research about family conflicts

Greater Good Science Center • Magazine • In Action • In Education

Family Conflict Is Normal; It’s the Repair That Matters

Three months into the pandemic, I had the urge to see my 28-year-old daughter and her husband, 2,000 miles away. She had weathered an acute health crisis, followed by community protests that propelled them both onto the streets to serve food and clean up neighborhoods. They were coping, but the accumulation of challenges made the mom in me want to connect with and support them. So, together with my husband, my other daughter, and her husband, our family of six adults and two dogs formed a new pod inside my daughter’s home in the steamy heat of the Minneapolis summer.

As I packed, a wisp of doubt crept in. We six hadn’t lived together under the same roof, ever . Would I blow it? Would I “flap my lips,” as a friend calls it, and accidentally say something hurtful? Some time back, in a careless moment of exhaustion, I had insulted my brand-new son-in-law with a thoughtless remark. He was rightfully hurt, and it took a long letter and a phone call to get us back on track.

My own siblings and I were raised inside the intractable rupture that was my parents’ marriage. Their lifelong conflict sowed discord and division in everyone around them. I worked hard to create a different, positive family climate with my husband and our children. My old ghosts were haunting me, though, and I didn’t want to ruin a good thing. 

Yet research shows that it’s not realistic, or possible, or even healthy to expect that our relationships will be harmonious all the time. Everything we know from developmental science and research on families suggests that rifts will happen—and what matters more is how you respond to them. With many families spending more time together than ever now, there are ample opportunities for tension and hurt feelings. These moments also offer ample invitations to reconnect.

Disconnections are a fact of life

Researcher Ed Tronick, together with colleague Andrew Gianino, calculated how often infants and caregivers are attuned to each other. (Attunement is a back-and-forth rhythm of interaction where partners share positive emotions.) They found that it’s surprisingly little. Even in healthy, securely attached relationships, caregivers and babies are in sync only 30% of the time. The other 70%, they’re mismatched, out of synch, or making repairs and coming back together. Cheeringly, even babies work toward repairs with their gazes, smiles, gestures, protests, and calls.

These mismatches and repairs are critical, Tronick explains. They’re important for growing children’s self-regulation, coping, and resilience. It is through these mismatches—in small, manageable doses—that babies, and later children, learn that the world does not track them perfectly. These small exposures to the micro-stress of unpleasant feelings, followed by the pleasant feelings that accompany repair, or coming back together, are what give them manageable practice in keeping their boat afloat when the waters are choppy. Put another way, if a caregiver met all of their child’s needs perfectly, it would actually get in the way of the child’s development. 
 “Repairing ruptures is the most essential thing in parenting,” says UCLA neuropsychiatrist Dan Siegel , director of the Mindsight Institute and author of several books on interpersonal neurobiology.

Life is a series of mismatches, miscommunications, and misattunements that are quickly repaired, says Tronick , and then again become miscoordinated and stressful, and again are repaired. This occurs thousands of times in a day, and millions of times over a year.

Greater Good in Spanish

Read this article in Spanish on La Red Hispana, the public-facing media outlet and distribution house of HCN , focused on educating, inspiring, and informing 40 million U.S. Hispanics.

Other research shows that children have more conflicts and repairs with friends than non-friends. Sibling conflict is legendary; and adults’ conflicts escalate when they become parents. If interpersonal conflict is unavoidable—and even necessary—then the only way we can maintain important relationships is to get better at re-synchronizing them, and especially at tending to repairs when they rupture.

“Relationships shrink to the size of the field of repair,” says Rick Hanson , psychologist and author of several books on the neuroscience of well-being. “But a bid for a repair is one of the sweetest and most vulnerable and important kinds of communication that humans offer to each other,” he adds. “It says you value the relationship.”

Strengthening the family fabric

In a small Canadian study , researchers examined how parents of four- to seven-year-old children strengthened, harmed, or repaired their relationships with their children. Parents said their relationships with their children were strengthened by “horizontal” or egalitarian exchanges like playing together, negotiating, taking turns, compromising, having fun, or sharing psychological intimacy—in other words, respecting and enjoying one another. Their relationships were harmed by an over-reliance on power and authority, and especially by stonewalling tactics like the “silent treatment.” When missteps happened, parents repaired and restored intimacy by expressing warmth and affection, talking about what happened, and apologizing.

This model of strengthening, harming, and repairing can help you think about your own interactions. When a family relationship is already positive, there is a foundation of trust and a belief in the other’s good intentions, which helps everyone restore more easily from minor ruptures. For this reason, it helps to proactively tend the fabric of family relationships. 
 That can begin with simply building up an investment of positive interactions:

• Spend “special time” with each child individually to create more space to deepen your one-to-one relationship. Let them control the agenda and decide how long you spend together.
• Appreciate out loud, share gratitude reflections, and notice the good in your children intermittently throughout the day or week.

You also want to watch out for ways you might harm the relationship. If you’re ever unsure about a child’s motives, check their intentions behind their behaviors and don’t assume they were ill-intentioned. Language like, “I noticed that…” or “Tell me what happened…” or “And then what happened?” can help you begin to understand an experience from the child’s point of view.

A Loving Space for Kids’ Emotions

Show love to your children by helping them process emotions

When speaking to a child, consider how they might receive what you’re saying. Remember that words and silence have weight; children are “ emotional Geiger counters ” and read your feelings much more than they process your words. If you are working through feelings or traumas that have nothing to do with them, take care to be responsible for your own feelings and take a moment to calm yourself before speaking.

In this context of connection and understanding, you can then create a family culture where rifts are expected and repairs are welcomed:

• Watch for tiny bids for repairs . Sometimes we have so much on our minds that we miss the look, gesture, or expression in a child that shows that what they really want is to reconnect.
• Normalize requests like “I need a repair” or “Can we have a redo?” We need to be able to let others know when the relationship has been harmed.
• Likewise, if you think you might have stepped on someone’s toes, circle back to check. Catching a misstep early can help.

When you’re annoyed by a family member’s behavior, try to frame your request for change in positive language; that is, say what you want them to do rather than what you don’t. Language like, “I have a request…” or “Would you be willing to…?” keeps the exchange more neutral and helps the recipient stay engaged rather than getting defensive.

You can also model healthy repairs with people around you, so they are normalized and children see their usefulness in real time. Children benefit when they watch adults resolve conflict constructively.


Four steps to an authentic repair

There are infinite varieties of repairs, and they can vary in a number of ways, depending on your child’s age and temperament, and how serious the rift was.

Infants need physical contact and the restoration of love and security. Older children need affection and more words. Teenagers may need more complex conversations. Individual children vary in their styles—some need more words than others, and what is hurtful to one child may not faze another child. Also, your style might not match the child’s, requiring you to stretch further.

Some glitches are little and may just need a check-in, but deeper wounds need more attention. Keep the apology in proportion to the hurt. What’s important is not your judgment of how hurt someone should be, but the actual felt experience of the child’s hurt. A one-time apology may suffice, but some repairs need to be acknowledged frequently over time to really stitch that fabric back together. It’s often helpful to check in later to see if the amends are working.

While each repair is unique, authentic repairs typically involve the same steps.

1. Acknowledge the offense. First, try to understand the hurt you caused. It doesn’t matter if it was unintentional or what your reasons were. This is the time to turn off your own defense system and focus on understanding and naming the other person’s pain or anger.

Sometimes you need to check your understanding. Begin slowly: “Did I hurt you? Help me understand how.” This can be humbling and requires that we listen with an open heart as we take in the other person’s perspective.

Try not to undermine the apology by adding on any caveats, like blaming the child for being sensitive or ill-behaved or deserving of what happened. Any attempt to gloss over, minimize, or dilute the wound is not an authentic repair. Children have a keen sense for authenticity. Faking it or overwhelming them will not work.

A spiritual teacher reminded me of an old saying, “It is acknowledging the wound that gets the thorn out.” It’s what reconnects our humanity.

Making an Effective Apology

A good apology involves more than saying "sorry"

2. Express remorse. Here, a sincere “I’m sorry” is sufficient.

Don’t add anything to it. One of the mistakes adults often make, according to therapist and author Harriet Lerner , is to tack on a discipline component: “Don’t let it happen again,” or “Next time, you’re really going to get it.” This, says Lerner, is what prevents children from learning to use apologies themselves. 
 Apologizing can be tricky for adults. It might feel beneath us, or we may fear that we’re giving away our power. We shouldn’t have to apologize to a child, because as adults we are always right, right? Of course not. But it’s easy to get stuck in a vertical power relationship to our child that makes backtracking hard.

On the other hand, some adults—especially women, says Rick Hanson —can go overboard and be too effusive, too obsequious, or even too quick in their efforts to apologize. This can make the apology more about yourself than the person who was hurt. Or it could be a symptom of a need for one’s own boundary work.   

There is no perfect formula for an apology except that it be delivered in a way that acknowledges the wound and makes amends. And there can be different paths to that. Our family sometimes uses a jokey, “You were right, I was wrong, you were right, I was wrong, you were right, I was wrong,” to playfully acknowledge light transgressions. Some apologies are nonverbal: My father atoned for missing all of my childhood birthdays when he traveled 2,000 miles to surprise me at my doorstep for an adult birthday. Words are not his strong suit, but his planning, effort, and showing up was the repair. Apologies can take on all kinds of tones and qualities.

3. Consider offering a brief explanation. If you sense that the other person is open to listening, you can provide a brief explanation of your point of view, but use caution, as this can be a slippery slope. Feel into how much is enough. The focus of the apology is on the wounded person’s experience. If an explanation helps, fine, but it shouldn’t derail the intent. This is not the time to add in your own grievances—that’s a conversation for a different time.

4. Express your sincere intention to fix the situation and to prevent it from happening again. With a child, especially, try to be concrete and actionable about how the same mistake can be prevented in the future. “I’m going to try really hard to…” and “Let’s check back in to see how it’s feeling…” can be a start.

Remember to forgive yourself, too. This is a tender process, we are all works in progress, and adults are still developing. I know I am.

Prior to our visit, my daughter and I had a phone conversation. We shared our excitement about the rare chance to spend so much time together. Then we gingerly expressed our concerns.

 “I’m afraid we’ll get on each other’s nerves,” I said.

“I’m afraid I’ll be cooking and cleaning the whole time,” she replied.

So we strategized about preventing these foibles. She made a spreadsheet of chores where everyone signed up for a turn cooking and cleaning, and we discussed the space needs that people would have for working and making phone calls.

Then I drew a breath and took a page from the science. “I think we have to expect that conflicts are going to happen,” I said. “It’s how we work through them that will matter. The love is in the repair.”

This article is excerpted from a longer article on Diana Divecha’s blog, developmentalscience.com.

About the Author

Diana Divecha

Diana Divecha, Ph.D. , is a developmental psychologist, an assistant clinical professor at the Yale Child Study Center and Yale Center for Emotional Intelligence, and on the advisory board of the Greater Good Science Center. Her blog is developmentalscience.com .

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The interactive effect of family conflict history and physiological reactivity on different forms of aggression in young women

Melissa j. hagan.

a San Francisco State University, United States

b University of California, San Francisco, United States

Sara F. Waters

c Washington State University, Vancouver, United States

Sarah Holley

Lucy moctezuma, miya gentry.

Evidence indicates that patterns of biological reactivity underlie different forms of aggression, but greater precision is needed in research targeting biopsychosocial processes that underlie such differences. This study investigated how sympathetic and parasympathetic nervous system (SNS and PNS) responses to social stress were associated with multiple forms of aggression in an ethnically-diverse sample of young adult females; it further examined whether early life exposure to family conflict moderated these relationships. In the context of high levels of family conflict history, greater SNS activation during a social conflict task was associated with more direct proactive aggression and increasing RSA was associated with more direct reactive aggression. Greater SNS activation during the task was associated with more direct reactive aggression regardless of family conflict history. Our findings affirm the need to capture the contributions of multiple physiological systems simultaneously and the importance of considering family history in the study of aggression.

1. Introduction

Young adults’ behavioral patterns forecast the quality of subsequent interactions with long-term partners and offspring, making this developmental period a critical time for interrupting cycles of aggression. A significant body of literature suggests that patterns of biological reactivity may underlie different forms of aggression, but greater precision is needed in research targeting the specific dynamic biopsychosocial processes that underlie such differences. Notably, studies on the psychophysiology of aggression have historically focused on males and have largely ignored the role of young adults’ early family environment, despite the strong influence that childhood experiences exert on long-term behavior problems. To address these gaps in the literature, the present study examined the associations between autonomic reactivity in response to social conflict and different forms of aggression in an ethnically-diverse sample of young adult females. It additionally sought to determine whether these associations are moderated by exposure to family conflict during childhood. In addition to shedding light on biological processes implicated in female aggression, this work has the potential to lead to more specificity in violence prevention research relevant to a developmental period largely overlooked in prevention science.

1.1. Psychophysiological stress reactivity and aggression

Multiple theories recognize that physiological arousal is a key component of aggression ( Anderson & Bushman, 2002 ; Goozen, Fairchild, & Harold, 2007 ) and that the interaction of psychosocial and biological mechanisms underlying aggressive and violent behavior must be more fully understood ( Murray-Close, 2013 ). Most studies on the physiology of aggression have focused on the autonomic nervous system (ANS), which is composed of the sympathetic (SNS) and parasympathetic (PNS) nervous systems ( Murray-Close & Rellini, 2012 ; Patrick & Verona, 2007 ). The SNS is responsible for supporting bodily functions during episodes of stress while the PNS is responsible for supporting bodily functions of rest; as such, each are regarded has having opposing effects on the body. Engagement of the SNS during stress underlies the “fight or flight” somatic response, resulting in glucose increases, elevation in heart rate and increased blood pressure. To facilitate this reactivity, withdrawal of the PNS occurs. Stress-induced change in PNS activity is determined by measuring the influence of the tenth cranial nerve, the vagus, on the heart. PNS activation (whereby the PNS is engaged rather than withdrawn during stress) is often referred to as vagal augmentation, or increased influence of the vagus, and vagal withdrawal describes decreased influence ( Mendes, 2009 ).

The body of work on ANS reactivity and aggression has produced inconsistent and often contradictory findings. For example, a number of studies have found that aggression in adulthood is associated with greater ANS reactivity to stress as indicated by elevated sympathetic reactivity ( Beauchaine, Gatzke-Kopp, & Mead, 2007 ; Lorber, 2004 ; Murray-Close & Crick, 2007 ). Conversely, other investigations have reported associations between aggression and lower ANS reactivity, as indicated by blunted sympathetic reactivity ( Ortiz & Raine, 2004 ; Posthumus, Böcker, Raaijmakers, Van Engeland, & Matthys, 2009 ) or blunted withdrawal of the parasympathetic system (i.e., vagal augmentation; Calkins, Graziano, & Keane, 2007 ; Katz, 2007 ; Obradović, Bush, Stamperdahl, Adler, & Boyce, 2010 ).

This inconsistency in the field is likely due to a number of issues. First, research in this area has tended to rely on non-specific measures of isolated parts of the human stress response system. As an example, an impressive body of research documents negative associations between resting heart rate or heart rate reactivity and aggression or disorders associated with aggression (i.e. conduct disorder, oppositional defiant disorder, antisocial personality disorder) ( Lorber, 2004 ; Ortiz & Raine, 2004 ). Heart rate reflects both SNS and PNS influences on the heart; the relative contributions of the two systems cannot be disentangled from this measure. A more complete understanding of how the ANS is related to aggression may be obtained by effectively measuring the two branches of the ANS independently and then examining their associations with aggression separately and in light of the other.

Second, much of the research on the psychophysiology of aggression has lacked specificity in aggression measurement. Several critical distinctions have been suggested regarding different forms of aggression. Direct aggression involves both overt physical attacks and verbal assaults of the intended victim, although many studies focus on physical aggression , specifically. Conversely, indirect aggression , which has also been referred to as relational aggression , involves harm delivered circuitously and/or through relational means such as social exclusion or spreading rumors ( Crick, Casas, & Mosher, 1997 ). While there may be differences in the neurobiological underpinnings of direct and indirect aggression, research exploring these distinctions is fairly limited ( Murray-Close & Crick, 2007 ; Murray-Close, Han, Cicchetti, Crick, & Rogosch, 2008 ; Sijtsema, Shoulberg, & Murray-Close, 2011 ). Illustratively, there is some evidence that increased ANS reactivity (e.g., increased systolic blood pressure reactivity or heart rate reactivity) is associated with indirect aggression in girls, whereas decreased ANS reactivity (e.g., blunted heart rate reactivity and blunted parasympathetic withdrawal) may be associated with direct aggression in boys and girls, respectively ( Murray-Close & Crick, 2007 ; Sijtsema et al., 2011 ).

Further, within direct and indirect aggression, theoretical and empirical evidence suggests two unique subtypes: proactive and reactive aggression ( Little et al., 2003 ; Poulin & Boivin, 2000 ; Stanford et al., 2003 ). Proactive aggression includes behaviors perpetrated for the purpose of gaining resources or control over others (and may or may not occur in response to specific provocation); conversely, reactive aggression involves behavioral responses that arise following a perceived threat or provocation ( Teten et al., 2011 ). Although proactive and reactive aggression can co-occur, they serve different functions and are associated with unique patterns of physiological reactivity ( Babcock, Tharp, Sharp, Heppner, & Stanford, 2014 ; Bobadilla, Wampler, & Taylor, 2012 ; Hubbard et al., 2002 ; Murray-Close & Rellini, 2012 ). A recent investigation of the biological underpinnings of reactive and proactive indirect aggression offers the most comprehensive and compelling evidence in young adults to date ( Murray-Close, Holterman, Breslend, & Sullivan, 2017 ). Utilizing a standardized social stress task, they found that blunted withdrawal of the PNS during stress (i.e., vagal augmentation) predicted proactive relational aggression, and greater SNS reactivity (changes in skin conductance) predicted reactive relational aggression. They also found that vagal augmentation was most likely to predict any form of aggression if the individual also exhibited low skin conductance reactivity.

Murray-Close et al. (2017) made a significant contribution to the field owing to their examination of different forms of stress (cognitive and social) and different forms of aggression, as well as the testing of interactions between multiple arms of the ANS. The current investigation furthers our understanding by employing an ecologically-valid stress task that involves social conflict (thus making it more relevant to aggression and frustration), and drawing upon a more ethnically diverse sample. Latina and African-American women may be three times as likely as White women to experience victimization and two times more likely to engage in aggression toward intimate partners ( Field & Caetano, 2005 ); however, very limited empirical research has focused on aggression in women of color, particularly during the period of young adulthood ( Goldstein, 2011 ; Rivera-Maestre, 2014 ). In addition, in the current work, we consider a factor known to exert a critical influence on the development of aggressive behavior: qualities of the early childhood family environment.

1.2. The role of the childhood family environment

Theories of diathesis-stress and differential susceptibility argue that connections between biology and behavior cannot be understood without considering environmental context early in life ( Ellis, Boyce, Belsky, Bakermans-Kranenburg, & van Ijzendoorn, 2011 ); a substantive body of research supports this claim (see review in Bush & Boyce, 2014 ). These models posit that complex interactions between stress reactivity and social experiences early in life underlie the emergence and maintenance of psychopathology. As outlined above, the majority of studies that have examined the associations between physiological stress reactivity and aggression have not assessed individuals’ history of trauma or quality of the childhood family environment ( Bohnke, Bertsch, Kruk, & Naumann, 2010 ; Gordis, Granger, Susman, & Trickett, 2006 ; Lorber, 2004 ; Patrick & Verona, 2007 ; Verona & Kilmer, 2007 ; Verona & Sullivan, 2008 ), though there are a few exceptions ( El-Sheikh, Hinnant, & Erath, 2011 ; Obradović, Bush, & Boyce, 2011 ; Saxbe, Margolin, Spies Shapiro, & Baucom, 2012 ).

Despite the strong theoretical and empirical foundation supporting biopsychosocial models of disordered behavior and extensive evidence that individuals raised in aggressive households have a greater risk of developing aggressive behavior patterns later in life ( Cui, Durtschi, Donnellan, Lorenz, & Conger, 2010 ; Herrenkohl & Herrenkohl, 2007 ), we could identify only a single study that tested a biopsychosocial model of aggression in young adults, specifically. It was found that vagal withdrawal (i.e. PNS reactivity) was positively associated with reactive aggression and negatively associated with proactive aggression in conditions of “low social adversity” (e.g., less poverty, lack of parental incarceration, uncrowded home, smaller family) ( Zhang & Gao, 2015 ). This study provides compelling preliminary evidence of important environmental influences on the association between stress reactivity in response to a non-social task and different forms of aggression in an ethnically diverse, yet relatively small (n = 84), sample of young adults.

1.3. The current study

The present study extends the existing base of research in a number of important ways. Specifically, the present study 1) utilizes multiple channels of ANS reactivity in reaction to a stressor; 2) employs differentiated measures of aggression (reactive direct, proactive direct, reactive indirect, and proactive indirect); 3) includes an ethnically-diverse female sample; and 4) includes reports of childhood family conflict in order to test moderating effects. Taken together, the current investigation will be the first study to involve a sophisticated test of the associations between physiological reactivity to stress, relevant developmental experiences, and aggressive behavior outcomes in population that is at elevated risk for aggression yet is underrepresented in the literature. Such an investigation may help to resolve the inconsistent findings in the field regarding associations between psychophysiology and aggression by considering direct associations between each branch of the ANS in the context of childhood exposure to family conflict, while controlling for the other branch of the ANS.

Based on prior examinations of the biological underpinnings of delinquency in children from high conflict families ( El-Sheikh et al., 2011 ) and models of differential susceptibility ( Bush & Boyce, 2014 ), we posited that blunted SNS reactivity to stress will be associated with greater proactive aggression and heightened SNS reactivity will be associated with greater reactive aggression among women exposed to higher levels of family conflict earlier in life, while controlling for PNS activity. We also hypothesized that blunted PNS reactivity (vagal augmentation) and greater PNS reactivity (vagal withdrawal) would be associated with greater proactive and reactive aggression, respectively, among women exposed to higher family conflict while controlling for SNS activity. We had no a priori hypotheses regarding the form of aggression (direct vs. indirect), but based on research with children, we tentatively expected that associations might be stronger for indirect aggression compared to direct aggression given that the sample includes only women and indirect aggression frequency and variability might be higher compared to physical aggression in this population.

2.1. Participants

One hundred seventy-eight female young adults attending a state university or community college in a major city in the Western United States participated in the study. Recruitment procedures included: flyers displayed on bulletin boards and metro lines surrounding the two campuses; scripted announcements in university classrooms; and flyer postings to online and in-person university courses. A special effort was made to recruit women of color by posting on Facebook pages of student groups representing Latinx and Asian students and making announcements in Ethnic Studies-focused courses. Due to the nature of the study, which included neurobiological measures of stress reactivity, eligibility criteria included the following: 18–35 years of age, English speaking, body max index less than 35, without a history of serious medical conditions (particularly heart or respiratory ones), and not taking medications that could interfere with the assessment of stress physiology.

Of the 178 participants who completed the study, nine failed attention check questions and/or did not speak fluent English, and ten participants were missing physiological data due to equipment failure or experimenter error. The final sample for the current analysis included 159 young women (Mean age: 21.6 years, SD = 3.15), including 130 undergraduate students without (52 %) and with (30 %) an Associate’s Degree and 29 master’s students (18 %). The sample was ethnically diverse: 32 % Latina/Hispanic, 27 % Asian/Pacific-Islander, 24 % White, 6% Black, 9% Multi-ethnic, and 3% Other. Of those who reported on parental nativity (n = 150), 50 % indicated that neither parent was born in the United States. The majority of women reported earning less than $10,000 per year (77.4 %).

2.2. Procedures

All procedures were approved by the university Institutional Review Board. Individuals who were interested in participating in the study were directed to an online registration form that included the eligibility criteria. If eligible, participants were instructed 24 h prior to their appointment to refrain from vigorous exercise, smoking, drinking alcohol, coffee/energy drinks, consuming food or cold medicine for at least 2 h before their scheduled lab visit. Appointments were either at 1 pm or 4 pm on a weekday and lasted approximately 2 h. Following the informed consent process, height and weight measurements were taken to calculate body mass index. Participants were then attached to physiological equipment. Following a baseline resting period, the participants completed two conflict discussion role play tasks and rated their mood and cognitive appraisals prior to and following the tasks. After detachment from the physiological sensors, participants completed a battery of questionnaires on a computer located in a room separate from where the stress tasks occurred. Participants were compensated with $25 in the form of an Amazon gift card or extra credit for a psychology course.

2.3. Measures

2.3.1. self-report questionnaires, 2.3.1.1. direct aggression..

Direct aggression was measured using the Reactive-Proactive Questionnaire (RPQ; Raine et al., 2006 ), with slight word modifications to ensure it was appropriate for emerging adults. The RPQ includes a 12-item reactive aggression subscale (e.g., “Yelled at others when they have annoyed you.”) and an 11-item proactive aggression subscale (e.g., “Had fights with others to show who was in control.”). Questions were rated on a scale of 0 (never) , 1 (sometimes) , or 2 ( often) and items on each of the two subscales were averaged, with higher scores reflecting more direct reactive or proactive aggression. Given that the RPQ was originally developed for child populations and measurement models have not been published for normative young adult populations, a confirmatory factor analysis (CFA) was conducted. Results showed that 4 items on the proactive subscale loaded poorly (<.30). These items were removed. Final analyses utilized the full 12-item reactive aggression scale (α = .81) and the reduced 7-item proactive aggression scale (α = .59).

2.3.1.2. Indirect aggression.

Indirect aggression was assessed using the peer-directed aggression subscales of the Self-Report of Aggression and Social Behavioral Measure ( Murray-Close, Ostrov, Nelson, Crick, & Coccaro, 2010 ). The original measure included 13 items assessing peer-directed proactive and reactive indirect aggression; however, the current study utilized the nine items employed in a previous study ( Murray Close et al., 2010 ; α = .81). Four items assess reactive indirect aggression (e.g., “When I am not invited to do something with a group of people, I will exclude those people from future activities.”) and five items assess proactive indirect aggression (e.g., “My friends know that I will think less of them if they do not do what I want them to.”). Items were rated on a scale from 0 ( never ) to 4 ( very often ) and averaged for each subscale, with higher scores reflecting more indirect aggression. Internal consistencies for the reactive and proactive subscales in the current study were .78 and .65, respectively.

2.3.1.3. Family conflict in childhood.

The Risky Family Environment questionnaire is a 13- item self-report measure that assesses aspects of the childhood family environment, such as chaos, predictability, warmth, and conflict ( Taylor, Lerner, Sage, Lehman, & Seeman, 2004 ). Participants indicated how true each statement was for them on a scale from 1 ( not at all ) to 5 ( very often ). For the current study, only the 7 conflict items were used (e.g., “How often did a parent or other adult in the household push, grab, shove, or slap you?”; α = .81).

2.4. Social conflict paradigm

2.4.1. role play tasks.

Participants completed two 5-minute role play tasks ( Larkin, Semenchuk, Frazer, Suchday, & Taylor, 1998 ), the order of which was counterbalanced across the sample. For each task, a trained confederate entered the room and sat facing directly across from the participant approximately 30 in. away. All confederates were instructed to display a neutral facial expression, maintain flat affect, make direct eye contact, and not engage with the participant outside of their assigned lines. In the Messy Roommate roleplay, participants interacted with a female confederate in a role play scenario in which participants were instructed to act out the following: “Your roommate is a slob and the apartment is a mess. You always do your share. You ask her to do the dishes because you have friends coming over. You get back home and the place is worse than when you left it. Your goal is to get your roommate to agree to clean up the apartment.” In the Noisy Neighbor role play task, participants interacted with a male confederate in a role play scenario in which participants were instructed to act out the following: “You are trying to study for an important exam. You really need to do well on this exam, but you can’t concentrate because your neighbor is playing his music too loud. You decide to ask him to turn down his music so you can study.”

2.4.2. Mood and cognitive appraisals

Participants’ negative mood and negative appraisals of the tasks were assessed prior to and following the role play tasks. The Positive and Negative Affect Schedule is a 20-item self-report measure that assesses current positive and negative affect (PANAS; Watson, Clark, & Tellegen, 1988 ). Participants indicated how much they currently felt each state on a scale from 1 ( not at all ) to 5 ( extremely ). Only the 10-item Negative Subscale was used in the current study (α = .83). The Stress Appraisal Measure is a 28-item self-report measure that assesses an individual’s appraisal of a specific stressful situation ( Peacock & Wong, 1990 ). Participants indicated how they felt about the situation on a scale from 1 ( not at all ) to 5 ( extremely) . Only the 4-item Threat Subscale was used in the current study (α = .70). These measures served as a manipulation check for the social stress tasks.

2.5. Physiological measurements

Autonomic Nervous System (ANS) stress reactivity was recorded using electrocardiography (ECG) and impedance cardiography (ICG) with BIOPAC (Biopac MP150, Data Acquisition System, Biopac Systems, Inc., www.biopac.com ). The experimenter applied two strips of impedance tape around the circumference of participants’ necks with its mylar 3 cm apart from each other and parallel to the ground. In a similar fashion two other strips were applied around the torso, right below the bra line. Two ECG electrodes were then placed, one on the right breastbone and the other under the left rib cage, slightly above the belly button. Data were sampled at 1000 Hz.

There were a total of four relevant consecutive recording sessions: Baseline, Social Stress task 1, Social Stress task 2 and Recovery, each five minutes long for a total of 20 min of recording per participant. Data was cleaned using Mindware HRV and IMP v3.0.15 by visually inspecting each 1-minute segment for artifacts and edited when needed. Segments in which more than 10 % of the data were missing were excluded from analyses. Minute segments were averaged together for each recording session to create a single mean score per session.

We focused specifically on Pre-Ejection Period (PEP; a time-based measure that is determined as the time from the left ventricle contracting to the opening of the aortic valve) and Respiratory Sinus Arrhythmia (RSA; a type of heart rate variability in which spectral analysis is used to derive the high frequency component of the interbeat Interval cycle (0.12 to 0.40 hz)) because they have been known to assess activation of the sympathetic and parasympathetic systems, respectively. Studies using pharmacological blockades have shown that PEP measures cardiac sympathetic activation without the influence of the vagus nerve ( Berntson et al., 1994 ), and RSA is considered mainly vagally mediated, reflecting cardiac parasympathetic activation without sympathetic input ( Mendes, 2009 ). For PEP, a smaller reactivity score means greater activation of SNS, whereas for RSA, a smaller reactivity score means less activation of PNS, both of which are interpreted as higher stress reactivity.

Paired t-tests contrasting average baseline PEP and average PEP during the first task indicated that PEP values decreased significantly from baseline ( M = 105.54, SD = 10.92) to the end of the first task ( M = 90.87, SD = 15.36), t (157) = 15.65, p < .001, and from baseline to the end of the second task ( M = 93.30, SD = 14.06), t (156) = 13.82, p < .001. RSA values also decreased from baseline ( M = 6.56, SD = 0.97) to the first task ( M = 6.45, SD = 0.90), although statistical significance was marginal, t (157) = 1.74, p = .09. There was no change in RSA values from baseline to the second task, ( M = 6.55, SD = 0.87), t (156) = .12, p = .91. PEP change from baseline to the first task was statistically significantly greater than PEP change from baseline to the second task ( M diff = −2.44, t = −5.13, p < .0001). Additionally, RSA change from baseline to the first task was also greater than RSA change from baseline to the second task ( M diff = −0.11, t = −3.26, p = .001). We interpret these differences as evidence of habituation to the second task. Thus, reactivity scores to be used in the preliminary and primary analyses were calculated by subtracting average PEP and RSA at baseline from average PEP and RSA during the first task, respectively.

2.6. Data analysis

Study variables were inspected for non-normality and outliers. Inspection of aggression and reactivity scores revealed a number of outliers. One case had a direct proactive aggression value above 3*Interquartile Range (IQR) and was winsorized to the next highest value. Two cases had indirect proactive aggression values more than 3*IQR; these values were winsorized to the next highest value. Four individuals had PEP reactivity scores that were 3*IQR and three individuals had RSA reactivity scores that were 3*IQR. These high levels could not be explained by these participants’ body mass index, behavior during the task, or daily use of caffeine, marijuana, or alcohol; therefore, these cases were winsorized to the next highest value and included in the analyses.

Correlational analyses were conducted to examine bivariate relations between the primary study variables and potential covariates, including age, income, and race/ethnicity. Given the ethnic diversity of the sample, we also explored whether the primary variables of interest differed across different ethnic groups. Primary analyses were conducted within a structural equation modeling (SEM) framework in Mplus v.8 using maximum likelihood estimation with robust standard errors, which is appropriate for non-normally distributed data. The SEM framework allowed for the simultaneous estimation of relations between the independent variables (i.e., PEP reactivity, RSA reactivity, and childhood family conflict) and the four different types of aggression: direct reactive, direct proactive, indirect reactive, and indirect proactive aggression. The three independent variables were mean-centered and interaction terms were created by taking the products of PEP reactivity × family conflict and RSA reactivity × family conflict. Specificity analyses were conducted to inspect the influence of a single participant who scored substantially higher on all aggression measures. There was a significant change in multiple coefficients when this participant was excluded, suggesting that this case exerted undue influence on the associations; therefore, all analyses were conducted excluding this one case.

3.1. Preliminary analyses

A manipulation check of the social stress tasks was conducted by examining changes in self-reported mood, self-reported negative cognitive appraisals, and autonomic reactivity to each of the tasks. Paired t-tests indicated a significant increase in negative mood from pre-task ( M = 13.63, SD = 4.67) to post-tasks ( M = 18.30, SD = 6.51), t (157) = −10.92, p < .001 and a significant increase in threat appraisal from pre-task ( M = 1.77, SD = 0.62) to post-tasks ( M = 2.32, SD = 0.88), t (156) = −8.59, p < .001, providing evidence that participants subjectively experienced the tasks as stressful.

Descriptives and zero-order correlations among the variables of interest are displayed in Table 1 . Mean levels of aggression were quite low. In addition, young women endorsed family conflict as happening “rarely” on average; however, 30 % of women reported that family conflict occurred “sometimes” or “often”. Family conflict was associated with greater direct reactive aggression but showed no statistically significant correlation with direct proactive aggression or either form of indirect aggression. Family conflict was also correlated with greater RSA reactivity (i.e., more parasympathetic withdrawal). Income and age were not statistically significantly correlated with any of the primary variables ( p s > .10, not shown). In addition to the expected positive associations among all aggression indicators, there was also a small but statistically significant positive correlation between PEP reactivity and RSA reactivity. The small to moderate correlations between the different types of direct and indirect aggression indicate the value of examining these as separate outcomes.

Kendall’s Tau Correlations.

Note : Negative RSA and PEP reactivity values = more reactivity so the negative correlation between PEP reactivity and reactive aggression is interpreted such that more PEP reactivity is associated with more aggression.

To explore whether the primary variables of interest differed across ethnicity, four groups were created based on previous research showing differing levels of aggression in White, Asian, and Latina populations. Due to the low proportion of African-American women (n = 9) and other race/ethnicities (e.g., American Indian/Native American/Indigenous) in the current sample, they were collapsed into a fourth “other” category. History of family conflict did not differ across the groups ( p = .84). In addition, regardless of type or form, aggression did not differ across the four groups ( p s .12–.92). Finally, although PEP reactivity also did not differ across race/ethnicity ( p = .21), RSA reactivity was significantly greater (more parasympathetic withdrawal indicated by larger decreases in RSA values) for women who identified as Latina compared to White women ( M diff = −.453, p = .04).

3.2. Primary analyses

Results are displayed in Table 2 , organized by type of aggression.

PEP reactivity interacting with family conflict (Conflict*PEP) and RSA reactivity interacting with family conflict (Conflict*RSA): Standardized estimates and standard errors.

3.2.1. Direct reactive aggression

Greater RSA augmentation (less parasympathetic withdrawal), greater PEP reactivity, and greater family conflict all predicted greater direct reactive aggression. However, these associations must be qualified given the statistically significant interaction between RSA reactivity and family conflict ( p = .038; Table 2 ). Simple slopes at +1 SD and −1 SD were estimated and tested following guidelines by Aiken and West (1991) using Mplus and plotted using the PROCESS Macro in SPSS. As shown in Fig. 1 , at high levels of family conflict (+1 SD ), greater RSA augmentation (i.e., less parasympathetic withdrawal, indicated by increased RSA) was associated with higher endorsement of direct reactive aggression, β = .23, SE = .11, p = .03. At low levels of family conflict (−1 SD ), RSA reactivity was not associated with direct reactive aggression ( p = .55).

RSA reactivity predicting direct reactive aggression at +1/−1 SD and mean levels of childhood family conflict.

3.2.2. Direct proactive aggression

The interaction between PEP reactivity and family conflict was statistically significant ( p = .007; Table 2 ). Simple slopes at +1 SD and −1 SD were estimated and tested following guidelines by Aiken and West (1991) using Mplus and plotted using the PROCESS Macro in SPSS. Neither simple slope reached conventional levels of statistical significance ( p s > .05); however, this is not unusual in the case of a full cross-over interaction like the one observed here ( Baron & Kenny, 1986 ). As shown in Fig. 2 , at high levels of family conflict (+1 SD ), greater PEP reactivity (i.e., more SNS activation, indicated by decreased PEP) was marginally associated with higher endorsement of direct proactive aggression, β = −.21, SE = .11, p = .06. At low levels of family conflict (−1 SD ), less PEP reactivity was associated with higher endorsement of direct proactive aggression but the effect was not significant, β = .16, SE = .10, p = .10.

PEP reactivity predicting direct proactive aggression at +1/−1 SD and mean levels of childhood family conflict.

3.2.3. Indirect reactive aggression

Neither interaction term was statistically significant, nor were there any main effects of RSA reactivity or family conflict history on indirect reactive aggression. There was a negative association between PEP reactivity and indirect reactive aggression, but this estimate did not reach statistical significance ( p = .07; Table 2 ).

3.2.4. Indirect proactive aggression

The interaction between PEP reactivity and family conflict was marginally significant for indirect proactive aggression ( p = .055; Table 2 ). Although the estimate did not reach statistical significance, simple slopes were tested to explore whether the pattern of the interaction mirrored that found for the direct form of proactive aggression. Greater PEP reactivity (i.e., more SNS activation) was associated with higher endorsement of indirect proactive aggression, β = −.24, SE = .10, p = .019. At low levels of family conflict (−1 SD ), the association between PEP reactivity and indirect proactive aggression was not statistically significant, β = .13, SE = .11, p = .24.

4. Discussion

Research has produced inconsistent and often contrary findings, with both high or low ANS reactivity shown to increase the risk of aggressive behavior. Although childhood exposure to family conflict is known to predict aggression later in life, few investigations have examined how family history of aggression and biological processes work together in a dynamic fashion to increase the risk of aggressive behavior, particularly among ethnically-diverse female populations. To address this gap, the current study tested whether childhood family conflict exposure moderated associations between physiological responses to social conflict and different forms of aggression (direct and indirect, reactive and proactive) in an ethnically-diverse sample of young adult females. In doing so, the investigation represents a sophisticated test of the associations between physiological reactivity to stress, relevant developmental experiences, and aggressive behavior outcomes in population that may be at elevated risk for aggression yet is underrepresented in the literature.

First, it was expected that, among women exposed to higher levels of family conflict earlier in life, blunted SNS reactivity to stress would be associated with greater proactive aggression, whereas heightened SNS reactivity would be associated with greater reactive aggression, while controlling for PNS reactivity. Family conflict moderated the association between SNS reactivity and proactive aggression only. Contrary to expectations, heightened SNS reactivity was associated with higher levels of direct proactive aggression among women exposed to high levels of family conflict. This finding is consistent with recent work showing that heightened baseline SNS arousal was associated with greater proactive aggression in young adult women (e.g., Armstrong et al., 2019 ), but suggests that family conflict exposure represents a critical contextual variable. The role of family conflict in the psychophysiology of proactive aggression is in line with differential susceptibility models of psychological problems, whereby individuals with heightened sensitivity to context are expected to develop particularly problematic behaviors under conditions of adversity. The lack of a correlation between SNS reactivity and family conflict history suggests that heightened sympathetic reactivity did not develop as a result of exposure to conflict. However, given the cross-sectional nature of the study, it is not possible to conclude that young women’s pattern of physiological responses were also evident earlier in life.

The association between heightened SNS reactivity and greater proactive aggression for women exposed to family conflict contrasts with previous findings of the opposite association among young women who experienced sexual abuse ( Murray-Close & Rellini, 2012 ). Although sexual abuse may exert a unique effect compared to exposure to family conflict, a number of differences between the two investigations may also account for the divergence in findings, including but not limited to the characteristics of the samples (the present study included an extremely diverse and larger sample of women), the measure of SNS (in the previous study, heart rate reactivity was used as an indicator of ANS response, which captures both sympathetic and parasympathetic influences) and the use of different stress tasks (the previous study employed a social stress interview). The use of an ecologically-valid social stress task in the current study is a unique strength given that stress reactivity to social conflict may be especially salient for those who have been exposed to family conflict.

The current study adds to the growing body of research implicating particular physiological patterns in the expression of different types of aggression, regardless of family history of aggression. It revealed direct associations between each branch of the ANS and multiple measures of aggression while controlling for the other branch of the ANS. This approach contrasts with the common practice of examining biological processes in isolation and is consistent with how these systems actually function in co-ordination within the individual. Consistent with previous research ( Hubbard et al., 2002 ; Murray-Close & Rellini, 2012 ), heightened SNS reactivity was related to significantly greater direct reactive and marginally indirect reactive aggression, suggesting that women who endorsed the use of reactive aggression became more physiologically activated, particularly in terms of the SNS fight-or-flight response, during social conflict. Reactive aggression may be a behavioral product of the high levels of physiological stress arousal these women experience when faced with perceived antagonism from others. The current study cannot elucidate causal relations, however. It may also be that a history of responding to others with reactive aggression has led to increased levels of physiological activation in response to conflict for these women. Future research employing a longitudinal design could help unpack potential causal pathways.

The association between RSA reactivity and aggression was confined to the reactive form of direct aggression only, was in the opposite direction of expectations, and was strongest for women who reported high levels of family conflict. Lower RSA reactivity or vagal augmentation (indicative of a blunted stress response whereby the PNS does not withdraw as expected) was associated with endorsement of greater direct reactive aggression, except for women who reported low levels of family conflict. This finding contrasts with preliminary evidence for an association between higher RSA reactivity (i.e., greater vagal withdrawal) and reactive aggression among young adults who reported experiencing low levels of social adversity ( Zhang & Gao, 2015 ). Because we included both branches of the ANS in the same model we see that PNS activation was accompanied by greater SNS activation (i.e., greater PEP reactivity), which is a state referred to as ANS coactivation ( Berntson, Cacioppo, & Quigley, 1991 ). As described by Murray-Close et al. (2017) , both heightened SNS responses to stress and heightened PNS responses (vagal augmentation) to stress are associated with strong or poorly regulated experiences of negative emotion, which may then lead to aggression. Our work indicates that ANS coactivation may be a physiological marker for direct reactive aggression in ethnically-diverse young adult women, especially those exposed to high family conflict.

The present findings must be considered in light of study limitations. Recent research has revealed complicated associations between aggression or aggression-related disorders and interactions between the PNS and SNS. For example, young adults who exhibit low sympathetic reactivity combined heightened parasympathetic reactivity (vagal withdrawal) show greater levels of relational or indirect aggression ( Murray-Close et al., 2017 ). The sample size of the present study did not have sufficient power to test a three-way interaction; future research involving significantly larger samples of participants should consider testing whether history of family conflict or childhood maltreatment influences mutli-system stress profiles associated with different forms of aggression. Additionally, although well-validated measures of direct and indirect measures of aggression were used in the current study, the internal consistency for the measures of proactive forms of aggression were relatively low. Notably, however, the interaction between family conflict and PEP reactivity was present for the two different measures of proactive aggression, adding confidence to the finding. The lower internal consistency observed in the proactive aggression measures may be a result of the lower endorsement of proactive aggression in this population. In fact, overall levels of aggression regardless of form or type appeared to be relatively lower in these women compared to other studies of female aggression (e.g., Dinić & Wertag, 2018 ; Morel, Haden, Meehan, & Papouchis, 2018 ). Thus, our findings indicate the SNS responses and a history of family conflict are important factors for understanding relatively low, non-clinical levels of aggression.

The current study also has a number of strengths. It advances the field by focusing on a developmental period often overlooked in investigations of aggression. Past research on aggression (as well as prevention/intervention programs) has focused predominately on children and adolescents ( Crick & Dodge, 1996 ) (or on adults with psychiatric disorder; Howells, Daffern, & Day, 2008 ). However, the majority of at-risk youth do not have access to effective interventions ( Mihalopoulos, Vos, Pirkis, & Carter, 2011 ), which means these same youth enter subsequent developmental stages without having had any corrective interpersonal experiences. Indeed, young adulthood is the most at-risk age group for exhibiting extreme aggressive behaviors, such as homicide ( U.S. Department of Justice, 2009 ), and interpersonal violence disproportionately occurs in young adulthood compared to other developmental stages ( Kim, Laurent, Capaldi, & Feingold, 2008 ). As such, young adulthood a critical time to interrupt the intergenerational transmission of aggression. Our findings demonstrate the importance of assessing the influences of multiple physiological systems on outcomes simultaneously as well as the need to consider the role of developmental history to more fully understand relationships between physiology and behavior. The identification of biological markers associated with different forms of aggression in diverse young women helps inform the development of prevention programs to break the intergenerational transmission of violent behavior in an under-studied and under-served population.

Acknowledgements

This work was supported by grants from the San Francisco State University (SFSU) Office of Research and Sponsored Programs and the National Institute of Health Building Infrastructure Leading to Diversity (BUILD) Initiative (UL1GM118985).

Declaration of Competing Interest

The authors have no conflicts of interest to report.

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Family Conflict Resolution: 6 Worksheets & Scenarios (+ PDF)

It is perhaps unrealistic to expect that relationships remain harmonious all the time; occasional disconnections and disagreements are a fact of life that can help a family grow and move forward, accommodating change (Divecha, 2020).

Repeating patterns of conflict, however, can be damaging for family members, especially children, negatively affecting mental and physical wellbeing (Sori, Hecker, & Bachenberg, 2016).

This article explores how to resolve conflict in family relationships and introduces strategies and activities that can help.

Before you continue, we thought you might like to download our three Positive Communication Exercises (PDF) for free . These science-based tools will help you and those you work with build better social skills and better connect with others.

This Article Contains:

How to resolve conflict in family relationships, 2 examples of conflict scenarios, 3 strategies for family counseling sessions, 6 activities and worksheets to try, a note on conflict resolution for kids, 3 best games and activities for kids, resources from positivepsychology.com, a take-home message.

“Families typically develop certain basic structural characteristics and interactive patterns that they utilize to respond to internal and external stressors.”

Goldenberg, 2017, p. 4

Built on shared assumptions and narratives that exist within the family structure, family members support the group as it adapts and copes with shifting environments and life events.

Such structures, at times, may support and even promote conflict that occurs within families. Indeed, rifts, clashes, and disagreements within the family can take many forms, including physical, verbal, financial, psychological, and sexual (Marta & Alfieri, 2014).

Therapy has the potential to help a family understand how it organizes itself and maintains cohesion, while improving how it communicates and overcomes problems that lead to conflict (Goldenberg, 2017).

As psychologist Rick Hanson writes, “a bid for repair is one of the sweetest and most vulnerable and important kinds of communication that humans offer to each other” (cited in Divecha, 2020).

Crucially, families can learn to navigate the inevitable tension and disconnection that arise from falling out of sync with one another (Divecha, 2020).

Repairing ruptures resulting from miscommunication, mismatches, and failing to attune to one another is vital for parenting and maintaining family union. But how?

While there are many ways to recover from and resolve conflict, the following four steps are invaluable for authentic repair (modified from Divecha, 2020):

• Acknowledge the offense Try to identify and understand the hurt you’ve caused. Whether intended and with apparent good reason or not, this is a valuable opportunity to dial down your defenses and focus on how the other person is feeling.

Acknowledging the hurt without adding caveats is a powerful way to show humanity.

It can help to check your understanding, “Did I upset you? Help me understand how.” Your approach must be open and authentic; unless heartfelt, it risks escalating emotions.

• Express remorse Sometimes, simply saying, “I’m sorry,” is enough, or at least an excellent place to start.

Take care though. Adding a comment, such as, “Well, you shouldn’t have done X,” weakens your expression of remorse, especially when dealing with children. They are learning from what you do – right and wrong.

Also, don’t go overboard. Being too quick to say sorry or going over the top with an apology can make it more about yourself than the person hurt.

• Offer a simple explanation If the other person is ready to listen (neither too upset nor too angry), a brief explanation can clarify the thinking behind your actions.

Remember to focus on the other person’s experience rather than a litany of excuses for poor behavior. And avoid using this as an opportunity to add grievances or assign blame for issues that have arisen recently.

• Learn and practice expressing your intentions to fix the situation and stop it from happening again. Be sincere. Say that you are sorry and mean it.

There is little point in apologizing and recovering from conflict if you intend to repeat the behavior.

Conflict is often avoidable. But if it isn’t, then it is possible to recover and maintain family relationships through authentic activities that repair damage (Divecha, 2020).

Family therapy can help resolve conflicts within the family unit through multiple routes, including:

• Exploring various relationships that make up the family.
• Bringing couples and families together to resolve interpersonal conflicts rather than treating them separately.
• Focusing on interventions with entire families rather than individuals.
• Establishing the role of dysfunctional families in individual mental health problems.

Family conflict can appear in all shapes and sizes. While minor disagreements between siblings may be resolved quickly, major rifts can form between child and parent, damaging previously strong bonds.

All relationships within a family can at one time or another descend into conflict. Two such examples include (modified from Goldenberg, 2017):

• Conflict over money Bob and Tess are married with two children. In therapy, Tess claims that Bob is mean with his money: checking grocery bills and yelling at the cost of their children’s birthday presents. Along with other relationship issues, conflict had led them to sleep in separate rooms.

Bob argues he works hard for his money and gives her a generous amount each month, but Tess spends beyond their means.

During therapy, it became clear that Bob comes from a working-class family and was taught from an early age to live frugally. His long-standing beliefs underpin (but do not excuse) his outbursts.

In time, therapy helps them become more supportive of one another, giving up their underlying power struggles and successfully moving away from stereotypical gender roles.

• Cultural and intergenerational conflict Despite Indira and Sanjay Singh moving to the United States while they were still at preschool age, they have retained the cultural and moral values of their place of birth: India. When their two children were born, they were also taught to be compliant and respect their parents, while friends from school were discouraged.

As the children grew older, it became clear that the conflict between the old and new culture was causing a rift, dividing children and parents. Despite reluctance from the parents, in time, all four attended family therapy and began to deal with cultural differences and expectations arising from multiculturalism.

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Conflict in family situations can be “chronic and unresolved,” cycling through “periods of emotional distance and closeness with intense negative feelings” (Metcalf, 2011, p. 45).

In family therapy, the many theories offer different lenses through which to view the world and, most importantly, help families manage and resolve conflict (Metcalf, 2011).

The following strategies can help protect the family from or cope with conflict in its many forms.

Build an environment of connection and understanding

Divecha (2020) suggests that by building an environment of connection and understanding, you can “create a family culture where rifts are expected and repairs are welcomed.”

Encourage clients to make small but vital changes to the family setting (modified from Divecha, 2020):

• Watch out for the easily missed signs that indicate a child, young adult, or partner wishes to find a way to reconnect and recover from conflict.
• Normalize requests, such as, “I need a repair” and “Can we have a redo?” that tell us a family member is ready to fix a damaged relationship.
• Maintain awareness. If we think we may have caused upset or harm, circle back and check in with the other person.

Building a better environment through frequent repairs can catch problems early and reduce the likelihood of escalation.

Use “I” statements

How we say something can have a significant impact on what others hear. Encourage family members to express how they feel without blaming others, such as (modified from Goldenberg, 2017):

“I am hurt by what you said last night” rather than accusations, such as, “You were out of order last night.”

Speak directly to the therapist

There may be times during a therapy session when tension between family members heightens and the emotional intensity needs to be de-escalated (Goldenberg, 2017).

A helpful communication technique is to ask the family member talking to address the therapist directly. This refocus encourages the speaker to express themselves more calmly and allows the other person time and space to listen and respond under less pressure.

The following activities focus on exploring family structures, beliefs, and problem-solving behavior to avoid or resolve conflict within the group.

Recognizing Family Narratives

Family narratives provide support for coping with upsetting events and recovering from conflict (Goldenberg, 2017).

Use the Recognizing Family Narratives worksheet to identify narratives that explain and justify the structure and interactive patterns that exist within the family.

The constructs we form can enable or inhibit how we cope with conflict and other life events within the family (Goldenberg, 2017).

Parenting With Purpose

Parenting can be difficult; it is easy to lose sight of what is important. Defining meaning and purpose for ourselves as parents and our children can offer a valuable compass for day-to-day decision-making (Hart, 2006).

The Parenting With Purpose worksheet is a helpful reminder of your values and purpose as a parent.

The answers to the questions can help you understand what kind of relationship you would like with your children and why.

What Is Working Within the Family?

While it is essential to identify and fix what is causing conflict within a family, it is equally valuable to recognize what is working.

Once we recognize where we are successful in a relationship, it can remind us that not everything is terrible. We are doing some things right, and we have something upon which we can build.

The What Is Working worksheet helps identify and share the positives in the relationships within the family.

Recognize that conflict doesn’t occur in the family all the time and encourage the activities that unite you as a group.

Meeting Our Family’s Needs

Sura Hart (2006, p. 175), former teacher and education project director for the Center for Nonviolent Communication, says that “you can find conflict in every human story, and in the conflict situation you can find the needs people are wanting to meet.”

Use the Meeting Our Family’s Needs worksheet to help each family member have their needs heard, understood, and, ultimately, accepted.

Consider Your Intentions

Words have the power to share love and anger. Without clear and conscious intention, it is possible to communicate unhelpful and even harmful messages (Hart, 2006).

Use the Consider Your Intentions worksheet to identify and understand your intentions and help you respect and care for other family members’ needs.

Perform an early check on your intentions before you engage with the other family member, especially if it has the potential to turn into conflict.

Using the answers, consider how you can show positive intentions and steer clear of harmful intentions, such as proving yourself right.

Seeing Family Conflict as a Problem to Solve

Conflict isn’t always to be avoided; clashes can be productive, stimulating learning, fostering understanding, and moving a relationship forward (Hart, 2006).

However, some conflict is unnecessary and avoidable, especially regarding daily tasks, such as tidying the house, going to bed, and completing chores.

Use the Seeing Family Conflict as a Problem to Solve worksheet to help recognize everyday actions as problems to overcome rather than points of contention.

14 Effective conflict resolution techniques – BRAINY DOSE

“Life is a series of mismatches, miscommunications, and misattunements that are quickly repaired” says family researcher Ed Tronick (cited in Divecha, 2020).

Children can learn from the family environment that conflict need not be out of proportion to the situation and may, ultimately, lead to positive change.

It helps when family relationships are overwhelmingly positive. Make sure to make “special time” available for each child, where they have control over what you do and for how long, writes Divecha (2020). Learn to show gratitude and appreciation for what the child does more readily without it becoming predictable and unthinking.

Board games such as Monopoly, Checkers, and Life can be played as a pair or a family. The children see that it’s okay to make mistakes and learn from their parents’ reaction to losing.

More physical, active games such as Tag or Hide and Seek allow the whole family to have fun, while, importantly, seeing each other having fun. Children need to experience their parents as humans with a wish to enjoy themselves. Parents benefit from experiencing their family laughing – a reminder that life is not all about duty and rules.

Quieter pastimes, including art and craft, can be a time to build and use mindfulness practices, considering colors, textures, and smells. Interactive activities such as making funny characters out of play dough or houses out of Lego is fun and beyond rules or feelings of failure.

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Family conflict can often be avoided. The following resources help individuals gain a greater understanding of other family members’ needs and feelings.

• Mind the Gap Identify and share the values you would like to exist within your family, such as love, trust, compassion, and teamwork.
• Conflict at School Conflict outside the home can have an impact inside. Help your children to reflect on the relationships they have at school.

Additional reading and resources include:

• Conflict Resolution in Relationships and Couples: 5 Strategies For more ideas on how to resolve conflict in other types of relationships, read our conflict resolution in relationships article.
• 14 Conflict Resolution Strategies & Techniques for the Workplace This article about conflict resolution in the workplace is a helpful additional read, especially where the lines between family and work is blurred – working in the family business, working from home – these all can cause conflict so be sure to have a look at this article too.

If you’re looking for more science-based ways to help others communicate better, check out this collection of 17 validated positive communication tools for practitioners. Use them to help others improve their communication skills and form deeper and more positive relationships.

It is vital that families learn to survive – and even grow – under adverse conditions. The family unit faces daily challenges from outside and conflict from within that can upset the internal stability that rests upon existing narratives, shared beliefs, and sometimes mistaken assumptions (Goldenberg, 2017).

It can become less about preventing all conflict, which is impossible, and more about creating a family environment that reduces unnecessary friction, repairs rifts and misunderstandings, grows, and moves forward.

Our communication – what we say and how we say it – remains crucial and can improve over time with practice and an improved awareness of one another’s needs. Family members can also learn skills and techniques to improve self-regulation, resilience, and coping that strengthen internal structures.

This article introduces tools and worksheets that help remove avoidable conflict and manage and resolve it within the family unit, where disagreement is inevitable. Try them out with your clients or within your own family to improve engagement, strengthen relationships, and build a more supportive and resilient family structure.

We hope you enjoyed reading this article. Don’t forget to download our three Positive Communication Exercises (PDF) for free .

• American Psychological Association. (2011). Family interventions. Retrieved October 6, 2021, from https://www.apa.org/pi/about/publications/caregivers/practice-settings/intervention/family
• Divecha, D. (2020, October 27). Family conflict is normal; it’s the repair that matter s. Greater Good. Retrieved October 4, 2021, from https://greatergood.berkeley.edu/article/item/family_conflict_is_normal_its_the_repair_that_matters
• Goldenberg, I. (2017). Family therapy: An overview . Cengage Learning.
• Hart, S. (2006). Respectful parents, respectful kids: 7 Keys to turn family conflict into co-operation . PuddleDancer Press.
• Marta, E., & Alfieri, S. (2014). Family conflicts. In A. C. Michalos (Ed.), Encyclopedia of quality of life and well-being research . Springer.
• Metcalf, L. (2011). Marriage and family therapy: A practice-oriented approach . Springer.
• Sori, C. F., Hecker, L., & Bachenberg, M. E. (2016). The therapist’s notebook for children and adolescents: Homework, handouts, and activities for use in psychotherapy . Routledge/Taylor & Francis.

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We have had major conflicts in the family with me, my husband, who is the stepdad, and my grown kids. One speaks to us but lives on the northern East Coast. Haven’t seen him in 5 years. The other grown child is my daughter. She has had no contact with us of any kind for 5 years. I look forward to learning how to defuse conflicts and then grow healthy relationships, with my kids especially.

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Article contents

Work-family conflict and work-life conflict.

• Ellen Ernst Kossek Ellen Ernst Kossek Basil S. Turner Professor of Management, Krannert School of Management, Purdue University
•  and  Kyung-Hee Lee Kyung-Hee Lee Krannert School of Management, Purdue University
• https://doi.org/10.1093/acrefore/9780190224851.013.52
• Published online: 26 October 2017

Work-family and work-life conflict are forms of inter-role conflict that occur when the energy, time, or behavioral demands of the work role conflicts with family or personal life roles. Work-family conflict is a specific form of work-life conflict. Work-family conflict is of growing importance in society as it has important consequences for work, non-work, and personal outcomes such as productivity, turnover, family well-being, health, and stress. Work-family conflict relates to critical employment, family, and personal life outcomes. These include work outcomes (e.g., job satisfaction, organizational commitment, and turnover), family outcomes (e.g., marital satisfaction and family satisfaction), and personal outcomes related to physical health (e.g., physical symptoms, eating and exercise behaviors), and psychological health (e.g., stress and depressive symptoms, life satisfaction). Many different theoretical perspectives are used to understand work-life conflict: starting with role theory, and more recently conservation of resources, job demands and resources, and life course theories. Many methodological challenges are holding back the advancement of work-family conflict research. These include (1) construct overlap between work-family conflict and work-life conflict, and work-life balance measures; (2) measurement issues related to directionality and operationalization; and (3) a lack of longitudinal and multilevel studies. Future research should include studies to (1) advance construct development on linkages between different forms of work-family and work-life conflict; (2) improve methodological modeling to better delineate work-family conflict mechanisms; (3) foster increased variation in samples; (4) develop resiliency interventions that fit specific occupational contextual demands; (5) increase integration and sophistication of theoretical approaches; and (6) update work-family studies to take into account the influence of the growing prevalence of technology that is transforming work-family relationships.

• work-family conflict
• work-life conflict

The Growing Societal Importance of Work-Family Conflict

Work-family conflict is a growing challenge for modern society, as a vast majority of men and women report that work interferes with their family responsibilities (Glavin & Schieman, 2012 ). Work-family conflict is rising due to the changing work and family demographic trends in the United States and around the globe, including growing numbers of mothers with children under 18 in the labor force; the rapid rise in elder care demands due to an aging population; and an increase in men’s involvement with family caregiving demands, particularly in developed Western countries (Kossek & Distelberg, 2009 ; Kossek & Ollier-Malaterre, 2013 ). Work-family conflict is also growing due to the spread of technology that has increased boundary blurring and the pace of daily life, due to the prevalence of personal electronic communication devices that can keep individuals constantly connected to work and family concerns 24-7 (Kossek, 2016 ).

Work-family conflict directly and indirectly affects most of the world population. Even single people and those without children—will report having some work-family conflict as all individuals may be sons, daughters, sisters, brothers, or may live with friends who function as family (Casper, Weltman, & Kwesiga, 2007 ). Work-family conflict also has rising indirect effects as studies show work-family conflicts may cross over to job colleagues (O’Neill et al., 2009 ) and families (Westman, 2001 ).

We organize this article by beginning with a definition of work-family conflict and noting that it is a specific form of work-life conflict. Next we discuss why work-family matters: its consequences. Then we consider theoretical perspectives of work-family conflict; methodological issues; and its mechanisms, including antecedents and mediators/moderators; and conclude with future research.

Definitions and Consequences

Work-family and work-life conflict.

Work-family conflict is a form of inter-role conflict that occurs when the energy, time, or behavioral demands of the work role conflicts with those of the family role (Greenhaus & Beutell, 1985 ). A key assumption of work-family conflict is that the demands and expectations of work (e.g., working late, travel) often conflict with those of the family (e.g., picking up a child after school to be able to attend their soccer practice or music lesson) or taking a parent to the doctor when they are sick and cannot drive themselves. When an individual’s multiple roles such as work and family become incompatible with each other, role conflict occurs (Kahn et al., 1964 ).

Work-life conflict is an extension of work-family conflict reflecting the reality that the work role may interfere with individuals’ other personal life roles and interests. Besides the family role, these can range from time for friends, exercise, military service, education, having time for self and recovery (Kossek, 2016 ), volunteering, or being active in religious organizations. While work-family conflict remains a key factor for many employees, a challenge with current research is that scholars often methodologically and theoretically confound all forms of non-work conflict in the work-family measure (Wilson & Baumann, 2015 ). Consequently, some researchers such as Siegel, Post, Brockner, Fishman, and Garden ( 2005 ) use the term “work-life conflict” to reflect the many additional non-work demands in individuals’ lives that are not restricted to those involving the family. In this article, we use the term work-family conflict and work-life conflict, interchangeably, unless otherwise noted.

Consequences of Work-Family Conflict for Work and Non-Work Roles and Stress

Work-family conflict is related to many critical employment and personal life outcomes. These include work outcomes (e.g., job satisfaction, organizational commitment, and turnover), family outcomes (e.g., marital satisfaction and family satisfaction), physical health (e.g., physical symptoms, eating and exercise behaviors), psychological health (e.g., stress and depressive symptoms), and life satisfaction (Allen & Armstrong, 2006 ; Allen, Herst, Bruck, & Sutton, 2000 ; Grandey & Cropanzano, 1999 ; Kossek, Lautsch, & Eaton, 2006 ; Kossek & Ozeki, 1998 ; Netemeyer, Boles, & McMurrian, 1996 ).

Allen and colleagues’ meta-analysis ( 2000 ) organized consequences of work-family conflict into three main groups: work-related, non-work-related, and stress-related and ranked the relative effect sizes. Among work-related outcomes, turnover intentions ( r = .29) had the strongest relationship followed by job satisfaction ( r = −.24), and organizational commitment ( r = −.23). The non-work-related outcomes were all significant in this order: life satisfaction ( r = −.28) had the strongest relationship, followed by martial satisfaction ( r = −.24) and family satisfaction ( r = −.17). Many stress-related outcomes were significant from alcohol abuse ( r = .17) to all others such as physical health strain and depressive symptoms all being at least r = −.29 and above with burnout being the highest at r = .42.

Theoretical Perspectives

Having discussed the importance of work-family conflict for individuals, families, and organizations, in this section we turn to its theoretical underpinnings. While its theoretical roots are most attributed to role theory, conservation of resources, demands and resources and life-course perspectives have also been used to understand work-family conflict. Role theory focuses on subjective conflict role demands of work and family domains while conservation of resources theory mainly focuses on individual coping strategies to protect depletion of resources. The demands-and-resources approach is often focused at the job level emphasizes the dual processes of job demands and job resources. While sometimes family resources are included, most of the management literature has emphasized the work domain. The conservation of resources theory relies on individual actions to preserve resources while the demands-resources approach emphasizes the importance of perceptions of the work environment. The life-course perspective integrates historical, social, and family contexts into work-family conflict research.

Role Theory

Grounded in role theory (Katz & Kahn, 1978 ), work-family conflict results from the incompatibility of role demands between work and family from time, strain, or behavior (Greenhaus & Beutell, 1985 ). Work role conflict can occur in two directions; from work to family or from family to work (Kossek & Ozeki, 1998 ). It can be asymmetrical in impact as work variables seems to be more strongly related to work-to-family conflict than family variables seem to be related to family-to-work conflict (Byron, 2005 ).

Time-based role conflict occurs when the time demands from work and family compete with each other (Greenhaus & Beutell, 1985 ).For example, overtime takes away hours a parent can spend with children (work-to family conflict); and illness of a family member may limit working hours (family-to-work conflict). Recent studies (Clarkberg & Moen, 2001 ; Dugan, Matthews, & Barnes-Farrell, 2012 ) suggest that subjective measures of time, namely, work hours preferences or perceptions of time pressures are key aspects to update measures of work-family conflict. Strain-based conflict occurs when strain in one role constrains individuals’ ability to perform another role (Greenhaus & Beutell, 1985 ). For example, a study of professionals found that exhaustion and anxiety from work can spill over to family or life domain (work-to-family conflict) limiting individuals’ role performance (Kinman & Jones, 2001 ). On the other hand, new parents may not get enough sleep, affecting their work performance (family-to-work conflict). Behavior-based conflict occurs when behavior patterns related to work and family are not compatible (Greenhaus & Beutell, 1985 ). While some scholars argue that behavior-based work-family conflict may not be relevant to most occupations (Mauno, Kinnunen, & Ruokolainen, 2006 ), it is clear that certain occupations such as military (Britt, Adler, & Castro, 2006 ) or prison guards (Kinman, Clements, & Hart, 2017 ) may require hostile or aggressive interpersonal interactions that may not be suitable in family interactions (work-to-family conflict) (Dierdorff & Ellington, 2008 ). Similarly, needing to be very nurturing with a preschooler may require behaviors that might not fit with a more hard-nosed environment such as being a CEO that has to downsize and fire people or being a police officer that has to arrest people (family-to-work conflict). Thus, there may be occupational variation in the processes and degree to which work-family processes such as positive and negative crossover of roles may operate.

Conservation of Resources Theory

Work-family conflict is typically conceptualized as a type of stress in conservation of resources theory (Hobfoll, 1989 ). When individuals are trying to balance the demands of work and family, they may experience or be threatened to experience the loss of resources such as time and energy, leading to stress that is one form of work-family conflict (Grandey & Cropanzano, 1999 ). Conservation of resources theory is based on the premise that (1) individuals seek to gain and protect objective sources or conditions; and (2) stress occurs when the loss of resources is threatened, and investment of resources does not lead to resource gain (Hobfoll, 1989 ). Conservation of resources theory often emphasizes protection of resources such as a good marriage, free time, personal health, self-discipline, financial assets, and tangible family help with work tasks (Hobfoll, 1989 ). Individuals also gain resources by performing a role well (e.g., promotion, higher pay, or self-esteem). However, resource loss has greater impact (negative) on individual outcomes than resource gain (Hobfoll, 2001 ).

According to the conservation of resources theory, there are several coping mechanisms of work-family conflict. One mechanism relates to the cross-domain investment of resources to prevent resource losses. For example, when individuals experience problems at work (e.g., low performance) or home (e.g., a sick child), they may feel they have to invest more resources in the problem area to prevent resource losses. This may increase stress in one domain that can spill over to the other domain (Grandey & Cropanzano, 1999 ) or limit resources for the other domain (Halbesleben, Harvey, & Bolino, 2009 ). A second mechanism relates to when individuals invest large amount of resources to work or experience chronic, minor losses without any return resource gain, and individuals experience personal burnout (Hobfoll, 2001 ). A third mechanism occurs when individuals may guard against future resource loss through proactive coping, which refers to “efforts undertaken to either prevent a potentially stressful event or modify its form before it occurs (Aspinwall & Taylor, 1997 , p. 417). Here, individuals strive to attain, maintain, and invest in new resources to be better prepared for potential future loss. The ability to engage in proactive coping may depend on the initial level of resources. Individuals have to have enough resources to be able to invest to gain new resources (e.g., new skills), ultimately protecting them from the future resource loss (Hobfoll, 2001 ).

Demands-and-Resources Approaches

Resources-and-demands approaches emphasize the need to examine demands and resources to understand job strain contributing to work-family conflict (Bakker & Demerouti, 2007 ; Bakker, Demerouti, De Boer, & Schaufeli, 2003 ; Voydanoff, 2005a ). The job demands-and-resources model assumes that job demands may deplete individuals’ resources, resulting in negative individual and work outcomes. On the other hand, job resources have potential to motivate individuals to perform better, leading to positive individual and work outcomes (Bakker & Demerouti, 2007 ). This approach also suggests that some job resources such as social support, autonomy, and supervisor feedback may act as a buffer between job demands and job strain (Bakker & Demerouti, 2007 ). For example, Xanthopoulou, Bakker, Demerouti, and Schaufeli ( 2007 ) note that high levels of autonomy and support reduce the impact of job demands on burnout among home-care organization employees.

Voydanoff ( 2005a ) extended one-domain demands-and-resources approaches by integrating both work and family domains. Based on person-environment fit theory (Edwards, Caplan, & Van Harrison, 1998 ; French, Caplan, & Van Harrison, 1982 ) and boundary theory (Ashforth, Kreiner, & Fugate, 2000 ), Voydanoff ( 2005a ) proposed that the cross-domain fit (the work demands-family resources fit and the family demands-work resources fit) is the key to decreasing work-family conflict and achieving work-family balance. Fit is achieved when “resources meet, offset, or satisfy” demands (Voydanoff, 2005a , p. 828). There are two mechanisms of work-family conflict. First, the fit between work demands-family resources and the fit between family demands and work resources have direct relationships with work-family conflict. Second, boundary-spanning strategies such as reducing hours, or reducing family or work demands may mediate or moderate the relationship between work-family fit and work-family conflict to enhance fit (Voydanoff, 2005a ).

Life-Course Perspective

The life-course perspective (Elder, 1998 ) provides a unique framework and concepts such as historical time, transitions, or linked lives to examine work-family conflict. First, the concept of historical time and social context captures shifts in workforce and career zeitgeist from the past. Contemporary workers are less likely to spend their whole career and regularly advance in one organization, and feel secure in their jobs than workers from previous decades. Yet they are more likely to customize their timing of retirement, pursue flexible work arrangements such as reduced workload and telework, and seek work-family balance (Greenhaus & Kossek, 2014 ). Given these historical and life-course changes, it is likely to expect changes in work-life conflict processes. Blair-Loy ( 2003 ) found that younger cohorts of female executives reported less work-family conflict than older cohorts, partly because they are more likely to hire someone to do domestic chores. Second, the concept of transition also helps us to understand how changing family demands over time may affect work-life conflict processes. For example, the child care demands for a newborn baby are quantitatively and qualitatively different from those of an adolescent and may require different types of resources. Furthermore, with the growing elderly population, more people provide informal care to elder family members. These elder care responsibilities may delay retirement to ensure financial and health care coverage, which in turn decrease job satisfaction and increase conflict (Dentinger & Clarkberg, 2002 ). Third, the concept of linked lives allows researchers to examine the crossover effect of family member strain from work-family conflict (Westman, 2001 ). For example, husbands’ work stress can decrease the sense of work-family balance in wives (Fagan & Press, 2008 ). Positive crossover effects can also occur as support from a partner can decrease individuals’ work-family conflict (Becker & Moen, 1999 ; van Daalen, Willemsen, & Sanders, 2006 ; Thorstad, Anderson, Hall, Willingham, & Carruthers, 2006 ). Now we turn to methodological issues related to definitions, measurement, and study designs, and then to mechanisms of work-family conflict.

Methodological Issues

Work-family conflict vs. work-family balance.

One main methodological issue is the issue of construct overlap, such as the work-family conflict and work-life conflict issues noted earlier. Work-family conflict and work-family balance are also closely related concepts. While there seems to be a consensus among scholars that work-family balance is distinct from work-family conflict, empirical evidence is scarce (Greenhaus & Allen, 2010 ). One recent study (Carlson, Grzywacz, & Zivnuska, 2009 ) found that work-life balance explained work and family outcomes beyond the variance explained by work-family conflict, supporting the argument that work-family balance is a distinct concept.

Although work-family balance frequently has been defined as the absence of work-family conflict (Grzywacz & Carlson, 2007 ), a growing number of researchers are conceptualizing work-life balance independent of work-family conflict. Work-family balance is defined as equal commitment to and equal satisfaction in work and family (Greenhaus, Collins, & Shaw, 2003 ; Marks & MacDermid, 1996 ). Some scholars focus on satisfaction with work-family balance defined as “an overall level of contentment resulting from an assessment of one’s degree of success at meeting work and family role demands” (Valcour, 2007 , p. 1512). However, Grzywacz and Carlson ( 2007 ) criticized these definitions arguing (1) that individuals do not seek to achieve equality in their work and family; and (2) that using satisfaction to define work-life balance reinforces the individualist views on work-family balance, making it an individual problem. Instead, they proposed the definition of work-family balance as “accomplishment of role-related expectations that are negotiated and shared between an individual and his or her role-related partners in the work and family domains” (Grzywacz & Carlson, 2007 , p. 458).

Conflict and balance are conceptually overlapping because these concepts are defined or imply the absence of the other. Although not overlapping, a new stream of research focuses on work-family enrichment to understand the positive dynamics between work and family to augment the conflict view, which examines negative dynamics. Work-family enrichment is defined by Greenhaus and Powell ( 2006 , p. 73) as “the extent to which experiences in one role improve the quality of life in the other role” Work-family enrichment theory maintains that positive processes and outcomes can occur from being involved in both work and family. They theorize that three possible mechanisms may foster these benefits: the positive additive effects of multiple roles for well-being; the opportunity to buffer roles so that when something is going wrong in one role, the other role can compensate; and the transfers of positive emotions and skills between roles.

Measurement Issues

Directionality.

Since the 1990s, researchers have realized that work-to-family and family-to-work conflict needed to be measured separately (MacDermid & Harvey, 2006 ). A meta-analysis study (Kossek & Ozeki, 1998 ) on relationships between work-family conflict and job-life satisfaction found stronger findings for bidirectional measures (work-to-family and family-to-work) than non-directional general measures. It also found stronger work-family relationships for women than men. Another meta-analysis (Mesmer-Magnus & Viswesvaran, 2005 ) concluded that work-to-family conflict and family-to-work conflict are related but distinct constructs, warranting separate examination. The bidirectional measures have deepened our understanding of work-family conflict. There is evidence that although work-to-family conflict and family-to-work conflict are correlated and both are associated with individuals’ well-being (Frone, Russell, & Barnes, 1996 ), work-to-family conflict is more common than family-to-work conflict (Frone, 2003 ; Kossek & Ozeki, 1998 ), suggesting asymmetry in impact on general well-being and health. Moreover, in general, work-related variables are more likely to be related to work-to-family conflict and family-related variables are more likely to be associated with family-to-work conflict (Byron, 2005 ; Frone, Yardley, & Markel, 1997 ; Michel, Kotrba, Mitchelson, Clark, & Baltes, 2011 ).

Operationalization and Measures of Work-Family Conflict

The lack of consistency of the operationalization of work-family conflict across studies has been an issue in work-family conflict literature (Allen et al., 2000 ; Kossek & Ozeki, 1998 ; Netemeyer et al., 1996 ). Different operationalization combined with different measures makes integrating and comparing study findings of work-family conflict challenging. Furthermore, after reviewing 67 studies, Allen and colleagues ( 2000 ) concluded that single-item measures, measures with unknown validity and measures with different foci were prevalent problems (for detailed list of measures, see Allen et al., 2000 ; Byron, 2005 ; Mesmer-Magnus & Viswesvaran, 2005 ). They recommended that measures should be developed that cover both work-to-family conflict and family-to-work conflict (e.g., Netemeyer et al., 1996 ) and Greenhaus and Beutell’s ( 1985 ) three forms of work-family conflict (time-, strain, and behavior-based conflict; e. g., Carlson, Kacmar, & Williams, 1998 ; Stephens & Sommer, 1996 ).

Cross-Sectional vs. Longitudinal Designs

While there have been many studies identifying antecedents, mediators/moderators, and consequences of work-family conflict, scholars cannot assume causal relationships because most are cross-sectional. Although some longitudinal studies have confirmed some causal relationships between antecedents, work-family conflict, and consequences (Dormann & Zapf, 2002 ; de Jonge et al., 2001 ; Wong, Hui, & Law, 1998 ), other studies found reciprocal or reverse relationships. For example, in a one-year longitudinal study (Kinnunen, Geurts, & Mauno, 2004 ), work-family conflict and well-being variables (job, family, and physical well-being) at time 1 predicted each other at time 2. In another study, general distress predicted work-to-family interference six months later but work-to-family interference did not predict general distress over time (Kelloway, Gottlieb, & Barham, 1999 ). More longitudinal studies are needed to understand causal processes of work-family conflict.

Yet sometimes longitudinal designs are not always appropriate or practical. There are several issues to consider when deciding to design a longitudinal work-family conflict study: (1) whether the research question is related to continuity and change over time, (2) time involved, (3) money involved, and (4) how to deal with missing data (Crouter & Pirretti, 2006 ). Work-family conflict also may be episodic as opposed to an on-going continuous phenomenon. Work-family researchers need to more carefully select the most appropriate study design based on the research question and practical issues.

Mechanisms of Work-Family and Work-Life Conflict

Research on work-family conflict has expanded from simply focusing on identifying antecedents and consequences to unveiling mechanisms or processes by identifying mediators and moderators, and using longitudinal design. Mediators help uncover hidden relationships or eliminate false relationships between variables. For example, many studies found a direct relationship between work-family conflict and turnover intention (Grandey & Cropanzano, 1999 ; Netemeyer et al., 1996 ). However, a study with 171 IT workers, Ahuja, Chudoba, Kacmar, McKnight, and George ( 2007 ) did not find a direct relationship between work-family conflict and turnover intentions, but the relationship was mediated by organizational commitment.

Moderators refine our understanding by highlighting the relationships between antecedent and outcome variables under certain conditions or for capturing variation in levels of sample characteristics. For example, in their study of accountants, Greenhaus, Parasuraman, and Collins ( 2001 ) found that the relationship between work-to-family conflict and withdrawal intentions and behaviors were stronger for accountants with lower levels of career involvement than those with higher levels of career involvement. Now we will briefly review antecedents, mediators/moderators, and consequences of work-family conflict separately.

Antecedents of Work-Family Conflict

Individual characteristics.

Meta-analysis studies (Byron, 2005 ; Kossek & Ozeki, 1998 ; Michel et al., 2011 ) identified some individual characteristics including gender, income, coping skills, and personality as antecedents of both work-to-family conflict and family-to-work conflict. Male workers tended to report higher work-to-family conflict while female workers tended to report higher family-to-work conflict. Income was only related to work-to-family conflict (Byron, 2005 ). Coping skills have not attracted much attention in work-family conflict literature (Kopelman, Greenhaus, & Connolly, 1983 ) despite some empirical evidence of usefulness in reducing conflict (Burke, 1998 ; Rotondo, Carlson, & Kincaid, 2003 ) and the growing interest in work-life interventions (Kossek, 2016 ). In a meta-analysis study (Michel et al., 2011 ), coping skills had similar effect sizes to work-to-family and family-to-work conflict ( ρ ‎ = .12 and ρ ‎ = .15, respectively), indicating that positive coping skills are valuable resources.

Some recent studies examine the relationships between personality characteristics (Bernas & Major, 2000 ; Grzywacz & Carlson, 2007 ; Stoeva, Chiu, & Greenhaus, 2002 ; Wayne, Musisca, & Fleeson, 2004 ) and work-family conflict. These studies generally were designed based on the assumption that some personal characteristics such as hardiness or agreeableness would be helpful in dealing with stress and strain while characteristics such as neuroticism would exacerbate work-family conflict. In fact, different big-five personality traits seem to have different effect on work-family conflict. For example, in a study with a large random sample (Wayne et al., 2004 ), neuroticism had the strongest positive relationship with both work-to-family and family-to-work conflict among the big-five personality characteristics. While agreeableness and conscientiousness were negatively associated with work-family conflict, extraversion and openness to experience were not. Kossek, Ruderman, Braddy, and Hannum ( 2012 ) found that variation in boundary management styles or how people organized work and non-work interruptions predicted work-family conflict with integrators reporting more work-family conflict than separators, a condition that was stronger under conditions of low job control. Kossek and Lautsch ( 2012 ) theorized a multi-level model suggesting that the more the organizational culture supported customization of work-family boundary management styles and diversity in boundary management style enactment, the lower the work-family conflict.

Family-Related Variables

Characteristics related to family structure including number of children, the age of children, and marital status have been identified as antecedents of work-to-family and family-to-work conflict. More children and having young children tend to be related to increased work-to-family and family-to-work conflict (Byron, 2005 ; Michel et al., 2011 ). Not surprisingly, parents with more children reported more family-to-work conflict than work-to-family conflict. Married workers reported higher work-to-family conflict but lower family-to-work conflict than single workers (Byron, 2005 ). One weakness of using family demographic measures alone, however, is that they measure role occupancy but not necessarily role involvement or the level of involvement in the family role.

Many variables related to the family role have been identified as antecedents of work-family conflict: (1) role involvement (e.g., hours spent, family involvement); (2) stress (e.g., family stress, family conflict, family overload); and (3) family identity (e.g., family identity salience, family centrality). Antecedents related to the family role such as family role involvement, hours spent, family conflict, family stress, and family role overload tend to be related to increased work-to-family and family-to-work conflict (Byron, 2005 ; Michel et al., 2011 ). However, family centrality (prioritizing family over work) was associated with lower levels of work-to-family and family-to-work conflict (Michel et al., 2011 ), suggesting some individuals may adopt strategies to reduce work-to-family conflict to protect the family role (Kossek et al., 2012 ) Family support can also be valuable as meta-analytic studies show that social support from family and spouse was negatively associated with both work-to-family and family-to-work conflict in similar magnitude (Byron, 2005 ; Michel et al., 2011 ).

Job-Related Variables

Many characteristics related to the job (e.g., organizational tenure, salary, work hours, job autonomy, job authority, job rank, blue collar vs. white collar, self-employment) have been examined as possible antecedents of work-family conflict and family-to-work conflict. However, there are conflicting findings on some of these variables. For example, organizational or job tenure tend to lead greater flexibility, leading to lower work-to-family conflict. Longer job tenure tends to be related to job status in the organization and higher job status tends to be related to more responsibilities and, thus, higher stress. Moreover, higher salary may relate to lower work-family conflict yet higher salary is also highly related to higher job status and more responsibilities (Michel et al., 2011 ). Thus these variables should not be looked at in isolation but together and family and work-role involvement must be measured simultaneously. Variables related to work-role involvement such as work hours, work demands, job involvement, job role ambiguity, and work identity have been identified as antecedents of work-to-family conflict (Byron, 2005 ; Dierdorff & Ellington, 2008 ; Michel et al., 2011 ; Voydanoff, 2005b ).

General support from supervisors and coworkers have been found to be negatively associated with both work-to-family and family-to-work conflict but the association was stronger with work-to-family conflict than to family-to-work conflict in meta-analysis studies (Byron, 2005 ; Michel et al., 2011 ; Kossek, Pichler, Hammer & Bodner, 2011 ).

Organization-Level and Occupational-Level Variables

Family-supportive work environments help workers to reduce work-to-family conflict (Kossek & Ozeki, 1998 ; Kossek et al., 2011 ; Mesmer-Magnus & Viswesvaran, 2006 ). The number of available work-family policies (e.g., flexible work arrangement, family leave, and dependent care assistant) have been the most common indicators of family-supportive work environments. However, without the organizations’ work-family culture, workers may not utilize the policies for fear of negative career consequences (Behson, 2002 ; Bragger et al., 2005 ). Thus, some scholars argue that the better indication of family-supportive environment is the perceived access to the work-family policy rather than the number of available policies (Kossek et al., 2011 ).

Supervisors play an important role in creating family-supportive environments. First of all, they can inform the employees the available work-family policies. In addition, supervisors who help employees to manage work-family demands can indirectly reduce work-to-family conflict by creating the family-supportive work environments. More importantly, family-supportive supervisors are directly associated with less work-to-family conflict (Hammer, Kossek, Bodner, & Crain, 2013 ; Hammer, Kossek, Yragui, Bodner, & Hanson, 2009 ). Furthermore, in another meta-analysis study, work-family specific support from supervisors was more strongly associated with work-to-family conflict than general supervisor support (Kossek et al., 2011 ).

The interest in occupation-level variables is a new development in work-family conflict literature. Dierdorff and Ellington ( 2008 ) argued that occupations dictate and shape certain role behaviors, which in turn explains the differences in work-family conflict across different occupations. They found that differences in role behaviors (interdependence and responsibility for others) across occupations explained variance in work-family conflict. Individuals with occupations that required higher levels of interdependence (having to interact with others to perform the job) and responsibility for others reported more work-family conflict than individuals whose occupations required lower levels of interdependence and responsibility for others. Occupations are also linked to access to work-family supports such as flexible work arrangements and job demands that may interfere with family life (Kossek & Perrigino, 2016 ). For example, professionals have greater access to telework unlike blue collar workers.

National/Cultural-Level Variables

Countries’ structure and culture are important contexts in understanding work-family conflict (for a comprehensive review, see Ollier-Malaterre & Foucreault, 2017 ). Similar to family-supportive work environments, national culture and policies may have impact on work-family conflict in many different ways. In a recent cross-national study in Europe, den Dulk, Groeneveld, Ollier-Malaterre, and Valcour ( 2013 ) found that national policies related to work-family support were strongly related to the extent that organizations adapted family-supportive policies such as dependent care arrangements (e.g., maternal/paternal leaves, family leave, child care support) and flexible work arrangements. The opposite pattern was found in the relationship between cultural centrality of work and organizations’ adoption of family-supportive policies. Organizations in the countries that value work as central to individuals and society adopted family-supportive policies less than those in the countries with lower levels of cultural centrality of work.

Another cultural value that is related to work-family conflict is individualism versus collectivism. Individuals in collectivistic countries tend to report more family-to-work conflict and less work-to-family conflict than those in individualist cultures (Allen, French, Dumani, & Shockley, 2015 ; Ng & Feldman, 2014 ). More family-to-work interruptions may explain higher levels of family-to-work conflict (Allen et al., 2015 ) while considering work as a necessary sacrifice for the family explains the lower levels of work-to-family conflict (Galovan et al., 2010 ) in collectivistic societies.

Mediators and Moderators of Work-Family Conflict

There is not a clear research literature clarifying identified mediators and moderators of work-family conflict, mostly due to the lack of longitudinal studies. A related issue in work-family conflict research is that the same variables have been used as antecedents and mediators/moderators in different (often cross-sectional) studies, potentially confusing the conceptualization of the mechanisms rather than helping to unveil new mechanisms.

Take personality as an example, which has been identified as an antecedent of work-family conflict. Yet personality has also been included as a mediator and a moderator between antecedents and work-family conflict (Stoeva et al., 2002 ) as well as between work-family conflict and consequences including job exhaustion and depression (Kinnunen, Vermulst, Gerris, & Mäkikangas, 2003 ). Stoeva and colleagues ( 2002 ) found that trait negativity mediated the relationship between stress and work-family conflict. Trait negativity also moderated the relationship so that the relationship between stress and work-family conflict was stronger for individuals with high negativity than individuals with low negativity. In another study (Kinnunen et al., 2003 ), emotional stability of fathers moderated the relationship between work-to-family conflict and well-being (e.g., job exhaustion and depression) and agreeableness moderated the relationship between family-to-work conflict and marital satisfaction. The relationships were stronger for emotionally unstable fathers and less agreeable fathers than their counterparts respectively.

Social support has also been included in work-family conflict studies as an antecedent, a mediator, and a moderator. Citing this as a limitation, Carlson and Perrewé ( 1999 ) tested four different models (social support as a mediator, a moderator, an antecedent of work-family conflict, and as an antecedent of stress) and confirmed that the antecedent to the stress model fit the data the best. However, their findings are not robust because they used cross-sectional data.

Individualism versus collectivism is another example. The relationships between work-family demands (antecedents) and work-to-family conflict found to be stronger in collectivistic cultures than in individualistic cultures (Lu et al., 2010 ). Collectivism also moderates the relationship between work-to-family conflict and depression in the same pattern (Fackrell, Galovan, Hill, & Holmes, 2013 ).

In most studies, individual characteristics such as gender, parental status, and marital status have been used as control variables. However, some meta-analysis studies included these as moderators and some of their findings have practical implications (Byron, 2005 ; Michel et al., 2011 ). For example, Michel and colleagues ( 2011 ) found that married individuals and parents may benefit more from family-supportive organizations (e.g., coworker social support, work schedule flexibility, family-supportive policies) than their counterparts.

Closing and Future Research

This preceding article suggests the need for more nuanced theoretically-based and longitudinal future research on work-family conflict. First, we need more in-depth research on construct development on linkages between different forms of work-family conflict and work-life conflict. For example, Wilson and Baumann ( 2015 ) have developed four new constructs that capture four types of inter-role conflict (work-to-personal, personal-to-work, family-to-personal, and personal-to-family conflict). Further, although there is clear evidence that work-to-family and family-to-work conflict are distinct constructs, they are still sometimes conceptualized and operationalized as one. This leads to the use of less reliable and valid measures and, consequently, hinders integration and comparison of the study findings. More efforts to validate existing measures and to use newer validated and theoretically stronger measures such as the Wilson and Baumann measures noted can help advance theory development and refinement.

Future research should conduct a more fine-grained analysis using these different forms of work-life and work-family conflict. We also need to bring in new measures of work-family balance and link to studies of work-family enrichment that focus on positive work-family relationships.

Second, we need to improve our methodological modeling to better explain and delineate the mechanisms of work-family conflict. While we have ample evidence of the antecedents and consequences of work-family conflict, we lack the understanding of conditions on which the relationships between variables vary. More studies that test mediation and moderation effects are needed. These models also need to consider contexts such as larger organizational, cross-cultural, and societal contexts. Many studies tend to focus on one level and more multi-level research is needed on nested relationships beyond an singular individual and organizational focus. Studies with multiple-level analyses will help us understand how different level variables interact with each other and how certain variables act differently across employee groups.

Although many antecedents and consequences of work-family conflict have been identified, our understanding of the mechanisms of work-family conflict is not complete due to the lack of longitudinal studies and consistent conceptualization. Without longitudinal studies, we cannot infer causal relationships based on study findings. The lack of longitudinal studies also leads to the conceptualization challenges. Because most of the studies that tested mediation or moderation effect used cross-sectional data, it is difficult to interpret or incorporate findings from the studies that used the same variables as antecedents, mediators, or moderators.

Third, we will need to increase the variation in samples and design interventions that fit these samples’ specific occupational contextual demands to better understand how to foster work-life resiliency (Kossek & Perrigino, 2016 ). Most studies still focus on white collar workers and professionals or overlook variation in the nature of job demands. The results may be different with blue collar workers or low-wage hourly workers because their needs are different. For example, Stanczyk, Henly, and Lambert ( 2016 ) observed that many women with an hourly retail job tend to have multiple jobs to compensate for the low wage and it may create additional conflict between work and family because of the scheduling complexity. Given the fact that many hourly workers may not have access to organizational family-supportive benefits such as paid leave and a dependent care assistant, we need to understand more about the work-family conflict processes to find ways to decrease work-family conflict. Research must move beyond simply describing work-family conflict to include interventions in randomized or naturally occurring field experiments to close the research-to-practice gap (Kossek, Baltes, & Matthews, 2011 ; Kossek, 2016 ).

Fourth, we need to integrate and have more sophistication in theoretical approaches. Theories that have guided so many studies in work-family conflict literature such as role theory, resource conservation theory, and life-course perspectives all served the field greatly. However, these theories can be complemented with mini theories. For example, challenge and hindrance stress theory (LePine, LePine, & Jackson, 2004 ) argues that not all stress is the same. They distinguish challenge stress (e.g., new skills, personal growth) form hindrance stress (e.g., role ambiguity, low-value work) and argue that challenge stress may be beneficial to individuals rather than creating negative consequences. Theories like this can help us tease out certain specific conditions that work-family conflict may arise.

Lastly, work-family studies need to catch up with how technology has transformed work-life relationships. With the wide use of smart phones, tablets, and laptop computers, new research is looking at boundary management strategies (Kossek & Lautsch, 2012 ) used by individuals and how these technologies have created more ways for us to interrupt others and to be interrupted by others both at work and home. Because the technologies created ways to be connected 24/7, some supervisors or families may expect their employees to be reachable any time. Moreover, we can take work to family events or vacations, should the need arise. More multilevel studies are needed to understand the full ramifications of these new communication and computer technologies that have fundamentally changed the relationship between the work and family spheres in the digital age (Kossek, 2016 ; Kossek & Lautsch, 2012 ).

Acknowledgment

Shared first authorship as both authors contributed in equal and distinctive ways to this entry.

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What are dysfunctional family relationships?

Common causes of family conflict, tips on interacting with difficult family members, when to cut ties with family members, dealing with difficult family relationships.

Struggling to coexist with difficult family members? Learn about common sources of conflict and how to deal with dysfunctional family relationships.

Mothers, fathers, siblings—your closest family members can form a lifelong social support system. They can celebrate your highs and give you comfort when you’re at your lows. Even so, disagreements and misunderstandings are bound to happen. Minor conflicts between family members are normal, and they typically resolve on their own or with some constructive dialogue. But other conflicts can be much more significant. In cases where resentment and toxic patterns arise, family interactions can become lasting sources of frustration and tear relationships apart.

Difficult family relationships can take on many forms. You might have an overly critical dad who makes you feel anxious. Perhaps a sibling’s jealousy is a constant source of tension at family functions. Or maybe you believe a new in-law’s controlling behavior leads to unnecessary drama.

These turbulent family relationships can have long-lasting effects on your health and well-being. You might:

• Begin to blame yourself for these poor relationships.
• Experience fear and anxiety surrounding family or holiday events.
• Hesitate to reach out to other family members.
• Suffer from lack of emotional or financial support during hard times.
• Develop trouble sleeping or focusing due to the stress of these interactions.

Research even indicates that poor relationships with parents, siblings, or spouses can contribute to midlife depression symptoms . Exposure to domestic conflicts can also have a long-term impact on a child’s well-being as well. One longitudinal study found that domestic arguments and violence can increase a child’s risk of developing mental and physical health problems later in life.

To minimize these consequences, you can learn how to identify causes of family tension and take steps to create peaceful interactions. While you might eventually find that cutting ties is the best option for your health and happiness, there are approaches you can take that can help repair family bonds and improve your relationships with those closest to you.

Speak to a Licensed Therapist

BetterHelp is an online therapy service that matches you to licensed, accredited therapists who can help with depression, anxiety, relationships, and more. Take the assessment and get matched with a therapist in as little as 48 hours.

Before you learn how to deal with difficult family members, it helps to examine why those relationships are rocky to begin with. Consider these common causes of family disputes and ways to navigate them:

Family finances

Family members tend to have some degree of financial overlap. Siblings might bicker over an inheritance. Parents may have strong opinions on how their children handle money. Or adult children might feel the need to control their aging parents’ finances.

When it comes to large family events, such as weddings or holiday parties, financial disagreements can often come to a head. However, there are ways to navigate money-related problems within your family.

Put things in writing. If you expect a family member to pay you back for a personal loan, for example, make a written agreement between the two of you. This can help you avoid arguments or even legal disputes.

Set boundaries. If a family member is pressuring you to loan or give them money or wants to dictate your finances, it’s important to clarify the type of behavior you won’t tolerate. Be clear so your family member will know when they’ve crossed the line.

Know when to be transparent. You don’t have to share all of your financial details with anyone. But, in cases where your decisions may affect your family members, it’s best to be transparent. You might want to talk to your children about details of their inheritance to avoid a future conflict, for example, or let your siblings know why you can’t contribute to a shared expense.

[Read: Coping with Financial Stress]

Caregiving responsibilities

Research from 2020 shows that about 19 percent of Americans are acting as unpaid family caregivers. The stresses and responsibilities of being a caregiver can weigh heavily on family relationships.

Studies indicate that tension between siblings tends to increase when a parent begins to need some level of caregiving. Perhaps you believe your sibling is in denial over your parent’s health and needs to be more proactive. Or maybe you and your sibling disagree on whether an assisted living facility is the right housing choice for your parent.

Conflicts over caregiving aren’t limited to sibling relationships. You might have arguments with your parents or spouse over how to raise your children.

When you and another family member are at odds over caregiving, try these tips:

Be open about what level of support you need as a caregiver. If you keep your feelings to yourself, resentment can grow and increase tensions.

Look for compromise and accept other people’s limitations. If your sibling can’t physically assist with caregiving, perhaps they can offer financial help. Remember to show your appreciation when your sibling takes on responsibilities.

If someone else is completely unable or unwilling to help with parental caregiving, try looking for support outside of your family .

[Read: Family Caregiving]

New family members

As your family expands, so does the potential for new conflicts. In one study of estrangement between mothers and adult children, more than 70 percent of the mothers said other family members caused the rift. The mothers often pointed to the child’s partner or spouse as the problem.

These conflicts aren’t limited to mothers and children, of course. You and your brother-in-law might have a contentious relationship. Or perhaps your father-in-law always seems to expect too much from you. To better get along with your in-laws:

Expect differences. Different families have different expectations, boundaries, and ways of doing things. Do you see your daughter-in-law as an untactful or even rude family member? Maybe she comes from a family background that encourages blunt language or tolerates teasing.

Focus on their most positive traits. Your in-laws are part of your family because someone else in your family saw the good in them. If you’re having a hard time seeing past their flaws, try making a list of their strengths.

Find common interests. Although it’s not always easy, you can usually find shared interests if you look hard enough. Ask about your in-laws’ hobbies, passions, and past experiences until you find something that’s relatable.

Political and religious differences

Religious and political similarities can affect the strength of family bonds. For example, studies indicate that when mothers share the same religion as adult children, they tend to experience higher-quality relationships.

On the other hand, when family members don’t have the same views on religion or politics, it can trigger heated arguments. Maybe your sibling objects to group prayers before meals. Or perhaps you hear insults and snide remarks when you express your political views. Here’s how to deal with difficult family members who have opposing views:

Identify useful conversations. When a debate starts, ask yourself what you hope to get from the interaction. Do you expect to completely change your family member’s mind? Or are you trying to gain insight into their beliefs? Is it at all possible that either of you will budge on your position? Even if you’ll never agree about something, you can still move the conversation forward if you’re both willing to be open and respectful of each other’s views.

Avoid sweeping generalizations. Statements like, “Everyone on the left is evil” or “Everyone on the right is an idiot” can quickly escalate arguments and further entrench people.

Try to see the human element in the other person’s values. Many political beliefs are shaped by an underlying concern for society, such as economic or environmental stability. By recognizing that, the other person’s views may not seem as wildly different from your own.

Know when to exit heated arguments. When emotions run too hot, make a respectful but firm exit from the conversation. You can say something like, “I’m not sure if this is productive. Let’s leave it there.” Contain the urge to have the “last word.”

Be mindful of your jokes. Humor can often help diffuse a tense argument . However, avoid aggressive jokes that target the other person’s beliefs or values.

Unresolved family issues

Things that happened in the past can have a lasting effect on family relationships. Did you and your son have an explosive argument when he was a teenager? If the matter went unresolved, he might continue to be resentful or distrustful of you. Did your parents seem to favor you over your brothers? Jealousy could become an underlying source of tension for your siblings.

Unresolved issues can often crop up during milestone events or times of change within the family. For example, insecurities over parental favoritism might reappear as you and your siblings begin to act as caregivers to an aging parent.

If you’re the one holding onto an issue, speak up. Invite the other person to a private conversation, where you can bring up the issue and share your perspective. Be willing to forgive if the party apologizes for their part in the problem.

If a family member is holding resentment, be empathetic. Try to understand how they perceived events and how the past continues to affect them. If you caused some harm to them in the past, apologize and ask how you can repair the damage to the relationship. For example, if you lost your temper with your son in the past, explain how you plan to do better going forward.

If neither person is at fault, it can still help to acknowledge the past and the effects of growing up in a dysfunctional family. Remember that no family is perfect, and past events influence present-day perceptions. Focus on what steps you can take in the present to resolve the conflict .

Despite your best efforts and intentions, sometimes you’ll find that you simply can’t get along with a family member. Perhaps someone continues to hold a grudge against you or refuses to change their behavior.

Your general plan might be to avoid difficult family members. However, that strategy can often be foiled by weddings, funerals, and other family gatherings. Here are some alternate options:

Manage your own stress

Prioritize de-stressing before and after you have to interact with a difficult family member. Effective stress management techniques can range from meditation to going for a walk to journaling your thoughts or chatting face-to-face with a close friend.

If you start to feel stressed by the difficult family member during the event itself, don’t hesitate to excuse yourself from the room and use some quick stress relief techniques to clear your head.

• Rely on your senses to ground yourself in the moment. Take in a deep breath of fresh air, find a friendly cat or dog to pet, or hum a tune to yourself. You can also use your imagination to picture something soothing, like your child’s face or a relaxing setting.
• If you tend to freeze when under stress, activities that involve physical movement are often most effective. Consider doing some stretches, swaying to background music, or jogging in place to burn off tension.

Set and maintain boundaries

Strong, clear boundaries can protect you from toxic family interactions. Imagine you and your spouse are about to visit overbearing in-laws. Talk to your spouse and set a limit on how long the visit will last. You can also set boundaries on conversation topics. If you and your in-laws have had heated arguments over religion, it might be best to steer clear of the topic.

If someone attempts to cross your boundaries, keep your temper in check. Instead, be clear and direct about the consequence. For example, you could say something like: “If you keep bringing up that topic, I’ll be leaving early.”

Build your emotional intelligence (EQ)

By strengthening your emotional intelligence, you can improve your ability to understand, manage, and express emotions. This can have a positive effect not just on your family relationships but on your overall mental health.

To enhance your EQ, you need to focus on four key skills:

• Self-management
• Self-awareness
• Social awareness
• Relationship management

You can develop these skills by taking steps such as using mindfulness to assess your emotional state and nonverbal cues. Read Improving Family Relationships with Emotional Intelligence for more strategies.

Change your focus

Be willing to acknowledge your family member’s strengths as well as their flaws. Perhaps your sibling is confrontational and demanding, but at least they’re always willing to help finance family events. Or maybe your mother-in-law is overly critical of you but always supportive of your children.

Practice empathy

Acknowledge that a difficult family member might be going through rough circumstances of their own. From personal insecurities to substance addiction or mental illness, certain underlying factors could be fueling your family member’s behavior.

Although these factors don’t excuse the behavior, by being more empathetic you might gain a better understanding of the person and why they act the way they do.

Use conflict resolution skills

Conflict resolution skills can come in handy anytime you’re dealing with family drama. These skills involve managing stress in the moment , being aware of both your own emotions and the other person’s, and prioritizing resolution over winning the argument.

You might notice that an aging parent is lashing out due to a feeling of declining independence. A deescalating step might be to ask them to do you a favor or give them a task that allows them to feel needed.

[Read: Conflict Resolution Skills]

Limit expectations and practice acceptance

Make peace with the fact that some people have viewpoints or priorities that may never match your own. Your adult children, siblings, or parents will do what they feel is right for them, and you can’t control their behavior. Try to treasure the relationship for what it is, or focus on other relationships that bring you joy.

At what point is a dysfunctional family relationship no longer worth saving? That may depend on different factors.

What’s the potential for change? The other person must be willing to acknowledge the problem and work to change. Some people don’t want to change, and you can’t control their behavior. If you’re dealing with a narcissistic family member , their inflated self-image, lack of empathy, and manipulative ways can hinder any meaningful progress.

How severe is the conflict? In cases of abuse , it’s usually advisable to cut ties with the family member. Remember that abuse doesn’t necessarily have to be physical. People who subject you to verbal, emotional, or psychological abuse can also harm your sense of well-being. This could include a father-in-law who aims to humiliate you or siblings who use guilt-tripping to manipulate you.

Dealing with doubts

Cutting ties means ending contact with the difficult family member, which is not always easy. You might repeatedly question your decision or have a hard time accepting that the relationship is unsalvageable.

Keep a list of specific reasons why you’ve decided to end contact. Did the person cross your boundaries too many times? Did the stress of your interactions negatively affect other areas of your life? Write it all down, so you don’t forget.

How to deal with the grief of ending a relationship

Depending on how close you were to the family member, you may need to take time to grieve the loss of the relationship.

Rather than suppress your feelings, identify and acknowledge them. It’s normal to experience anything from anger to sadness to guilt following the end of a relationship. You should also expect grief to intensify on days that remind you of the family member, such as birthdays or holidays.

Talk to friends and other family members about the situation. Now is a good time to reach out for support. Tell the supportive people in your life what you need from them. You might even strengthen bonds with other family members.

Maintain your hobbies and health. Continue to engage in activities you love, and look after your physical healthy by exercising regularly, getting enough sleep, and eating nutritious foods. Don’t use drugs or alcohol to cope with your negative feelings .

Moving forward

Over time, people’s behaviors and circumstances can change. So, know that cutting off ties doesn’t necessarily have to be permanent. If you see evidence that your family member is truly willing to make amends, there may be a chance of reconciliation.

Don’t rush reconciliation, though. You should both accept that the process may take time and requires concrete steps for improving the relationship. With a combination of patience and improved communication , you might be able to repair that broken bond and move forward with a healthier relationship.

More Information

• Help with Relationships - Articles addressing common relationship problems, such as arguments, conflict, and communication. (Relate UK)
• Buist, K. L., van Tergouw, M. S., Koot, H. M., & Branje, S. (2019). Longitudinal Linkages between Older and Younger Sibling Depressive Symptoms and Perceived Sibling Relationship Quality. Journal of Youth and Adolescence , 48(6), 1190–1202. Link
• Con, G., Suitor, J. J., Rurka, M., & Gilligan, M. (2019). Adult Children’s Perceptions of Maternal Favoritism During Caregiving: Comparisons Between Turkey and the United States. Research on Aging , 41(2), 139–163. Link
• Full-report-caregiving-in-the-united-states-01-21.pdf. (n.d.). Retrieved January 12, 2022, from Link
• Gilligan, M., Suitor, J., Nam, S., Routh, B., Rurka, M., & Con, G. (2017). Family Networks and Psychological Well-Being in Midlife. Social Sciences , 6(3), 94. Link
• Paradis, A. D., Reinherz, H. Z., Giaconia, R. M., Beardslee, W. R., Ward, K., & Fitzmaurice, G. M. (2009). Long-Term Impact of Family Arguments and Physical Violence on Adult Functioning at Age 30 Years: Findings From the Simmons Longitudinal Study. Journal of the American Academy of Child & Adolescent Psychiatry , 48(3), 290–298. Link
• Schoppe-Sullivan, S. J., Coleman, J., Wang, J., & Yan, J. J. (2021). Mothers’ attributions for estrangement from their adult children. Couple and Family Psychology: Research and Practice . Link
• Sechrist, J., Suitor, J. J., Vargas, N., & Pillemer, K. (2011). The Role of Perceived Religious Similarity in the Quality of Mother-child Relations in Later Life: Differences Within Families and Between Races. Research on Aging , 33(1), 3–27. Link
• Suitor, J. J., Gilligan, M., Johnson, K., & Pillemer, K. (2014). Caregiving, Perceptions of Maternal Favoritism, and Tension Among Siblings. The Gerontologist , 54(4), 580–588. Link
• Waldinger, R. J., Vaillant, G. E., & Orav, E. J. (2007). Childhood Sibling Relationships as a Predictor of Major Depression in Adulthood: A 30-Year Prospective Study. American Journal of Psychiatry , 164(6), 949–954. Link

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High-integrity Pueraria montana var. lobata genome and population analysis revealed the genetic diversity of Pueraria genus

Xuan-Zhao Huang, Shao-Da Gong and Xiao-hong Shang contributed equally to this work.

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Xuan-Zhao Huang, Shao-Da Gong, Xiao-hong Shang, Min Gao, Bo-Yuan Zhao, Liang Xiao, Ping-li Shi, Wen-dan Zeng, Sheng Cao, Zheng-dan Wu, Jia-Ming Song, Ling-Ling Chen, Hua-bing Yan, High-integrity Pueraria montana var. lobata genome and population analysis revealed the genetic diversity of Pueraria genus, DNA Research , Volume 31, Issue 3, June 2024, dsae017, https://doi.org/10.1093/dnares/dsae017

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Pueraria montana var. lobata ( P. lobata ) is a traditional medicinal plant belonging to the Pueraria genus of Fabaceae family. Pueraria montana var . thomsonii ( P. thomsonii ) and Pueraria montana var. montana ( P. montana ) are its related species. However, evolutionary history of the Pueraria genus is still largely unknown. Here, a high-integrity, chromosome-level genome of P. lobata and an improved genome of P. thomsonii were reported. It found evidence for an ancient whole-genome triplication and a recent whole-genome duplication shared with Fabaceae in three Pueraria species. Population genomics of 121 Pueraria accessions demonstrated that P. lobata populations had substantially higher genetic diversity, and P. thomsonii was probably derived from P. lobata by domestication as a subspecies. Selection sweep analysis identified candidate genes in P. thomsonii populations associated with the synthesis of auxin and gibberellin, which potentially play a role in the expansion and starch accumulation of tubers in P. thomsonii . Overall, the findings provide new insights into the evolutionary and domestication history of the Pueraria genome and offer a valuable genomic resource for the genetic improvement of these species.

Pueraria (2 n  = 2 x  = 22) is a genus of perennial vines in the Fabaceae family comprising more than 20 species native to Asia. Pueraria montana var. lobata ( P. lobata ) ( Fig. 1a ) with its related species, Pueraria montana var. thomsonii ( P. thomsonii ) and Pueraria montana var. montana ( P. montana ), are focal of the study in Pueraria. And their nutritional value, medicinal components, and morphological characteristics exhibited widely variations. 1 P. lobata and P. thomsonii are traditional Chinese medicinal materials with a long history of medicinal use in China, first recorded in the ‘Shen Nong’s Herbal Book’. Their roots are rich in puerarin, daidzein, genistein, and other flavonoids or isoflavone secondary metabolites. 2 , 3 The difference in morphological characteristics is that the roots of P. thomsonii are more expanded than those of P. lobata . However, P. montana is a variant with no expanded roots, exhibiting great difference with P. lobata and P. thomsonii ( Fig. 1b ). The root of P. montana does not contain puerarin, so it has low nutritional and medicinal value but strong resistance and can survive at low temperature. 4

Morphology and genome features of the P. lobata . (a) Morphological characteristics of P. lobata . (left, vines and leaves; middle, flower; right, root). (b) Evolutionary relationships of P. lobata , P. thomsonii , and P. montana with their divergence time (Mya, million years ago). (c) The landscape of genome features of P. lobata and P. thomsonii . (I) length of individual chromosomes; (II) GC contents; (III) repetitive sequences density; (IV) gene density; (V) DNA-Transposable elements density; (VI) long terminal repeat (LTR) density; (VII) inner lines indicate syntenic blocks.

P. montana could be differentiated from P. thomsonii and P. lobata based on significant differences in root morphology and nutrient content. However, it is challenging to distinguish P. thomsonii and P. lobata by traditional morphological characteristics or nutrient content. 5 , 6 The need for a precise classification of P. thomsonii and P. lobata significantly limits their potential value in medicine and nutrition. 7 In the past, DNA molecular marker technology and chloroplast genomic information have aided in classifying and utilizing Pueraria species, especially in distinguishing between P. thomsonii and P. lobata . 8–10 However, genome information has more significant advantages for addressing these issues, and high-quality genome assembly will provide the basis for detecting genomic variation and exploring evolutionary history. Advances in sequencing technology and reduced costs have enabled large-scale genome sequencing of plant populations, promoting plant research significantly. 11 , 12 Population genomic information can reveal populations’ genetic composition and diversity, effectively solve the challenging problem of classifying closely related species, better elucidate the evolutionary relationships among different subgroups and individuals, and provide critical evidence for species’ domestication and origin history. 13–15 Currently, research on the genomics and population genetics of Pueraria species needs to be developed more. Therefore, integrating these approaches to achieve a more precise classification of Pueraria species and exploit their potential genetic resources is of great significance.

The high-quality genomes of P. thomsonii and P. montana at the chromosome level were obtained in the previous study, and multi-omics analysis was used to comprehensively explore the biosynthetic pathways of critical secondary metabolites, such as isoflavones and puerarin in P. thomsonii . 4 , 16 Additionally, a comparison of gene families between P. thomsonii and P. montana was conducted to elucidate the underlying reasons behind distinct metabolic and cold-adaptation characteristics exhibited by these two species. 4 However, the more comprehensive comparative analysis of the genomes, phylogeny, and population genetics among the three Pueraria species has yet to be elucidated.

In this study, a high-quality chromosome-level genome of P. lobata was constructed using a combination of PacBio reads, paired-end reads, ONT reads, and Hi–C data. In addition, it generated an updated genome of P. thomsonii by removing the redundant haploid contigs. Whole-genome duplication (WGD) events, gene family expansion, and contraction occurring in Pueraria plants were explored through comparative genomics analysis. Whole-genome sequencing of 121 Pueraria accessions was used to address the evolutionary relationship among the species and identify selective signatures during domestication in P. thomsonii population. These results provide novel insights into the evolutionary history of the Pueraria genome and offer comprehensive information for breeding in the future.

Sample preparation and sequencing

The P. lobata accession ‘YG-19’ was selected for genome sequencing, having been grown in Luojiao Village, Guiping City, Guangxi Province. Genomic DNA was isolated from young leaves using a standard CTAB protocol and its integrity was verified by agarose gel electrophoresis. The genome sequencing was performed using Single-molecule real-time (SMRT) PacBio sequencing libraries, prepared using the SMRTbell Express Template Prep Kit 2.0 by Pacific Bioscience recommendation. The resulting libraries were sequenced on a PacBio Sequel II platform. Additionally, paired-end reads sequencing was performed using libraries selected for PE150 and sequenced using a BGIseq 500 sequencer. For ONT and Hi–C sequencing, the ONT and Hi–C libraries were prepared following the manufacturer’s instructions and the genome was sequenced on the Nanopore PromethION and BGI MGISEQ-2000 using standard protocols.

Genome assembly and quality assessment

For the P. lobata genome, a de novo assembly strategy was adopted. Short-read paired-end sequencing reads were used to count the total number and frequency of k-mer ( k  = 17) using Jellyfish software (v2.2.9), 17 and then Genomescope (v1.0) 18 was used to predict genomic features. Pacbio long reads were preliminarily corrected and assembled with NextDenovo (v2.5.0,  https://github.com/Nextomics/NextDenovo ), and both long reads and short reads were used to polish the resulting contig using NextPolish (v1.4.0). 19 We used 3D-DNA pipeline 20 to correct the resulting contigs with the Hi–C data, and then the PurgeHaplotigs software (v1.1.2) 21 was used to remove the redundant contigs. The final draft genome was assembled into scaffolds with Hi–C data using Juicer 22 and 3D-DNA pipeline. 20 These scaffolds were then manually curated using Juicebox. 23 Genomic sequence gaps were filled using TGS-gapcloser (v1.1.1) 24 and LR-gapcloser 25 in combination with ONT ultra-long reads (> 10 kb). Finally, Racon (v1.5.0) 26 with Pacbio reads and Pilon (v1.23) 27 with BGI short-reads were used to do a final error correction of the genomic gaps on the padding.

The quality of the P. thomsonii genome was improved by removing redundant sequences resulting from the high heterozygosity. The genome file was obtained from a previous study, 16 and genome size and heterozygosity were estimated by using the same process as applied to P. lobata genome. Redundant sequences were removed using Purge_Dups software (v1.2.5). 28 Finally, this updated version P. thomsonii genome was employed for subsequent analyses and evaluations.

The genome completeness was evaluated using BUSCO (v5.3.0) which contained 2,326 genes in the eudicots_odb10 database. 29 Short reads were mapped with BWA software (v0.7.17), 30 Pacbio long reads and ONT reads with minimap2 31 to assess the accuracy of the assembled genome. Picard software (v2.27.1) ( https://broadinstitute.github.io/picard ) was used to remove PCR duplicates in the short-read alignment, and BCFtools commands mpileup and call (v1.9) 32 were then used for SNV calling.

Genome annotation

The repetitive sequences in the P. lobata and P. thomsonii genomes were identified by using a combination of homologous similarity and de novo prediction. In the homology-based annotation step, repetitive sequences were predicted using RepeatMasker (v4.0.9) 33 and RepeatProteinMasker (v4.0.9) by searching against the RepBase library ( http://www.girinst.org/repbase ). During the de novo step, de novo repeat libraries were constructed based on the genome sequences using the de novo prediction program RepeatModeler (v1.0.11, http://www.repeatmasker.org/RepeatModeler/ ). Subsequently, the de novo repeat library was used to identify repetitive sequences using RepeatMasker (v4.0.9). We then combined all the repeat prediction results to remove redundancy and obtain the final set of the genome repeat sequences. Additionally, tandem repeats in the genome were identified using Tandem Repeats Finder ( http://tandem.bu.edu/trf/trf.html ). Three methods were used to predict protein-coding genes in the genomes of P. lobata and P. thomsonii , including homology-based prediction, de novo prediction, and transcriptomes data prediction. AUGUSTUS (v3.3.2), 34 Genscan (v1.0), 35 and GlimmmerHMM (v3.0.4) 36 were used to perform de novo gene prediction. The protein sequences of six species ( Medicago sativa , Oryza sativa , Melilotus albus , Medicago truncatula , Glycine max , and Arabidopsis thaliana ) were aligned to our genomes for homology-based gene prediction, and the structure of coding genes was predicted using Exonerate (v2.4.0). 37 The RNA sequencing reads were assembled using HISAT (v2.1.0) 38 and StringTie (v2.1.4), 39 and then TransDecoder ( https://github.com/TransDecoder ) were used for gene prediction. The results of the three methods are integrated and filtered to form a non-redundant, more complete gene set using MAKER (v2.31.10). 40

To predict gene functions, protein-coding genes to different protein databases, such as NR, UniProt, and Pfam, using BLASTP (with an E-value threshold of 1e-5) (v2.12.0+) 41 were mapped based on sequence similarity. We performed KEGG annotation using KOBAS (v3.0), 42 and extracted Gene Ontology information from the respective UniProt descriptions. Next, InterProScan (5.52-86.0) 43 was used to search the InterPro database and obtain the proteins’ conserved sequences, motifs, and structural domains.

Comparative genomics analysis

Orthofinder (v2.5.4, -S blast) 44 was used to detect gene families of P. lobata , P. thomsonii , P. montana , as well as the selected 12 species, including eight Fabaceae species outside the Pueraria genus ( A. duranensis , C. cajan , C. arietinum , G. max , M. sativa , P. vulgaris , M. truncatula , and P. sativum ), three non-Fabaceae dicotyledons ( V. vinifera , A. thaliana , and P. trichocarpa ) and one monocotyledon ( O. sativa ). Multiple sequence alignments were performed on the single-copy genes of 15 species using Muscle (v3.8.1). 45 The phylogenetic tree was then reconstructed using the maximum likelihood method with RAxML (v8.2.12). 46 The protein sequence alignment was converted to codon alignment with PAL2NAL ( http://www.bork.embl.de/pal2nal/ ). The MCMCTree program from the PAML package was used to estimate the species divergence times based on the TimeTree database. 47 Gene family expansions and contractions were analyzed using CAFE5 48 with default settings based on the identified phylogenetic tree and gene family statistics. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of expanding gene families were performed using the R package clusterProfiler (v4.2.2, p  < 0.05, q  < 0.2). 49 We used the python version of MCScan (v20101014) 50 to identify syntenic blocks among P. lobata , P. thomsonii , and P. montana .

Analysis of WGD events

The paralogs and one-to-one orthologs from G. max , 51 V. vinifera , 51 P. thomsonii , P. lobata , and P. montana 4 were performed all-versus-all BLASTP (v2.12.0+) similarity searches with an E-value threshold of 1e−5. WGDI (v0.6.0) 52 was used to identify syntenic blocks and calculate synonymous substitutions rate (Ks) with default parameters based on the result of alignment within or between the selected species and corresponding genome annotation. The syntenic blocks of paralogs or one-to-one orthologs and the distribution of Ks values were used to determine WGD events.

Re-sequencing and variant calling

Young leaves of 110 accessions with P. thomsonii and P. lobata were individually harvested, and genomic DNA was extracted. DNA libraries construction and re-sequencing were performed with DNBSEQ workflow (BGI), generating 5.56 Tb reads with 150-bp paired-end. All Pueraria accessions re-sequenced in this study were identified, collected, and deposited in the Guangxi Academy of Agricultural Sciences, Nanning, China. Additionally, the genome sequencing data of 11 P. montana accessions were downloaded from our previous study. 4 Raw re-sequenced data was filtered by SOAPnuke software 53 with the following parameters: ‘-n 0.01 -l 20 -q 0.3 --adaMR 0.25 --ada_trim --polyX 50 --minReadLen 150’. The clean reads were mapped to the P. lobata genome by BWA with default parameters. Samtools (v1.15.1) was used to sort the alignment results and convert them into BAM files, and PCR duplicates were marked with Picard. Variant detection was performed by GATK (v3.8-0-ge9d8) 54 following the prescribed procedures for variation disclosure. GATK IndelRealigner locally realigned BAM files to eliminate mismatches around small-scale deletions and insertions. The genome Variant Call Formats (gVCFs) for each accession were generated by GATK HaplotypeCaller, and all gVCF files were merged to generate the VCF file of all accessions using GATK CombineGVCFs and GenotypeGVCFs. Furthermore, the hard filter was performed to raw variants using GATK VariantFiltration with following parameters: for SNPs, ‘QUAL < 30.0 || QD < 2.0 || MQ < 40.0 || FS > 60.0 || SOR > 3.0 || MQRankSum < -12.5 || ReadPosRankSum < -8.0’; for InDels, ‘QUAL < 30.0 || QD < 2.0 || ReadPosRankSum < -20.0 || InbreedingCoeff < -0.8 || FS > 200.0 || SOR > 10.0’. The SNPs and InDels of filtered variants were selected to screen further using parameters of ‘--maf 0.05 --max-missing 0.9 --max-alleles 2’ with VCFtools (v0.1.16), 55 generating a high-confidence SNPs and InDels set with biallelic, respectively. For InDels, only those with a length of less than 50 bp will be retained. The identified variants were annotated using SnpEff (v5.1d) 56 with P. lobata genome and its gene annotation file. SNPs and InDels were categorized based on their chromosome position and effects.

Population genetic analysis

Based on the high-confidence SNPs set, we implemented LD pruning with PLINK (v1.90b6.21) 57 option ‘--indep-pairwise 50 5 0.2’, generating a core set of 1,061,987 SNPs for population genetic analyses. The maximum-likelihood tree was constructed using IQ-TREE (v2.2.0.3), 58 based on the best model (TVM + F + I + R8) determined by the Bayesian information criterion, and the format conversion of the input file was performed using vcf2phlip (v2.8) ( https://github.com/edgardomortiz/vcf2phylip ). Bootstrap support values were calculated using the ultrafast bootstrap approach (UFboot) with 1,000 replicates. The closely related species G. max was used as an outgroup downloaded from a previous study. 59 The phylogenetic tree was visualized by iTOL ( https://itol.embl.de ). The genetic ancestry was examined using ADMIXTURE (v1.3.0) 60 with K values (the putative number of population) from 2 to 10, and the cross-validation (CV) was set to 5-fold. Even though the cross-validation (CV) error gradually decreased from K  = 2 to 9, we chose K  = 4 to divide groups or subgroups, rather than K  = 9 with the minimum CV error. The reasons are as follows: (1) from K  = 4 on, the CV error decreases (or increases) at a slower rate and falls within the narrow range of 0.31006 to 0.31749; (2) at K  = 4, the corresponding ancestries are enough to categorize most P. montana , P. lobata , and P. thomsonii accessions into distinct groups or subgroups. Principal component analysis (PCA) was performed using GCTA (v1.93.2beta). 61 Considering the differences in genetic structure caused by the diversity of P. lobata accessions, the top three principal components were used to clearly distinguish the different groups or subgroups. Based on the population structure analyses mentioned above, 38 ungrouped accessions were removed from subsequent analyses. Additionally, the GMM93 ( P. montana ) accession within the subgroup G3-1 was suspected to be mis-identified and excluded from subsequent analysis. The squared correlation coefficient ( r 2 ) between pairwise SNPs in subgroups G3-1 and G3-2 was calculated to estimate the LD decay using PopLDdecay (v3.42). 62 Nucleotide diversity ( π ) and fixation index ( F ST ) of different populations were calculated by VCFtools with 50 kb windows sliding in 20 kb steps; Similarly, Tajima’s D value was calculated with 50 kb windows, and the statistical significance between subgroup G3-1 and G3-2 was compared using the two-sided Wilcoxon rank-sum test.

Identification of selective sweeps

Two statistical methods were employed to identify candidate genomic regions potentially affected by selection based on the high-confidence SNPs set. The cross-population composite likelihood ratio test (XP-CLR, https://github.com/hardingnj/xpclr ) was performed in subgroups G3-1 and G3-2 with 50 kb windows sliding in 20 kb steps. The windows with the top 5% XP-CLR score were taken as outliers. Based on the nucleotide diversity ( π ) of subgroups G3-1 and G3-2 calculated above, the statistic π (G3-2/G3-1) was then calculated concerning subgroups G3-1 and G3-2. An abnormally low value (5% outliers) suggests selection in subgroup G3-2, and the top value (5% outliers) indicates selection in subgroup G3-1. The overlapping regions with the top 5% XP-CLR score and low or top 5% π (G3-2/G3-1) value were assigned to candidate selective regions. Adjacent putative regions were merged into a single region to represent the effect of a single selective sweep. Haplotype differentiation patterns of gene loci were visualized by RectChr (v1.36, https://github.com/BGI-shenzhen/RectChr ).

Genome sequencing, assembly, and annotation

Multiple sequencing datasets were used to assemble the genome of P. lobata ( Fig. 1a ). First, k-mer analysis ( k  = 17) revealed an estimated genome size of 1.06 Gb using 144.68 Gb (136 × coverage) of paired-end reads ( Supplementary Fig. S1 , Supplementary Table S1 ). Pacbio sequencing (182.63 Gb, 172 × coverage) was used for the initial contig assembly, followed by polishing and quality improvement of the resulting sequences ( Supplementary Table S1 ). Given the high heterozygosity in specific genomic regions, this may lead to the assembly of regional duplication. We further improved the assembly by removing redundant contigs, resulting in the removal of 193 Mb of sequences from the initial 1.21 Gb assembly ( Supplementary Table S2 ). The contigs were then grouped, sorted, and oriented using Hi–C interaction datasets (152.41 Gb, 144 × coverage) to achieve a chromosome-level assembly ( Supplementary Table S1 ). To enhance the continuity and completeness of the P. lobata genome, we used ONT ultra-long reads (82 Gb, 77 × coverage) with N50 of 36.56 kb to fill gaps in the genome ( Supplementary Table S1 ). As a result, we obtained a relatively complete genome of P. lobata , with a size of 1.05 Gb, and 91.69% of the sequences were anchored to 11 chromosomes, including 7 gap-free chromosomes, and the scaffold N50 was 86.86 Mb ( Fig. 1c , Supplementary Fig. S2,-S3 , Supplementary Table S3 ). Additionally, we performed a redundancy removal process on the previously published P. thomsonii genome, resulting in a new version of the genome with a size of 1.03 Gb and scaffold N50 was 98.03 Mb ( Fig. 1c , Supplementary Table S4 ).

The quality of de novo assembled P. lobata genome and the updated P. thomsonii genome were evaluated by using multiple methods. Accuracy of the two genomes was demonstrated by high mapping rates obtained from different sequencing data sets, including PacBio long reads, short paired-end reads, and ONT reads. The mapping rates for paired-end reads of P. lobata and P. thomsonii were 99.35% and 99.16%, respectively, and homozygous single-nucleotide variations (SNVs) accounted for approximately 0.0019% and 0.0057% of the two genomes ( Supplementary Table S5 ). Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis estimated the completeness of the P. lobata and P. thomsonii genomes to be 99.0% (2,303 out of 2,326) and 98.5% (2,291 out of 2,326), respectively, indicating the high completeness of our genomes ( Supplementary Table S6 ).

Subsequently, repetitive sequence elements, protein-coding genes, and non-coding RNAs of both genomes were identified. It predicted 679.32 Mb (64.7%) and 651.91 Mb (62.9%) of repetitive sequences from P. lobata and P. thomsonii assemblies, respectively ( Supplementary Table S7 ), which is consistent with previous reports. 16 In P. lobata genome, Long Terminal Repeats (LTRs) were the most abundant repetitive elements (17.2%), followed by DNA transposable elements (3.67%) and LINEs (3.35%). Among the LTRs, Gypsy and Copia accounted for 9.91% and 6.84%, respectively. In P. thomsonii genome, LTRs (14.3%), LINEs (5.02%), and DNA transposable elements (3.42%) were the most abundant repetitive sequences, with Gypsy (6.37%) and Copia (7.41%) being the best represented among the LTRs.

Using homology analysis, de novo prediction, and transcriptome evidence, it annotated the protein-coding genes of P. lobata and P. thomsonii after masking repetitive sequences. It identified 38,386 genes in P. lobata genome, with an average gene length of 5,312 bp and average coding DNA sequences (CDS) length of 1,274 bp, and predicted 38,891 genes in P. thomsonii genome, with an average gene length of 4,477 bp and an average CDS length of 1,254 bp ( Supplementary Table S8 ). We further compared the number of genes, gene length, and CDS length among three Pueraria species ( P. lobata , P. thomsonii , and P. montana ) and Glycine max . The gene number of three Pueraria species was found to be similar, while P. lobata exhibited a more significant average gene length and average CDS length compared to the other three species ( Supplementary Table S8 ).

Compared to public databases, including Interpro, Pfam, GO, Uniprot, Pathway, and KEGG, approximately 97.27% (37,339) and 97.38% (37,873) of these genes were functionally annotated in P. lobata and P. thomsonii genome, respectively ( Supplementary Table S9 ). 3,432 and 3,072 non-coding RNAs were also identified, including microRNAs, transfer RNAs, ribosomal RNAs, and small nuclear RNAs ( Supplementary Table S10 ).

Comparative genomic and evolutionary analysis

To explore the genomic evolution of Pueraria , we clustered genes from the three Pueraria species ( P. lobata , P. thomsonii , and P. montana ), eight Fabaceae species outside the Pueraria genus ( A. duranensis , C. cajan , C. arietinum , G. max , M. sativa , P. vulgaris , M. truncatula , and P. sativum ), and other four representative species, including three non-Fabaceae dicotyledons ( V. vinifera , A. thaliana , and P. trichocarpa ) and one monocotyledon ( O. sativa ) ( Fig. 2a ). In total, we identified 35,121 gene families, with 17,416, 17,487, and 17,037 families detected in P. lobata , P. thomsonii , and P. montana , respectively ( Supplementary Table S11 ).

Genome comparison and evolution analysis. (a) Gene numbers of each category in 15 representative species. (b) Venn diagram showing the shared and unique gene families among P. lobata, P. thomsonii , P. montana , and G. max . (c) Phylogenomic analysis and expansion/contraction of the gene family. The numbers on the nodes represent the species divergence time with the confidence range list in brackets. (d) Genomic collinearity between three Pueraria crops. (e) Distribution of synonymous substitutions (Ks) values of syntenic paralogs in five selected species. Estimated whole-genome duplication (WGD) and whole-genome triplication (WGT) events occurring in Pueraria were highlighted.

The genes of three Pueraria species re-clustered by using G. max as the outgroup. These four species shared 18,203 gene families, while P. lobata , P. thomsonii , and P. montana shared 19,470 gene families, which can be considered a conservative gene set for the Pueraria species ( Fig. 2b ). It found 237 and 324 unique gene families in the genomes of P. lobata and P. thomsonii , including 1,074 genes and 1,286 genes respectively, which were significantly less than that (1,094 unique gene families; 3,954 genes) in P. montana genome ( Fig. 2b ). Importantly, P. lobata shared the majority gene families with P. thomsonii , indicating their closer evolutionary relationship.

Single-copy gene families obtained from 15 representative plant genomes were used to reconstruct a phylogenetic tree and estimate divergence times ( Fig. 2c ). The results supported a close evolutionary relationship among three Pueraria crops. Specifically, our phylogenetic analysis shows that P. lobata and P. thomsonii have the closest relationship, with a divergence time of 1.1 Mya. The common ancestor of P. lobata and P. thomsonii diverged from P. montana approximately 5.8 Mya. Moreover, the estimated divergence time between Pueraria species and G. max was 15.3 Mya. These findings provide valuable insights into the evolutionary history of Pueraria genus and its relationship with other plant species.

Gene family expansion and contraction were investigated in 15 representative plants ( Fig. 2c ). There were 800/624, 675/819, and 915/1133 expanded/contracted gene families in P. lobata , P. thomsonii , and P. montana genome, respectively. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses on the expanded gene families of each Pueraria species were conducted ( Supplementary Fig. S4 ). GO enrichment analysis indicated that the expanded gene families of P. lobata and P. thomsonii are related to stress responses, such as ‘response to oxidative stress’, ‘cellular response to salt stress’, and ‘response to herbicide’. This result suggests that P. lobata and P. thomsonii may be more capable of adapting to diverse environmental conditions. KEGG enrichment analysis shows that the expanded genes of P. lobata are involved in ‘Photosynthesis’, ‘Oxidative phosphorylation’, and ‘Ribosome’. Additionally, it was found that ‘Sesquiterpenoid and triterpenoid biosynthesis’ and ‘Quorum sensing’ are the most enriched terms of P. thomsonii and P. montana , respectively. Overall, the expansion of distinct gene families may have driven the observed differentiation among three Pueraria species. We also observed a significant expansion of gene families related to ‘Isoflavones biosynthesis’ and ‘Flavones and flavonols biosynthesis’ in the common ancestor of P. lobata and P. thomsonii ( Supplementary Fig. S5 ). In contrast, it does not exist in P. montana . This result indicates the potential role of these expanded gene families in enhancing the medicinal properties of Pueraria species.

Syntenic analysis and whole-genome duplication

We conducted genome comparisons among P. lobata , P. thomsonii , and P. montana , and identified syntenic blocks that are distributed across 11 chromosomes, indicating a strong interspecies synteny ( Fig. 2d ). A total of 500 syntenic blocks comprising 27,295 gene pairs were identified between P. lobata and P. thomsonii , of which 309 blocks containing 25,851 gene pairs were located on the same chromosome. Furthermore, it observed 361 syntenic blocks with 23,285 gene pairs shared between P. lobata and P. montana , with 231 blocks containing 18,083 gene pairs located on the same chromosome ( Supplementary Table S12 ). The largest block with the highest number of genes between P. lobata and P. thomsonii was located at the end of chromosome 9 and contained 951 pairs of orthologous genes, covering 26.7 Mb and 26.9 Mb of genomic regions on the P. lobata and P. thomsonii genomes, respectively. Meanwhile, 425 syntenic blocks containing 23,266 gene pairs were detected between P. thomsonii and P. montana , with 17,789 gene pairs located on the same chromosome ( Supplementary Table S12 ). High chromosomal relatedness was observed among the three Pueraria genomes, with an almost one-to-one synteny relationship between P. lobata and P. thomsonii , providing genomic evidence for the evolution of Pueraria species.

Two peaks of Ks values corresponding to two whole-genome duplication (WGD) events were detected in the Pueraria genus by analyzing synonymous substitutions (Ks). The first WGD event, represented by the ancient peak (Ks = 1.666–1.714), was consistent with the whole-genome triplication (γ event) in core eudicots, 63 as observed in V. vinifera (Ks = 1.240) and G. max (Ks = 1.738) ( Fig. 2e ). 64 , 65 The second WGD event, shared by Fabaceae, 65 is indicated by the recent peak (Ks = 0.563–0.572) ( Fig. 2e ). Syntenic blocks of paralogs with three Pueraria species indicate that the recent Ks peak was generated by a WGD event rather than segmental duplication ( Supplementary Fig. S6 ). Based on these results, we presume that the three Pueraria species did not undergo a lineage-specific WGD event.

To investigate the order of species differentiation, the syntenic blocks of orthologs and Ks values for two pairs of three Pueraria species were identified. We note that the Ks peak of P. thomsonii versus P. lobata (Ks = 0.004) is significantly lower than that in P. thomsonii versus P. montana (Ks = 0.043) or P. lobata versus P. montana (Ks = 0.041) ( Supplementary Fig. S7 ). According to the difference of Ks peak, it speculates that P. lobata and P. thomsonii are more closely related, which is also confirmed by phylogenetic tree ( Fig. 2c ).

Genomic polymorphism and population structure

To investigate genomic polymorphisms in three Pueraria species, a total of 121 Pueraria accessions were collected in this study, including 64 P. thomsonii and 46 P. lobata accessions with an average depth of 48×, 11 P. montana accessions from our previous study with an average depth of 28 × ( Supplementary Table S13 ). The P. thomsonii and P. lobata accessions sequenced in this study are mostly distributed in southern China, with over half of the accessions from Guangxi province and the remaining accessions mainly from Guangdong, Jiangxi, and Yunnan provinces ( Supplementary Fig. S8 ). All sequencing reads were mapped to P. lobata genome, and all mapping rates ranged from 96.07% to 99.20%, leading to the identification and annotation of 14,132,140 high-confidence single-nucleotide polymorphisms (SNPs) and 1,799,556 insertions/deletions (InDels) ( Supplementary Table S13 ). Of these, 577,166 SNPs (2.71%) and 26,355 InDels (0.90%) were in coding regions, with 308,061 nonsynonymous SNPs and 14,573 frameshift InDels that could potentially cause significant changes in protein sequences ( Supplementary Table S14–S15 ). Most of SNPs were found in intergenic regions (52.91%), followed by upstream (17.20%), downstream (16.25%), and intronic regions (9.36%).

We aimed to determine the evolutionary relationships among the three Pueraria species by examining their population genetics. To this end, we explored the phylogenetic relationships and population structure based on a core dataset of SNPs (Method). It conducted a phylogenetic tree and found that the 121 Pueraria accessions could be divided into three clades ( Fig. 3a ). Clade1 comprises nine P. montana accessions, representing the P. montana population. Clade2 and Clade3 harbor most P. lobata and P. thomsonii accessions, standing for the P. lobata and P. thomsonii populations ( Supplementary Table S13 ). Combining the results of estimated ancestral component and principal component analysis (PCA), G1 possesses a significant evolutionary distance from both G2 and G3 (Clade3) ( Fig. 3b , Supplementary Fig. S9 ). Notably, eight P. lobata accessions in G2 differ from those in G3 (Clade3), as revealed by principal components 2 (PC2) and 3 (PC3), suggesting an earlier divergence of G2 ( Fig. 3a–c , Supplementary Fig. S9 ). As the K value increased from 3 to 9, G3 (Clade3) could be further subdivided into two subgroups and 36 ungrouped accessions, which aligns with the optimal K value ( K  = 4) we have chosen ( Fig. 3b , Supplementary Fig. S10 ). The classification criterion of the subgroup is as follows: (i) Any individual with a major ancestry component (> 70%) will be categorized into the corresponding subgroup; (ii) Subgroups must constitute a monophyletic branch in the phylogenetic tree. Subgroup G3-1 was predominantly composed of P. lobata accessions, with origins from Guangxi and Yunnan provinces ( Supplementary Table S13 ). The ungrouped accessions in G3 exhibit more admixture and relatively scattered PCs ( Fig. 3b–c , Supplementary Fig. S9 , S 11 ), likely resulting from wide crossing or wild introgression during domestication and cultivar development involving several related species. 66 Subgroup G3-2 includes most P. thomsonii accessions whose genetic structure demonstrates a remarkable similarity in all the analyses conducted, which is substantially different from the situation observed in other groups or subgroups ( Fig. 3a-c , Supplementary Fig. S9 , S 11 ). In summary, our results suggest that P. thomsonii (G3-2) was derived from P. lobata as a subspecies.

Phylogeny, population structure and genomic diversity of Pueraria accessions. (a) Maximum likelihood phylogenetic tree of 121 Pueraria accessions, using G. max as outgroup. The color of the branches represents different groups or subgroups. (b) Model-based clustering analysis with different numbers of groups or subgroups. Each vertical bar represents one individual, and colored segments represent the proportions of ancestral components. (c) PCA plot with the first two principal components. Colors of different groups or subgroups correspond to those in the phylogenetic tree. The more detailed principal components and quantities of G1 and subgroup G3-2 were shown in the zoomed-in view, respectively. (d) Nucleotide diversity (π) and fixation index ( F ST ) across the four groups and subgroups. Values in circles represent measures of π for the groups or subgroups, and values between pairs indicate F ST value.

Genomic diversity and selection signatures during domestication

Nucleotide diversity ( π ) and fixation indexes ( F ST ) were estimated to compare genome-wide genetic diversity among the above four major groups and subgroups. Despite having a larger accession size, subgroup G3-2 exhibited significantly lower nucleotide diversity ( π =1.79 × 10 −4 ) than subgroup G3-1 (π=2.45 × 10 −4 ) ( Fig. 3d ). This finding is likely due to that the accessions in subgroup G3-1 were mainly from wild populations, while those in subgroup G3-2 were mostly from landraces or cultivars ( Supplementary Table S13 ). The decrease in nucleotide diversity in subgroup G3-2 suggests that it may has undergone more artificial selection. The level of genetic differentiation between subgroup G3-1 and G2 is the lowest ( F ST  = 0.2939), followed by that between subgroup G3-1 and G3-2 ( F ST  = 0.3064), with the remaining levels of genetic differentiation among the other groups or subgroups being significantly higher ( Fig. 3d ). A significant proportion of SNPs (83.4%) identified in subgroup G3-2 are shared with subgroup G3-1, indicating that subgroup G3-1 has served as a primary source of genetic material for subgroup G3-2, potentially explaining the low level of genetic differentiation between them ( Supplementary Fig. S12a ). Linkage disequilibrium (LD), as indicated by r 2 , was calculated to compare LD decay between subgroups G3-2 and G3-1. The result showed that the LD decay reached half its maximum average correlation coefficient at a shorter distance in subgroup G3-2 (0.15 kb) than in subgroup G3-1 (2.61 kb) ( Supplementary Fig. S12b ). This finding is consistent with previous studies on G. max or V. vinifera , where wild populations and cultivars exhibited similar results. 14 , 67 The faster LD decay observed in subgroup G3-2 implies that it may have experienced stronger selection, as supported by the greater Tajima’s D value of subgroup G3-2 ( Supplementary Fig. S12c ).

The most significant phenotypic difference between P. thomsonii and P. lobata is that the root tuber of P. thomsonii is larger and accumulates a higher content of starch, traits that were likely selected during domestication. 68 , 69 To identify potential selective signals associated with P. thomsonii domestication, the cross-population composite likelihood ratio test (XP-CLR) and nucleotide diversity ratio were performed by comparing subgroup G3-2 versus G3-1. Combining these approaches, we identified only five selected regions in subgroup G3-1, consistent with our hypothesis that it underwent relatively weak selection. In contrast, 533 selected regions were found in subgroup G3-2, covering 3.85% (40.41 Mb) of the P. lobata genome and harboring 1,774 genes ( Fig. 4a–c , Supplementary Table S16 ). Previous studies conducted by our team have elucidated the puerarin synthesis pathway specific to P. lobata and P. thomsonii . 16 Within the selected region, we discovered the PlChr10.CHS (PlobChr10G00353750) is situated in the puerarin synthesis pathway, potentially contributing to variations in puerarin content between P. lobata and P. thomsonii ( Fig. 4a , Supplementary Table S17 ). In addition, several genes related to plant hormones were detected in selected regions, including PlChr01.IAA (PlobChr1G00059530), PlChr01.GA2ox (PlobChr1G00059170), PlChr07.GH3s (PlobChr7G00257580 and PlobChr7G00273940) and PlChr08.YUC (PlobChr8G00206820) ( Fig. 4a–c , Supplementary Table S17 ). Previous research has demonstrated that genes associated with auxin are significant contributors to starch synthesis. Specifically, the YUC gene, responsible for auxin synthesis, considerably influences the transcriptional levels of three key genes involved in starch granule synthesis and affects the accumulation of starch granules within the root apex of A. thaliana . 70 Gibberellin regulates the ratio of xylem to phloem in vascular tissue, 71 and the abnormal vascular tissue, consisting primarily of xylem and phloem, is responsible for the expansion of tubers. 72 In addition, the differentiation patterns of haplotypes for PlChr01.GA2ox and PlChr08.YUC were investigated, and it was determined that they carried unique haplotypes in subgroups G3-2 and G3-1, respectively ( Fig. 4d–e ). In summary, it suggests that genes associated with the synthesis of auxin and gibberellin, which have undergone strong selective pressure, may have played a significant role in the domestication process of root expansion and high starch accumulation in P. thomsonii .

Identification of selective sweeps associated with domestication traits in P. thomsonii . (a) Manhattan plot of the selective sweeps identified from the comparison of subgroup G3-2 and G3-1 by XP-CLR. Dashed lines represent the top 5% of the XP-CLR scores. Functionally characterized candidate genes associated with plant development were highlighted. (b–c) Distribution of nucleotide diversity (π) ratio with the upstream and downstream regions of PlChr01.GA2ox and PlChr08.YUC . Horizontal dashed lines represent the bottom 5% of the π ratio. Vertical dashed lines indicate the position of PlChr01.GA2ox and PlChr08.YUC . (d–e) Haplotype distributions were shown for SNPs within PlChr01.GA2ox and PlChr08.YUC . Each column represents the SNPs of PlChr01.GA2ox and PlChr08.YUC . Each row indicates the accessions of subgroups G3-2 or G3-1. Four colors represent different types of SNP allele respectively.

Pueraria belongs to the Fabaceae family and is a plant with significant economic value widely cultivated throughout Asia. Traditional Pueraria categories need to be clarified for evolutionary studies and exploitation of medicinal usage, mainly because of a lack of genomic and population genetic information. In this study, based on ONT reads and PacBio long reads, we constructed a high-quality genome of P. lobata with some chromosomes without gaps. The continuity of the P. lobata genome was improved by filling gaps with ONT ultra-long reads, although the specific regions corresponding to telomeres and centromeres remain unidentified. Completing these regions would necessitate the utilization of high-fidelity (HiFi) reads with low error rates. 73–75 Through a comparison of the sizes of P. lobata genome, P. montana genome, 4 and the previous P. thomsonii genome, 16 we observed that the genome size of P. lobata (~1.05 Gb) is more closely related to that of P. montana (~978 Mb), while exhibiting a substantial difference from that of previous P. thomsonii (~1.38 Gb). Based on k-mer analysis ( k  = 17) with paired-end reads, the size and heterozygosity of the previous P. thomsonii genome were reevaluated to be 1.02 Gb and 1.25% ( Supplementary Fig. S13 ), respectively, which closely resemble those of P. lobata genome ( Supplementary Fig. S1 ). In addition, the result of BUSCO analysis shows that the completeness and duplication of the reference gene set in the previous P. thomsonii genome were 98.9% and 33.1% ( Supplementary Table S4 ), respectively. These results suggest that the previous P. thomsonii genome likely contains many redundant haploid contigs. This phenomenon could be attributed to the high levels of heterozygosity typical in the genomes of highly heterozygous species, such as lychee, 76 Medicago ruthenica , 77 and Cinnamomum camphora . 78 Therefore, we have excised the redundant regions from the previous P. thomsonii genome, leading to the generation of an updated genome. This improved genome provides a robust foundation for conducting more comprehensive investigations into P. thomsonii .

In the three Pueraria species, they all have a karyotype of 2 n  = 2 x  = 22. We observed significant genome syntenic relationships among P. lobata , P. thomsonii , and P. montana , indicating their high genetic relationship ( Fig. 2d ). This result suggests the possibility of extensive interspecific hybridization among Pueraria species. Enrichment analysis showed that gene families associated with stress responses were expanded in P. lobata and P. thomsonii . In contrast, changes in gene families associated with secondary metabolites such as isoflavonoids may have contributed to their different nutritional values. Numerous reports have been on the WGD events and evolutionary relationships of Fabaceae species; however, few researches have been conducted on Pueraria species. 65 , 79–81 In this study, we inferred that three Pueraria species collectively experienced two WGD events, with the most recent one being shared with Fabaceae plants. 82 Since then, none of these species has undergone separate WGD events. Previous studies have reported a recent WGD event in P. thomsonii (~4.8 Mya). 16 Nevertheless, such a recent WGD event could produce many collinearity blocks of paralogs, as seen in G. max , a closely related species to P. thomsonii . However, this was not observed in P. thomsonii genome ( Supplementary Fig. S14 ). 65 Therefore, it concludes that this event was likely due to segmental duplication rather than an authentic WGD event. A similar phenomenon has been observed in V. radiata . 79 Phylogenetic tree constructed using single-copy genes and Ks analysis based on orthologs also indicated that the three Pueraria species are closely related to G. max and belong to Papilionoideae ( Fig. 2c , Supplementary Fig. S7 ). 80 Among them, P. thomsonii and P. lobata exhibit a closer genetic relationship, consistent with their similar biological morphology and functions. Our results further contribute to the understanding of evolutionary relationships among Fabaceae species.

In addition, we first reported the characterization of genome-wide SNPs from 121 Pueraria accessions, which are mainly distributed in the south of China. Based on these SNPs, three Pueraria species populations were differentiated into three groups: G1, G2, and G3. Among them, G3 could be further divided into two subgroups. The subgroup G3-1 displayed greater population diversity than the subgroup G3-2, rendering it a valuable genetic resource for improving the P. thomsonii germplasm. Additionally, we found that the GMM93 ( P. montana ) accession was classified into subgroup G3-1 and exhibited a distant phylogenetic relationship with other P. montana accessions in both previous and current studies ( Fig. 3b–c ). 4 Given the current limitations of morphological-based identification of Pueraria species, we place greater confidence in the findings derived from genomics and population genetics analyses. Consequently, we infer that GMM93 is more likely to P. lobata rather than P. montana . Previous studies indicated that the three Pueraria species have a large mixed distribution in the southwestern of China, which may be the center of their origin. 83 Notably, most accessions in G1 and G2, located at the root of the phylogenetic tree, were collected from Yunnan and Guangxi provinces ( Supplementary Table S13 ). Thus, we speculate that the three Pueraria species may have originated from Yunnan and Guangxi provinces. The phylogenetic tree conducted with SNPs corroborated the close evolutionary relationship between P. thomsonii and P. lobata . Further combined with the differences in population diversity between subgroup G3-1 and G3-2, we suggest that P. thomsonii was likely domesticated from P. lobata as a subspecies. Even though our whole-genome SNP data could not able to display the whole scheme of P. thomsonii domestication history, it revealed some valuable details about the evolutionary relationship of three Pueraria species. This study offers a valuable genomic resource for the genetic improvement of Pueraria species.

This work was supported by the National Natural Science Foundation of China (32270712, 32100526, 82204563), Young Elite Scientists Sponsorship Program by CAST (2022QNRC001), the State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources (SKLCUSA-a202205), Chief Expert of Tuberous Crops Innovation Team in Guangxi Province (nycytxgxcxtd-2023-11-01), and Guangxi Science and Technology Major Program (GuikeAA23023035-6).

The authors declare no competing interests.

J.S., L.C., and H.Y. conceived and designed the study. X.S., L.X., P.S., W.Z., S.C., and Z.W. contributed to sample preparation. X.H., S.G., M.G., B.Z., and J.S. performed the bioinformatics analyses. X.H., S.G., X.S., J.S., H.Y., and L.C. wrote and revised the manuscript. All authors read and approved the final manuscript.

All data used in this study are publicly available. Whole genome sequencing data have been deposited in BioProject under accession numbers PRJCA016835 at https://ngdc.cncb.ac.cn/gwh .

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Conflict Management in Family Businesses

• First Online: 08 June 2024

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• Veland Ramadani   ORCID: orcid.org/0000-0002-8495-9141 5 ,
• Erick P. C. Chang 6 ,
• Ramo Palalić 7 &
• Esra Memili 8  

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Like every other business, a family firm is not safe from conflicts from within, whether created intentionally or unintentionally. Sometimes, the organizational design and/or organizational culture can cause conflicts that might result in a bad image of the whole organization. This chapter overviews the most critical elements in conflict management that can happen in family businesses as it happens in other organizations. The best practices and examples of how such conflicts are solved are provided in this content. The role of organizational culture, as well as the best approaches to resolving these issues, is elaborated. Other important issues related to conflict management that can be applied to family businesses are explored.

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Arkansas State University, Jonesboro, AR, USA

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Ramadani, V., Chang, E.P.C., Palalić, R., Memili, E. (2024). Conflict Management in Family Businesses. In: Entrepreneurial Family Businesses. Springer Texts in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-031-59261-4_7

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