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from Ridsdale; Practitioner, 238:108-13. 1994.

• Is the study relevant & important to our practice?
• Is the work useful & original? Does it add to the fund of useful knowledge?
• Was the study setting similar enough to our working environment that, assuming the results are valid, they may be extrapolated to our practice?
• Was the architecture or design of the study appropriate to answer the questions posed in the introduction?
• Is the connection between the hypothesis & the instruments used clearly justified?
• Is the relationship between outcomes & measures plausible?
• Are the instruments used appropriate to the study & have they been validated previously?
• Are the population & the population sample defined & recognisably similar to that seen in practice?
• Are the recruitment definitions & inclusion/exclusion criteria clearly stated?
• Is the sample size sufficient to answer the questions posed, & has there been an attempt to estimate the required numbers in advance?
• Is the response rate adequate? Are drop-outs well described, & is there any reason to think that they differ materially from responders?
• Are the tables & figures clear?
• Have stastistical tests been applied appropriately?
• Are p values or confidence intervals used?
• Where statistically significant differences are found, are they sufficient to be clinically important?
• Does the discussion show an awareness of the methodological limitations of the study design? Are problems or difficulties acknowledged?
• Are the conclusions drawn justified by the results presented?
• Is a comparison drawn with other published work?
• Do the authors speculate too far beyond the evidence presented?

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Full text is available as a scanned copy of the original print version. Get a printable copy (PDF file) of the complete article (890K), or click on a page image below to browse page by page. Links to PubMed are also available for Selected References .

Selected References

These references are in PubMed. This may not be the complete list of references from this article.

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Criteria for Good Qualitative Research: A Comprehensive Review

• Regular Article
• Open access
• Published: 18 September 2021
• Volume 31 , pages 679–689, ( 2022 )

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• Drishti Yadav   ORCID: orcid.org/0000-0002-2974-0323 1  

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This review aims to synthesize a published set of evaluative criteria for good qualitative research. The aim is to shed light on existing standards for assessing the rigor of qualitative research encompassing a range of epistemological and ontological standpoints. Using a systematic search strategy, published journal articles that deliberate criteria for rigorous research were identified. Then, references of relevant articles were surveyed to find noteworthy, distinct, and well-defined pointers to good qualitative research. This review presents an investigative assessment of the pivotal features in qualitative research that can permit the readers to pass judgment on its quality and to condemn it as good research when objectively and adequately utilized. Overall, this review underlines the crux of qualitative research and accentuates the necessity to evaluate such research by the very tenets of its being. It also offers some prospects and recommendations to improve the quality of qualitative research. Based on the findings of this review, it is concluded that quality criteria are the aftereffect of socio-institutional procedures and existing paradigmatic conducts. Owing to the paradigmatic diversity of qualitative research, a single and specific set of quality criteria is neither feasible nor anticipated. Since qualitative research is not a cohesive discipline, researchers need to educate and familiarize themselves with applicable norms and decisive factors to evaluate qualitative research from within its theoretical and methodological framework of origin.

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Introduction

“… It is important to regularly dialogue about what makes for good qualitative research” (Tracy, 2010 , p. 837)

To decide what represents good qualitative research is highly debatable. There are numerous methods that are contained within qualitative research and that are established on diverse philosophical perspectives. Bryman et al., ( 2008 , p. 262) suggest that “It is widely assumed that whereas quality criteria for quantitative research are well‐known and widely agreed, this is not the case for qualitative research.” Hence, the question “how to evaluate the quality of qualitative research” has been continuously debated. There are many areas of science and technology wherein these debates on the assessment of qualitative research have taken place. Examples include various areas of psychology: general psychology (Madill et al., 2000 ); counseling psychology (Morrow, 2005 ); and clinical psychology (Barker & Pistrang, 2005 ), and other disciplines of social sciences: social policy (Bryman et al., 2008 ); health research (Sparkes, 2001 ); business and management research (Johnson et al., 2006 ); information systems (Klein & Myers, 1999 ); and environmental studies (Reid & Gough, 2000 ). In the literature, these debates are enthused by the impression that the blanket application of criteria for good qualitative research developed around the positivist paradigm is improper. Such debates are based on the wide range of philosophical backgrounds within which qualitative research is conducted (e.g., Sandberg, 2000 ; Schwandt, 1996 ). The existence of methodological diversity led to the formulation of different sets of criteria applicable to qualitative research.

Among qualitative researchers, the dilemma of governing the measures to assess the quality of research is not a new phenomenon, especially when the virtuous triad of objectivity, reliability, and validity (Spencer et al., 2004 ) are not adequate. Occasionally, the criteria of quantitative research are used to evaluate qualitative research (Cohen & Crabtree, 2008 ; Lather, 2004 ). Indeed, Howe ( 2004 ) claims that the prevailing paradigm in educational research is scientifically based experimental research. Hypotheses and conjectures about the preeminence of quantitative research can weaken the worth and usefulness of qualitative research by neglecting the prominence of harmonizing match for purpose on research paradigm, the epistemological stance of the researcher, and the choice of methodology. Researchers have been reprimanded concerning this in “paradigmatic controversies, contradictions, and emerging confluences” (Lincoln & Guba, 2000 ).

In general, qualitative research tends to come from a very different paradigmatic stance and intrinsically demands distinctive and out-of-the-ordinary criteria for evaluating good research and varieties of research contributions that can be made. This review attempts to present a series of evaluative criteria for qualitative researchers, arguing that their choice of criteria needs to be compatible with the unique nature of the research in question (its methodology, aims, and assumptions). This review aims to assist researchers in identifying some of the indispensable features or markers of high-quality qualitative research. In a nutshell, the purpose of this systematic literature review is to analyze the existing knowledge on high-quality qualitative research and to verify the existence of research studies dealing with the critical assessment of qualitative research based on the concept of diverse paradigmatic stances. Contrary to the existing reviews, this review also suggests some critical directions to follow to improve the quality of qualitative research in different epistemological and ontological perspectives. This review is also intended to provide guidelines for the acceleration of future developments and dialogues among qualitative researchers in the context of assessing the qualitative research.

The rest of this review article is structured in the following fashion: Sect.  Methods describes the method followed for performing this review. Section Criteria for Evaluating Qualitative Studies provides a comprehensive description of the criteria for evaluating qualitative studies. This section is followed by a summary of the strategies to improve the quality of qualitative research in Sect.  Improving Quality: Strategies . Section  How to Assess the Quality of the Research Findings? provides details on how to assess the quality of the research findings. After that, some of the quality checklists (as tools to evaluate quality) are discussed in Sect.  Quality Checklists: Tools for Assessing the Quality . At last, the review ends with the concluding remarks presented in Sect.  Conclusions, Future Directions and Outlook . Some prospects in qualitative research for enhancing its quality and usefulness in the social and techno-scientific research community are also presented in Sect.  Conclusions, Future Directions and Outlook .

For this review, a comprehensive literature search was performed from many databases using generic search terms such as Qualitative Research , Criteria , etc . The following databases were chosen for the literature search based on the high number of results: IEEE Explore, ScienceDirect, PubMed, Google Scholar, and Web of Science. The following keywords (and their combinations using Boolean connectives OR/AND) were adopted for the literature search: qualitative research, criteria, quality, assessment, and validity. The synonyms for these keywords were collected and arranged in a logical structure (see Table 1 ). All publications in journals and conference proceedings later than 1950 till 2021 were considered for the search. Other articles extracted from the references of the papers identified in the electronic search were also included. A large number of publications on qualitative research were retrieved during the initial screening. Hence, to include the searches with the main focus on criteria for good qualitative research, an inclusion criterion was utilized in the search string.

From the selected databases, the search retrieved a total of 765 publications. Then, the duplicate records were removed. After that, based on the title and abstract, the remaining 426 publications were screened for their relevance by using the following inclusion and exclusion criteria (see Table 2 ). Publications focusing on evaluation criteria for good qualitative research were included, whereas those works which delivered theoretical concepts on qualitative research were excluded. Based on the screening and eligibility, 45 research articles were identified that offered explicit criteria for evaluating the quality of qualitative research and were found to be relevant to this review.

Figure  1 illustrates the complete review process in the form of PRISMA flow diagram. PRISMA, i.e., “preferred reporting items for systematic reviews and meta-analyses” is employed in systematic reviews to refine the quality of reporting.

PRISMA flow diagram illustrating the search and inclusion process. N represents the number of records

Criteria for Evaluating Qualitative Studies

Fundamental criteria: general research quality.

Various researchers have put forward criteria for evaluating qualitative research, which have been summarized in Table 3 . Also, the criteria outlined in Table 4 effectively deliver the various approaches to evaluate and assess the quality of qualitative work. The entries in Table 4 are based on Tracy’s “Eight big‐tent criteria for excellent qualitative research” (Tracy, 2010 ). Tracy argues that high-quality qualitative work should formulate criteria focusing on the worthiness, relevance, timeliness, significance, morality, and practicality of the research topic, and the ethical stance of the research itself. Researchers have also suggested a series of questions as guiding principles to assess the quality of a qualitative study (Mays & Pope, 2020 ). Nassaji ( 2020 ) argues that good qualitative research should be robust, well informed, and thoroughly documented.

Qualitative Research: Interpretive Paradigms

All qualitative researchers follow highly abstract principles which bring together beliefs about ontology, epistemology, and methodology. These beliefs govern how the researcher perceives and acts. The net, which encompasses the researcher’s epistemological, ontological, and methodological premises, is referred to as a paradigm, or an interpretive structure, a “Basic set of beliefs that guides action” (Guba, 1990 ). Four major interpretive paradigms structure the qualitative research: positivist and postpositivist, constructivist interpretive, critical (Marxist, emancipatory), and feminist poststructural. The complexity of these four abstract paradigms increases at the level of concrete, specific interpretive communities. Table 5 presents these paradigms and their assumptions, including their criteria for evaluating research, and the typical form that an interpretive or theoretical statement assumes in each paradigm. Moreover, for evaluating qualitative research, quantitative conceptualizations of reliability and validity are proven to be incompatible (Horsburgh, 2003 ). In addition, a series of questions have been put forward in the literature to assist a reviewer (who is proficient in qualitative methods) for meticulous assessment and endorsement of qualitative research (Morse, 2003 ). Hammersley ( 2007 ) also suggests that guiding principles for qualitative research are advantageous, but methodological pluralism should not be simply acknowledged for all qualitative approaches. Seale ( 1999 ) also points out the significance of methodological cognizance in research studies.

Table 5 reflects that criteria for assessing the quality of qualitative research are the aftermath of socio-institutional practices and existing paradigmatic standpoints. Owing to the paradigmatic diversity of qualitative research, a single set of quality criteria is neither possible nor desirable. Hence, the researchers must be reflexive about the criteria they use in the various roles they play within their research community.

Improving Quality: Strategies

Another critical question is “How can the qualitative researchers ensure that the abovementioned quality criteria can be met?” Lincoln and Guba ( 1986 ) delineated several strategies to intensify each criteria of trustworthiness. Other researchers (Merriam & Tisdell, 2016 ; Shenton, 2004 ) also presented such strategies. A brief description of these strategies is shown in Table 6 .

It is worth mentioning that generalizability is also an integral part of qualitative research (Hays & McKibben, 2021 ). In general, the guiding principle pertaining to generalizability speaks about inducing and comprehending knowledge to synthesize interpretive components of an underlying context. Table 7 summarizes the main metasynthesis steps required to ascertain generalizability in qualitative research.

Figure  2 reflects the crucial components of a conceptual framework and their contribution to decisions regarding research design, implementation, and applications of results to future thinking, study, and practice (Johnson et al., 2020 ). The synergy and interrelationship of these components signifies their role to different stances of a qualitative research study.

Essential elements of a conceptual framework

In a nutshell, to assess the rationale of a study, its conceptual framework and research question(s), quality criteria must take account of the following: lucid context for the problem statement in the introduction; well-articulated research problems and questions; precise conceptual framework; distinct research purpose; and clear presentation and investigation of the paradigms. These criteria would expedite the quality of qualitative research.

How to Assess the Quality of the Research Findings?

The inclusion of quotes or similar research data enhances the confirmability in the write-up of the findings. The use of expressions (for instance, “80% of all respondents agreed that” or “only one of the interviewees mentioned that”) may also quantify qualitative findings (Stenfors et al., 2020 ). On the other hand, the persuasive reason for “why this may not help in intensifying the research” has also been provided (Monrouxe & Rees, 2020 ). Further, the Discussion and Conclusion sections of an article also prove robust markers of high-quality qualitative research, as elucidated in Table 8 .

Quality Checklists: Tools for Assessing the Quality

Numerous checklists are available to speed up the assessment of the quality of qualitative research. However, if used uncritically and recklessly concerning the research context, these checklists may be counterproductive. I recommend that such lists and guiding principles may assist in pinpointing the markers of high-quality qualitative research. However, considering enormous variations in the authors’ theoretical and philosophical contexts, I would emphasize that high dependability on such checklists may say little about whether the findings can be applied in your setting. A combination of such checklists might be appropriate for novice researchers. Some of these checklists are listed below:

The most commonly used framework is Consolidated Criteria for Reporting Qualitative Research (COREQ) (Tong et al., 2007 ). This framework is recommended by some journals to be followed by the authors during article submission.

Standards for Reporting Qualitative Research (SRQR) is another checklist that has been created particularly for medical education (O’Brien et al., 2014 ).

Also, Tracy ( 2010 ) and Critical Appraisal Skills Programme (CASP, 2021 ) offer criteria for qualitative research relevant across methods and approaches.

Further, researchers have also outlined different criteria as hallmarks of high-quality qualitative research. For instance, the “Road Trip Checklist” (Epp & Otnes, 2021 ) provides a quick reference to specific questions to address different elements of high-quality qualitative research.

Conclusions, Future Directions, and Outlook

This work presents a broad review of the criteria for good qualitative research. In addition, this article presents an exploratory analysis of the essential elements in qualitative research that can enable the readers of qualitative work to judge it as good research when objectively and adequately utilized. In this review, some of the essential markers that indicate high-quality qualitative research have been highlighted. I scope them narrowly to achieve rigor in qualitative research and note that they do not completely cover the broader considerations necessary for high-quality research. This review points out that a universal and versatile one-size-fits-all guideline for evaluating the quality of qualitative research does not exist. In other words, this review also emphasizes the non-existence of a set of common guidelines among qualitative researchers. In unison, this review reinforces that each qualitative approach should be treated uniquely on account of its own distinctive features for different epistemological and disciplinary positions. Owing to the sensitivity of the worth of qualitative research towards the specific context and the type of paradigmatic stance, researchers should themselves analyze what approaches can be and must be tailored to ensemble the distinct characteristics of the phenomenon under investigation. Although this article does not assert to put forward a magic bullet and to provide a one-stop solution for dealing with dilemmas about how, why, or whether to evaluate the “goodness” of qualitative research, it offers a platform to assist the researchers in improving their qualitative studies. This work provides an assembly of concerns to reflect on, a series of questions to ask, and multiple sets of criteria to look at, when attempting to determine the quality of qualitative research. Overall, this review underlines the crux of qualitative research and accentuates the need to evaluate such research by the very tenets of its being. Bringing together the vital arguments and delineating the requirements that good qualitative research should satisfy, this review strives to equip the researchers as well as reviewers to make well-versed judgment about the worth and significance of the qualitative research under scrutiny. In a nutshell, a comprehensive portrayal of the research process (from the context of research to the research objectives, research questions and design, speculative foundations, and from approaches of collecting data to analyzing the results, to deriving inferences) frequently proliferates the quality of a qualitative research.

Prospects : A Road Ahead for Qualitative Research

Irrefutably, qualitative research is a vivacious and evolving discipline wherein different epistemological and disciplinary positions have their own characteristics and importance. In addition, not surprisingly, owing to the sprouting and varied features of qualitative research, no consensus has been pulled off till date. Researchers have reflected various concerns and proposed several recommendations for editors and reviewers on conducting reviews of critical qualitative research (Levitt et al., 2021 ; McGinley et al., 2021 ). Following are some prospects and a few recommendations put forward towards the maturation of qualitative research and its quality evaluation:

In general, most of the manuscript and grant reviewers are not qualitative experts. Hence, it is more likely that they would prefer to adopt a broad set of criteria. However, researchers and reviewers need to keep in mind that it is inappropriate to utilize the same approaches and conducts among all qualitative research. Therefore, future work needs to focus on educating researchers and reviewers about the criteria to evaluate qualitative research from within the suitable theoretical and methodological context.

There is an urgent need to refurbish and augment critical assessment of some well-known and widely accepted tools (including checklists such as COREQ, SRQR) to interrogate their applicability on different aspects (along with their epistemological ramifications).

Efforts should be made towards creating more space for creativity, experimentation, and a dialogue between the diverse traditions of qualitative research. This would potentially help to avoid the enforcement of one's own set of quality criteria on the work carried out by others.

Moreover, journal reviewers need to be aware of various methodological practices and philosophical debates.

It is pivotal to highlight the expressions and considerations of qualitative researchers and bring them into a more open and transparent dialogue about assessing qualitative research in techno-scientific, academic, sociocultural, and political rooms.

Frequent debates on the use of evaluative criteria are required to solve some potentially resolved issues (including the applicability of a single set of criteria in multi-disciplinary aspects). Such debates would not only benefit the group of qualitative researchers themselves, but primarily assist in augmenting the well-being and vivacity of the entire discipline.

To conclude, I speculate that the criteria, and my perspective, may transfer to other methods, approaches, and contexts. I hope that they spark dialog and debate – about criteria for excellent qualitative research and the underpinnings of the discipline more broadly – and, therefore, help improve the quality of a qualitative study. Further, I anticipate that this review will assist the researchers to contemplate on the quality of their own research, to substantiate research design and help the reviewers to review qualitative research for journals. On a final note, I pinpoint the need to formulate a framework (encompassing the prerequisites of a qualitative study) by the cohesive efforts of qualitative researchers of different disciplines with different theoretic-paradigmatic origins. I believe that tailoring such a framework (of guiding principles) paves the way for qualitative researchers to consolidate the status of qualitative research in the wide-ranging open science debate. Dialogue on this issue across different approaches is crucial for the impending prospects of socio-techno-educational research.

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The prevalence and possible risk factors of gaming disorder among adolescents in China

• Lina Zhang 1 ,
• Jiaqi Han 2 ,
• Mengqi Liu 3 , 4 ,
• Cheng Yang 5 &
• Yanhui Liao 6  

BMC Psychiatry volume  24 , Article number:  381 ( 2024 ) Cite this article

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Nowadays, moderate gaming behaviors can be a pleasant and relaxing experiences among adolescents. However, excessive gaming behavior may lead to gaming disorder (GD) that disruption of normal daily life. Understanding the possible risk factors of this emerging problem would help to suggest effective at preventing and intervening. This study aimed to investigate the prevalence of GD and analyze its possible risk factors that adolescents with GD.

Data were collected between October 2020 and January 2021. In total, a sample of 7901 students (4080 (52%) boys, 3742 (48%) girls; aged 12–18 years) completed questionnaires regarding the Gaming-Related Behaviors Survey, Gaming Disorder Symptom Questionnaire-21 (GDSQ-21); Behavioral Inhibition System and Behavioral Activation System Scale (BIS/BAS Scale); Emotion Regulation Questionnaire (ERQ); Short-form Egna Minnenav Barndoms Uppfostran for Chinese (s-EMBU-C); and Adolescent Self-Rating Life Events Checklist (ASLEC).

The prevalence of GD was 2.27% in this adolescent sample. The GD gamers were a little bit older (i.e., a higher proportion of senior grades), more boys, with more gaming hours per week in the last 12 months, with more reward responsiveness, maternal rejecting and occurrence of negative life events (e.g., interpersonal relationships, being punished and bereavement factors).

These possible risk factors may influence the onset of GD. Future research in clinical, public health, education and other fields should focus on these aspects for provide target prevention and early intervention strategies.

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Introduction

Video games (typically online games) have become an immensely popular form of entertainment for adolescents. Although moderate gaming has been found to be associated with relaxation and stress reduction [ 1 , 2 , 3 ], excessive use of games may take an uncontrolled addictive form in some individuals [ 4 , 5 , 6 , 7 , 8 ]. Psychiatrists and other health professionals have suggested that excessive use of gaming may cause negative outcomes for interpersonal relationships, physical well-being, mental health, education, and employment [ 9 ]. In 2013, the Fifth Edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-5) introduced Internet gaming disorder (henceforth referred to as IGD) and suggested it as a possible condition for further study [ 10 ]. In June 2018, the 11th Revision of the International Classification of Diseases (ICD-11) included Gaming Disorder (henceforth referred to as GD) as a disease entity. GD is characterized by impaired control over gaming, increasing prioritization of gaming over other life interests and daily activities, and continuation or escalation of gaming despite negative consequences [ 11 ]. For adolescents, the prevalence of IGD has been reported to be 9.9% (CI = 1.0-21.5%) in Asia, 9.4% (95% CI = 8.3-10.5%) in North America, 4.4% (95% CI = 1.9-7.4%) in Australia and 3.9% (95% CI = 2.8-5.3%) in Europe [ 12 ]. In addition, the present research shows that individuals’ gaming behaviours cause not only functional impairments in main areas but also other related mental health issues. Thus, preventing GD seems to be of essential importance, as shown by calls for preventive interventions for groups at high risk of GD (e.g., adolescents) at the social, family and school levels [ 13 ]. To prevent GD from developing, we need to investigate the China prevalence of GD and analyze the possible risk factors that problematic gaming behaviour among adolescents [ 14 ].

Studies on demographic differences have reported higher prevalence rates of IGD among males than among females [ 15 , 16 , 17 ]. Furthermore, IGD may be observed up to five times more often among males than among females in children and adolescents [ 18 ]. As adolescence is a period of transition, some of these minors might lack accurate knowledge of their own behaviour and sufficient self-control, and some might be particularly susceptible to factors associated with persistent on-/off-line gaming [ 19 , 20 , 21 ].

Symptoms of IGD and the underlying neurobiological mechanisms. Kuss et al. [ 22 ]. reported that compared with healthy controls, gaming addicted individuals have poorer response inhibition and emotion regulation, impaired prefrontal cortex function and cognitive control, poorer working memory and decision-making, and deficits in the neural reward system. Several studies of individuals with IGD have shown increased sensitivity to reward and decreased ability to control impulsivity in the face of reward stimuli [ 23 , 24 ]. Additionally, IGD has also been linked to psychological detriments and negative consequences, such as negative and depressed moods [ 25 ], trait anxiety, social phobia, substance abuse and aggressive behaviours [ 26 , 27 ], decreased conscientiousness [ 28 ], higher impulsivity [ 29 ] and lower self-esteem [ 30 ].

The socioenvironment is one of the crucial factors that plays a role in IGD [ 31 ]. Many studies have shown that adolescents with IGD are associated with parental and familial risk factors, including but not limited to insufficient parental care, oppressive and hostile parents, poor parent-child relations, and poor family cohesion and family violence [ 32 , 33 ]. In addition, being bullied at school is more strongly associated with IGD [ 15 ].

The most consistent finding was that game design and video game type were related to IGD symptoms. Modern games provide communication platforms, instant feedback and rewards and are more likely to create an immersive experience for gamers, increasing gamer loyalty and engagement. A study of patients with GD who played ‘online’ games found that the two most common types of game played were massive multiplayer online role-playing games (MMORPGs) [ 7 ] and first-person shooters (FPSs) games [ 34 ].

Despite these contributions, there are still few studies focusing on the prevalence and possible risk factors of GD in adolescents based on the ICD-11 diagnostic guidelines. As GD is recognized as a behavioral addictions, it is necessary to identify risk factors that increase the likelihood of developing the disorder. To sum up, the current study, based on the ICD-11 GD diagnostic guidelines, aimed to investigate the prevalence and undergo a comprehensive synthesis to analyse risk factors such as sociodemographic predictors, psychological factors, parenting styles and negative life events, and game-related factors (e.g. gaming hours per week ) and GD among adolescents.

Participants and procedures

Using convenience sampling, 7901 middle school students were enrolled from twelve middle schools in Urumqi, Kashi and Bole City of Xinjiang Uygur Autonomous Region, China from 2020 to 2021. In each area, two junior high schools and two senior high schools were selected, and in each school, four classes were selected from each grade (grades 1–3 of junior high schools and grades 1–3 of senior high schools). The classes were randomly selected in each school. The inclusion criteria were as follows: being 12–18 years old, voluntary participating in the study; the subjects themselves and at least one of their parents/monitors completed the informed consent. The exclusion criteria for patients were: having mental illness or serious physical illness, having severe cognitive impairment, or any inability to fill out questionnaires.

Ultimately, a valid sample of 7790 students aged between 12 and 18 years (mean = 14.99; SD = 1.65; boy = 52.0%) participated in the current study, for an effective rate of 98.6%.

Sociodemographics and gaming-related behaviours

Sociodemographic data included participants’ age, gender, family structure (having siblings or being an only child), who the student lived with, and socioeconomic status (i.e., the highest level of education of family members, occupational and income strata of the family). Participants subjectively scored the occupational and income strata of the family members living with them from 1 (lowest) to 10 (highest). The detailed information on the occupational and income strata is presented in Supplementary Tables 1 and 2 . Gaming-related behaviours included the types of games most often played and the game hours per week spent playing on primarily online, stand-alone and/or video games.

Assessment of gaming disorder symptoms

The Gaming Disorder Symptom Questionnaire-21 (GDSQ-21) was used to assess GD [ 35 ], which consists of 21 items with three subscales, impaired control, increasing priority, and continued use despite the occurrence of negative consequences. This instrument is used to assess the severity of GD symptoms by examining both online and/or offline gaming activities occurring over a 12-month period. Participants indicated how much they agreed with the statements on a 5-point Likert scale: 0 (“hardly ever”), 1 (“less than once a month”), 2 (“once a month”), 3 (“once a week”), and 4 (“almost every day”). Its three-dimensional structure corresponds to the new ICD-11 diagnostic concept of GD. It has good validity and internal consistency, with a Cronbach’s alpha coefficient of 0.964, and plays an important role in the investigation of GD. The scoring is the same as that of the original version of the GDSQ-21: with the cutoff of ≥ 14 for impaired control dimension, ≥ 11 for increasing priority, ≥ 4 for continued, and ≥ 62 for the whole scale, met each dimension and total score can effectively screen for GD.

Psychological status

To measure participants’ sensitivity to punishment and rewards, the Chinese version of the Behavioral Inhibition System and Behavioral Activation System (BIS/BAS) scale was used [ 36 ], it has 20 items to which participants respond on a 4-point Likert scale from 1(“totally agree”) to 4(“totally disagree”). The BIS/BAS consists of 20-item self-rating questionnaire with good psychometric properties. The questionnaire comprises 13 BAS items and 7 BIS items. The 3 subscales of the BAS assess responsiveness to reward, drive towards appetitive goals, and fun seeking. In the present study, the Cronbach’s alpha coefficient of the scale was 0.891.

Emotion regulation

To assess an individual’s typical level of emotion dysregulation, the Chinese version of the Emotion Regulation Questionnaire (ERQ) scale was used [ 37 ]. The ERQ is a 10-item self-rating questionnaire of how frequently people use two emotion regulation strategies: cognitive reappraisal (6 items), an antecedent-focused strategy, and expressive suppression (4 items), a response-focused strategy. The items are rated on a 7-point Likert scale ranging from 1 (“strongly disagree”) to 7 (“strongly agree”). In this study, the Cronbach’s alpha coefficient of the scale was 0.967, which reflects good reliability.

Family functioning

Parenting styles and behaviours were assessed by the Chinese version of the Short-form Egna Minnenav Barndoms Uppfostran for Chinese (s-EMBU-C) [ 38 ], which has 42 items, divided into paternal and maternal versions. Each version of the scale contains three subscales, namely, refusal, emotional warmth, and overprotection. All items are rated on a 4-point Likert scale, with each subscale being scored as follows: 1 (“never”), 2 (“occasionally”), 3 (“often”), and 4 (“always”). In the current study, the Cronbach’s alpha coefficient of the scale was 0.884.

Negative life events

Negative life events were measured by the Adolescent Self-Rating Life Events Checklist (ASLEC) [ 39 ], which evaluates the impact of negative life events experienced within the past 12 months. The ASLEC consists of 26 items, including 6 subscales: interpersonal relationships, study pressure, being punished, bereavement, health adjustment and others. Each item is scored on a 5-point Likert scale ranging from 1 (“not at all”) to 5 (“extremely severe”). In our study, the Cronbach’s alpha coefficient of internal consistency was 0.938.

Statistical analyses

First, based on the ICD-11 diagnostic guidelines, the GDSQ-21 cut-off point was used to calculate the prevalence of GD. Besides estimating prevalence, Univariate analyses were conducted: independent samples t tests and chi-square tests were used to further compare the sociodemographic variables, psychological factors, parenting styles and negative life events, and game-related factors (e.g., hours spent on game design and types of video games) of the two groups.

Second, binary logistic regressions analyses were carried out with the GDSQ-21 score as the dependent variable and sociodemographic variables, psychological factors, parenting styles and negative life events as independent variables. These variables are summarized in Supplementary Table 3 .

Before conducting the regression analysis, to make the regression model more reasonable, it is necessary to first conduct univariate analysis to determine which variables are related to GD. To avoid omitting variables that may have an effect, variables with a statistically significant difference p  < 0.2 should be considered for inclusion in the regression equation as potential predictors.

In addition, in terms of gaming behaviour characteristics, there were differences between GD and Non-GD. Theoretically, these characteristics could be the result of GD, the cause of GD, or the accompanying manifestations of the disorder. Thus, this study does not consider these gaming behaviour characteristics causal variables for the occurrence of GD, but there are differences between GD and Non-GD in these variables. Therefore, univariate analysis of gaming behaviour characteristics was also conducted.

All the statistical analyses were carried out with SPSS software (version 25.0).

Prevalence of GD and sociodemographic characteristics among participants

We identified that the 12-month prevalence was 2.27% ( n  = 177) adolescents with GD and 97.73% ( n  = 7613) adolescents with Non-GD. All participants were divided into GD (boys/girls = 145/32, mean age: 15.62 ± 1.69) and Non-GD (boys/girls = 3597/4016, mean age: 14.98 ± 1.64). The detailed sociodemographic characteristics of the GD and the Non-GD are presented in Table  1 . Compared to Non-GD, in the GD there were more boys ( χ² = 83.31, p  < 0.001), they were a little bit older (i.e., a higher proportion of senior grades), and more likely to be only children ( χ² = 2.01, p  < 0.01), who the student lives with ( χ² = 16.50, p  < 0.05). Those in the GD were in lower occupational strata by their family ( t  = 1.51, p  < 0.05) and income strata by their family ( t  = 1.72, p  < 0.2).

Gaming-related behaviours

Gaming-related behaviours for the whole sample, the GD and the Non-GD are presented in Table  2 . Compared to the Non-GD, the GD spent significantly more hours on online or playing on-/offline games. Moreover, GD prefer to choose specific game genres.

Univariate analysis of psychological factors

For reward processing, emotional characteristics, regulatory strategies, parenting styles and behaviours, and impact of negative life events (i.e., BIS/BAS, ERQ, s-EMBU-C, ASLEC questionnaires), t tests were used to determine the differences between the GD and the Non-GD, as shown in Table  3 . The results showed that the GD and the Non-GD were significantly different in terms of BIS- behavioral inhibition ( t = -1.933, p  < 0.02); BAS- reward responsiveness ( t = -4.659, p  < 0.001) and drive ( t = -3.451, p  < 0.001); ERQ-expressive suppression ( t  = 0.480, p  < 0.02); s-EMBU-C-paternal refusal ( t = -6.745, p  < 0.001), emotional warmth ( t  = 2.996, p  < 0.01), overprotection ( t = -5.213, p  < 0.001), maternal refusal ( t = -7.657, p  < 0.001), emotional warmth ( t  = 2.936, p  < 0.01), and overprotection ( t = -5.419, p  < 0.001); and ASLEC-interpersonal relationships ( t = -7.756, p  < 0.001), study pressure ( t = -6.280, p  < 0.001), being punished ( t = -7.022, p  < 0.001), bereavement ( t = -3.458, p  < 0.01), and health adjustment ( t = -5.967, p  < 0.001). No significant differences were detected between the GD and the Non-GD in terms of BAS-fun seeking or ERQ-cognitive reappraisal.

Logistic regression analysis

The results of the binary logistic regression analysis are shown in Table  4 . Variables that were significantly different in the univariate analysis were included in the regression model as independent variables. These variables consisted of age; gender; being an only child; who the student lived with; family occupational strata, family income strata; BIS- behavioral inhibition; BAS-reward responsiveness and drive; ERQ-expressive suppression; s-EMBU-C-paternal and maternal of refusal, emotional warmth, and overprotection; and ASLEC-interpersonal relationships, study pressure, being punished, bereavement, and health adjustment.

Regarding sociodemographic characteristics, age (odds ratio: 1.261) and gender (odds ratio: 0.211) were significantly associated with GD. The BAS-reward score (odds ratio:1.099) was a significant psychological predictor of GD. s-EMBU-C-maternal refusal (odds ratio: 1.061) was a significant family-environment predictor of GD. ASLEC-interpersonal relationships (odds ratio: 1.070), being punished (odds ratio: 1.073) and bereavement (odds ratio: 0.860) were significant socioenvironmental predictors of GD. Specifically, boys were 0.211 times more likely to have GD than girls. With a one-year increase in age, participants were 1.261 times more likely to be classified as having a GD (participants were between the ages of 12 and 18). With a one-unit score higher for the s-EMBU-C-maternal refusal, ASLEC- interpersonal relationships, being punished and bereavement factors, the probability of GD increased by 1.061, 1.070, 1.073 and 0.86 times, respectively.

This study aimed to investigate the prevalence of GD and analyze its possible risk factors of IGD among adolescents attending school in China based on the diagnostic guidelines the ICD-11 proposes. Three major findings emerged from this investigation: (1) Compared to the Non-GD, GD were a little bit older and more boys. (2) The hours spent on games playing are positively associated with GD. Moreover, GD preferred to choose specific game genres. (3) Some factors (psychological, parenting styles and negative life events) are associated with GD.

Prevalence of GD

Our results reported the 12-month prevalence among adolescents of China. A recent study showed 2.2% of the 28 representative sample studies prevalence estimates, which is nearly comparable to our findings [ 40 ]. The increasing popularity of the Internet in China in recent years may contribute to the growing size of underage Internet users. The number of juvenile internet users reached 193 million in 2022 [ 41 ]. The proportion of underage Internet users who play computer games has also increased. Excessive gaming behavior and poor usage habits can be very engaging, time consuming and easily addictive to some gaming users. As young people are mentally and physically immature, their physical and mental health is highly susceptible to environmental and behavioral influences and they are more likely to develop mental health problems directly related to their gaming behavior.

Sociodemographic characteristics of participants with GD

In terms of age, a greater proportion of patients in the GD were in the upper grades than those in the Non-GD. Previous studies have also suggested that age has an inverted U-shaped relationship with online GD [ 42 , 43 ] and is correlated with the amount of hours spent playing games [ 44 , 45 ]. Adolescents in higher grades were more likely to be gaming addicted [ 46 ].

Gender as a risk factor for GD. In this study, there were more boys with GD than girls. This finding is consistent with previous research showing that GD was more likely to occur in the male users [ 47 , 48 , 49 , 50 ]. This may be because male are more likely to choose competitive [ 51 ] and adversarial activities [ 52 ] for entertainment, and a significant proportion of all types of games have these characteristics. Compared to male gamers, female gamers engage in gaming for entertainment and socializing rather than to experience combat or to alleviate negative emotions [ 53 , 54 , 55 , 56 ], and they also spend less hours online and looking at the screen while playing [ 57 ]. In addition, behavioral addictions such as polysubstance dependence and gambling are generally more prevalent in males than females [ 58 , 59 ]. This suggested that gender, addiction susceptibility and other factors may contribute to the greater susceptibility of males to addiction, which may similarly contribute to the higher prevalence of males than females with GD. In addition, brain imaging studies have shown that the males and females respond differently to gaming cues [ 60 ], with more activation in areas such as the striatum and orbitofrontal cortex in males, which may be the brain mechanism for the aforementioned gender differences [ 61 ].

The greater proportion of only children among those with GD (results of univariate analysis) is consistent with previous research findings that adolescents’ peer interactions are both necessary for their social needs and have recreational properties that allow them to enrich their leisure time [ 62 ]. The peer interactions of only children may be more limited to classmates and friends, and they may be more likely to find ways to interact with peers through the virtual world of online games when social needs are relatively inadequately met.

In terms of the level of education, occupational strata and income strata of the family members living with participants. Previous studies have suggested that the educational level of the family may be associated with the onset of GD [ 63 ], but this study failed to find a difference in this variable between GD and Non-GD. One of the reasons this study failed to find an association between parental education level and GD in adolescents may be that the popularity of smartphones and the mobile Internet in China in recent years has made people’s information sources extremely rich and significantly decreased the threshold of information access [ 64 ], allowing parents with different levels of education to learn about the dangers of GD and preventive measures, thus responding to adolescent gaming. This has led to a homogenization of the response to adolescent gaming problems, making the effect of education level of the family members less significant. On the other hand, this study revealed that family members with GD had lower occupational and income strata than Non-GD. Given that occupational and income are closely related and that higher occupational and income strata are more likely to help families provide good material and spiritual life for their adolescents, this study hypothesizes that gaming is a relatively accessible and inexpensive entertainment for adolescents with relatively low material and mental life, making them more likely to use gaming and more likely to develop GD.

Game hours and game genre preference of GD

This study found that people with GD spent more hours and money on gaming-related behaviours than Non-GD, which is consistent with previous findings [ 65 ]. In addition, previous research has shown that males spend twice as more game hours as females playing video games each week and on weekends [ 66 ], an easily understandable characteristic that is more likely to promote GD as game immersion and game hours per week increase. Importantly, gamers with GD are also more likely to engage in in-game payment behaviour. In recent years, the gaming industry has proliferated the variety of their revenue streams (such as increasing membership fees and selling virtual props and cosmetic skins) [ 67 ]. In addition, online gaming is more addictive than offline gaming, possibly because of its inherent social reinforcement [ 68 ].

In terms of game genre preference, this study revealed that people with GD prefer specific game genres, considering that they may be designed to capture the attention of gamers and promote their addiction to endless gaming experiences, such as multiplayer online battle arenas (MOBAs) games, which provide a social environment built entirely on gaming screens. The short duration of these games, their ability to provide rapid positive feedback and their suitability for use on mobile phones may be important reasons games in this genre were widely played by those with GD. Future research should focus on the regulation of gaming products and genres to effectively prevent and control GD in the future.

Psychological factors, parenting styles and negative life events associated with GD

Among the factors influencing GD, this study focused on psychological factors in terms of reward processing and emotional characteristics. Univariate analysis results showed that compared to Non-GD, GD have lower behavioral inhibition, having greater reward reactivity and drive, using more expressive inhibition in emotion regulation. The logistic regression revealed that the BIS inhibition dimension and ERQ did not predict GD among adolescents, whereas the reward response on the BAS activation dimension was predictive of GD. This suggesting that adolescents primarily seek pleasure and rewards when playing games and that many online games themselves allow players to earn points, level up, and obtain rewards that tend to induce positive pleasure and reward effects.

The parenting styles of paternal and maternal have an important influence on the development of GD among adolescents. Univariate analysis revealed that GD have more experiencing rejection parenting styles, having lower emotional warmth, and experiencing greater overprotection. According to the logistic regression model, maternal rejection was the only significant family correlate. The more the mother rejected and denied the child, used inappropriate parenting styles and punished the child too harshly, the more likely the child was to develop GD. In general, family parenting is a combination of both parents’ parenting attitudes and behaviours, but children general have the most contact with their mothers and develop more attachment to them, so the mother’s feedback and evaluation of the child is particularly important, especially during the adolescent years when self-perception is still unclear. If the mother has a clear tendency to reject the child and has disrespectful thoughts towards the child, this may have a greater negative impact on the child, which may increase more game hours the adolescent spends gaming.

Negative life events also play an important role in the development of gaming problems in adolescents. Univariate analyses revealed that GD have more experiencing more negative life events. The interpersonal relationships, being punished and bereavement factors were significant negative life events in the regression model. When adolescents felt stress or negative emotions in their interpersonal relationships and being punished, some of them adolescents began to use gaming as a way of relieving dissatisfaction and escaping from real-life problems. When experiencing life events such as the loss of family, friends and job, individuals may become consumed with grief and temporarily turn away from games. Later, when the individual is unable to avoid the event or solve the problem in the usual way, the individual may use game to escape from the sadness.

Mannikko et al [ 69 ]. suggested that excessive gameplay can harm adolescents on their psychological, social, and physical health. The results of our study showed that GD have higher reward responsiveness, more maternal rejecting and more occurrence of negative life events (e.g., interpersonal relationships, being punished and bereavement factors). In addition, many other possible risk factors for GD also needs to be further explored. The possible risk factors that have been identified carry clinical importance as they provide a more holistic approach towards adolescent in the prevention of GD.

Limitations of study

As with all research, this study has some limitations and strengths. First, we used a convenience sampling method to conduct this research in twelve schools in the Xinjiang Uygur Autonomous Region, China, so the results should be validated in other regions of China in the future. Second, all of the assessments were self-reported and might have suffered from social desirability bias. Third, this study was that the GD was evaluated only the GDSQ-21, and no evaluation was performed according to psychiatric clinical diagnostic interviews. Therefore, the accuracy, specificity, and sensitivity could not be determined. Future research in the field should compare clinically diagnosed samples using actual GDSQ-21 test scores. Fourth, this study was cross sectional study, which prevents drawing conclusions about the causal relationships between variables. Therefore, further research is needed to explore these longitudinal relationships.

In conclusion, the results of our study showed the prevalence of GD, and possible risk factors, which the reward responsiveness, maternal rejecting and occurrence of negative life events associated with GD. This study showed a positive association between gaming hours and GD, and GD preferred to choose a specific game genre. Furthermore, we found that gender and age were significant predictors of gaming harm with a little bit older males (i.e., a higher proportion of senior grades) being more susceptible. This study may provide some suggestion for real life. In prevention and intervention, prevention efforts should aim at identifying possible risk factors.

Data availability

The datasets used and/or analyzed during the present study are available from the corresponding author upon reasonable request.

Abbreviations

Diagnostic and Statistical Manual of Mental Disorders

Internet gaming disorder

International Classification of Diseases 11th Revision

• Gaming disorder

Gaming Disorder Symptom Questionnaire-21

Behavioral Inhibition System and Behavioral Activation System Scale

Emotion Regulation Questionnaire

Short-form Egna Minnenav Barndoms Uppfostran for Chinese

Adolescent Self-Rating Life Events Checklist

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Acknowledgements

The authors thank all of the participants who participated in the study.

This study was supported by the Non-profit Central Research Institute Fund of the Chinese Academy of Medical Sciences (No. 2019HY320001) and STI 2030—Major Projects (No. 2022ZD0211200).

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Authors L.Z., Y.L., designed the study. L.Z., J.H., M.L., C.Y., collected the data. L.Z., J.H., Y.L., conducted the statistical analysis. Y.L., J.H., M.L., C.Y., interpreted the data. L.Z., wrote the manuscript. Y.L., obtained the funding. All authors contributed to and have approved the final manuscript.

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Zhang, L., Han, J., Liu, M. et al. The prevalence and possible risk factors of gaming disorder among adolescents in China. BMC Psychiatry 24 , 381 (2024). https://doi.org/10.1186/s12888-024-05826-9

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Turnover intention and its associated factors among nurses in Ethiopia: a systematic review and meta-analysis

• Eshetu Elfios 1 ,
• Israel Asale 1 ,
• Merid Merkine 1 ,
• Temesgen Geta 1 ,
• Kidist Ashager 1 ,
• Getachew Nigussie 1 ,
• Ayele Agena 1 ,
• Bizuayehu Atinafu 1 ,
• Eskindir Israel 2 &
• Teketel Tesfaye 3  

BMC Health Services Research volume  24 , Article number:  662 ( 2024 ) Cite this article

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Nurses turnover intention, representing the extent to which nurses express a desire to leave their current positions, is a critical global public health challenge. This issue significantly affects the healthcare workforce, contributing to disruptions in healthcare delivery and organizational stability. In Ethiopia, a country facing its own unique set of healthcare challenges, understanding and mitigating nursing turnover are of paramount importance. Hence, the objectives of this systematic review and meta-analysis were to determine the pooled proportion ofturnover intention among nurses and to identify factors associated to it in Ethiopia.

A comprehensive search carried out for studies with full document and written in English language through an electronic web-based search strategy from databases including PubMed, CINAHL, Cochrane Library, Embase, Google Scholar and Ethiopian University Repository online. Checklist from the Joanna Briggs Institute (JBI) was used to assess the studies’ quality. STATA version 17 software was used for statistical analyses. Meta-analysis was done using a random-effects method. Heterogeneity between the primary studies was assessed by Cochran Q and I-square tests. Subgroup and sensitivity analyses were carried out to clarify the source of heterogeneity.

This systematic review and meta-analysis incorporated 8 articles, involving 3033 nurses in the analysis. The pooled proportion of turnover intention among nurses in Ethiopia was 53.35% (95% CI (41.64, 65.05%)), with significant heterogeneity between studies (I 2  = 97.9, P  = 0.001). Significant association of turnover intention among nurses was found with autonomous decision-making (OR: 0.28, CI: 0.14, 0.70) and promotion/development (OR: 0.67, C.I: 0.46, 0.89).

Conclusion and recommendation

Our meta-analysis on turnover intention among Ethiopian nurses highlights a significant challenge, with a pooled proportion of 53.35%. Regional variations, such as the highest turnover in Addis Ababa and the lowest in Sidama, underscore the need for tailored interventions. The findings reveal a strong link between turnover intention and factors like autonomous decision-making and promotion/development. Recommendations for stakeholders and concerned bodies involve formulating targeted retention strategies, addressing regional variations, collaborating for nurse welfare advocacy, prioritizing career advancement, reviewing policies for nurse retention improvement.

Peer Review reports

Turnover intention pertaining to employment, often referred to as the intention to leave, is characterized by an employee’s contemplation of voluntarily transitioning to a different job or company [ 1 ]. Nurse turnover intention, representing the extent to which nurses express a desire to leave their current positions, is a critical global public health challenge. This issue significantly affects the healthcare workforce, contributing to disruptions in healthcare delivery and organizational stability [ 2 ].

The global shortage of healthcare professionals, including nurses, is an ongoing challenge that significantly impacts the capacity of healthcare systems to provide quality services [ 3 ]. Nurses, as frontline healthcare providers, play a central role in patient care, making their retention crucial for maintaining the functionality and effectiveness of healthcare delivery. However, the phenomenon of turnover intention, reflecting a nurse’s contemplation of leaving their profession, poses a serious threat to workforce stability [ 4 ].

Studies conducted globally shows that high turnover rates among nurses in several regions, with notable figures reported in Alexandria (68%), China (63.88%), and Jordan (60.9%) [ 5 , 6 , 7 ]. In contrast, Israel has a remarkably low turnover rate of9% [ 8 ], while Brazil reports 21.1% [ 9 ], and Saudi hospitals26% [ 10 ]. These diverse turnover rates highlight the global nature of the nurse turnover phenomenon, indicating varying degrees of workforce mobility in different regions.

The magnitude and severity of turnover intention among nurses worldwide underscore the urgency of addressing this issue. High turnover rates not only disrupt healthcare services but also result in a loss of valuable skills and expertise within the nursing workforce. This, in turn, compromises the continuity and quality of patient care, with potential implications for patient outcomes and overall health service delivery [ 11 ]. Extensive research conducted worldwide has identified a range of factors contributing to turnover intention among nurses [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. These factors encompass both individual and organizational aspects, such as high workload, inadequate support, limited career advancement opportunities, job satisfaction, conflict, payment or reward, burnout sense of belongingness to their work environment. The complex interplay of these factors makes addressing turnover intention a multifaceted challenge that requires targeted interventions.

In Ethiopia, a country facing its own unique set of healthcare challenges, understanding and mitigating nursing turnover are of paramount importance. The healthcare system in Ethiopia grapples with issues like resource constraints, infrastructural limitations, and disparities in healthcare access [ 18 ]. Consequently, the factors influencing nursing turnover in Ethiopia may differ from those in other regions. Previous studies conducted in the Ethiopian context have started to unravel some of these factors, emphasizing the need for a more comprehensive examination [ 18 , 19 ].

Although many cross-sectional studies have been conducted on turnover intention among nurses in Ethiopia, the results exhibit variations. The reported turnover intention rates range from a minimum of 30.6% to a maximum of 80.6%. In light of these disparities, this systematic review and meta-analysis was undertaken to ascertain the aggregated prevalence of turnover intention among nurses in Ethiopia. By systematically analyzing findings from various studies, we aimed to provide a nuanced understanding of the factors influencing turnover intention specific to the Ethiopian healthcare context. Therefore, this systematic review and meta-analysis aimed to answer the following research questions.

What is the pooled prevalence of turnover intention among nurses in Ethiopia?

What are the factors associated with turnover intention among nurses in Ethiopia?

The primary objective of this review was to assess the pooled proportion of turnover intention among nurses in Ethiopia. The secondary objective was identifying the factors associated to turnover intention among nurses in Ethiopia.

Study design and search strategy

A comprehensive systematic review and meta-analysis was conducted, examining observational studies on turnover intention among nurses in Ethiopia. The procedure for this systematic review and meta-analysis was developed in accordance with the Preferred Reporting Items for Systematic review and Meta-analysis Protocols (PRISMA-P) statement [ 20 ]. PRISMA-2015 statement was used to report the findings [ 21 , 22 ]. This systematic review and meta-analysis were registered on PROSPERO with the registration number of CRD42024499119.

We conducted systematic and an extensive search across multiple databases, including PubMed, CINAHL, Cochrane Library, Embase, Google Scholar and Ethiopian University Repository online to identify studies reporting turnover intention among nurses in Ethiopia. We reviewed the database available at http://www.library.ucsf.edu and the Cochrane Library to ensure that the intended task had not been previously undertaken, preventing any duplication. Furthermore, we screened the reference lists to retrieve relevant articles. The process involved utilizing EndNote (version X8) software for downloading, organizing, reviewing, and citing articles. Additionally, a manual search for cross-references was performed to discover any relevant studies not captured through the initial database search. The search employed a comprehensive set of the following search terms:“prevalence”, “turnover intention”, “intention to leave”, “attrition”, “employee attrition”, “nursing staff turnover”, “Ethiopian nurses”, “nurses”, and “Ethiopia”. These terms were combined using Boolean operators (AND, OR) to conduct a thorough and systematic search across the specified databases.

Eligibility criteria

Inclusion criteria.

The established inclusion criteria for this meta-analysis and systematic review are as follows to guide the selection of articles for inclusion in this review.

Population: Nurses working in Ethiopia.

Study period: studies conducted or published until 23November 2023.

Study design: All observational study designs, such as cross-sectional, longitudinal, and cohort studies, were considered.

Setting: Only studies conducted in Ethiopia were included.

Outcome; turnover intention.

Study: All studies, whether published or unpublished, in the form of journal articles, master’s theses, and dissertations, were included up to the final date of data analysis.

Language: This study exclusively considered studies in the English language.

Exclusion criteria

Excluded were studies lacking full text or Studies with a Newcastle–Ottawa Quality Assessment Scale (NOS) score of 6 or less. Studies failing to provide information on turnover intention among nurses or studies for which necessary details could not be obtained were excluded. Three authors (E.E., T.G., K.A) independently assessed the eligibility of retrieved studies, other two authors (E.I & M.M) input sought for consensus on potential in- or exclusion.

Quality assessment and data extraction

Two authors (E.E, A.A, G.N) independently conducted a critical appraisal of the included studies. Joanna Briggs Institute (JBI) checklists of prevalence study was used to assess the quality of the studies. Studies with a Newcastle–Ottawa Quality Assessment Scale (NOS) score of seven or more were considered acceptable [ 23 ]. The tool has nine parameters, which have yes, no, unclear, and not applicable options [ 24 ]. Two reviewers (I.A, B.A) were involved when necessary, during the critical appraisal process. Accordingly, all studies were included in our review. ( Table  1 ) Questions to evaluate the methodological quality of studies on turnover intention among nurses and its associated factors in Ethiopia are the followings:

Q1 = was the sample frame appropriate to address the target population?

Q2. Were study participants sampled appropriately.

Q3. Was the sample size adequate?

Q4. Were the study subjects and the setting described in detail?

Q5. Was the data analysis conducted with sufficient coverage of the identified sample?

Q6. Were the valid methods used for the identification of the condition?

Q7. Was the condition measured in a standard, reliable way for all participants?

Q8. Was there appropriate statistical analysis?

Q9. Was the response rate adequate, and if not, was the low response rate.

managed appropriately?

Data was extracted and recorded in a Microsoft Excel as guided by the Joanna Briggs Institute (JBI) data extraction form for observational studies. Three authors (E.E, M.G, T.T) independently conducted data extraction. Recorded data included the first author’s last name, publication year, study setting or country, region, study design, study period, sample size, response rate, population, type of management, proportion of turnover intention, and associated factors. Discrepancies in data extraction were resolved through discussion between extractors.

Data processing and analysis

Data analysis procedures involved importing the extracted data into STATA 14 statistical software for conducting a pooled proportion of turnover intention among nurses. To evaluate potential publication bias and small study effects, both funnel plots and Egger’s test were employed [ 25 , 26 ]. We used statistical tests such as the I statistic to quantify heterogeneity and explore potential sources of variability. Additionally, subgroup analyses were conducted to investigate the impact of specific study characteristics on the overall results. I 2 values of 0%, 25%, 50%, and 75% were interpreted as indicating no, low, medium, and high heterogeneity, respectively [ 27 ].

To assess publication bias, we employed several methods, including funnel plots and Egger’s test. These techniques allowed us to visually inspect asymmetry in the distribution of study results and statistically evaluate the presence of publication bias. Furthermore, we conducted sensitivity analyses to assess the robustness of our findings to potential publication bias and other sources of bias.

Utilizing a random-effects method, a meta-analysis was performed to assess turnover intention among nurses, employing this method to account for observed variability [ 28 ]. Subgroup analyses were conducted to compare the pooled magnitude of turnover intention among nurses and associated factors across different regions. The results of the pooled prevalence were visually presented in a forest plot format with a 95% confidence interval.

Study selection

After conducting the initial comprehensive search concerning turnover intention among nurses through Medline, Cochran Library, Web of Science, Embase, Ajol, Google Scholar, and other sources, a total of 1343 articles were retrieved. Of which 575 were removed due to duplication. Five hundred ninety-three articles were removed from the remaining 768 articles by title and abstract. Following theses, 44 articles which cannot be retrieved were removed. Finally, from the remaining 131 articles, 8 articles with a total 3033 nurses were included in the systematic review and meta-analysis (Fig.  1 ).

PRISMA flow diagram of the selection process of studies on turnover intention among nurses in Ethiopia, 2024

Study characteristics

All included 8 studies had a cross-sectional design and of which, 2 were from Tigray region, 2 were from Addis Ababa(Capital), 1 from south region, 1 from Amhara region, 1 from Sidama region, and 1 was multiregional and Nationwide. The prevalence of turnover intention among nurses ‘ranges from 30.6 to 80.6%. Table  2 .

Pooled prevalence of turnover intention among nurses in Ethiopia

Our comprehensive meta-analysis revealed a notable turnover intention rate of 53.35% (95% CI: 41.64, 65.05%) among Ethiopian nurses, accompanied by substantial heterogeneity between studies (I 2  = 97.9, P  = 0.000) as depicted in Fig.  2 . Given the observed variability, we employed a random-effects model to analyze the data, ensuring a robust adjustment for the significant heterogeneity across the included studies.

Forest plot showing the pooled proportion of turnover intention among nurses in Ethiopia, 2024

Subgroup analysis of turnover intention among nurses in Ethiopia

To address the observed heterogeneity, we conducted a subgroup analysis based on regions. The results of the subgroup analysis highlighted considerable variations, with the highest level of turnover intention identified in Addis Ababa at 69.10% (95% CI: 46.47, 91.74%) and substantial heterogeneity (I 2  = 98.1%). Conversely, the Sidama region exhibited the lowest level of turnover intention among nurses at 30.6% (95% CI: 25.18, 36.02%), accompanied by considerable heterogeneity (I 2  = 100.0%) ( Fig.  3 ).

Subgroup analysis of systematic review and meta-analysis by region of turnover intention among nurses in Ethiopia, 2024

Publication bias of turnover intention among nurses in Ethiopia

The Egger’s test result ( p  = 0.64) is not statistically significant, indicating no evidence of publication bias in the meta-analysis (Table  3 ). Additionally, the symmetrical distribution of included studies in the funnel plot (Fig.  4 ) confirms the absence of publication bias across studies.

Funnel plot of systematic review and meta-analysis on turnover intention among nurses in Ethiopia, 2024

Sensitivity analysis

The leave-out-one sensitivity analysis served as a meticulous evaluation of the influence of individual studies on the comprehensive pooled prevalence of turnover intention within the context of Ethiopian nurses. In this systematic process, each study was methodically excluded from the analysis one at a time. The outcomes of this meticulous examination indicated that the exclusion of any particular study did not lead to a noteworthy or statistically significant alteration in the overall pooled estimate of turnover intention among nurses in Ethiopia. The findings are visually represented in Fig.  5 , illustrating the stability and robustness of the overall pooled estimate even with the removal of specific studies from the analysis.

Sensitivity analysis of pooled prevalence for each study being removed at a time for systematic review and meta-analysis of turnover intention among nurses in Ethiopia

Factors associated with turnover intention among nurses in Ethiopia

In our meta-analysis, we comprehensively reviewed and conducted a meta-analysis on the determinants of turnover intention among nurses in Ethiopia by examining eight relevant studies [ 6 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. We identified a significant association between turnover intention with autonomous decision-making (OR: 0.28, CI: 0.14, 0.70) (Fig.  6 ) and promotion/development (OR: 0.67, CI: 0.46, 0.89) (Fig.  7 ). In both instances, the odds ratios suggest a negative association, signifying that increased levels of autonomous decision-making and promotion/development were linked to reduced odds of turnover intention.

Forest plot of the association between autonomous decision making with turnover intention among nurses in Ethiopia2024

Forest plot of the association between promotion/developpment with turnover intention among nurses in Ethiopia, 2024

In our comprehensive meta-analysis exploring turnover intention among nurses in Ethiopia, our findings revealed a pooled proportion of turnover intention at 53.35%. This significant proportion warrants a comparative analysis with turnover rates reported in other global regions. Distinct variations emerge when compared with turnover rates in Alexandria (68%), China (63.88%), and Jordan (60.9%) [ 5 , 6 , 7 ]. This comparison highlights that the multifaceted nature of turnover intention, influenced by diverse contextual, cultural, and organizational factors. Conversely, Ethiopia’s turnover rate among nurses contrasts with substantially lower figures reported in Israel (9%) [ 8 ], Brazil (21.1%) [ 9 ], and Saudi hospitals (26%) [ 10 ]. Challenges such as work overload, economic constraints, limited promotional opportunities, lack of recognition, and low job rewards are more prevalent among nurses in Ethiopia, contributing to higher turnover intention compared to their counterparts [ 7 , 29 , 36 ].

The highest turnover intention was observed in Addis Ababa, while Sidama region displayed the lowest turnover intention among nurses, These differences highlight the complexity of turnover intention among Ethiopian nurses, showing the importance of specific interventions in each region to address unique factors and improve nurses’ retention.

Our systematic review and meta-analysis in the Ethiopian nursing context revealed a significant inverse association between turnover intention and autonomous decision-making. The odd of turnover intention is approximately reduced by 72% in employees with autonomous decision-making compared to those without autonomous decision-making. This finding was supported by other similar studies conducted in South Africa, Tanzania, Kenya, and Turkey [ 37 , 38 , 39 , 40 ].

The significant association of turnover intention with promotion/development in our study underscores the crucial role of career advancement opportunities in alleviating turnover intention among nurses. Specifically, our analysis revealed that individuals with promotion/development had approximately 33% lower odds of turnover intention compared to those without such opportunities. These results emphasize the pivotal influence of organizational support in shaping the professional environment for nurses, providing substantive insights for the formulation of evidence-based strategies targeted at enhancing workforce retention. This finding is in line with former researches conducted in Taiwan, Philippines and Italy [ 41 , 42 , 43 ].

Our meta-analysis on turnover intention among Ethiopian nurses reveals a considerable challenge, with a pooled proportion of 53.35%. Regional variations highlight the necessity for region-specific strategies, with Addis Ababa displaying the highest turnover intention and Sidama region the lowest. A significant inverse association was found between turnover intention with autonomous decision-making and promotion/development. These insights support the formulation of evidence-based strategies and policies to enhance nurse retention, contributing to the overall stability of the Ethiopian healthcare system.

Recommendations

Federal ministry of health (fmoh).

The FMoH should consider the regional variations in turnover intention and formulate targeted retention strategies. Investment in professional development opportunities and initiatives to enhance autonomy can be integral components of these strategies.

Ethiopian nurses association (ENA)

ENA plays a pivotal role in advocating for the welfare of nurses. The association is encouraged to collaborate with healthcare institutions to promote autonomy, create mentorship programs, and advocate for improved working conditions to mitigate turnover intention.

Healthcare institutions

Hospitals and healthcare facilities should prioritize the provision of career advancement opportunities and recognize the value of professional autonomy in retaining nursing staff. Tailored interventions based on regional variations should be considered.

Policy makers

Policymakers should review existing healthcare policies to identify areas for improvement in nurse retention. Policy changes that address challenges such as work overload, limited promotional opportunities, and economic constraints can positively impact turnover rates.

Future research initiatives

Further research exploring the specific factors contributing to turnover intention in different regions of Ethiopia is recommended. Understanding the nuanced challenges faced by nurses in various settings will inform the development of more targeted interventions.

Strength and limitations

Our systematic review and meta-analysis on nurse turnover intention in Ethiopia present several strengths. The comprehensive inclusion of diverse studies provides a holistic view of the issue, enhancing the generalizability of our findings. The use of a random-effects model accounts for potential heterogeneity, ensuring a more robust and reliable synthesis of data.

However, limitations should be acknowledged. The heterogeneity observed across studies, despite the use of a random-effects model, may impact the precision of the pooled estimate. These considerations should be taken into account when interpreting and applying the results of our analysis.

Data availability

Data set used on this analysis will available from corresponding author upon reasonable request.

Abbreviations

Ethiopian Nurses Association

Federal Ministry of Health

Joanna Briggs Institute

Preferred Reporting Items for Systematic review and Meta-analysis Protocols

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Eshetu Elfios, Israel Asale, Merid Merkine, Temesgen Geta, Kidist Ashager, Getachew Nigussie, Ayele Agena & Bizuayehu Atinafu

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E.E. conceptualized the study, designed the research, performed statistical analysis, and led the manuscript writing. I.A, T.G, M.M contributed to the study design and provided critical revisions. K.A., G.N, B.A., E.I., and T.T. participated in data extraction and quality assessment. M.M. and T.G. K.A. and G.N. contributed to the literature review. I.A, A.A. and B.A. assisted in data interpretation. E.I. and T.T. provided critical revisions to the manuscript. All authors read and approved the final version.

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Elfios, E., Asale, I., Merkine, M. et al. Turnover intention and its associated factors among nurses in Ethiopia: a systematic review and meta-analysis. BMC Health Serv Res 24 , 662 (2024). https://doi.org/10.1186/s12913-024-11122-9

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• About Adverse Childhood Experiences
• Risk and Protective Factors
• Program: Essentials for Childhood: Preventing Adverse Childhood Experiences through Data to Action
• Adverse childhood experiences can have long-term impacts on health, opportunity and well-being.
• Adverse childhood experiences are common and some groups experience them more than others.

What are adverse childhood experiences?

Adverse childhood experiences, or ACEs, are potentially traumatic events that occur in childhood (0-17 years). Examples include: 1

• Experiencing violence, abuse, or neglect.
• Witnessing violence in the home or community.
• Having a family member attempt or die by suicide.

Also included are aspects of the child’s environment that can undermine their sense of safety, stability, and bonding. Examples can include growing up in a household with: 1

• Substance use problems.
• Mental health problems.
• Instability due to parental separation.
• Instability due to household members being in jail or prison.

The examples above are not a complete list of adverse experiences. Many other traumatic experiences could impact health and well-being. This can include not having enough food to eat, experiencing homelessness or unstable housing, or experiencing discrimination. 2 3 4 5 6

Quick facts and stats

ACEs are common. About 64% of adults in the United States reported they had experienced at least one type of ACE before age 18. Nearly one in six (17.3%) adults reported they had experienced four or more types of ACEs. 7

Preventing ACEs could potentially reduce many health conditions. Estimates show up to 1.9 million heart disease cases and 21 million depression cases potentially could have been avoided by preventing ACEs. 1

Some people are at greater risk of experiencing one or more ACEs than others. While all children are at risk of ACEs, numerous studies show inequities in such experiences. These inequalities are linked to the historical, social, and economic environments in which some families live. 5 6 ACEs were highest among females, non-Hispanic American Indian or Alaska Native adults, and adults who are unemployed or unable to work. 7

ACEs are costly. ACEs-related health consequences cost an estimated economic burden of $748 billion annually in Bermuda, Canada, and the United States. 8

ACEs can have lasting effects on health and well-being in childhood and life opportunities well into adulthood. 9 Life opportunities include things like education and job potential. These experiences can increase the risks of injury, sexually transmitted infections, and involvement in sex trafficking. They can also increase risks for maternal and child health problems including teen pregnancy, pregnancy complications, and fetal death. Also included are a range of chronic diseases and leading causes of death, such as cancer, diabetes, heart disease, and suicide. 1 10 11 12 13 14 15 16 17

ACEs and associated social determinants of health, such as living in under-resourced or racially segregated neighborhoods, can cause toxic stress. Toxic stress, or extended or prolonged stress, from ACEs can negatively affect children’s brain development, immune systems, and stress-response systems. These changes can affect children’s attention, decision-making, and learning. 18

Children growing up with toxic stress may have difficulty forming healthy and stable relationships. They may also have unstable work histories as adults and struggle with finances, jobs, and depression throughout life. 18 These effects can also be passed on to their own children. 19 20 21 Some children may face further exposure to toxic stress from historical and ongoing traumas. These historical and ongoing traumas refer to experiences of racial discrimination or the impacts of poverty resulting from limited educational and economic opportunities. 1 6

Adverse childhood experiences can be prevented. Certain factors may increase or decrease the risk of experiencing adverse childhood experiences.

Preventing adverse childhood experiences requires understanding and addressing the factors that put people at risk for or protect them from violence.

Creating safe, stable, nurturing relationships and environments for all children can prevent ACEs and help all children reach their full potential. We all have a role to play.

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• Sedlak A, Mettenburg J, Basena M, et al. Fourth national incidence study of child abuse and neglect (NIS-4): Report to Congress. Executive Summary. Washington, DC: U.S. Department of Health an Human Services, Administration for Children and Families.; 2010.
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• Swedo EA, Aslam MV, Dahlberg LL, et al. Prevalence of Adverse Childhood Experiences Among U.S. Adults — Behavioral Risk Factor Surveillance System, 2011–2020. MMWR Morb Mortal Wkly Rep 2023;72:707–715. DOI: http://dx.doi.org/10.15585/mmwr.mm7226a2 .
• Bellis, MA, et al. Life Course Health Consequences and Associated Annual Costs of Adverse Childhood Experiences Across Europe and North America: A Systematic Review and Meta-Analysis. Lancet Public Health 2019.
• Adverse Childhood Experiences During the COVID-19 Pandemic and Associations with Poor Mental Health and Suicidal Behaviors Among High School Students — Adolescent Behaviors and Experiences Survey, United States, January–June 2021 | MMWR
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• Schofield TJ, Lee RD, Merrick MT. Safe, stable, nurturing relationships as a moderator of intergenerational continuity of child maltreatment: a meta-analysis. J Adolesc Health. 2013;53(4 Suppl):S32-38. https://doi.org/10.1016/j.jadohealth.2013.05.004 .

Adverse Childhood Experiences (ACEs)

ACEs can have a tremendous impact on lifelong health and opportunity. CDC works to understand ACEs and prevent them.

Pregnancy Checklist

Be prepared for the big day with this pregnancy to-do list by trimester and month.

This article is based on reporting that features expert sources.

With all the logistics that arise with planning for conception and pregnancy, it’s no surprise that the 40-week-long endeavor brings out many challenges.

Whether you’re hoping for a positive pregnancy test in the near future or already have a baby on the way, here’s a list of useful tips to help with how to prepare for pregnancy.

First Trimester Pregnancy Checklist 

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During the first trimester, you’ll experience hormonal changes as your body demonstrates the earliest signs of pregnancy.

You may not know you’re pregnant during the first month of pregnancy. The first probable signs of pregnancy may appear around 12 to 15 days after ovulation at the earliest. This is when levels of human chorionic gonadotropin (hCG), a hormone produced by the placenta, are high enough to become detectable on a pregnancy test .

At this time, you may experience other presumptive signs of pregnancy, such as:

• Sore breasts
• A missed period
• Nausea and vomiting

During the first month, check a few early pregnancy tasks off your list, including:

• Choose your pregnancy and birth provider, like an OB-GYN, midwife or family medicine OB provider
• Select which hospital you plan to give birth at, if your provider has delivery privileges at multiple locations
• Schedule your initial prenatal appointment
• Treat any comorbid conditions and review your current medications, as some may need to be changed during pregnancy

Dr. Kecia Gaither, a double board-certified OB-GYN and maternal-fetal medicine provider, suggests treating conditions like:

• Thyroid disease
• Hypertension

“Comorbid conditions, especially uncontrolled diabetes, can significantly increase the risk of congenital abnormalities,” explains Gaither, who also serves as director of perinatal services and maternal-fetal medicine at New York City Health + Hospitals, Lincoln in the Bronx.

Congratulations! Month two is when most women discover their pregnancies.

As soon as you learn you're pregnant, it’s important to stop smoking , drinking or using drugs. Talk with your medical provider about which prescription medications you may need to start, stop or change at this time.

You will also likely begin taking supplements under the direction of your medical provider. Gaither emphasizes the importance of optimizing your pregnancy meal plan and maintaining healthy iron and folate levels for optimal fetal development.

This is because key fetal development occurs during month two, such as:

• Development of the neural tube, which will later become organs in the nervous system, like the brain and spinal cord
• Digestive tract development
• Bone formation

Month three

Month three is often an exciting time in pregnancy, when most people have the first chance to hear the baby’s heart rate. The heart rate may be detectable as early as six weeks, but most initial prenatal appointments occur between eight and 12 weeks.

By this point, you may already be experiencing morning sickness, which is nausea or vomiting, most commonly during the first three months of pregnancy.

To combat these symptoms, try:

• Eating small, frequent meals
• Staying hydrated
• Eating a small snack, like a few crackers, before getting out of bed

While morning sickness is common, reach out to your provider if you experience the following:

• Nausea or vomiting that is preventing you from your daily activities
• Inability to stay hydrated
• Feeling faint, dizzy or confused due to your symptoms
• Vomiting multiple times a day, unrelieved by home care

You may need a hydration infusion to keep you hydrated, or your provider may prescribe medications to combat your symptoms.

Second Trimester Checklist 

By the second trimester, the reality of preparing for a baby will start to set in. During this trimester, the early stages of nesting – a drive to prepare your home and lifestyle to accommodate your new addition – may begin.

Around week 10, you’ll have an opportunity to perform noninvasive prenatal genetic testing (NIPT), which uses the mother's blood to screen for chromosome balance and genetic conditions, such as Down syndrome.

By this time your pregnancy may also start to show. If you haven’t already, make sure to add some maternity and loose-fitting clothing to your wardrobe.

Dr. Andrea Braden, a board-certified OB-GYN and lactation consultant, suggests not to wait on purchasing new bras.

“Your breast size starts to increase during pregnancy and for preparation for nursing after," she explains. "Typically, you'll need to buy a new bra as it is, so I would say go ahead and buy bras that have the dual function of being a pregnancy bra in a nursing bra.”

Make sure that by month five, you have a stable exercise routine or movement plan to ensure a healthy pregnancy.

According to the American College of Obstetrics and Gynecology, exercise during pregnancy is essential to:

• Reduce aches and pains
• Relieve constipation
• Decrease the risk of pregnancy complications

Month five is also when you may feel some of the first signs of fetal movement.

Month six is a great opportunity to start the first stages of nesting.

Consider the following nesting activities:

• Planning baby purchases or creating a baby registry
• Planning for potential projects around the house or in the nursery
• If you are working, start to consider how you will handle medical leave and time off to recover after birth and bond with your baby

Third Trimester Checklist 

You’re in the final stretch! The third trimester is a great time to finalize your plans and preferences for labor and delivery.

Month seven

Taking a hospital birth class? Best to take it in the third trimester so your memory is fresh, explains Kristin Revere, the owner and founder of Gold Coast Doulas in Grand Rapids, Michigan. If you’re opting for a birth without an epidural, she explains you may consider taking birth classes like hypnobirthing or Lamaze as early as six weeks into pregnancy if you want to get a head start. This will help you mentally prepare to cope with labor pain.

Since you're starting your third trimester, it's a good idea to start preparing for your baby to enter the world.

• Choose your baby's pediatrician .
• Purchase a car seat and have it inspected and properly installed.
• Build a crib or bassinet for the nursery.

Month eight

By month eight, you may be experiencing significant pregnancy-related aches and pains or having trouble sleeping. Ashley Mareko, surrogate program director at Surrogate First, says she used acupuncture and chiropractic services throughout her pregnancy but began going once a week in her third trimester.

Many pregnant women, like Mareko, share anecdotal evidence of acupuncture and chiropractic services helping with reducing pregnancy and labor pain or assisting with labor induction. Researchers acknowledge that the body of evidence supporting acupuncture is limited, but ACOG does not discourage acupuncture or acupressure use in pregnancy. The American Pregnancy Association shares that there are no major concerns with chiropractic care during pregnancy.

At the beginning of month nine, it’s helpful to start planning for birth and the postpartum period.

Here are a few tips:

• Cook some make-ahead freezer meals for nutritious, easy meals after birth.
• Start packing your hospital bag for delivery , just in case the baby comes a few weeks early.
• Finalize your birth plan, and ask the hospital about any pertinent birth or visitation policies. 

Bottom Line

The course of your pregnancy will bring new challenges and learning experiences, and no two pregnancies are exactly the same. Consult with your pregnancy provider to get pregnancy advice tailored to your health and wellness.

Antidepressants During Pregnancy

Payton Sy June 1, 2023

The U.S. News Health team delivers accurate information about health, nutrition and fitness, as well as in-depth medical condition guides. All of our stories rely on multiple, independent sources and experts in the field, such as medical doctors and licensed nutritionists. To learn more about how we keep our content accurate and trustworthy, read our  editorial guidelines .

Braden is a board-certified OB-GYN based in Atlanta and a breastfeeding medicine specialist at Lybbie, a lactation innovation company.

Gaither is a double board-certified OB-GYN and maternal fetal medicine provider. She is also the director of perinatal services and maternal-fetal medicine at New York City Health and Hospitals, Lincoln in the Bronx.

Mareko is the surrogate program director at SurrogateFirst, a surrogacy matching service. She is based in Los Angeles.

Revere is the founder of Gold Coast Doulas in Grand Rapids, Michigan.

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