Pub Date : 2026-01-05DOI: 10.1016/j.ajp.2026.104835
Rajiv Tandon
{"title":"The Asian Journal of Psychiatry: An end of year review 2025","authors":"Rajiv Tandon","doi":"10.1016/j.ajp.2026.104835","DOIUrl":"10.1016/j.ajp.2026.104835","url":null,"abstract":"","PeriodicalId":8543,"journal":{"name":"Asian journal of psychiatry","volume":"116 ","pages":"Article 104835"},"PeriodicalIF":4.5,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-04DOI: 10.1016/j.ajp.2026.104831
Tsz Lam Chan , Valerie Yan Tung Siu , Shan-yan Huang , Amos En Zhe Lian , Marc Eric S. Reyes , Görkem Derin , Aslı Dila Akiş , Audrey Zatopek , Stanley Kam Ki Lam , Peejay D. Bengwasan , Hong Wang Fung
Whether functional neurological symptom disorder should be classified as a dissociative disorder remains a subject of debate. This multi-site, cross-cultural study investigated functional neurological symptoms and psychoform dissociation among college students in the Philippines (N = 219), Turkey (N = 160), Malaysia (N = 240), and Taiwan (N = 766). Across the four samples, between 50.0 % and 74.2 % of participants with functional neurological symptoms exhibited co-occurring psychoform dissociative symptoms. Controlling for confounding variables (e.g., age, gender, childhood adversities, and symptoms of depression, anxiety, and complex PTSD), psychoform dissociative symptoms emerged as the strongest and most robust correlate of functional neurological symptoms in three out of four samples (Philippines: β = .502, Turkey: β = .665, Malaysia: β = .541). Psychoform dissociative symptoms were also significantly associated with functional neurological symptoms in the Taiwan sample (β = .122), although not the strongest predictor. The results that were replicated across four culturally different samples support classifying functional neurological symptom disorder as possibly dissociative in nature in future ICD and DSM. Individuals who present with functional neurological symptoms should be screened for dissociative disorders.
{"title":"Functional neurological symptoms and their correlates across four Asian samples: Should they be classified as a dissociative disorder?","authors":"Tsz Lam Chan , Valerie Yan Tung Siu , Shan-yan Huang , Amos En Zhe Lian , Marc Eric S. Reyes , Görkem Derin , Aslı Dila Akiş , Audrey Zatopek , Stanley Kam Ki Lam , Peejay D. Bengwasan , Hong Wang Fung","doi":"10.1016/j.ajp.2026.104831","DOIUrl":"10.1016/j.ajp.2026.104831","url":null,"abstract":"<div><div>Whether functional neurological symptom disorder should be classified as a dissociative disorder remains a subject of debate. This multi-site, cross-cultural study investigated functional neurological symptoms and psychoform dissociation among college students in the Philippines (N = 219), Turkey (N = 160), Malaysia (N = 240), and Taiwan (N = 766). Across the four samples, between 50.0 % and 74.2 % of participants with functional neurological symptoms exhibited co-occurring psychoform dissociative symptoms. Controlling for confounding variables (e.g., age, gender, childhood adversities, and symptoms of depression, anxiety, and complex PTSD), psychoform dissociative symptoms emerged as the strongest and most robust correlate of functional neurological symptoms in three out of four samples (Philippines: β = .502, Turkey: β = .665, Malaysia: β = .541). Psychoform dissociative symptoms were also significantly associated with functional neurological symptoms in the Taiwan sample (β = .122), although not the strongest predictor. The results that were replicated across four culturally different samples support classifying functional neurological symptom disorder as possibly dissociative in nature in future ICD and DSM. Individuals who present with functional neurological symptoms should be screened for dissociative disorders.</div></div>","PeriodicalId":8543,"journal":{"name":"Asian journal of psychiatry","volume":"116 ","pages":"Article 104831"},"PeriodicalIF":4.5,"publicationDate":"2026-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-04DOI: 10.1016/j.ajp.2026.104830
D. Swainson Sujana, Peter Augustin D
In deep learning, the robustness and generalizability of models significantly depend on diverse and heterogeneous training data. Acquiring such an extensive dataset is challenging in fields like disorder prediction due to data scarcity, which can be attributed to factors such as privacy concerns, limited patient population, or inadequate facilities. Data augmentation can be an ideal solution to this problem, particularly in the field of disorder prediction, like autism, using medical imaging. Data augmentation can expand and balance datasets by generating high-quality and varied data, thereby improving the generalizability of deep learning models. This study proposed two types of augmentation methods: 1. Spatial level 2. Intensity level augmentation techniques. Eight different levels of augmentations were experimented with across these categories. This study found that the combination of spatial and intensity level augmentations enhanced the model’s generalizability and robustness, achieving an AUC value of 0.7433. Additionally, it was observed that the Left to Right flip method, under spatial augmentation, diminished the model’s performance, whereas random noise injection, under intensity level augmentation, improved prediction accuracy.
{"title":"The effect of spatial and intensity level augmentation of structural magnetic resonance images on autism diagnosis model","authors":"D. Swainson Sujana, Peter Augustin D","doi":"10.1016/j.ajp.2026.104830","DOIUrl":"10.1016/j.ajp.2026.104830","url":null,"abstract":"<div><div>In deep learning, the robustness and generalizability of models significantly depend on diverse and heterogeneous training data. Acquiring such an extensive dataset is challenging in fields like disorder prediction due to data scarcity, which can be attributed to factors such as privacy concerns, limited patient population, or inadequate facilities. Data augmentation can be an ideal solution to this problem, particularly in the field of disorder prediction, like autism, using medical imaging. Data augmentation can expand and balance datasets by generating high-quality and varied data, thereby improving the generalizability of deep learning models. This study proposed two types of augmentation methods: 1. Spatial level 2. Intensity level augmentation techniques. Eight different levels of augmentations were experimented with across these categories. This study found that the combination of spatial and intensity level augmentations enhanced the model’s generalizability and robustness, achieving an AUC value of 0.7433. Additionally, it was observed that the Left to Right flip method, under spatial augmentation, diminished the model’s performance, whereas random noise injection, under intensity level augmentation, improved prediction accuracy.</div></div>","PeriodicalId":8543,"journal":{"name":"Asian journal of psychiatry","volume":"116 ","pages":"Article 104830"},"PeriodicalIF":4.5,"publicationDate":"2026-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145916666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-04DOI: 10.1016/j.ajp.2026.104832
Zahid Hyder Wadani
{"title":"Strengthening maternal mental health through Collaborative Care Model: A scalable opportunity for LMICs","authors":"Zahid Hyder Wadani","doi":"10.1016/j.ajp.2026.104832","DOIUrl":"10.1016/j.ajp.2026.104832","url":null,"abstract":"","PeriodicalId":8543,"journal":{"name":"Asian journal of psychiatry","volume":"116 ","pages":"Article 104832"},"PeriodicalIF":4.5,"publicationDate":"2026-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145916659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1016/j.ajp.2025.104826
Abanoub Riad , Muhammad Alkasaby , Nisarat Changchroenkul , Michal Koščík
Background
Research excellence is increasingly used as a benchmark for academic evaluation in medical sciences, including psychiatry. However, bibliometric analyses often prioritize productivity over quality. This study examined national, institutional, and individual determinants of psychiatric research excellence using a multi-level ecological framework.
Methods
We analyzed the Stanford–Elsevier Lists of the top 2 % scholars (2017–2023), incorporating 51 independent variables. These included: (a) national determinants grouped into five domains (mental healthcare, gender equity, socioeconomic development, budgetary policies, and disease burden), (b) institutional factors derived from global and discipline-specific rankings, and (c) individual factors of gender and academic age. The primary outcome was the number of excellent psychiatric scholars (EPS), with secondary indicators including citation counts, modified H-index, composite score, and self-citation share.
Results
Psychiatric research excellence was concentrated in high-income, English-speaking countries, with significant institutional elitism. A small number of institutions hosted a disproportionate share of EPS. Gender disparities persisted, with female representation negatively associated with national gender gaps in employment and education, but positively linked to government spending on education. Academic age positively correlated with citation-based performance metrics. Multivariable models confirmed the explanatory roles of gender, academic age, official language, gender equity, and human development.
Conclusion
Psychiatric research excellence reflects systemic advantages related to income, language, institutional prestige, and gender equity. Equitable funding, support for emerging research environments, and expanded international collaboration are essential to fostering broader participation in high-impact psychiatric research.
{"title":"National-, institutional-, and individual-level determinants of psychiatric research excellence: Analysis of Stanford-Elsevier lists of the top 2 % scholars worldwide (2017–2023)","authors":"Abanoub Riad , Muhammad Alkasaby , Nisarat Changchroenkul , Michal Koščík","doi":"10.1016/j.ajp.2025.104826","DOIUrl":"10.1016/j.ajp.2025.104826","url":null,"abstract":"<div><h3>Background</h3><div>Research excellence is increasingly used as a benchmark for academic evaluation in medical sciences, including psychiatry. However, bibliometric analyses often prioritize productivity over quality. This study examined national, institutional, and individual determinants of psychiatric research excellence using a multi-level ecological framework.</div></div><div><h3>Methods</h3><div>We analyzed the Stanford–Elsevier Lists of the top 2 % scholars (2017–2023), incorporating 51 independent variables. These included: (a) national determinants grouped into five domains (mental healthcare, gender equity, socioeconomic development, budgetary policies, and disease burden), (b) institutional factors derived from global and discipline-specific rankings, and (c) individual factors of gender and academic age. The primary outcome was the number of excellent psychiatric scholars (EPS), with secondary indicators including citation counts, modified H-index, composite score, and self-citation share.</div></div><div><h3>Results</h3><div>Psychiatric research excellence was concentrated in high-income, English-speaking countries, with significant institutional elitism. A small number of institutions hosted a disproportionate share of EPS. Gender disparities persisted, with female representation negatively associated with national gender gaps in employment and education, but positively linked to government spending on education. Academic age positively correlated with citation-based performance metrics. Multivariable models confirmed the explanatory roles of gender, academic age, official language, gender equity, and human development.</div></div><div><h3>Conclusion</h3><div>Psychiatric research excellence reflects systemic advantages related to income, language, institutional prestige, and gender equity. Equitable funding, support for emerging research environments, and expanded international collaboration are essential to fostering broader participation in high-impact psychiatric research.</div></div>","PeriodicalId":8543,"journal":{"name":"Asian journal of psychiatry","volume":"116 ","pages":"Article 104826"},"PeriodicalIF":4.5,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although several psychotherapeutic interventions have been introduced for patients receiving maintenance hemodialysis (MHD), challenges such as feelings of shame persist. Prior studies indicate that robot-assisted interviews evoke less shame than human interactions. The Technology Acceptance Model (TAM) provides a robust framework for examining factors influencing technology adoption. This study applied TAM to evaluate the use of a communication robot (Sota-100) in psychotherapeutic interventions for patients with MHD.
Methods
Twenty-six outpatients with MHD participated. Each completed an interaction session with Sota-100 and a self-report questionnaire using a 5-point Likert scale.
Results
The intention to use Sota-100 counseling was significantly higher than that for human counseling (p = 0.003). A Wilcoxon signed-rank test confirmed that Sota-100 was easy to use (p = 0.023). Spearman’s correlation showed significant associations between ease of use and perceived usefulness in reducing anxiety and stress (p = 0.028), decreasing boredom and loneliness (p < 0.001), enhancing motivation for self-administration (p = 0.004), and intention to use Sota-100 (p = 0.005).
Conclusion
Most patients with MHD were receptive to Sota-100, supporting the applicability of TAM. Improving robot usability could further alleviate anxiety, stress, boredom, and loneliness, enhance self-management motivation, and strengthen patients’ willingness to engage with robotic support in psychosocial care.
{"title":"Acceptance of communication robots among patients undergoing maintenance hemodialysis with psychological stress","authors":"Hirokazu Kumazaki, Hiroko Kamide, Megumi Kawata, Yuka Nakazawa, Shun Shimoguchi, Kenta Torigoe, Tomoya Nishino, Yuichiro Yoshikawa, Hiroshi Ishiguro","doi":"10.1016/j.ajp.2025.104811","DOIUrl":"10.1016/j.ajp.2025.104811","url":null,"abstract":"<div><h3>Objective</h3><div>Although several psychotherapeutic interventions have been introduced for patients receiving maintenance hemodialysis (MHD), challenges such as feelings of shame persist. Prior studies indicate that robot-assisted interviews evoke less shame than human interactions. The Technology Acceptance Model (TAM) provides a robust framework for examining factors influencing technology adoption. This study applied TAM to evaluate the use of a communication robot (Sota-100) in psychotherapeutic interventions for patients with MHD.</div></div><div><h3>Methods</h3><div>Twenty-six outpatients with MHD participated. Each completed an interaction session with Sota-100 and a self-report questionnaire using a 5-point Likert scale.</div></div><div><h3>Results</h3><div>The intention to use Sota-100 counseling was significantly higher than that for human counseling (p = 0.003). A Wilcoxon signed-rank test confirmed that Sota-100 was easy to use (p = 0.023). Spearman’s correlation showed significant associations between ease of use and perceived usefulness in reducing anxiety and stress (p = 0.028), decreasing boredom and loneliness (p < 0.001), enhancing motivation for self-administration (p = 0.004), and intention to use Sota-100 (p = 0.005).</div></div><div><h3>Conclusion</h3><div>Most patients with MHD were receptive to Sota-100, supporting the applicability of TAM. Improving robot usability could further alleviate anxiety, stress, boredom, and loneliness, enhance self-management motivation, and strengthen patients’ willingness to engage with robotic support in psychosocial care.</div></div>","PeriodicalId":8543,"journal":{"name":"Asian journal of psychiatry","volume":"116 ","pages":"Article 104811"},"PeriodicalIF":4.5,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145916650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Association between Muslim population, legal status, political system, geography, income category, human development index, and suicide rates in Asian countries: An ecological analysis","authors":"S.M. Yasir Arafat, Marthoenis Marthoenis, Rizwana Amin, David Lester, Nafia Farzana Chowdhury, Mohsen Rezaeian","doi":"10.1016/j.ajp.2025.104825","DOIUrl":"10.1016/j.ajp.2025.104825","url":null,"abstract":"","PeriodicalId":8543,"journal":{"name":"Asian journal of psychiatry","volume":"116 ","pages":"Article 104825"},"PeriodicalIF":4.5,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145916675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1016/j.ajp.2026.104828
Ezgi Cellat , Emre Demir
Objective
The aim of this study is to analyze AI-based scientific publications in psychiatry using bibliometric methods to identify prominent themes, research trends, and future opportunities.
Methods
Original articles published between 1980 and 2025 and indexed in the “Psychiatry” category of the Web of Science were screened. The search strategy included keywords such as “artificial intelligence,” “machine learning,” and “deep learning.” A total of 2328 original research articles were included in the analysis. Bibliometric analyses were conducted using the Bibliometrix package in RStudio. Publication trends over the years, keyword analysis, trend analysis, and factor analysis were applied.
Results
Keyword analyses revealed that themes such as depressive disorders, schizophrenia, suicide, anxiety, bipolar disorder, psychosis, and digital health were central. Trend analyses showed that neurobiological markers dominated between 2014 and 2017; early psychosis, symptom severity, and fMRI were prominent between 2018 and 2020; and neurodegenerative disorders and connectivity concepts gained importance after 2021. The rise of themes such as “mental health,” “digital health,” and “interpretability” in 2024–2025 reflects both the digitalization of healthcare delivery and the growing demand for algorithmic transparency.
Conclusion
The findings indicate that AI in psychiatry holds transformative potential not only for diagnosis and prediction but also for digital health, personalized treatment, ethical governance, and community mental health. Moreover, the intensive examination of focus areas such as depression, schizophrenia, and suicide highlights the strong alignment of the field with clinical priorities. However, external validity, data heterogeneity, explainability, and ethical integration remain critical research gaps to be addressed.
目的：本研究的目的是使用文献计量学方法分析基于人工智能的精神病学科学出版物，以确定突出的主题、研究趋势和未来机会。方法：筛选发表于1980 - 2025年间并收录于Web of Science“精神病学”分类的原创文章。搜索策略包括“人工智能”、“机器学习”和“深度学习”等关键词。共有2328篇原创研究论文被纳入分析。使用RStudio中的Bibliometrix软件包进行文献计量学分析。运用关键词分析、趋势分析、因子分析等方法对历年出版趋势进行分析。结果：关键词分析显示，抑郁症、精神分裂症、自杀、焦虑、双相情感障碍、精神病和数字健康等主题是中心。趋势分析显示，2014年至2017年，神经生物学标志物占主导地位；2018 - 2020年早期精神病、症状严重程度、fMRI表现突出；神经退行性疾病和连接概念在2021年之后变得重要起来。2024-2025年“心理健康”、“数字健康”和“可解释性”等主题的兴起，既反映了医疗保健服务的数字化，也反映了对算法透明度日益增长的需求。结论：研究结果表明，精神病学中的人工智能不仅在诊断和预测方面具有变革潜力，而且在数字健康、个性化治疗、伦理治理和社区心理健康方面也具有变革潜力。此外，对抑郁症、精神分裂症和自杀等重点领域的深入研究突出了该领域与临床优先事项的强烈一致性。然而，外部有效性、数据异质性、可解释性和伦理整合仍然是需要解决的关键研究空白。
{"title":"Artificial intelligence in psychiatry: Current and emerging trends, clinical applications, and research gaps explored through a bibliometric analysis","authors":"Ezgi Cellat , Emre Demir","doi":"10.1016/j.ajp.2026.104828","DOIUrl":"10.1016/j.ajp.2026.104828","url":null,"abstract":"<div><h3>Objective</h3><div>The aim of this study is to analyze AI-based scientific publications in psychiatry using bibliometric methods to identify prominent themes, research trends, and future opportunities.</div></div><div><h3>Methods</h3><div>Original articles published between 1980 and 2025 and indexed in the “Psychiatry” category of the Web of Science were screened. The search strategy included keywords such as “artificial intelligence,” “machine learning,” and “deep learning.” A total of 2328 original research articles were included in the analysis. Bibliometric analyses were conducted using the Bibliometrix package in RStudio. Publication trends over the years, keyword analysis, trend analysis, and factor analysis were applied.</div></div><div><h3>Results</h3><div>Keyword analyses revealed that themes such as depressive disorders, schizophrenia, suicide, anxiety, bipolar disorder, psychosis, and digital health were central. Trend analyses showed that neurobiological markers dominated between 2014 and 2017; early psychosis, symptom severity, and fMRI were prominent between 2018 and 2020; and neurodegenerative disorders and connectivity concepts gained importance after 2021. The rise of themes such as “mental health,” “digital health,” and “interpretability” in 2024–2025 reflects both the digitalization of healthcare delivery and the growing demand for algorithmic transparency.</div></div><div><h3>Conclusion</h3><div>The findings indicate that AI in psychiatry holds transformative potential not only for diagnosis and prediction but also for digital health, personalized treatment, ethical governance, and community mental health. Moreover, the intensive examination of focus areas such as depression, schizophrenia, and suicide highlights the strong alignment of the field with clinical priorities. However, external validity, data heterogeneity, explainability, and ethical integration remain critical research gaps to be addressed.</div></div>","PeriodicalId":8543,"journal":{"name":"Asian journal of psychiatry","volume":"116 ","pages":"Article 104828"},"PeriodicalIF":4.5,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145916740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1016/j.ajp.2026.104829
Anxin Wen
{"title":"Looking closer at the numbers: Outcome reporting and priority groups in Qatar’s evolving mental health system","authors":"Anxin Wen","doi":"10.1016/j.ajp.2026.104829","DOIUrl":"10.1016/j.ajp.2026.104829","url":null,"abstract":"","PeriodicalId":8543,"journal":{"name":"Asian journal of psychiatry","volume":"116 ","pages":"Article 104829"},"PeriodicalIF":4.5,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145910288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1016/j.ajp.2025.104814
Tian Ruan , Minghang Li
Objective
To synthesize empirical evidence on the association between post-traumatic growth (PTG) and job burnout among medical staff across varied healthcare settings during the COVID-19 normalization period (2022 onward).
Methods
Following PRISMA guidelines, a database indexing over 126 million records was searched, yielding 499 records for screening, and 11 studies that measured both PTG and burnout in active healthcare professionals. Data on study design, setting, instruments, sample characteristics, and key findings were extracted.
Results
Nine quantitative (seven cross-sectional, one longitudinal, one unspecified design) and two qualitative studies met inclusion criteria, encompassing nurses, physicians, psychiatrists, paramedics, and medical rescuers in eight countries. Standardized instruments (e.g., Post-Traumatic Growth Inventory variants; Maslach Burnout Inventory variants) were most common. Eight studies reported a significant inverse correlation between PTG and burnout (e.g., odds ratio= 0.653, 95 % CI= 0.525–0.812, p < 0.001; r = –0.276, p = 0.034). Five studies identified PTG as a mediator or moderator of stress–burnout pathways. Qualitative analyses described a trajectory from acute stress through cognitive restructuring to growth, with burnout linked to unresolved trauma.
Conclusions
Consistent evidence indicates that higher PTG protects against burnout in medical staff post-pandemic peak. Psychological resources—resilience, self-compassion, adaptive coping, meaning in work, and job satisfaction—emerge as key mediators or moderators. Interventions fostering PTG and its correlates may mitigate burnout in healthcare workers.
{"title":"The inverse relationship between post-traumatic growth and job burnout among medical staff during the COVID-19 normalization period: A systematic review","authors":"Tian Ruan , Minghang Li","doi":"10.1016/j.ajp.2025.104814","DOIUrl":"10.1016/j.ajp.2025.104814","url":null,"abstract":"<div><h3>Objective</h3><div>To synthesize empirical evidence on the association between post-traumatic growth (PTG) and job burnout among medical staff across varied healthcare settings during the COVID-19 normalization period (2022 onward).</div></div><div><h3>Methods</h3><div>Following PRISMA guidelines, a database indexing over 126 million records was searched, yielding 499 records for screening, and 11 studies that measured both PTG and burnout in active healthcare professionals. Data on study design, setting, instruments, sample characteristics, and key findings were extracted.</div></div><div><h3>Results</h3><div>Nine quantitative (seven cross-sectional, one longitudinal, one unspecified design) and two qualitative studies met inclusion criteria, encompassing nurses, physicians, psychiatrists, paramedics, and medical rescuers in eight countries. Standardized instruments (e.g., Post-Traumatic Growth Inventory variants; Maslach Burnout Inventory variants) were most common. Eight studies reported a significant inverse correlation between PTG and burnout (e.g., odds ratio= 0.653, 95 % CI= 0.525–0.812, p < 0.001; r = –0.276, p = 0.034). Five studies identified PTG as a mediator or moderator of stress–burnout pathways. Qualitative analyses described a trajectory from acute stress through cognitive restructuring to growth, with burnout linked to unresolved trauma.</div></div><div><h3>Conclusions</h3><div>Consistent evidence indicates that higher PTG protects against burnout in medical staff post-pandemic peak. Psychological resources—resilience, self-compassion, adaptive coping, meaning in work, and job satisfaction—emerge as key mediators or moderators. Interventions fostering PTG and its correlates may mitigate burnout in healthcare workers.</div></div>","PeriodicalId":8543,"journal":{"name":"Asian journal of psychiatry","volume":"116 ","pages":"Article 104814"},"PeriodicalIF":4.5,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145916722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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