Network and Factor Structure of Depression and Anxiety Symptoms in Telemental Healthcare Patients From Bangladesh: Evidence for Precision Mental Healthcare.
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| Title: | Network and Factor Structure of Depression and Anxiety Symptoms in Telemental Healthcare Patients From Bangladesh: Evidence for Precision Mental Healthcare. |
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| Authors: | Rahman, Md Hafizur (AUTHOR), Manna, Ridwana Maher (AUTHOR), Usmani, Nasimul Ghani (AUTHOR), Chandra, Pradip (AUTHOR), Amin, Md Bony (AUTHOR), Ara, Tasnu (AUTHOR), Amin, Md Robed (AUTHOR), Khan, Maruf Ahmed (AUTHOR), Ahmed, Helal Uddin (AUTHOR), Akter, Ema (AUTHOR), Islam, S. M. Hasibul (AUTHOR), Ahmed, Anisuddin (AUTHOR), Shomik, Mohammad Sohel (AUTHOR), Arifeen, Shams El (AUTHOR), Hossain, Aniqa Tasnim (AUTHOR), Rahman, Ahmed Ehsanur (AUTHOR), Bosurgi, Raffaella (AUTHOR) |
| Source: | Depression & Anxiety (1091-4269). 6/17/2026, Vol. 2026, p1-12. 12p. |
| Subjects: | Mental depression, Anxiety, Factor analysis, Symptoms, Mental health services, Medical telematics, Data analysis |
| Geographic Terms: | Bangladesh |
| Abstract: | Background: Identifying core mental health symptoms is crucial for precision‐targeted interventions, especially in resource‐limited settings. However, symptom structures among individuals actively seeking telemental healthcare remain underexplored in Bangladesh and similar contexts. This study aimed to map symptom severity, factor structures, and interrelationships between depressive and anxiety symptoms to inform precision‐driven mental healthcare approaches. Methods: We conducted an observational study among 4,900 patients who attended a health facility‐based telemental healthcare in Bangladesh from January 2023 to July 2024. We assessed depression using PHQ‐9 and anxiety using GAD‐7 and applied exploratory factor analysis and network analysis. Results: Overall, 84% (95% CI: 83–86) screened positive for depressive symptoms, 85% (95% CI: 83–86) screened positive for anxiety symptoms, and 77% (95% CI: 76–78) presented co‐occurring symptoms. Commonly reported symptoms included fatigue (57%), anhedonia (42%), sleep disturbance (42%), nervousness (70%), and uncontrollable worrying (66%). Factor analysis revealed "depressed mood" (λ = 0.58) and "anhedonia" (λ = 0.51) as core depressive features, and "uncontrollable worry" (λ = 0.68) and "nervousness" (λ = 0.61) as core anxiety features. Network analysis revealed strong associations between "anhedonia" and "depressed mood" in depression and "trouble relaxing" and "restlessness" in anxiety. "Uncontrollable worrying" showed the highest centrality, and "sleep disturbance" and "trouble relaxing" served as important bridge symptoms linking depression and anxiety domains. Conclusions: Depressive and anxiety symptoms in people seeking telemental healthcare cluster around a small number of key and connecting symptoms, rather than contributing equally to overall distress. Precision mental healthcare in resource‐limited settings can use this structure to direct limited time and resources toward the symptoms that matter most. Protocol Registration: Institutional Review Board (IRB) of https://www.icddrb.org/. Protocol number: PR‐22103. [ABSTRACT FROM AUTHOR] |
| Copyright of Depression & Anxiety (1091-4269) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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