Assessment of a Pilot Program for Remote Support on Mental Health for Young Physicians in Rural Settings in Peru: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Telemedicine-based interventions show promise in addressing mental health issues among rural populations, yet evidence regarding their impact among the health care workforce in these contexts remains limited. OBJECTIVE: This study aimed to evaluate the characteristics and the responses and perceptions of recently graduated physicians who work in rural areas of Peru as part of the Servicio Rural Urbano Marginal en Salud (Rural-Urban Marginal Health Service [SERUMS], in Spanish) toward a telehealth intervention to provide remote orientation and accompaniment in mental health. METHODS: A mixed methods study was carried out involving physicians who graduated from the Universidad Nacional Mayor de San Marcos and participated in the Mental Health Accompaniment Program (MHAP) from August 2022 to February 2023. This program included the assessment of mental health conditions via online forms, the dissemination of informational materials through a website, and, for those with moderate or high levels of mental health issues, the provision of personalized follow-up by trained personnel. Quantitative analysis explored the mental health issues identified among physicians, while qualitative analysis, using semistructured interviews, examined their perceptions of the services provided. RESULTS: Of 75 physicians initially enrolled to the MHAP, 30 (41.6%) opted to undergo assessment and use the services. The average age of the participants was 26.8 (SD 1.9) years, with 17 (56.7%) being female. About 11 (36.7%) reported have current or previous mental health issues, 17 (56.7%) indicating some level of depression, 14 (46.7%) indicated some level of anxiety, 5 (16.6%) presenting a suicidal risk, and 2 (6.7%) attempted suicide during the program. Physicians who did not use the program services reported a lack of advertising and related information, reliance on personal mental health resources, or neglect of symptoms. Those who used the program expressed a positive perception regarding the services, including evaluation and follow-up, although some faced challenges accessing the website. CONCLUSIONS: The MHAP has been effective in identifying and managing mental health problems among SERUMS physicians in rural Peru, although it faced challenges related to access and participation. The importance of mental health interventions in this context is highlighted, with recommendations to improve accessibility and promote self-care among participants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".