Author comment: Peer counseling for perinatal depression in low- and middle-income countries: A scoping review — R0/PR1
Bibliographic record
Abstract
Perinatal depression is associated with adverse maternal, newborn and child health outcomes. Treatment gaps and sociocultural factors contribute to its disproportionate burden in low- and middle-income countries (LMICs). Task-sharing approaches, such as peer counseling, have been developed to improve access to mental health services. We conducted a scoping review to map the current literature on peer counseling for perinatal women experiencing depression in LMICs. We searched CINAHL, MEDLINE, APA PsycINFO, Global Health and EMBASE for literature with no date limits. We included 73 records in our analysis, with most being systematic reviews and meta-analyses, randomized controlled trials and qualitative studies. Most studies were conducted in India and Pakistan and published from 2020 onward. The Thinking Healthy Program (THP) and its Peer-Delivered (THPP) adaptation were the most common interventions. Studies suggested effectiveness, feasibility, acceptability and transferability of peer counseling, particularly within the THPP, for perinatal depression. Studies indicated that local women, as peers and lay counselors, are preferred and effective implementation agents. Gaps in the evidence include those relating to understanding perinatal depression (e.g., contextual understandings of the etiology, comorbidity and heterogeneity and social conditions of psychosocial distress including long-term impacts on relationships and children’s development) and understanding and improving implementation. Further research on the adaptation, scaling up and integration of peer-delivered approaches with other approaches to improve impact are needed. There are also gaps in understanding the perspectives and experiences of peer counselors. Evidence gaps may stem from an emphasis on conventional public health approaches and measures derived from Western psychiatry, such as randomized controlled trials. There is relatively little research or implementation that prioritizes peer counselors in terms of understanding their perspectives and experiences (e.g., of professionalization), despite them being central to peer-delivered models. Task sharing has the potential to both empower peer counselors through mental health benefits and professional opportunities but also render peer counselors susceptible to vicarious exposure to traumatic stories and difficult situations amid limitations in available support. Better understanding counselors’ and perinatal women’s experiences can help decolonize the evidence base and improve implementation.
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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 | 0.034 | 0.229 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.019 | 0.013 |
| Insufficient payload (model declined to judge) | 0.019 | 0.008 |
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".