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Record W4403546596 · doi:10.1017/gmh.2024.73

Peer counseling for perinatal depression in low- and middle-income countries: A scoping review

2024· review· en· W4403546596 on OpenAlexaff
Alexander Cuncannon, Aneel Singh Brar, Aliyah Dosani

Bibliographic record

VenueCambridge Prisms Global Mental Health · 2024
Typereview
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsMount Royal UniversityAlberta Children's HospitalUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsPsycINFOPsychosocialCINAHLMedicinePsychological interventionMental healthMEDLINEGlobal mental healthSystematic reviewAntenatal depressionPsychiatryPsychologyClinical psychologyAnxiety

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0110.012
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.040
GPT teacher head0.407
Teacher spread0.366 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

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