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Record W4283366153 · doi:10.2196/37211

Adaptation of a Problem-solving Program (Friendship Bench) to Treat Common Mental Disorders Among People Living With HIV and AIDS and on Methadone Maintenance Treatment in Vietnam: Formative Study

2022· article· en· W4283366153 on OpenAlexvenueno aff
Trần Việt Hà, Ha T. T. Nong, Thuy Thi Thu Tran, Teresa Filipowicz, Kelsey R. Landrum, Brian W. Pence, Lê Minh Giang, Minh X. Nguyen, Dixon Chibanda, Ruth Verhey, Vivian F. Go, Hien Thi Ho, Bradley N. Gaynes

Bibliographic record

VenueJMIR Formative Research · 2022
Typearticle
Languageen
FieldHealth Professions
TopicProblem Solving Skills Development
Canadian institutionsnot available
FundersNational Institute on Drug Abuse
KeywordsAdaptation (eye)Mental healthMethadoneMedicineMethadone maintenancePsychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The prevalence of common mental disorders (CMDs) among people living with HIV and people who inject drugs is high worldwide and in Vietnam. However, few evidence-informed CMD programs for people living with HIV who inject drugs have been adapted for use in Vietnam. We adapted the Friendship Bench (FB), a problem-solving therapy (PST)-based program that was successfully implemented among patients with CMDs in primary health settings in Zimbabwe and Malawi for use among people living with HIV on methadone maintenance treatment (MMT) with CMDs in Hanoi, Vietnam. OBJECTIVE: This study aimed to describe the adaptation process with a detailed presentation of 4 phases from the third (adaptation) to the sixth (integration) of the Assessment-Decision-Adaptation-Production-Topical Experts-Integration-Training-Testing (ADAPT-ITT) framework. METHODS: The adaptation phase followed a qualitative study design to explore symptoms of CMDs, facilitators, and barriers to conducting FB for people living with HIV on MMT in Vietnam, and patient, provider, and caretaker concerns about FB. In the production phase, we revised the original program manual and developed illustrated PST cases. In the topical expert and integration phases, 2 investigators (BNG and BWP) and 3 subject matter experts (RV, DC, and GML) reviewed the manual, with reviewer comments incorporated in the final, revised manual to be used in the training. The draft program will be used in the training and testing phases. RESULTS: The study was methodologically aligned with the ADAPT-ITT goals as we chose a proven, effective program for adaptation. Insights from the adaptation phase addressed the who, where, when, and how of FB program implementation in the MMT clinics. The ADAPT-ITT framework guided the appropriate adaptation of the program manual while maintaining the core components of the PST of the original program throughout counseling techniques in all program sessions. The deliverable of this study was an adapted FB manual to be used for training and piloting to make a final program manual. CONCLUSIONS: This study successfully illustrated the process of operationalizing the ADAPT-ITT framework to adapt a mental health program in Vietnam. This study selected and culturally adapted an evidence-informed PST program to improve CMDs among people living with HIV on MMT in Vietnam. This adapted program has the potential to effectively address CMDs among people living with HIV on MMT in Vietnam. TRIAL REGISTRATION: ClinicalTrials.gov NCT04790201; https://clinicaltrials.gov/ct2/show/NCT04790201.

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)0.022
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.046
GPT teacher head0.416
Teacher spread0.370 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations12
Published2022
Admission routes1
Has abstractyes

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