Evidence map›Paper›PMID 39348342›Full record

ArticlePloS one2024

Adaptation of unified protocol treatment for transdiagnostic disorders in Pakistan: A heuristic framework.

Asma Nisa, Salma Siddiqui, Amantia A Ametaj, Fahad Khan

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Trial
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Asma NisaDepartment of Behavioral Sciences, School of Social Sciences and Humanities, National University of Sciences and Technology, Islamabad, Pakistan.ORCID 0009-0007-5934-3381
Salma SiddiquiDepartment of Behavioral Sciences, School of Social Sciences and Humanities, National University of Sciences and Technology, Islamabad, Pakistan.
Amantia A AmetajInstitute for Health Equity and Social Justice, Northeastern University, Boston, Massachusetts, United States of America.
Fahad KhanKhalil Centre, Lombard, Illinois, United States of America.ORCID 0000-0002-4477-1494

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The access to evidence-based treatments for mental health problems is limited in low-resource settings. Transdiagnostic approaches, such as the Unified Protocol (UP), are a potential solution for these settings because they are multi-problem focused, modular, flexible, and have low complexity. This study aimed to adapt UP to the mental health context of an urban speciality clinic in Pakistan using a four-step process of heuristic framework. The study employed an iterative and stakeholder-based approach to align the protocol with local values, language, and needs. Primarily, the proposed modifications focus on language use, matching literacy level, graphical illustrations, and relevance of examples. A multi-method approach including expert review, cognitive interviewing, and adaptation testing ensured cultural equivalence. Participants diagnosed with depression and anxiety were provided culturally adapted treatment (N = 15) at the testing phase. Findings indicated that the participants not only experienced significant reductions in symptoms of depression and anxiety but also found the culturally adapted UP to be easy to understand, culturally relevant, and engaging. This study provides evidence that the UP can be culturally adapted and used in the mental health context of Pakistan. The findings suggest that the UP is a promising intervention for individuals with depression and anxiety in low-resource settings.

Indexed as

DepressionAdultAnxietyFemaleHumansMaleMiddle AgedPakistanYoung Adult

Identifiers

PMID39348342
PMCPMC11441672

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.