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Record W4410398032 · doi:10.1186/s43058-025-00731-y

The Consolidated Approach to Intervention Adaptation (CLARION): Developing and undertaking an empirically and theoretically driven intervention adaptation

2025· article· en· W4410398032 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueImplementation Science Communications · 2025
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsUniversité de MontréalUniversité du Québec en OutaouaisCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalMcGill University Health CentreSt Mary's Hospital CentreJewish General HospitalUniversity of British ColumbiaMcGill University
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchCanada Excellence Research Chairs, Government of CanadaRéseau de recherche portant sur les interventions en sciences infirmières du Québec
KeywordsCLARIONAdaptation (eye)Intervention (counseling)OperationalizationPaceContext (archaeology)Psychological interventionComputer scienceProcess managementPsychologyEngineeringNeuroscienceArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Intervention adaptation, the deliberate modification of the design or delivery of interventions to a new context, is more resource efficient than de novo development. However, adaptation must be approached methodically, as some modifications, such as those to the core components, may compromise the intervention's initial efficacy. While adaptation frameworks have been published, none have been identified as more likely to result in successful adaptations. Further, frameworks lack the step-by-step details needed for operationalization. Therefore, the goal of this paper is to share our experience in addressing these methodological limitations in intervention adaptation. The objectives were to describe: 1) our development of a step-by-step, theoretically and empirically driven approach to intervention adaptation labelled the ConsoLidated AppRoach to Intervention adaptatiON (CLARION), 2) the application of CLARION in adapting a depression self-management intervention, 3) the facilitators and challenges encountered when using CLARION. METHODS: The development of CLARION was informed by the Medical Research Council guidance, the Method for Program Adaptation through Community Engagement (M-PACE), and a published scoping review identifying the key steps in existing adaptation frameworks. M-PACE was selected for its patient-oriented research principles, its application to a similar complex intervention, and for offering some of the specificity needed for execution. However, the scoping review indicated that M-PACE lacked three critical steps: selecting a candidate intervention, understanding its core components, and pre-testing the adapted intervention. These were added to form CLARION, which was structured in two stages: the first involves selecting an intervention, identifying core components, and deciding on modifications; the second stage solicits interest stakeholder feedback to assess the acceptability of the preliminary adapted intervention (pre-test). RESULTS: Once CLARION was developed, it was put into action to adapt a depression self-management intervention. CLARION demonstrated several strengths: 1) clearly articulating core components before deciding on modifications, 2) mobilizing a diverse steering committee of experts, including patient partners and developers of the original intervention, which balanced input and efficiency, and 3) establishing committee decision-making rules prior to adjudication (specific criteria and 75% supermajority). Key challenges included defining the types of modifications requiring committee input, determining the extent of the committee's involvement, and prioritizing the presence of all committee members at meetings to avoid difficulties integrating incongruent feedback. CONCLUSIONS: The development of CLARION contributes to best practices for intervention adaptation by identifying step-by-step guidance as well as facilitators and barriers to its application.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.662
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.184
GPT teacher head0.538
Teacher spread0.354 · 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