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Record W4417485504 · doi:10.1017/cts.2025.10219

Fidelity of intervention delivery in psychosocial and behavioral programs (FIPP): A modified Delphi study and final guideline

2025· article· en· W4417485504 on OpenAlexafffund
Mackenzie Martin, Alicia C. Bunger, EB Caron, Mary Dozier, Jamie M. Lachman, Joanne Nicholson, Marija Raleva, Rachel C. Shelton, Yulia Shenderovich, Kirsty Sprange, Elaine Toomey, Susan M. Breitenstein

Bibliographic record

VenueJournal of Clinical and Translational Science · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsMacEwan University
FundersSocial Sciences and Humanities Research Council of CanadaHealth and Care Research Wales
KeywordsFidelityPsychological interventionPsychosocialGuidelineConsistency (knowledge bases)Intervention (counseling)Delphi method

Abstract

fetched live from OpenAlex

Introduction: Fidelity - ensuring interventions are implemented as intended - is a key focus in implementation science. Despite its benefits in research and practice, data on the fidelity of implementation are often overlooked, measured inconsistently, or underreported. In 2024, we proposed a preliminary guideline for one component of fidelity - the fidelity of delivery in parenting interventions. This study builds upon that work, refining the guideline for psychosocial and behavioral interventions. Methods: = 5) resulting in six rounds of iterative revisions to produce the final FIPP. Results: The modified Delphi technique resulted in a final FIPP with 35 items across six categories: intervention, facilitator, fidelity measure, and fidelity assessor characteristics; fidelity assessment method; and fidelity results and discussion. The final FIPP was produced based on engagement and data from the survey participants, consensus meeting panelists, and email panelists. Conclusions: This study advances reporting on fidelity of delivery in psychosocial and behavioral interventions by refining the FIPP guideline through a rigorous, consensus-driven process. The FIPP provides a comprehensive structure to improve the consistency and transparency of fidelity of delivery assessment. By promoting standardized reporting, the FIPP enhances the quality of implementation science, ultimately supporting more effective interventions and better participant outcomes. Researchers and practitioners are encouraged to adopt the FIPP to strengthen intervention fidelity and drive meaningful progress in the field.

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 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)0.013
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.339
GPT teacher head0.604
Teacher spread0.264 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes2
Has abstractyes

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