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Record W2136385807 · doi:10.1186/s13012-015-0320-3

What is the extent and quality of documentation and reporting of fidelity to implementation strategies: a scoping review

2015· review· en· W2136385807 on OpenAlexaff
Susan E. Slaughter, Erna Snelgrove‐Clarke

Bibliographic record

VenueImplementation Science · 2015
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsDalhousie UniversityUniversity of Alberta
Fundersnot available
KeywordsFidelityData extractionDocumentationChecklistPsychological interventionHealth informaticsImplementation researchQuality (philosophy)Computer scienceProcess managementMedicineMEDLINEPublic healthPsychologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Implementation fidelity is critical to the internal and external validity of implementation research. Much of what is written about implementation fidelity addresses fidelity of evidence-informed interventions rather than fidelity of implementation strategies. The documentation and reporting of fidelity to implementation strategies requires attention. Therefore, in this scoping review, we identify the extent and quality of documentation and reporting of fidelity of implementation strategies that were used to implement evidence-informed interventions. METHODS: A six-stage methodological framework for scoping studies guided our work. Studies were identified from the outputs of the Effective Practice and Organization of Care (EPOC) review group within the Cochrane Database of Systematic Reviews. EPOC's primary focus, implementation strategies influencing provider behavior change, optimized our ability to identify articles for inclusion. We organized the retrieved articles from the systematic reviews by journal and selected the three journals with the largest number of retrieved articles. Using a data extraction tool, we organized retrieved article data from these three journals. In addition, we summarized implementation strategies using the EPOC categories. Data extraction pertaining to the quality of reporting the fidelity of implementation strategies was facilitated with an "Implementation Strategy Fidelity Checklist" based on definitions adapted from Dusenbury et al. We conducted inter-rater reliability checks for all of the independently scored articles. Using linear regression, we assessed the fidelity scores in relation to the publication year. RESULTS: Seventy-two implementation articles were included in the final analysis. Researchers reported neither fidelity definitions nor conceptual frameworks for fidelity in any articles. The most frequently employed implementation strategies included distribution of education materials (n = 35), audit and feedback (n = 32), and educational meetings (n = 25). Fidelity of implementation strategies was documented in 51 (71 %) articles. Inter-rater reliability coefficients of the independent reviews for each component of fidelity were as follows: adherence = 0.85, dose = 0.89, and participant responsiveness = 0.96. The mean fidelity score was 2.6 (SD = 2.25). We noted a statistically significant decline in fidelity scores over time. CONCLUSIONS: In addition to identifying the under-reporting of fidelity of implementation strategies in the health literature, we developed and tested a simple checklist to assess the reporting of fidelity of implementation strategies. More research is indicated to assess the definitions and scoring schema of this checklist. Careful reporting of details about fidelity of implementation strategies will make an important contribution to implementation science.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Reporting · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptMetaresearch
Domain: Reporting · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.441
metaresearch head score (Gemma)0.764
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.559
Threshold uncertainty score0.689

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4410.764
Meta-epidemiology (narrow)0.0020.004
Meta-epidemiology (broad)0.0100.011
Bibliometrics0.0320.031
Science and technology studies0.0040.007
Scholarly communication0.0200.025
Open science0.0060.007
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.913
GPT teacher head0.824
Teacher spread0.089 · 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

Labeled directly by 2 models reading the full record.

Study designSystematic review
DomainReporting
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

Citations167
Published2015
Admission routes1
Has abstractyes

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