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Record W2163281668 · doi:10.1186/s12874-015-0037-7

Development, inter-rater reliability and feasibility of a checklist to assess implementation (Ch-IMP) in systematic reviews: the case of provider-based prevention and treatment programs targeting children and youth

2015· article· en· W2163281668 on OpenAlexaff
Margaret Cargo, Ivana Stankov, James Thomas, Michael Saini, Patricia Rogers, Evan Mayo‐Wilson, Karin Hannes

Bibliographic record

VenueBMC Medical Research Methodology · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersUniversity of South Australia
KeywordsChecklistInter-rater reliabilityPsychological interventionKappaSystematic reviewMedicineReliability (semiconductor)CLARITYCohen's kappaMEDLINEFamily medicinePsychologyComputer sciencePsychiatryRating scale

Abstract

fetched live from OpenAlex

BACKGROUND: Several papers report deficiencies in the reporting of information about the implementation of interventions in clinical trials. Information about implementation is also required in systematic reviews of complex interventions to facilitate the translation and uptake of evidence of provider-based prevention and treatment programs. To capture whether and how implementation is assessed within systematic effectiveness reviews, we developed a checklist for implementation (Ch-IMP) and piloted it in a cohort of reviews on provider-based prevention and treatment interventions for children and young people. This paper reports on the inter-rater reliability, feasibility and reasons for discrepant ratings. METHODS: Checklist domains were informed by a framework for program theory; items within domains were generated from a literature review. The checklist was pilot-tested on a cohort of 27 effectiveness reviews targeting children and youth. Two raters independently extracted information on 47 items. Inter-rater reliability was evaluated using percentage agreement and unweighted kappa coefficients. Reasons for discrepant ratings were content analysed. RESULTS: Kappa coefficients ranged from 0.37 to 1.00 and were not influenced by one-sided bias. Most kappa values were classified as excellent (n = 20) or good (n = 17) with a few items categorised as fair (n = 7) or poor (n = 1). Prevalence-adjusted kappa coefficients indicate good or excellent agreement for all but one item. Four areas contributed to scoring discrepancies: 1) clarity or sufficiency of information provided in the review; 2) information missed in the review; 3) issues encountered with the tool; and 4) issues encountered at the review level. Use of the tool demands time investment and it requires adjustment to improve its feasibility for wider use. CONCLUSIONS: The case of provider-based prevention and treatment interventions showed relevancy in developing and piloting the Ch-IMP as a useful tool for assessing the extent to which systematic reviews assess the quality of implementation. The checklist could be used by authors and editors to improve the quality of systematic reviews, and shows promise as a pedagogical tool to facilitate the extraction and reporting of implementation characteristics.

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)0.157
metaresearch head score (Gemma)0.126
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1570.126
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.938
GPT teacher head0.763
Teacher spread0.175 · 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; both teacher heads agree on what is shown here.

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

Citations25
Published2015
Admission routes1
Has abstractyes

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