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Record W2987336749 · doi:10.1186/s13643-019-1161-y

Systematic review of the use of process evaluations in knowledge translation research

2019· review· en· W2987336749 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

VenueSystematic Reviews · 2019
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsQueen's UniversityUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsMedicineKnowledge translationProcess (computing)Translational researchSystematic reviewResearch designMEDLINEKnowledge managementPathologySocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Experimental designs for evaluating knowledge translation (KT) interventions can provide strong estimates of effectiveness but offer limited insight into how the intervention worked. Consequently, process evaluations have been used to explore the causal mechanisms at work; however, there are limited standards to guide this work. This study synthesizes current evidence of KT process evaluations to provide future methodological recommendations. METHODS: Peer-reviewed search strategies were developed by a health research librarian. Studies had to be in English, published since 1996, and were not excluded based on design. Studies had to (1) be a process evaluation of a KT intervention study in primary health, (2) be a primary research study, and (3) include a licensed healthcare professional delivering or receiving the intervention. A two-step, two-person hybrid screening approach was used for study inclusion with inter-rater reliability ranging from 94 to 95%. Data on study design, data collection, theoretical influences, and approaches used to evaluate the KT intervention, analysis, and outcomes were extracted by two reviewers. Methodological quality was assessed with the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of the 20,968 articles screened, 226 studies fit our inclusion criteria. The majority of process evaluations used qualitative forms of data collection (43.4%) and individual interviews as the predominant data collection method. 72.1% of studies evaluated barriers and/or facilitators to implementation. 59.7% of process evaluations were stand-alone evaluations. The timing of data collection varied widely with post-intervention data collection being the most frequent (46.0%). Only 38.1% of the studies were informed by theory. Furthermore, 38.9% of studies had MMAT scores of 50 or less indicating poor methodological quality. CONCLUSIONS: There is widespread acceptance that the generalizability of quantitative trials of KT interventions would be significantly enhanced through complementary process evaluations. However, this systematic review found that process evaluations are of mixed quality and lack theoretical guidance. Most process evaluation data collection occurred post-intervention undermining the ability to evaluate the process of implementation. Strong science and methodological guidance is needed to underpin and guide the design and execution of process evaluations in KT science. REGISTRATION: This study is not registered with PROSPERO.

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)0.099
metaresearch head score (Gemma)0.119
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.225
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0990.119
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0120.001
Bibliometrics0.0010.006
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.979
GPT teacher head0.821
Teacher spread0.157 · 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