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Record W1983583508 · doi:10.4236/ojpp.2013.34071

Understanding the Implementation of a Complex Intervention Aiming to Change a Health Professional Role: A Conceptual Framework for Implementation Evaluation

2013· article· en· W1983583508 on OpenAlexafffund
Sabina Abou Malham, Marie Hatem, Nicole Leduc

Bibliographic record

VenueOpen Journal of Philosophy · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health ResearchInstitut pour la Recherche en Santé Publique
KeywordsOperationalizationConceptual frameworkIntervention (counseling)Process (computing)Implementation researchComputer scienceDisciplineKnowledge managementEngineering ethicsManagement scienceProcess managementSociologyEpistemologyPsychological interventionMedicineNursingSocial science

Abstract

fetched live from OpenAlex

This paper proposes a conceptual framework for understanding the implementation process of a complex intervention concerned with professional role change. The proposed framework holds that the intervention must address three interacting systems (socio-cultural, educational and disciplinary) through which a health professional role is evolved. Each system is operationalized by four dimensions (values, methods, actors and targets). As for the implementation, the framework posits that it can be analyzed, by depicting the barriers and facilitators located within the dimensions of the three interacting systems and within the intervention involved in the process through using the “menu of constructs” approach suggested by the Consolidated Framework for Implementation Research (CFIR). The implications of this framework, on theoretical research and practical levels, are reviewed.

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 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)0.203
metaresearch head score (Gemma)0.169
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.203
Threshold uncertainty score0.983

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2030.169
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0070.004
Science and technology studies0.0050.023
Scholarly communication0.0140.020
Open science0.0060.010
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0060.000

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 head0.870
GPT teacher head0.717
Teacher spread0.153 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations3
Published2013
Admission routes2
Has abstractyes

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