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Record W4245221410 · doi:10.21203/rs.3.rs-106901/v1

Development of an Implementation Process Model: A Delphi Study

2020· preprint· en· W4245221410 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.

Bibliographic record

VenueResearch Square (Research Square) · 2020
Typepreprint
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDelphiProcess (computing)Computer scienceProcess managementDelphi methodBusinessArtificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

Abstract Background: There is general scarcity of research on key elements of implementation processes and the factors which impact implementation success. Implementation of healthcare interventions is a complex process. Tools to support implementation can facilitate this process and improve effectiveness of the interventions and clinical outcomes. Understanding the impact of implementation support tools is a critical aspect of this process. The objective of this study was to solicit knowledge and consensus from relevant implementation science and knowledge translation healthcare experts in order to refine and validate a process model of key elements in the implementation process. Methods: A two round consensus-based modified Delphi study involving international experts in knowledge translation and implementation (researchers, scientists, professors, decision-makers) was conducted. Participants rated and commented on all aspects of the process model, including the organization, content, scope, and structure. Delphi questions rated at 75% agreement or lower were reviewed and revised. Qualitative comments supported the restructuring and refinement. A second-round survey followed the same process as Round 1. Results: Fifty-four experts participated in Round 1, and 32 experts participated in Round 2. Twelve percent (n=6) of the Round 1 questions did not reach consensus. Key themes for revision and refinement were: stakeholder engagement throughout the process, iterative nature of the implementation process; importance of context; and importance of using guiding theories or frameworks. The process model was revised and refined based on the quantitative and qualitative data and reassessed by the experts in Round 2. Consensus was achieved on all items in Round 2 and the Delphi concluded. Additional feedback was obtained regarding terminology, target users and definition of the implementation process. Conclusions: High levels of agreement were attained for all sub-domains, elements, and sub-elements of the Implementation Process Model. This validated model will be used to develop an Implementation Support Tool to be used by healthcare providers to facilitate effective implementation and improved clinical outcomes.

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)0.079
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0790.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.007
Science and technology studies0.0040.003
Scholarly communication0.0010.001
Open science0.0080.007
Research integrity0.0010.009
Insufficient payload (model declined to judge)0.0010.000

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 head0.526
GPT teacher head0.648
Teacher spread0.122 · 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