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Record W1999076129 · doi:10.1258/135581902320432714

Improved preventive care in family practices with outreach facilitation: understanding success and failure

2002· article· en· W1999076129 on OpenAlexaff
William Hogg, Neill Bruce Baskerville, Candace I. J. Nykiforuk, Dan Mallen

Bibliographic record

VenueJournal of Health Services Research & Policy · 2002
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsGrand River HospitalUniversity of WaterlooUniversity of Ottawa
Fundersnot available
KeywordsFacilitatorOutreachIntervention (counseling)FacilitationNursingBest practicePsychologyCoding (social sciences)MedicineMedical educationSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: To understand why some family practices with a facilitator improved preventive performance more than others. Sustainability of practice improvements one year after the intervention was also explored. METHODS: Interviews with physicians and nurses from seven practices and data gathered during the intervention were used to form case studies of three high performing and four low performing family practices. Case studies were developed using cross-case analysis with a combination of the constant-comparative method and memoing-diagramming. Two researchers independently conducted in-depth coding of transcripts and documents, individual case construction for each study site, and then cross-case analysis of the identified themes between study sites. RESULTS: Staff involvement and a positive attitude toward implementation of changes were central to high improvement in performance. A lack of computers, low staff involvement or high staff turnover were associated with low improvement in performance. Personal characteristics of the facilitator are important. Six of the seven practices still had the prevention tools in place one year after the intervention and all noted that participation had improved their understanding of preventive medicine. CONCLUSIONS: When using facilitators, one should avoid practices in turmoil, strive for continuity over time, and recognise the importance of the relationship between the facilitator and the practice.

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)0.011
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.002
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 head0.578
GPT teacher head0.671
Teacher spread0.094 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations49
Published2002
Admission routes1
Has abstractyes

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