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Record W2300408461 · doi:10.22230/jripe.2010v1n3a29

Creating Sustainable Change in the Interprofessional Academic Family Practice Setting: An Appreciative Inquiry Approach

2010· article· en· W2300408461 on OpenAlexaffvenueabout
Lesley Gotlib Conn, Ivy Oandasan, Catherine Creede, Difat Jakubovicz, Lynn Wilson

Bibliographic record

VenueJournal of Research in Interprofessional Practice and Education · 2010
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAppreciative inquiryTeamworkIntervention (counseling)NursingHealth carePsychologyTheory of changeMedical educationMedicineSociologyPedagogyPolitical science

Abstract

fetched live from OpenAlex

Background: There is a global shift toward integrated care approaches in primary care. Understanding how to optimize healthcare team effectiveness is of utmost interest in Canada, where primary care reform targets the development of interprofessional teams of providers collaborating to improve patient care. This article presents findings from a longitudinal study of one primary healthcare team in transformation. A theory-based organizational change model is applied to understanding the processes of change in interprofessional healthcare teams.Methods and Findings: We report findings from two years after the implementation of an intervention to advance teamwork in one family health team in Ontario. The intervention was informed by the Appreciative Inquiry (AI) approach. Fifty hours of unstructured clinic observations and interviews were conducted. The findings revealed that a change in team practice, such as patient-centredness, and formal and informal communication opportunities, precede change in team discourse—the way that members speak and think about themselves as an integrated team.Conclusions: The evolution of teamwork in the family practice setting is a gradual, steady process that begins with important changes in the way that things are done (i.e., first-order change), and with continued support and nurturance, can eventually lead to changes in the way that members think and speak about their team (i.e., second-order change).

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)0.035
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0350.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.006
Open science0.0010.000
Research integrity0.0010.013
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 head0.164
GPT teacher head0.603
Teacher spread0.439 · 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 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

Citations13
Published2010
Admission routes3
Has abstractyes

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