MétaCan
Menu
Back to cohort
Record W1984460816 · doi:10.3109/13561820.2013.763777

Healthcare providers' intentions to engage in an interprofessional approach to shared decision-making in home care programs: A mixed methods study

2013· article· en· W1984460816 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Interprofessional Care · 2013
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsInstitut National de Santé Publique du QuébecCentre hospitalier universitaire de QuébecUniversité LavalUniversity of AlbertaCentre de Santé et de Services Sociaux de la Vieille-CapitaleUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsTheory of planned behaviorHealth carePsychologyDescriptive statisticsNursingGroup cohesivenessQualitative researchTeamworkQualitative propertyCohesion (chemistry)Control (management)MedicineSocial psychology

Abstract

fetched live from OpenAlex

In an interprofessional approach to shared decision-making (IP-SDM), an interprofessional team collaborates in identifying best options and helps patients determine their preferences, enabling them to take more control over the treatment plan. However, little is known about fostering IP-SDM in Canada's healthcare system. Therefore, we sought to evaluate health professionals' intentions to engage in IP-SDM in home care and explore the factors associated with this intention. A total of 272 eligible home care providers completed a questionnaire based on the theory of planned behavior. Eight managers and one healthcare team caring for the frail elderly were interviewed about possible barriers and facilitators. Analysis involved descriptive statistics and multivariate analysis of quantitative data and content analysis of qualitative data. On a scale of - 3 (strongly disagree) to +3 (strongly agree), the mean intention to engage in IP-SDM was positive (1.42 ± 1.39). The intention was influenced by the following theory-based determinants (R(2) = 57%; p ≤ 0.002), i.e. cognitive attitude (p < 0.001) subjective norm (p < 0.0001) and perceived behavioral control (p < 0.0001), with variations depending on the type of provider. Barriers included lack of time, poor team cohesion and high staff turnover. Facilitators included team cohesion and shared tools. Future programs implementing IP-SDM could address these barriers and facilitators.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0030.002
Research integrity0.0010.006
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 head0.156
GPT teacher head0.511
Teacher spread0.354 · 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