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Record W3012465551 · doi:10.1186/s12913-020-5064-3

Variations in factors associated with healthcare providers’ intention to engage in interprofessional shared decision making in home care: results of two cross-sectional surveys

2020· article· en· W3012465551 on OpenAlexafffundabout
Rhéda Adekpedjou, Julie Haesebaert, Dawn Stacey, Nathalie Brière, Adriana Freitas, Louis‐Paul Rivest, France Légaré

Bibliographic record

VenueBMC Health Services Research · 2020
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsOttawa HospitalCentres Intégré Universitaires de Santé et de Services SociauxBombardier Recreational Products (Canada)Centre intégré universitaire de santé et de services sociaux de la Capitale-NationaleUniversity of OttawaUniversité Laval
FundersMinistère de la SantéMinistère de la Santé et des Services sociauxCanadian Frailty NetworkUniversité Laval
KeywordsPsychosocialMedicineHealth careNursing researchCross-sectional studyTheory of planned behaviorHealth administrationIntervention (counseling)Descriptive statisticsNursingInterquartile rangePsychological interventionFamily medicinePublic healthControl (management)Psychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: DOLCE (Improving Decision making On Location of Care with the frail Elderly and their caregivers) was a post-intervention clustered randomised trial (cRT) to assess the effect of training home care teams on interprofessional shared decision-making (IP-SDM). Alongside the cRT, we sought to monitor healthcare providers' level of behavioural intention to engage in an IP-SDM approach and to identify factors associated with this intention. METHODS: We conducted two cross-sectional surveys in the province of Quebec, Canada, one each at cRT entry and exit. Healthcare providers (e.g. nurses, occupational therapists and social workers) in the 16 participating intervention and control sites self-completed an identical paper-based questionnaire at entry and exit. Informed by the Integrated model for explaining healthcare professionals' clinical behaviour by Godin et al. (2008), we assessed their behavioural intention to engage in IP-SDM to support older adults and caregivers of older adults with cognitive impairment to make health-related housing decisions. We also assessed psychosocial variables underlying their behavioural intention and collected sociodemographic data. We used descriptive statistics and linear mixed models to account for clustering. RESULTS: Between 2014 and 2016, 271 healthcare providers participated at study entry and 171 at exit. At entry, median intention level was 6 in a range of 1 (low) to 7 (high) (Interquartile range (IQR): 5-6.5) and factors associated with intention were social influence (β = 0.27, P < 0.0001), beliefs about one's capabilities (β = 0.43, P < 0.0001), moral norm (β = 0.31, P < 0.0001) and beliefs about consequences (β = 0.21, P < 0.0001). At exit, median intention level was 5.5 (IQR: 4.5-6.5). Factors associated with intention were the same but did not include moral norm. However, at exit new factors were kept in the model: working in rehabilitation (β = - 0.39, P = 0.018) and working as a technician (β = - 0.41, P = 0.069) (compared to as a social worker). CONCLUSION: Intention levels were high but decreased from entry to exit. Factors associated with intention also changed from study entry to study exit. These findings may be explained by the major restructuring of the health and social care system that took place during the 2 years of the study, leading to rapid staff turnover and organisational disturbance in home care teams. Future research should give more attention to contextual factors and design implementation interventions to withstand the disruption of system- and organisational-level disturbances. TRIAL REGISTRATION: Clinicaltrials.gov (NCT02244359). Registered on September 19th, 2014.

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)0.010
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.004
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 head0.381
GPT teacher head0.544
Teacher spread0.164 · 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 designObservational
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

Citations39
Published2020
Admission routes3
Has abstractyes

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