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Record W2971394833 · doi:10.1080/10401334.2019.1654387

Developing a Framework of Integrated Competencies for Adaptive Expertise in Integrated Physical and Mental Health Care

2019· article· en· W2971394833 on OpenAlex
Sanjeev Sockalingam, Zarah Chaudhary, Rachael Barnett, Jana Lazor, Maria Mylopoulos

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTeaching and Learning in Medicine · 2019
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsThe Wilson CentreUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsBiopsychosocial modelIntegrated careThematic analysisAlliancePsychologyContext (archaeology)Medical educationMental healthHealth careNursingMedicineQualitative researchPsychiatry

Abstract

fetched live from OpenAlex

Phenomenon: Despite the emergence of the integrated care (IC) model, IC is variably taught and is challenged by current siloed competency domains. This study aimed to define IC competencies spanning multiple competency domains. Approach: Iterative facilitated discussions were conducted at a half-day education retreat with 25 key informants including clinician educators and education scientists. Seven one-on-one semistructured interviews were subsequently conducted with different interprofessional providers in IC settings within a Canadian context. Data collection grounded in patient cases with a physical illness and concurrent mental illness (medical psychiatry) were used to elicit identification of complex patient needs and the key medical psychiatry knowledge and skills required to address these needs. A thematic analysis of transcripts was performed using constant comparison to iteratively identify themes. Findings: Participants described 4 broad competency domains necessary for expertise in IC: (a) extensive integrated knowledge of biopsychosocial aspects of disease, systems of care, and social determinants of care; (b) skills to establish a longitudinal alliance with the patient and functional relationships with colleagues; (c) constructing a comprehensive understanding of individual patients’ complex needs and how these can be met within their health and social systems; and (d) the ability to effectively meet the patient’s needs using IC models. These 4 domains were linked by an overarching philosophy of care encompassing key enabling attitudes such as proactively pursuing depth to understand patient and system complexity while maintaining a patient-centered approach. Insights: The study addresses how development of IC expertise can be fostered by integration of individual IC competency domains. The findings align with previous research suggesting that competencies from existing frameworks are being enacted jointly in expert capabilities to meet the complex needs of patients, in this case with comorbid physical and mental health concerns.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.439
Teacher spread0.406 · 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