MétaCan
Menu
Back to cohort
Record W4380089994 · doi:10.1108/jica-11-2022-0055

Collective case study: integrated health and social care for older adults within a Canadian context

2023· article· en· W4380089994 on OpenAlexaffabout
Siu Mee Cheng, Cristina Catallo

Bibliographic record

VenueJournal of Integrated Care · 2023
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsContext (archaeology)Integrated careGovernment (linguistics)Social WelfareHealth careOriginalityFocus groupPublic relationsNova scotiaSocial workQualitative researchPsychologyNursingGerontologySociologyMedicinePolitical scienceBusinessMarketingGeographySocial science

Abstract

fetched live from OpenAlex

Purpose Canada's population is aging and there are concerns that the welfare system may not support the increased demands on it. Integrated health and social care (IHSC) produces positive health and system outcomes but it needs to be better understood within a Canadian context. The purpose of this collective case study of three IHSC initiatives in Alberta, Ontario and Nova Scotia was to determine the factors that support successful services integration among different healthcare and social services organizations serving older adults within a Canadian context. Design/methodology/approach This study used the Cheng and Catallo (2020) IHSC conceptual framework (CF) to guide the research. Primary data were based on key informant interviews of representatives from organizations that comprised each case and focus groups. A cross-case analysis was undertaken to determine common themes. Findings The cross-case analysis revealed that the three cases shared common integration and external influence factors based on the Cheng and Catallo (2020) CF. Some new factors were identified. Originality/value The study revealed that the Canadian context was important in influencing integration in the three cases and that there is a unique Canadian aspect to IHSC. The study offers up practical insights for government leaders and service administrators to improve IHSC for older adults. The study also identifies how the Cheng and Catallo (2020) IHSC CF can be enhanced and points to research opportunities to test the framework.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.604
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
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 head0.031
GPT teacher head0.426
Teacher spread0.395 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Integrated CareSame topicInterprofessional Education and CollaborationFrench-language works237,207