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Record W4214806101 · doi:10.5334/ijic.5978

Community Volunteers and Primary Care Providers Supporting Older Adults in System Navigation: A Mixed Methods Study

2022· article· en· W4214806101 on OpenAlexaffabout
Jessica Gaber, Stephanie Di Pelino, Julie Datta, Samina Talat, Tracy Browne, Sarah Marentette‐Brown, Sivan Bomze, Pamela Forsyth, Doug Oliver, Tracey Carr, Dee Mangin

Bibliographic record

VenueInternational Journal of Integrated Care · 2022
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsCanadian Red Cross SocietyMcMaster University
Fundersnot available
KeywordsFocus groupPrimary careNursingIntervention (counseling)MedicinePsychologyFamily medicineMedical educationGerontology

Abstract

fetched live from OpenAlex

Introduction: Primary care providers and community volunteers have important roles in supporting patient system navigation and utilization of community-based health and social services (CBHSS). This study aimed to explore the experiences and impacts of system navigation in a complex intervention supporting older adults. Methods: We used a convergent mixed methods design. Participants included primary care team members (n = 67), community volunteers (n = 38), and programme clients (n = 128) across six communities in Ontario, Canada. Data sources included focus groups, interviews, system navigation function survey for volunteers, CBHSS use survey for clients, and implementation data on CBHSS recommended by providers and volunteers and used by clients. Results: Results showed the different patterns of how CBHSS categories were recommended and ultimately used. Exercise-related CBHSS were both recommended and used, independence-related CBHSS were mostly only recommended with less uptake, and chronic health condition and diet/nutrition CBHSS were most often used by clients. Discussion: Primary care teams' practice of system navigation was impacted by programme participation, including through learning about local CBHSS. However, volunteers felt more confident in tasks that did not include connecting to CBHSS. The programme did seem to result in many referrals, though the actual client uptake tended to be to more clinical rather than healthy lifestyle resources.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.334
Teacher spread0.322 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2022
Admission routes2
Has abstractyes

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