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Record W3032080176 · doi:10.5770/cgj.23.384

Health-care Workforce Training to Effectively Support Family Caregivers of Seniors in Care

2020· article· en· W3032080176 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Geriatrics Journal · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsAthabasca UniversityCovenant HealthGrey Nuns Community HospitalUniversity of Alberta
Fundersnot available
KeywordsWorkforceMedicineThematic analysisFamily caregiversNursingHealth carePopulationGerontologyQualitative researchPolitical science

Abstract

fetched live from OpenAlex

INTRODUCTION: Family caregivers (FCGs) play an integral, yet often invisible, role in the Canadian health-care system. As the population ages, their presence will become even more essential as they help balance demands on the system and enable community-dwelling seniors to remain so for as long as possible. To preserve their own well-being and capacity to provide ongoing care, FCGs require support to the meet the challenges of their daily caregiving responsibilities. Supporting FCGs results in better care provision to community-dwelling seniors receiving health-care services, as well as enhancing the quality of life for FCGs. Although FCGs rely upon health-care professionals (HCPs) to provide them with support and services, there is a paucity of research pertaining to the type of health workforce training (HWFT) that HCPs should receive to address FCG needs. Programs that train HCPs to engage with, empower, and support FCGs are required. OBJECTIVE: To describe and discuss key findings of a caregiver symposium focused on determining components of HWFT that might better enable HCPs to support FCGs. METHODS: A one-day symposium was held on February 22, 2018 in Edmonton, Alberta, to gather the perspectives of FCGs, HCPs, and stakeholders. Attendees participated in a series of working groups to discuss barriers, facilitators, and recommendations related to HWFT. Proceedings and working group discussions were transcribed, and a qualitative thematic analysis was conducted to identify key themes. RESULTS: Participants identified the following topic areas as being essential to training HCPs in the provision of support for FCGs: understanding the FCG role, communicating with FCGs, partnering with FCGs, fostering FCG resilience, navigating healthcare systems and accessing resources, and enhancing the culture and context of care. CONCLUSIONS: FCGs require more support than is currently being provided by HCPs. Training programs need to specifically address topics identified by participants. These findings will be used to develop HWFT for HCPs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
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 head0.045
GPT teacher head0.344
Teacher spread0.299 · 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