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Record W4379376526 · doi:10.1017/s0714980823000119

Examining the Needs of Family Caregivers of People Living with Dementia in the Community during the COVID-19 Pandemic

2023· article· en· W4379376526 on OpenAlexafffund
Gwen McGhan, Deirdre McCaughey, Kristin Flemons

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of Calgary
FundersAlzheimer Society
KeywordsDementiaPandemicFamily caregiversFamily memberCoronavirus disease 2019 (COVID-19)GerontologyFocus groupPublic healthHealth carePsychologyMedicineNursingFamily medicinePolitical scienceSociologyDisease

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has had a disproportionate effect on older adults and their family caregivers (FCGs). For FCGs, the pandemic has impacted almost every dimension of their lives and caregiving routines, from their own risk of becoming ill to their access to resources that support caregiving. The purpose of this mixed-methods study was to examine the impact of COVID-19 on FCGs' ability to provide care for their family member with dementia. A total of 115 FCGs who identified as having their family member living with dementia residing in the community completed the survey. Ten family caregivers participated in the follow-up focus groups. Recommendations to address the needs of FCGs now and in the future include: (1) making resources for care provision consistently available and tailored, (2) providing support for navigating the health care system, and (3) supplying concise information on how to provide care during public health emergencies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.142
Threshold uncertainty score0.282

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.298
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissement→Same topicGeriatric Care and Nursing Homes→French-language works237,207→