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Record W4390200125 · doi:10.1002/alz.073100

Challenges when monitoring and providing care to loved ones,Perspectives of Dementia caregivers in Canada

2023· article· en· W4390200125 on OpenAlexaffabout
Fariha Chowdhury, Dale Dauphinée, Luis Luy, Susan Macaulay, Sara S. Masoud, Nancy E. Mayo, Eunjung Na, Ashwak Rhayel, Carole L. White, Ayse Kuspinar

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill UniversityMcMaster University
Fundersnot available
KeywordsDementiaActive listeningPsychological interventionPsychosocialThematic analysisPsychologySession (web analytics)InterviewQualitative researchMedicineNursingGerontologyPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Abstract Background Family caregivers see firsthand the progression of their care recipient’s dementia and know every aspect of their lives and needs. They make important decisions on interventions and care. Currently, there are no measures that account for caregivers’ perspectives when evaluating the impact of dementia or interventions. The aim of this study was to explore the perspectives of caregivers’ of people living with dementia across Canada to generate domains for a new caregiver‐reported measure. Method Participants were recruited across Canada. Listening sessions were conducted virtually over three months, using open‐ended questions to encourage participants to share their perspectives. A semi‐structured interview guide was developed to facilitate the sessions. The interviewer asked questions to encourage caregivers to share their experiences on providing care, dementia monitoring, treatment impact and seeking alternative care. The data were coded and analyzed using NVivo. A thematic analysis approach was applied by two reviewers to analyze the data. Result Seven listening sessions were conducted with 34 caregivers who were providing care to their loved ones with dementia. Seventy‐four percent of the participants were women and 59% had 6 or more years of caregiving experience. Each listening session included three to six caregivers and was approximately one hour long. Example of codes included gait limitations, distance walked, difficulties with memory, and changes in behaviour. Overall, data were organized into three broad themes (i) psychosocial impact of dementia, (ii) physical and emotional changes for dementia monitoring and treatment, (iii) symptomalogy changes for dementia monitoring and treatment. Conclusion This study explored the perspective of caregivers across Canada, the activities and symptoms that are important to assess when evaluating dementia progression. It also questioned caregivers on how best to evaluate treatment effects. These findings may help identify strategies to better support caregivers and improve the quality of life of individuals living with dementia. Furthermore, the findings of this study can be a resource to help healthcare professionals, communities, and policymakers to provide better support for caregivers and the lives of individuals with dementia.

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)0.004
metaresearch head score (Gemma)0.010
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.417

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0260.006
Scholarly communication0.0060.002
Open science0.0020.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.304
Teacher spread0.262 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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