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Living with the dying: Using the wisdom of mindfulness to support caregivers of older adults with dementia

2006· article· en· W2059519595 on OpenAlexaff
Corey S. Mackenzie, Patricia A. Poulin

Bibliographic record

VenueInternational Journal of Health Promotion and Education · 2006
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMindfulnessPsychoeducationPsychological interventionDementiaIntervention (counseling)Caregiver stressFamily caregiversPsychologyMindfulness-based stress reductionQuality of life (healthcare)MedicineNursingClinical psychologyGerontologyDisease

Abstract

fetched live from OpenAlex

High levels of stress among family and professional caregivers of older adults with dementia are associated with physical and mental health problems, and decreased quality of care. Existing stress reduction interventions are based on the western medical model of care. They typically focus on providing caregivers with support, psychoeducation or behaviour management skills, and these interventions have typically had modest outcomes. An especially promising intervention for dementia caregivers, which is based on the eastern holistic model of care, is mindfulness training. Despite more than 20 years of research demonstrating the effectiveness of mindfulness-based interventions, their applicability for caregivers has received very little attention in the psychological research literature. We discuss how mindfulness training, as an alternative or adjunct to existing interventions, can help caregivers cope with providing care to dying older adults more skilfully, leading to reduced stress, enhanced well-being and improved quality of care.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.029
GPT teacher head0.362
Teacher spread0.333 · 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 designObservational
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

Citations14
Published2006
Admission routes1
Has abstractyes

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