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A Relaxation Training Program To Increase Self-Efficacy for Anxiety Control in Alzheimer Family Caregivers

2001· article· en· W2031646307 on OpenAlexaff
Pauline A. Fisher, Heather Spenec Laschinger

Bibliographic record

VenueHolistic Nursing Practice · 2001
Typearticle
Languageen
FieldPsychology
TopicFamily Caregiving in Mental Illness
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsIntervention (counseling)Relaxation (psychology)AnxietyFamily caregiversSelf-efficacyClinical psychologyMedicinePsychologyIncidence (geometry)Caregiver burdenDiseasePhysical therapyPsychiatryPsychotherapistDementiaInternal medicine

Abstract

fetched live from OpenAlex

This study investigated whether relaxation training would increase caregivers' self-efficacy for controlling anxiety associated with difficult behaviors by care recipients. Thirty-six individuals caring for relatives with Alzheimer's disease were taught four types of relaxation techniques. Caregivers' self-efficacy increased following the intervention. Length of time spent in the caregiving role and duration of time since care recipients' diagnosis were significantly related to caregiver self-efficacy before the intervention, but became non-significant following the intervention. An insignificant decrease in incidence of reported behavioral problems occurred following the intervention.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.081
GPT teacher head0.405
Teacher spread0.324 · 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 designNon-randomized trial
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

Citations38
Published2001
Admission routes1
Has abstractyes

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