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Record W2915615906 · doi:10.1177/1539449219829849

Increasing Meaningful Occupation for Women Who Provide Care for Their Spouse: A Pilot Study

2019· article· en· W2915615906 on OpenAlexaboutno aff
Patricia Watford, Vanessa Jewell, Karen Atler

Bibliographic record

VenueOTJR Occupational Therapy Journal of Research · 2019
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
FundersCreighton University
KeywordsSpousePleasureIntervention (counseling)PsychologyAffect (linguistics)Quality of life (healthcare)GerontologyClinical psychologyMedicinePsychotherapistPsychiatrySociology

Abstract

fetched live from OpenAlex

Caregiving for a loved one can be difficult and negatively affect health and quality of life. This pilot mixed-method study explored an intervention to increase participation in meaningful occupation for women who care for their spouse. Participants completed the World Health Organization Quality of Life: Brief Version (WHOQOL-BREF) and Canadian Occupational Performance Measure (COPM). The 4-week intervention consisted of an activity log (Daily Experiences of Pleasure, Productivity, and Restoration Profile) and a reflective journal (Journal of Activities and Experiences). Researchers analyzed data from the reflective journal using content analysis. Preliminary findings showed an increase in the physical health domain ( p < .05), and satisfaction with meaningful activities had clinical significance. Qualitative themes included caregiving is a demanding role, writing down experiences helped caregivers take action, and caregivers reorganized daily activities. Although preliminary results showed a positive trend, the intervention was brief, and more research is needed to determine whether greater gains are possible, and can be sustained.

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 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)0.019
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.316
GPT teacher head0.561
Teacher spread0.244 · 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 teacher head, not a consensus.

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

Citations8
Published2019
Admission routes1
Has abstractyes

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