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Record W3216739822 · doi:10.1111/ajag.13011

Factors associated with caregiver distress among home care clients in New Zealand: Evidence based on data from interRAI Home Care assessment

2021· article· en· W3216739822 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAustralasian Journal on Ageing · 2021
Typearticle
Languageen
FieldPsychology
TopicFamily Caregiving in Mental Illness
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDistressMedicineLogistic regressionActivities of daily livingCaregiver stressDepression (economics)Caregiver burdenGerontologyCohortScale (ratio)PsychologyClinical psychologyDementiaPsychiatryDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify factors associated with caregiver distress among home care clients in New Zealand. METHODS: The cohort consisted of 105,978 community-dwelling people aged 65 years or older requiring home care services in New Zealand who had at least one informal caregiver. Bivariate and multivariable logistic regression analyses were used to identify factors associated with caregiver distress. RESULTS: Variables associated with risk of caregiver distress included Depression Rating Scale score, aggressive behaviour symptoms, primary informal caregiver relationship to patient, Cognitive Performance Scale score, Changes in Health, End-stage disease, and Signs and Symptoms Scale score, informal care time, secondary informal caregiver relationship to care recipient, activities of daily living hierarchy scale score and any hospitalisation. CONCLUSIONS: The study has identified important characteristics that are associated with caregiver stress. These results suggest that caregiver distress can be relieved by promoting protective factors and aiming to reduce risk factors among home care clients in New Zealand.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.080
GPT teacher head0.348
Teacher spread0.268 · 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