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Record W2088668002 · doi:10.1159/000355365

Health Economic Analysis on a Psychosocial Intervention for Family Caregivers of Persons with Dementia

2013· article· en· W2088668002 on OpenAlexaff
Beth Dahlrup, Eva Nordell, Katarina Steen Carlsson, Sölve Elmståhl

Bibliographic record

VenueDementia and Geriatric Cognitive Disorders · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsInstitute of Health Economics
Fundersnot available
KeywordsPsychosocialDementiaPsychologyIntervention (counseling)Family caregiversPsychiatryGerontologyClinical psychologyMedicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: Psychosocial intervention has shown positive effects on the caregivers' burden and satisfaction. The aims of this study were to describe the cost and cost-effectiveness of such an intervention. METHODS: We analyzed resource use and costs of formal care for 308 persons with dementia and their caregivers' health-related quality of life (HRQoL). RESULTS: The costs of home help services were lower in the subgroup of spouse caregivers in the intervention group and the cost of nursing home placement was lower in the intervention group. While the person with dementia lived at home, caregivers in the intervention group reported a higher HRQoL (p < 0.01). After the person with dementia had moved to a nursing home, spouses in the control group had a lower HRQoL (p < 0.001). CONCLUSION: The result can be interpreted as a positive effect of the intervention focusing on the identified specific needs of the family caregivers.

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)0.007
metaresearch head score (Gemma)0.023
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 score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.019
GPT teacher head0.378
Teacher spread0.360 · 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

Citations17
Published2013
Admission routes1
Has abstractyes

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