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Record W2514705396 · doi:10.2340/16501977-2115

Effects of adult day care services on disability in older persons: Evaluation of a designed service package in Iran

2016· article· en· W2514705396 on OpenAlexaff
Mohammad Shahbazi, Mahshid Foroughan, Reza Salman Roghani

Bibliographic record

VenueJournal of Rehabilitation Medicine · 2016
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsMedicineRehabilitationGerontologyPhysical therapyActivities of daily living

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the effects of a rehabilitation service package designed by the State Welfare Organization of Iran for adult day care centres on the disability of older clients. METHODS: A case-control study, with 46 older participants in the case group and 46 participants, matched for level of disability, in a control group. The World Health Organization Disability Assessment Schedule 2 was used to collect data at 4 time-points: baseline and 2, 4, and 6 months later. Data were analysed using repeated-measures analysis of variation. RESULTS: The rehabilitation service package had significant effects on the disability scores of older users of day care services. The disability scores significantly changed within the subjects (p = 0.010) and between the 2 groups (p < 0.001). Within-subjects effects in all 6 domains ("understanding and communication" (p = 0.002), "getting around" (p = 0.046), "self-care" (p < 0.001), "getting along with people" (p < 0.001), "life activity" (p < 0.001) and "participation" (p < 0.001)) and between-subjects effects, in all except the "self-care" domain, showed significant differences during the 6-month study period (p = 0.003, p < 0.001, p <0.001, p < 0.001, and p < 0.001, respectively). CONCLUSION: The adult day care service package may have a positive role in decreasing measures of disability among older persons over a 6-month period.

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)0.007
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.430
Teacher spread0.390 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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