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Record W4395072861 · doi:10.1080/26892618.2024.2338297

Study Protocol of Implementation and Evaluation of Aging Home Modification Intervention Program (AhMIP) for Iranian Community-Dwelling Older Adults

2024· article· en· W4395072861 on OpenAlexaff
Elham Lotfalinezhad, Maryam Chehregosha, Fatemeh Mehravar, Shannon Freeman, Karen Andersen‐Ranberg, Farzaneh Barati, H Mancheri, Haidar Nadrian, Vahid Rashedi, Leila Jouybari, Shahab Papi

Bibliographic record

VenueJournal of Aging and Environment · 2024
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsGerontologyProtocol (science)Intervention (counseling)Aging in placeMedicinePsychologyNursingAlternative medicine

Abstract

fetched live from OpenAlex

Introduction With the rapid increase in the older population in Iran, the housing needs of this age group are also changing. The residential environment plays an important role in the ability of older adults to perform daily activities. This study will be conducted to implement and evaluate a home modification intervention program to support older adults.Method This paper describes the protocol for a triangulation mixed methods design study with three substudies. The first substudy is a cross-sectional study to be conducted on 422 community-dwelling older adults to assess their current status at home, functional abilities, fear of falling, and quality of life. In the second substudy, a randomized clinical intervention trial will be conducted on 116 older adults (58 intervention group and 58 control group) with the intervention of home modifications based on the results of the Home Falls and Accidents Screening Tool. The third substudy is a qualitative study with an in-depth, semi-structured interview approach to find out about older adults’ experienecs regarding AhMIP.Conclusion The quantitative and qualitative findings of this study can be useful in designing intervention programs to improve the living environment of older Iranian adults and promote their quality of life.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.911
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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)0.0000.000

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 head0.085
GPT teacher head0.465
Teacher spread0.380 · 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.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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