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Record W2746131271 · doi:10.1177/0008417417714284

Fall determinants and home modifications by occupational therapists to prevent falls

2018· article· en· W2746131271 on OpenAlexvenueno aff
Patrick Maggi, Johanna De Almeida Mello, Sam Delye, Sophie Cès, Jean Macq, Christiane Gosset, Anja Declercq

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2018
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyFall preventionOccupational scienceMedicinePsychologyGerontologyNursingHuman factors and ergonomicsPhysical therapyPoison controlEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Approximately one third of older people over 65 years fall each year. Home modifications may decrease occurrence of falls. PURPOSE: This study aims to determine the risk factors of falls for frail older persons and to evaluate the impact of home modifications by an occupational therapist on the occurrence of falls. METHOD: We conducted a longitudinal study using a quasiexperimental design to examine occurrence of falls. All participants 65 years of age and older and were assessed at baseline and 6 months after the intervention. Bivariate analysis and logistic regression models were used to study the risk factors of falls and the effect of home modifications on the incidence of falls. FINDINGS: The main predictors of falls were vision problems, distress of informal caregiver, and insufficient informal support. Home modifications provided by an occupational therapist showed a significant reduction of falls. IMPLICATIONS: Informal caregivers and their health status had an impact on the fall risk of frail older persons. Home modifications by an occupational therapist reduced the fall risk of frail older persons at 6-months follow-up.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.105
GPT teacher head0.428
Teacher spread0.323 · 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

Citations31
Published2018
Admission routes1
Has abstractyes

Explore more

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