The Relationship Between Kinesiophobic Attitude and Frailty in Older People
Bibliographic record
Abstract
AIM: To investigate the relationship between kinesiophobic attitudes and their causes and frailty in older people. METHODS: This descriptive, relationship-seeking study was conducted with 302 people aged over 65 years. The data were collected through face-to-face interviews between July and September 2023, using a personal information form, the Tampa Scale of Kinesiophobia, the Kinesiophobia Causes Scale (KCS) and the Edmonton Frail Scale (EFS). The data were analysed using Pearson's correlation test, linear regression and binary logistic regression. RESULTS: A total of 92.7% of older adults experienced high levels of kinesiophobia, while 80.5% presented various degrees of frailty. Most people's kinesiophobia is caused by psychological factors. There is a positive and significant correlation between kinesiophobia and frailty, as well as between the causes of kinesiophobia and frailty. The linear regression model showed that age, sex, physical activity, pain score, kinesiophobic attitudes and causes explained 52.1% of the variation in the EFS score. The binary logistic regression model, based on the frailty categorical variable (frail vs. non-frail), found that age, sex, physical activity, pain score and kinesiophobic attitudes accounted for 49.0% of the variation in the EFS score. CONCLUSIONS: Kinesiophobic attitudes and causes are important risk factors for frailty and can predict an individual's frailty state.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".