Psychometric Properties of the Multidimensional Health Locus of Control Scale Form C in a Non-Western Culture
Bibliographic record
Abstract
Form C of the Multidimensional Health Locus of Control Scales (MHLC-C) was designed to investigate health-related control beliefs of persons with an existing medical condition. The aim of the present study was to examine the psychometric properties of this instrument in a culture characterized by external control beliefs and learned helplessness-contrary to the societal context of original test development. Altogether, 374 Hungarian patients with cancer, irritable bowel syndrome, diabetes, and cardiovascular and musculoskeletal disorders were enrolled in the study. Besides the MHLC-C, instruments measuring general control beliefs, anxiety, depression, self-efficacy, and health behaviors were also administered to evaluate the validity of the scale. Both exploratory and confirmatory factor analytic techniques were used to investigate the factor structure of the scale. Our results showed that the Hungarian adaptation of the instrument had a slightly different structure than the one originally hypothesized: in the present sample, a three-factor structure emerged where the items of the Doctors and the Others subscales loaded onto a single common component. Internal reliability of all three subscales was adequate (alphas between .71 and .79). Data concerning the instrument's validity were comparable with previous results from Western countries. These findings may suggest that health locus of control can be construed very similarly to Western countries even in a post-communist society-regardless of the potential differences in general control beliefs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".