In newborns, changing parenteral nutrition sets every 48 hours rather than every 24 hours did not increase infusate contamination
Bibliographic record
Abstract
Objectives Reliable and valid assessment of subjective risk perception is a crucial part of cardiovascular disease (CVD) prevention and rehabilitation. Since the recently developed Attitudes and Beliefs about Cardiovascular Disease (ABCD) Risk Questionnaire complies with these requirements, the aim of the present study was to investigate the psychometric properties of the Hungarian version of the measure. Design and setting Community-based cross-sectional observational study Participants In sum, 410 (M=49.53 years, SD=8.09) Hungarian adults (inclusion criteria: aged 35 and above, not under treatment with a psychiatric disorder) were included in the present study (female: n=277, 67.6%; college or university-level education: n=247, 60.2%). Methods We translated the ABCD Risk Questionnaire into Hungarian and checked its psychometric properties and validity indices. Primary outcome measures Internal consistency, explorative and confirmative factorial validity. Associations with sociodemographic and health-related characteristics, as well as with measures of mental health (depressive symptoms, perceived stress and well-being). Results Exploratory and confirmatory factor analyses supported a three-factor solution, corresponding to the original subscales of Risk Perception, Perceived Benefits and Healthy Eating Intentions, with a moderate correlation between the latent constructs. The respondents’ level of knowledge on CVD risk factors was largely independent of their subjective risk perception. The results also provided evidence on the weak-to-medium associations between mental health indices and CVD-related perceptions. Based on the results, a shortened scale version was also suggested. Conclusion This study confirms the factorial structure, internal consistency and validity of the Hungarian version of the ABCD Risk Questionnaire in a non-English-speaking community sample. The ABCD Risk Perception Questionnaire is a parsimonious and psychometrically adequate measure to assess CVD-related attitudes and knowledge in the general population. Further research is needed in socioeconomically more diverse and in clinical samples, as well as in longitudinal intervention studies.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".