Cardiovascular Disease Risk Related Knowledge, Perception, Behaviours, and Utilization of Routine Screening Services among a Nigerian Adult Population: A Cross-Sectional Analytic Study.
Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease (CVD) risk preventive interventions should be informed by and targeted at addressing health literacy needs of individuals and communities. This study assessed the CVD risk knowledge, perception, behaviours, and utilization of routine risk screening services among a Nigerian adult population. METHODS: A cross-sectional analytic study design was employed to assess the CVD risk knowledge, perception, behaviours, and utilization of risk screening services among a random multistage sample of 900 adults. Data were collected using an interviewer-administered semi-structured questionnaire adapted from the WHO STEPS questionnaire. Descriptive and inferential analyses of data collected were carried out using the IBM SPSS version 28 software. RESULTS: The mean age of the study participants was 45.0 (SD = 18.7) years, with 66.8% reporting three concurrent risk behaviours, and 34.2% reporting utilization of at least one CVD risk screening service in the preceding year. Overall good CVD risk knowledge, and perception among the study participants was 77.2% and 19.6% respectively. Education, urban settlement, family history of CVD, good overall CVD risk knowledge and perception were predictors of the utilization of CVD risk screening services. CONCLUSION: A significant proportion of the study participants reported multiple CVD risk behaviours, had poor risk perception and utilization of risk screening services despite having a good overall CVD risk knowledge. There is need for concerted efforts by the relevant stakeholder in the State Ministry of Health to target the adult population in the study setting with health promotion information on CVD risk prevention and the benefits of early risk detection.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".