Assessing Situational Awareness for Healthful Behaviors and the “Self-Care Gap” Among Non-Hispanic Black and Hispanic Men With Chronic Conditions
Bibliographic record
Abstract
ObjectiveThis study sought to identify factors associated with (1) situational awareness (i.e., daily recognition of situations to make choices to act in the best interest of one's health) and (2) the self-care gap (i.e., not acting in one's best interest despite having recognized at least one opportunity to perform healthful behaviors).MethodsData from 1,761 non-Hispanic Black (58.4%) and Hispanic (41.6%) men aged 40 years or older with chronic conditions were collected using an internet-delivered questionnaire. Two linear regression models were fitted to assess factors associated with situational awareness and the self-care gap, respectively. Regression models were adjusted for sociodemographics, disease symptomatology, preventive screening activity, health behaviors, and health-related perceptions.ResultsSituational awareness levels were lower for older individuals (B = -.03, p < .001). Men who had higher fatigue (B = .11, p = .002), more stress (B = .07, p = .032), utilized more prevention screenings (B = .13, p = .001), adhered to physical activity guidelines (B = .36, p = .044), and received more social support (B = .89, p < .001) reported higher situational awareness. The self-care gap was more pronounced among non-Hispanic Black men (B = -.32, p = .026). Men who reported higher fatigue (B = .06, p = .041), clinical depression (B = .39, p = .039), more barriers to self-care (B = .11, p < .001), and higher frustrations with health care (B = .12, p < .001) were associated with greater self-care gaps.ConclusionsMen's recognition of healthful opportunities was largely driven by their disease symptomatology, greater engagement in preventive screenings, and receiving social support. However, the self-care gap was seemingly driven by mental health and challenges with disease self-management and health care interactions. Efforts are needed to narrow disparities in the self-care gap between non-Hispanic Black and Hispanic men.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".