Challenges to Social Connection Among Black Men with Chronic Conditions: Examination of Structural, Functional, and Quality Domains
Bibliographic record
Abstract
Objectives: Limited social connection places individuals at greater risk for chronic conditions; however, there is limited research examining the association between chronic conditions and barriers to disease self-management on social connections. Our study addresses this gap in the empirical literature by examining these issues among Black men aged 40+ years with 1 or more chronic conditions. Methods: Data came from a national sample of 1200 Black men. We conducted 3 multivariate logistic regression models examining social connection domains (did not have people to call for help, felt isolated from others, and were not content with relationships/friendships) on 3 independent variables: the number of chronic health conditions, cut down or skipped social activities because of health problems, and self-reported barriers to disease self-management. Sociodemographic covariates for all regression models included age, education, partner status, and annual household income. Results: Men were aged 56.7 (±9.7) years and self-reported 4.0 (±2.9) chronic conditions. Approximately 1 in 4 participants reported that they did not have enough people to call for help (25.2%), felt isolated from others (26.0%), and were not content with friendships/relationships (23.8%). Across multivariate models, men who reported more barriers to disease self-management were significantly more likely to report a social connection domain challenge. The number of chronic conditions and cutting down or skipping social activities because of health problems were also associated with a greater likelihood of social connection challenges. Conclusions: Efforts to improve the self-management of illness symptomology may mitigate challenges to social connection among middle-aged and older Black men.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".