Biopsychosocial Profiles of Patients With Cardiac Disease in Remote Rehabilitation Processes: Mixed Methods Grounded Theory Approach
Bibliographic record
Abstract
BACKGROUND: Digital development has caused rehabilitation services and rehabilitees to become increasingly interested in using technology as a part of rehabilitation. This study was based on a previously published study that categorized 4 groups of patients with cardiac disease based on different experiences and attitudes toward technology (e-usage groups): feeling outsider, being uninterested, reflecting benefit, and enthusiastic using. OBJECTIVE: This study identifies differences in the biopsychosocial profiles of patients with cardiac disease in e-usage groups and deepen the understanding of these profiles in cardiac rehabilitation. METHODS: Focus group interviews and measurements were conducted with 39 patients with coronary heart disease, and the mean age was 54.8 (SD 9.4, range 34-77) years. Quantitative data were gathered during a 12-month rehabilitation period. First, we used analysis of variance and Tukey honestly significant difference test, a t test, or nonparametric tests-Mann-Whitney and Kruskal-Wallis tests-to compare the 4 e-usage groups-feeling outsider, being uninterested, reflecting benefit, and enthusiastic using-in biopsychosocial variables. Second, we compared the results of the 4 e-groups in terms of recommended and reference values. This analysis contained 13 variables related to biomedical, psychological, and social functioning. Finally, we formed biopsychosocial profiles based on the integration of the findings by constant comparative analysis phases through classic grounded theory. RESULTS: The biomedical variables were larger for waistline (mean difference [MD] 14.2; 95% CI 1.0-27.5; P=.03) and lower for physical fitness (MD -0.72; 95% CI -1.4 to -0.06; P=.03) in the being uninterested group than in the enthusiastic using group. The feeling outsider group had lower physical fitness (MD -55.8; 95% CI -110.7 to -0.92; P=.047) than the enthusiastic using group. For psychosocial variables, such as the degree of self-determination in exercise (MD -7.3; 95% CI -13.5 to -1.1; P=.02), the being uninterested group had lower values than the enthusiastic using group. Social variables such as performing guided tasks in the program (P=.03) and communicating via messages (P=.03) were lower in the feeling outsider group than in the enthusiastic using group. The feeling outsider and being uninterested groups had high-risk lifestyle behaviors, and adherence to the web-based program was low. In contrast, members of the being uninterested group were interested in tracking their physical activity. The reflecting benefit and enthusiastic using groups had low-risk lifestyle behavior and good adherence to web-based interventions; however, the enthusiastic using group had low self-efficacy in exercise. These profiles showed how individuals reflected their lifestyle risk factors differently. We renamed the 4 groups as building self-awareness, increasing engagement, maintaining a healthy lifestyle balance, and strengthening self-confidence. CONCLUSIONS: The results facilitate more effective and meaningful personalization guidance and inform the remote rehabilitation. Professionals can tailor individual web-based lifestyle risk interventions using these biopsychosocial profiles.
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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 | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 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".