Mental health and the relationship between health promotion counseling and health outcomes in chronic conditions
Bibliographic record
Abstract
Objective To explore the relationship between health promotion counseling (HPC) provided by FPs and health-related quality of life (HRQL) and the use of health care services among patients with chronic conditions, while assessing the effect of mental health on these relationships. Design Telephone survey using random-digit dialing. Setting Alberta. Participants A total of 1615 participants with chronic conditions. Main outcome measures Health promotion counseling provided by FPs, which was assessed using 4 questions; HRQL using the Euro quality of life 5-dimensions (EQ-5D) questionnaire; and the use of health care services assessed with self-reported emergency department (ED) visits and hospitalizations. Results Of the 1615 participants with chronic conditions, 55% were female and more than two-thirds were older than age 45 years. Less than two-thirds of participants received HPC from their FPs. In patients without anxiety or depression, those who needed help from their FPs in making changes to prevent illness had a 0.05 lower EQ-5D score than those who did not ( P < .001); and those who received diet counseling had a 0.03 higher EQ-5D score than their counterparts did ( P = .048). However, these associations were not observed in patients with anxiety or depression. Patients were more likely to have visited EDs if they needed their physicians’ help in making changes to prevent illness (odds ratio 1.43, 95% CI 1.08 to 1.89) and less likely to visit EDs if they had been encouraged by their physicians to talk about their health concerns (odds ratio 0.69, 95% CI 0.52 to 0.91). None of the HPC items was associated with hospitalizations. Conclusion Not all patients with chronic conditions are receiving HPC from their FPs. Also, there is an association between HPC and important health outcomes (ie, HRQL and ED visits), but this association is not apparent for those with anxiety or depression.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".