Analysing comfort with primary care discussions and openness to social prescribing as mediators of the associations between loneliness and wellbeing among Canadians aged 55 and older
Bibliographic record
Abstract
Abstract Background Addressing the complex health and wellbeing challenges of older adults is a critical public health priority as populations age. Social Prescribing (SP) represents a promising strategy, connecting patients to non-clinical, community-based resources to enhance physical, mental, and social wellbeing. Methods To develop a SP theory of change, this study used cross-sectional data from 2,450 community-dwelling older adults who participated in a population survey. Factor analyses identified four factors of comfort with primary care discussions (general, mental, physical, and social wellness) and three factors of openness to SP (effectiveness, meaningfulness, and supportiveness). Path analysis was conducted for each set of mediators separately. Results Path analyses revealed that comfort with primary care discussions about social wellness (β = 0.08**) is associated with better wellbeing. People who report social loneliness are most comfortable with primary care discussions about general wellness (β = − 0.17***) and least comfortable with primary care discussions about mental wellness (β = − 0.24***), whereas people who report emotional loneliness are more likely to have similar levels of comfort to discuss general wellness and mental wellness (β = − 0.18***; − 0.18***). In addition, social loneliness is associated with less comfort with primary care discussions about social wellness (β = − 0.19***) and mental wellness (β = − 0.19***), whereas association is not found for emotional loneliness. These suggest that addressing the SP needs of people who experience emotional loneliness requires a different strategy. Reporting emotional loneliness is associated with expressing support for SP (β = 0.14***), which may be key to improving wellbeing (β = 0.10***) among this population. Overall, social loneliness has a total effect size of β total = − 0.19, whereas emotional loneliness has a total effect size of β total = − 0.45, more than 2.3 times larger. Conclusions While SP may be acceptable to those who need it, some may experience greater difficulties accessing SP through primary care providers without interventions tailored to their loneliness status that could elicit buy-in and enrolment. Primary care providers may wish to pay closer attention to people with emotional loneliness. Other considerations, such as trust and motivational interviewing for positive self-beliefs may explain potential changes from loneliness to wellbeing.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".