Exploring the Impact of a Digital Reading Program on Apathy Among Community-Dwelling Older Adults in Rural Canada: Insights from Socioemotional Selectivity Theory
Bibliographic record
Abstract
Background/Objectives: Apathy, characterized by diminished motivation and reduced engagement in goal-directed behavior, is a prevalent concern among older adults, particularly in rural communities where opportunities for meaningful engagement may be limited. This study explores the preliminary impact of an in-person eBook club program on apathy among community-dwelling older adults in Northern British Columbia. Methods: This eight-week pilot single-group, pre-post mixed-methods study combined the use of eReaders to access weekly reading materials with facilitated in-person group discussions designed to foster emotional and social connection. Apathy was assessed using the 3-item Geriatric Depression Scale (GDS-3A) before and after the program. Results: A Wilcoxon signed-rank test revealed a statistically significant reduction in apathy scores (Z = −4.01, p < 0.001), with a large effect size (r = 0.76). While not powered for hypothesis testing, these findings suggest the program may have a meaningful effect. Qualitative analysis of participants who reported higher baseline apathy scores identified three key mechanisms of change: positivity effect, selective pruning of social networks, and adaptive coping, consistent with socioemotional selectivity theory. Conclusions: These preliminary results support the feasibility and potential value of theory-informed, low-cost group reading programs for addressing apathy in older adults and can inform the design of a larger, controlled study.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".