Social Networks May Shape Visually Impaired Older Adults’ Occupational Engagement: A Narrative Inquiry
Bibliographic record
Abstract
Age-related vision loss (ARVL) has been shown to interfere with older adults' occupational engagement. The primary purpose was to examine the role social networks play in facilitating/constraining engagement in desired occupations for older adults with ARVL. This study adopted a constructivist narrative methodology. Five older adults, ≥ 60 years of age with ARVL, participated in three virtual interviews, which were coded using thematic analysis. Three overarching themes were identified: (a) Diverse Social Networks Fulfill Different Occupational and Psychosocial Needs, (b) Retaining a Sense of Independence through Seeking Reciprocity in Social Relationships, and (c) Community Mobility and Technology Support as Essential for Preserving Social Relationships. Findings broaden understandings of how informal/formal social networks are involved in shaping visually-impaired older adults' adaptation to ARVL and related occupational changes. Findings may help improve the quality and delivery of low-vision rehabilitation services to optimize their contribution to occupational engagement.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".