Facilitators and barriers faced by community organizations supporting older adults during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: During the COVID-19 pandemic, olderadult-focused community organizations played an essential role in supporting the wellbeing of older adults. Supporting older adults during this time required extensive modifications to existing programming but their adaptations during the COVID-19 pandemic are not well documented. The purpose of this study was to understand how older adult-focused community organizations adopted virtual delivery formats during the COVID-19 pandemic and their perspectives of the barriers and facilitators for organizations and older adults. METHODS: To understand the changes that were made, we conducted a qualitative environmental scan of community-based services across British Columbia. Online searches were complemented by snowball sampling and key informant interviews. We identified 90 older adult-serving community organizations and interviewed 26. We used reflexive thematic analysis to understand the main strategies. RESULTS: These community organizations described barriers related to older adults' wellbeing, information technology proficiency, and personal/organizational losses related to changes in program structure. Facilitators for virtual activities and events included inter- and intra-organizational collaboration, intrinsic qualities of program design, physical resources to supporting virtual programming, and availability of technological resources. Organizations described meeting the challenge by increasing the 'depth' and 'breadth' of their reach. CONCLUSION: Older adult-focused community organizations recognized the critical role they played for older adults and adapted their resources to meet those needs. Informational technology was quickly and effectively leveraged to promote social interaction for older adults when physical distancing was required during the COVID-19 pandemic. Barriers related to cost, time, and ultimately older adults' interest in a virtual delivery format were critical limitations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".