Communication technology adoption among older adult veterans: the interplay of social and cognitive factors
Bibliographic record
Abstract
OBJECTIVES: InTouch is an electronic communication platform designed to be accessible by computer-naive seniors. The present study explored the process of adoption and use of the application by seniors with and without mild cognitive impairment (MCI) through the lens of Social Cognitive Theory (SCT). METHOD: We studied adoption and use of InTouch for social communication over a 12-week period in a 475-bed Veteran's care facility at Sunnybrook Health Sciences Centre in Toronto, Canada. Eleven older adult veterans participated, six of whom had MCI, as indicated by their Montreal Cognitive Assessment score. Veterans were partnered with volunteers, each was provided with an iPad with the InTouch application. Qualitative data were collected through interviews, field notes, and direct observation. Quantitative data were collected from data logging of the software and medical charts. Data types and sources were triangulated and examined through the lens of SCT. RESULTS: A total of 2361 messages (102 videos, 359 audios, 417 photos, 1438 texts) were sent by 10 of the 11 veterans over the 12-week study period. There was no apparent difference in extent of adoption or use, between participants with and without MCI. Participants used various resources and techniques to learn, provided that they felt motivated to connect with others using the app. CONCLUSION: This pilot illustrates both the accessibility of InTouch and the promise of using extrinsic motivators such as social bonding to promote learning in institutionalized older adults with and without cognitive impairment, whose intrinsic motivation and self-efficacy may well be suffering.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".