Patient and Carer-Related Facilitators and Barriers to the Adoption of Assistive Technologies for the Care of Older Adults: Systematic Review
Bibliographic record
Abstract
© Stephen Malden, Kris McGill, Bruce Guthrie, Helen Frost, Susan D Shenkin, Adanna Ezike, Beth Bareham, Stewart W Mercer, Caroline Pearce, Cara Wilson, Ian Underwood, John Vines, Sue Lewis, Amy O'Donnell. Background: Assistive technologies (ATs) are used increasingly in community settings to assist in the care of older adults. Despite a rapid increase in the capabilities and uptake of these technologies, gaps remain in understanding the main barriers to their usage. Objective: This systematic review investigated the barriers and facilitators to the use of AT in the care of older adults. Methods: Six electronic databases were searched from January 2011 to March 2024. Primary studies were included if they used qualitative methods reporting findings related to barriers or facilitators to the implementation of AT (eg, ambient and wearable sensors, alarms, telehealth or mobile health [mHealth]) for older adults (from the perspective of either carers or older adults) in community settings. All data were screened independently by two reviewers. Study quality was assessed using the Critical Appraisal Skills Program (CASP). Data from each included study were synthesized using thematic synthesis, before barriers were mapped against the domains of the Technology Acceptance Model (TAM). Results: Ninety-five studies were included in the review. The number of studies published in the field of barriers to AT use has increased 3-fold post-COVID-19 in comparison to the previous decade. Ten barriers—privacy, cost, insufficient knowledge, fear of misuse, usability, poor functionality, perceived lack of need, stigma, and lack of human interaction—were identified, as well as three facilitators—awareness of health benefits, targeted training, and user-centered design. Persistent barriers relating to all domains of the TAM were identified, with the majority of these relating to the “behavioral intention to use” domain (cost, privacy, stigma, and fear of misuse). The majority of studies had a moderate/high risk of bias. Conclusions: There remain distinct barriers to sustained usage of AT for the care of older adults, particularly concerning adoption as defined by the TAM. Further studies investigating the acceptability of ATs are needed to increase the understanding of optimization strategies.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".