Effect of a tailored assistive technology intervention on older adults and their family caregiver: a pragmatic study protocol
Bibliographic record
Abstract
BACKGROUND: Many older adults with mobility limitations use assistive technology to help them perform daily activities. However, little attention has been paid to the impact on their family caregivers. This neglect produces an incomplete portrayal of the outcomes of assistive technology provision. This paper describes the protocol for a study that examines the impact of a tailored assistive technology intervention that is inclusive of assistance users and their family caregivers. METHODS/DESIGN: This research will use a combination of quantitative and qualitative methods. The quantitative portion will be an experimental, single-blinded study in which participants are randomly assigned to either an experimental assistive technology intervention or a standard care group. We will enroll 240 participants (120 dyads) into the study from three Canadian sites. Participants will include older adults (>55) and family caregivers who provide ≥4 h per week of assistance with daily activities and social participation. The primary outcome measure for the older adults will be the Functional Autonomy Measurement System, and the primary outcome measure for the caregivers will be the Caregiver Assistive Technology Outcomes Measure. Qualitative data will be collected through detailed records of the therapists' interventions, as well as through interviews with dyads and therapists following the interventions. Data collection will occur at baseline (T0) with follow-ups at 6 weeks (T1), 22 weeks (T2), and 58 weeks (T3) after baseline evaluation. DISCUSSION: The findings from this study will help service providers and clinicians to move forward with assistive technology recommendations that are more attuned to the needs of both older adults with mobility limitations and their family caregivers. Additionally, the study's findings will enhance our conceptual understanding of the spectrum of assistive technology outcomes and set the stage for econometric studies assessing cost-effectiveness. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01640470 . Registered 11/21/2011.
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 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 | 0.050 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 0.004 |
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".