Protocol for an acceptability and feasibility study of sensor‐instrumented SmartSocks® for use by people with dementia
Bibliographic record
Abstract
Abstract Background Currently ∼50% of people with dementia experience behavioural symptoms linked to unmanaged distress. Effective and safe management of these symptoms is critical to maintain the quality of life and overall care of people with dementia. Technological solutions have the potential to help with research into these symptoms. Milbotix are a health tech start‐up who are developing ‘SmartSocks®, a sock‐based wearable that provides wellbeing insights: notably by continually monitoring the physiological state of the wearer to recognise early signs of distress. In this study we will assess the acceptability and feasibility of SmartSocks® for clinical research in dementia in a care home environment. Method 30 people with dementia living in care homes in the UK will be asked to wear the SmartSocks®. We will conduct a survey of care home staff to assess the acceptability of the SmartSocks® so that we can ensure the socks are suitable for the care home environment. We will then carry out a focus group with care home staff to evaluate the integration of the SmartSocks® into care planning so that we can determine how care homes use the socks alongside best practice in care. We will determine the concurrent validity of SmartSocks® data with established measures of agitation and pain so that we can evaluate the potential of the socks to be used to deliver better care and used as objective outcome measures in clinical trials. Finally, we will estimate the cost of providing the socks and will assess if there are differences between the groups in resource use utilization and health related quality of life data. Result We present a protocol for feasibility and acceptability study of a novel wearable technology. Conclusion The study will start recruiting in July 2024 and finish in December 2024. Results will be used to inform the design of larger substantive studies that will test the efficacy of SmartSocks® in managing and measuring agitation and distress in care homes.
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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 | 0.054 | 0.060 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.113 | 0.032 |
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".