Impacts of Motion-Based Technology on Balance, Movement Confidence, and Cognitive Function Among People With Dementia or Mild Cognitive Impairment: Protocol for a Quasi-Experimental Pre- and Posttest Study
Bibliographic record
Abstract
BACKGROUND: While exercise can benefit the health and well-being of people with dementia or mild cognitive impairment, many exercise programs offered to this population are passive, unengaging, and inaccessible, resulting in poor adherence. Motion-based technologies are increasingly being explored to encourage exercise participation among people with dementia or mild cognitive impairment. However, the impacts of using motion-based technologies with people with dementia or mild cognitive impairment on variables including balance, movement confidence, and cognitive function have yet to be determined. OBJECTIVE: The purpose of this study is to examine the impacts of a group motion-based technology intervention on balance, movement confidence, and cognitive function among people with dementia or mild cognitive impairment. METHODS: In this quasi-experimental pre- and posttest design, we will recruit 24 people with dementia or mild cognitive impairment from 4 adult day programs and invite them to play Xbox Kinect bowling in a group setting, twice weekly for 10 weeks. We will require participants to speak and understand English, be without visual impairment, and be able to stand and walk. At pretest, participants will complete the Mini-Balance Evaluation Systems Test (Mini-BESTest) and the Montreal Cognitive Assessment (MoCA). We will video record participants during weeks 1, 5, and 10 of the intervention to capture behavioral indicators of movement confidence (eg, fluency of motion) through coding. At posttest, the Mini-BESTest and MoCA will be repeated. We will analyze quantitative data collected through the Mini-BESTest and the MoCA using an intent-to-treat analysis, with study site and number of intervention sessions attended as covariates. To analyze the videos, we will extract count and percentage data from the coded recordings. RESULTS: This study will address the question of whether a group motion-based technology intervention, delivered in an adult day program context, has the potential to impact balance, movement confidence, and cognitive function among people with dementia or mild cognitive impairment. The project was funded in 2019 and enrollment was completed on February 28, 2020. Data analysis is underway and the first results are expected to be submitted for publication in 2021. CONCLUSIONS: This study will assess the feasibility and potential benefits of using motion-based technology to deliver exercise interventions to people with dementia or mild cognitive impairment. This work can also be used as the basis for developing specific software and future exercise programs using motion-based technology for people with dementia or mild cognitive impairment, as well as understanding some of the conditions in which these programs can be delivered. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/18209.
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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 | 0.020 | 0.014 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.041 | 0.008 |
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".