Smartphone-Based Experience Sampling in People With Mild Cognitive Impairment: Feasibility and Usability Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Daily functioning of people with cognitive disorders such as mild cognitive impairment (MCI) is usually depicted by retrospective questionnaires, which can be memory-biased and neglect fluctuations over time or contexts. OBJECTIVE: This study examines the feasibility and usability of applying the experience sampling method (ESM) in people with MCI to provide a detailed and dynamic picture of behavioral, emotional, and cognitive patterns in everyday life. METHODS: For 6 consecutive days, 21 people with MCI used an ESM app on their smartphones. At 8 semi-random timepoints per day, participants filled in momentary questionnaires on mood, activities, social context, and subjective cognitive complaints. Feasibility was determined through self-reports and observable human-technology interactions. Usability was demonstrated on an individual and group level. RESULTS: Of the 21 participants, 3 dropped out due to forgetting to carry their smartphones or forgetting the study instructions. In the remaining 18 individuals, the compliance rate was high, at 78.7%. Participants reported that momentary questions reflected their daily experiences well. Of the 18 participants, 13 (72%) experienced the increase in awareness of their own memory functions as pleasant or neutral. CONCLUSIONS: Support was found for the general feasibility of smartphone-based experience sampling in people with MCI. However, many older adults with MCI are currently not in possession of smartphones, and study adherence seems challenging for a minority of individuals. Momentary data can increase the insights into daily patterns and may guide the person-tailored development of self-management strategies in clinical settings.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it