Identifying the methods and metrics used to assess and describe sedentary behaviour in people with cognitive impairment: A systematic review
Bibliographic record
Abstract
BACKGROUND: Greater sedentary behaviour (SB) is associated with adverse outcomes, including loss of functional independence, disability, and dementia. Few studies have investigated SB in people living with cognitive impairment (PwCI), including mild cognitive impairment (MCI) and dementia. Current evidence suggests PwCI are more sedentary than their peers without cognitive impairment, highlighting the need to reduce SB to improve health and mitigate disability. However, our understanding of how to accurately and reliably measure SB in PwCI is limited and precludes developing effective methods to reduce SB. Device-based measures provide sensitive estimates of SB, although it is unclear whether these devices are accurate and reliable across PwCI. The lack of synthesised literature limits understanding of the common measures used to investigate SB in PwCI. To address knowledge gaps, we conducted a systematic review to identify the current device-based methods for assessing SB in PwCI. METHODS: This systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Figure 1). 2,029 articles were identified following initial search, 16 were included based on predetermined criteria (Table 1) following a review of titles, abstracts and full texts. RESULTS: Of the included 16 studies (total N = 1,675 (range: 8-414), 55% female, age range: 68-91.7) seven studies investigated MCI, seven investigated dementia and two investigated both MCI and dementia. Cognitive impairment was assessed via the Mini Mental State Examination (MMSE) (n = 11, score range:15.5-28.65), and the Montreal Cognitive Assessment (MoCA) (n = 5, score range:13.1-24) and the Clinical Dementia Rating Scale (CDR) (n = 1). All studies employed accelerometery to measure SB in PwCI. Ten different accelerometer devices were used; devices were placed on the wrist (n = 7), trunk (n = 8), and thigh (n = 1). Metrics used to describe SB were commonly related to SB volume (Table 2). CONCLUSION: The results of this review will guide future selection of digital tools and measures to investigate SB in PwCI. Recommendations will advise the most appropriate protocols to monitor and measure SB in PwCI, supporting personalised care across cognitive impairment and care settings.
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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 | 0.066 | 0.234 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.019 |
| Bibliometrics | 0.024 | 0.021 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".