Behavioural Coding and Analysis of persons living with Dementia in their own home.
- Submitting institution
-
University of Wales Trinity Saint David / Prifysgol Cymru Y Drindod Dewi Sant
- Unit of assessment
- 32 - Art and Design: History, Practice and Theory
- Output identifier
- TS1
- Type
- T - Other
- DOI
-
-
- Location
- eHealth Digital Media Ltd
- Brief description of type
- Data set and documentary film
- Open access status
- Out of scope for open access requirements
- Month
- August
- Year
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Research was commissioned by eHealth Digital Media, who produce behavioural change content via the PocketMedic platform. The brief was to: a) Investigate the day-to-day challenges that dementia sufferers present in domestic situations; b) identify key behavioural patterns to help improve both the carer-patient interaction and the utilitarian aspects of home living; c) develop a research dataset for subsequent development of an e-health resource. Advanced User Experience (UX) & behavioural research tools were used in an observational study with two identified cohabiting participants living with dementia. This utilised eye-tracking technology and multiple cameras to capture insight into the daily experiences of patients, carers and relatives and a behavioural coding system based on the Activities of Daily Living framework. Activity patterns, incidents and the challenges faced in day to day living were recorded and coded using specialist software to produce a dataset of point-events (moments) and state-events (over a duration) that can be orchestrated into representative digital content, recording a state-events such as ‘Dressing’ and point-events, such as ‘Spatial Difficulty’. Key moments, or montaged sequences were evaluated to give the observations a richer critical scientific context and underpinning.
Research insights include a dataset of coded behavioural patterns has been generated that informs a deeper understanding of the experience of living with dementia. By comprehensively tagging the observation, the research compiles patterns and repetitions in behaviour longitudinally. The dataset was delivered to eHealth Digital Media Ltd for adoption in the PocketMedic platform. The dataset, comprising 10 curated videos, coding and summary has reviewed by clinicians and academics, and is being developed for a new PocketMedic health resource (subscription based to NHS, clinicians, healthcare professionals and carers). Digital content from the dataset has been disseminated through a series of video narratives in collaboration with PocketMedic. First disseminated Aug 2019.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -