| 1. |
|
|
| 2. |
- Astell, A. J., et al.
(författare)
-
Developing a pragmatic evaluation of ICTs for older adults with cognitive impairment at scale : the IN LIFE experience
- 2022
-
Ingår i: Universal Access in the Information Society. - Heidelberg, Germany : Springer. - 1615-5289 .- 1615-5297. ; 21:1, s. 1-19
-
Tidskriftsartikel (refereegranskat)abstract
- Implementing information and communications technology (ICT) at scale requires evaluation processes to capture the impacton users as well as the infrastructure into which it is being introduced. For older adults living with cognitive impairment, thisrequires evaluation that can accommodate diferent levels of cognitive impairment, alongside input from family and formalcaregivers, plus stakeholder organisations. The European Horizon 2020 project INdependent LIving support Functions forthe Elderly (IN LIFE) set out to integrate 17 technologies into a single digital platform for older people living with cognitive impairment plus their families, care providers and stakeholders. The IN LIFE evaluation took place across six nationalpilot sites to examine a number of variables including impact on the users, user acceptance of the individual services andthe overall platform, plus the economic case for the IN LIFE platform. The results confrmed the interest and need amongolder adults, family caregivers, formal caregivers and stakeholders, for information and communications technology (ICT).Relative to the baseline, quality of life improved and cognition stabilised; however, there was an overall reluctance to payfor the platform. The fndings provide insights into existing barriers and challenges for adoption of ICT for older peopleliving with cognitive impairment.
|
|
| 3. |
- Astell, A. J., et al.
(författare)
-
Developing a pragmatic evaluation of ICTs for older adults with cognitive impairment at scale: the IN LIFE experience
- 2021
-
Ingår i: Universal Access in the Information Society. - Heidelberg, Germany : Springer. - 1615-5289 .- 1615-5297.
-
Tidskriftsartikel (refereegranskat)abstract
- Implementing information and communications technology (ICT) at scale requires evaluation processes to capture the impact on users as well as the infrastructure into which it is being introduced. For older adults living with cognitive impairment, this requires evaluation that can accommodate different levels of cognitive impairment, alongside input from family and formal caregivers, plus stakeholder organisations. The European Horizon 2020 project INdependent LIving support Functions for the Elderly (IN LIFE) set out to integrate 17 technologies into a single digital platform for older people living with cognitive impairment plus their families, care providers and stakeholders. The IN LIFE evaluation took place across six national pilot sites to examine a number of variables including impact on the users, user acceptance of the individual services and the overall platform, plus the economic case for the IN LIFE platform. The results confirmed the interest and need among older adults, family caregivers, formal caregivers and stakeholders, for information and communications technology (ICT). Relative to the baseline, quality of life improved and cognition stabilised; however, there was an overall reluctance to pay for the platform. The findings provide insights into existing barriers and challenges for adoption of ICT for older people living with cognitive impairment.
|
|
| 4. |
|
|
| 5. |
|
|
| 6. |
|
|
| 7. |
- Fagerberg, P, et al.
(författare)
-
Fast Eating Is Associated with Increased BMI among High-School Students
- 2021
-
Ingår i: Nutrients. - : MDPI AG. - 2072-6643. ; 13:3
-
Tidskriftsartikel (refereegranskat)abstract
- Fast self-reported eating rate (SRER) has been associated with increased adiposity in children and adults. No studies have been conducted among high-school students, and SRER has not been validated vs. objective eating rate (OBER) in such populations. The objectives were to investigate (among high-school student populations) the association between OBER and BMI z-scores (BMIz), the validity of SRER vs. OBER, and potential differences in BMIz between SRER categories. Three studies were conducted. Study 1 included 116 Swedish students (mean ± SD age: 16.5 ± 0.8, 59% females) who were eating school lunch. Food intake and meal duration were objectively recorded, and OBER was calculated. Additionally, students provided SRER. Study 2 included students (n = 50, mean ± SD age: 16.7 ± 0.6, 58% females) from Study 1 who ate another objectively recorded school lunch. Study 3 included 1832 high-school students (mean ± SD age: 15.8 ± 0.9, 51% females) from Sweden (n = 748) and Greece (n = 1084) who provided SRER. In Study 1, students with BMIz ≥ 0 had faster OBER vs. students with BMIz < 0 (mean difference: +7.7 g/min or +27%, p = 0.012), while students with fast SRER had higher OBER vs. students with slow SRER (mean difference: +13.7 g/min or +56%, p = 0.001). However, there was “minimal” agreement between SRER and OBER categories (κ = 0.31, p < 0.001). In Study 2, OBER during lunch 1 had a “large” correlation with OBER during lunch 2 (r = 0.75, p < 0.001). In Study 3, fast SRER students had higher BMIz vs. slow SRER students (mean difference: 0.37, p < 0.001). Similar observations were found among both Swedish and Greek students. For the first time in high-school students, we confirm the association between fast eating and increased adiposity. Our validation analysis suggests that SRER could be used as a proxy for OBER in studies with large sample sizes on a group level. With smaller samples, OBER should be used instead. To assess eating rate on an individual level, OBER can be used while SRER should be avoided.
|
|
| 8. |
|
|
| 9. |
|
|
| 10. |
- Langlet, B, et al.
(författare)
-
Predicting Real-Life Eating Behaviours Using Single School Lunches in Adolescents
- 2019
-
Ingår i: Nutrients. - : MDPI AG. - 2072-6643. ; 11:3
-
Tidskriftsartikel (refereegranskat)abstract
- Large portion sizes and a high eating rate are associated with high energy intake and obesity. Most individuals maintain their food intake weight (g) and eating rate (g/min) rank in relation to their peers, despite food and environmental manipulations. Single meal measures may enable identification of “large portion eaters” and “fast eaters,” finding individuals at risk of developing obesity. The aim of this study was to predict real-life food intake weight and eating rate based on one school lunch. Twenty-four high-school students with a mean (±SD) age of 16.8 yr (±0.7) and body mass index of 21.9 (±4.1) were recruited, using no exclusion criteria. Food intake weight and eating rate was first self-rated (“Less,” “Average” or “More than peers”), then objectively recorded during one school lunch (absolute weight of consumed food in grams). Afterwards, subjects recorded as many main meals (breakfasts, lunches and dinners) as possible in real-life for a period of at least two weeks, using a Bluetooth connected weight scale and a smartphone application. On average participants recorded 18.9 (7.3) meals during the study. Real-life food intake weight was 327.4 g (±110.6), which was significantly lower (p = 0.027) than the single school lunch, at 367.4 g (±167.2). When the intra-class correlation of food weight intake between the objectively recorded real-life and school lunch meals was compared, the correlation was excellent (R = 0.91). Real-life eating rate was 33.5 g/min (±14.8), which was significantly higher (p = 0.010) than the single school lunch, at 27.7 g/min (±13.3). The intra-class correlation of the recorded eating rate between real-life and school lunch meals was very large (R = 0.74). The participants’ recorded food intake weights and eating rates were divided into terciles and compared between school lunches and real-life, with moderate or higher agreement (κ = 0.75 and κ = 0.54, respectively). In contrast, almost no agreement was observed between self-rated and real-life recorded rankings of food intake weight and eating rate (κ = 0.09 and κ = 0.08, respectively). The current study provides evidence that both food intake weight and eating rates per meal vary considerably in real-life per individual. However, based on these behaviours, most students can be correctly classified in regard to their peers based on single school lunches. In contrast, self-reported food intake weight and eating rate are poor predictors of real-life measures. Finally, based on the recorded individual variability of real-life food intake weight and eating rate, it is not advised to rank individuals based on single recordings collected in real-life settings.
|
|
