scholarly journals The Conceptualization of a Just-in-Time Adaptive Intervention (JITAI) for the Reduction of Sedentary Behavior in Older Adults

2017 ◽  
Author(s):  
Andre M MMller ◽  
Ann Blandford ◽  
Lucy Yardley
Keyword(s):  
Older Adults ◽  
Sedentary Behavior ◽  
Just In Time ◽  
Adaptive Intervention

scholarly journals Associations between objectively measured physical activity, sedentary behaviour and time in bed among 75+ community-dwelling Danish older adults

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Li-Tang Tsai ◽  
Eleanor Boyle ◽  
Jan C. Brønd ◽  
Gry Kock ◽  
Mathias Skjødt ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Sedentary Behavior ◽  
Sedentary Behaviour ◽  
Sleep Duration ◽  
Activity Level ◽  
Time In Bed ◽  
Objectively Measured ◽  
Objectively Measured Physical Activity ◽  
Vector Magnitude

Abstract Background Older adults are recommended to sleep 7–8 h/day. Time in bed (TIB) differs from sleep duration and includes also the time of lying in bed without sleeping. Long TIB (≥9 h) are associated with self-reported sedentary behavior, but the association between objectively measured physical activity, sedentary behavior and TIB is unknown. Methods This study was based on cross-sectional analysis of the Healthy Ageing Network of Competence (HANC Study). Physical activity and sedentary behaviour were measured by a tri-axial accelerometer (ActiGraph) placed on the dominant wrist for 7 days. Sedentary behavior was classified as < 2303 counts per minute (cpm) in vector magnitude and physical activity intensities were categorized, as 2303–4999 and ≥ 5000 cpm in vector magnitude. TIB was recorded in self-reported diaries. Participants were categorized as UTIB (usually having TIB 7–9 h/night: ≥80% of measurement days), STIB (sometimes having TIB 7–9 h/night: 20–79% of measurement days), and RTIB (rarely having TIB 7–9 h/night: < 20% of measurement days). Multinominal regression models were used to calculate the relative risk ratios (RRR) of being RTIB and STIB by daily levels of physical activity and SB, with UTIB as the reference group. The models were adjusted for age, sex, average daily nap length and physical function. Results Three hundred and fourty-one older adults (median age 81 (IQR 5), 62% women) were included with median TIB of 8 h 21 min (1 h 10 min)/day, physical activity level of 2054 (864) CPM with 64 (15) % of waking hours in sedentary behavior. Those with average CPM within the highest tertile had a lower RRR (0.33 (0.15–0.71), p = 0.005) for being RTIB compared to those within the lowest tertile of average CPM. Accumulating physical activity in intensities 2303–4999 and ≥ 5000 cpm/day did not affect the RRR of being RTIB. RRR of being RTIB among highly sedentary participants (≥10 h/day of sedentary behavior) more than tripled compared to those who were less sedentary (3.21 (1.50–6.88), p = 0.003). Conclusions For older adults, being physically active and less sedentary was associated with being in bed for 7–9 h/night for most nights (≥80%). Future longitudinal studies are warranted to explore the causal relationship sbetween physical activity and sleep duration.

scholarly journals Conscious and Non-Conscious Processes Regulate Minority Older Adults’ Sedentary Behavior

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 335-335
Author(s):  
Jaclyn Maher ◽  
Derek Hevel ◽  
Kourtney Sappenfield ◽  
Heidi Scheer ◽  
Christine Zecca ◽  
...  
Keyword(s):  
Older Adults ◽  
Sedentary Behavior ◽  
Action Planning ◽  
Interactive Effects ◽  
Black African ◽  
Affective Consequences ◽  
Introductory Session ◽  
Conscious Processes ◽  
Multilevel Linear Regression ◽  
Age Range

Abstract Accumulating evidence suggests that sedentary behavior (SB), or time spent sitting, is regulated by both conscious (e.g., intentions) and non-conscious (e.g., habits) motivational processes. Much of the work investigating these processes has employed summary-based measures of typical motivation and behavior. This study employed ecological momentary assessment (EMA) methods and accelerometry to determine the extent to which conscious and non-conscious processes regulate minority older adults’ momentary decisions to engage in SB. Over the course of the 8-day study, minority older adults (N=91; age range: 60-89 years, 96% Black/African American) answered 6 EMA questionnaires/day on a mobile phone and wore an ActivPAL activity monitor to measure SB. EMA questionnaires assessed momentary intentions to limit SB over the next two hours. SB habit strength was self-reported at an introductory session. Results from a multilevel linear regression model indicated that on occasions when individuals had stronger intentions than usual to limit SB, they subsequently engaged in less SB (b=-3.72, p&lt;0.01). Individuals who had stronger SB habits, tended to engage in more SB (b=3.00, p&lt;0.01). An additional multilevel model revealed that habits did not significantly moderate the association between momentary intentions and subsequent SB (b=-1.06, p=0.09). In conclusion, minority older adults’ momentary SB appears to be directly influenced by both conscious and non-conscious motivational processes, though the interactive effects are unclear. Interventions to reduce minority older adults’ SB should include content to increase intentions to limit SB (e.g., information on instrumental and affective consequences) and disrupt habitual SB (e.g., action planning).

scholarly journals Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application: A Feasibility Study

2021 ◽  
Vol 18 (11) ◽  
pp. 6059
Author(s):  
Shihan Wang ◽  
Karlijn Sporrel ◽  
Herke van Hoof ◽  
Monique Simons ◽  
Rémi D. D. de Boer ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Physical Activities ◽  
Lessons Learned ◽  
Just In Time ◽  
Healthcare Intervention ◽  
Adaptive Intervention ◽  
Mobile Healthcare ◽  
Crucial Component ◽  
Application Data ◽  
The Right

Just-in-time adaptive intervention (JITAI) has gained attention recently and previous studies have indicated that it is an effective strategy in the field of mobile healthcare intervention. Identifying the right moment for the intervention is a crucial component. In this paper the reinforcement learning (RL) technique has been used in a smartphone exercise application to promote physical activity. This RL model determines the ‘right’ time to deliver a restricted number of notifications adaptively, with respect to users’ temporary context information (i.e., time and calendar). A four-week trial study was conducted to examine the feasibility of our model with real target users. JITAI reminders were sent by the RL model in the fourth week of the intervention, while the participants could only access the app’s other functionalities during the first 3 weeks. Eleven target users registered for this study, and the data from 7 participants using the application for 4 weeks and receiving the intervening reminders were analyzed. Not only were the reaction behaviors of users after receiving the reminders analyzed from the application data, but the user experience with the reminders was also explored in a questionnaire and exit interviews. The results show that 83.3% reminders sent at adaptive moments were able to elicit user reaction within 50 min, and 66.7% of physical activities in the intervention week were performed within 5 h of the delivery of a reminder. Our findings indicated the usability of the RL model, while the timing of the moments to deliver reminders can be further improved based on lessons learned.

scholarly journals The Role of Physical Activity and Sedentary Behavior in Predicting Daily Pain and Fatigue in Older Adults: a Diary Study

2017 ◽  
Vol 52 (1) ◽  
pp. 19-28 ◽  
Author(s):  
Saengryeol Park ◽  
Cecilie Thøgersen-Ntoumani ◽  
Jet J C S Veldhuijzen van Zanten ◽  
Nikos Ntoumanis
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Sedentary Behavior ◽  
Diary Study ◽  
Daily Pain

Social isolation due to COVID-19: impact on loneliness, sedentary behavior, and falls in older adults

2021 ◽  
pp. 1-8
Author(s):  
Beatriz Caruso Soares ◽  
Daniele Alves Costa ◽  
Juliana de Faria Xavier ◽  
Larissa Alamino Pereira de Viveiro ◽  
Thaiany Pedrozo Campos Antunes ◽  
...  
Keyword(s):  
Older Adults ◽  
Sedentary Behavior ◽  
Social Isolation ◽  
Falls In Older Adults
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