Habitual behavior is often hard to change because of a lack of self-monitoring skills. Digital technologies offer an unprecedented chance to facilitate self-monitoring by delivering feedback on undesired habitual behavior. This review analyzed the results of 72 studies in which feedback from digital technology attempted to disrupt and change undesired habits. A vast majority of these studies found that feedback through digital technology is an effective way to disrupt habits, regardless of target behavior or feedback technology used.
Background Eating behaviour of older adults is influenced by a complex interaction of determinants. Understanding the determinants of a specific target group is important when developing targeted health-promoting strategies. The aim of this study was to explore interpersonal determinants of eating behaviours in older adults living independently in a specific neighbourhood in the Netherlands. Methods In the neighbourhood of interest, populated by relatively many older adults, fifteen semi-structured interviews were conducted with independently living older adults (aged 76.9 ± 6.4y). Interviews were complemented with observations among the target group: three occasions of grocery shopping and three collective eating occasions in the neighbourhood. A thematic approach was used to analyse the qualitative data. Results When we asked the older adults unprompted why they eat what they eat, the influence of interpersonal determinants did not appear directly; respondents rather mentioned individual (e.g. habits) and environmental factors (e.g. food accessibility). Key findings regarding interpersonal factors were: 1) Behaviours are shaped by someone’s context; 2) Living alone influences (determinants of) eating behaviour via multiple ways; 3) There is a salient norm that people do not interfere with others’ eating behaviour; 4) Older adults make limited use of social support (both formal and informal) for grocery shopping and cooking, except for organised eating activities in the neighbourhood. In this particular neighbourhood, many facilities (e.g. shops at walking distance) are present, and events (e.g. dinners) are organised with and for the target group, which likely impact (determinants of) their behaviours. Conclusions The study showed that older adults do not directly think of interpersonal factors influencing their eating behaviour, but rather of individual or environmental factors. However, multiple interpersonal factors did appear in the interviews and observations. Moreover, neighbourhood-specific factors seem to play a role, which underlines the need to understand the specific (social) setting when developing and implementing intervention programmes. Insights from this study can assist in developing health-promoting strategies for older adults, taking into account the context of the specific neighbourhood.
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Smartphones and similar devices allow access to a wealth of information. Navigating this wealth of information is problematic. Semantic locations, assigned to observed GPS user movements, can help in providing inforamtion that is useful to the user at a specific time or place. This paper shows how a stream of sensor data can be processed and interpreted to determine (i) the locations of interest for a user, such as home, work, etc, and (ii) to predict the expected future transitions between such locations. We have implemented our algorithms in a fully functional prototype smartphone app and backend, and we present results based on actual usage data gathered over the past few months. We conclude that inferred semantic location information allows a smart device to offer personalized, contextual, information without the need for the user to perform any explicit query. Our system is open source, and can be used to build context-aware recommender systems that suggest content which is at the right time and at the right place.
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