7,351 research outputs found
Typical Phone Use Habits: Intense Use Does Not Predict Negative Well-Being
Not all smartphone owners use their device in the same way. In this work, we
uncover broad, latent patterns of mobile phone use behavior. We conducted a
study where, via a dedicated logging app, we collected daily mobile phone
activity data from a sample of 340 participants for a period of four weeks.
Through an unsupervised learning approach and a methodologically rigorous
analysis, we reveal five generic phone use profiles which describe at least 10%
of the participants each: limited use, business use, power use, and
personality- & externally induced problematic use. We provide evidence that
intense mobile phone use alone does not predict negative well-being. Instead,
our approach automatically revealed two groups with tendencies for lower
well-being, which are characterized by nightly phone use sessions.Comment: 10 pages, 6 figures, conference pape
Academic Performance and Behavioral Patterns
Identifying the factors that influence academic performance is an essential
part of educational research. Previous studies have documented the importance
of personality traits, class attendance, and social network structure. Because
most of these analyses were based on a single behavioral aspect and/or small
sample sizes, there is currently no quantification of the interplay of these
factors. Here, we study the academic performance among a cohort of 538
undergraduate students forming a single, densely connected social network. Our
work is based on data collected using smartphones, which the students used as
their primary phones for two years. The availability of multi-channel data from
a single population allows us to directly compare the explanatory power of
individual and social characteristics. We find that the most informative
indicators of performance are based on social ties and that network indicators
result in better model performance than individual characteristics (including
both personality and class attendance). We confirm earlier findings that class
attendance is the most important predictor among individual characteristics.
Finally, our results suggest the presence of strong homophily and/or peer
effects among university students
GPS-derived daily mobility and daily well-being in community-dwelling older adults
Introduction: Mobility as a multidimensional concept has rarely been examined as a day-to-day varying phenomenon in its within-person association with older adults’ daily well-being. This study examined associations between daily mobility and daily well-being in community-dwelling older adults with a set of GPS-derived mobility indicators that were representative of older adults’ daily mobility.
Methods: Participants wore a custom-built mobile GPS sensor (“uTrail”) and completed smartphone-based experience sampling questionnaires on momentary affective states (7 times per day) and daily life satisfaction (in the evening). Analyses included data across 947 days from 109 Swiss older adults aged 65–89 years.
Results: Multilevel modeling showed that, within persons, a day with a larger life space area, more time spent in passive transport modes, and a higher number of different locations was associated with higher daily life satisfaction but not daily positive or negative affect. Follow-up analysis showed that the daily maximum distance from home was positively associated with daily life satisfaction, providing a first indication that exposure to non-habitual environments might be a possible underlying mechanism to explain the effects of mobility.
Conclusions: Traveling a long distance away from home and visiting diverse locations may be a way to improve life satisfaction. Results are discussed in the context of research on healthy aging
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Technology and Caregiving: Emerging Interventions and Directions for Research.
An array of technology-based interventions has increasingly become available to support family caregivers, primarily focusing on health and well-being, social isolation, financial, and psychological support. More recently the emergence of new technologies such as mobile and cloud, robotics, connected sensors, virtual/augmented/mixed reality, voice, and the evermore ubiquitous tools supported by advanced data analytics, coupled with the integration of multiple technologies through platform solutions, have opened a new era of technology-enabled interventions that can empower and support family caregivers. This paper proposes a conceptual framework for identifying and addressing the challenges that may need to be overcome to effectively apply technology-enabled solutions for family caregivers. The paper identifies a number of challenges that either moderate or mediate the full use of technologies for the benefit of caregivers. The challenges include issues related to equity, inclusion, and access; ethical concerns related to privacy and security; political and regulatory factors affecting interoperability and lack of standards; inclusive/human-centric design and issues; and inherent economic and distribution channel difficulties. The paper concludes with a summary of research questions and issues that form a framework for global research priorities
Content validity and methodological considerations in ecological momentary assessment studies on physical activity and sedentary behaviour : a systematic review
Background Ecological momentary assessment (EMA) is a method of collecting real-time data based on repeated measures and observations that take place in participant's daily environment. EMA has many advantages over more traditional, retrospective questionnaires. However, EMA faces some challenges to reach its full potential. The aims of this systematic review are to (1) investigate whether and how content validity of the items (i.e. the specific questions that are part of a larger EMA questionnaire) used in EMA studies on physical activity and sedentary behaviour was assessed, and (2) provide an overview of important methodological considerations of EMA in measuring physical activity and sedentary behaviour. Methods Thirty papers (twenty unique studies) were systematically reviewed and variables were coded and analysed within the following 4 domains: (1) Content validity, (2) Sampling approach, (3) Data input modalities and (4) Degree of EMA completion. Results Only about half of the studies reported the specific items (n = 12) and the source of the items (n = 11). None of the studies specifically assessed the content validity of the items used. Only a minority (n = 5) of the studies reported any training, and one tested the comprehensibility of the EMA items. A wide variability was found in the design and methodology of the EMA. A minority of the studies (n = 7) reported a rationale for the used prompt frequency, time selection, and monitoring period. Retrospective assessment periods varied from 'now' to 'in the last 3.5 hours'. In some studies there was a possibility to delay (n = 6) or deactivate (n = 10) the prompt, and some provided reminders after the first prompt (n = 9). Conclusions Almost no EMA studies reported the content validation of the items used. We recommend using the COSMIN checklist (COnsensus-based Standards for the selection of health Measurement INstruments) to report on the content validity of EMA items. Furthermore, as often no rationale was provided for several methodological decisions, the following three recommendations are made. First, provide a rationale for choosing the sampling modalities. Second, to ensure assessment 'in the moment', think carefully about the retrospective assessment period, reminders, and deactivation of the prompt. Third, as high completion rates are important for representativeness of the data and generalizability of the findings, report completion rates
Happier People Live More Active Lives: Using Smartphones to Link Happiness and Physical Activity.
Physical activity, both exercise and non-exercise, has far-reaching benefits to physical health. Although exercise has also been linked to psychological health (e.g., happiness), little research has examined physical activity more broadly, taking into account non-exercise activity as well as exercise. We examined the relationship between physical activity (measured broadly) and happiness using a smartphone application. This app has collected self-reports of happiness and physical activity from over ten thousand participants, while passively gathering information about physical activity from the accelerometers on users' phones. The findings reveal that individuals who are more physically active are happier. Further, individuals are happier in the moments when they are more physically active. These results emerged when assessing activity subjectively, via self-report, or objectively, via participants' smartphone accelerometers. Overall, this research suggests that not only exercise but also non-exercise physical activity is related to happiness. This research further demonstrates how smartphones can be used to collect large-scale data to examine psychological, behavioral, and health-related phenomena as they naturally occur in everyday life.Engineering and Physical Sciences Research Council (UBhave project (Ubiquitous and Social Computing for Positive Behaviour Change, Grant ID: EP/I032673/1))This is the final version of the article. It first appeared from Public Library of Science via https://doi.org/http://dx.doi.org/10.1371/journal.pone.016058
M-health review: joining up healthcare in a wireless world
In recent years, there has been a huge increase in the use of information and communication technologies (ICT) to deliver health and social care. This trend is bound to continue as providers (whether public or private) strive to deliver better care to more people under conditions of severe budgetary constraint
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