Abstract Because physical inactivity and unhealthy diets are highly prevalent, there is a need for cost-effective interventions that can reach large populations. Electronic health (eHealth) and ...mobile health (mHealth) solutions have shown promising outcomes and have expanded rapidly in the past decade. The purpose of this report is to provide an overview of the state of the evidence for the use of eHealth and mHealth in improving physical activity and nutrition behaviors in general and special populations. The role of theory in eHealth and mHealth interventions is addressed, as are methodological issues. Key recommendations for future research in the field of eHealth and mHealth are provided.
The dramatic growth of Web 2.0 technologies and online social networks offers immense potential for the delivery of health behavior change campaigns. However, it is currently unclear how online ...social networks may best be harnessed to achieve health behavior change.
The intent of the study was to systematically review the current level of evidence regarding the effectiveness of online social network health behavior interventions.
Eight databases (Scopus, CINAHL, Medline, ProQuest, EMBASE, PsycINFO, Cochrane, Web of Science and Communication & Mass Media Complete) were searched from 2000 to present using a comprehensive search strategy. Study eligibility criteria were based on the PICOS format, where "population" included child or adult populations, including healthy and disease populations; "intervention" involved behavior change interventions targeting key modifiable health behaviors (tobacco and alcohol consumption, dietary intake, physical activity, and sedentary behavior) delivered either wholly or in part using online social networks; "comparator" was either a control group or within subject in the case of pre-post study designs; "outcomes" included health behavior change and closely related variables (such as theorized mediators of health behavior change, eg, self-efficacy); and "study design" included experimental studies reported in full-length peer-reviewed sources. Reports of intervention effectiveness were summarized and effect sizes (Cohen's d and 95% confidence intervals) were calculated wherever possible. Attrition (percentage of people who completed the study), engagement (actual usage), and fidelity (actual usage/intended usage) with the social networking component of the interventions were scrutinized.
A total of 2040 studies were identified from the database searches following removal of duplicates, of which 10 met inclusion criteria. The studies involved a total of 113,988 participants (ranging from n=10 to n=107,907). Interventions included commercial online health social network websites (n=2), research health social network websites (n=3), and multi-component interventions delivered in part via pre-existing popular online social network websites (Facebook n=4 and Twitter n=1). Nine of the 10 included studies reported significant improvements in some aspect of health behavior change or outcomes related to behavior change. Effect sizes for behavior change ranged widely from -0.05 (95% CI 0.45-0.35) to 0.84 (95% CI 0.49-1.19), but in general were small in magnitude and statistically non-significant. Participant attrition ranged from 0-84%. Engagement and fidelity were relatively low, with most studies achieving 5-15% fidelity (with one exception, which achieved 105% fidelity).
To date there is very modest evidence that interventions incorporating online social networks may be effective; however, this field of research is in its infancy. Further research is needed to determine how to maximize retention and engagement, whether behavior change can be sustained in the longer term, and to determine how to exploit online social networks to achieve mass dissemination. Specific recommendations for future research are provided.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
To assess the effects of early and late bedtimes and wake up times on use of time and weight status in Australian school-aged children.
Observational cross-sectional study involving use of time ...interviews and pedometers.
Free-living Australian adolescents.
2200 9- to 16-year-olds from all states of Australia
NA.
Bedtimes and wake times were adjusted for age and sex and classified as early or late using median splits. Adolescents were allocated into 4 sleep-wake pattern groups: Early-bed/Early-rise; Early-bed/Late-rise; Late-bed/Early-rise; Late-bed/Late-rise. The groups were compared for use of time (screen time, physical activity, and study-related time), sociodemographic characteristics, and weight status. Adolescents in the Late-bed/Late-rise category experienced 48 min/d more screen time and 27 min less moderate-to-vigorous physical activity (MVPA) (P<0.0001) than adolescents in the Early-bed/Early-rise category, in spite of similar sleep durations. Late-bed/Late-rise adolescents had a higher BMI z-score (0.66 vs. 0.45, P=0.0015). Late-bed/Late-rise adolescents were 1.47 times more likely to be overweight or obese than Early-bed/Early-rise adolescents, 2.16 times more likely to be obese, 1.77 times more likely to have low MVPA, and 2.92 times more likely to have high screen time. Late-bed/Late-rise adolescents were more likely to come from poorer households, to live in major cities, and have fewer siblings.
Late bedtimes and late wake up times are associated with an unfavorable activity and weight status profile, independent of age, sex, household income, geographical remoteness, and sleep duration.
The COVID-19 pandemic has dramatically impacted lifestyle behaviour as public health initiatives aim to "flatten the curve". This study examined changes in activity patterns (physical activity, ...sedentary time, sleep), recreational physical activities, diet, weight and wellbeing from before to during COVID-19 restrictions in Adelaide, Australia. This study used data from a prospective cohort of Australian adults (parents of primary school-aged children; n = 61, 66% female, aged 41±6 years). Participants wore a Fitbit Charge 3 activity monitor and weighed themselves daily using Wi-Fi scales. Activity and weight data were extracted for 14 days before (February 2020) and 14 days during (April 2020) COVID-19 restrictions. Participants reported their recreational physical activity, diet and wellbeing during these periods. Linear mixed effects models were used to examine change over time. Participants slept 27 minutes longer (95% CI 9-51), got up 38 minutes later (95% CI 25-50), and did 50 fewer minutes (95% CI -69--29) of light physical activity during COVID-19 restrictions. Additionally, participants engaged in more cycling but less swimming, team sports and boating or sailing. Participants consumed a lower percentage of energy from protein (-0.8, 95% CI -1.5--0.1) and a greater percentage of energy from alcohol (0.9, 95% CI 0.2-1.7). There were no changes in weight or wellbeing. Overall, the effects of COVID-19 restrictions on lifestyle were small; however, their impact on health and wellbeing may accumulate over time. Further research examining the effects of ongoing social distancing restrictions are needed as the pandemic continues.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Virtual assistants can be used to deliver innovative health programs that provide appealing, personalized, and convenient health advice and support at scale and low cost. Design characteristics that ...influence the look and feel of the virtual assistant, such as visual appearance or language features, may significantly influence users' experience and engagement with the assistant.
This scoping review aims to provide an overview of the experimental research examining how design characteristics of virtual health assistants affect user experience, summarize research findings of experimental research examining how design characteristics of virtual health assistants affect user experience, and provide recommendations for the design of virtual health assistants if sufficient evidence exists.
We searched 5 electronic databases (Web of Science, MEDLINE, Embase, PsycINFO, and ACM Digital Library) to identify the studies that used an experimental design to compare the effects of design characteristics between 2 or more versions of an interactive virtual health assistant on user experience among adults. Data were synthesized descriptively. Health domains, design characteristics, and outcomes were categorized, and descriptive statistics were used to summarize the body of research. Results for each study were categorized as positive, negative, or no effect, and a matrix of the design characteristics and outcome categories was constructed to summarize the findings.
The database searches identified 6879 articles after the removal of duplicates. We included 48 articles representing 45 unique studies in the review. The most common health domains were mental health and physical activity. Studies most commonly examined design characteristics in the categories of visual design or conversational style and relational behavior and assessed outcomes in the categories of personality, satisfaction, relationship, or use intention. Over half of the design characteristics were examined by only 1 study. Results suggest that empathy and relational behavior and self-disclosure are related to more positive user experience. Results also suggest that if a human-like avatar is used, realistic rendering and medical attire may potentially be related to more positive user experience; however, more research is needed to confirm this.
There is a growing body of scientific evidence examining the impact of virtual health assistants' design characteristics on user experience. Taken together, data suggest that the look and feel of a virtual health assistant does affect user experience. Virtual health assistants that show empathy, display nonverbal relational behaviors, and disclose personal information about themselves achieve better user experience. At present, the evidence base is broad, and the studies are typically small in scale and highly heterogeneous. Further research, particularly using longitudinal research designs with repeated user interactions, is needed to inform the optimal design of virtual health assistants.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Abstract
Background
Time spent in daily activities (sleep, sedentary behaviour and physical activity) has important consequences for health and wellbeing. The amount of time spent varies from day to ...day, yet little is known about the temporal nature of daily activity patterns in adults. The aim of this review is to identify the annual rhythms of daily activity behaviours in healthy adults and explore what temporal factors appear to influence these rhythms.
Methods
Six online databases were searched for cohort studies exploring within-year temporal patterns (e.g. season effects, vacation, cultural festivals) in sleep, sedentary behaviour or physical activity in healthy 18 to 65-year-old adults. Screening, data extraction, and risk of bias scoring were performed in duplicate. Extracted data was presented as mean daily minutes of each activity type, with transformations performed as needed. Where possible, meta-analyses were performed using random effect models to calculate standardised mean differences (SMD).
Results
Of the 7009 articles identified, 17 studies were included. Studies were published between 2003 and 2019, representing 14 countries and 1951 participants, addressing variation in daily activities across season (
n
= 11), Ramadan (
n
= 4), vacation (
n
= 1) and daylight savings time transitions (
n
= 1). Meta-analyses suggested evidence of seasonal variation in activity patterns, with sleep highest in autumn (+ 12 min); sedentary behaviour highest in winter (+ 19 min); light physical activity highest in summer (+ 19 min); and moderate-to-vigorous physical activity highest in summer (+ 2 min) when compared to the yearly mean. These trends were significant for light physical activity in winter (SMD = − 0.03, 95% CI − 0.58 to − 0.01,
P
= 0.04). Sleep appeared 64 min less during, compared to outside Ramadan (non-significant). Narrative analyses for the impact of vacation and daylight savings suggested that light physical activity is higher during vacation and that sleep increases after the spring daylight savings transition, and decreases after the autumn transition.
Conclusions
Research into temporal patterns in activity behaviours is scarce. Existing evidence suggests that seasonal changes and periodic changes to usual routine, such as observing religious events, may influence activity behaviours across the year. Further research measuring 24-h time use and exploring a wider variety of temporal factors is needed.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Fitspiration is a social media phenomenon purported to inspire viewers to lead healthier lifestyles but can result in negative psychological outcomes such as body dissatisfaction. This study aimed to ...develop a tool to audit Instagram fitspiration accounts and screen for content that could have potentially negative psychological effects.
This study developed and implemented an audit tool to (1) identify credible fitspiration accounts (i.e., accounts that do not portray potentially harmful or unhealthy content) and (2) describe the content of identified accounts. The most recent 15 posts of 100 leading Instagram fitspiration accounts were audited. Accounts were deemed non-credible and were excluded if they contained fewer than four fitness-related posts or portrayed nudity or inappropriate clothing, sexualisation or objectification, extreme body types, "thinspiration", or negative messages.
Many accounts contained fewer than four fitness-related posts (n = 41), sexualisation or objectification (n = 26), nudity or inappropriate clothing (n = 22), and/or extreme body types (n = 15). Three accounts failed on all four criteria, while 13, 10 and 33 failed on three, two, or one criterion, respectively. Therefore, only 41% of accounts were considered credible. Inter-rater reliability (percentage agreement and Brennan and Prediger's coefficient κ
) was high (Stage 1: 92% agreement 95% CI 87, 97, κ
0.84 95% CI 0.73, 0.95; Stage 2: 93% agreement 95% CI 83, 100, κ
0.85 95% CI 0.67, 1.00). Account holders of credible fitspiration accounts were predominantly female (59%), aged 25-34 (54%), Caucasian (62%), and from the United States (79%). Half held a qualification related to physical activity or physical health (e.g., personal trainer, physiotherapy; 54%). Most included accounts included an exercise video (93%) and example workout (76%).
While many popular Instagram fitspiration accounts offered credible content such as example workouts, many accounts contained sexualisation, objectification or promotion of unhealthy or unrealistic body shapes. The audit tool could be used by Instagram users to ensure the accounts they follow do not portray potentially harmful or unhealthy content. Future research could use the audit tool to identify credible fitspiration accounts and examine whether exposure to these accounts positively influences physical activity.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The health effects of daily activity behaviours (physical activity, sedentary time and sleep) are widely studied. While previous research has largely examined activity behaviours in isolation, recent ...studies have adjusted for multiple behaviours. However, the inclusion of all activity behaviours in traditional multivariate analyses has not been possible due to the perfect multicollinearity of 24-h time budget data. The ensuing lack of adjustment for known effects on the outcome undermines the validity of study findings. We describe a statistical approach that enables the inclusion of all daily activity behaviours, based on the principles of compositional data analysis. Using data from the International Study of Childhood Obesity, Lifestyle and the Environment, we demonstrate the application of compositional multiple linear regression to estimate adiposity from children’s daily activity behaviours expressed as isometric log-ratio coordinates. We present a novel method for predicting change in a continuous outcome based on relative changes within a composition, and for calculating associated confidence intervals to allow for statistical inference. The compositional data analysis presented overcomes the lack of adjustment that has plagued traditional statistical methods in the field, and provides robust and reliable insights into the health effects of daily activity behaviours.
How people use their time has been linked with their health. For example, spending more time being physically active is known to be beneficial for health, whereas long durations of sitting have been ...associated with unfavourable health outcomes. Accordingly, public health messages have advocated swapping strategies to promote the reallocation of time between parts of the time-use composition, such as “Move More, Sit Less”, with the aim of achieving optimal distribution of time for health. However, the majority of research underpinning these public health messages has not considered daily time use as a composition, and has ignored the relative nature of time-use data. We present a way of applying compositional data analysis to estimate change in a health outcome when fixed durations of time are reallocated from one part of a particular time-use composition to another, while the remaining parts are kept constant, based on a multiple linear regression model on isometric log ratio coordinates. In an example, we examine the expected differences in Body Mass Index z-scores for reallocations of time between sleep, physical activity and sedentary behaviour.
Objective
To examine the combined influence of moderate‐to‐vigorous physical activity (MVPA) and sedentary behavior on obesity in US adults.
Design and Methods
Cross‐sectional analyses were ...undertaken on a nationally representative sample of 5,083 adults from the April 2003 and June 2005 National Health and Nutrition Examination Survey. Self‐reported TV time was divided into low, moderate, and high categories. Accelerometer‐derived total sedentary and MVPA minutes divided into low, moderate, and high tertiles. The independent associations between MVPA, TV, and total sedentary time and obesity were examined using logistic regression. Participants were then cross tabulated into nine MVPA–sedentary behavior groups, and logistic regression was used to examine the combined influence of MVPA and sedentary behavior on the odds of being obese.
Results
MVPA was consistently inversely associated with obesity, regardless of sedentary behavior odds ratio (OR) = 1.80‐4.00. There were inconsistent positive associations between TV time and risk of obesity in men, but not between total sedentary time and risk of obesity in either men or women.
Conclusions
Obesity was more strongly related to MVPA than either TV time or total sedentary time in US adults. Small differences in daily MVPA (5‐10 min) were associated with relatively large differences in risk of obesity.
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