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Assessing, Evaluating and Changing Health Behaviours Using IT-based Tools (e- & mHeath)

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Health Communication and Informatics".

Deadline for manuscript submissions: closed (30 September 2020) | Viewed by 46573

Special Issue Editor


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Guest Editor
Physical Activity Research Group, Appleton Institute, Central Queensland University, Bruce Highway, Rockhampton, QLD 4700, Australia
Interests: physical activity; ehealth, mhealth; digital health; computer-tailoring; web-based; internet-based; app-based; tracker-based; behavioural interventions; health behaviour change; preventive medicine; health eduction

Special Issue Information

Dear Colleagues,

The focus of this special issue is on using e- & mHealth tools (e.g., websites, apps, chat bots, conversational agents, JITAIs, artificial intelligence, trackers, social media) to measure, examine or change health behaviours (e.g., physical activity, sedentary behaviour, sleep, diet, mental health, weight, smoking). I’m particularly interested in innovative approaches to using e- & mHealth tools to (e.g., applying artificial intelligence) change health behaviours, even if the work is in early stages (i.e., pilot studies), as such, all study designs are welcome. Though note that research replicating previous work will need to be of higher methodological quality than research exploring new frontiers. Please feel free to contact me and ask whether your proposed study is within the scope of the special issue.

Prof. Corneel Vandelanotte
Guest Editor

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Keywords

  • E-health
  • M-health
  • Digital health
  • Internet-based
  • Web-based

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Published Papers (12 papers)

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14 pages, 1723 KiB  
Article
A Process Evaluation Examining the Performance, Adherence, and Acceptability of a Physical Activity and Diet Artificial Intelligence Virtual Health Assistant
by Courtney R. Davis, Karen J. Murphy, Rachel G. Curtis and Carol A. Maher
Int. J. Environ. Res. Public Health 2020, 17(23), 9137; https://doi.org/10.3390/ijerph17239137 - 7 Dec 2020
Cited by 27 | Viewed by 4170
Abstract
Artificial intelligence virtual health assistants are a promising emerging technology. This study is a process evaluation of a 12-week pilot physical activity and diet program delivered by virtual assistant “Paola”. This single-arm repeated measures study (n = 28, aged 45–75 years) was [...] Read more.
Artificial intelligence virtual health assistants are a promising emerging technology. This study is a process evaluation of a 12-week pilot physical activity and diet program delivered by virtual assistant “Paola”. This single-arm repeated measures study (n = 28, aged 45–75 years) was evaluated on technical performance (accuracy of conversational exchanges), engagement (number of weekly check-ins completed), adherence (percentage of step goal and recommended food servings), and user feedback. Paola correctly asked scripted questions and responded to participants during the check-ins 97% and 96% of the time, respectively, but correctly responded to spontaneous exchanges only 21% of the time. Participants completed 63% of weekly check-ins and conducted a total of 3648 exchanges. Mean dietary adherence was 91% and was lowest for discretionary foods, grains, red meat, and vegetables. Participants met their step goal 59% of the time. Participants enjoyed the program and found Paola useful during check-ins but not for spontaneous exchanges. More in-depth knowledge, personalized advice and spontaneity were identified as important improvements. Virtual health assistants should ensure an adequate knowledge base and ability to recognize intents and entities, include personality and spontaneity, and provide ongoing technical troubleshooting of the virtual assistant to ensure the assistant remains effective. Full article
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11 pages, 1105 KiB  
Article
Changing Health Behavior with Social Technology? A Pilot Test of a Mobile App Designed for Social Support of Physical Activity
by Anne Marie Kanstrup, Pernille Scholdan Bertelsen and Casper Knudsen
Int. J. Environ. Res. Public Health 2020, 17(22), 8383; https://doi.org/10.3390/ijerph17228383 - 12 Nov 2020
Cited by 7 | Viewed by 2192
Abstract
Mobile applications targeting people engaged in physical activity have increased. However, while research has identified social support as a key factor for people’s engagement in physical activity, most mobile health (mHealth) applications are designed for individual use. In this paper, we report on [...] Read more.
Mobile applications targeting people engaged in physical activity have increased. However, while research has identified social support as a key factor for people’s engagement in physical activity, most mobile health (mHealth) applications are designed for individual use. In this paper, we report on a research study exploring opportunities for designing mHealth to facilitate social support around physical activity. A mHealth application was designed, and pilot tested for eight weeks with healthcare professionals (n = 3) and two groups of citizens (n = 20) who were motivated but challenged physically due to various health conditions. Data was collected via online monitoring of the use of the mHealth application during the pilot test and via qualitative interviews with the participants before and after. The results support the idea that designing for social health support is important but so is identifying key challenges related to (i) the facilitation of technology-mediated social health support, especially to a target group that is living with health challenges, and (ii) finding a balance between social and health agendas that bring social support to the foreground for the participants. Full article
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20 pages, 1957 KiB  
Article
Development of the Digital Assessment of Precise Physical Activity (DAPPA) Tool for Older Adults
by Rosie Essery, James Denison-Day, Elisabeth Grey, Emma Priestley, Katherine Bradbury, Nanette Mutrie and Max J. Western
Int. J. Environ. Res. Public Health 2020, 17(21), 7949; https://doi.org/10.3390/ijerph17217949 - 29 Oct 2020
Cited by 1 | Viewed by 3301
Abstract
Physical activity (PA) is central to maintaining health and wellbeing as we age. Valid, reliable measurement tools are vital for understanding, and evaluating PA. There are limited options for comprehensively, accurately and affordably measuring older adults’ PA at scale at present. We aimed [...] Read more.
Physical activity (PA) is central to maintaining health and wellbeing as we age. Valid, reliable measurement tools are vital for understanding, and evaluating PA. There are limited options for comprehensively, accurately and affordably measuring older adults’ PA at scale at present. We aimed to develop a digital PA measurement tool specifically for adults aged 65+ using a person-based approach. We collated evidence from target users, field experts and the relevant literature to learn how older adults comprehend PA and would accept a digital tool. Findings suggest that older adults’ PA is often integrated into their daily life activities and that commonly applied terminology (e.g., moderate and vigorous) can be difficult to interpret. We also found that there is increasing familiarity with digital platforms amongst older adults, and that technological simplicity is valued. These findings informed the development of a digital tool that asks users to report their activities across key PA domains and dimensions from the previous 7-days. Users found the tool easy to navigate and comprehensive in terms of activity reporting. However, real-world usability testing revealed that users struggled with seven-day recall. Further work will address the identified issues, including creating a single-day reporting option, before commencing work to validate this new tool. Full article
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21 pages, 2134 KiB  
Article
Optimising Web-Based Computer-Tailored Physical Activity Interventions for Prostate Cancer Survivors: A Randomised Controlled Trial Examining the Impact of Website Architecture on User Engagement
by Amy Finlay, Holly Evans, Andrew Vincent, Gary Wittert, Corneel Vandelanotte and Camille E Short
Int. J. Environ. Res. Public Health 2020, 17(21), 7920; https://doi.org/10.3390/ijerph17217920 - 28 Oct 2020
Cited by 15 | Viewed by 3049
Abstract
Background: Web-based computer-tailored interventions can assist prostate cancer survivors to become more physically active by providing personally relevant behaviour change support. This study aimed to explore how changing the website architecture (free choice vs. tunnelled) impacted engagement within a physical activity computer-tailored intervention [...] Read more.
Background: Web-based computer-tailored interventions can assist prostate cancer survivors to become more physically active by providing personally relevant behaviour change support. This study aimed to explore how changing the website architecture (free choice vs. tunnelled) impacted engagement within a physical activity computer-tailored intervention targeting prostate cancer survivors. Methods: On a 2:2:1 ratio, 71 Australian prostate cancer survivors with local or locally advanced disease (mean age: 66.6 years ± 9.66) were randomised into either a free-choice (N = 27), tunnelled (N = 27) or minimal intervention control arm (N =17). The primary outcome was differences in usage of the physical activity self-monitoring and feedback modules between the two intervention arms. Differences in usage of other website components between the two intervention groups were explored as secondary outcomes. Further, secondary outcomes involving comparisons between all study groups (including the control) included usability, personal relevance, and behaviour change. Results: The average number of physical activity self-monitoring and feedback modules accessed was higher in the tunnelled arm (M 2.6 SD 1.3) compared to the free-choice arm (M 1.5 SD 1.4), p = 0.01. However, free-choice participants were significantly more likely to have engaged with the social support (p = 0.008) and habit formation (p = 0.003) ‘once-off’ modules compared to the standard tunnelled arm. There were no other between-group differences found for any other study outcomes. Conclusion: This study indicated that website architecture influences behavioural engagement. Further research is needed to examine the impact of differential usage on mechanisms of action and behaviour change. Full article
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20 pages, 709 KiB  
Article
Effects of an Activity Tracker and App Intervention to Increase Physical Activity in Whole Families—The Step It Up Family Feasibility Study
by Stephanie Schoeppe, Jo Salmon, Susan L. Williams, Deborah Power, Stephanie Alley, Amanda L. Rebar, Melanie Hayman, Mitch J. Duncan and Corneel Vandelanotte
Int. J. Environ. Res. Public Health 2020, 17(20), 7655; https://doi.org/10.3390/ijerph17207655 - 20 Oct 2020
Cited by 17 | Viewed by 3892
Abstract
(1) Background: Interventions using activity trackers and smartphone apps have demonstrated their ability to increase physical activity in children and adults. However, they have not been tested in whole families. Further, few family-centered interventions have actively involved both parents and assessed physical activity [...] Read more.
(1) Background: Interventions using activity trackers and smartphone apps have demonstrated their ability to increase physical activity in children and adults. However, they have not been tested in whole families. Further, few family-centered interventions have actively involved both parents and assessed physical activity effects separately for children, mothers and fathers. Objective: To examine the feasibility and short-term effects of an activity tracker and app intervention to increase physical activity in the whole family (children, mothers and fathers). (2) Methods: This was a single-arm feasibility study with pre-post intervention measures. Between 2017–2018, 40 families (58 children aged 6–10 years, 39 mothers, 33 fathers) participated in the 6-week Step it Up Family program in Queensland, Australia. Using commercial activity trackers combined with apps (Garmin Vivofit Jr for children, Vivofit 3 for adults; Garmin Australasia Pty Ltd., Sydney, Australia), the intervention included individual and family-level goal-setting, self-monitoring, performance feedback, family step challenges, family social support and modelling, weekly motivational text messages and an introductory session. Parent surveys were used to assess physical activity effects measured as pre-post intervention changes in moderate-to-vigorous physical activity (MVPA) in children, mothers and fathers. Objective Garmin activity tracker data was recorded to assess physical activity levels (steps, active minutes) during the intervention. (3) Results: Thirty-eight families completed the post intervention survey (95% retention). At post intervention, MVPA had increased in children by 58 min/day (boys: 54 min/day, girls: 62 min/day; all p < 0.001). In mothers, MVPA increased by 27 min/day (p < 0.001) and in fathers, it increased by 31 min/day (p < 0.001). The percentage of children meeting Australia’s physical activity guidelines for children (≥60 MVPA min/day) increased from 34% to 89% (p < 0.001). The percentage of mothers and fathers meeting Australia’s physical activity guidelines for adults (≥150 MVPA min/week) increased from 8% to 57% (p < 0.001) in mothers and from 21% to 68% (p < 0.001) in fathers. The percentage of families with ‘at least one child and both parents’ meeting the physical activity guidelines increased from 0% to 41% (p < 0.001). Objective activity tracker data recorded during the intervention showed that the mean (SD) number of active minutes per day in children was 82.1 (17.1). Further, the mean (SD) steps per day was 9590.7 (2425.3) in children, 7397.5 (1954.2) in mothers and 8161.7 (3370.3) in fathers. (4) Conclusions: Acknowledging the uncontrolled study design, the large pre-post changes in MVPA and rather high step counts recorded during the intervention suggest that an activity tracker and app intervention can increase physical activity in whole families. The Step it Up Family program warrants further efficacy testing in a larger, randomized controlled trial. Full article
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21 pages, 1543 KiB  
Article
The Feasibility and Preliminary Efficacy of an eHealth Lifestyle Program in Women with Recent Gestational Diabetes Mellitus: A Pilot Study
by Megan E. Rollo, Jennifer N. Baldwin, Melinda Hutchesson, Elroy J. Aguiar, Katie Wynne, Ashley Young, Robin Callister, Rebecca Haslam and Clare E. Collins
Int. J. Environ. Res. Public Health 2020, 17(19), 7115; https://doi.org/10.3390/ijerph17197115 - 28 Sep 2020
Cited by 21 | Viewed by 4241
Abstract
Self-administered eHealth interventions provide a potential low-cost solution for reducing diabetes risk. The aim of this pilot randomised controlled trial (RCT) was to evaluate the feasibility, including recruitment, retention, preliminary efficacy (primary outcome) and acceptability (secondary outcome) of the “Body Balance Beyond” eHealth [...] Read more.
Self-administered eHealth interventions provide a potential low-cost solution for reducing diabetes risk. The aim of this pilot randomised controlled trial (RCT) was to evaluate the feasibility, including recruitment, retention, preliminary efficacy (primary outcome) and acceptability (secondary outcome) of the “Body Balance Beyond” eHealth intervention in women with previous gestational diabetes mellitus (GDM). Women with overweight/obesity who had recent GDM (previous 24 months) were randomised into one of three groups: 1) high personalisation (access to “Body Balance Beyond” website, individual telehealth coaching via video call by a dietitian and exercise physiologist, and text message support); 2) low personalisation (website only); or 3) waitlist control. To evaluate preliminary efficacy, weight (kg), glycosylated hemoglobin, type A1C (HbA1c), cholesterol (total, low-density lipoprotein (LDL) and high-density lipoprotein (HDL)), diet quality and moderate–vigorous physical activity were analysed at baseline and at 3 and 6 months using generalised linear mixed models. To investigate acceptability, process evaluation was conducted at 3 and 6 months. Of the 327 potential participants screened, 42 women (mean age 33.5 ± 4.0 years and BMI 32.4 ± 4.3 kg/m2) were randomised, with 30 (71%) completing the study. Retention at 6 months was 80%, 54% and 79% for high personalisation, low personalisation and waitlist control, respectively (reasons: personal/work commitments, n = 4; started weight-loss diet, n = 1; pregnant, n = 1; resources not useful, n = 1; and not contactable, n = 5). No significant group-by-time interactions were observed for preliminary efficacy outcomes, with the exception of HDL cholesterol, where a difference favoured the low personalisation group relative to the control (p = 0.028). The majority (91%) of women accessed the website in the first 3 months and 57% from 4–6 months. The website provided useful information for 95% and 92% of women at 3 and 6 months, respectively, although only a third of women found it motivating (30% and 25% at 3 and 6 months, respectively). Most women agreed that the telehealth coaching increased their confidence for improving diet (85%) and physical activity (92%) behaviours, although fewer women regarded the text messages as positive (22% and 31% for improving diet and physical activity, respectively). The majority of women (82% at 3 months and 87% at 6 months) in the high personalisation group would recommend the program to other women with GDM. Recruiting and retaining women with a recent diagnosis of GDM is challenging. The “Body Balance Beyond” website combined with telehealth coaching via video call is largely acceptable and useful for women with recent GDM. Further analysis of the effect on diabetes risk reduction in a larger study is needed. Full article
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21 pages, 1524 KiB  
Article
Efficacy of a Multi-component m-Health Weight-loss Intervention in Overweight and Obese Adults: A Randomised Controlled Trial
by Mitch J. Duncan, Sasha Fenton, Wendy J. Brown, Clare E. Collins, Nicholas Glozier, Gregory S. Kolt, Elizabeth G. Holliday, Philip J. Morgan, Beatrice Murawski, Ronald C. Plotnikoff, Anna T. Rayward, Emmanuel Stamatakis, Corneel Vandelanotte and Tracy L. Burrows
Int. J. Environ. Res. Public Health 2020, 17(17), 6200; https://doi.org/10.3390/ijerph17176200 - 26 Aug 2020
Cited by 39 | Viewed by 7033
Abstract
Background: This study compared the efficacy of two multi-component m-health interventions with a wait-list control group on body weight (primary outcome), and secondary outcomes of cardiovascular risk factors, lifestyle behaviours, and mental health. Methods: Three-arm randomised controlled trial (Enhanced: physical activity, diet, sleep, [...] Read more.
Background: This study compared the efficacy of two multi-component m-health interventions with a wait-list control group on body weight (primary outcome), and secondary outcomes of cardiovascular risk factors, lifestyle behaviours, and mental health. Methods: Three-arm randomised controlled trial (Enhanced: physical activity, diet, sleep, Traditional: physical activity, diet, Control) with assessments conducted at baseline, 6 and 12 months. Participants (n = 116) were overweight or obese adults aged 19–65 (M = 44.5 [SD = 10.5]). The 6-month intervention was delivered via a smartphone app providing educational materials, goal-setting, self-monitoring and feedback, and also included one face-to-face dietary consultation, a Fitbit and scales. The trial was prospectively registered and conducted between May 2017 and September 2018. Group differences on primary and secondary outcomes were examined between the Pooled Intervention groups (Pooled Intervention = Enhanced and Traditional) and Control groups, and then between Enhanced and Traditional groups. Results: Nineteen participants (16.4%) formally withdrew from the trial. Compared with the Control group, average body weight of the Pooled Intervention group did not differ at 6 (between-group difference = −0.92, (95% CI −3.33, 1.48)) or 12 months (0.00, (95% CI −2.62, 2.62)). Compared with the Control group, the Pooled Intervention group significantly increased resistance training (OR = 7.83, (95% CI 1.08, 56.63)) and reduced energy intake at 6 months (−1037.03, (−2028.84, −45.22)), and improved insomnia symptoms at 12 months (−2.59, (−4.79, −0.39)). Compared with the Traditional group, the Enhanced group had increased waist circumferences (2.69, (0.20, 5.18)) and sedentary time at 6 months (105.66, (30.83, 180.48)), and improved bed time variability at 12 months (−1.08, (−1.86, −0.29)). No other significant differences were observed between groups. Conclusions: Relative to Controls, the Pooled Intervention groups did not differ on body weight but improved resistance training, and reduced energy intake and insomnia symptom severity. No additional weight loss was apparent when targeting improvements in physical activity, diet and sleep in combination compared with physical activity and diet. Full article
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18 pages, 538 KiB  
Article
Be Healthe for Your Heart: A Pilot Randomized Controlled Trial Evaluating a Web-Based Behavioral Intervention to Improve the Cardiovascular Health of Women with a History of Preeclampsia
by Melinda J. Hutchesson, Rachael Taylor, Vanessa A. Shrewsbury, Lisa Vincze, Linda E. Campbell, Robin Callister, Felicity Park, Tracy L. Schumacher and Clare E. Collins
Int. J. Environ. Res. Public Health 2020, 17(16), 5779; https://doi.org/10.3390/ijerph17165779 - 10 Aug 2020
Cited by 15 | Viewed by 3109
Abstract
This pilot randomized controlled trial (RCT) aimed to determine the acceptability and preliminary efficacy of a web-based cardiovascular disease (CVD) prevention intervention for women following preeclampsia. Australian women with a recent history (≤4 years post diagnosis) of preeclampsia were randomized into two study [...] Read more.
This pilot randomized controlled trial (RCT) aimed to determine the acceptability and preliminary efficacy of a web-based cardiovascular disease (CVD) prevention intervention for women following preeclampsia. Australian women with a recent history (≤4 years post diagnosis) of preeclampsia were randomized into two study arms: (1) Be Healthe for your Heart, a web-based behavioral intervention or; (2) Control, access to the National Heart Foundation website. Assessments were conducted at baseline, and after three months. Intervention acceptability and impact on absolute CVD 30-year risk score, CVD risk markers and health behaviors were assessed. Twenty-four of 31 (77.4%) women completed the three-month assessment. Eleven out of 13 intervention participants (84.6%) agreed/strongly agreed they were satisfied with the program, with a mean score of 4.2 ± 0.9 (maximum of five). There were no significant between or within group differences in absolute CVD risk, CVD risk markers or health behaviors from baseline to three months. Women with a history of preeclampsia were successfully recruited and retained and they reported high levels of acceptability with the Be Healthe for your Heart program. Further research is therefore needed from powered trials to determine the impact of web-based lifestyle interventions on CVD risk in this at-risk group. Full article
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15 pages, 1320 KiB  
Article
Development of a Personalized m/eHealth Algorithm for the Resumption of Activities of Daily Life Including Work and Sport after Total and Unicompartmental Knee Arthroplasty: A Multidisciplinary Delphi Study
by A. Carlien Straat, Pieter Coenen, Denise J. M. Smit, Gerben Hulsegge, Esther V. A. Bouwsma, Judith A. F. Huirne, Rutger C. van Geenen, Rob P. A. Janssen, Tim A. E. J. Boymans, Gino M. M. J. Kerkhoffs, Johannes R. Anema and P. Paul F. M. Kuijer
Int. J. Environ. Res. Public Health 2020, 17(14), 4952; https://doi.org/10.3390/ijerph17144952 - 9 Jul 2020
Cited by 14 | Viewed by 3209
Abstract
Evidence for recommendations concerning the resumption of activities of daily life, including work and sport, after knee arthroplasty is lacking. Therefore, recommendations vary considerably between hospitals and healthcare professionals. We aimed to obtain multidisciplinary consensus for such recommendations. Using a Delphi procedure, we [...] Read more.
Evidence for recommendations concerning the resumption of activities of daily life, including work and sport, after knee arthroplasty is lacking. Therefore, recommendations vary considerably between hospitals and healthcare professionals. We aimed to obtain multidisciplinary consensus for such recommendations. Using a Delphi procedure, we strived to reach consensus among a multidisciplinary expert panel of six orthopaedic surgeons, three physical therapists, five occupational physicians and one physician assistant on recommendations regarding the resumption of 27 activities of daily life. The Delphi procedure involved three online questionnaire rounds and one face-to-face consensus meeting. In each of these four rounds, experts independently decided at what time daily life activities could feasibly and safely be resumed after knee arthroplasty. We distinguished patients with a fast, average and slow recovery. After four Delphi rounds, the expert panel reached consensus for all 27 activities. For example, experts agreed that total knee arthroplasty patients with a fast recovery could resume cycling six weeks after the surgery, while those with an average and slow recovery could resume this activity after nine and twelve weeks, respectively. The consensus recommendations will subsequently be integrated into an algorithm of a personalized m/eHealth portal to enhance recovery among knee arthroplasty patients. Full article
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20 pages, 1889 KiB  
Article
Detecting Binge Drinking and Alcohol-Related Risky Behaviours from Twitter’s Users: An Exploratory Content- and Topology-Based Analysis
by Cristina Crocamo, Marco Viviani, Francesco Bartoli, Giuseppe Carrà and Gabriella Pasi
Int. J. Environ. Res. Public Health 2020, 17(5), 1510; https://doi.org/10.3390/ijerph17051510 - 26 Feb 2020
Cited by 12 | Viewed by 3718
Abstract
Binge Drinking (BD) is a common risky behaviour that people hardly report to healthcare professionals, although it is not uncommon to find, instead, personal communications related to alcohol-related behaviors on social media. By following a data-driven approach focusing on User-Generated Content, we aimed [...] Read more.
Binge Drinking (BD) is a common risky behaviour that people hardly report to healthcare professionals, although it is not uncommon to find, instead, personal communications related to alcohol-related behaviors on social media. By following a data-driven approach focusing on User-Generated Content, we aimed to detect potential binge drinkers through the investigation of their language and shared topics. First, we gathered Twitter threads quoting BD and alcohol-related behaviours, by considering unequivocal keywords, identified by experts, from previous evidence on BD. Subsequently, a random sample of the gathered tweets was manually labelled, and two supervised learning classifiers were trained on both linguistic and metadata features, to classify tweets of genuine unique users with respect to media, bot, and commercial accounts. Based on this classification, we observed that approximately 55% of the 1 million alcohol-related collected tweets was automatically identified as belonging to non-genuine users. A third classifier was then trained on a subset of manually labelled tweets among those previously identified as belonging to genuine accounts, to automatically identify potential binge drinkers based only on linguistic features. On average, users classified as binge drinkers were quite similar to the standard genuine Twitter users in our sample. Nonetheless, the analysis of social media contents of genuine users reporting risky behaviours remains a promising source for informed preventive programs. Full article
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17 pages, 1556 KiB  
Article
Impact of a Social Media Campaign on Reach, Uptake, and Engagement with a Free Web- and App-Based Physical Activity Intervention: The 10,000 Steps Australia Program
by Anna T. Rayward, Corneel Vandelanotte, Kelly Corry, Anetta Van Itallie and Mitch J. Duncan
Int. J. Environ. Res. Public Health 2019, 16(24), 5076; https://doi.org/10.3390/ijerph16245076 - 12 Dec 2019
Cited by 16 | Viewed by 4558
Abstract
Social media campaigns provide broad-reach and convenience for promoting freely-available health programs. However, their effectiveness and subsequent engagement of new users is unknown. This study aimed to assess the reach and new member registration rates resulting from a dedicated 10,000 Steps social media [...] Read more.
Social media campaigns provide broad-reach and convenience for promoting freely-available health programs. However, their effectiveness and subsequent engagement of new users is unknown. This study aimed to assess the reach and new member registration rates resulting from a dedicated 10,000 Steps social media campaign (SMC) and to compare program engagement and time to non-usage attrition of new users from the SMC with other users. SMC reach (using Facebook, Instagram, and display advertisements engagement metrics), new-user numbers, engagement (usage of the website and its features), and time to non-usage attrition were assessed using generalized linear regression, binary logistic regression, and Cox proportion hazards regression models. During the SMC, Instagram and display advertisement impressions, Facebook reach and new daily registrations were significantly higher compared with six weeks and one year prior. There were no between-group differences in the average usage of most website/program features. Risk of non-usage attrition was higher among new users from the SMC than new users from one year prior. The SMC was effective in promoting awareness of the 10,000 Steps program. Further research to identify long-term engagement strategies and the most effective combination of social media platforms for promotion of, and recruitment to, health programs is warranted. Full article
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14 pages, 1033 KiB  
Study Protocol
Protocol of the STRess at Work (STRAW) Project: How to Disentangle Day-to-Day Occupational Stress among Academics Based on EMA, Physiological Data, and Smartphone Sensor and Usage Data
by Larissa Bolliger, Junoš Lukan, Mitja Luštrek, Dirk De Bacquer and Els Clays
Int. J. Environ. Res. Public Health 2020, 17(23), 8835; https://doi.org/10.3390/ijerph17238835 - 27 Nov 2020
Cited by 15 | Viewed by 3188
Abstract
Several studies have reported on increasing psychosocial stress in academia due to work environment risk factors like job insecurity, work-family conflict, research grant applications, and high workload. The STRAW project adds novel aspects to occupational stress research among academic staff by measuring day-to-day [...] Read more.
Several studies have reported on increasing psychosocial stress in academia due to work environment risk factors like job insecurity, work-family conflict, research grant applications, and high workload. The STRAW project adds novel aspects to occupational stress research among academic staff by measuring day-to-day stress in their real-world work environments over 15 working days. Work environment risk factors, stress outcomes, health-related behaviors, and work activities were measured repeatedly via an ecological momentary assessment (EMA), specially developed for this project. These results were combined with continuously tracked physiological stress responses using wearable devices and smartphone sensor and usage data. These data provide information on workplace context using our self-developed Android smartphone app. The data were analyzed using two approaches: 1) multilevel statistical modelling for repeated data to analyze relations between work environment risk factors and stress outcomes on a within- and between-person level, based on EMA results and a baseline screening, and 2) machine-learning focusing on building prediction models to develop and evaluate acute stress detection models, based on physiological data and smartphone sensor and usage data. Linking these data collection and analysis approaches enabled us to disentangle and model sources, outcomes, and contexts of occupational stress in academia. Full article
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