My Activity Coach - using video-coaching to assist a web-based computer-tailored physical activity intervention: a randomised controlled trial protocol

A systematic review on eHealth technology personalization approaches

Despite the widespread use of personalization of eHealth technologies, there is a lack of comprehensive understanding regarding its application. This systematic review aims to bridge this gap by identifying and clustering different personalization approaches based on the type of variables used for user segmentation and the adaptations to the eHealth technology and examining the role of computational methods in the literature. From the 412 included reports, we identified 13 clusters of personalization approaches, such as behavior + channeling and environment + recommendations. Within these clusters, 10 computational methods were utilized to match segments with technology adaptations, such as classification-based methods and reinforcement learning. Several gaps were identified in the literature, such as the limited exploration of technology-related variables, the limited focus on user interaction reminders, and a frequent reliance on a single type of variable for personalization. Future research should explore leveraging technology-specific features to attain individualistic segmentation approaches.

Telehealth Technologies in Diabetes Self-management and Education

BACKGROUND

The coronavirus pandemic of 2019 (COVID-19) forced worldwide recognition and implementation of telehealth as a means of providing continuity of care by varied health care institutions. Diabetes is a global health threat with rates that continue to accelerate, thereby causing an increased need for clinicians to provide diabetes care and education to keep up with demand. Utilizing technology to provide education via phone/smartphone, video/audio, web, text message, mobile apps, or a combination of these methods can help improve patient access and clinical outcomes, cut costs, and close gaps in care.

METHODS

While numerous publications have summarized the various tools and technologies available for capturing remote clinical data and their relevance to diabetes care and self-management, this review focuses on self-educational telehealth tools available for diabetes self-management, their advantages and disadvantages, and factors that need to be considered prior to implementation. Recent relevant studies indexed by PubMed were included.

RESULTS

The widespread use and popularity of phones/smartphones, tablets, computers, and the Internet by patients of all age groups, cultures, socioeconomic and geographic areas allow for increased outreach, flexibility, and engagement with diabetes education, either in combination or as an adjunct to traditional in-person visits. Demonstrated benefits of using health technologies for diabetes self-management education include improved lifestyle habits, reduced hemoglobin A1C levels, decreased health care costs, and better medication adherence. Potential drawbacks include lack of regulation, need for staff training on methodologies used, the requirement for patients to be tech savvy, privacy concerns, lag time with technology updates/glitches, and the need for more long-term research data on efficacy.

CONCLUSIONS

Telehealth technologies for diabetes self-education improve overall clinical outcomes and have come a long way. With increasing numbers of patients with diabetes, it is expected that more optimal and user-friendly methodologies will be developed to fully engage and help patients communicate with their physicians.

Designing and evaluation of E-health educational intervention on students' physical activity: an application of Pender's health promotion model

BACKGROUND

The present study was conducted to design and evaluate the software and web-based curriculum based on Pender Model in order to promote students' physical activity.

METHODS

This is a quasi-experimental study conducted on 225 eligible students who were randomly divided into two groups of web and software-based intervention and control. The sample size of the study was selected using stratified sampling method. The evaluation was done with pre-test and post-test and follow-up, which were performed immediately two and six months following the intervention. The data were analyzed employing statistical software SPSS using descriptive statistics, chi-square, one way ANOVA, and repeated measures ANOVA.

RESULTS

The obtained results revealed that the level of physical activity after the intervention in the web and software groups significantly increased compared to the control group (p < 0.001). Moreover, the mean score of Pender model constructs, immediately two and six months after the intervention, was significantly different in the web and software groups (p < 0.001).

CONCLUSION

Our results indicated that, providing tailored message based on health promotion model's constructs has a positive effect on promoting physical activity of students.

TRIAL REGISTRATION

Name: Iranian Registry of Clinical Trials. Registration number: IRCT20181009041298N1 . Registration date: 2018-12-02 [retrospectively registered].

How do mobile health applications support behaviour changes? A scoping review of mobile health applications relating to physical activity and eating behaviours

OBJECTIVE

The objective of this review was to analyse how researchers conducting studies about mobile health applications (MHApps) effectiveness assess the conditions of this effectiveness.

STUDY DESIGN

A scoping review according to PRIMSA-ScR checklist.

METHODS

We conducted a scoping review of efficacy/effectiveness conditions in high internal validity studies assessing the efficacy of MHApps in changing physical activity behaviours and eating habits. We used the PubMed, Web of Science, SPORTDiscus and PsycINFO databases and processed the review according to the O'Malley and PRISMA-ScR recommendations. We selected studies with high internal validity methodologies (randomised controlled trials, quasi-experimental studies, systematic reviews and meta-analyses), dealing with dietary and/or physical activity behaviours; covering primary, secondary or tertiary prevention and dealing with behaviour change (uptake, maintenance). We excluded articles on MHApps relating to high-level sport and telemedicine. The process for selecting studies followed a set protocol with two authors who independently appraised the studies.

RESULTS

Twenty-two articles were finally selected and analysed. We noted that the mechanisms and techniques to support behaviour changes were poorly reported and studied. There was no explanation of how these MHApps work and how they could be transferred or not. Indeed, the main efficacy conditions reported by authors refer to practical aspects of the tools. Moreover, the issue of social inequalities was essentially reduced to access to the technology (the shrinking access divide), and literacy was poorly studied, even though it is an important consideration in digital prevention. All in all, even when they dealt with behaviours, the evaluations were tool-focused rather than intervention-focused and did not allow a comprehensive assessment of MHApps.

CONCLUSION

To understand the added value of MHApps in supporting behaviour changes, it seems important to draw on the paradigms relating to health technology assessment considering the characteristics of the technologies and on the evaluation of complex interventions considering the characteristics of prevention. This combined approach may help to clarify how these patient-focused MHApps work and is a condition for improved assessment of MHApps in terms of effectiveness, transferability and scalability.

Validity and responsiveness to change of the Active Australia Survey according to gender, age, BMI, education, and physical activity level and awareness

BACKGROUND

This study aimed to investigate the validity of the Active Australia Survey across different subgroups and its responsiveness to change, as few previous studies have examined this.

METHODS

The Active Australia Survey was validated against the ActiGraph as an objective measure of physical activity. Participants (n = 465) wore the ActiGraph for 7 days and subsequently completed the Active Australia Survey. Moderate activity, vigorous activity and total moderate and vigorous physical activity were compared using Spearman rank-order correlations. Changes in physical activity between baseline and 3-month assessments were correlated to examine responsiveness to change. The data were stratified to assess outcomes according to different subgroups (e.g., gender, age, weight, activity levels).

RESULTS

With regards to the validity, a significant correlation of ρ = 0.19 was found for moderate physical activity, ρ = 0.33 for vigorous physical activity and ρ = 0.23 for moderate and vigorous physical activity combined. For vigorous physical activity correlations were higher than 0.3 for most subgroups, whereas they were only higher than 0.3 in those with a healthy weight for the other activity outcomes. With regards to responsiveness to change, a correlation of ρ = 0.32 was found for moderate physical activity, ρ = 0.19 for vigorous physical activity and ρ = 0.35 for moderate and vigorous physical activity combined. For moderate and vigorous activity combined correlations were higher than 0.4 for several subgroups, but never for vigorous physical activity.

CONCLUSIONS

Little evidence for the validity of Active Australia Survey was found, although the responsiveness to change was acceptable for several subgroups. Findings from studies using the Active Australia Survey should be interpreted with caution.

TRIAL REGISTRATION

World Health Organisation Universal Trial Number: U111-1119-1755. Australian New Zealand Clinical Trials Registry, ACTRN12611000157976 . Registration date: 8 March 2011.

Ontological Review of Persuasion Support Systems (PSS) for Health Behavior Change through Physical Activity

Persuasion Support Systems (PSS) for health behavior change can play an important role in promoting health and well-being through physical activity. It is an emerging application at the crossroad between information systems, persuasion, and healthcare. We propose an ontology to systematically and systemically describe the construct of PSS for health behavior change. The ontology deconstructs the construct into its constituent dimensions and elements, and assembles them into a complete, parsimonious description of the same. We then map the corpus of literature on PSS for health behavior change through physical activity onto the ontology. The resulting ontological map highlights the research topics that are highly- and lightly-emphasized, as well as those with little or no emphasis. It illuminates the landscape of research in the corpus; it highlights biases in emphases that can help and hinder the advancement of the corpus. It can be used to develop a roadmap for future research.

User Models for Personalized Physical Activity Interventions: Scoping Review

Background

Fitness devices have spurred the development of apps that aim to motivate users, through interventions, to increase their physical activity (PA). Personalization in the interventions is essential as the target users are diverse with respect to their activity levels, requirements, preferences, and behavior.

Objective

This review aimed to (1) identify different kinds of personalization in interventions for promoting PA among any type of user group, (2) identify user models used for providing personalization, and (3) identify gaps in the current literature and suggest future research directions.

Methods

A scoping review was undertaken by searching the databases PsycINFO, PubMed, Scopus, and Web of Science. The main inclusion criteria were (1) studies that aimed to promote PA; (2) studies that had personalization, with the intention of promoting PA through technology-based interventions; and (3) studies that described user models for personalization.

Results

The literature search resulted in 49 eligible studies. Of these, 67% (33/49) studies focused solely on increasing PA, whereas the remaining studies had other objectives, such as maintaining healthy lifestyle (8 studies), weight loss management (6 studies), and rehabilitation (2 studies). The reviewed studies provide personalization in 6 categories: goal recommendation, activity recommendation, fitness partner recommendation, educational content, motivational content, and intervention timing. With respect to the mode of generation, interventions were found to be semiautomated or automatic. Of these, the automatic interventions were either knowledge-based or data-driven or both. User models in the studies were constructed with parameters from 5 categories: PA profile, demographics, medical data, behavior change technique (BCT) parameters, and contextual information. Only 27 of the eligible studies evaluated the interventions for improvement in PA, and 16 of these concluded that the interventions to increase PA are more effective when they are personalized.

Conclusions

This review investigates personalization in the form of recommendations or feedback for increasing PA. On the basis of the review and gaps identified, research directions for improving the efficacy of personalized interventions are proposed. First, data-driven prediction techniques can facilitate effective personalization. Second, use of BCTs in automated interventions, and in combination with PA guidelines, are yet to be explored, and preliminary studies in this direction are promising. Third, systems with automated interventions also need to be suitably adapted to serve specific needs of patients with clinical conditions. Fourth, previous user models focus on single metric evaluations of PA instead of a potentially more effective, holistic, and multidimensional view. Fifth, with the widespread adoption of activity monitoring devices and mobile phones, personalized and dynamic user models can be created using available user data, including users’ social profile. Finally, the long-term effects of such interventions as well as the technology medium used for the interventions need to be evaluated rigorously.

Persuasive system features in computer-mediated lifestyle modification interventions for physical activity

Objective: Increasing physical activity has been identified as one of the most important factors in lifestyle modification. Previous studies have reported the effectiveness of using the Internet in motivating behavioral modifications of physical activities. The aim of this study is to identify the persuasive system features most frequently used in computer-mediated physical activities in the current literature.Materials and Methods: In this review, intervention studies were identified through a structured computerized search of PubMed, PsychInfo, and Web of Science. The results of the search were analyzed using the persuasive systems design (PSD) features identified by Oinas-Kukkonen and Harjumaa (2009).Results: Thirty-eight articles were reviewed, and the features of the physical activity interventions described were mapped to the identified facets of PSD. The PSD features used most often by researchers in the studies considered in this research included tailoring, tunneling, reminders, trustworthiness, and expertise. The effectiveness of the interventions described in the studies was also compared. The stage of change theory was applied in several intervention studies, and the importance of stage of change has been identified in effectiveness of persuasion toward physical activity.

Web-Based Video-Coaching to Assist an Automated Computer-Tailored Physical Activity Intervention for Inactive Adults: A Randomized Controlled Trial

BACKGROUND

Web-based physical activity interventions that apply computer tailoring have shown to improve engagement and behavioral outcomes but provide limited accountability and social support for participants. It is unknown how video calls with a behavioral expert in a Web-based intervention will be received and whether they improve the effectiveness of computer-tailored advice.

OBJECTIVE

The purpose of this study was to determine the feasibility and effectiveness of brief video-based coaching in addition to fully automated computer-tailored advice in a Web-based physical activity intervention for inactive adults.

METHODS

Participants were assigned to one of the three groups: (1) tailoring + video-coaching where participants received an 8-week computer-tailored Web-based physical activity intervention ("My Activity Coach") including 4 10-minute coaching sessions with a behavioral expert using a Web-based video-calling program (eg, Skype; n=52); (2) tailoring-only where participants received the same intervention without the coaching sessions (n=54); and (3) a waitlist control group (n=45). Demographics were measured at baseline, intervention satisfaction at week 9, and physical activity at baseline, week 9, and 6 months by Web-based self-report surveys. Feasibility was analyzed by comparing intervention groups on retention, adherence, engagement, and satisfaction using t tests and chi-square tests. Effectiveness was assessed using linear mixed models to compare physical activity changes between groups.

RESULTS

A total of 23 tailoring + video-coaching participants, 30 tailoring-only participants, and 30 control participants completed the postintervention survey (83/151, 55.0% retention). A low percentage of tailoring + video-coaching completers participated in the coaching calls (11/23, 48%). However, the majority of those who participated in the video calls were satisfied with them (5/8, 71%) and had improved intervention adherence (9/11, 82% completed 3 or 4 modules vs 18/42, 43%, P=.01) and engagement (110 minutes spent on the website vs 78 minutes, P=.02) compared with other participants. There were no overall retention, adherence, engagement, and satisfaction differences between tailoring + video-coaching and tailoring-only participants. At 9 weeks, physical activity increased from baseline to postintervention in all groups (tailoring + video-coaching: +150 minutes/week; tailoring only: +123 minutes/week; waitlist control: +34 minutes/week). The increase was significantly higher in the tailoring + video-coaching group compared with the control group (P=.01). No significant difference was found between intervention groups and no significant between-group differences were found for physical activity change at 6 months.

CONCLUSIONS

Only small improvements were observed when video-coaching was added to computer-tailored advice in a Web-based physical activity intervention. However, combined Web-based video-coaching and computer-tailored advice was effective in comparison with a control group. More research is needed to determine whether Web-based coaching is more effective than stand-alone computer-tailored advice.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ACTRN): 12614000339651; http://www.anzctr.org.au/TrialSearch.aspx?searchTxt=ACTRN12614000339651+&isBasic=True (Archived by WebCite at http://www.webcitation.org/6jTnOv0Ld).

Engagement and attrition in Internet smoking cessation interventions: Insights from a cross-sectional survey of "one-hit-wonders"

INTRODUCTION

Internet interventions can reach large numbers of individuals. However, low levels of engagement and high rates of follow-up attrition are common, presenting major challenges to evaluation. This study investigated why registrants of an Internet smoking cessation intervention did not return after joining ("one hit wonders"), and explored the impact of graduated incentives on survey response rates and responder characteristics.

METHODS

A sample of "one hit wonders" that registered on a free smoking cessation website between 2014 and 2015 were surveyed. The initial invitation contained no incentive. Subsequent invitations were sent to random subsamples of non-responders from each previous wave offering $25 and $50 respectively. Descriptive statistics characterized respondents on demographic characteristics, reasons for not returning, and length of time since last visit. Differences were investigated with Fisher's Exact tests, Kruskal-Wallis, and logistic regression.

RESULTS

Of 8779 users who received the initial invitation, 132 completed the survey (1.5%). Among those subsequently offered a $25 incentive, 127 (3.7%) responded. Among those offered a $50 incentive, 97 responded (5.7%). The most common reasons endorsed for not returning were being unable to quit (51%), not having enough time (33%), having forgotten about the website (28%), and not being ready to quit (21%). Notably, however, 23% reported not returning because they had successfully quit smoking. Paid incentives yielded a higher proportion of individuals who were still smoking than the $0 incentive (72% vs. 61%). Among $0 and $25 responders, likelihood of survey response decreased with time since registration; the $50 incentive removed the negative effect of time-since-registration on probability of response.

CONCLUSIONS

One third of participants that had disengaged from an Internet intervention reported abstinence at follow-up, suggesting that low levels of engagement are not synonymous with treatment failure in all cases. Paid incentives above $25 may be needed to elicit survey responses, especially among those with longer intervals of disengagement from an intervention.

An Evaluation of Web- and Print-Based Methods to Attract People to a Physical Activity Intervention

Background

Cost-effective and efficient methods to attract people to Web-based health behavior interventions need to be identified. Traditional print methods including leaflets, posters, and newspaper advertisements remain popular despite the expanding range of Web-based advertising options that have the potential to reach larger numbers at lower cost.

Objective

This study evaluated the effectiveness of multiple Web-based and print-based methods to attract people to a Web-based physical activity intervention.

Methods

A range of print-based (newspaper advertisements, newspaper articles, letterboxing, leaflets, and posters) and Web-based (Facebook advertisements, Google AdWords, and community calendars) methods were applied to attract participants to a Web-based physical activity intervention in Australia. The time investment, cost, number of first time website visits, the number of completed sign-up questionnaires, and the demographics of participants were recorded for each advertising method.

Results

A total of 278 people signed up to participate in the physical activity program. Of the print-based methods, newspaper advertisements totaled AUD $145, letterboxing AUD $135, leaflets AUD $66, posters AUD $52, and newspaper article AUD $3 per sign-up. Of the Web-based methods, Google AdWords totaled AUD $495, non-targeted Facebook advertisements AUD $68, targeted Facebook advertisements AUD $42, and community calendars AUD $12 per sign-up. Although the newspaper article and community calendars cost the least per sign-up, they resulted in only 17 and 6 sign-ups respectively. The targeted Facebook advertisements were the next most cost-effective method and reached a large number of sign-ups (n=184). The newspaper article and the targeted Facebook advertisements required the lowest time investment per sign-up (5 and 7 minutes respectively). People reached through the targeted Facebook advertisements were on average older (60 years vs 50 years, P<.001) and had a higher body mass index (32 vs 30, P<.05) than people reached through the other methods.

Conclusions

Overall, our results demonstrate that targeted Facebook advertising is the most cost-effective and efficient method at attracting moderate numbers to physical activity interventions in comparison to the other methods tested. Newspaper advertisements, letterboxing, and Google AdWords were not effective. The community calendars and newspaper articles may be effective for small community interventions.

ClinicalTrial

Australian New Zealand Clinical Trials Registry: ACTRN12614000339651; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=363570&isReview=true (Archived by WebCite at http://www.webcitation.org/6hMnFTvBt)

Pancreatic cancer survivors' preferences, barriers, and facilitators related to physical activity and diet interventions

PURPOSE

To conduct a telephone survey establishing pancreatic cancer survivors' level of interest in, preferences for, and perceived barriers and facilitators to participating in exercise and diet intervention programming. These data will inform the development of such interventions for newly-diagnosed patients.

METHODS

Seventy-one survivors treated for resectable pancreatic adenocarcinoma from October 2011 to August 2014 were identified through an institutional cancer registry and contacted via telephone. A telephone survey was conducted to query survivors' level of interest in, preferences for, and perceived barriers and facilitators to participating in an exercise and dietary intervention program shortly after disease diagnosis. Acceptability of a technology-based visual communication (e.g., Skype™, FaceTime®) intervention was also assessed.

RESULTS

Fifty participants completed the survey (response rate 71.8 %). Over two-thirds of participants reported interest in exercise and diet intervention programming. Over half reported comfort with a technology-delivered visual communication intervention. Barriers to participation included older age and physical, personal, and emotional problems. The most common facilitator was program awareness. Outcomes for future research important to participants were supportive care and quality of life.

CONCLUSIONS

Most pancreatic cancer patients are interested in exercise and diet interventions shortly after diagnosis; however, some barriers to program participation exist.

IMPLICATIONS FOR CANCER SURVIVORS

Future research and intervention planning for pancreatic cancer survivors should focus on developing messaging and strategies that provide support for survivorship outcomes, increase survivor awareness, address lack of familiarity with technology, reduce fears about potential barriers, and help survivors overcome these barriers. In so doing, survivorship needs can be better met and quality of life improved in this understudied population.

Online Patient Education for Chronic Disease Management: Consumer Perspectives

Patient education plays an important role in chronic disease management. The aim of this study is to identify patients' preferences in regard to the design features of effective online patient education (OPE) and the benefits. A review of the existing literature was conducted in order to identify the benefits of OPE and its essential design features. These design features were empirically tested by conducting survey with patients and caregivers. Reliability analysis, construct validity and regression analysis were performed for data analysis. The results identified patient-tailored information, interactivity, content credibility, clear presentation of content, use of multimedia and interpretability as the essential design features of online patient education websites for chronic disease management.