Louise Poppe

A self-regulation-based eHealth intervention to promote a healthy lifestyle : investigating user and website characteristics related to attrition

Background eHealth interventions can reach large populations and are effective in increasing physical activity (PA) and fruit and vegetable intake. Nevertheless, the effects of eHealth interventions are overshadowed by high attrition rates. Examining more closely when users decide to leave the intervention can help eHealth developers to make informed decisions about which intervention components should be reshaped or simply removed. Investigating which users are more likely to quit an intervention can inform developers about whether and how their intervention should be adapted to specific subgroups of users. Objective This study investigated the pattern of attrition in a Web-based intervention to increase PA, fruit, and vegetable intake. The first aim was to describe attrition rates according to different self-regulation components. A second aim was to investigate whether certain user characteristics are predictors for start session completion, returning to a follow-up session and intervention completion. Methods The sample consisted of 549 adults who participated in an online intervention, based on self-regulation theory, to promote PA and fruit and vegetable intake, called “MyPlan 1.0.” Using descriptive analysis, attrition was explored per self-regulation component (eg, action planning and coping planning). To identify which user characteristics predict completion, logistic regression analyses were conducted. Results At the end of the intervention program, there was an attrition rate of 78.2% (330/422). Attrition rates were very similar for the different self-regulation components. However, attrition levels were higher for the fulfillment of questionnaires (eg, to generate tailored feedback) than for the more interactive components. The highest amount of attrition could be observed when people were asked to make their own action plan. There were no significant predictors for first session completion. Yet, two subgroups had a lower chance to complete the intervention, namely male users (OR: 2.24, 95% CI=1.23-4.08) and younger adults (OR: 1.02, 95% CI=1.00-1.04). Furthermore, younger adults were less likely to return to the website for the first follow-up after one week (OR: 1.03, 95% CI=1.01-1.04). Conclusions This study informs us that eHealth interventions should avoid the use of extensive questionnaires and that users should be provided with a rationale for several components (eg, making an action plan and completing questions). Furthermore, future interventions should focus first on motivating users for the behavior change before guiding them through action planning. Though, this study provides no evidence for removal of one of the self-regulation techniques based on attrition rates. Finally, strong efforts are needed to motivate male users and younger adults to complete eHealth interventions.

Different effects of executive and visuospatial working memory on visual consciousness

Consciousness and working memory are two widely studied cognitive phenomena. Although they have been closely tied on a theoretical and neural level, empirical work that investigates their relation is largely lacking. In this study, the relationship between visual consciousness and different working memory components is investigated by using a dual-task paradigm. More specifically, while participants were performing a visual detection task to measure their visual awareness threshold, they had to concurrently perform either an executive or visuospatial working memory task. We hypothesized that visual consciousness would be hindered depending on the type and the size of the load in working memory. Results showed that maintaining visuospatial content in working memory hinders visual awareness, irrespective of the amount of information maintained. By contrast, the detection threshold was progressively affected under increasing executive load. Interestingly, increasing executive load had a generic effect on detection speed, calling into question whether its obstructing effect is specific to the visual awareness threshold. Together, these results indicate that visual consciousness depends differently on executive and visuospatial working memory.

Physical Activity, Sedentary Behavior, and Diet-Related eHealth and mHealth Research: Bibliometric Analysis

Background Electronic health (eHealth) and mobile health (mHealth) approaches to address low physical activity levels, sedentary behavior, and unhealthy diets have received significant research attention. However, attempts to systematically map the entirety of the research field are lacking. This gap can be filled with a bibliometric study, where publication-specific data such as citations, journals, authors, and keywords are used to provide a systematic overview of a specific field. Such analyses will help researchers better position their work. Objective The objective of this review was to use bibliometric data to provide an overview of the eHealth and mHealth research field related to physical activity, sedentary behavior, and diet. Methods The Web of Science (WoS) Core Collection was searched to retrieve all existing and highly cited (as defined by WoS) physical activity, sedentary behavior, and diet related eHealth and mHealth research papers published in English between January 1, 2000 and December 31, 2016. Retrieved titles were screened for eligibility, using the abstract and full-text where needed. We described publication trends over time, which included journals, authors, and countries of eligible papers, as well as their keywords and subject categories. Citations of eligible papers were compared with those expected based on published data. Additionally, we described highly-cited papers of the field (ie, top ranked 1%). Results The search identified 4805 hits, of which 1712 (including 42 highly-cited papers) were included in the analyses. Publication output increased on an average of 26% per year since 2000, with 49.00% (839/1712) of papers being published between 2014 and 2016. Overall and throughout the years, eHealth and mHealth papers related to physical activity, sedentary behavior, and diet received more citations than expected compared with papers in the same WoS subject categories. The Journal of Medical Internet Research published most papers in the field (9.58%, 164/1712). Most papers originated from high-income countries (96.90%, 1659/1717), in particular the United States (48.83%, 836/1712). Most papers were trials and studied physical activity. Beginning in 2013, research on Generation 2 technologies (eg, smartphones, wearables) sharply increased, while research on Generation 1 (eg, text messages) technologies increased at a reduced pace. Reviews accounted for 20 of the 42 highly-cited papers (n=19 systematic reviews). Social media, smartphone apps, and wearable activity trackers used to encourage physical activity, less sedentary behavior, and/or healthy eating were the focus of 14 highly-cited papers. Conclusions This study highlighted the rapid growth of the eHealth and mHealth physical activity, sedentary behavior, and diet research field, emphasized the sizeable contribution of research from high-income countries, and pointed to the increased research interest in Generation 2 technologies. It is expected that the field will grow and diversify further and that reviews and research on most recent technologies will continue to strongly impact the field.

The Effect of the eHealth Intervention ‘MyPlan 1.0’ on Physical Activity in Adults Who Visit General Practice: A Quasi-Experimental Trial

Physical inactivity is one of the major risk factors for poor health in the world. Therefore, effective interventions that promote physical activity are needed. Hence, we developed an eHealth intervention for adults, i.e., ‘MyPlan 1.0’, which includes self-regulation techniques for behaviour change. This study examined the effect of ‘MyPlan 1.0’ on physical activity (PA) levels in general practice. 615 adults (≥18 years) were recruited in 19 Flemish general practices, for the intervention group (n = 328) or for the wait-list control group (n = 183). Participants in the intervention group received the web-based intervention ‘MyPlan 1.0’ and were prompted to discuss their personal advice/action plan with their general practitioner. Participants in the wait-list control group only received general advice from the website. Self-reported physical activity was assessed with the International Physical Activity Questionnaire (IPAQ) at baseline and after one month. A three-level (general practice, adults, time) regression analysis was conducted in MLwiN. Significant intervention effects were found for total PA and moderate to vigorous PA with an increase for the intervention group compared to a decrease in the control condition. However, there was a high dropout rate in the intervention group (76%) and the wait-list control group (57%). Our self-regulation intervention was effective in increasing physical activity levels in adults. Future studies should consider strategies to prevent the large dropout from participants.

Do patients with chronic unilateral orofacial pain due to a temporomandibular disorder show increased attending to somatosensory input at the painful side of the jaw

Background Patients with chronic orofacial pain due to temporomandibular disorders (TMD) display alterations in somatosensory processing at the jaw, such as amplified perception of tactile stimuli, but the underlying mechanisms remain unclear. This study investigated one possible explanation, namely hypervigilance, and tested if TMD patients with unilateral pain showed increased attending to somatosensory input at the painful side of the jaw. Methods TMD patients with chronic unilateral orofacial pain (n = 20) and matched healthy volunteers (n = 20) performed a temporal order judgment (TOJ) task indicated which one of two tactile stimuli, presented on each side of the jaw, they had perceived first. TOJ methodology allows examining spatial bias in somatosensory processing speed. Furthermore, after each block of trials, the participants rated the perceived intensity of tactile stimuli separately for both sides of the jaw. Finally, questionnaires assessing pain catastrophizing, fear-avoidance beliefs, and pain vigilance, were completed. Results TMD patients tended to perceive tactile stimuli at the painful jaw side as occurring earlier in time than stimuli at the non-painful side but this effect did not reach conventional levels of significance (p = .07). In the control group, tactile stimuli were perceived as occurring simultaneously. Secondary analyses indicated that the magnitude of spatial bias in the TMD group is positively associated with the extent of fear-avoidance beliefs. Overall, intensity ratings of tactile stimuli were significantly higher in the TMD group than in the control group, but there was no significant difference between the painful and non-painful jaw side in the TMD patients. Discussion The hypothesis that TMD patients with chronic unilateral orofacial pain preferentially attend to somatosensory information at the painful side of the jaw was not statistically supported, although lack of power could not be ruled out as a reason for this. The findings are discussed within recent theories of pain-related attention.

Experiences and Opinions of Adults with Type 2 Diabetes Regarding a Self-Regulation-Based eHealth Intervention Targeting Physical Activity and Sedentary Behaviour

Background: Online interventions targeting a healthy lifestyle in adults with type 2 diabetes are more effective when informed by behaviour change theories. Although these theories provide guidance in developing the content of an intervention, information regarding how to present this content in an engaging way is often lacking. Consequently, incorporating users’ views in the creation of eHealth interventions has become an important target. Methods: Via a qualitative interview study with 21 adults with type 2 diabetes who had completed an online self-regulation-based intervention (‘MyPlan 2.0’), we assessed participants’ opinions regarding the usefulness of the implemented self-regulation techniques, the design of the programme as well as their knowledge regarding physical activity and sedentary behaviour. A directed content analysis was performed to synthesize the interview data. Results: Participants experienced difficulties completing the coping planning component. The simple design of the website was considered helpful, and most participants were aware of the beneficial effects of an active lifestyle. Conclusions: ‘MyPlan 2.0’ was well-accepted by the majority of participants. However, the coping planning component will need to be adapted. Based on these findings, recommendations on how to tailor eHealth interventions to the population of adults with type 2 diabetes have been formulated.

Physical activity to improve cognition in older adults: can physical activity programs enriched with cognitive challenges enhance the effects? A systematic review and meta-analysis

BackgroundAging-related cognitive decline and cognitive impairment greatly impacts older adults’ daily life. The worldwide ageing of the population and associated wave of dementia urgently calls for prevention strategies to reduce the risk of cognitive decline. Physical activity (PA) is known to improve cognitive function at older age through processes of neuroplasticity. Yet, emerging studies suggest that larger cognitive gains may be induced when PA interventions are combined with cognitive activity (CA). This meta-analysis evaluates these potential synergistic effects by comparing cognitive effects following combined PAu2009+u2009CA interventions to PA interventions (PA only), CA interventions (CA only) and control groups.MethodsPubmed, Embase, PsycInfo, CINAHL and Sportdiscus were searched for English peer-reviewed papers until April 2018. Data were extracted on cognition and factors potentially influencing the cognitive effects: mode of PAu2009+u2009CA combination (sequential or simultaneous), session frequency and duration, intervention length and study quality. Differences between older adults with and without mild cognitive impairments were also explored.ResultsForty-one studies were included. Relative to the control group, combined PAu2009+u2009CA intervention showed significantly larger gains in cognition (gu2009=u20090.316; 95% CI 0.188–0.443; pu2009<u2009.001). Studies that compared combined PAu2009+u2009CA with PA only, showed small but significantly greater cognitive improvement in favor of combined interventions (gu2009=u20090.160; 95% CI 0.041–0.279; pu2009=u2009.008). No significant difference was found between combined PAu2009+u2009CA and CA only interventions. Furthermore, cognitive effects tended to be more pronounced for studies using simultaneous designs (gu2009=u20090.385; 95%CI 0.214–0.555; pu2009<u2009.001) versus sequential designs (gu2009=u20090.114; 95%CI -0.102- 0.331, pu2009=u2009.301). Effects were not moderated by session frequency, session duration, intervention length or study quality. Also, no differences in effects were found between older adults with and without mild cognitive impairments.ConclusionFindings of the current meta-analysis suggest that PA programs for older adults could integrate challenging cognitive exercises to improve cognitive health. Combined PAu2009+u2009CA programs should be promoted as a modality for preventing as well as treating cognitive decline in older adults. Sufficient cognitive challenge seems more important to obtain cognitive effects than high doses of intervention sessions.

Users’ thoughts and opinions about a self-regulation-based eHealth intervention targeting physical activity and the intake of fruit and vegetables : a qualitative study

Purpose EHealth interventions are effective in changing health behaviours, such as increasing physical activity and altering dietary habits, but suffer from high attrition rates. In order to create interventions that are adapted to end-users, in-depth investigations about their opinions and preferences are required. As opinions and preferences may vary for different target groups, we explored these in two groups: the general population and a clinical sample. Methods Twenty adults from the general population (mean age = 42.65, 11 women) and twenty adults with type 2 diabetes (mean age = 64.30, 12 women) performed ‘MyPlan 1.0’, which is a self-regulation-based eHealth intervention designed to increase physical activity and the intake of fruit and vegetables in the general population. The opinions and preferences of end-users were explored using a think aloud procedure and a questionnaire. During a home visit, participants were invited to think aloud while performing ‘MyPlan 1.0’. The thoughts were transcribed verbatim and inductive thematic analysis was applied. Results Both groups had similar opinions regarding health behaviours and ‘MyPlan 1.0’. Participants generally liked the website, but often experienced it as time-consuming. Furthermore, they regularly mentioned that a mobile application would be useful to remind them about their goals on a daily basis. Finally, users’ ideas about how to pursue health behaviours often hindered them to correctly use the website. Conclusions Although originally created for the general population, ‘MyPlan 1.0’ can also be used in adults with type 2 diabetes. Nevertheless, more adaptations are needed to make the eHealth intervention more convenient and less time-consuming. Furthermore, users’ ideas regarding a healthy lifestyle should be taken into account when designing online interventions.

How Users Experience and Use an eHealth Intervention Based on Self-Regulation: Mixed-Methods Study

Background eHealth interventions show stronger effects when informed by solid behavioral change theories; for example, self-regulation models supporting people in translating vague intentions to specific actions have shown to be effective in altering health behaviors. Although these theories inform developers about which behavioral change techniques should be included, they provide limited information about how these techniques can be engagingly implemented in Web-based interventions. Considering the high levels of attrition in eHealth, investigating users’ experience about the implementation of behavior change techniques might be a fruitful avenue. Objective The objective of our study was to investigate how users experience the implementation of self-regulation techniques in a Web-based intervention targeting physical activity and sedentary behavior in the general population. Methods In this study, 20 adults from the general population used the intervention for 5 weeks. Users’ website data were explored, and semistructured interviews with each of the users were performed. A directed content analysis was performed using NVivo Software. Results The techniques “providing feedback on performance,” “action planning,” and “prompting review of behavioral goals” were appreciated by users. However, the implementation of “barrier identification/problem solving” appeared to frustrate users; this was also reflected by the users’ website data—many coping plans were of poor quality. Most users were well aware of the benefits of adopting a more active way of living and stated not to have learned novel information. However, they appreciated the provided information because it reminded them about the importance of having an active lifestyle. Furthermore, prompting users to self-monitor their behavioral change was not sufficiently stimulating to make users actually monitor their behavior. Conclusions Iteratively involving potential end users offers guidance to optimally adapt the implementation of various behavior change techniques to the target population. We recommend creating short interventions with a straightforward layout that support users in creating and evaluating specific plans for action.

The validity of smart devices to measure physical activity in daily life (Preprint)

Background Wearables for monitoring physical activity (PA) are increasingly popular. These devices are not only used by consumers to monitor their own levels of PA but also by researchers to track the behavior of large samples. Consequently, it is important to explore how accurately PA can be tracked via these devices. Objectives The aim of this study was, therefore, to investigate convergent validity of 3 Android Wear smartwatches—Polar M600 (Polar Electro Oy, Kempele, Finland), Huawei Watch (Huawei Technologies Co, Ltd, Shenzhen, Guangdong, China), Asus Zenwatch3 (AsusTek Computer Inc, Taipei, Taiwan)—and Fitbit Charge with an ActiGraph accelerometer for measuring steps and moderate to vigorous physical activity (MVPA) on both a day level and 15-min level. Methods A free-living protocol was used in which 36 adults engaged in usual daily activities over 2 days while wearing 2 different wearables on the nondominant wrist and an ActiGraph GT3X+ accelerometer on the hip. Validity was evaluated on both levels by comparing each wearable with the ActiGraph GT3X+ accelerometer using correlations and Bland-Altman plots in IBM SPSS 24.0. Results On a day level, all devices showed strong correlations (Spearman r=.757-.892) and good agreement (interclass correlation coefficient, ICC=.695-.885) for measuring steps, whereas moderate correlations (Spearman r=.557-.577) and low agreement (ICC=.377-.660) for measuring MVPA. Bland-Altman revealed a systematic overestimation of the wearables for measuring steps but a variation between over- and undercounting of MVPA. On a 15-min level, all devices showed strong correlations (Spearman r=.752-.917) and good agreement (ICC=.792-.887) for measuring steps, whereas weak correlations (Spearman r=.116-.208) and low agreement (ICC=.461-.577) for measuring MVPA. Bland-Altman revealed a systematic overestimation of the wearables for steps but under- or overestimation for MVPA depending on the device. Conclusions In sum, all 4 consumer-level devices can be considered accurate step counters in free-living conditions. This study, however, provides evidence of systematic bias for all devices in measurement of MVPA. The results on a 15-min level also indicate that these devices are not sufficiently accurate to provide correct real-time feedback.