Purpose: Gestational diabetes is a common pregnancy complication with acute peripartum risks as well as heightened chronic disease risk that includes a ten-fold risk for developing type 2 diabetes compared with normoglycaemic pregnancies.  Mobile health technology (mHealth) provides a practical solution to supporting women during both pregnancy and postpartum with lifestyle modification. However, the optimal design for this population is unknown. We aimed to systematically review the perspectives of women with GDM or a recent history of GDM on mHealth pregnancy and postpartum lifestyle interventions to inform future intervention development.

Methods: Five electronic databases (PubMed, MEDLINE, EMBASE, CINAHL, PsycINFO and Cochrane Central Register of Controlled Trials) were searched up to April 2020. Study quality was evaluated using Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research and a reflexive thematic synthesis performed. The COM-B model was used to frame findings for use in future mHealth intervention development.  

Results: 14 studies met the inclusion criteria representing the views of 327 women. Three pregnancy themes were identified: support, connectedness, and trust. Pregnant women valued mHealth interventions that sat alongside usual care and provided healthcare professional support, trusted information and self-monitoring. The health of their baby was a major motivator. Two postpartum themes were identified: support and connectedness. Postpartum women valued peer connections and use of rewards to remain motivated. They identified more limitations with mHealth interventions than pregnant women. Seven recommendations for future intervention design were made, mostly with high or moderate confidence. 

Conclusions: Women’s views on mHealth lifestyle interventions differ between pregnancy and the postpartum period. The use of participatory design is key in the development of mHealth interventions and this review summarises the needs of the users. The results also reflect the impact a GDM diagnosis has on a woman highlighting the need for ongoing support continuing postpartum. Future research should aim to improve the quality of qualitative research reporting to increase confidence in findings.

Purpose: Many theoretical frameworks have been developed to understand health behaviors such as physical activity. The determinants within these frameworks are usually considered relatively stable over time. However, in reality individual-level determinants vary over time, and also vary within and between individuals. In order to make health behavior change interventions more personalized, information on the time-dependent variations of determinants is urgently needed. To do so, the COM-B framework can be used as a dynamic framework, including reflective (conscious) as well as automatic (unconscious) processes that may vary over time (i.e. within and between days). The aim of this study was to examine the time-dependent variability of emotions, physical complaints, intention and self-efficacy towards physical activity using Ecological Momentary Assessment (EMA).

Methods: Observational data were collected in 67 Belgian older adults , using time-based EMA. EMA is a methodology to repeatedly collect real-time data on subjects’ behavior and/or experiences in their natural environments. Participants answered questions regarding emotions, physical complaints, intention and self-efficacy towards physical activity six times a day using a smartphone-based questionnaire (The Smartphone Ecological Momentary Assessment ³ (SEMA³) application). Additionally, participants filled in an intake questionnaire assessing socio-demographics. Generalized linear mixed models were estimated using R version 4.0.1.

Results/findings: Emotions vary within individuals within days (approximately 49% of the total variance), except for enthusiasm which rather varies between individuals (54.4%). Physical complaints vary between individuals (approximately 60%), and less within individuals within days. However, tiredness and dizziness also vary within individuals within days (51.8% and 46.6%). Intention and self-efficacy both vary more within days within individuals (64.5% and 51.1%) than between individuals. More detailed findings will be presented at ISBNPA XChange 2021.

Conclusions: This study shows that emotions, dizziness, tiredness, intention and self-efficacy are strongly time-dependent, and should be treated as ‘dynamic’ or unstable behavior determinants. This study provides us with important insights concerning the development of more personalized health behavior change interventions, anticipating real-time dynamics of determinants instead of considering determinants as stable within individuals.

Purpose: Social networking sites (SNS) and online communities provide a huge potential for supporting behavior change. However, SNS-based interventions largely vary in their effectiveness and engagement rates. We examine whether a brief Self-Determination-Theory-based communication intervention via an educational video can positively affect behavior change, perceived need-support, and engagement in an SNS-based physical activity and eating behavior intervention.

Methods: We tested the effects of a Self-Determination-Theory-based intervention video (vs. a control video on netiquette rules) on need-supportive communication strategy use to fictive Facebook postings (Experiment 1, N = 76) and perceived need-support, engagement, and behavior change in a forum-based behavior change intervention (Experiment 2, N = 190). In Experiment 2, in addition to a goal-setting intervention, participants joined a peer-based online support forum for two weeks in order to improve their eating or physical activity behavior. Data from both experiments were analyzed with (generalized) mixed models and follow-up tests.

Results/Findings: Experiment 1: Participants from the intervention but not from the control group showed an increase in the number of need-supportive communication strategies (condition*time interaction, partial η² = .31). Between-group differences were consistent and large for competence- and relatedness-supportive strategies (all ds > 0.94) but small and less consistent for autonomy-supportive strategies. Experiment 2: Participants watching the intervention video had a higher engagement (number of logins, number of postings, and subjective forum visit frequency) than participants watching the control video. There were no other effects on our primary and secondary outcomes. The missing effects could be due to low strategy uptake and restricted applicability of the communication strategies to all postings.

Conclusions: A brief Self-Determination-Theory-based video intervention may be suitable to promote need-supportive communication strategy use and could serve as a low-cost intervention to improve need-supportive communication. However, its applicability and effectiveness in ecologically valid contexts need further evaluation. Future studies should incorporate additional strategies for improving communication strategy uptake and engagement in SNS and online communities.

Purpose: Digital apps potentially provide an easily accessible way to reinforce implementation and scaling up lifestyle counselling to promote a healthy diet and prevent type 2 diabetes (T2D). Eating competence (EC) has been associated with good diet quality and successful weight management, which, in turn, are major protective factors against T2D. However, it is still unclear how EC including positive attitude towards eating, regular meals, internally regulated eating and accepting and eating different foods is affected by the use of digital apps. Therefore, we studied the association between the use of a digital lifestyle intervention app and changes in EC in a subgroup of participants of the Finnish StopDiabetes trial.

Methods: Altogether 1938 Finnish adults (mean age 55 years, 80% women) at increased risk for T2D were randomized to receive either a ‘digital’ or ‘digital + face-to-face group counselling’ intervention. The intervention continued for 12 months and was conducted in primary healthcare. Participants got access to the BitHabit app, which included nearly 500 simple behavioral suggestions intended to support habit formation for a healthier lifestyle, including eating behaviors and attitudes. The participants were able to browse, select, and track habits from 13 different lifestyle categories. EC was measured by the Satter Eating Competence Inventory 2.0TM at baseline and at the end of the one-year of intervention. Statistical analyses were performed using linear mixed-effects models with adjustments.

Results: The median (interquartile range) for the habit actions tracked in the app was 391 (53 to 1146) during the one-year intervention. A higher number of actions was associated with an increase in EC (p<0.001) regardless of the intervention arm. The number of actions in all lifestyle categories, except for Non-smoking, were associated with improvements in EC during the intervention (all p<0.05), the most significant categories being Vegetables and fruit, Sugar, Sedentary behavior, and Meal frequency. 

Conclusions: The active use of the app, especially for tracking diet-related habits, could enhance EC in adults at increased risk for T2D. The habit formation app with a wide selection of health promoting behaviors seems a promising tool to influence eating behavior and, thus, for the prevention of T2D within primary healthcare services.

Purpose: This study investigated whether a combined diet and physical activity (PA) web-based computer-tailored intervention, called MyLifestyleCoach, effectively promoted dietary and PA behaviors. This intervention was based on self-determination theory and motivational interviewing.

Methods: A two-arm randomized controlled trial with 1142 Dutch adults was conducted. The intervention and control group completed questionnaires at baseline, 6, and 12 months from baseline. Only the intervention condition had access to MyLifestyleCoach. The waiting list control condition had access to the intervention after completing the 12-month follow-up questionnaire. A modified food frequency questionnaire was used to measure dietary behaviors (fruit, vegetables, fish, and unhealthy snacks). The Dutch Short Questionnaire to ASsess Health was used to measure the weekly minutes of moderate-to-vigorous PA (MVPA). Usage data, which is operationalized as completed sessions in this study, was assessed by log data. Two-step linear mixed effect models were performed. In the first step, a model consisting of condition, time, potentially confounding variables and a random intercept for participants was tested. In the second step, an interaction term was added to investigate the intervention’s (time × condition) and usage (time × opening session and time × completed sessions) effects over time for the dietary and PA outcomes.

Findings: The results showed no differences over time between the groups for all four dietary behaviors and the weekly minutes of MVPA. Furthermore, participants who followed the opening session of the intervention, in which they received general feedback on their behaviors, consumed significantly more fruit at 6 months and vegetables at 12 months than participants who did not follow the interventions’ opening session, including the participants in the waiting list condition. Lastly, participants who followed more sessions in the diet module consumed more fruit at 6 months and vegetables at 6 and 12 months and consumed unhealthy snacks less often at 12 months post-baseline.

Conclusions: In this study, the intervention was not effective in changing dietary and PA behavior. Moderation analyses suggest that this may partly be due to sub-optimal use of the intervention components. Further research should focus on improving intervention use.

Purpose: Fathers play a unique and important role in shaping their children’s physical activity (PA), but are rarely engaging in parenting programs. Lifestyle targeting fathers and their children are therefore a novel and promising way to improve PA of both. A theory-based lifestyle intervention to improve (co-)PA in fathers and children was co-created with fathers. The aim of this study was to investigate the effects of the Run Daddy Run intervention on (co-)PA as the main outcome, and a host of physical, psychological and family secondary outcomes.

Methods: A total of 90 fathers and one of their children (6-8 years old) participated in the study (control group (n=55); intervention group (n=35)). The Behavior Change Wheel was used as a theoretical framework to develop the Run Daddy Run intervention, combined with a co-creation approach. The proposed intervention consisted of 6 (inter)active father-child sessions and an eHealth component, delivered over a 14-week intervention period. However, due to COVID-19, only 2/6 face-to-face sessions could be implemented as planned, the remaining sessions were delivered using online activities. Baseline measurements were conducted between November 2019 and January 2020, post-test measurements in June 2020 with (co-)PA as the main outcome variable. Follow-up measurements were conducted in November 2020. Outcomes were measured using accelerometry and an online questionnaire. Linear mixed models were used to evaluate the effects of the intervention, using SPSS 26.0.

Results: The intervention was effective in improving co-PA of fathers and children on weekdays (p=0.010) and weekend days (p=0.025), MPA of the father (p=0.027) and LPA of the child (p<0.001). Positive intervention effects were also found for SB, some parental practices and psychosocial determinants of (co-)PA (all p<0.05). No effects were found for BMI, and an inverse intervention effect was found for MPA and VPA of the child.

Conclusions: The positive intervention effects have important implications for future research and health policy, where targeting fathers might be a novel and effective approach to improve health and health behaviours in children. However, more efforts should be made to invest  in MPA in children and VPA in children and fathers.