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BackgroundInterventions delivered through new device technology, including mobile phone apps, appear to be an effective method to reach young adults. Previous research indicates that self-efficacy and social support for physical activity and self-regulation behavior change techniques (BCT), such as goal setting, feedback, and self-monitoring, are important for promoting physical activity; however, little is known about evaluations by the target population of BCTs applied to physical activity apps and whether these preferences are associated with individual personality characteristics.ObjectiveThis study aimed to explore young adults’ opinions regarding BCTs (including self-regulation techniques) applied in mobile phone physical activity apps, and to examine associations between personality characteristics and ratings of BCTs applied in physical activity apps.MethodsWe conducted a cross-sectional online survey among healthy 18 to 30-year-old adults (N=179). Data on participants’ gender, age, height, weight, current education level, living situation, mobile phone use, personality traits, exercise self-efficacy, exercise self-identity, total physical activity level, and whether participants met Dutch physical activity guidelines were collected. Items for rating BCTs applied in physical activity apps were selected from a hierarchical taxonomy for BCTs, and were clustered into three BCT categories according to factor analysis: “goal setting and goal reviewing,” “feedback and self-monitoring,” and “social support and social comparison.”ResultsMost participants were female (n=146), highly educated (n=169), physically active, and had high levels of self-efficacy. In general, we observed high ratings of BCTs aimed to increase “goal setting and goal reviewing” and “feedback and self-monitoring,” but not for BCTs addressing “social support and social comparison.” Only 3 (out of 16 tested) significant associations between personality characteristics and BCTs were observed: “agreeableness” was related to more positive ratings of BCTs addressing “goal setting and goal reviewing” (OR 1.61, 95% CI 1.06-2.41), “neuroticism” was related to BCTs addressing “feedback and self-monitoring” (OR 0.76, 95% CI 0.58-1.00), and “exercise self-efficacy” was related to a high rating of BCTs addressing “feedback and self-monitoring” (OR 1.06, 95% CI 1.02-1.11). No associations were observed between personality characteristics (ie, personality, exercise self-efficacy, exercise self-identity) and participants’ ratings of BCTs addressing “social support and social comparison.”ConclusionsYoung Dutch physically active adults rate self-regulation techniques as most positive and techniques addressing social support as less positive among mobile phone apps that aim to promote physical activity. Such ratings of BCTs differ according to personality traits and exercise self-efficacy. Future research should focus on which behavior change techniques in app-based interventions are most effective to increase physical activity.

Many children do not meet the recommendations for healthy sleep, which is concerning given the potential negative effects on children's health. To promote healthy sleep, it is crucial to understand its determinants. This concept mapping study therefore explores perspectives of children and parents on potential determinants of children's inadequate sleep. The focus lies on 9-12 year old children (n = 45), and their parents (n = 33), from low socioeconomic neighbourhoods, as these children run a higher risk of living in a sleep-disturbing environment (e.g., worries, noise). All participants generated potential reasons (i.e., ideas) for children's inadequate sleep. Next, participants sorted all ideas by relatedness and rated their importance. Subsequently, multidimensional scaling and hierarchical cluster analyses were performed to create clusters of ideas for children and parents separately. Children and parents both identified psychological (i.e., fear, affective state, stressful situation), social environmental (i.e., sleep schedule, family sleep habits), behavioural (i.e., screen behaviour, physical activity, diet), physical environmental (i.e., sleep environment such as temperature, noise, light), and physiological (i.e., physical well-being) determinants. These insights may be valuable for the development of future healthy sleep interventions.Knowledge of the most relevant determinants is essential for the development of effective interventions [15]. A recent review of prospective studies [16] found evidence that spending more time on screens (e.g., TV, computer, games), having a difficult temperament, and past poor or inadequate sleep health (i.e., sleep quality or quantity) were longitudinally associated with shorter sleep duration. Another review summarized empirical evidence related to common paediatric sleep recommendations and identified having an inappropriate bedtime, not having a relaxing bedtime routine, having an irregular sleep schedule, a negative emotional environment (e.g., family stress, family conflict), and poorer emotional well-being (e.g., higher levels of internalizing symptoms) as potential determinants of children's inadequate sleep [17]. However, the perspectives of children and their parents are lacking in the current literature.The perspectives of children and their parents could bring about new and important insights into potential determinants of inadequate sleep, which can subsequently inform intervention development. Consequently, the aim of this study is to explore the perspectives of children and parents living in low-SEP neighbourhoods on potential determinants of children's inadequate sleep health. Materials and MethodsA participatory mixed-methods concept mapping study was conducted to assess children's and parents' perspectives on potential determinants of children's inadequate sleep health [18]. For the qualitative part of this approach, participants generated ideas about potential determinants during group brainstorm sessions, and subsequently rated these ideas according t...

Background: All 24-h movement behaviors, i.e. physical activity, sedentary behavior and sleep, are important for optimal health in children. Currently, no tools exist that include all 24-h behaviors and have been proven to be both reliable and valid. Potential reasons for the inadequate validity and reliability of existing questionnaires are the lack of focus on the content validity and lack of involvement of children in the development. Therefore, the aim of this study was to co-create a 24-h movement behavior tool together with 9-12-year-old children. Methods: Concept mapping and photovoice meetings were held to identify children's physical activity behaviors. During concept mapping meetings with four groups of children (n = 40), children generated an extensive list of physical activities they engaged in, sorted the activities in categories and rated the frequency and perceived intensity of these activities. Using photovoice, three groups of children (n = 24) photographed their physical activities during one weekday and one weekend day, named the photographs, and placed them on a timeline. Furthermore, researchers obtained information on relevant items regarding sleep and sedentary behavior by screening existing questionnaires. Thereafter, we developed the first version of MyDailyMoves. Subsequently, we examined the content validity of the tool together with three groups of children (n = 22) and one group of researchers (n = 7) using focus group meetings. Results: MyDailyMoves has a timeline format, onto which children add the activities they performed the previous day. Based on the concept mapping and photovoice studies, eight physical activity categories were included: playing inside, playing outside, sports, hobbies, chores, personal care, transport, and others. Sleep questions and two more sedentary categories (schoolwork and screen time) were added to MyDailyMoves to define and complete the timeline. The content validity study showed that all items in the tool were relevant. However, children mentioned that the activity category 'eating' was missing and the understandability of how to use the tool should be improved by adding an explanatory video. Both suggestions were adopted in the second version. Conclusion: Including the children's perceptions throughout the tool development process resulted in a comprehensive and practical tool which is easy for children to use.

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Inadequate sleep health (e.g. insufficient sleep duration, poor sleep quality and irregular sleep timing [Buysse, 2014]) among children is an important public health concern (Matricciani, Olds, & Petkov, 2012; Matricciani, Paquet, Galland, Short, & Olds, 2019), as healthy sleep is essential for a wide range of physical, mental, and behavioural outcomes (Astill, Van der Heijden, Van Ijzendoorn, & Van

An increasing number of children experience inadequate sleep, which negatively effects their health. To promote healthy sleep among children, it is essential to understand the underlying determinants. This online concept mapping study therefore explores potential determinants of children’s inadequate sleep as perceived by professionals with expertise in the sleep health of children aged 4–12 years. Participants (n = 27) were divided in three groups: (1) doctors (n = 9); (2) nurses (n = 11); (3) sleep experts (n = 7). Participants generated potential determinants (i.e., ideas) of children’s inadequate sleep. Subsequently, they sorted all ideas by relatedness and rated their importance. These data were analysed using multidimensional scaling and hierarchical cluster analysis. The results of all three groups were combined and validated by an additional group of professionals (n = 16). A large variety of perceived determinants were identified. The most important determinants perceived by all groups belonged to the categories psychosocial determinants (i.e., worrying, a change in daily life), daytime and evening activities (i.e., screen use before bedtime, stimulating game play before bedtime, inadequate amount of daytime physical activity), and pedagogical determinants (i.e., inconsistent sleep schedule, lack of a bedtime routine). These perspectives are valuable for future longitudinal studies on the determinants of children’s sleep and the development of future healthy sleep interventions.

BackgroundTo design a comprehensive approach to promote children's sleep health in Amsterdam, the Netherlands, we combined Intervention Mapping (IM) with the Health in All Policies (HiAP) perspective. We aimed to create an approach that fits local infrastructures and policy domains across sectors.MethodsFirst, a needs assessment was conducted, including a systematic review, two concept mapping studies, and one cross-sectional sleep diary study (IM step 1). Subsequently, semi-structured interviews with stakeholders from policy, practice and science provided information on potential assets from all relevant social policy sectors to take into account in the program design (HiAP and IM step 1). Next, program outcomes and objectives were specified (IM step 2), with specific objectives for policy stakeholders (HiAP). This was followed by the program design (IM step 3), where potential program actions were adapted to local policy sectors and stakeholders (HiAP). Lastly, program production (IM step 4) focused on creating a multi-sector program (HiAP). An advisory panel guided the research team by providing tailored advice during all steps throughout the project.ResultsA blueprint was created for program development to promote children's sleep health, including a logic model of the problem, a logic model of change, an overview of the existing organizational structure of local policy and practice assets, and an overview of policy sectors, and related objectives and opportunities for promoting children's sleep health across these policy sectors. Furthermore, the program production resulted in a policy brief for the local government.ConclusionsCombining IM and HiAP proved valuable for designing a blueprint for the development of an integrated multi-sector program to promote children's sleep health. Health promotion professionals focusing on other (health) behaviors can use the blueprint to develop health promotion programs that fit the local public service infrastructures, culture, and incorporate relevant policy sectors outside the public health domain.