Active gaming in Dutch adolescents: a descriptive study

<p>Abstract</p> <p>Background</p> <p>Adequate levels of physical activity are part of a healthy lifestyle and in this way linked to better health outcomes. For children and adolescents, the physical activity guideline recommends at least 60 minutes of moderate-to-vigorous physical activity every day. However, many adolescents are not physically active enough and they spend a lot of their time on sedentary activities (such as video games). A new generation of video games that require body movements to play them, so-called "active games", could serve to increase physical activity in adolescents. The activity level while playing these games is comparable to light-to-moderate intensity physical activity. The current study aims to increase our understanding of 1) the demographic characteristics of adolescents who play active games regularly (≥ 1 hour per week) and non-regularly (<; 1 hour per week), 2) time spent on active games, 3) the contribution of active games to daily physical activity and 4) the type and amount of activities being replaced by active gaming.</p> <p>Methods</p> <p>A cross-sectional survey was conducted in a Dutch internet panel, questioning adolescents in conjunction with one of their parents. A random sample of 320 households (with stratification on gender of the parent and the adolescent, the age of the adolescent and the region of the household) was selected that owned a console or application for active video games and that had a child aged 12 through 16 years. 201 child–parent couples (63% response) completed an internet survey with questions about demographics, physical activity and sedentary behaviour, and gaming behaviour. The questionnaire also contained questions designed to assess whether and how active gaming replaces other activities. Besides descriptive analyses, independent t-test, Pearson’s chi-square and Mann–Whitney test (when data were not normally distributed) were used for comparisons between regular and non-regular active gamers.</p> <p>Results</p> <p>Eleven percent of the adolescents with an active game in their household never used the game. There were no significant differences in gender, education level (of adolescent and parent), ethnicity and sedentary behaviour between regular (n = 65) and non-regular active gamers (n = 114). Adolescents’ (regular and non-regular active gamers) meantime spent on active gaming was 80 (± 136) minutes a week; this potentially amounts to 11% of total physical activity. When time spent on active gaming was included in the calculation of the percentage of adolescents that met the physical activity guideline, the percentage increased significantly (p <; 0.05) from 67 to 73%. According to the adolescents, active gaming mainly replaces sedentary screen time such as TV viewing, internet and non-active gaming. Parental opinions concurred with this appraisal.</p> <p>Conclusions</p> <p>The results of this study confirm the idea that active gaming may contribute to an active lifestyle in adolescents, primarily because it potentially contributes substantially to time spent on physical activity. Secondly, active gamers indicate that they spent time on active games which they would have spent otherwise on less active activities.</p

Which game narratives do adolescents of different gameplay and sociodemographic backgrounds prefer? a mixed-methods analysis

OBJECTIVE: The aim of this study was to investigate which narrative elements of digital game narratives are preferred by the general adolescent population, and to examine associations with gender, socioeconomic status (SES), and gameplay frequency. Further, the study aims to discuss how results can be translated to serious digital games. MATERIALS AND METHODS: Adolescents were recruited through school to complete a survey on narrative preferences in digital games. The survey included questions on sociodemographic information, frequency of gameplay, and an open-ended question on what could be an appealing narrative for them. Data were analyzed in a mixed-methods approach, using thematic analysis and chi-square analyses to determine narrative preferences and the associations between game narrative elements and player characteristics (gender, SES, and frequency of gameplay). RESULTS: The sample consisted of 446 adolescents (12-15 years old) who described 30 narrative subthemes. Preferences included human characters as protagonists; nonhuman characters only as antagonists; realistic settings, such as public places or cities; and a strong conflict surrounding crime, catastrophe, or war. Girls more often than boys defined characters by their age, included avatars, located the narrative in private places, developed profession-related skills, and included a positive atmosphere. Adolescents of nonacademic education more often than adolescents of academic education defined characters by criminal actions. Infrequent players more often included human characters defined by their age than frequent players. After performing a Bonferroni correction, narrative preferences for several gender differences remained. CONCLUSION: Different narrative elements related to subgroups of adolescents by gender, SES, and frequency of gameplay. Customization of narratives in serious digital health games should be warranted for boys and girls; yet, further research is needed to specify how to address girls in particular

Is Workstyle a Mediating Factor for Pain in the Upper Extremity Over Time?

Introduction Upper extremity musculoskeletal disorders influence workers’ quality of life. Workstyle may be one factor to deal with in workers with pain in the upper extremity. The objective of this study was to determine if workstyle is a mediating factor for upper extremity pain in a changing work environment of office workers over time. Methods Office workers with upper extremity pain filled out a Workstyle questionnaire (WSF) at baseline (n = 110). After 8 and 12 months follow-up assessment took place. Participants were divided into a good and an adverse workstyle group at baseline. The presence of upper extremity pain in both groups was calculated and relative risks were determined. Chi-square tests were used. Results Eight months after baseline, 80% of the adverse and 45% of the good workstyle group reported pain. The relative risk (RR) of having upper extremity pain for the adverse compared to the good workstyle group was 1.8 (95% CI 1.08–2.86) (P = 0.055). Twelve months after baseline, upper extremity pain was more often presented in the adverse workstyle compared to the good workstyle group (RR = 3.0, (95% CI 1.76–5.11), P = 0.003). Twelve months after baseline, 100% of the adverse workstyle group and 33% of the good workstyle group reported pain in the upper extremity. Conclusion Workstyle seems to be a mediating factor for upper extremity pain in office workers in a changing work environment. It is recommended to assess workstyle among office workers with upper extremity pain, and to include workstyle behaviour in treatments

The structure of oppositionality: Response disposition and situational aspects

Background: The Amsterdam Scale of Oppositionality (ASO) is a recently developed self-report instrument to measure the full range of oppositionality. It was used to test the assumption that oppositionality can best be conceptualized as a combination of emotions and behaviors varying across contexts, i.e., with parents, peers and authority figures. Method: The sample consisted of 560 boys and 598 girls, aged 8 to 12 years. The thirty items of the ASO, grouped in item parcels, were analyzed using confirmatory factor analyses. Results: Results confirmed the main hypothesis. The best fitting models contained strongly related emotional and behavioral factors and three mutually related situational factors. Oppositionality appeared to be to a large extent situation-specific. Girls are more affected by the situation than boys and show less oppositionality only outside the family context. Conclusions: Results are discussed with respect to the concept of oppositionality, varying expectations for interpersonal consequences, and implications for clinical assessment and studies of inter-informant reliability

The importance of both setting and intensity of physical activity in relation to non-clinical anxiety and depression

Physical activity is associated with good physical and mental health. Current recommendations suggest that people should achieve 30 minutes of moderate-intensity activity most days of the week to gain health benefits. This activity may be accumulated in leisure time, in active commuting, at work or in the home. Here we look at the cross-sectional relationship between physical activity and mental health as measured by the HADS anxiety and depression scores in a sample of 1,742 participants from a Scottish general population survey. The participants were men and women in three age cohorts aged around 24, 44 and 64 years who, in 1995, were interviewed face to face and also self-completed the HADS depression and anxiety scale. Respondents reported their levels of physical activity at work, in the home and in leisure time; the intensities of activity were also determined. Physical activity was related to depression scores but not to anxiety scores. There was no relationship between work physical activity and depression score. Among women, depression score increased with each additional episode of vigorous home activity. In both sexes, depression score decreased with each additional episode of vigorous leisure activity, but among men the decrease in depression score with moderate leisure activity was reversed if a lot of moderate activity was undertaken. We have found a variable relationship between depression scores and various settings for physical activity. Researchers, policymakers and practitioners who are interested in the relationship between physical activity and mental health should take into account the setting for activity as well as frequency, duration and intensity of activity

The SOS-framework (Systems of Sedentary behaviours): An international transdisciplinary consensus framework for the study of determinants, research priorities and policy on sedentary behaviour across the life course: A DEDIPAC-study

© 2016 The Author(s).Background: Ecological models are currently the most used approaches to classify and conceptualise determinants of sedentary behaviour, but these approaches are limited in their ability to capture the complexity of and interplay between determinants. The aim of the project described here was to develop a transdisciplinary dynamic framework, grounded in a system-based approach, for research on determinants of sedentary behaviour across the life span and intervention and policy planning and evaluation. Methods: A comprehensive concept mapping approach was used to develop the Systems Of Sedentary behaviours (SOS) framework, involving four main phases: (1) preparation, (2) generation of statements, (3) structuring (sorting and ranking), and (4) analysis and interpretation. The first two phases were undertaken between December 2013 and February 2015 by the DEDIPAC KH team (DEterminants of DIet and Physical Activity Knowledge Hub). The last two phases were completed during a two-day consensus meeting in June 2015. Results: During the first phase, 550 factors regarding sedentary behaviour were listed across three age groups (i.e., youths, adults and older adults), which were reduced to a final list of 190 life course factors in phase 2 used during the consensus meeting. In total, 69 international delegates, seven invited experts and one concept mapping consultant attended the consensus meeting. The final framework obtained during that meeting consisted of six clusters of determinants: Physical Health and Wellbeing (71 % consensus), Social and Cultural Context (59 % consensus), Built and Natural Environment (65 % consensus), Psychology and Behaviour (80 % consensus), Politics and Economics (78 % consensus), and Institutional and Home Settings (78 % consensus). Conducting studies on Institutional Settings was ranked as the first research priority. The view that this framework captures a system-based map of determinants of sedentary behaviour was expressed by 89 % of the participants. Conclusion: Through an international transdisciplinary consensus process, the SOS framework was developed for the determinants of sedentary behaviour through the life course. Investigating the influence of Institutional and Home Settings was deemed to be the most important area of research to focus on at present and potentially the most modifiable. The SOS framework can be used as an important tool to prioritise future research and to develop policies to reduce sedentary time

A systematic review of correlates of sedentary behaviour in adults aged 18–65 years: a socio-ecological approach

Background: Recent research shows that sedentary behaviour is associated with adverse cardio-metabolic consequences even among those considered sufficiently physically active. In order to successfully develop interventions to address this unhealthy behaviour, factors that influence sedentariness need to be identified and fully understood. The aim of this review is to identify individual, social, environmental, and policy-related determinants or correlates of sedentary behaviours among adults aged 18-65 years. Methods: PubMed, Embase, CINAHL, PsycINFO and Web of Science were searched for articles published between January 2000 and September 2015. The search strategy was based on four key elements and their synonyms: (a) sedentary behaviour (b) correlates (c) types of sedentary behaviours (d) types of correlates. Articles were included if information relating to sedentary behaviour in adults (18-65 years) was reported. Studies on samples selected by disease were excluded. The full protocol is available from PROSPERO (PROSPERO 2014:CRD42014009823). Results: 74 original studies were identified out of 4041: 71 observational, two qualitative and one experimental study. Sedentary behaviour was primarily measured as self-reported screen leisure time and total sitting time. In 15 studies, objectively measured total sedentary time was reported: accelerometry (n = 14) and heart rate (n = 1). Individual level factors such as age, physical activity levels, body mass index, socio-economic status and mood were all significantly correlated with sedentariness. A trend towards increased amounts of leisure screen time was identified in those married or cohabiting while having children resulted in less total sitting time. Several environmental correlates were identified including proximity of green space, neighbourhood walkability and safety and weather. Conclusions: Results provide further evidence relating to several already recognised individual level factors and preliminary evidence relating to social and environmental factors that should be further investigated. Most studies relied upon cross-sectional design limiting causal inference and the heterogeneity of the sedentary measures prevented direct comparison of findings. Future research necessitates longitudinal study designs, exploration of policy-related factors, further exploration of environmental factors, analysis of inter-relationships between identified factors and better classification of sedentary behaviour domains