ECSS Paris 2023: OP-SH13
Purpose: Physical inactivity is considered one of the major risk factors for noncommunicable diseases (NCDs), alongside tobacco use, alcohol consumption, and unhealthy diets. While systems to monitor the implementation of evidence-based policies to address these risk factors exist for each of the four fields, a composite instrument to systematically assess progress across the board is currently lacking. We developed an index that allows for scoring government performance on PA policy alongside the three other risk factors, and applied it to a sample of European countries. Methods: We systematically searched for existing tools for assessing the adoption of policies to address key risk factors for NCDs. For tobacco and alcohol, we identified suitable and internationally established benchmarking tools. For unhealthy diets, a new index was developed assessing the adoption of six nutrition policy measures. For physical activity, we used data from WHO’s 2022 Global Status Report on Physical Activity to develop a simple additive score for government performance in the areas of active societies, active environments, active people, and active systems. Unlike the other three NCD areas, data were based on government self-reports rather than from independent sources. The four sub-indices were integrated into an overarching index ranging from 0 (no implementation of any policies) to 100 (full implementation of all policies). We then applied this index to 18 European countries. Results: Among the 18 countries assessed, the Public Health Index ranged from 32 (Switzerland) to 72 (UK), with a median score of 50 (interquartile range: 43-64). The highest scoring countries (score ≥ 60) included the UK, Finland, Ireland, Norway, France and Lithuania, and the lowest scoring countries (score ≤ 40) were Luxembourg, Austria, Germany and Switzerland. Scores across the risk factors nutrition, alcohol and tobacco policy were correlated, in particular among lowest scoring countries. Scores in the physical activity policy varied less across countries, and correlated less with the scores of the other three risk factors. Conclusion: The Public Health Index allows for a structured and systematic comparison of the adoption of policies for addressing four major NCD risk factors. In our sample, policy adoption varies considerably, but substantial gaps are evident across all countries. The index is highly useful for putting physical activity policy data into the larger context of countries’ general NCD policies. At the same time, the scoring for physical activity still lags behind the other three areas in terms of methodological rigor and data quality, thus warranting further efforts to meet international standards in NCD policy monitoring and to render results more comparable to those from other policy areas.
Read CV Peter GeliusECSS Paris 2023: OP-SH13
Excessive smartphone and social network use are emerging public health concerns linked to poorer mental health. Other online behaviours, including gaming and gambling, also negatively affect psychological and physical well-being. University Students (US) may be particularly vulnerable due to academic demands, sedentary habits, and high digital exposure. Although Physical activity (PA) has been proposed as a protective factor, evidence remains inconsistent, with studies reporting both inverse and direct associations between PA and problematic technology use. Therefore, this study aimed to 1) compare PA levels and digital problematic use indicators between US and age-matched Vocational Training Students (VTS), 2) examine socioeconomic differences between these groups, 3) analyse associations between PA and digital problematic use, and 4) explore gender differences. A cross-sectional, comparative, and correlational study was conducted with 257 Spanish adults enrolled in university (n=131, age=23±5 years) or vocational training programmes (n=126; age=20±3 years). Participants completed a questionnaire that included the following scales in their Spanish validated version: Smartphone Addiction Scale, Social Network Addiction Scale, Internet Gaming Disorder, Online Gambling Diagnostic Questionnaire, International Physical Activity Questionnaire, Satisfaction with Life Scale and Rosenberg Self-Esteem Scale. Socioeconomic status was also collected. Mann-Whitney U test for comparisons and the Spearman correlation test were performed. US exhibited significantly lower levels of PA compared to VTS (p<.001). In addition, US reported significantly higher levels of Smartphone Problematic Use (SPU; p=.004) and Social Network Problematic Use (SNPU, p=.003). Conversely, US showed lower scores of Internet Gaming Disorder (IGD; p=.002) and Problematic Online Gambling (POG; p=.002), as well as higher socioeconomic status (p=.002) compared to VTS. Across the total sample, PA was inversely correlated with SPU (p<.001) and SNPU (p=.002) scores, while it was positively correlated with POG (p=.006) scores. Additionally, participants classified as problematic users of smartphones and social networks demonstrated significantly lower levels of PA (p<.05) and self-esteem (p<.05). Regarding gender, women reported higher levels of SPU (p=.011) and SNPU (p<.001), whereas men showed higher levels of PA (p<.001), self-esteem (p=.002), IGD (p<.001) and POG (p<.001). US appear to present lower PA and higher SPU and SNPU scores compared to VTS. Conversely, VTS seem to show higher IGD and POG scores, which might be partially related to their lower socioeconomic status. The inverse associations observed between PA and SPU-SNPU suggest that a more active lifestyle could be related to lower problematic technology use. Thus, promoting PA within university settings may represent a potentially beneficial strategy to encourage healthier behavioural patterns related to SPU and SNPU.
Read CV Javier Fernández SánchezECSS Paris 2023: OP-SH13
INTRODUCTION: Leaderboards are persuasive tools in health and fitness promotions. Yet, the underlying mechanisms by which different leaderboard ranks influence health and fitness behavior remain unclear (James et al., 2025). Building upon leaderboard literature and social comparison theory, we aim to examine the non-linear effects of leaderboard rank on physical activity and test how upward and downward social comparison orientations shape these effects, thereby explaining plateaus and progress patterns in fitness behavior. METHODS: We designed a two-wave online survey with a one-week lag to mitigate common method bias and examine non-linear effects of leaderboard design and social comparison on physical activity. We focused on WeRun, a fitness leaderboard feature of WeChat, and administered the study via Credamo. Participants’ daily step counts (wave 2 steps as dependent variable), leaderboard ranks, and received likes over seven days were recorded by the WeRun app and self-reported by participants. Social comparison was assessed using a validated four-dimensional scale (Esteves et al., 2021). We integrated generalized additive models (GAM) to model non-linear associations and LightGBM with SHAP to quantify feature importance, thereby exploring plateau and progression patterns (Hofman et al., 2021). In total, 1,267 healthy Chinese users (64.4% female; mean age 30.2) were included in the analysis. RESULTS: The GAM revealed non-linear effects (adjusted R² = 45.8%). Leaderboard rank showed a U-shaped relationship (EDF = 2.67, p < .001), with step counts lowest at mid-ranks. Received likes exhibited a plateau beyond 3–4 likes (EDF = 1.85, p = .006). Upward contrast decreased activity only at very low levels (EDF = 2.24, p = .045); downward contrast increased activity only at very high levels (EDF = 2.02, p = .025). Thus, physical activity is optimally promoted when users do not contrast with upward targets but strongly contrast with downward targets. Furthermore, LightGBM combined with SHAP identified leaderboard rank and received likes as the most important predictors of step counts. Partial dependence plots further confirmed this U-shaped relationship. CONCLUSION: We found non-linear, threshold-based patterns in the effects of leaderboard rank on physical activity. The findings may practically inform the design of fitness leaderboards to mitigate demotivation among mid-rank users and theoretically extend social comparison theory. REFERENCES: Esteves et al., (2021). Online social games: The effect of social comparison elements on continuance behaviour. Information & Management, 58(4), 103452. Hofman et al., (2021). Integrating explanation and prediction in computational social science. Nature, 595(7866), 181-188. James et al., (2025). Is fitness technology-facilitated social comparison the thief of well-being? The mediating role of social comparison on the relationships between passion and performance self-esteem. Information Systems Research.
Read CV Yanxiang YangECSS Paris 2023: OP-SH13