Combining Web-Based Gamification and Physical Nudges With an App (MoveMore) to Promote Walking Breaks and Reduce Sedentary Behavior of Office Workers: Field Study.

BACKGROUND: Sedentary behavior (SB) and lack of physical activity (PA) have been associated with poorer health outcomes and are increasingly prevalent in individuals working in sedentary occupations such as office jobs. Gamification and nudges have attracted attention as promising strategies to promote changes in health behavior. However, most effectiveness studies thus far lacked active controls, and few studies have tested interventions combining these strategies. OBJECTIVE: This study investigates the effectiveness of combining a gamified digital app with physical nudges to increase PA and reduce SB in Dutch office workers. METHODS: Employees in the municipality of Rotterdam (N=298) from two office locations were randomized at the location level to either a 10-week intervention, combining a 5-week gamification phase encompassing a gamified digital app with social support features and a 5-week physical nudges phase, or to an active control (ie, basic digital app with self-monitoring and goal setting). The primary outcome was the daily step count, objectively measured via accelerometers. Secondary outcomes were self-reported PA and SB measured at baseline and at 5, 10, and 14 weeks. Mixed effects models were used to analyze the effects of the intervention on the outcome measures. RESULTS: A total of 78.5% (234/298) of participants completed the study and provided accelerometer data, whereas 36.9% (110/298) participants completed the self-report measures at 14 weeks. In the gamification phase, step count data were missing for 13.5% (473/3492) of observations in the control and 11.4% (445/3888) in the intervention condition; however, these percentages increased to 39.6% (1154/2910) and 59.6% (1932/3492) at follow-up, respectively. During the gamification phase, intervention participants increased their number of daily steps by 634 (95% CI 154.2-1113.8; P=.01) more than participants in the control group, after controlling for relevant factors. Improvements were not sustained during the physical nudges phase (P=.76) or follow-up (P=.88). CONCLUSIONS: A digital intervention with gamification and social support features significantly increased the step count of office workers compared with an active control. Physical nudges in the workplace were insufficient to promote the maintenance of behavioral changes achieved in the gamification phase. Future research should explore the long-term effectiveness of similar gamified digital interventions. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN) 49129401; https://www.isrctn.com/ISRCTN14881571.

The BeHealthyR Study: a randomized trial of a multicomponent intervention to reduce stress, smoking and improve financial health of low-income residents in Rotterdam.

BACKGROUND: Compared to higher socioeconomic status (SES) groups, those in lower SES groups are financially strained, experience higher rates of smoking-related morbidity, are in poorer health and have reduced life expectancy. This is especially true for the city of Rotterdam, where a large inequality in health is observed between low and high SES groups. The BeHealthyR study (Dutch: Grip en Gezondheid) is a randomized controlled trial (RCT) which will evaluate the impact of a theory-based multicomponent behavior intervention aiming to reduce stress, smoking, and improve financial health by means of a group-based stress management program combining cognitive and behavioral techniques, and nudges in low-SES residents living in Rotterdam. METHODS: The BeHealthyR study is a three-arm RCT. Between February 2018 and July 2019, low-SES participants who perceive stress, smoke, are financially strained and reside in Rotterdam (one of the four largest cities in The Netherlands) are recruited. Subsequently, participants are randomly assigned to either a stress management condition (SM), stress management with a buddy condition (SM-B) or a control condition (CC). Participants in the SM and SM-B conditions will attend four weekly group sessions (1.5 h/session) and a follow-up session eight weeks later. The SM condition includes psychoeducation and exercises, and cognitive and behavioral intervention techniques. Demographic data and objective measures will be collected at baseline (T0), four weeks post-baseline (T1), and twelve weeks post-baseline (T2). Primary outcome measures are to reduce stress, smoking and improve financial health. We hypothesize that low-SES participants in the intervention conditions, compared with those in the control condition, will experience less stress, smoke less and have improved financial health. DISCUSSION: This study is a group-based intervention which aims to investigate the effects of a theory-based behavioral change intervention employing several components on reducing stress, smoking, and improving financial health in low-SES residents living in Rotterdam. If effective, the findings from the present study will serve to inform future directions of research and clinical practice with regard to behavioral change interventions for low-SES groups. TRIAL REGISTRATION: ClinicalTrials.gov (ID: NCT03553979 ). Registered on January 1 2018.

Socioeconomic inequalities in frailty among older adults in six low- and middle-income countries: Results from the WHO Study on global AGEing and adult health (SAGE).

OBJECTIVES: The aim of this study was to investigate socioeconomic inequalities in frailty among older adults in six low- and middle-income countries (LMICs), and to examine to what extent chronic diseases account for these inequalities. STUDY DESIGN: Data were used from the Study on global AGEing and adult health (SAGE) wave 1 (2007-2010). Nationally representative samples of adults aged 50+ years from China, Ghana, India, Mexico, the Russian Federation and South Africa were analyzed (n = 31,174). MAIN OUTCOME MEASURES: Educational level and wealth were used as socioeconomic indicators. Frailty was assessed with modified criteria for the frailty phenotype. Self-reported disease diagnoses were used. A relative index of inequality (RII) was calculated to compare socioeconomic inequalities in frailty between countries. RESULTS: People in lower socioeconomic positions had higher prevalence rates of frailty. The largest inequalities in frailty were found in Mexico (RII 3.7, 95% CI 2.1-6.4), and the smallest inequalities in Ghana (RII 1.1, 95% CI 0.7-1.8). Mediation analyses revealed that the chronic diseases considered in this study do not explain the higher prevalence of frailty seen in lower socioeconomic groups. CONCLUSIONS: Substantial socioeconomic inequalities in frailty were observed in LMICs, but additional research is needed to find explanations for these. Given that the population of older adults in many LMICs is expanding at a greater rate than in many high-income countries, our results indicate an urgent public health need to address frailty in these countries.