Physical Activity with Sports Scientist (PASS) programme to promote physical activity among patients with non-communicable diseases: a pragmatic randomised controlled trial protocol.

Physical activity (PA) effectively prevents and treats non-communicable diseases in clinical settings. PA promotion needs to be more consistent, especially in busy primary care. Sports scientists have the potential to support PA promotion in primary care. The Physical Activity with Sports Scientist (PASS) programme is created to personalise PA promotion led by a sports scientist in a primary care clinic. A pragmatic randomised controlled trial with two parallel groups will be conducted at a family medicine clinic. Physically inactive participants aged 35-70 years who have type 2 diabetes mellitus, hypertension or dyslipidaemia will be invited. The control group (n=60) will receive usual care. The intervention group (n=60) will receive the PASS programme and usual care. The PASS programme will consist of a tailored PA prescription after the physician's consultation at the first visit and monthly phone follow-ups. The primary outcome is the proportion of participants who have achieved the PA goal defined as aerobic activity (≥150 min/week of moderate to vigorous-intensity PA), muscle-strengthening activity (≥2 days/week of moderate or greater intensity) and multicomponent PA (≥2 days/week of moderate or greater intensity). Secondary outcomes are body composition and physical fitness. The primary and secondary outcomes will be measured and compared between the control and intervention groups at visit 1 (month 0: baseline measurements), visit 2 (months 3-4: follow-up measurements), visit 3 (months 6-8: end-point measurements) and visit 4 (months 9-12: continuing measurements). The study protocol was registered with the Thai Clinical Trials Registry. Trial registration number: TCTR20240314001.

Thai Preschoolers' movement behaviors outside kindergarten: prevalence of meeting individual and integrated movement guidelines.

BACKGROUND: This study aimed to investigate movement behaviors of Thai preschoolers (aged 3-6 years) occurring outside kindergarten in urban areas across Thailand. METHODS: Surveillance of digital Media in eArLy chiLdhood Questionnaire® was used to collect data from 1051 parents recruited from 12 schools. Descriptive statistics and logistic regressions were applied for data analysis. RESULTS: Thai preschoolers engaged in physical activity (PA), sedentary screen time, and sleep on weekends significantly more than weekdays with no significant sex differences. Preschoolers met the sleep guidelines the most (62.3%), followed by PA guidelines (48.0%), and screen time (ST) guidelines the least (44.1%). Only 14.6% met the integrated movement guidelines, and 11% met none of the guidelines. Age was positively associated with meeting the PA guidelines, and negatively associated with meeting the sleep and integrated movement guidelines. The number of digital devices at home and geographical region influenced preschoolers in meeting the PA and ST guidelines. CONCLUSIONS: Thai preschoolers' time spent on all forms of activities outside kindergarten was significantly more on weekends than weekdays with no sex disparity. The prevalence of meeting the integrated movement guidelines was low, and needs to be addressed through comprehensive programs including all forms of activities concurrently. IMPACT: Thai preschoolers engaged in physical activity (PA), screen time (ST), and sleep on weekends significantly more than weekdays with no significant sex differences. Only 14.6% of preschoolers met the integrated movement guidelines. Age had a significant relationship with meeting the PA, sleep, and integrated movement guidelines. Meeting the PA and ST guidelines in preschoolers was positively associated with the number of digital devices at home. Despite some limitations, this study presented preschoolers' time engaged in the three movement behaviors concurrently, and provided important inputs for development of the national strategic plan to promote PA among Thai children and youth.

Multilevel factors associated with physical activity participation among Thai university students.

This study investigated physical activity (PA) levels in Thai university students and their associated factors at multiple levels. Data of 3,930 university students age ≥18 years analyzed in this study were retrieved from a cross-sectional online survey, namely the ASEAN University Network - Health Promotion Network (AUN-HPN) health behavioral survey. The hierarchical generalized linear model considering clustering effects was applied to examine factors associated with sufficient PA across multiple levels. At the individual level, being female, underweight, and overweight had significantly lower odds of having sufficient PA. Sophomores had 22 % greater odds compared with freshmen. Students engaging in 1-3 and 4-6 sports activities had 3 and almost 4 times respectively higher odds of having sufficient PA. Students engaged in >8 h of sedentary time, and consumed adequate amounts of fruit/vegetables had 70 % and 59 % respectively higher odds of having sufficient PA. At the environmental level, students who traveled inactively to/from university, attended a university with private recreational facilities, and a university that adopted the healthy university framework (HUF) had significantly greater odds of having sufficient PA. A majority of university students were sufficiently physically active, despite gender disparity. When promoting PA among them, focus may be targeted at females and sophomores, and consider addressing the number of sports activities engaged, fruit/vegetable consumption, availability of private university recreational facilities, and adoption of the HUF. The results support the implementation of the AUN-HPN HUF, and future initiatives within the country and the wider network for health and PA promotion.

Machine Learning-Based Prediction of Mental Well-Being Using Health Behavior Data from University Students.

BACKGROUND: Since the onset of the COVID-19 pandemic in early 2020, the importance of timely and effective assessment of mental well-being has increased dramatically. Machine learning (ML) algorithms and artificial intelligence (AI) techniques can be harnessed for early detection, prognostication and prediction of negative psychological well-being states. METHODS: We used data from a large, multi-site cross-sectional survey consisting of 17 universities in Southeast Asia. This research work models mental well-being and reports on the performance of various machine learning algorithms, including generalized linear models, k-nearest neighbor, naïve Bayes, neural networks, random forest, recursive partitioning, bagging, and boosting. RESULTS: Random Forest and adaptive boosting algorithms achieved the highest accuracy for identifying negative mental well-being traits. The top five most salient features associated with predicting poor mental well-being include the number of sports activities per week, body mass index, grade point average (GPA), sedentary hours, and age. CONCLUSIONS: Based on the reported results, several specific recommendations and suggested future work are discussed. These findings may be useful to provide cost-effective support and modernize mental well-being assessment and monitoring at the individual and university level.

Ecological correlates of sport and exercise participation among Thai adolescents: A hierarchical examination of a cross-sectional population survey.

BACKGROUND: Understanding factors influencing adolescents' sport/exercise participation (S/EP) is vital to developing effective interventions, but currently, evidence from less developed countries is limited. The purpose of this study was to examine correlates of S/EP across individual, interpersonal, and environmental levels in a nationally representative sample of Thai adolescents. METHODS: Data from 4617 Thai adolescents aged 14-17 years old were obtained from recruited schools across Thailand. Data on S/EP (outcome variable), and psychosocial, home, and community environment covariates were collected from individual adolescents using the Thailand Physical Activity Children Survey, Student Questionnaire. School environmental data were collected at the school level using a School Built Environment Audit. Hierarchical regressions taking into account school clustering effects were applied for data analysis. RESULTS: At the individual level, age and body mass index were independently and strongly correlated with S/EP. Adolescents with high preference for physical activity (PA) (odd ratio (OR) = 1.71, p < 0.001) and at least a moderate level of self-efficacy (OR = 1.33, p = 0.001) were more likely to have high S/EP. At the interpersonal level, adolescents whose parents joined their sports/exercise at least 1-2 times/week (OR = 1.36, p = 0.003) received ≥3 types of parental support (OR = 1.43, p = 0.005) and who received siblings' (OR = 1.26, p = 0.004) and friends' (OR = 1.99, p < 0.001) support had a greater chance of high S/EP. At the environmental level, adolescents' S/EP was greater when there were at least 3-4 pieces of home sport/exercise equipment (OR = 2.77, p = 0.003), grass areas at school (OR = 1.56, p < 0.001), and at least 1-2 PA facilities in the community (OR = 1.30, p = 0.009). CONCLUSION: Multiple factors at different levels within an ecological framework influencing Thai adolescents' S/EP were generally similar to those found in developed countries, despite some differences. For those interested in promoting and supporting Thai adolescents' engagement in sports/exercise, further exploration of the influence of self-efficacy and attitude toward PA is required at the individual level; parental and peer support at the interpersonal level; and home sport equipment, school grass areas, and neighborhood PA facilities at the environment level.

University students' overall and domain-specific physical activity during COVID-19: A cross-sectional study in seven ASEAN countries.

This research investigated the overall and domain-specific physical activity (PA) of university students in the coronavirus disease 2019 (COVID-19) pandemic. A cross-sectional study was applied to socioeconomic (SE) and PA online data collected from 15,366 students across 17 universities in seven Association of Southeast Asian Nations (ASEAN) countries. Statistical analyses using logistic regressions established SE-PA relationships. Over half (60.3%) of ASEAN university students met age-span specific PA guidelines. Students participated in recreational PA the most, followed by study-related activities and 44.1% of students engaged in >8 hrs/day of sedentary time (ST). Compared to students with a normal body mass index (BMI), students who were underweight (UW), overweight (OW), and obese (OB) respectively, had a 14% (UW odds ratio (OR) = 1.14, p = 0.005), 25% (OW OR = 1.25, p < 0.001), and 24% (OB OR = 1.24, p = 0.005) greater probability of meeting PA guidelines. Those who engaged in active transport and belonged to a sports club (SC) had 42% (SC OR = 0.58, p < 0.001, for both) less probability of meeting the PA guidelines, compared with those who travelled inactively and did not belong to a sports club, respectively. Students who participated in 4-6 sport or exercise activities had ten times more likelihood of meeting PA guidelines (OR = 10.15, p < 0.001), compared with those who did not play any sport or do any exercise. Students who spent >8 hrs/day of ST had 32% (ST OR = 0.68, p < 0.001) less probability of meeting PA guidelines, compared with those who spent <3 hrs of ST. These data showed that over half of ASEAN university students achieved PA guidelines and were highly sedentary during the COVID-19 pandemic. Recreational and study-related activities were important for students to maintain sufficient PA and should be actively promoted within the restrictions imposed during periods of the COVID-19 pandemic lockdowns.

The clusters of health-risk behaviours and mental wellbeing and their sociodemographic correlates: a study of 15,366 ASEAN university students.

BACKGROUND: This study investigated, through cluster analysis, the associations between behavioural characteristics, mental wellbeing, demographic characteristics, and health among university students in the Association of Southeast Asian Nations (ASEAN) University Network - Health Promotion Network (AUN-HPN) member universities. METHODS: Data were retrieved from a cross-sectional self-administered online survey among undergraduate students in seven ASEAN countries. A two-step cluster analysis was employed, with cluster labels based on the predominant characteristics identified within the clusters. The 'healthy' cluster was assigned as the reference group for comparisons using multinomial logistic regression analysis. RESULTS: The analytic sample size comprised 15,366 university students. Five clusters of student-types were identified: (i) 'Healthy' (n = 1957; 12.7%); (ii) 'High sugary beverage consumption' (n = 8482; 55.2%); (iii) 'Poor mental wellbeing' (n = 2009; 13.1%); (iv) 'Smoker' (n = 1364; 8.9%); and (v) 'Alcohol drinker' (n = 1554; 10.1%). Being female (OR 1.28, 95%CI 1.14, 1.45) and being physically inactive (OR 1.20, 95%CI 1.04, 1.39) increased the odds of belonging to the 'High sugary beverage consumption' cluster. Being female (OR 1.21, 95%CI 1.04, 1.41), non-membership in a sports club (OR 1.83, 95%CI 1.43, 2.34) were associated with 'Poor mental wellbeing'. Obesity (OR 2.03, 95%CI 1.47, 2.80), inactively commuting to campus (OR 1.34, 95%CI 1.09, 1.66), and living in high-rise accommodation (OR 2.94, 95%CI 1.07, 8.07) were associated with membership in the 'Smoker' cluster. Students living in The Philippines, Singapore, Thailand, and Vietnam had a higher likelihood of being alcohol drinkers, compared with those who lived in Brunei. CONCLUSIONS: ASEAN university students exhibited health-risk behaviours that typically clustered around a specific health behaviour and mental wellbeing. The results provided support for focusing interventions on one dominant health-risk behaviour, with associated health-risk behaviours within clusters being potential mediators for consideration.

Prevalence of Health-Risk Behaviors and Mental Well-Being of ASEAN University Students in COVID-19 Pandemic.

The prevalence of epidemiological health-risk behaviors and mental well-being in the COVID-19 pandemic, stratified by sociodemographic factors in Association of South East Asian Nations (ASEAN) university students, were examined in the research. Data were collected in March-June 2021 via an online survey from 15,366 university students from 17 universities in seven ASEAN countries. Analyzed data comprised results on physical activity, health-related behaviors, mental well-being, and sociodemographic information. A large proportion of university students consumed sugar-sweetened beverages (82.0%; 95%CI: 81.4, 82.6) and snacks/fast food daily (65.2%; 95%CI: 64.4, 66.0). About half (52.2%; 95%CI: 51.4, 53.0) consumed less than the recommended daily amounts of fruit/vegetable and had high salt intake (54%; 95%CI: 53.3, 54.8). Physical inactivity was estimated at 39.7% (95%CI: 38.9, 40.5). A minority (16.7%; 95%CI: 16.1, 17.3) had low mental well-being, smoked (8.9%; 95%CI: 8.4, 9.3), and drank alcohol (13.4%; 95%CI: 12.8, 13.9). Country and body mass index had a significant correlation with many health-risk behaviors and mental well-being. The research provided important baseline data for guidance and for the monitoring of health outcomes among ASEAN university students and concludes that healthy diet, physical activity, and mental well-being should be key priority health areas for promotion among university students.

Prediction Modeling of Mental Well-Being Using Health Behavior Data of College Students.

Background: Since the onset of the COVID-19 pandemic in early 2020, the importance of timely and effective assessment of mental well-being has increased dramatically. Due to heightened risks for developing mental illness, this trend is likely to continue during the post-pandemic period. Machine learning (ML) algorithms and artificial intelligence (AI) techniques can be harnessed for early detection, prognostication and prediction of negative psychological well-being states. Objective: Studies using machine learning classification of mental well-being are scarce in Asian populations. This investigation aims to develop reliable machine learning classifiers based on health behavior indicators applicable to university students in South-East Asia. Methods: Using data from a large, multi-site cross-sectional survey, this research work models mental well-being and reports on the performance of various machine learning algorithms, such as generalized linear models, k-nearest neighbor, naïve-Bayes, neural networks, random forest, recursive partitioning, bagging, and boosting. Prediction models were evaluated using various metrics such as accuracy, error rate, kappa, sensitivity, specificity, Area Under the recursive operating characteristic Curve (AUC), and Gini Index. Results: Random forest and adaptive boosting algorithms achieved the highest accuracy of identifying negative mental well-being traits. The top five most salient features associated with predicting poor mental well-being include body mass index, number of sports activities per week, grade point average (GPA), sedentary hours, and age. Conclusions: Based on the reported results, several specific recommendations and suggested future work are discussed. These findings may be useful to provide cost-effective support and modernize mental well-being assessment and monitoring at the individual and university level.

How to Make Physical Activity Promotion Work in Thai Schools: Perspectives of Multiple Stakeholders.

BACKGROUND: This study aimed to determine current practice in physical activity (PA) promotion in Thai schools, explore barriers and facilitators to PA promotion within the school setting, and identify strategies to support schools' future practice. METHODS: A qualitative study design was applied comprising document analysis, focus groups, in-depth interviews, and onsite observations. The focus groups and in-depth interviews were conducted with 144 informants, purposively recruited through 24 schools in 4 regions across Thailand. Inductive content analysis was used. RESULTS: Most schools were promoting PA in the absence of written policies, and without an accurate understanding of PA. Nonalignment of school performance indicators and policies, concerns about children's academic performance, and lack of budget were raised as barriers to PA promotion, whereas strong partnerships with multiple local stakeholders facilitated school-based PA promotion. Mandated government PA policies and more information support were suggested as strategies to enhance schools' future practices. CONCLUSIONS: For PA promotion to be successful in the school setting, significant challenges will need to be addressed. Results from this study help the government and concerned stakeholders to better understand the situation at the school level, and further strive for achieving the target PA levels specified in the National PA Plan.

School policies and practices associated with Thai children's overall and domain specific physical activity.

School has a significant role in providing opportunities for children to engage in physical activity (PA) through policies and practices. This study aimed to identify the prevalence of school policies and practices related to physical activity (PA) and their association with Thai students' overall and domain specific PA. This cross-sectional analysis included 5,830 students aged 6-17 years from 136 schools recruited though a multi-stage stratified cluster sampling across Thailand. Student's PA data were assessed using a student survey and school data were collected by a principal survey. Associations between students' PA and school variables were examined using logistic regressions. Despite a high prevalence of Thai schools reporting many policies and practices promoting PA in different areas, students reported low levels of PA. None of the school PA policies and practices was associated with students' overall and domain specific activities, with active transport as the one exception. When schools had an active transport policy, students were 40% (OR = 1.40, p = 0.01) more likely to travel actively to/from school. The identified positive relationship between school active transport policy and students' active travel behavior suggests a potential wider adoption of the policy promoting school active transport aiming to increase student's PA levels among all Thai schools. Intervention studies are necessary to confirm this finding. Our study also reflected that, for greater levels of children's school-based PA, strategies to translate the existing school PA policies into effective implementation should be an emphasis for Thai schools.

"Are Thai children and youth sufficiently active? prevalence and correlates of physical activity from a nationally representative cross-sectional study".

BACKGROUND: Children and youth gain multiple health benefits from regular participation in physical activity (PA). However, in Thailand there is limited national data on children and youth's PA behaviors and recent reports suggest that Thai children and youth have low levels of PA. Furthermore, there is almost no data on the factors associated with inactivity to support the development of a Thai National PA Plan. The purpose of this paper is to investigate Thai children and youth's participation in PA and its correlates across sociodemographic characteristics and different PA domains. METHODS: This study applied a cross-sectional study design with a multi-stage stratified cluster sampling. A national representative sample of 13,255 children and youth aged 6-17 years were used for data analysis. A previously validated questionnaire was used to assess PA prevalence. Logistic regression was conducted to examine the relationships of socio-demographic factors, and participation in different PA domains with overall PA. RESULTS: Only 23.4% of Thai children and youth met recommended levels of PA and there were large gender and regional differences. PA levels generally declined with age, although the level observed in the 10-13 year group was slightly higher than other year groups. A majority of children and youth engaged in a large number of different activities across PA domains. Sex, age, BMI, geographical regions, organized sports, participation in sport and recreational activities were significant predictors of meeting the global PA guidelines, whereas participation in physical education, active transport, and the number of screen time activities had no association. Girls were less likely to achieve sufficient PA levels (OR = 0.49, 95%CI; 0.45-0.54, p < 0.001), as were obese children (OR = 0.78, 95%CI; 0.64-0.94, p = 0.01), children living in the West (OR = 0.47, 95%CI; 0.38-0.59, p < 0.001), and those who did no participation in organized sports and sport/exercise activities, or minimal participation (1-2 activities) in recreational activities (OR = 0.79, 95%CI; 0.68-0.90, p < 0.001). CONCLUSIONS: The prevalence estimate of meeting the recommended guideline of sufficient PA in Thai children and youth is low, despite the high levels of engagement in a large number of PA. The results indicate that policy and interventions aimed at increasing PA are needed with special attention required to address specific groups less likely to meet the PA guideline. Strategies to promote a large volume of participation in all possible types of PA as part of Thai children and youth's daily life should be considered.

Results From Thailand's 2016 Report Card on Physical Activity for Children and Youth.

BACKGROUND: Physical activity (PA) is recognized as one of the core modifiable risk factors of noncommunicable diseases. However, little is known about PA in the Thai population, particularly in children. The report card (RC) project provided Thailand with an opportunity to assess PA behaviors in children. This paper summarizes the methodology, grading process, and the final grades of the Thai RC. METHODS: A school-based survey was conducted to collect data from a nationally representative sample of children aged 6 to 17 years. Survey results provided the primary source for the RC. Nine indicators were graded using the Global Matrix 2.0 framework. Grading was undertaken by a national committee comprising experts from key stakeholders. RESULTS: Grades ranged from F to B. Overall PA and Sedentary Behaviors both received the grade D-. Organized Sport Participation scored a C. Active Play scored the grade F. Active Transport and support from Family and Peers were both graded B. School, Community, and Government indicators were scored C. CONCLUSIONS: In Thai children, participation in PA and active play is very low; conversely, sedentary behaviors are high. These first data on patterns of activity for the Thailand RC will serve to guide national actions and advocacy aimed at increasing PA in children.