STUDY DESIGN AND SETTINGS: The Online Randomized Controlled Trials of Health Information Database was used as the sampling frame to identify a subset of self-recruited online trials of self-management interventions. The authors cataloged what these online trials were assessing, appraised study quality, extracted information on how trials were run, and assessed the potential for bias. We searched out how public and patient participation was integrated into online trial design and how this was reported. We recorded patterns of use for registration, reporting, settings, informed consent, public involvement, supplementary materials, and dissemination planning.
RESULTS: The sample included 41 online trials published from 2002 to 2015. The barriers to replicability and risk of bias in online trials included inadequate reporting of blinding in 28/41 (68%) studies; high attrition rates with incomplete or unreported data in 30/41 (73%) of trials; and 26/41 (63%) of studies were at high risk for selection bias as trial registrations were unreported. The methods for (23/41, 56%) trials contained insufficient information to replicate the trial, 19/41 did not report piloting the intervention. Only 2/41 studies were cross-platform compatible. Public involvement was most common for advisory roles (n = 9, 22%), and in the design, usability testing, and piloting of user materials (n = 9, 22%).
CONCLUSION: This study catalogs the state of online trials of self-management in the early 21st century and provides insights for online trials development as early as the protocol planning stage. Reporting of trials was generally poor and, in addition to recommending that authors report their trials in accordance with CONSORT guidelines, we make recommendations for researchers writing protocols, reporting on and evaluating online trials. The research highlights considerable room for improvement in trial registration, reporting of methods, data management plans, and public and patient involvement in self-recruited online trials of self-management interventions.
Methods: In this cross-sectional survey study, 285 Malaysian elite athletes (170 males, 115 females) aged 15-44 years (M = 18.89, SD = 4.49) completed measures of various PSTs and mental toughness. Latent profile analysis was employed to determine the type and number of profiles that best represent athletes' reports of their use of PSTs in practice and competition settings, and examine differences between these classes in terms of self-reported mental toughness.
Results: Our results revealed three profiles (low, moderate, high use) in both practice and competition settings that were distinguished primarily according to quantitative differences in the absolute levels of reported use across most of the PSTs assessed in practice and competition settings, which in turn, were differentially related with mental toughness. Specifically, higher use of PSTs was associated with higher levels of mental toughness.
Conclusion: This study provides one of the first analyses of the different configurations of athletes' use of PSTs that typify unique subgroups of performers. An important next step is to examine the longitudinal (in) stability of such classes and therefore provide insight into the temporal dynamics of different configurations of athletes' use of PSTs.
OBJECTIVE: This study aims to assess physical activity levels among Malaysian adolescents and investigate the association between physical activity levels and body composition such as body mass index (BMI), waist circumference (WC) and percentage of body fat.
SUBJECTS AND METHODS: 1361 school-going 13 year old multi-ethnic adolescents from population representative samples in Malaysia were involved in our study. Self-reported physical activity levels were assessed using the validated Malay version of the Physical Activity Questionnaire for Older Children (PAQ-C). Height, weight, body fat composition and waist circumference (WC) were measured. Data collection period was from March to May 2012.
RESULTS: 10.8% of the males and 7.4% of the females were obese according to the International Obesity Task Force standards. A majority of the adolescents (63.9%) were physically inactive. There is a weak but significant correlation between physical activity scores and the indicators of obesity. The adjusted coefficient for body fatness was relatively more closely correlated to physical activity scores followed by waist circumference and lastly BMI.
CONCLUSION: This study demonstrates that high physical activity scores were associated with the decreased precursor risk factors of obesity.