ABSTRACT
In recent years, health development in Indonesia is relatively low, and the importance of sport in implementing public policy has been observed. One of the problems is the lack of physical activities to improve physical fitness. It has been reported that only 17% of the Indonesian population has relatively good physical fitness (Fadhlurrohman M, Purnomo E, n.d.). Social development strategies are implemented at various levels. On a large scale, this means that these strategies involve governments, international organizations, and, on a smaller scale, local communities. The initiatives undertaken at the local level are important because their effectiveness is usually higher than national programs (Clark et al., 2012). Another reason supporting this research is that mobile health technologies, especially smartphones (i.e., broadband-enabled phones with the capacity to download apps), are rapidly growing (Knight et al., 2015). This research aimed to improve the efficiency of measuring physical fitness based on the software application technology on Android. Research methods: This research used a quantitative approach. The developed application has four main features: quotes, articles, videos, and search for sports practitioners. This research uses the research and development ADDIE (analysis, design, development or production, implementation or delivery, and evaluation) model as the research method (Kaye Shelton, Dallas Baptist University & George Saltsman, Abilene Christian University, 2007). This approach is implemented in five stages: (1) analysis, (2) application design, (3) application development, (4) implementation, and (5) evaluation. The sample consisted of 30 participants. A total of 50% of the participants were sports students from the State University of Jakarta, and 50% were from the Local Youth Organization, Ujung Menteng Village, Bekasi;the participants were 18-39 years old. Descriptive analysis was performed using the t-test. The data were collected through observation with a total of 45 questions and interviews. The result is the total number of correct answers on the pre-test 914 (68%) and post-test 1179 (87.3%). Result. There is an effect of using the application, as evidenced by the significant difference between the pre-test and post-test values. The objective of this research was to create an application software product to increase knowledge and physical fitness. Conclusions. The developed software was validated by a review team consisting of a physiologist, physical fitness expert, and digital experts from State University of Jakarta. The most important motives were general health orientation, life meaning and self-esteem, which are related to health development in Indonesia.
ABSTRACT
BACKGROUND: Parallel intervention studies involving volunteers usually require a procedure to allocate the subjects to study-arms. Statistical models to evaluate the different outcomes of the study-arms will include study-arm as a factor along with any covariate that might affect the results. To ensure that the effects of the covariates are confounded to the least possible extent with the effects of the arms, stratified randomization can be applied. However, there is at present no clear-cut procedure when there are multiple covariates. METHODS: For parallel study designs with simultaneous enrollment of all subjects prior to intervention, we propose a D-optimal blocking procedure to allocate subjects with known values of the covariates to the study arms. We prove that the procedure minimizes the variances of the baseline differences between the arms corrected for the covariates. The procedure uses standard statistical software. RESULTS: We demonstrate the potential of the method by an application to a human parallel nutritional intervention trial with three arms and 162 healthy volunteers. The covariates were gender, age, body mass index, an initial composite health score, and a categorical indicator called first-visit group, defining groups of volunteers who visit the clinical centre on the same day (17 groups). Volunteers were allocated equally to the study-arms by the D-optimal blocking procedure. The D-efficiency of the model connecting an outcome with the study-arms and correcting for the covariates equals 99.2%. We simulated 10,000 random allocations of subjects to arms either unstratified or stratified by first-visit group. Intervals covering the middle 95% of the D-efficiencies for these allocations were [82.0, 92.0] and [93.2, 98.4], respectively. CONCLUSIONS: Allocation of volunteers to study-arms with a D-optimal blocking procedure with the values of the covariates as inputs substantially improves the efficiency of the statistical model that connects the response with the study arms and corrects for the covariates. TRIAL REGISTRATION: Dutch Trial Register NL7054 ( NTR7259 ). Registered May 15, 2018.