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Background: Combination HIV prevention approaches that include both biomedical and non-biomedical interventions often hold greater promise to improve health outcomes and reduce the risk of HIV transmission. Objectives: Evaluate the relative properties of four leading candidate trial designs - 'single-factor', 'multiarm', 'all-in-one', and 'factorial' designs - for assessing individual and/or combination prevention intervention approaches. Methods: Monte-Carlo simulations are conducted, assuming a putative combination approach could choose its components from two candidate biomedical interventions, i.e. Treatment-as-Prevention (TasP) and Preexposure Prophylaxis (PrEP), and three candidate behavioral interventions, i.e. linkage-to-care, counseling, and use of condoms. Various scenarios for individual components' effect sizes, their possible interaction, and the sample size based on real clinical studies are considered. Results: The all-in-one and factorial designs used to assess a combination approach and the multi-arm design used to assess multiple individual components are consistently more powerful than single-factor designs. The all-in-one design is powerful when the individual components are effective without negative interaction, while the factorial design is more consistently powerful across a broad array of settings. Conclusions: The multi-arm design is useful for evaluating single factor regimens, while the all-in-one and factorial designs are sensitive in assessing the overall efficacy when there is interest in combining individual component regimens anticipated to have complementary mechanisms. The factorial design is a preferred approach when assessing combination regimens due to its favorable power properties and since it is the only design providing direct insights about the contribution of individual components to the combination approach's overall efficacy and about potential interactions. [ABSTRACT FROM AUTHOR]

To investigate musculoskeletal pain patterns in the upper body according to smartphone usage posture. A cross-sectional online survey using google foam. The questionnaire consisted of 4 sections with 84 questions: 1) basic information on the participant's characteristics and smartphones, 2) smartphone use posture (whole body positions, neck flexion degree, and hand-held posture), 3) the smartphone addiction scale, and 4) characteristics of musculoskeletal pain. No specific research setting is required. 237 individuals who have used smartphones regularly for more than 5 years participated in this study from China and Korea. Not applicable. The musculoskeletal pain and discomfort intensity was assessed using VAS and the Students Specific Cornell Musculoskeletal Discomfort Questionnaires (SS-CMDQ) & Cornell Hand Discomfort Questionnaires (CMDQ). Prone position users reported upper arm pain more frequently compared to other positions. People who use a smartphone on the side-lying and prone reported a higher level of Low back pain compared to sitting position. Pain score in the shoulder area was highest in the most flexed neck posture (p< 0.05), The frequency of hand pain was in the order of wrist (21.7%), 4-5rh fingers (20.7%), 2-3rd fingers (18.2%), thumb (16.9%), and hyper thenar area (15%). The most painful hand regions were the wrist and thumb. Both pain frequency and intensity were the lowest in the people who held smartphones with two hands horizontally. Holding the phone in one hand with pinky support was associated with the most frequent and severe pain in all hand areas, especially in 4-5rh fingers. There are differences in the musculoskeletal pain pattern of the upper body according to the smartphone posture. Educating and promoting a good smartphone using posture is necessary to prevent musculoskeletal pain. Further experimental studies on individuals with smartphone-related musculoskeletal symptoms are required. No conflict of interest. [ABSTRACT FROM AUTHOR]

To indirectly estimate the lower extremity strength, we developed a camera based VR cycling game. Because, strength is the most important element in physical rehabilitation, however, direct measure of strength is not possible when developing VR based rehabilitation contents using motion capture camera. Therefore, we studied the correlation between VR cycling speed and the peak knee torque measured using a Biodex isokinetic dynamometer to see if the maximum pedaling speed during VR cycling can indirectly represent lower limb muscle strength. A cross sectional correlational study. The subjects pedaled at a maximum speed for 15 seconds in VR environment. VR speedometer is programmed using the Unity engine, which counts number of revolutions whenever a trigger collider on the right ankle touches the trigger collider placed in the path of the right foot during cycling. Then the number of revolution acquired in 15 seconds was converted to revolutions per minute (RPM). Peak flexion/extension torques were measured using an isokinetic dynamometer to confirm the lower extremity muscle strength. All measurements were obtained at the Experimental motor behavior laboratory in the University. Thirty healthy adults without known medical, physical, and cognitive conditions that would interfere with the experimental procedure. Not applicable. Main outcome measures were the pedaling speed (RPM) obtained by VR speedometer and the peak knee flexion/extension torque measured using isokinetic dynamometer. The results of the Pearson correlation analysis revealed a significant moderate positive correlation between the pedaling speed of the VR cycling game and the peak torque of knee flexion (r=0.639) and extension (r=0.598). This study suggests the potential of measuring the maximum pedaling speed using motion capture camera in a VR environment as an indirect assessment of muscle strength. However, technological improvements must be followed to obtain more accurate estimation of muscle strength from the VR cycling test. No conflict of interest existing. [ABSTRACT FROM AUTHOR]