METHOD: We conducted a cross-sectional study in which we used purposive sampling and a self-administered questionnaire. Based on the literature review, experts' input and in-depth interviews, new items were generated for SS-Bloat scale. Content validity was assessed by experts and pre-tested with 30 individuals with AB. Construct validity was determined based on exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Reliability was determined based on Cronbach's alpha and composite reliability (CR).
RESULTS: During the development stage, eight items were generated for SS-Bloat scale and remained the same after content validity and pre-testing. A total of 152 participants with a mean age of 31.27 years old (68.3% female, 32.7% male) completed the questionnaire. Based on the EFA, three problematic items were removed. The total variance explained was 35.6% with acceptable reliability (α = 0.66). The model was then tested using CFA. The initial model did not fit the data well. After several model re-specifications, the final measurement model of SS-Bloat scale fit the data well with acceptable fit indices (comparative fit index [CFI] = 0.994 and Tucker-Lewis index [TLI] = 0.984). The CR was satisfactory with value of 0.84.
CONCLUSION: SS-Bloat scale was deemed valid and reliable for assessing the level of social support among AB patients. The questionnaire can be useful for both research studies and clinical purposes, as it is easy to use.
METHODS: A total of 1,025 Chinese university athletes (65% male, mean age 20 ± 1.54 years) were included in this study. Confirmatory factor analysis (CFA) and multi-group CFA (MGCFA) were conducted using Mplus 8.0 to evaluate the factorial structure and assess measurement invariance across sports levels.
RESULTS: Both the three-factor and second-order models demonstrated a good fit for the Chinese adaptation of the Sport MHC-SF. Chi-square values were 262.704 (74) and 262.705 (74), respectively, with a comparative fit index (CFI) of 0.968, a Tucker-Lewis index (TLI) of 0.961, a standardized root mean square residual (SRMR) of 0.027, and a root mean square error of approximation (RMSEA) of 0.050 (90% CI: 0.043-0.056). Measurement invariance across ranked and non-ranked athletes was confirmed, with minimal changes in fit indices (ΔCFI ≤ 0.01, ΔTLI ≤ 0.01, ΔRMSEA ≤ 0.015) from configural to strict invariance.
CONCLUSION: The Chinese adaptation of the Sport MHC-SF scale has strong construct validity, reliability, and measurement invariance, making it a reliable tool for future research on the well-being of Chinese athletes. This study fills a critical gap in cross-cultural validation, offering a foundation for future research and practical applications in sports psychology among Chinese athletes.
METHOD: A cross-sectional survey was conducted among university undergraduate students in Nigeria. The study consisted of 300 participants in the EFA (males 55.7%, females 44.3%) and 430 participants in the CFA (males 54.0%, females 46.0%). Participants were selected using a convenience sampling approach to assess their perceptions regarding SDH. Content Validity Index (CVI), Face Validity Index (FVI), Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Composite Reliability (CR), Average Variance Extracted (AVE), Cronbach's alpha, and Intraclass Correlation Coefficient (ICC) were computed to determine the psychometric properties of the newly developed SDH scale.
RESULTS: In the EFA, two factors were extracted (structural determinants of SDH and intermediary determinants of SDH), with all 20 items retained. The total variance explained by the EFA model was 61.8%, and the factor correlation was 0.178. The Cronbach's alpha values of the two factors were 0.917 and 0.939. In the CFA, the initial model did not fit the data well based on fit indices. After several re-specification of the model, the final re-specified measurement model demonstrated adequate fit factor structure of the SDH scale with two factors and 20 items (CFI = 0.943, TLI = 0.930, SRMR = 0.056, RMSEA = 0.053, RMSEA p-value = 0.220). The CR was 0.797 for structural determinants of SDH and 0.794 for intermediary determinants of SDH. The ICC was 0.938 for structural determinants of SDH and 0.941 for intermediary determinants of SDH.
CONCLUSION: The findings indicate that the SDH scale has adequate psychometric properties and can be used to assess the perceived level of SDH. We recommended that this tool be tested in other populations with diverse age groups and other demographic characteristics.
METHODS: A cross-sectional survey was conducted with 726 university students (mean age = 19.2 years, SD = 0.92). The participants completed the Physical Activity Rating Scale-3, the Self-Control Scale, and the Connor-Davidson Resilience Scale. Descriptive statistics, correlation analyses, regression analyses, and mediation analysis were performed using SPSS 28.0 and PROCESS 4.0.
RESULTS: Significant differences in self-control (F = 29.67, P < 0.001) and psychological resilience (F = 21.95, P < 0.001) were observed across physical activity levels. Physical activity positively predicted self-control (β = 0.269, P < 0.001) and psychological resilience (β = 0.251, P < 0.001). Self-control was a significant predictor of psychological resilience (β = 0.511, P < 0.001). Mediation analysis indicated that self-control partially mediated the relationship between physical activity and psychological resilience, accounting for 51.46% of the total effect.
CONCLUSION: Physical activity enhances psychological resilience directly and indirectly through the improvement of self-control. These findings highlight the potential value of promoting regular physical activity as an effective strategy for strengthening psychological resilience and improving mental well-being among university students.
METHODS: In this research study, the participants were three groups of Malay adolescents aged 13 years old-15 years old: i) adolescents with S-SLI with music training, ii) adolescents with S-SLI without music training and iii) typically developing adolescents. Before and after music training, the participants were given a sentence-picture matching task. Accuracy measures and reaction times were captured using E-Prime 2.0.
RESULTS: The results indicated that with music training, the accuracy and reaction time associated with which object questions among the two SLI groups were significantly higher and lower, respectively.
CONCLUSION: The implications of using rhythmic music training in enhancing syntactic structure processing are also discussed.
METHODS: The study adopted a cross-sectional design with purposive sampling. Participants who consented and met the criteria for bloating based on the Rome IV classification completed designated questionnaires. Independent variables comprised health beliefs, intentions, health-promoting behaviors, social support, depression, and anxiety, while dependent variables included bloating severity (general and within 24 h) and QoL. Structural Equation Modeling (SEM) was conducted utilizing Mplus 8.0 to analyze the relationships between these factors.
RESULTS: A total of 323 participants, with a mean age of 27.69 years (SD = 11.50), predominantly females (64.7%), volunteered to participate in the study. The final SEM model exhibited good fit based on various indices (CFI = 0.922, SRMR = 0.064, RMSEA (95% CI) = 0.048 (0.041-0.054), p-value = 0.714), with 15 significant path relationships identified. The model explained 12.0% of the variance in severity within 24 h, 6% in general severity, and 53.8% in QoL.
CONCLUSION: The findings underscore the significant influence of health beliefs, intentions, behaviors, social support, depression, and anxiety on symptom severity and QoL in individuals experiencing abdominal bloating.
METHODS: Thirty university badminton players aged from 19 to 22 years old were randomly divided equally into two groups, where the probiotic group (PG; n = 15) received a drink that contained Lactobacillus casei Shirota (3 × 1010 CFU) and placebo group (CG; n = 15) a placebo drink for six weeks. Anxiety, stress and mood levels were determined using the CSAI-2R, PSS and BRUMS questionnaires, respectively. Fitness levels were measured using by subjecting the players to 20-m shuttle runs (aerobic capacity), handgrips (muscular strength), vertical jumps (leg power), 40-m dash (speed) and T-test (agility). The Student's t-test (p < 0.05) was used to determine the differences between PG and CG players.
RESULTS: After six weeks, the anxiety and stress levels of PG players significantly decreased by 16% (p < 0.001) and 20% (p < 0.001), respectively, but there were no significant changes detected in CG players. Supplementation of probiotics also improved aerobic capacity in PG players by 5.9% (p < 0.001) but did not influence the speed, strength, leg power and agility.
CONCLUSIONS: Probiotics supplementation showed improved aerobic capacity and relieve anxiety and stress. However, further studies need to be carried out to determine the mechanisms through which probiotic intake produces these effects.