Validation of the 4-Item and 10-Item Uncertainty Stress Scale in a Community-Based Sample of Chinese Adults.

Purpose: The objectives of this study were to examine the psychometric properties of the Uncertainty Stress Scale (USS) and to compare the usefulness of two versions of the scale (USS-4 and USS-10) among a large community-based sample of Chinese adults. Participants and Methods: The Uncertainty Stress Scale was validated in 904 community residents (mean age: 32.71 ± 10.99; male: 41.7%) through an online survey conducted in February 2020. Psychometric properties of reliability (Cronbach's alpha), construct validity (confirmatory factor analysis), and criterion validity (correlation and ROC curve analyses) were evaluated using established benchmarks. To validate the USS, we used the Chinese version of the Perceived Stress Scale (CPSS). In addition, sensitivity, specificity, and suitable cutoff values of the two versions of USS were determined. Results: Both versions of the USS had high internal consistency (USS-10: 0.941; USS-4: 0.851). Confirmatory factor analyses supported a one-factor structure for both measures. Both USS-4 and USS-10 scores were significantly positively correlated with CPSS scores, indicating acceptable criterion validity. Conclusion: The findings of the current study confirmed that the psychometric properties of two Chinese versions of USS are acceptable. Furthermore, the 4-item USS was as effective as the 10-item USS for the measurement of uncertainty stress in our community-based sample of Chinese adults suggesting that the USS-4 is a time-efficient alternative to the USS-10 which can be used when the circumstances require a time-efficient instrument (eg, in epidemiological studies with a large test battery).

Associations between sedentary behavior and negative emotions in adolescents during home confinement: Mediating role of social support and sleep quality

Background Prolonged periods of sedentary behaviour, for instance, engendered by home confinement in Shenzhen city, has led to negative mental health consequences, especially in adolescents. Previous research suggests, in general, that sedentary behavior can increase negative emotions. However, the specific mechanism driving the relationship between sedentary behavior and negative emotions is still relatively unclear. Social support and sleep quality might partly explain the effect of sedentary behavior on negative emotions. Thus, the current study aimed to examine the associations between sedentary behavior and negative emotions, and to investigate if social support and sleep quality mediate such a relationship. Method During home confinement due to the COVID-19 Omicron variant outbreak, 1179 middle and high school students in Shenzhen were invited to voluntarily complete an e-questionnaire, including the 21-item Depression Anxiety Stress Scale (DASS-21), the short form of the International Physical Activity Questionnaire (IPAQ-SF), the Social Support Rating Scale (SSRS) and the Pittsburgh Sleep Quality Index (PSQI). Data from 1065 participants were included in the analysis. Results We observed significant sex-related and demografic-related differences in emotional (e.g., anxiety, stress and social support) and other outcome variables (e.g., sitting duration and PSQI score). Furthermore, sedentary behavior, social support, and sleep quality were associated with negative emotions (p < .01), even after controlling for sex, age, only-child case, body mass index, and metabolic equivalent level. In addition, social support and sleep quality partially mediated the association between sedentary behavior and negative emotions. Conclusion The findings of the current study suggest that social support and sleep quality partially mediate the relationship between sedentary behavior and negative emotions in middle and high school students during home confinement in Shenzhen city.

Going digital - a commentary on the terminology used at the intersection of physical activity and digital health.

In recent years digital technologies have become a major means for providing health-related services and this trend was strongly reinforced by the current Coronavirus disease 2019 (COVID-19) pandemic. As it is well-known that regular physical activity has positive effects on individual physical and mental health and thus is an important prerequisite for healthy aging, digital technologies are also increasingly used to promote unstructured and structured forms of physical activity. However, in the course of this development, several terms (e.g., Digital Health, Electronic Health, Mobile Health, Telehealth, Telemedicine, and Telerehabilitation) have been introduced to refer to the application of digital technologies to provide health-related services such as physical interventions. Unfortunately, the above-mentioned terms are often used in several different ways, but also relatively interchangeably. Given that ambiguous terminology is a major source of difficulty in scientific communication which can impede the progress of theoretical and empirical research, this article aims to make the reader aware of the subtle differences between the relevant terms which are applied at the intersection of physical activity and Digital Health and to provide state-of-art definitions for them.

Four Weeks of Detraining Induced by COVID-19 Reverse Cardiac Improvements from Eight Weeks of Fitness-Dance Training in Older Adults with Mild Cognitive Impairment.

Physical training is considered as a low-cost intervention to generate cardioprotective benefits and to promote physical and mental health, while reducing the severity of acute respiratory infection symptoms in older adults. However, lockdown measures during COVID-19 have limited people's opportunity to exercise regularly. The aim of this study was to investigate the effect of eight weeks of Fitness and Dance training, followed by four weeks of COVID-19-induced detraining, on cardiac adaptations and physical performance indicators in older adults with mild cognitive impairment (MCI). Twelve older adults (6 males and 6 females) with MCI (age, 73 ± 4.4 y; body mass, 75.3 ± 6.4 kg; height, 172 ± 8 cm; MMSE score: 24-27) participated in eight weeks of a combined Fitness-Dance training intervention (two sessions/week) followed by four weeks of training cessation induced by COVID-19 lockdowns. Wireless Polar Team Pro and Polar heart rate sensors (H10) were used to monitor covered distance, speed, heart rate (HR min, avg and max), time in HR zone 1 to 5, strenuousness (load score), beat-to-beat interval (max RR and avg RR) and heart rate variability (HRV-RMSSD). One-way ANOVA was used to analyze the data of the three test sessions (T1: first training session, T2: last training session of the eight-week training program, and T3: first training session after the four-week training cessation). Statistical analysis showed that eight weeks of combined Fitness-Dance training induced beneficial cardiac adaptations by decreasing HR (HR min, HR avg and HR max) with p < 0.001, ES = 0.5-0.6 and Δ = -7 to-9 bpm, and increasing HRV related responses (max and avg RR and RMSSD), with p < 0.01 and ES = 0.4. Consequently, participants spent more time in comfortable HR zones (e.g., p < 0.0005; ES = 0.7; Δ = 25% for HR zone 1) and showed reduced strenuousness (p = 0.02, Δ = -15% for load score), despite the higher covered total distance and average speed (p < 0.01; ES = 0.4). However, these changes were reversed after only four weeks of COVID-19 induced detraining, with values of all parameters returning to their baseline levels. In conclusion, eight weeks of combined Fitness-Dance training seems to be an efficient strategy to promote cardioprotective benefits in older adults with MCI. Importantly, to maintain these health benefits, training has to be continued and detraining periods should be reduced. During a pandemic, home-based exercise programs may provide an effective and efficient alternative of physical training.