Background In order to implement running to promote physical activity, it is essential to quantify the extent to which running improves health. Objective The aim was to summarise the literature on the effects of endurance running on biomedical indices of health in physically inactive adults. Data Sources Electronic searches were conducted in October 2014 on PubMed, Embase, CINAHL, SPORTDiscus, PEDro, the Cochrane Library and LILACS, with no limits of date and language of publication. Study Selection Randomised controlled trials (with a minimum of 8 weeks of running training) that included physically inactive but healthy adults (18–65 years) were selected. The studies needed to compare intervention (i.e. endurance running) and control (i.e. no intervention) groups. Study Appraisal and Synthesis Methods Two authors evaluated study eligibility, extracted data, and assessed risk of bias; a third author resolved any uncertainties. Random-effects meta-analyses were performed to summarise the estimates for length of training and sex. A dose-response analysis was performed with random-effects meta-regression in order to investigate the relationship between running characteristics and effect sizes. Results After screening 22,380 records, 49 articles were included, of which 35 were used to combine data on ten biomedical indices of health. On average the running programs were composed of 3.7 ± 0.9 sessions/week, 2.3 ± 1.0 h/week, 14.4 ± 5.4 km/week, at 60–90 % of the maximum heart rate, and lasted 21.5 ± 16.8 weeks. After 1 year of training, running was effective in reducing body mass by 3.3 kg [95 % confidence interval (CI) 4.1–2.5], body fat by 2.7 % (95 % CI 5.1–0.2), resting heart rate by 6.7 min⁻¹ (95 % CI 10.3–3.0) and triglycerides by 16.9 mg dl⁻¹ (95 % CI 28.1–5.6). Also, running significantly increased maximal oxygen uptake (VO_2max) by 7.1 ml min⁻¹ kg⁻¹ (95 % CI 5.0–9.1) and high-density lipoprotein (HDL) cholesterol by 3.3 mg dl⁻¹ (95 % CI 1.2–5.4). No significant effect was found for lean body mass, body mass index, total cholesterol and low-density lipoprotein cholesterol after 1 year of training. In the dose-response analysis, larger effect sizes were found for longer length of training. Limitations It was only possible to combine the data of ten out the 161 outcome measures identified. Lack of information on training characteristics precluded a multivariate model in the dose-response analysis. Conclusions Endurance running was effective in providing substantial beneficial effects on body mass, body fat, resting heart rate, VO_2max, triglycerides and HDL cholesterol in physically inactive adults. The longer the length of training, the larger the achieved health benefits. Clinicians and health authorities can use this information to advise individuals to run, and to support policies towards investing in running programs.

Is Kinesio Taping more effective than a sham taping/placebo, no treatment or other interventions in people with musculoskeletal conditions? Is the addition of Kinesio Taping to other interventions more effective than other interventions alone in people with musculoskeletal conditions? Systematic review of randomised trials. People with musculoskeletal conditions. Kinesio Taping was compared with sham taping/placebo, no treatment, exercises, manual therapy and conventional physiotherapy. Pain intensity, disability, quality of life, return to work, and global impression of recovery. Twelve randomised trials involving 495 participants were included in the review. The effectiveness of the Kinesio Taping was tested in participants with: shoulder pain in two trials; knee pain in three trials; chronic low back pain in two trials; neck pain in three trials; plantar fasciitis in one trial; and multiple musculoskeletal conditions in one trial. The methodological quality of eligible trials was moderate, with a mean of 6.1 points on the 10-point PEDro Scale score. Overall, Kinesio Taping was no better than sham taping/placebo and active comparison groups. In all comparisons where Kinesio Taping was better than an active or a sham control group, the effect sizes were small and probably not clinically significant or the trials were of low quality. This review provides the most updated evidence on the effectiveness of the Kinesio Taping for musculoskeletal conditions. The current evidence does not support the use of this intervention in these clinical populations. PROSPERO registration: CRD42012003436.

Governments have restricted public life during the COVID-19 pandemic, inter alia closing sports facilities and gyms. As regular exercise is essential for health, this study examined the effect of pandemic-related confinements on physical activity (PA) levels. A multinational survey was performed in 14 countries. Times spent in moderate-to-vigorous physical activity (MVPA) as well as in vigorous physical activity only (VPA) were assessed using the Nordic Physical Activity Questionnaire (short form). Data were obtained for leisure and occupational PA pre- and during restrictions. Compliance with PA guidelines was calculated based on the recommendations of the World Health Organization (WHO). In total, n = 13,503 respondents (39 ± 15 years, 59% females) were surveyed. Compared to pre-restrictions, overall self-reported PA declined by 41% (MVPA) and 42.2% (VPA). Reductions were higher for occupational vs. leisure time, young and old vs. middle-aged persons, previously more active vs. less active individuals, but similar between men and women. Compared to pre-pandemic, compliance with WHO guidelines decreased from 80.9% (95% CI: 80.3–81.7) to 62.5% (95% CI: 61.6–63.3). Results suggest PA levels have substantially decreased globally during the COVID-19 pandemic. Key stakeholders should consider strategies to mitigate loss in PA in order to preserve health during the pandemic.

Researching a topic and generating an academic paper is a nuanced skill. It can take months or years to produce and publish one, if it is ever published at all. What if there were a way to make this happen instantly? Artificial intelligence (AI) may hold a flame to quickly analyse a research topic and generate an academic paper. There are many forms of AI; this editorial discusses natural language model-based AI, such as ChatGPT, and their potential ability to generate academic papers.