Primary dysmenorrhea (PD) refers to painful cramps before and/or during menstruation. There is a need for emphasis on alternative methods of conservative treatment, so as to reduce the dependence on drugs for alleviating the symptoms. The aim was to find out the effectiveness of some physiotherapy techniques in the treatment of PD. A systematic review and meta-analysis was conducted according to PRISMA standards. The descriptors were “dysmenorrhea”, “physical the-rapy”, “physiotherapy”, and “manual therapy”. The search was performed in five databases: Scopus, PubMed, PEDro, Web of Science, and Medline, in February 2021. The inclusion criteria were randomized controlled trials over the last six years. Articles not related to the treatment of PD or using pharmacology as the main treatment were excluded. Nine articles met the objectives and criteria, with a total of 692 participants. The most used scale to measure pain was the VAS (visual analogue scale). The main techniques were isometric exercises, massage therapy, yoga, electrotherapy, connective tissue manipulation, stretching, kinesio tape, progressive relaxation exercises and aerobic dance. Meta-analysis shows benefits of physiotherapy treatment for pain relief compared with no intervention or placebo (MD: −1.13, 95% CI: −1.61 to −0.64, I²: 88%). The current low-quality evidence suggests that physiotherapy may provide a clinically significant reduction in menstrual pain intensity. Given the overall health benefits of physiotherapy and the low risk of side effects reported, women may consider using it, either alone or in conjunction with other therapeutic modalities.

Students often experience the university period as a very stressful time. The teacher is a key figure who can cushion this stressful experience for the student. This study therefore aims to analyse the influence of teachers from the Self-Determination Theory perspective on academic stress, motivation, critical thinking, metacognitive strategies and academic performance in university students. The study involved 2456 university students with an average age of 22.51 years. A structural equation model was created to analyse the causal relationships between the variables. The results showed that the psychological controlling of the teacher positively predicted academic stress while autonomy support negatively predicted academic stress. Academic stress negatively predicted motivation, metacognitive strategies, critical thinking and academic performance. Academic motivation positively predicted metacognitive strategies and critical thinking. Finally, metacognitive strategies and critical thinking positively predicted academic performance. These results highlight the importance of the role that the teacher adopts during classes and the protective factor of academic motivation in the presence of stress.

One of the most useful indicators of relative dispersion is the coefficient of variation. The characteristics of the coefficient of variation have contributed to its widespread use in most scientific and academic disciplines, with real life applications. The traditional estimators of the coefficient of variation are based on conventional moments; therefore, these are highly affected by the presence of extreme values. In this article, we develop some novel calibration-based coefficient of variation estimators for the study variable under double stratified random sampling (DSRS) using the robust features of linear (L and TL) moments, which offer appropriate coefficient of variation estimates. To evaluate the usefulness of the proposed estimators, a simulation study is performed by using three populations out of which one is based on the COVID-19 pandemic data set and the other two are based on apple fruit data sets. The relative efficiency of the proposed estimators with respect to the existing estimators has been calculated. The superiority of the suggested estimators over the existing estimators are clearly validated by using the real data sets.

Koyuncu and Kadilar kk.2009 introduced a family of estimators under simple random sampling. In this article; we adapt these estimators for ranked set sampling. Further, we suggest a regression-type estimator of population mean utilizing available supplementary information under ranked set sampling scheme alongside the sensitivity issue when the variate of interest is sensitive. The bias and mean square error of the suggested estimator is determined theoretically for both situations. A simulation study has been done to demonstrate the percentage relative efficiency of proposed estimators over the adapted and reviewed estimators.