BACKGROUND: The proper interpretation of a study\'s results requires both excellent understanding of good methodological practices and deep knowledge of prior results, aided by the availability of effect sizes.
METHODS: This review takes the form of an expository essay exploring the complex and nuanced relationships among statistical significance, clinical importance, and effect sizes.
RESULTS: Careful attention to study design and methodology will increase the likelihood of obtaining statistical significance and may enhance the ability of investigators/readers to accurately interpret results. Measures of effect size show how well the variables used in a study account for/explain the variability in the data. Studies reporting strong effects may have greater practical value/utility than studies reporting weak effects. Effect sizes need to be interpreted in context. Verbal summary characterizations of effect sizes (e.g., \"weak\", \"strong\") are fundamentally flawed and can lead to inappropriate characterization of results. Common language effect size (CLES) indicators are a relatively new approach to effect sizes that may offer a more accessible interpretation of results that can benefit providers, patients, and the public at large.
CONCLUSIONS: It is important to convey research findings in ways that are clear to both the research community and to the public. At a minimum, this requires inclusion of standard effect size data in research reports. Proper selection of measures and careful design of studies are foundational to the interpretation of a study\'s results. The ability to draw useful conclusions from a study is increased when investigators enhance the methodological quality of their work.

OBJECTIVE: Temporomandibular disorder (TMD) is the term used to describe a pathology (dysfunction and pain) in the masticatory muscles and temporomandibular joint (TMJ). There is an apparent upward trend in the publication of dental research and a need to continually improve the quality of research. Therefore, this study was conducted to analyse the use of sample size and effect size calculations in a TMD randomised controlled trial.
METHODS: The period was restricted to the full 5 years, i.e., papers published in 2019, 2020, 2021, 2022, and 2023. The filter article type-\"Randomized Controlled Trial\" was used. The studies were graded on a two-level scale: 0-1. In the case of 1, sample size (SS) and effect size (ES) were calculated.
RESULTS: In the entire study sample, SS was used in 58% of studies, while ES was used in 15% of studies.
CONCLUSIONS: Quality should improve as research increases. One factor that influences quality is the level of statistics. SS and ES calculations provide a basis for understanding the results obtained by the authors. Access to formulas, online calculators and software facilitates these analyses. High-quality trials provide a solid foundation for medical progress, fostering the development of personalized therapies that provide more precise and effective treatment and increase patients\' chances of recovery. Improving the quality of TMD research, and medical research in general, helps to increase public confidence in medical advances and raises the standard of patient care.

Background: There is limited knowledge regarding the comparative patient-reported outcomes (PROMs) and effect sizes (ESs) across orthopedic elective surgery. Methods: All patient data between January 2020 and December 2022 were collected, and treatment outcomes assessed as a PROM difference between baseline and one-year follow-up. The cohort was divided into subgroups (hand, elbow, shoulder, spine, hip, knee, and foot/ankle). The PROM ESs were calculated for each patient separately, and patients with ES > 0.5 were considered responders. Results: In total, 7695 patients were operated on. The mean ES across all patient groups was 1.81 (SD 1.41), and the largest ES was observed in shoulder patients and the smallest in hand patients. Overall, shoulder, hip, and knee patients had a larger ES compared to hand, spine, and foot/ankle patients (p < 0.0001). The proportion of positive responders ranged between 91-94% in the knee, shoulder, and hip, and 69-70% in the hand, spine, and foot/ankle subgroups. Conclusions: The ESs are generally high throughout elective orthopedic surgery. However, based on our institutional observations, shoulder, hip, and knee patients experience larger treatment effects compared to hand, spine, and foot/ankle patients, among whom there are also more non-responders. The expected treatment outcomes should be clearly communicated to patients when considering elective surgery. Because of the study limitations, the results should be approached with some caution.

UNASSIGNED: Restricted mean survival time is the expected duration of survival up to a chosen time of restriction τ. For comparison studies, the difference in restricted mean survival times between two groups provides a summary measure of the treatment effect that is free of assumptions regarding the relative shape of the two survival curves, such as proportional hazards. However, it can be difficult to judge the magnitude of the effect from a comparison of restricted means due to the truncation of observation at time τ.
UNASSIGNED: In this article, we describe additional ways of expressing the treatment effect based on restricted means that can be helpful in this regard. These include the ratio of restricted means, the ratio of life-years (or time) lost, and the average integrated difference between the survival curves, equal to the difference in restricted means divided by τ. These alternative metrics are straightforward to calculate and provide a means for scaling the effect size as an aid to interpretation. Examples from two randomized, multicenter clinical trials in prostate cancer, NRG/RTOG 0521 and NRG/RTOG 0534, with primary endpoints of overall survival and biochemical/radiological progression-free survival, respectively, are presented to illustrate the ideas.
UNASSIGNED: The four effect measures (restricted mean survival time difference, restricted mean survival time ratio, time lost ratio, and average survival rate difference) were 0.45 years, 1.05, 0.81, and 0.038 for RTOG 0521 and 1.36 years, 1.17, 0.56, and 0.12 for RTOG 0534 with τ = 12 and 11 years, respectively. Thus, for example, the 0.45-year difference in the first trial translates into a 19% reduction in time lost and a 3.8% average absolute difference between the survival curves over the 12-year horizon, a modest effect size, whereas the 1.36-year difference in the second trial corresponds to a 44% reduction in time lost and a 12% absolute survival difference, a rather large effect.
UNASSIGNED: In addition to the difference in restricted mean survival times, these alternative measures can be helpful in determining whether the magnitude of the treatment effect is clinically meaningful.

The statistical significance of a clinical trial analysis result is determined by a mathematical calculation and probability based on null hypothesis significance testing. However, statistical significance does not always align with meaningful clinical effects; thus, assigning clinical relevance to statistical significance is unreasonable. A statistical result incorporating a clinically meaningful difference is a better approach to present statistical significance. Thus, the minimal clinically important difference (MCID), which requires integrating minimum clinically relevant changes from the early stages of research design, has been introduced. As a follow-up to the previous statistical round article on P values, confidence intervals, and effect sizes, in this article, we present hands-on examples of MCID and various effect sizes and discuss the terms statistical significance and clinical relevance, including cautions regarding their use.

Background Small-group discussions (SGDs) are pivotal in medical education, facilitating the development of critical thinking, communication skills, and teamwork. However, traditional SGDs face challenges such as scalability and maintaining student engagement. This study aims to evaluate the \"Distribute, Discuss, and Develop\" (3D) method for enhancing learning outcomes in medical education. Methods A single-blinded interventional study was conducted with 125 first-year Bachelor of Medicine and Bachelor of Surgery students, who were divided into intervention and control groups through random assignment. The intervention group employed the 3D method across two thematic units: hematology and muscle nerve physiology. The study assessed learning outcomes using pre- and posttests, class-average normalized gain (\"g\"), and feedback questionnaires to capture student perceptions of interaction, communication enhancement, and session summarization. Results The intervention group showed significantly improved learning outcomes in both thematic units, with larger effect sizes (hematology: 1.55; muscle nerve physiology: 1.4) compared to the control group. The normalized gain \"g\" indicated a medium effectiveness level for the intervention group in both themes, suggesting enhanced learning. Feedback questionnaires revealed higher satisfaction levels within the intervention group regarding interaction, communication skills, and session summarization. Conclusions The 3D method addresses the challenges faced by traditional SGDs, providing a scalable and engaging approach to medical education. By fostering more effective student-centered learning, the method enhances the comprehension of complex physiological concepts and improves communication skills. The 3D method significantly improves learning outcomes, interaction, and communication skills in medical education. This innovative approach to SGDs offers a promising strategy for enhancing the educational experience in medical schools, supporting the development of more articulate and professionally competent medical graduates.

To illustrate how (standardised) effect sizes (ES) vary based on calculation method and to provide considerations for improved reporting.
Data from three trials of tanezumab in subjects with osteoarthritis were analyzed. ES of tanezumab versus comparator for WOMAC Pain (outcome) was defined as least squares difference between means (mixed model for repeated measures analysis) divided by a pooled standard deviation (SD) of outcome scores. Three approaches to computing the SD were evaluated: Baseline (the pooled SD of WOMAC Pain values at baseline [pooled across treatments]); Endpoint (the pooled SD of these values at the time primary endpoints were assessed); and Median (the median pooled SD of these values based on the pooled SDs across available timepoints). Bootstrap analyses were used to compute 95% confidence intervals (CI).
ES (95% CI) of tanezumab 2.5 mg based on Baseline, Endpoint, and Median SDs in one study were - 0.416 (- 0.796, - 0.060), - 0.195 (- 0.371, - 0.028), and - 0.196 (- 0.373, - 0.028), respectively; negative values indicate pain improvement. This pattern of ES differences (largest with Baseline SD, smallest with Endpoint SD, Median SD similar to Endpoint SD) was consistent across all studies and doses of tanezumab.
Differences in ES affect interpretation of treatment effect. Therefore, we advocate clearly reporting individual elements of ES in addition to its overall calculation. This is particularly important when ES estimates are used to determine sample sizes for clinical trials, as larger ES will lead to smaller sample sizes and potentially underpowered studies.
Clinicaltrials.gov NCT02697773, NCT02709486, and NCT02528188.

UNASSIGNED: This study tested the hypothesis that a neuroprotective combined therapy based on epidermal growth factor (EGF) and growth hormone-releasing hexapeptide (GHRP6) could be safe for acute ischemic stroke patients, admitting up to 30% of serious adverse events (SAE) with proven causality.
UNASSIGNED: A multi-centric, randomized, open-label, controlled, phase I-II clinical trial with parallel groups was conducted (July 2017 to January 2018). Patients aged 18-80 years with a computed tomography-confirmed ischemic stroke and less than 12 h from the onset of symptoms were randomly assigned to the study groups I (75 μg rEGF + 3.5 mg GHRP6 i.v., n=10), II (75 μg rEGF + 5 mg GHRP6 i.v., n=10), or III (standard care control, n=16). Combined therapy was given BID for 7 days. The primary endpoint was safety over 6 months. Secondary endpoints included neurological (NIHSS) and functional [Barthel index and modified Rankin scale (mRS)] outcomes.
UNASSIGNED: The study population had a mean age of 66 ± 11 years, with 21 men (58.3%), a baseline median NIHSS score of 9 (95% CI: 8-11), and a mean time to treatment of 7.3 ± 2.8 h. Analyses were conducted on an intention-to-treat basis. SAEs were reported in 9 of 16 (56.2%) patients in the control group, 3 of 10 (30%) patients in Group I (odds ratio (OR): 0.33; 95% CI: 0.06-1.78), and 2 of 10 (20%) patients in Group II (OR: 0.19; 95% CI: 0.03-1.22); only two events in one patient in Group I were attributed to the intervention treatment. Compliance with the study hypothesis was greater than 0.90 in each group. Patients treated with EGF + GHRP6 had a favorable neurological and functional evolution at both 90 and 180 days, as evidenced by the inferential analysis of NIHSS, Barthel, and mRS and by their moderate to strong effect size. At 6 months, proportion analysis evidenced a higher survival rate for patients treated with the combined therapy. Ancillary analysis including merged treated groups and utility-weighted mRS also showed a benefit of this combined therapy.
UNASSIGNED: EGF + GHRP6 therapy was safe. The functional benefits of treatment in this study supported a Phase III study.
UNASSIGNED: RPCEC00000214 of the Cuban Public Registry of Clinical Trials, Unique identifier: IG/CIGB-845I/IC/1601.

Neuroimaging biomarkers have shown high potential to map the disease processes in the application to neurodegenerative diseases (NDD), e.g., diffusion tensor imaging (DTI). For DTI, the implementation of a standardized scanning and analysis cascade in clinical trials has potential to be further optimized. Over the last few years, various approaches to improve DTI applications to NDD have been developed. The core issue of this review was to address considerations and limitations of DTI in NDD: we discuss suggestions for improvements of DTI applications to NDD. Based on this technical approach, a set of recommendations was proposed for a standardized DTI scan protocol and an analysis cascade of DTI data pre-and postprocessing and statistical analysis. In summary, considering advantages and limitations of the DTI in NDD we suggest improvements for a standardized framework for a DTI-based protocol to be applied to future imaging studies in NDD, towards the goal to proceed to establish DTI as a biomarker in clinical trials in neurodegeneration.

As a long-established model of schooling, the boarding system is commonly practiced in countries around the world. Numerous scholars have conducted a great deal of research on the relationship between the boarding school and student development, but the results of the research are quite divergent. In order to clarify the real effects of boarding school on students\' development, this study used meta-analysis to quantify 49 (91 effect sizes) experimental or quasi-experimental studies on related topics at home and abroad. The results find that: (1) Overall, boarding school has no significant predictive effect on student development, with a combined effect size of 0.002 (p > 0.05); (2) Specifically, boarding school has a significant positive predictive effect on students\' cognitive development (g = 0.248, p < 0.001), a significant negative predictive effect on students\' affective and attitudinal development (g = -0.159, p < 0.05), and no significant predictive effect on students\' behavioral development (g = -0.115, p > 0.05) and physical development (g = -0.038, p > 0.05); (3) The relationship between the two is moderated by the school stage and the type of boarding school, but not by the instruments; (4) Compared with primary school students, senior high school students and urban boarding students, the negative predictive effect of boarding system on junior middle school students and rural boarding students is more significant. In addition, there are some limitations in the study, such as the limited number of moderator variables included, the results of the study are easily affected by the quality of the included literature, and the dimensionality of the core variable \"student development\" is not comprehensive enough. In the future, further validation should be conducted through in-depth longitudinal or experimental studies.