Experimental tests of interventions need to have sufficient sample size to constitute a robust test of the intervention's effectiveness with reasonable precision and power. To estimate the required sample size adequately, researchers are required to specify an effect size. But what effect size should be used to plan the required sample size? Various inroads into selecting the effect size have been suggested in the literature-including using conventions, prior research, and theoretical or practical importance. In this paper, we first discuss problems with some of the proposed methods of selecting the effect size for study planning. We then lay out a method for intervention researchers that provides a way out of many of these problems. The proposed method requires setting a meaningful change definition, it is specifically suited for applied researchers interested in planning tests of intervention effectiveness. We provide a hands-on walk through of the method and provide easy-to-use functions to implement it.
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http://dx.doi.org/10.1080/08870446.2020.1841762 | DOI Listing |
Objective: To clarify the screening behavior and influencing factors of females with breast cancer and cervical cancer in suburban areas and to provide a scientific basis for the subsequent implementation of targeted health education, intervention measures and the formulation of relevant policies.
Methods: This study used a multi-stage stratified random sampling method to select 4, 000 women in urban and rural areas of Beijing to analyze their behavior, basic situation, and influencing factors regarding cervical and breast cancer screening.
Results: The sample size of the final included valid analysis was 3861 people, and the screening rate was 27.
Hypertension is a critical risk factor and cause of mortality in cardiovascular diseases, and it remains a global public health issue. Therefore, understanding its mechanisms is essential for treating and preventing hypertension. Gene expression data is an important source for obtaining hypertension biomarkers.
View Article and Find Full Text PDFPLoS One
January 2025
Curriculum in Toxicology & Environmental Medicine, UNC Chapel Hill, Chapel Hill, North Carolina, United States of America.
Growing evidence supports the importance of extracellular vesicle (EV) as mediators of communication in pathological processes, including those underlying respiratory disease. However, establishing methods for isolating and characterizing EVs remains challenging, particularly for respiratory samples. This study set out to address this challenge by comparing different EV isolation methods and evaluating their impacts on EV yield, markers of purity, and proteomic signatures, utilizing equine/horse bronchoalveolar lavage samples.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Faculty of Technical Chemistry, Institute of Chemical Technologies and Analytics, Technische Universität Wien, Vienna 1060, Austria.
Atomic force microscopy-infrared spectroscopy (AFM-IR) is a photothermal scanning probe technique that combines nanoscale spatial resolution with the chemical analysis capability of mid-infrared spectroscopy. Using this hybrid technique, chemical identification down to the single molecule level has been demonstrated. However, the mechanism at the heart of AFM-IR, the transduction of local photothermal heating to cantilever deflection, is still not fully understood.
View Article and Find Full Text PDFAppl Psychol Health Well Being
February 2025
Department of Education and Psychology, Division of Health Psychology, Freie Universität Berlin, Berlin, Germany.
Background: Interventions targeting social media use show mixed results in improving well-being outcomes, particularly for persons with problematic forms of smartphone use. This study assesses the effectiveness of an intervention app in enhancing well-being outcomes and the moderating role of persons' perceptions about problematic smartphone use (PSU).
Methods: In a randomized controlled trial, N = 70 participants, allocated to the intervention (n = 35) or control condition (n = 35), completed weekly online surveys at baseline, post-intervention, and follow-up.
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