The N-Pact Factor, Replication and Power Associated with Quantitative Research in Physical Activity and Health

Physical Activity (PA) and health science researchers often face challenges related to sample size, which can impact the reliability and generalizability of study findings. The purpose of the current paper is to address these issues by discussing key statistical concepts: effect size and Type I and Type II errors, with a specific focus on examining statistical power and sample size using studies from the <italic>Disability and Health Journal (DHJ)</italic>. We examined research articles published in <italic>DHJ</italic> over a 15-year period (2008–2022), covering 62 issues and analyzing a total of 1,177 articles. Our analysis revealed that the median sample sizes for various research types were as follows: correlational studies (NF = 197), quasi-experimental studies (NF = 140), and experimental studies (NF = 100). These findings highlight the differences in sample sizes across research designs, underscoring the need for careful consideration of sample size. Additionally, we examined three distinct five-year blocks within this period (2008–2012, 2013–2017, and 2018–2022) to identify trends over time, finding that the largest sample sizes for correlational, quasi-experimental, and experimental studies were observed in the first five-year block (2008–2012). This trend analysis provides valuable insights into sample size considerations and highlights the importance of planning for adequate power in PA and health research.