Literature DB >> 31368728

An N-pact factor for clinical psychological research.

Kathleen W Reardon1, Avanté J Smack1, Kathrin Herzhoff1, Jennifer L Tackett1.   

Abstract

Although an emphasis on adequate sample size and statistical power has a long history in clinical psychological science (Cohen, 1992), increased attention to the replicability of scientific findings has renewed focus on the importance of statistical power (Bakker, van Dijk, & Wicherts, 2012). These recent efforts have not yet circled back to modern clinical psychological research, despite the importance of sample size and power in producing a credible body of evidence. As one step in this process of scientific self-examination, the present study estimated an N-pact Factor (the statistical power of published empirical studies to detect typical effect sizes; Fraley & Vazire, 2014) in 2 leading clinical journals (the Journal of Abnormal Psychology [JAP] and the Journal of Consulting and Clinical Psychology [JCCP]) for the years 2000, 2005, 2010, and 2015. Study sample size, as one proxy for statistical power, is a useful focus because it allows comparisons with other subfields and may highlight some of the core methodological differences between clinical and other areas. We found that, across all years examined, the average median sample size in clinical research was 179 participants (175 for JAP and 182 for JCCP). The power to detect a small to medium effect size of .20 is just below 80% for both journals. Although the clinical N-pact factor was higher than that estimated for social psychology, the statistical power in clinical journals is still limited to detect many effects of interest to clinical psychologists, with little evidence of improvement in sample sizes over time. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Entities:  

Year:  2019        PMID: 31368728     DOI: 10.1037/abn0000435

Source DB:  PubMed          Journal:  J Abnorm Psychol        ISSN: 0021-843X


  3 in total

1.  Open science practices for eating disorders research.

Authors:  Natasha L Burke; Guido K W Frank; Anja Hilbert; Thomas Hildebrandt; Kelly L Klump; Jennifer J Thomas; Tracey D Wade; B Timothy Walsh; Shirley B Wang; Ruth Striegel Weissman
Journal:  Int J Eat Disord       Date:  2021-09-23       Impact factor: 5.791

2.  Sample size, sample size planning, and the impact of study context: systematic review and recommendations by the example of psychological depression treatment.

Authors:  Raphael Schuster; Tim Kaiser; Yannik Terhorst; Eva Maria Messner; Lucia-Maria Strohmeier; Anton-Rupert Laireiter
Journal:  Psychol Med       Date:  2021-04-21       Impact factor: 7.723

3.  Machine learning to advance the prediction, prevention and treatment of eating disorders.

Authors:  Shirley B Wang
Journal:  Eur Eat Disord Rev       Date:  2021-07-06
  3 in total

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