Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/53638
Title: Datafile for meta-analysis on the efficacy of assertiveness training for social anxiety
Contributor(s): Malouff, John  (creator)orcid 
Publication Date: 2022-11-02
DOI: 10.25952/kk33-tk97
Handle Link: https://hdl.handle.net/1959.11/53638
Abstract/Context: This is the datafile for a meta-analysis. The meta-analysis synthesised research assessing the efficacy of assertiveness training for reducing social anxiety. A comprehensive search led to six relevant randomised control trials (RCTs) with a total of 298 participants. Meta-analysis using a random-effects model showed that assertiveness training was significantly more effective for reducing social anxiety than a wait-list control. The weighted meta-analytic effect size, g = 1.21, indicates a large positive effect. These results support the use of assertiveness training for persistent social anxiety.
Publication Type: Dataset
Fields of Research (FOR): 170106 Health, Clinical and Counselling Psychology
Fields of Research (FoR) 2020: 520399 Clinical and health psychology not elsewhere classified
Socio-Economic Objective (SEO): 920410 Mental Health
Socio-Economic Objective (SEO) 2020: 200409 Mental health
Keywords: assertion
assertiveness
meta-analysis
training
social anxiety
Location: Armidale, New South Wales, Australia
HERDC Category Description: X Dataset
Project: Efficacy of Assertiveness Training for Social Anxiety: A Meta-analysis of Randomised Controlled Trials
Dataset Managed By: John Malouff
Rights Holder: John Malouff
Dataset Stored at: University of New England
Primary Contact Details: John Malouff - jmalouff@une.edu.au
Dataset Custodian Details: John Malouff - jmalouff@une.edu.au
Appears in Collections:Dataset
School of Psychology

Files in This Item:
2 files
File Description SizeFormat 
Show full item record

Page view(s)

548
checked on Apr 2, 2023
Google Media

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons