Multidimensional Depression Assessment Scale (MDAS) across ethnic groups: A study of measurement invariance and network modelling.

  • Williams, Joanne (Principal Investigator)
  • Chan, Stella (Co-investigator)
  • Cheung, Amy (Principal Investigator)

Project Details


This project, funded by Katie Shu Sui Pui Charitable Trust, is a collaboration with Dr Amy Chan (PI) (The Open University of Hong Kong) Prof Stella Chan (CoI) (University of Reading) and Prof Jo Williams (CoI) (University of Edinburgh). Abstract: Depression has been identified as a serious threat to global wellbeing. The heterogeneous nature of symptomatology leads to the development and validation of numerous self-report assessment instruments. However, the widely used self-report instruments such as Beck Depressive Inventory (BDI), Centre for Epidemiologic Studies Depression Scale (CES-D), Patients Health Questionnaire (PHQ) and Hospital Anxiety and Depression Scale (Depression subscale) (HADS-D) overlook interpersonal symptoms which have important relationship with depression as both consequences and maintaining factors of depression severity. Interpersonal symptoms could also be the expression of distress in Asian population. The Multidimensional Depression Assessment Scale (MDAS) is the first self-report questionnaire developed by Cheung and Power (2012) and validated with an emerging track record research (Cheung, Chan & Williams, 2020). It entails comprehensive symptom subscale on emotional, cognitive, somatic and interpersonal symptoms. Its psychometric properties has been demonstrated in UK community sample, Chinese clinical and pregnant sample with sound validity and reliability. It is expected to perform well and provide a comprehensive and thorough examination of depression in various domains. In addition, its comprehensive list of symptoms could shed light onto the cultural construct of depression when factor analysis of MDAS is applied in various cultural groups. The current project aims to examine the factor structure of MDAS and its measurement invariance across four major ethnic groups in the world: Asian, Caucasian, Black and Hispanic and identifying the best-fit factor model across these ethnic groups. It also aims to study the interconnection between symptoms on MDAS through network modelling to identify symptoms that are more closely related to each other. The current project has substantial clinical and research implications for the future clinical application of MDAS in depression measurement by establishing a measurement invariant tool to be used across cultures highlighting the cultural construct of depression.
Effective start/end date1/09/2031/08/21


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