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Evaluation of the Cardiac Depression Visual Analogue Scale in a medical and non-medical sample

Mirella Di Benedetto1, Matthew Sheehan

  • 1a School of Health Sciences, RMIT University , Melbourne , Australia .

Insights

The Cardiac Depression Visual Analogue Scale (CDVAS) effectively measures depressive symptoms in general medical patients. This brief, valid, and reliable tool aids in identifying depression in diverse healthcare settings.

Area of Science:

  • Psychiatry
  • Psychometrics
  • Clinical Psychology

Background:

  • Comorbid depression and medical illness negatively impacts patient outcomes, including medication adherence and mortality.
  • There is a need for validated psychological instruments to detect depressive symptoms in medical environments.
  • The Cardiac Depression Visual Analogue Scale (CDVAS) was developed for cardiac populations but requires validation in broader medical samples.

Purpose of the Study:

  • To evaluate the psychometric properties of the Cardiac Depression Visual Analogue Scale (CDVAS) in a general medical population.
  • To assess the reliability and validity of the CDVAS for detecting depressive symptoms.

Main Methods:

  • A sample of 117 participants completed the CDVAS, Cardiac Depression Scale (CDS), Depression Anxiety Stress Scales (DASS), and a demographic/health questionnaire.
  • Psychometric analyses included internal reliability, concurrent validity, discriminant validity, predictive validity, and principal components analysis.

Main Results:

  • The CDVAS demonstrated adequate internal reliability (α = .76).
  • Strong concurrent validity was found with the CDS (r = .89) and DASS depression sub-scale (r = .70).
  • Principal components analysis confirmed a single-component structure, supporting construct validity.

Conclusions:

  • The CDVAS is a short, simple, valid, and reliable measure for assessing depressive symptoms.
  • The scale is suitable for use in general and medical patient samples.
  • The CDVAS can aid in the detection of depression within diverse healthcare settings.