Developing a new multi-dimensional depression assessment scale
Cheung, Ho Nam
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Depression is a global risk factor of mental health. Empirical studies (e.g. Beck, 1967, 1976) and clinical observations (APA, 1996, 2000) showed that it has symptoms in 4 domains-, emotional, cognitive, somatic and interpersonal. A good depression assessment instrument makes clinicians more effective in screening out non-depressed people and choosing the appropriate treatment. However, commonly used depression assessment scale such as BDI-II, Hamilton depression rating scale, and CES-D put little attention on evaluating interpersonal symptoms. Only three per cent of the total items in all depression scales were on interpersonal domain. Therefore, a new depression assessment scale, aiming to evaluate all 4 domains of depressive symptom, was developed. In Study 1, an 85-item questionnaire containing all the possible depressive symptoms was distributed to 87 participants from mental health professions. Based on their clinical experience and knowledge, they rated how typical each symptom was on a 5-point Likert scale in which 5 represented the most typical symptom and 1 as the least typical symptom. The mean score for each item was calculated and ranked. Items with strong correlations were excluded. Finally, forty-eight Items with the highest mean scores were put into the new multidimensional depression assessment scale, which aimed to assess the severity and symptom pattern of depression. The new depression assessment scale contained 52 items, 48 from the first study and 4 from psychiatrists after checking the validity of the scale. It consisted of 4 subscales, emotional, cognitive, somatic and interpersonal. One hundred mentally healthy participants finished the questionnaire, as well as BDI-II. Reliability analysis and Pearson correlation gave high Cronbach's alpha (>0.8) for each subscale and good correlation (>0.7) between the new scale, its subscales, and BDI-II. All the evidence indicated that the new depression scale had good psychometric characteristics. It was found to be reliable and valid for the use of assessing depression severity and symptoms.