Depression Treatment: Testing the Assumption of Measurement Invariance in the SAMHSA Mental Health and Alcohol Abuse Stigma Assessment in Older Adults.

Testing the Assumption of Measurement Invariance in the SAMHSA Mental Health and Alcohol Abuse Stigma Assessment in Older Adults.

Filed under: Depression Treatment

Ageing Int. 2012 Dec; 37(4): 441-458
King-Kallimanis BL, Oort FJ, Lynn N, Schonfeld L

This study examined the assumption of measurement invariance of the SAMSHA Mental Health and Alcohol Abuse Stigma Assessment. This is necessary to make valid comparisons across time and groups. The data come from the Primary Care Research in Substance Abuse and Mental Health for Elderly trial, a longitudinal multisite, randomized trial examining two modes of care (Referral and Integrated). A sample of 1,198 adults over the age of 65 who screened positive for depression, anxiety, and/or at-risk drinking was used. Structural equation modeling was used to assess measurement invariance in a two-factor measurement model (Perceived Stigma, Comfort Level). Irrespective of their stigma level, one bias indicated that with time, respondents find it easier to acknowledge that it is difficult to start treatment if others know they are in treatment. Other biases indicated that sex, mental quality of life and the subject of stigma had undue influence on respondents’ feeling people would think differently of them if they received treatment and on respondents’ comfort in talking to a mental health provider. Still, in the present study, these biases in response behavior had little effect on the evaluation of group differences and changes in stigma. Stigma decreased for patients of both the Referral and Integrated care groups.
HubMed – depression


The Effects of a Mindfulness-Based Intervention on Emotional Distress, Quality-of-Life, and HbA1c in Outpatients With Diabetes (DiaMind): A randomized controlled trial.

Filed under: Depression Treatment

Diabetes Care. 2012 Nov 27;
van Son J, Nyklícek I, Pop VJ, Blonk MC, Erdtsieck RJ, Spooren PF, Toorians AW, Pouwer F

OBJECTIVEEmotional distress is common in outpatients with diabetes, affecting ?20-40% of the patients. The aim of this study was to determine the effectiveness of group therapy with Mindfulness-Based Cognitive Therapy (MBCT), relative to usual care, for patients with diabetes with regard to reducing emotional distress and improving health-related quality-of-life and glycemic control.RESEARCH DESIGN AND METHODSIn the present randomized controlled trial, 139 outpatients with diabetes (type 1 or type 2) and low levels of emotional well-being were randomized to MBCT (n = 70) or a waiting list group (n = 69). Primary outcomes were perceived stress (Perceived Stress Scale), anxiety and depressive symptoms (Hospital Anxiety and Depression Scale), mood (Profiles of Mood States), and diabetes-specific distress (Problem Areas In Diabetes). Secondary outcomes were health-related quality-of-life (12-Item Short-Form Health Survey), and glycemic control (HbA(1c)). Assessments were conducted at baseline and at 4 and 8 weeks of follow-up.RESULTSCompared with control, MBCT was more effective in reducing stress (P < 0.001, Cohen d = 0.70), depressive symptoms (P = 0.006, d = 0.59), and anxiety (P = 0.019, d = 0.44). In addition, MBCT was more effective in improving quality-of-life (mental: P = 0.003, d = 0.55; physical: P = 0.032, d = 0.40). We found no significant effect on HbA(1c) or diabetes-specific distress, although patients with elevated diabetes distress in the MBCT group tended to show a decrease in diabetes distress (P = 0.07, d = 0.70) compared with the control group.CONCLUSIONSCompared with usual care, MBCT resulted in a reduction of emotional distress and an increase in health-related quality-of-life in diabetic patients who had lower levels of emotional well-being. HubMed – depression


A structured framework for assessing sensitivity to missing data assumptions in longitudinal clinical trials.

Filed under: Depression Treatment

Pharm Stat. 2012 Nov 28;
Mallinckrodt CH, Lin Q, Molenberghs M

The objective of this research was to demonstrate a framework for drawing inference from sensitivity analyses of incomplete longitudinal clinical trial data via a re-analysis of data from a confirmatory clinical trial in depression. A likelihood-based approach that assumed missing at random (MAR) was the primary analysis. Robustness to departure from MAR was assessed by comparing the primary result to those from a series of analyses that employed varying missing not at random (MNAR) assumptions (selection models, pattern mixture models and shared parameter models) and to MAR methods that used inclusive models. The key sensitivity analysis used multiple imputation assuming that after dropout the trajectory of drug-treated patients was that of placebo treated patients with a similar outcome history (placebo multiple imputation). This result was used as the worst reasonable case to define the lower limit of plausible values for the treatment contrast. The endpoint contrast from the primary analysis was?-?2.79?(p ?=? .013). In placebo multiple imputation, the result was?-?2.17. Results from the other sensitivity analyses ranged from?-?2.21 to?-?3.87 and were symmetrically distributed around the primary result. Hence, no clear evidence of bias from missing not at random data was found. In the worst reasonable case scenario, the treatment effect was 80% of the magnitude of the primary result. Therefore, it was concluded that a treatment effect existed. The structured sensitivity framework of using a worst reasonable case result based on a controlled imputation approach with transparent and debatable assumptions supplemented a series of plausible alternative models under varying assumptions was useful in this specific situation and holds promise as a generally useful framework. Copyright © 2012 John Wiley & Sons, Ltd.
HubMed – depression


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