STUDY OBJECTIVES: To assess the feasibility of using the SF-36v2 mental health (MH) and mental component summary (MCS) scores for classification of risk for major depressive disorder (MDD), and to determine cut-off scores based on the sensitivity and specificity in a general US representative sample, and a chronic pain subpopulation. METHODS: Data were analyzed from the 2013 US National Health and Wellness Survey (adults 18 y old and above; N=75,000), and among a chronic pain subpopulation (n=6679). Risk of MDD was a score ≥10 on the Patient Health Questionnaire (PHQ-9). Logistic regression modeling was used to predict at risk for MDD and receiver operating characteristic curves were produced. RESULTS: The total sample had MH scores of 48.8 and MCS scores of 48.9, similar to the normative US population mean. Percent of respondents with a PHQ-9≥10 were 15.0% and 29.1% for the total sample and chronic pain subpopulation, respectively. Cut-off scores (PHQ-9≥10) in the total sample for the MH and MCS were 43.0 and 46.0, respectively. Specificities for the MH and MCS were 77.8% and 76.1%; sensitivities were 84.9% and 88.1%, respectively. Among the subpopulation with chronic pain, cut-off scores for the MH and MCS were 40.4 and 43.1, respectively. Corresponding specificities for the MH and MCS were 77.9% and 73.9%; sensitivities were 78.3% and 83.4%, respectively. CONCLUSIONS: The SF-36v2 was found to have sufficient specificity and sensitivity to categorize participants at risk for MDD. If no depression questionnaire is available, it is feasible to use the SF-36v2 to characterize the MH of populations.
STUDY OBJECTIVES: To assess the feasibility of using the SF-36v2 mental health (MH) and mental component summary (MCS) scores for classification of risk for major depressive disorder (MDD), and to determine cut-off scores based on the sensitivity and specificity in a general US representative sample, and a chronic pain subpopulation. METHODS: Data were analyzed from the 2013 US National Health and Wellness Survey (adults 18 y old and above; N=75,000), and among a chronic pain subpopulation (n=6679). Risk of MDD was a score ≥10 on the Patient Health Questionnaire (PHQ-9). Logistic regression modeling was used to predict at risk for MDD and receiver operating characteristic curves were produced. RESULTS: The total sample had MH scores of 48.8 and MCS scores of 48.9, similar to the normative US population mean. Percent of respondents with a PHQ-9≥10 were 15.0% and 29.1% for the total sample and chronic pain subpopulation, respectively. Cut-off scores (PHQ-9≥10) in the total sample for the MH and MCS were 43.0 and 46.0, respectively. Specificities for the MH and MCS were 77.8% and 76.1%; sensitivities were 84.9% and 88.1%, respectively. Among the subpopulation with chronic pain, cut-off scores for the MH and MCS were 40.4 and 43.1, respectively. Corresponding specificities for the MH and MCS were 77.9% and 73.9%; sensitivities were 78.3% and 83.4%, respectively. CONCLUSIONS: The SF-36v2 was found to have sufficient specificity and sensitivity to categorize participants at risk for MDD. If no depression questionnaire is available, it is feasible to use the SF-36v2 to characterize the MH of populations.
Authors: Laura C Simko; Leda F Espinoza; Kara McMullen; David N Herndon; Oscar Suman; James A Fauerbach; Karen Kowalske; Shelley Wiechman; Lewis E Kazis; Colleen M Ryan; Jeffrey C Schneider Journal: J Burn Care Res Date: 2018-04-20 Impact factor: 1.819
Authors: Anthonia U Chinweuba; Ijeoma L Okoronkwo; Agnes N Anarado; Noreen E Agbapuonwu; Ngozi P Ogbonnaya; Chikaodili N Ihudiebube-Splendor Journal: BMC Womens Health Date: 2018-01-10 Impact factor: 2.809