Detecting DSM-5 somatic symptom disorder: criterion validity of the Patient Health Questionnaire-15 (PHQ-15) and the Somatic Symptom Scale-8 (SSS-8) in combination with the Somatic Symptom Disorder – B Criteria Scale (SSD-12)

2019 ◽  
Vol 50 (2) ◽  
pp. 324-333 ◽  
Author(s):  
Anne Toussaint ◽  
Paul Hüsing ◽  
Sebastian Kohlmann ◽  
Bernd Löwe
Keyword(s):  
Diagnostic Accuracy ◽  
Sensitivity And Specificity ◽  
Somatic Symptom ◽  
Patient Health Questionnaire ◽  
Health Questionnaire ◽  
Somatic Symptom Disorder ◽  
Symptom Scale ◽  
Dsm 5 ◽  
Patient Health ◽  
Scale 8

BackgroundThe fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) introduced somatic symptom and related disorders (SSD) to improve the diagnosis of somatoform disorders. It is unclear whether existing questionnaires are useful to identify patients with SSD. Our study investigates the diagnostic accuracy of the Patient Health Questionnaire-15 (PHQ-15) and the Somatic Symptom Scale-8 (SSS-8) in combination with the Somatic Symptom Disorder – B Criteria Scale (SSD-12).MethodsFor this cross-sectional study, participants were recruited from a psychosomatic outpatient clinic. PHQ-15, SSS-8, and SSD-12 were administered and compared with SSD criteria from a diagnostic interview. Sensitivity and specificity were calculated for optimal individual and combined cutpoints. Receiver operator curves were created and area under the curve (AUC) analyses assessed.ResultsData of n = 372 patients [31.2% male, mean age: 39.3 years (s.d. = 13.6)] were analyzed. A total of 56.2% fulfilled the SSD criteria. Diagnostic accuracy was moderate for each questionnaire (PHQ-15: AUC = 0.70; 95% CI = 0.65–0.76; SSS-8: AUC = 0.71; 95% CI = 0.66–0.77; SSD-12: AUC = 0.74; 95% CI = 0.69–0.80). Combining questionnaires improved diagnostic accuracy (PHQ-15 + SSD-12: AUC = 0.77; 95% CI = 0.72–0.82; SSS-8 + SSD-12: AUC = 0.79; 95% CI = 0.74–0.84). Optimal combined cutpoints were ⩾9 for the PHQ-15 or SSS-8, and ⩾23 for the SSD-12 (sensitivity and specificity = 69% and 70%).ConclusionsThe combination of the PHQ-15 or SSS-8 with the SSD-12 provides an easy-to-use and time- and cost-efficient opportunity to identify persons at risk for SSD. If systematically applied in routine care, effective screening and subsequent treatment might help to improve quality of life and reduce health care excess costs.

scholarly journals Developing the Patient Health Questionnaire-8 for a greater impact on the quality of life of patients with functional dyspepsia compared to Somatic Symptom Scale-8

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Chaoqun Yuan ◽  
Guizhen Yong ◽  
Xi Wang ◽  
Ting Xie ◽  
Chunyan Wang ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Regression Analysis ◽  
Somatic Symptom ◽  
Linear Regression Analysis ◽  
Reliability And Validity ◽  
Health Questionnaire ◽  
Symptom Scale ◽  
Patient Health ◽  
Scale 8

Abstract Background To develop the Patient Health Questionnaire-8 (PHQ-8) as a more reliable approach than the Somatic Symptom Scale-8 (SSS-8), evaluating somatization which might be a critical factor influencing the quality of life (QoL) in patients with functional dyspepsia (FD). Also, the effects of somatization on QoL of FD patients were assessed by these two approaches. Methods Herein, 612 FD patients completed a questionnaire involving 25 items. 8/25 items were selected to develop the PHQ-8 by four methods of discrete degree, correlation coefficient, factor analysis, and Cronbach’s α coefficient. Reliability and validity of the PHQ-8 and the SSS-8 were compared by principal component and confirmatory factor analyses. The effects of somatization, depression, and anxiety on the Nepean Dyspepsia Index (NDI) for QoL were explored by Pearson’s correlation coefficient and linear regression analysis. Results The Cronbach’s α coefficient for the PHQ-8 and the SSS-8 was 0.601 and 0.553, respectively, and the cumulative contribution rate of three extracted factors for the developed PHQ-8 and SSS-8 was 55.103% and 51.666%, respectively. Somatization evaluated by the PHQ-8 (r = 0.309, P < 0.001) and the SSS-8 (r = 0.281, P < 0.001) was found to be correlated to NDI. The model used for the PHQ-8 showed that the values of goodness-of-fit index (GFI) and adjusted GFI (AGFI) were 0.984 and 0.967, respectively, which indicated that the model fitted well. Linear regression analysis unveiled that somatization (β = 0.270, P < 0.001), anxiety (β = 0.163, P < 0.001), and depression (β = 0.136, P = 0.003) assessed by the PHQ-8 were correlated to NDI. In addition, somatization (β = 0.250, P < 0.001), anxiety (β = 0.156, P < 0.001), and depression (β = 0.155, P = 0.001) evaluated by the SSS-8 were correlated to NDI. Conclusions PHQ-8 showed a superior reliability and validity, and somatization assessed by the developed PHQ-8 showed a greater influence on the QoL of FD patients as compared to the SSS-8. Our findings suggested that the developed PHQ-8 may show improvement in a reliable assessment of the effects of somatization on FD patients in lieu of the SSS-8.

Using the Patient Health Questionnaire to estimate prevalence and gender differences of somatic symptoms and psychological co-morbidity in a secondary inpatient population with abdominal pain

2021 ◽  
pp. 000486742110446
Author(s):  
Melissa Stieler ◽  
Peter Pockney ◽  
Cassidy Campbell ◽  
Vaisnavi Thirugnanasundralingam ◽  
Lachlan Gan ◽  
...  
Keyword(s):  
Gender Differences ◽  
Abdominal Pain ◽  
Somatic Symptom ◽  
Somatic Symptoms ◽  
Patient Health Questionnaire ◽  
Health Questionnaire ◽  
Cut Points ◽  
Co Morbidity ◽  
Female Predominance ◽  
Patient Health

Background: Somatic disorders and somatic symptoms are common in primary care populations; however, little is known about the prevalence in surgical populations. Identification of inpatients with high somatic symptom burden and psychological co-morbidity could improve access to effective psychological therapies. Methods: Cross-sectional analysis ( n = 465) from a prospective longitudinal cohort study of consecutive adult admissions with non-traumatic abdominal pain, at a tertiary hospital in New South Wales, Australia. We estimated somatic symptom prevalence with the Patient Health Questionnaire-15 at three cut-points: moderate (⩾10), severe (⩾15) and ‘bothered a lot’ on ⩾3 symptoms; and psychological co-morbidity with the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 at standard (⩾10) cut-points. We also examined gender differences for somatic symptoms and psychological co-morbidity. Results: Prevalence was moderate (52%), female predominance (odds ratio = 1.71; 95% confidence interval = [1.18, 2.48]), severe (20%), no gender difference (1.32; [0.83, 2.10]) and ‘bothered a lot’ on ⩾3 symptoms (53%), female predominance (2.07; [1.42, 3.03]). Co-morbidity of depressive, anxiety and somatic symptoms ranged from 8.2% to 15.9% with no gender differences. Conclusion: Somatic symptoms were common and psychological triple co-morbidity occurred in one-sixth of a clinical population admitted for abdominal pain. Co-ordinated surgical and psychological clinical intervention and changes in clinical service organisation may be warranted to provide optimal care.

scholarly journals Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis

BMJ ◽  
2019 ◽  
pp. l1476 ◽  
Author(s):  
Brooke Levis ◽  
Andrea Benedetti ◽  
Brett D Thombs
Keyword(s):  
Major Depression ◽  
Sensitivity And Specificity ◽  
Meta Analysis ◽  
Patient Health Questionnaire ◽  
Individual Participant Data ◽  
Health Questionnaire ◽  
Structured Interviews ◽  
Diagnostic Interviews ◽  
Patient Health ◽  
Individual Participant

Abstract Objective To determine the accuracy of the Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression. Design Individual participant data meta-analysis. Data sources Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science (January 2000-February 2015). Inclusion criteria Eligible studies compared PHQ-9 scores with major depression diagnoses from validated diagnostic interviews. Primary study data and study level data extracted from primary reports were synthesized. For PHQ-9 cut-off scores 5-15, bivariate random effects meta-analysis was used to estimate pooled sensitivity and specificity, separately, among studies that used semistructured diagnostic interviews, which are designed for administration by clinicians; fully structured interviews, which are designed for lay administration; and the Mini International Neuropsychiatric (MINI) diagnostic interviews, a brief fully structured interview. Sensitivity and specificity were examined among participant subgroups and, separately, using meta-regression, considering all subgroup variables in a single model. Results Data were obtained for 58 of 72 eligible studies (total n=17 357; major depression cases n=2312). Combined sensitivity and specificity was maximized at a cut-off score of 10 or above among studies using a semistructured interview (29 studies, 6725 participants; sensitivity 0.88, 95% confidence interval 0.83 to 0.92; specificity 0.85, 0.82 to 0.88). Across cut-off scores 5-15, sensitivity with semistructured interviews was 5-22% higher than for fully structured interviews (MINI excluded; 14 studies, 7680 participants) and 2-15% higher than for the MINI (15 studies, 2952 participants). Specificity was similar across diagnostic interviews. The PHQ-9 seems to be similarly sensitive but may be less specific for younger patients than for older patients; a cut-off score of 10 or above can be used regardless of age.. Conclusions PHQ-9 sensitivity compared with semistructured diagnostic interviews was greater than in previous conventional meta-analyses that combined reference standards. A cut-off score of 10 or above maximized combined sensitivity and specificity overall and for subgroups. Registration PROSPERO CRD42014010673.

scholarly journals Depression Screening Tools for Patients with Kidney Failure

2020 ◽  
Vol 15 (12) ◽  
pp. 1785-1795
Author(s):  
Karli Kondo ◽  
Jennifer R. Antick ◽  
Chelsea K. Ayers ◽  
Devan Kansagara ◽  
Pavan Chopra
Keyword(s):  
Systematic Review ◽  
Diagnostic Accuracy ◽  
Beck Depression Inventory ◽  
Kidney Failure ◽  
Assessment Tools ◽  
Screening Tools ◽  
Depression Screening ◽  
Patient Health Questionnaire ◽  
Health Questionnaire ◽  
Patient Health

Background and objectivesPatients with kidney failure experience depression at rates higher than the general population. Despite the Centers for Medicare and Medicaid Services’ ESRD Quality Incentive Program requirements for routine depression screening for patients with kidney failure, no clear guidance exists.Design, setting, participants, & measurementsFor this systematic review, we searched MEDLINE, PsycINFO, and other databases from inception to June 2020. Two investigators screened all abstracts and full text. We included studies assessing patients with kidney failure and compared a tool to a clinical interview or another validated tool (e.g., Beck Depression Inventory II). We abstracted data related to sensitivity and specificity, positive and negative predictive value, and the area under the curve. We evaluated the risk of bias using the Quality Assessment of Diagnostic Accuracy Studies 2.ResultsA total of 16 studies evaluated the performance characteristics of depression assessment tools for patients with kidney failure. The Beck Depression Inventory II was by far the best studied. A wide range of thresholds were reported. Shorter tools in the public domain such as the Patient Health Questionnaire 9 and Geriatric Depression Scale 15 (adults over 60) performed well but were not well studied. Short tools such as the Beck Depression Inventory–Fast Screen may be a good option for an initial screen.ConclusionsThere is limited research evaluating the diagnostic accuracy of most screening tools for depression in patients with kidney failure, and existing studies may not be generalizable to US populations. Studies suffer from limitations related to methodology quality and/or reporting. Future research should target widely used, free tools such as the Patient Health Questionnaire 2 and the Patient Health Questionnaire 9.Clinical Trial registry name and registration number:Systematic Review Registration: PROSPERO CRD42020140227.

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