Usefulness of the SF-36 Health Survey in screening for depressive and anxiety disorders in rheumatoid arthritis

BACKGROUND: This study aimed to assess the accuracy of the Short-Form Health Survey (SF-36) mental health subscale (MH) and mental component summary (MCS) scores in identifying the presence of probable major depressive or anxiety disorder in patients with rheumatoid arthritis. METHODS: SF-36 data were collected in 100 hospital outpatients with rheumatoid arthritis. MH and MCS scores were compared against depression and anxiety data collected using validated measures as part of routine clinical practice. Sensitivity and specificity of the SF-36 were established using receiver operating characteristic (ROC) curve analysis, and area under the curve (AUC) compared the performance of the SF-36 components with the 9-item Patient Health Questionnaire (PHQ9) for depression and the 7-item Generalised Anxiety Disorder (GAD7) questionnaire for anxiety. RESULTS: The MH with a threshold of ≤52 had sensitivity and specificity of 81.0 and 71.4 % respectively to detect anxiety, correctly classifying 73.5 % of patients with probable anxiety disorder. A threshold of ≤56 had sensitivity and specificity of 92.6 and 73.2 % respectively to detect depression, correctly classifying 78.6 % of patients, and the same threshold could also be used to detect either depression or anxiety with a sensitivity of 87.9 %, specificity of 76.9 % and accuracy of 80.6 %. The MCS with a threshold of ≤35 had sensitivity and specificity of 85.7 and 81.9 % respectively to detect anxiety, correctly classifying 82.8 % of patients with probable anxiety disorder. A threshold of ≤40 had sensitivity and specificity of 92.3 and 70.2 % respectively to detect depression, correctly classifying 76.3 % of patients. A threshold of ≤38 could be used to detect either depression or anxiety with a sensitivity of 87.5 %, specificity of 80.3 % and accuracy of 82.8 %. CONCLUSION: This analysis may increase the utility of a widely-used questionnaire. Overall, optimal use of the SF-36 for screening for mental disorder may be through using the MCS with a threshold of ≤38 to identify the presence of either depression or anxiety. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12891-016-1083-y) contains supplementary material, which is available to authorized users

Are depression and anxiety associated with disease activity in rheumatoid arthritis?:A prospective study

BACKGROUND: This study aimed to investigate the impact of depression and anxiety scores on disease activity at 1-year follow-up in people with Rheumatoid Arthritis (RA). METHODS: The Hospital Anxiety Depression Scale (HADS) was used to measure depression and anxiety in a cross-section of RA patients. The primary outcome of interest was disease activity (DAS28), measured one-year after baseline assessment. Secondary outcomes were: tender joint count, swollen joint count, erythrocyte sedimentation rate and patient global assessment, also measured one-year after baseline assessment. We also examined the impact of baseline depression and anxiety on odds of reaching clinical remission at 1-year follow-up. RESULTS: In total, 56 RA patients were eligible for inclusion in this analysis. Before adjusting for key demographic and disease variables, increased baseline depression and anxiety were associated with increased disease activity at one-year follow-up, although this was not sustained after adjusting for baseline disease activity. There was a strong association between depression and anxiety and the subjective components of the DAS28 at 12-month follow-up: tender joint count and patient global assessment. After adjusting for age, gender, disease duration and baseline tender joint count and patient global assessment respectively, higher levels of depression and anxiety at baseline were associated with increased tender joint count and patient global assessment scores at 1-year follow-up. CONCLUSIONS: Symptoms of depression and anxiety have implications for disease activity, as measured via the DAS28, primarily due to their influence on tender joints and patient global assessment. These findings have implications for treatment decision-making as inflated DAS28 despite well controlled inflammatory disease markers may indicate significant psychological morbidity and related non-inflammatory pain, rather than true disease activity

Stakeholder perspectives on contributors to delayed and inaccurate diagnosis of cardiovascular disease and their implications for digital health technologies: a UK-based qualitative study

Objective: The aim of this study is to understand stakeholder experiences of diagnosis of cardiovascular disease (CVD) to support the development of technological solutions that meet current needs. Specifically, we aimed to identify challenges in the process of diagnosing CVD, to identify discrepancies between patient and clinician experiences of CVD diagnosis, and to identify the requirements of future health technology solutions intended to improve CVD diagnosis. Design: Semistructured focus groups and one-to-one interviews to generate qualitative data that were subjected to thematic analysis. Participants: UK-based individuals (N=32) with lived experience of diagnosis of CVD (n=23) and clinicians with experience in diagnosing CVD (n=9). Results: We identified four key themes related to delayed or inaccurate diagnosis of CVD: symptom interpretation, patient characteristics, patient–clinician interactions and systemic challenges. Subthemes from each are discussed in depth. Challenges related to time and communication were greatest for both stakeholder groups; however, there were differences in other areas, for example, patient experiences highlighted difficulties with the psychological aspects of diagnosis and interpreting ambiguous symptoms, while clinicians emphasised the role of individual patient differences and the lack of rapport in contributing to delays or inaccurate diagnosis. Conclusions: Our findings highlight key considerations when developing digital technologies that seek to improve the efficiency and accuracy of diagnosis of CVD

Variability of speech timing features across repeated recordings: a comparison of open-source extraction techniques

Variations in speech timing features have been reliably linked to symptoms of various health conditions, demonstrating clinical potential. However, replication challenges hinder their translation; extracted speech features are susceptible to methodological variations in the recording and processing pipeline. Investigating this, we compared exemplar timing features extracted via three different techniques from recordings of healthy speech. Our results show that features extracted via an intensity-based method differ from those produced by forced alignment. Different extraction methods also led to differing estimates of within-speaker feature variability over time in an analysis of recordings repeated systematically over three sessions in one day (n=26) and in one week (n=28). Our findings highlight the importance of feature extraction in study design and interpretation, and the need for consistent, accurate extraction techniques for clinical research