Diagnosis of depression by primary care physicians versus a structured diagnostic interview. Understanding discordance

In this paper, false-negative and false-positive cases of depressive illness are examined, differentiating levels of disagreement between a primary care physician's diagnosis and a standardized research diagnosis. Two stratified random samples of primary care patients in Seattle, USA (N = 373) and Groningen, The Netherlands (N = 340) were examined with the Composite International Diagnostic Interview-Primary Health Care Version (CIDI-PHC). Physician's severity ratings and diagnosis of psychological disorder were obtained. Three levels of disagreement between physician and CIDI diagnosis were distinguished: 1) complete disagreement about the presence of psychiatric symptoms (true false-negative and true false-positive patients); 2) disagreement over severity of recognized psychological illness (underestimated or overestimated); and 3) disagreement over the specific psychiatric diagnosis among those given a diagnosis (misdiagnosed or given another CIDI diagnosis). All three levels of disagreement were common. Only 27% of the false-negative cases were due to complete disagreement (true false-negatives), and 55% of the false-positives were due to complete disagreement (true false-positives). The true false-negative patients were younger, more often employed, rated their own health more favorably, visited their doctor for a somatic complaint and made fewer visits than the underestimated, misdiagnosed, and concordant positive patients. Complete disagreement in depressive diagnoses between the primary care physician and research interview is not as frequent as indicated by an undifferentiated false-negative/ false-positive analysis. Differentiating levels of disagreement does more justice to diagnostic practice in primary care and provides guidance on how to improve the diagnostic accuracy of primary care physicians.     

Patients’ and Psychologists’ Preferences for Feedback Reports on Expected Mental Health Treatment Outcomes: A Discrete-Choice Experiment

In recent years, there has been an increasing focus on routine outcome monitoring (ROM) to provide feedback on patient progress during mental health treatment, with some systems also predicting the expected treatment outcome. The aim of this study was to elicit patients’ and psychologists’ preferences regarding how ROM system-generated feedback reports should display predicted treatment outcomes. In a discrete-choice experiment, participants were asked 12–13 times to choose between two ways of displaying an expected treatment outcome. The choices varied in four different attributes: representation, outcome, predictors, and advice. A conditional logistic regression was used to estimate participants’ preferences. A total of 104 participants (68 patients and 36 psychologists) completed the questionnaire. Participants preferred feedback reports on expected treatment outcome that included: (a) both text and images, (b) a continuous outcome or an outcome that is expressed in terms of a probability, (c) specific predictors, and (d) specific advice. For both patients and psychologists, specific predictors appeared to be most important, specific advice was second most important, a continuous outcome or a probability was third most important, and feedback that includes both text and images was fourth in importance. The ranking in importance of both the attributes and the attribute levels was identical for patients and psychologists. This suggests that, as long as the report is understandable to the patient, psychologists and patients can use the same ROM feedback report, eliminating the need for ROM administrators to develop different versions.

     

Music-assisted relaxation to improve sleep quality: meta-analysis

Title.  Music-assisted relaxation to improve sleep quality: meta-analysis.
Aim.  This paper is a report of a meta-analysis conducted to evaluate the efficacy of music-assisted relaxation for sleep quality in adults and elders with sleep complaints with or without a co-morbid medical condition.
Background.  Clinical studies have shown that music can influence treatment outcome in a positive and beneficial way. Music holds the promise of counteracting psychological presleep arousal and thus improving the preconditions for sleep.
Data sources.  We conducted a search in the Embase (1997 – July 2008), Medline (1950 – July 2008), Cochrane (2000 – July 2008), Psychinfo (1987 – July 2008) and Cinahl (1982 – July 2008) databases for randomized controlled trials reported in English, German, French and Dutch. The outcome measure of interest was sleep quality.
Methods.  Data were extracted from the included studies using predefined data fields. The researchers independently assessed the quality of the trials using the Delphi list. Only studies with a score of 5 points or higher were included. A pooled analysis was performed based on a fixed effect model.
Results.  Five randomized controlled trials with six treatment conditions and a total of 170 participants in intervention groups and 138 controls met our inclusion criteria. Music-assisted relaxation had a moderate effect on the sleep quality of patients with sleep complaints (standardized mean difference, −0·74; 95% CI: −0·96, −0·46). Subgroup analysis revealed no statistically significant contribution of accompanying measures.
Conclusion.  Music-assisted relaxation can be used without intensive investment in training and materials and is therefore cheap, easily available and can be used by nurses to promote music-assisted relaxation to improve sleep quality.     

Accuracy of general practitioner's prognosis of the 1-year course of depression and generalised anxiety

BACKGROUND: A prognosis serves important functions for the management of common mental disorders in primary care. AIMS: To establish the accuracy of the general practitioner's (GP) prognosis. METHOD: The agreement between GP prognosis and observed course was determined for 138 cases of ICD-10 depression and 65 of generalised anxiety disorder, identified among consecutive attenders of 18 GPs. RESULTS: Modest agreement between GP prognosis and course was found, both for depression (kappa=0.21) and generalised anxiety (kappa=0.11). Better agreement (kappa=0.45 for depression, and kappa=0.33 for generalised anxiety) was observed between the course and predictions from a statistical model based on information potentially available to the GP at the time the prognosis was made. This model assesses attainable performance for GPs. CONCLUSIONS: General practitioners do a fair job in predicting the 1-year course of depression and generalised anxiety. Even so, their performance falls significantly short of attainable performance.     

Species specificity and lack of production of STb enterotoxin by Escherichia coli strains isolated from humans with diarrheal illness.

Escherichia coli strains produce at least two heat-stable enterotoxins, STa and STb. STa is well known to be important in the pathogenesis of human diarrheal disease; the role of STb has not been defined. Fifty-two E. coli strains recovered from human diarrheal illness in northeast Brazil or Bangladesh were examined in weaned porcine ligated intestinal segments for STb activity. A total of 113 E. coli strains from human diarrheal disease in northeast Brazil and 28 E. coli strains from Bangladesh were examined for DNA hybridization to a STb gene probe. None of these strains produced STb as detected by enterotoxic activity or by the gene probe. We also examined adult human ileal mucosa for responses to STb in the Ussing chamber in vitro. In contrast to piglet jejunum, which consistently responds electrogenically to crude STb, human ileal tissue showed no response to STb but responded electrogenically to theophylline (10 mM). These results suggest that STb-producing E. coli strains are not a major cause of diarrheal illness in humans.     

Predicting Return to Work in Employees Sick-Listed Due to Minor Mental Disorders

Objective To investigate which factors predict return to work (RTW) after 3 and 6 months in employees sick-listed due to minor mental disorders. Methods Seventy GPs recruited 194 subjects at the start of sick leave due to minor mental disorders. At baseline (T0), 3 and 6 months later (T1 and T2, respectively), subjects received a questionnaire and were interviewed by telephone. Using multivariate logistic regression analyses, we developed three prediction models to predict RTW at T1 and T2. Results The RTW rates were 38% after 3 months (T1) and 61% after 6 months (T2). The main negative predictors of RTW at T1 were: (a) a duration of the problems of more than 3 months before sick leave; and (b) somatisation. The main negative predictors of RTW at T2 were: (a) a duration of the problems of more than 3 months before sick leave; (b) more than 3 weeks of sick leave before inclusion in the study; and (c) anxiety. The main negative predictors of RTW at T2 for those who had not resumed work at T1 were: (a) more than 3 weeks of sick leave before inclusion in the study; and (b) depression at T1. The predictive power of the models was moderate with AUC-values between 0.695 and 0.763. Conclusions The main predictors of RTW were associated with the severity of the problems. A long duration of the problems before the occurrence of sick leave and a long duration of sick leave before seeking help predict a relatively small probability to RTW within 3–6 months. High baseline somatisation and anxiety, and high depression after 3 months make the prospect even worse. Since these predictors are readily assessable with just a few questions and a symptom questionnaire, this opens the opportunity to select high-risk employees for a targeted intervention to prevent long-term absenteeism.     

Applicability of two brief evidence-based interventions to improve sleep quality in inpatient mental health care

The present study explored the applicability of two brief evidence-based interventions to improve sleep quality in inpatient psychiatry. The study involved three comparable admission wards of a psychiatric hospital. Stimulus control was introduced at the first ward, and music-assisted relaxation at the second. At the third ward, no intervention was introduced. A mixed-method study was employed. We found that nurses share the opinion that both interventions can be applied, but patients are hard to motivate. They perceived the lack of available time, busyness at the ward, and the lack of cooperation of patients as the main obstacles. The perception of a successful implementation is correlated with the perception of gained attention for sleep problems, the perception of increased care options, and the impression of effectiveness. Qualitative data showed that the effectiveness of the interventions was compromised by operational issues, commitment issues, adaptation to contextual limitations, and conflicting individual beliefs. We concluded that music-assisted relaxation is applicable in inpatient psychiatry. The application of stimulus control met with insurmountable operational issues. The nursing team is a very important factor for the implementation of evidence-based interventions at ward level. The lack of a shared urge for change and responsibility for continuity are important factors contributing to failure.     

Predicting Future Service Use in Dutch Mental Healthcare: A Machine Learning Approach

A mental healthcare system in which the scarce resources are equitably and efficiently allocated, benefits from a predictive model about expected service use. The skewness in service use is a challenge for such models. In this study, we applied a machine learning approach to forecast expected service use, as a starting point for agreements between financiers and suppliers of mental healthcare. This study used administrative data from a large mental healthcare organization in the Netherlands. A training set was selected using records from 2017 (N?=?10,911), and a test set was selected using records from 2018 (N?=?10,201). A baseline model and three random forest models were created from different types of input data to predict (the remainder of) numeric individual treatment hours. A visual analysis was performed on the individual predictions. Patients consumed 62 h of mental healthcare on average in 2018. The model that best predicted service use had a mean error of 21 min at the insurance group level and an average absolute error of 28 h at the patient level. There was a systematic under prediction of service use for high service use patients. The application of machine learning techniques on mental healthcare data is useful for predicting expected service on group level. The results indicate that these models could support financiers and suppliers of healthcare in the planning and allocation of resources. Nevertheless, uncertainty in the prediction of high-cost patients remains a challenge.

     

Review of systematic reviews about the efficacy of non-pharmacological interventions to improve sleep quality in insomnia

Background Insomnia is a very common condition in various populations. Non-pharmacological interventions might offer (safe) alternatives for hypnotics. Aim To evaluate the evidence for efficacy from systematic reviews about non-pharmacological interventions to improve sleep quality in insomnia by a systematic review of systematic reviews and meta-analyses. Search strategy Search strategies were conducted in the Database of Abstracts of Reviews of Effects (2002-July 2008), The Cochrane Database of Systematic Reviews (2000-July 2008) and PubMed (1950-July 2008). Sleep quality was the outcome measure of interest. Selection criteria Systematic reviews about the efficacy of one or more non-pharmacological interventions for insomnia, concerning both adult and elderly populations, were included. Reviews that included studies performed among populations suffering with severe neurological or cognitive impairments or with addictive disorders were excluded. Data analysis Relevant data were extracted. The quality of the reviews found was appraised by using the Overview Quality Assessment Questionnaire. The evidence was appraised and divided into six classes. Results and conclusions Sixteen reviews about 17 interventions were included. Six reviews were of adequate methodological quality. Of these, only one provided an effect size: a moderate effect was found for music-assisted relaxation. Weak evidence indicating a large effect was found for multicomponent cognitive behavioural therapy, progressive muscle relaxation, stimulus control and 'behavioural only'. Weak evidence indicating a moderate effect was found for paradoxical intention. Finally, weak evidence indicating a moderate to large effect was found for relaxation training. Because of the lack of sufficient methodological quality and the lack of calculated effect sizes, most of the included reviews were not suitable for drawing rigorous conclusions about the effect of non-pharmacological interventions on sleep quality in insomniacs. The non-pharmacological treatment of insomnia would benefit from renewed reviews based on a rigorous methodological approach.