A Pilot Study Evaluating the Physiological Parameters of Performance-Induced Stress in Undergraduate Music Students.

Music performance anxiety (MPA) is a specific condition for musicians. Although it can have a negative influence on their music careers, little attention is paid to this phenomenon both in the professional environment and in stress research. In the current pilot study, insight was gained into the physiology of the autonomic stress response related to anxiety in musicians when performing on stage by using a wearable biosensor patch for registration of a range of physiological parameters. Also, the validity of two different psychometric questionnaires in objectifying the stress response on stage to predict the individual stress response was explored. The autonomic physiological parameters (heart rate, respiratory rate, skin temperature) of 11 violists and violinists were collected while performing on stage and in resting state using the VitalConnect HealthPatch®. In addition, scores on validated questionnaires in research on MPA (State Anxiety Inventory, Kenny Music Performance Anxiety Inventory, Short Form Health Survey) were collected in order to try to objectify the magnitude of the subjective level of both MPA and experienced stress. The registration of the autonomic parameters showed a significant increase in heart rate, respiratory rate, and stress level from resting state measurements during stage performance. Analysis of heart rate variability showed a shift from indices of parasympathetic nervous system activity during baseline measurements towards indices of sympathetic nervous system activity during stress measurements. Surprisingly, none of the questionnaires was correlated to the physiological stress parameters on stage. In conclusion, the wearable biosensor patch proved to be an adequate tool to assess physiological stress parameters on stage. The different questionnaires did not contribute to the prediction of its occurrence in a group of musicians.

Effect of chronic somatic diseases on the course of late-life depression.

OBJECTIVE: To examine the influence of specific chronic somatic diseases and overall somatic diseases burden on the course of depression in older persons. METHODS: This was a prospective cohort study with a 2-year follow-up. Participants were depressed persons (n = 285) from the Netherlands Study of Depression in Older Persons. The presence of chronic somatic diseases was based on self-report. Diagnosis of depression was assessed with the Composite International Diagnostic Interview, and severity of depression was measured with the Inventory of Depressive Symptomatology Self-report. RESULTS: Cardiovascular diseases (odds ratio [OR] = 1.67, 95% confidence interval [CI] = 1.02-2.72, p = 0.041), musculoskeletal diseases (OR = 1.71, 95% CI = 1.04-2.80, p = 0.034), and the number of chronic somatic diseases (OR = 1.37, 95% CI = 1.16-1.63, p < 0.001) were associated with having a depressive disorder at 2-year follow-up. Furthermore, chronic non-specific lung diseases, cardiovascular diseases, musculoskeletal diseases, cancer, or cumulative somatic disease burden were associated with a chronic course of depression. CONCLUSIONS: Somatic disease burden is associated with a poor course of late-life depression. The course of late-life depression is particularly unfavorable in the presence of chronic non-specific lung diseases, cardiovascular diseases, musculoskeletal diseases, and cancer. Copyright © 2016 John Wiley & Sons, Ltd.

The development, implementation and evaluation of a transitional care programme to improve outcomes of frail older patients after hospitalisation.

BACKGROUND: fragmented healthcare systems are poorly suited to treat the increasing number of older patients with multimorbidity. OBJECTIVE: to report on the development, implementation and evaluation of a regional transitional care programme, aimed at improving the recovery rate of frail hospitalised older patients. METHODS: the programme was drafted in co-creation with organisations representing older adults, care providers and knowledge institutes. Conducting an action research project, the incidence of adverse outcomes within 3 months after hospital admission, and long-term care expenses (LTCE) were compared between samples in 2010-11 (pre-programme) and 2012-13 (post-programme) in frail and non-frail patients. Hospitalised patients aged ≥70 years were included in four hospitals in the targeted region. RESULTS: developed innovations addressed (i) improved risk management; (ii) delivery of integrated, function-oriented care; (iii) specific geriatric interventions; and (iv) optimisation of transfers. The incidence of adverse outcomes was compared in 813 and 904 included patients respectively in the two samples. In frail patients, the incidence of adverse outcomes decreased from 49.2% (149/303) in the pre-programme sample to 35.5% (130/366) in the post-programme sample. The risk ratio (RR), adjusted for heterogeneity between hospitals, was 0.72 (95% CI: 0.60-0.87). In non-frail patients the incidence of adverse outcomes remained unchanged (RR: 1.02, 95% CI: 0.76-1.36). LTCE were similar in the two samples. CONCLUSIONS: by involving stakeholders in designing and developing the transitional care programme, commitment of healthcare providers was secured. Feasible innovations in integrated transitional care for frail older patients after hospitalisation were sustainably implemented from within healthcare organisations.

Predicting outcomes of mood, anxiety and somatoform disorders: the Leiden routine outcome monitoring study.

BACKGROUND: Mood, anxiety and somatoform (MAS) disorders are highly prevalent disorders with substantial mutual comorbidity and a large disease burden. Early identification of patients at risk for poor outcome in routine clinical practice is of clinical importance. The purpose of this study was to predict outcomes in outpatients with MAS disorders using routine outcome monitoring (ROM) data. METHODS: We conducted a cohort study of 892 adult MAS patients in a naturalistic outpatient psychiatric specialty care setting and validated our results in a replication cohort of 1392 patients. Poor outcome was defined as a <50% reduction (compared to baseline) on the self-report brief symptom inventory (BSI) or a score of ≥3 on the observer-rated clinical global impression severity scale (CGI-S). During a follow-up of up to 2 years, Cox regression models were used to analyze the independent baseline predictors for poor outcome. RESULTS: In multivariable Cox regression models, independent and replicated predictors for poor outcome were higher age (overall p<0.001 for combined cohorts in multivariable Cox regression model), having comorbid MAS disorders or a somatoform disorder (<0.001), dysfunctional personality traits (i.e., tendency to self-harm [p<0.001], intimacy problems [p<0.001] and affective lability [p<0.001]), and a low reported general health status (p<0.001). LIMITATIONS: Detailed treatment information was not available. CONCLUSIONS: MAS patients meeting the profile of being elderly, suffering from comorbid MAS disorders or a somatoform disorder, with cluster B personality traits, and a poor reported general health may need special preventive measures to minimise the risk of poor outcome.

Predicting outcome of depression using the depressive symptom profile: the Leiden Routine Outcome Monitoring Study.

BACKGROUND: To investigate the predictive value of items for individual depressive symptoms measured with the self-rated Beck Depression Inventory-Revised (BDI-II) self-report scale on outcome in a large naturalistic cohort of depressive outpatients. METHODS: We used a cohort of 1,489 adult patients aged 18-65 years with major depressive disorder or dysthymic disorder established with the MINI-Plus diagnostic interview. All patients had a routine outcome monitoring baseline measurement in 2004-2009, with a maximum of 2 years follow-up. We used multivariable Cox regression models to predict remission (MADRS < 10; where MADRS stands for Montgomery-Åsberg Depression Rating Scale) and response (≥50% improvement), and adjusted for clinical and demographic characteristics (i.e. marital status, level of education, working status, comorbid anxiety, avoidant and borderline personality traits, and suicidality) that were identified as predictors in earlier studies. RESULTS: Of the 21 BDI-II items, the items "pessimism" and "loss of energy" independently predicted for both remission and response. For pessimism, the hazard ratio (HR) for remission was 0.81 (95% confidence interval [CI]: 0.73-0.89, P < .001) and for loss of energy, the HR was 0.81 (95% CI: 0.72-0.92, P = .001). CONCLUSIONS: These findings of robust prediction of poor outcome by baseline items of "pessimism" and "loss of energy" in a naturalistic treatment setting may help clinicians to identify depressive patients in need for additional or alternative therapeutic approaches.

Vitality predicts level of guideline-concordant care in routine treatment of mood, anxiety and somatoform disorders.

OBJECTIVE: To examine the clinical and psychosocial correlates of adherence to treatment guidelines among outpatients with common mental disorders in a routine clinical setting. METHODS: In this retrospective cohort study, we analysed 192 patients who were treated for a mood, anxiety or somatoform disorder with pharmacotherapy, psychotherapy or a combination of both treatment modalities. Guideline adherence was assessed with a disorder independent set of quality indicators during up to 3 years of follow-up. At baseline, a standardized diagnostic interview, the Brief Symptom Inventory (BSI), the Short Form 36 (SF-36) and demographic variables were assessed. Using multivariable regression analysis we identified independent predictors associated with guideline adherence. RESULTS: Patients were aged 36.8 years (SD 11.6) on average. The majority of patients were treated with psychotherapy (47.4%), followed by pharmacotherapy (37.5%) and a combination of pharmacotherapy and psychotherapy (15.1%). Three adherence groups were defined: low (29.7%), intermediate (43.2%) and high (27.1%). Univariate predictors of low adherence were low scores on the subscales vitality and social functioning of the SF-36. In the multivariable model, low adherence was independently predicted by a score lower than 50 on the subscale vitality of the SF-36 (odds ratio per 10 units increase in vitality = 1.34, 95% confidence interval: 1.06-1.71). No significant differences were found within socio-demographic variables, co-morbidity and the scores on the BSI subscales between the adherence groups. CONCLUSIONS: We found that patients with low scores on the vitality subscale of the SF-36 were at the highest risk to receive low guideline-concordant care. Understanding factors that affect treatment adherence may help to prevent non-adherence and increase the quality of care as well as cost-effectiveness.