Design of the Lifestyle Interventions for severe mentally ill Outpatients in the Netherlands (LION) trial; a cluster randomised controlled study of a multidimensional web tool intervention to improve cardiometabolic health in patients with severe mental illness

Background: The cardiometabolic health of persons with a severe mental illness (SMI) is alarming with obesity rates of 45-55% and diabetes type 2 rates of 10-15%. Unhealthy lifestyle behaviours play a large role in this. Despite the multidisciplinary guideline for SMI patients recommending to monitor and address patients' lifestyle, most mental health care professionals have limited lifestyle-related knowledge and skills, and (lifestyle) treatment protocols are lacking. Evidence-based practical lifestyle tools may support both patients and staff in improving patients' lifestyle. This paper describes the Lifestyle Interventions for severe mentally ill Outpatients in the Netherlands (LION) trial, to investigate whether a multidimensional lifestyle intervention using a web tool can be effective in improving cardiometabolic health in SMI patients. Methods/Design: The LION study is a 12-month pragmatic single-blind multi-site cluster randomised controlled trial. 21 Flexible Assertive Community Treatment (ACT) teams and eight sheltered living teams of five mental health organizations in the Netherlands are invited to participate. Per team, nurses are trained in motivational interviewing and use of the multidimensional web tool, covering lifestyle behaviour awareness, lifestyle knowledge, motivation and goal setting. Nurses coach patients to change their lifestyle using the web tool, motivational interviewing and stages-of-change techniques during biweekly sessions in a) assessing current lifestyle behaviour using the traffic light method (healthy behaviours colour green, unhealthy behaviours colour red), b) creating a lifestyle plan with maximum three attainable lifestyle goals and c) discussing the lifestyle plan regularly. The study population is SMI patients and statistical inference is on patient level using multilevel analyses. Primary outcome is waist circumference and other cardiometabolic risk factors after six and twelve months intervention, which are measured as part of routine outcome monitoring using standard protocols. Secondary outcomes include depressive and negative symptoms, cost-effectiveness, and barriers and facilitators in intervention implementation. Discussion: Adequate health care should target both mental health and lifestyle behaviours in SMI patients. This trial contributes by studying a 12-month multidimensional lifestyle intervention as a potential evidence based (nursing) tool for targeting multiple lifestyle behaviours in SMI patients

Multimodal lifestyle intervention using a web-based tool to improve cardiometabolic health in patients with serious mental illness:results of a cluster randomized controlled trial (LION)

Background: Unhealthy lifestyle behaviours contribute to alarming cardiometabolic risk in patients with serious mental illness (SMI). Evidence-based practical lifestyle tools supporting patients and staff in improving patient lifestyle are lacking. Methods: This multi-site randomized controlled pragmatic trial determined the effectiveness of a twelve-month multimodal lifestyle approach, including a web-based tool to improve patients' cardiometabolic health, versus care-as-usual. Using the web tool, nurses (trained in motivational interviewing) assisted patients in assessing their lifestyle behaviours, creating a risk profile and constructing lifestyle goals, which were discussed during fortnightly regular care visits. Twenty-seven community-care and sheltered-living teams were randomized into intervention (N=17) or control (N=10) groups, including 244 patients (140 intervention/104 control, 49.2% male, 46.1 +/- 10.8 years) with increased waist circumference (WC), BMI or fasting glucose. The primary outcomes concerned differences in WC after six and twelve months intervention, while BMI and metabolic syndrome Z-score were secondary outcome measures. Results: General multilevel linear mixed models adjusted for antipsychotic medication showed that differences in WC change between intervention and control were-0.15 cm (95%CI: -2.49; 2.19) after six and -1.03 cm (95%CI: -3.42; 1.35) after twelve months intervention; however, the differences were not statistically significant. No intervention effects were found for secondary outcome measures. The intervention increased patients' readiness to change dietary behaviour. Conclusion: A multimodal web-based intervention facilitating nurses to address lifestyle changes in SMI patients did not improve patient cardiometabolic health. Web-tool use was lower than expected and nurses need more lifestyle coaching knowledge and skills. The type of intervention and delivery mode need optimization to realize effective lifestyle care for SMI patients

Insights of Patients and Clinicians on the Promise of the Experience Sampling Method for Psychiatric Care

OBJECTIVE: This qualitative study aimed to map the relevance of the experience sampling method (ESM) for psychiatric practice and identify barriers and facilitators for implementation, as perceived by patients and clinicians. METHODS: Participants were 22 patients with various diagnoses and 21 clinicians (e.g., psychiatrists, psychologists) who participated in interviews or focus groups. Using Atlas.TI, the authors conducted qualitative thematic analysis to analyze the transcripts, resulting in four themes: applications, advantages, undesirable effects, and requirements for implementation of ESM in care. RESULTS: Clinicians and patients believed ESM could be relevant in every phase of care to increase patients' awareness, insight, and self-management; personalize interventions; and alert patients to rising symptoms. Further, ESM was expected to improve the patient-clinician relationship; lead to objective, personalized, reliable and visual data; and increase efficiency of care. However, participants warned against high assessment burden and potential symptom worsening. CONCLUSIONS: This study provides first evidence that the potential of ESM is recognized by both patients and clinicians. Key recommendations for optimal implementation of ESM in psychiatric care include flexible application of ESM, collaboration between patient and clinician, regular evaluation, awareness of negative reactivity, availability to patients with different psychiatric syndromes, and implementation by an interdisciplinary team of patients, clinicians, researchers, and information technology specialists

Life years lost for users of specialized mental healthcare

Background: Mental disorders are burdensome and are associated with increased mortality. Mortality has been researched for various mental disorders, especially in countries with national registries, including the Nordic countries. Yet, knowledge gaps exist around national differences, while also relatively less studies compare mortality of those seeking help for mental disorders in specialized mental healthcare (SMH) by diagnosis. Additional insight into such mortality distributions for SMH users would be beneficial for both policy and research purposes. We aim to describe and compare the mortality in a population of SMH users with the mortality of the general population. Additionally, we aim to investigate mortality differences between sexes and major diagnosis categories: anxiety, depression, schizophrenia spectrum and other psychotic disorders, and bipolar disorder.Methods: Mortality and basic demographics were available for a population of N = 10,914 SMH users in the north of The Netherlands from 2010 until 2017. To estimate mortality over the adult lifespan, parametric Gompertz distributions were fitted on observed mortality using interval regression. Life years lost were computed by calculating the difference between integrals of the survival functions for the general population and the study sample, thus correcting for age. Survival for the general population was obtained from Statistics Netherlands (CBS).Results: SMH users were estimated to lose 9.5 life years (95% CI: 9.4–9.6). Every major diagnosis category was associated with a significant loss of life years, ranging from 7.2 (95% CI: 6.4–7.9) years for anxiety patients to 11.7 (95% CI: 11.0–12.5) years for bipolar disorder patients. Significant differences in mortality were observed between male SMH users and female SMH users, with men losing relatively more life years: 11.0 (95% CI: 10.9–11.2) versus 8.3 (95% CI: 8.2–8.4) respectively. This difference was also observed between sexes within every diagnosis, although the difference was insignificant for bipolar disorder. Conclusion: There were significant differences in mortality between SMH users and the general population. Substantial differences were observed between sexes and between diagnoses. Additional attention is required, and possibly specific interventions are needed to reduce the amount of life years lost by SMH users.</p

Polygenic risk score for schizophrenia was not associated with glycemic level (HbA1c) in patients with non-affective psychosis:Genetic Risk and Outcome of Psychosis (GROUP) cohort study

Introduction: Type 2 diabetes (T2D) is a common comorbidity in patients with schizophrenia (SCZ). The underlying pathophysiologic mechanisms are yet to be fully elucidated, although it can be argued that shared genes, environmental factors or their interaction effect are involved. This study investigated the association between polygenic risk score of SCZ (PRSSCZ) and glycated haemoglobin (HbA1c) while adjusting for polygenic risk score of T2D (PRST2D), and clinical and demographic covariables. Methods: Genotype, clinical and demographic data of 1129 patients with non-affective psychosis were extracted from Genetic Risk and Outcome of Psychosis (GROUP) cohort study. The glycated haemoglobin (HbA1c) was the outcome. PRS was calculated using standard methods. Univariable and multivariable linear regression analyses were applied to estimate associations. Additionally, sensitivity analysis based on multiple imputation was done. After correction for multiple testing, a two-sided p-value ≤.003 was considered to discover evidence for an association. Results: Of 1129 patients, 75.8% were male with median age of 29 years. The mean (standard deviation) HbA1c level was 35.1 (5.9) mmol/mol. There was no evidence for an association between high HbA1c level and increased PRSSCZ (adjusted regression coefficient (aβ) = 0.69, standard error (SE) = 0.77, p-value =.37). On the other hand, there was evidence for an association between high HbA1c level and increased PRST2D (aβ = 0.93, SE = 0.32, p-value =.004), body mass index (aβ = 0.20, SE = 0.08, p-value =.01), diastolic blood pressure (aβ = 0.08, SE = 0.04, p-value =.03), late age of first psychosis onset (aβ = 0.19, SE = 0.05, p-value =.0004) and male gender (aβ = 1.58, SE = 0.81, p-value =.05). After multiple testing correction, there was evidence for an association between high HbA1c level and late age of first psychosis onset. Evidence for interaction effect between PRSscz and antipsychotics was not observed. The multiple imputation-based sensitivity analysis provided consistent results with complete case analysis. Conclusions: Glycemic dysregulation in patients with SCZ was not associated with PRSSCZ. This suggests that the mechanisms of hyperglycemia or diabetes are at least partly independent from genetic predisposition to SCZ. Our findings show that the change in HbA1c level can be caused by at least in part due to PRST2D, late age of illness onset, male gender, and increased body mass index and diastolic blood pressure

Do routine outcome monitoring results translate to clinical practice? A cross-sectional study in patients with a psychotic disorder

Background: The use of Routine Outcome Monitoring (ROM) in mental health care has increased widely during the past decade. Little is known, however, on the implementation and applicability of ROM outcome in daily clinical practice. In the Netherlands, an extensive ROM-protocol for patients with psychotic disorders has been implemented over the last years (ROM-Phamous). The current study investigated to what extent ROM results translate to daily clinical practice. Therefore, we investigated whether clinical problems as identified with ROM were detected and used in the treatment of patients with psychotic disorders. Methods: Out of the ROM database of 2010 (n = 1040), a random sample of 100 patients diagnosed with a psychotic disorder was drawn. ROM-data used in this study included a physical examination, laboratory tests, interviews and self-report questionnaires. Based on these data, the prevalence of positive and negative symptoms, psychosocial problems and cardiovascular risk factors was determined. Next, we investigated whether these problems, as identified with ROM, were reflected in the treatment plans of patients, as an indication of the use of ROM in clinical practice. Results: The sample consisted of 63 males and 37 females. The mean age was 44 and the mean duration of illness was 17.7 years. The prevalence of positive and negative symptoms, psychosocial problems and cardiovascular risk factors ranged from 11 to 86 %. In the majority of cases, problems as identified with ROM were not reflected in the treatment plans of patients. Conclusions: We found a substantial discrepancy between the ROM measurements and the treatment plans, i.e. low rates of detection of symptoms, psychosocial problems and cardiovascular risk factors in the treatment plans, even though these problems were identified with ROM. The opposite occurred as well, where problems were reflected in the treatment plans but not identified with ROM. Thus, ROM and daily clinical practice appear to be two separate processes, whereas ideally they should be integrated. Strong efforts should be made to integrate ROM and consequent treatment activities. Such integration may help to provide patients with adequate and customized care and simultaneously minimize under-and over-treatment