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Personal recovery transcends illness and is a unifying human experience. Core elements in personal recovery are hope, meaning, and rebuilding oneself. Here we aim to investigate whether factors associated with personal recovery in patients with non-affective psychosis, unaffected siblings and healthy controls are similar. We investigated the association between personal recovery and resilience, social support, socio-demographic and illness-related variables in 580 patients, 630 siblings, and 351 healthy controls who participated in the Genetic Risk and Outcome of Psychosis (GROUP) study. Bi-variate associations between personal recovery and individual variables were assessed and multiple linear regression analyses were performed to estimate the proportion of variance in personal recovery that could be accounted for by the predictors and to investigate which predictors independently added to the model. Positive self was significantly and independently associated with personal recovery in all three groups. Pro-active action taking also seems to be important. Social functioning significantly contributed to explained variance in patients and siblings. Regarding illness-related factors, depressive symptoms had impact on personal recovery in both patients and siblings, whereas positive symptoms only did in siblings. The findings imply that not only personal recovery itself, but also some associated factors are universally human and suit us all. This means that patients and non-patients share supportive factors of personal recovery which may help to reach mutual understanding. Recovery-oriented practices and mental health services might be more effective when focusing also on improving self-image, functional coping styles and generating social interaction, next to the reduction of affective symptoms.

Migrants and their offspring are at increased risk of developing mental disorders. Previous research has shown associations between adverse social factors (e.g., discrimination, lack of social support) and mental health problems in migrants, but it is unknown how these associations are understood by migrants themselves. In this study, we aimed to gain explorative insight into the way young Moroccan-Dutch people experience their social environment, and how they relate this social environment to the development of mental health problems. At www.marokko.nl , the largest online discussion platform for young Moroccan-Dutch people, contributors discuss a broad variety of subjects, including societal, cultural, religious, and mental health issues. Combining deductive and inductive approaches to qualitative data analysis, we analysed 22 forum discussions at marokko.nl about mental health problems, after which data saturation was reached. Contributors described feeling isolated and experiencing discrimination in their social environment. Contributor comments identified social challenges arising from Dutch society, Dutch culture (e.g., being too individualistic), Moroccan culture (e.g., strict parenting style), and living between these two cultures. These social challenges are perceived to be associated with mental health problems. Furthermore, we created a model describing the different types of explanations contributors used for mental health problems, being: religious (e.g., possession); medical (i.e., a bio-psycho-social cause); or a combination of both. This model can help clinicians in delivering culturally sensitive mental health care. Lastly, this study shows the taboo on mental health problems in the Moroccan-Dutch population and the opportunity to open up in the online environment.

Background. Bipolar disorder (BD) is a chronic psychiatric condition characterized by large episodic changes in mood and energy. Recently, BD has been proposed to be conceptualized as chronic cyclical mood instability, as opposed to the traditional view of alternating discrete episodes with stable periods in-between. Recognizing this mood instability may improve care and calls for high-frequency measures coupled with advanced statistical models. Methods. To uncover empirically derived mood states, a multilevel hidden Markov model (HMM) was applied to 4-month ecological momentary assessment (EMA) data in twenty patients with BD, yielding ~9.820 assessments in total. EMA data comprised self-report questionnaires (5x daily) measuring manic and depressive constructs. Manic and depressive symptoms were also assessed weekly using the Altman Self-Rating Mania Scale and the Quick Inventory for Depressive Symptomatology Self-Report. Alignment between HMM-uncovered momentary mood states and weekly questionnaires was assessed with a multilevel linear model.Results. HMM uncovered four mood states (euthymic, manic, mixed, and depressive) that aligned with weekly symptom scores. Mood states switched more frequently than weekly data suggested. On average, patients remained

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.

Background The internet enables sharing of narratives about health concerns on a substantial scale, and some digital health narratives have been integrated into digital health interventions. Narratives describing recovery from health problems are a focus of research, including those presented in recorded (eg, invariant) form. No clinical trial has been conducted on a web-based intervention providing access to a collection of Recorded Recovery Narratives (RRNs). Objective This study presents knowledge produced through the development of the Narrative Experiences Online (NEON) Intervention, a web-based intervention incorporating the algorithmic recommendation of RRNs. Methods Knowledge was gathered through knowledge integration (KI) activities. KI1 synthesized previous studies to produce the NEON Impact Model describing how accessing RRNs produces health-related outcomes. KI2 developed curation principles for the NEON Collection of RRNs through consultation with the NEON Lived Experience Advisory Panel and the curation of a preliminary collection. KI3 identified harm minimization strategies for the NEON Intervention through consultation with the NEON International Advisory Board and Lived Experience Advisory Panel. The NEON Intervention was finalized through 2 research studies (RS). In RS1, mental health service users (N=40) rated the immediate impact of randomly presented narratives to validate narrative feedback questions used to inform the recommendation algorithm. In RS2, mental health service users (n=25) were interviewed about their immediate response to a prototype of the NEON Intervention and trial procedures and then were interviewed again after 1 month of use. The usability and acceptability of the prototype and trial procedures were evaluated and refinements were made. Results KI1 produced the NEON Impact Model, which identifies moderators (recipient and context), mechanisms of connection (reflection, comparison, learning, and empathy), processes (identification of change from narrative structure or content and internalization of observed change), and outcomes (helpful and unhelpful). KI2 identified 22 curation principles, including a mission to build a large, heterogeneous collection to maximize opportunities for connection. KI3 identified seven harm minimization strategies, including content warnings, proactive and reactive blocking of narratives, and providing resources for the self-management of emotional distress. RS1 found variation in the impact of narratives on different participants, indicating that participant-level feedback on individual narratives is needed to inform a recommender system. The order of presentation did not predict narrative feedback. RS2 identified amendments to web-based trial procedures and the NEON Intervention. Participants accessed some narratives multiple times, use reduced over the 4-week period, and narrative feedback was provided for 31.8% (105/330) of narrative accesses. Conclusions RRNs can be integrated into web-based interventions. Evaluating the NEON Intervention in a clinical trial is feasible. The mixed methods design for developing the NEON Intervention can guide its extension to other clinical populations, the design of other web-based mental health interventions, and the development of narrative-based interventions in mental health.

Background Self-monitoring has been shown to improve the self-management and treatment of patients with bipolar disorder. However, current self-monitoring methods are limited to once-daily retrospectively assessed mood, which may not suit the rapid mood fluctuations in bipolar disorder. The experience sampling method (ESM), which assesses mood in real-time several times a day, may overcome these limitations. This study set out to assess the experiences of patients and clinicians with the addition of ESM monitoring, real-time alerts, and personalized feedback to clinical care. Participants were twenty patients with bipolar disorder type I/II and their clinicians. For four months, patients completed five ESM assessments per day on mood, symptoms, and activities. Weekly symptom questionnaires alerted patients and clinicians to potential episodes. After the monitoring, a personalized feedback report based on the patient’s data was discussed between patient and clinician. Three months later, patient and clinician were both interviewed. Results Thematic analysis of the transcripts resulted in four themes: perceived effects of the monitoring, alerts, and feedback, and recommendations for implementation of ESM. ESM was perceived as helping patients to cope better with their disorder by increasing awareness, offering new insights, and encouraging life style adjustments. ESM was further believed to facilitate communication between patient and clinician and to lead to new treatment directions. However, high assessment burden and pre-occupation with negative mood and having a disorder were also described. Patients and clinicians advocated for increased personalization and embedding of ESM in care. Conclusions This study demonstrates that long-term ESM monitoring, alerts, and personalized feedback are perceived as beneficial to the treatment and self-management of patients with bipolar disorder. Future research should further test the clinical utility of ESM. Clinically relevant feedback and technology need to be developed to enable personalized integration of ESM in clinical care.

BACKGROUND The internet enables sharing of narratives about health concerns on a substantial scale, and some digital health narratives have been integrated into digital health interventions. Narratives describing recovery from health problems are a focus of research, including those presented in recorded (eg, invariant) form. No clinical trial has been conducted on a web-based intervention providing access to a collection of Recorded Recovery Narratives (RRNs). OBJECTIVE This study presents knowledge produced through the development of the Narrative Experiences Online (NEON) Intervention, a web-based intervention incorporating the algorithmic recommendation of RRNs. METHODS Knowledge was gathered through knowledge integration (KI) activities. KI1 synthesized previous studies to produce the NEON Impact Model describing how accessing RRNs produces health-related outcomes. KI2 developed curation principles for the NEON Collection of RRNs through consultation with the NEON Lived Experience Advisory Panel and the curation of a preliminary collection. KI3 identified harm minimization strategies for the NEON Intervention through consultation with the NEON International Advisory Board and Lived Experience Advisory Panel. The NEON Intervention was finalized through 2 research studies (RS). In RS1, mental health service users (N=40) rated the immediate impact of randomly presented narratives to validate narrative feedback questions used to inform the recommendation algorithm. In RS2, mental health service users (n=25) were interviewed about their immediate response to a prototype of the NEON Intervention and trial procedures and then were interviewed again after 1 month of use. The usability and acceptability of the prototype and trial procedures were evaluated and refinements were made. RESULTS KI1 produced the NEON Impact Model, which identifies moderators (recipient and context), mechanisms of connection (reflection, comparison, learning, and empathy), processes (identification of change from narrative structure or content and internalization of observed change), and outcomes (helpful and unhelpful). KI2 identified 22 curation principles, including a mission to build a large, heterogeneous collection to maximize opportunities for connection. KI3 identified seven harm minimization strategies, including content warnings, proactive and reactive blocking of narratives, and providing resources for the self-management of emotional distress. RS1 found variation in the impact of narratives on different participants, indicating that participant-level feedback on individual narratives is needed to inform a recommender system. The order of presentation did not predict narrative feedback. RS2 identified amendments to web-based trial procedures and the NEON Intervention. Participants accessed some narratives multiple times, use reduced over the 4-week period, and narrative feedback was provided for 31.8% (105/330) of narrative accesses. CONCLUSIONS RRNs can be integrated into web-based interventions. Evaluating the NEON Intervention in a clinical trial is feasible. The mixed methods design for developing the NEON Intervention can guide its extension to other clinical populations, the design of other web-based mental health interventions, and the development of narrative-based interventions in mental health.

Background Mental health recovery narratives are a core component of recovery-oriented interventions such as peer support and anti-stigma campaigns. A substantial number of recorded recovery narratives are now publicly available online in different modalities and in published books. Whilst the benefits of telling one’s story have been investigated, much less is known about how recorded narratives of differing modalities impact on recipients. A previous qualitative study identified connection to the narrator and/or to events in the narrative to be a core mechanism of change. The factors that influence how individuals connect with a recorded narrative are unknown. The aim of the current study was to characterise the immediate effects of receiving recovery narratives presented in a range of modalities (text, video and audio), by establishing the mechanisms of connection and the processes by which connection leads to outcomes. Method A study involving 40 mental health service users in England was conducted. Participants were presented with up to 10 randomly-selected recovery narratives and were interviewed on the immediate impact of each narrative. Thematic analysis was used to identify the mechanisms of connection and how connection leads to outcome. Results Receiving a recovery narrative led participants to reflect upon their own experiences or those of others, which then led to connection through three mechanisms: comparing oneself with the narrative and narrator; learning about other’s experiences; and experiencing empathy. These mechanisms led to outcomes through three processes: the identification of change (through attending to narrative structure); the interpretation of change (through attending to narrative content); and the internalisation of interpretations. Conclusions This is the first study to identify mechanisms and processes of connection with recorded recovery narratives. The empirically-based causal chain model developed in this study describes the immediate effects on recipients. This model can inform selection of narratives for use in interventions, and be used to support peer support workers in recounting their own recovery narratives in ways which are maximally beneficial to others.

Children from families with a mental illness are at risk of developing negative health outcomes. Online interventions are a new way to offer support to these children. The present study utilized a website that had been developed to support Dutch youth who had a family member with a mental illness. The objective was to analyse monitored and unmonitored chatroom conversations among these young people, and specifically to compare supportive messages and self-disclosures of experiences. We electronically imported session transcripts of 34 chatroom conversations into the qualitative analysis software Atlas.ti. A content analysis was performed on 4252 messages from 22 female participants. A correlational analysis was then conducted to identify significant associations between sent and received supportive statements and disclosing statements. We found supporting comments in approximately 34% of the conversations and disclosures of problems in the home in approximately 15-18% of the messages. Participants made approximately twice as many disclosing statements and approximately half as many supportive statements in the monitored sessions compared to the unmonitored sessions. The number of disclosures that were sent was positively correlated with the amount of social support that was received. The number of disclosures sent was negatively correlated with the amount of social support that was sent, but only in the unmonitored sessions. Considering the greater reach of Internet interventions, online chatroom sessions might be provided as complementary to, or as an alternative to, face-to-face groups for supporting youth with a family member who has a mental illness.

OBJECTIVE: Allostatic load (AL) reflects the deteriorating influences of stress on the body, and comprises a selection of biological markers. AL is associated with negative life events, stress, and negative affect (NA), as well as poor health outcomes. However, whether AL is also associated with positive affect (PA) is not clear. The present study therefore explores the association between PA and AL, accounting for age, sex, NA, and health behaviors.METHODS: Data of 45,225 individuals from the first wave of the multi-disciplinary prospective population-based cohort study Lifelines were used. AL was operationalized as the sum of twelve inflammatory, cardiovascular, and metabolic markers. The association between PA and AL was tested in a cross-sectional study design using multiple linear regression analysis, adjusting for NA, confounders, and health behaviors. In addition, we explored whether the relation was moderated by age, sex and NA.RESULTS: The AL profile was inversely associated with PA (B = -0.083, pCONCLUSIONS: PA was associated with a more favorable AL profile, especially in women. These results add to the evidence that PA might be of relevance to the etiology of disease.

The aim of the present study was to explore the strengths children reported to have acquired while coping with their parents illness, and the external factors these children indicated had facilitated their coping process. A systematic literature search was conducted of peer-reviewed papers that focused on self-reported experiences of children with parents who had mental illness, and revealed their strengths and resources. The search included the following databases: MEDLINE, PsycINFO, and CINAHL. Results were filtered according to whether search terms appeared in the title or abstract. Fifty-seven full-text papers were reviewed; 26 of them met the inclusion criteria and were included in the review. The statements were analysed using content analysis. The search identified 160 relevant statements, 38 (24%) of which could be described as self-reported strengths, and 122 (76%) as self-reported resources. According to these statements, the children described themselves as more mature, independent, and empathic than their peers who did not have a parent with a mental illness, and as having acquired several abilities. The statements about resources indicated that the children regarded social support, information, and particularly the support of mental health-care professionals as helpful when living with a parent with a mental illness. Recommendations for nursing actions to support children's ability to cope with their parents' illness are outlined.

HowNutsAreTheDutch (Dutch: HoeGekIsNL) is a national crowdsourcing study designed to investigate multiple continuous mental health dimensions in a sample from the general population (n = 12,503). Its main objective is to create an empirically based representation of mental strengths and vulnerabilities, accounting for (i) dimensionality and heterogeneity, (ii) interactivity between symptoms and strengths, and (iii) intra-individual variability. To do so, HowNutsAreTheDutch (HND) makes use of an internet platform that allows participants to (a) compare themselves to other participants via cross-sectional questionnaires and (b) to monitor themselves three times a day for 30 days with an intensive longitudinal diary study via their smartphone. These data enable for personalized feedback to participants, a study of profiles of mental strengths and weaknesses, and zooming into the fine-grained level of dynamic relationships between variables over time. Measuring both psychiatric symptomatology and mental strengths and resources enables for an investigation of their interactions, which may underlie the wide variety of observed mental states in the population. The present paper describes the applied methods and technology, and presents the sample characteristics. Copyright © 2015 John Wiley & Sons, Ltd.

Introduction: Migration is seen as a risk factor for developing psychiatric symptoms and experiencing social exclusion. In the Netherlands, the Moroccan-Dutch population is the second largest migrant group. 70% of all young Moroccan-Dutch people meet each other in the online community www. marokko. nl. Within this community, we investigated the association between experiences of social exclusion and self-reported depressive symptoms and psychotic experiences.Materials and methods: Participants were recruited via the website www. marokko. nl. They completed an online survey, with screening instruments for depressive symptoms (K10) and psychotic experiences (PQ-16), measures of social exclusion ( perceived discrimination, social defeat and social support), and questions about demographical information. With regression analysis the association between social exclusion and psychiatric symptoms was investigated.Results: We included 267 participants; 87% were female. 27% of the sample has received mental healthcare in the past. Over 50% of these people screened positive for depressive symptoms and psychotic experiences. Perceived discrimination and social defeat were significantly associated with psychotic experiences and social defeat was associated with depressive symptoms. Social support and higher education were associated with less depressive symptoms and psychotic experiences.Discussion: Our findings suggest that the online environment allows for epidemiological research and early symptom detection. Levels of psychopathology were high in our sample. This suggests that a part of this young ethnic minority population might not get adequate mental healthcare. Since this population can be reached through Internet, the online environment may therefore also offer an appropriate setting for intervention, to increase resilience towards social exclusion.

The aim of this review was to investigate to what extent information technology may support self-management among service users with psychotic disorders. The investigation aimed to answer the following questions: What types of e mental health self-management interventions have been developed and evaluated? What is the current evidence on clinical outcome and cost-effectiveness of the identified interventions? To what extent are e mental health self-management interventions oriented toward the service user? Methods: A systematic review of references through July 2012 derived from MEDLINE, PsycINFO, AMED, CINAHL, and the Library, Information Science and Technology database was performed. Studies of e mental health self-management interventions for persons with psychotic disorders were selected independently by three reviewers. Results: Twenty-eight studies met the inclusion criteria. E mental health self-management interventions included psycho-education, medication management, communication and shared decision making, management of daily functioning, lifestyle management, peer support, and real-time self-monitoring by daily measurements (experience sampling monitoring). Summary effect sizes were large for medication management (.92) and small for psychoeducation (.37) and communication and shared decision making (.21). For all other studies, individual effect sizes were calculated. The only economic analysis conducted reported more short-term costs for the e mental health intervention. Conclusions: People with psychotic disorders were able and willing to use e mental health services. Results suggest that e mental health services are at least as effective as usual care or nontechnological approaches. Larger effects were found for medication management e mental health services. No studies reported a negative effect. Results must be interpreted cautiously, because they are based on a small number of studies.

The results of routine patient assessments in psychiatric healthcare in the Northern Netherlands are primarily used to support clinicians. We developed Wegweis, a web-based advice platform, to make this data accessible and understandable for patients.Objective: We show that a fully automated explanation and interpretation of assessment results for schizophrenia patients, which prioritizes the information in the same way that a clinician would, is possible and is considered helpful and relevant by patients. The goal is not to replace the clinician but rather to function as a second perspective and to enable patient empowerment through knowledge.Methods: We have developed and implemented an ontology-based approach for selecting and ranking information for schizophrenia patients based on their routine assessment results. Our approach ranks information by severity of associated schizophrenia-related problems and uses an ontology to decouple problems from advice, which adds robustness to the system, because advice can be inferred for problems that have no exact match.Results: We created a problem ontology, validated by a group of experts, to combine and interpret the results of multiple schizophrenia-specific questionnaires. We designed and implemented a novel ontology-based algorithm for ranking and selecting advice, based on questionnaire answers. We designed, implemented, and illustrated Wegweis, a proof of concept for our algorithm, and, to the best of our knowledge, the first fully automated interpretation of assessment results for patients suffering from schizophrenia. We evaluated the system vis-a-vis the opinions of clinicians and patients in two experiments. For the task of identifying important problems based on MANSA questionnaires (the MANSA is a satisfaction questionnaire commonly used in schizophrenia assessments), our system corresponds to the opinion of clinicians 94% of the time for the first three problems and 72% of the time, overall. Patients find two out of the first three advice topics selected by the system to be relevant and roughly half of the advice topics overall.Conclusions: Our findings suggest that an approach that uses problem severities to identify important problems for a patient corresponds closely to the way a clinician thinks. Furthermore, after applying a severity threshold, the majority of advice units selected by the system are considered relevant by the patients. Our findings pave the way for the development of systems that facilitate patient-centered care for chronic illnesses by automating the sharing of assessment results between patient and clinician. (C) 2013 Elsevier B.V. All rights reserved.

In dit artikel gaan we in opWegweis, een onderzoeksproject dat zich bezighoudt met e-health ontwikkelingen voor mensen met een psychotische kwetsbaarheid. Allereerst vertellen we iets over technologische ontwikkelingen voor de doelgroep. Daarna volgt een beschrijving van een trial die vanuit hetWegweisproject is opgezet. Tenslotte bespreken we mogelijke implicaties voor de klinische praktijk.

Objective: Recent developments in research and mobile health enable a quantitative idiographic approach in health research. The present study investigates the potential of an electronic diary crowdsourcing study in the Netherlands for (1) large-scale automated self-assessment for individual-based health promotion and (2) enabling research at both the between-persons and within-persons level. To illustrate the latter, we examined between-persons and within-persons associations between somatic symptoms and quality of life.Methods: A website provided the general Dutch population access to a 30-day (3 times a day) diary study assessing 43 items related to health and well-being, which gave participants personalized feedback. Associations between somatic symptoms and quality of life were examined with a linear mixed model.Results: A total of 629 participants completed 28,430 assessments, with a mean (SD) of 45 (32) assessments per participant. Most participants (n = 517 [82%]) were women and 531 (84%) had high education. Almost 40% of the participants (n = 247) completed enough assessments (t = 68) to generate personalized feedback including temporal dynamics between well-being, health behavior, and emotions. Substantial between-person variability was found in the within-person association between somatic symptoms and quality of life.Conclusions: We successfully built an application for automated diary assessments and personalized feedback. The application was used by a sample of mainly highly educated women, which suggests that the potential of our intensive diary assessment method for large-scale health promotion is limited. However, a rich data set was collected that allows for group-level and idiographic analyses that can shed light on etiological processes and may contribute to the development of empirical-based health promotion solutions.

Finding the best vector autoregression model for any dataset, medical or otherwise, is a process that, to this day, is frequently performed manually in an iterative manner requiring a statistical expertize and time. Very few software solutions for automating this process exist, and they still require statistical expertize to operate. We propose a new application called Autovar, for the automation of finding vector autoregression models for time series data. The approach closely resembles the way in which experts work manually. Our proposal offers improvements over the manual approach by leveraging computing power, e.g., by considering multiple alternatives instead of choosing just one. In this paper, we describe the design and implementation of Autovar, we compare its performance against experts working manually, and we compare its features to those of the most used commercial solution available today. The main contribution of Autovar is to show that vector autoregression on a large scale is feasible. We show that an exhaustive approach for model selection can be relatively safe to use. This study forms an important step toward making adaptive, personalized treatment available and affordable for all branches of healthcare.

Background: Clinical guidelines for the treatment of people experiencing psychosis have existed for over a decade, but implementation of recommended interventions is limited. Identifying influences on implementation may help to reduce this translational gap. The Structured Assessment of Feasibility (SAFE) measure is a standardised assessment of implementation blocks and enablers. The aim of this study was to characterise and compare the implementation blocks and enablers for recommended psychosis interventions.Methods: SAFE was used to evaluate and compare three groups of interventions recommended in the 2014 NICE psychosis guideline: pharmacological (43 trials testing 5 interventions), psychosocial (65 trials testing 5 interventions), and recovery (19 trials testing 5 interventions). The 127 trial reports rated with SAFE were supplemented by published intervention manuals, research protocols, trial registrations and design papers. Differences in the number of blocks and enablers across the three interventions were tested statistically, and feasibility profiles were generated.Results: There was no difference between psychosocial and recovery interventions in the number of blocks or enablers to implementation. Pharmacological interventions (a) had fewer blocks than both psychosocial interventions (X-2(3) = 133.77, p Conclusions: Feasibility profiles show that pharmacological interventions are relatively easy to implement but can sometimes involve risks. Psychosocial and recovery interventions are relatively complex but tend to be more flexible and more often manualised. SAFE ratings can contribute to tackling the current implementation challenges in mental health services, by providing a reporting guideline structure for researchers to maximise the potential for implementation and by informing prioritisation decisions by clinical guideline developers and service managers.

HowNutsAreTheDutch (Dutch: HoeGekIsNL) is a national crowdsourcing study designed to investigate multiple continuous mental health dimensions in a sample from the general population (n = 12,503). Its main objective is to create an empirically based representation of mental strengths and vulnerabilities, accounting for (i) dimensionality and heterogeneity, (ii) interactivity between symptoms and strengths, and (iii) intra‐individual variability. To do so, HowNutsAreTheDutch (HND) makes use of an internet platform that allows participants to (a) compare themselves to other participants via cross‐sectional questionnaires and (b) to monitor themselves three times a day for 30 days with an intensive longitudinal diary study via their smartphone. These data enable for personalized feedback to participants, a study of profiles of mental strengths and weaknesses, and zooming into the fine‐grained level of dynamic relationships between variables over time. Measuring both psychiatric symptomatology and mental strengths and resources enables for an investigation of their interactions, which may underlie the wide variety of observed mental states in the population. The present paper describes the applied methods and technology, and presents the sample characteristics. Copyright © 2015 John Wiley & Sons, Ltd.

BackgroundHealth promotion can be tailored by combining ecological momentary assessments (EMA) with time series analysis. This combined method allows for studying the temporal order of dynamic relationships among variables, which may provide concrete indications for intervention. However, application of this method in health care practice is hampered because analyses are conducted manually and advanced statistical expertise is required. ObjectiveThis study aims to show how this limitation can be overcome by introducing automated vector autoregressive modeling (VAR) of EMA data and to evaluate its feasibility through comparisons with results of previously published manual analyses. MethodsWe developed a Web-based open source application, called AutoVAR, which automates time series analyses of EMA data and provides output that is intended to be interpretable by nonexperts. The statistical technique we used was VAR. AutoVAR tests and evaluates all possible VAR models within a given combinatorial search space and summarizes their results, thereby replacing the researcher’s tasks of conducting the analysis, making an informed selection of models, and choosing the best model. We compared the output of AutoVAR to the output of a previously published manual analysis (n=4). ResultsAn illustrative example consisting of 4 analyses was provided. Compared to the manual output, the AutoVAR output presents similar model characteristics and statistical results in terms of the Akaike information criterion, the Bayesian information criterion, and the test statistic of the Granger causality test. ConclusionsResults suggest that automated analysis and interpretation of times series is feasible. Compared to a manual procedure, the automated procedure is more robust and can save days of time. These findings may pave the way for using time series analysis for health promotion on a larger scale. AutoVAR was evaluated using the results of a previously conducted manual analysis. Analysis of additional datasets is needed in order to validate and refine the application for general use.

Introduction Migration is a risk factor for the onset of psychopathology. A range of social factors may play a role in the aetiology of psychiatric disorders in migrants. A better understanding of these associations is needed to develop preventive interventions to reduce the disease burden in the migrant population. Research among minority groups is generally time consuming and it is difficult to recruit participants. Internet can offer interesting new possibilities to conduct research among ethnic minorities. This article describes the design of an epidemiological study in the Moroccan-Dutch population, which will be entirely performed online. We investigate the association between social factors and psychopathology.Methods and analysis The website Marokko.nl is visited by 70% of the young Moroccan-Dutch population in the Netherlands. This website therefore provides a unique possibility for research within this population. We will conduct a survey with online questionnaires via this website. The online survey consists of several validated short self-report questionnaires, measuring depressive and anxiety symptoms (The Kessler Psychological Distress Scale (K10)), psychotic symptoms (The Prodromal Questionnaire-16 (PQ-16)) and instruments measuring discrimination, social support and social defeat. Furthermore, demographic characteristics are collected. We will use univariate and multivariate methods for analysing the data.Ethics and dissemination The local medical ethical committee has assessed the study protocol and judged that the study could be conducted without their approval. Knowledge dissemination will take place through peer-reviewed publication in scientific journals as well as publication for participants on the project website.Discussion In this study we further explore the association between psychopathology and social factors within an online Moroccan-Dutch sample. The recruitment of participants via the website Marokko.nl creates a big advantage in collecting a large sample of a specific migrant population. Strengths and limitations of the methodology are discussed. Furthermore, we review the advantages and challenges of online epidemiological research methods.

We examined agreement between the CANSAS self-report version (CANSAS-P) and the Camberwell Assessment of Need (CAN) interview in 200 long-term patients with affective and psychotic disorders. Intra-class correlations were fair to good for unmet needs. Overall, more unmet needs were reported on the CANSAS-P than in the CAN interview. No differences were found for patients with psychotic versus affective disorders. We conclude from this that the CANSAS-P is a promising screening instrument to detect unmet needs in people with severe mental illnesses. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

BackgroundMental health policy makers encourage the development of electronic decision aids to increase patient participation in medical decision making. Evidence is needed to determine whether these decision aids are helpful in clinical practice and whether they lead to increased patient involvement and better outcomes. ObjectiveThis study reports the outcome of a randomized controlled trial and process evaluation of a Web-based intervention to facilitate shared decision making for people with psychotic disorders. MethodsThe study was carried out in a Dutch mental health institution. Patients were recruited from 2 outpatient teams for patients with psychosis (N=250). Patients in the intervention condition (n=124) were provided an account to access a Web-based information and decision tool aimed to support patients in acquiring an overview of their needs and appropriate treatment options provided by their mental health care organization. Patients were given the opportunity to use the Web-based tool either on their own (at their home computer or at a computer of the service) or with the support of an assistant. Patients in the control group received care as usual (n=126). Half of the patients in the sample were patients experiencing a first episode of psychosis; the other half were patients with a chronic psychosis. Primary outcome was patient-perceived involvement in medical decision making, measured with the Combined Outcome Measure for Risk Communication and Treatment Decision-making Effectiveness (COMRADE). Process evaluation consisted of questionnaire-based surveys, open interviews, and researcher observation. ResultsIn all, 73 patients completed the follow-up measurement and were included in the final analysis (response rate 29.2%). More than one-third (48/124, 38.7%) of the patients who were provided access to the Web-based decision aid used it, and most used its full functionality. No differences were found between the intervention and control conditions on perceived involvement in medical decision making (COMRADE satisfaction with communication: F1,68=0.422, P=.52; COMRADE confidence in decision: F1,67=0.086, P=.77). In addition, results of the process evaluation suggest that the intervention did not optimally fit in with routine practice of the participating teams. ConclusionsThe development of electronic decision aids to facilitate shared medical decision making is encouraged and many people with a psychotic disorder can work with them. This holds for both first-episode patients and long-term care patients, although the latter group might need more assistance. However, results of this paper could not support the assumption that the use of electronic decision aids increases patient involvement in medical decision making. This may be because of weak implementation of the study protocol and a low response rate. Trial RegistrationDutch Trial Register (NTR) trial number: 10340; http://www.trialregister.nl/trialreg/admin/rctsearch.asp?Term=10340 (Archived by WebCite at http://www.webcitation.org/6Jj5umAeS).

BackgroundRoutine Outcome Monitoring (ROM) is a systematic way of assessing service users’ health conditions for the purpose of better aiding their care. ROM consists of various measures used to assess a service user’s physical, psychological, and social condition. While ROM is becoming increasingly important in the mental health care sector, one of its weaknesses is that ROM is not always sufficiently service user-oriented. First, clinicians tend to concentrate on those ROM results that provide information about clinical symptoms and functioning, whereas it has been suggested that a service user-oriented approach needs to focus on personal recovery. Second, service users have limited access to ROM results and they are often not equipped to interpret them. These problems need to be addressed, as access to resources and the opportunity to share decision making has been indicated as a prerequisite for service users to become a more equal partner in communication with their clinicians. Furthermore, shared decision making has been shown to improve the therapeutic alliance and to lead to better care. ObjectiveOur aim is to build a web-based support system which makes ROM results more accessible to service users and to provide them with more concrete and personalized information about their functioning (ie, symptoms, housing, social contacts) that they can use to discuss treatment options with their clinician. In this study, we will report on the usability of the web-based support system for service users with schizophrenia. MethodsFirst, we developed a prototype of a web-based support system in a multidisciplinary project team, including end-users. We then conducted a usability study of the support system consisting of (1) a heuristic evaluation, (2) a qualitative evaluation and (3) a quantitative evaluation. ResultsFifteen service users with a schizophrenia diagnosis and four information and communication technology (ICT) experts participated in the study. The results show that people with a schizophrenia diagnosis were able to use the support system easily. Furthermore, the content of the advice generated by the support system was considered meaningful and supportive. ConclusionsThis study shows that the support system prototype has valuable potential to improve the ROM practice and it is worthwhile to further develop it into a more mature system. Furthermore, the results add to prior research into web applications for people with psychotic disorders, in that it shows that this group of end users can work with web-based and computer-based systems, despite the cognitive problems they experience.

Background: Subclinical psychotic experiences are common in the general population and form a paradox. On the one hand, psychotic experiences have a relatively high prevalence in the general population and the majority of such experiences is transient. Even most individuals considered to be at Ultra High Risk (UHR) do not develop a clinical psychotic disorder. On the other hand, psychotic experiences are associated with a large number of concurrent mental health problems. Even in individuals at UHR who do not develop a clinical psychotic disorder, psychotic experiences are associated with mental health problems and poorer psychosocial functioning. A challenge for both researchers and clinicians is to adequately distinguish those with benign experiences from those with more pathological psychotic experiences. One possible explanation for this is that most research on psychotic experiences has focused exclusively on positive psychotic experiences. However, psychosis is currently conceptualized as a multidimensional construct. Another possible explanation may be that they form a heterogeneous concept as not all experiences may be pathological in nature. The goal of the present study was to perform quantitative and qualitative examinations of the heterogeneity of individuals reporting subclinical psychotic experiences in a unique Dutch internet-based general population sample. Methods: The HowNutsAreTheDutch study is a large-scale crowdsourcing project, and its aims are twofold: to (i) investigate the continuity of multiple mental health dimensions in the Dutch population and (ii) gain more insight into the interactions between mental strengths and mental vulnerabilities/problems. Positive and negative subclinical psychotic experiences were measured with the Community Assessment of Psychic Experiences (CAPE) in n = 2870 individuals. The prevalence of these experiences and their associations with demographics, affect, psychopathology and quality of life were investigated first. Next, Latent Class Analysis (LCA) was used to identify data-driven subgroups with different symptom patterns. These subgroups were also compared on aforementioned factors. Results: Subclinical psychotic experiences were commonly reported. Prevalence rates differed strongly between items, ranging from 1-89% (mean: 21% for positive and 56% for negative experiences). Both positive and negative psychotic experiences were associated with younger age, more negative affect, anxiety and depression and less positive affect and quality of life. Seven latent classes were identified that were labeled as ‘Mentally fit’, ‘Lethargic’, ‘Blunted’, ‘Distressed’, ‘Spiritual’, ‘Grandiose’, and ‘Pathological’. These classes demonstrated both quantitative differences in the number/severity of reported psychotic experiences and qualitative differences in the patterns of reported experiences. Discussion: Subclinical psychotic experiences show both dimensional severity variations and discrete symptom pattern variations across individuals in the general population, suggesting that, to understand and capture all interindividual variations in subclinical psychotic experiences, their number, nature and context should all be considered at the same time. Only some psychotic experiences may lay on a true psychopathological psychosis continuum. Taking into account the base rate in the population as well as the context of psychotic experiences (i.e. the larger pattern in which they occur) could help to determine whether such experiences should be interpreted as a warning signal or not. This may help us to identify those individuals who are at most risk for developing mental health problems and may guide services of early detection and intervention

Each person is different and should be treated assuch. Comparing personal data to group averages can give basicideas about personal conditions, but does not suffice for providing‘true’ personalized feedback. In health psychology, a paradigmshift is taking place from a general population approach towardsa more person-centered one. Instead of comparing a person withpopulation averages, the focus shifts towards comparing peoplewith themselves over time. The ‘Leefplezier’ project elaborateson this focus shift, by helping to sustain or improve the wellbeingof elderly people. The participating elderly people are askedto keep track of various psychological factors for a period oftime, by means of repetitive questionnaires via a mobile phoneapplication. At the end of this period, feedback is automaticallygenerated, based on the resulting time series dataset and by meansof automated vector autoregression.