Education level and COVID-19 vaccination willingness in adolescents.

Vaccination is essential to control the COVID-19 pandemic. High vaccination willingness is a key for successful vaccination programs. This study assessed attitudes toward vaccination in Austrian adolescents and determined whether there are differences in vaccination readiness regarding education status, gender and migration background. Two cross-sectional online surveys were conducted from March to July 2021 in apprentices and high school students. Willingness to receive COVID-19 vaccination was rated on a 5-point scale. In total, n = 2006 (n = 1442 apprentices and n = 564 high school students) completed the survey. Willingness to receive COVID-19 vaccination was higher in students compared to apprentices (p < 0.001). Furthermore, migration background (p = 0.023) and female gender (p = 0.001) were associated with lower vaccination willingness. In conclusion, more efforts are required to improve confidence and willingness to vaccinate adolescents with lower educational levels, those with migrant backgrounds and females.

Mental health burden of high school students, and suggestions for psychosocial support, 1.5 years into the COVID-19 pandemic in Austria.

The COVID-19 pandemic and containment efforts seem to be particularly challenging for adolescents. This study assessed mental health in high school students 1.5 years after the pandemic began in Austria. A cross-sectional survey was carried out from September to November 2021. Well-being (WHO-5), depressive symptoms, anxiety symptoms and sleep quality were assessed. A total of 1505 adolescents participated (78% girls). The cut-offs for clinically relevant symptoms were exceeded by 62% girls and 38.1% boys for depression (PHQ-9 score ≥ 11), 49% girls and 29% boys for anxiety (GAD-7 score ≥ 11) and 28% girls and 17% boys for insomnia (ISI score ≥ 15). The prevalence of suicidal ideation (item 9 of the PHQ-9) within the last 2 weeks was 47% in girls and 32% in boys. These data collected in autumn 2021 (the start of the second semester of reopened schools; t2) were compared to data collected in February 2021 (one semester after remote schooling; t1). A matched pairs analysis according to age, gender, region, school type and migration background resulted in a total sample size of N = 2514 adolescents. Results showed small deteriorations in mental health (i.e., well-being, depression, insomnia, suicidal ideation) in girls at t2 compared to t1, and an increase in suicidal thoughts in boys (all p-values < 0.05). Qualitative data show that young people have a need for more psychological support, both professional and informal, as well as increased mental health literacy. Results suggest that mental health burden in adolescents remains high 1.5 years into the pandemic and highlight the need to implement timely psychological support.

Stress levels in high-school students after a semester of home-schooling.

There has been an increase in stress in adolescents since the beginning of the COVID-19 pandemic. Social distancing and home-schooling are just two of many stress factors for this age group. The aim of this study was to assess stress in high-school students after a semester of home-schooling. A cross-sectional online survey (February 3rd to 28th 2021) was performed, measuring stress with the Perceived Stress Scale (PSS-10) in Austria. In total, N = 2884 students (age: M = 16.47 (SD = 1.44); 70.4% females) completed the survey. Mean PSS-10 score was M = 23.50 (SD = 7.47) [females: M = 24.69 (SD = 6.80); males: M = 20.11 (SD = 7.93); p < 0.001]. 11.0% reported low stress (females: 7.2%; males 20.9%), 52.5% moderate stress (females: 51.5%; males: 57.3%), and 36.5% high stress (females: 41.3%; males 21.8%); p < 0.001. Around one-third of high-school students suffer from high stress level, females almost twice as often as males. Psychological support should particularly focus on stress and possibilities to reduce it.

An Albanian translation of a questionnaire for self-reported tinnitus assessment.

OBJECTIVE: To our knowledge, there is no published study investigating the characteristics of people experiencing tinnitus in Albania. Such a study would be important, providing the basis for further research in this region and contributing to a wider understanding of tinnitus heterogeneity across different geographic locations. The main objective of this study was to develop an Albanian translation of a standardised questionnaire for tinnitus research, namely the European School for Interdisciplinary Tinnitus Research-Screening Questionnaire (ESIT-SQ). A secondary objective was to assess its applicability and usefulness by conducting an exploratory survey on a small sample of the Albanian tinnitus population. DESIGN AND STUDY SAMPLE: Three translators were recruited to create the Albanian ESIT-SQ translation following good practice guidelines. Using this questionnaire, data from 107 patients attending otolaryngology clinics in Albania were collected. RESULTS: Participants reporting various degrees of tinnitus symptom severity had distinct phenotypic characteristics. Application of a random forest approach on this preliminary dataset showed that self-reported hearing difficulty, and tinnitus duration, pitch and temporal manifestation were important variables for predicting tinnitus symptom severity. CONCLUSIONS: Our study provided an Albanian translation of the ESIT-SQ and demonstrated that it is a useful tool for tinnitus profiling and subgrouping.

Mental Health During COVID-19 Lockdown in the United Kingdom.

OBJECTIVE: The coronavirus disease (COVID-19) pandemic and related lockdown measures have raised important questions about the impact on mental health. This study evaluated several mental health and well-being indicators in a large sample from the United Kingdom (UK) during the COVID-19 lockdown where the death rate is currently among the highest in Europe. METHODS: A cross-sectional online survey with a study sample that mirrors general population norms according to sex, age, education, and region was launched 4 weeks after lockdown measures were implemented in the UK. Measures included mental health-related quality of life (World Health Organization Quality-of-Life Brief Version psychological domain), well-being (World Health Organization Well-Being Index), depression (Patient Health Questionnaire-9), anxiety (Generalized Anxiety Disorder-7), perceived stress (Perceived Stress Scale-10), and insomnia (Insomnia Severity Index). Analyses of variances, Bonferroni-corrected post hoc tests, and t tests were applied to examine mental health indicators across different sociodemographic groups (age, sex, employment, income, physical activity, relationship status). RESULTS: The sample comprised n = 1006 respondents (54% women) from all regions of the UK. Approximately 52% of respondents screened positive for a common mental disorder, and 28% screened positive for clinical insomnia. Mean scores and standard deviations were as follows: Patient Health Questionnaire-9, mean = 9.0 ± 7.7; Generalized Anxiety Disorder-7, mean = 8.0 ± 6.5; Insomnia Severity Index, mean = 10.4 ± 7.0; Perceived Stress Scale-10, mean = 17.7 ± 7.9; World Health Organization Quality-of-Life Brief Version, mean = 58.6 ± 21.4; and World Health Organization Well-Being Index score, mean = 13.0 ± 6.0. Statistical analyses consistently indicated more severe mental health problems in adults younger than 35 years, women, people with no work, and people with low income (all p values < .05). Mental health indices also varied across UK regions. CONCLUSIONS: The prevalence of depressive, anxiety, and insomnia symptoms is significantly higher in the UK relative to prepandemic epidemiological data. Further studies are needed to clarify the causes for these high rates of mental health symptoms.

Second-generation antidepressants for treatment of seasonal affective disorder.

BACKGROUND: Seasonal affective disorder (SAD) is a seasonal pattern of recurrent depressive episodes that is often treated with second-generation antidepressants (SGAs), light therapy, or psychotherapy. OBJECTIVES: To assess the efficacy and safety of second-generation antidepressants (SGAs) for the treatment of seasonal affective disorder (SAD) in adults in comparison with placebo, light therapy, other SGAs, or psychotherapy. SEARCH METHODS: This is an update of an earlier review first published in 2011. We searched the Cochrane Central Register of Controlled Trials (CENTRAL; 2020, Issue 1) in the Cochrane Library (all years), Ovid MEDLINE, Embase, and PsycINFO (2011 to January 2020), together with the Cochrane Common Mental Disorders Controlled Trials Register (CCMDCTR) (all available years), for reports of randomised controlled trials (RCTs). We hand searched the reference lists of all included studies and other systematic reviews. We searched ClinicalTrials.gov for unpublished/ongoing trials. We ran a separate update search for reports of adverse events in the Ovid databases.  SELECTION CRITERIA: For efficacy we included RCTs of SGAs compared with other SGAs, placebo, light therapy, or psychotherapy in adult participants with SAD. For adverse events we also included non-randomised studies. DATA COLLECTION AND ANALYSIS: Two review authors independently screened abstracts and full-text publications against the inclusion criteria. Data extraction and 'Risk of bias' assessment were conducted individually. We pooled data for meta-analysis where the participant groups were similar, and the studies assessed the same treatments with the same comparator and had similar definitions of outcome measures over a similar duration of treatment. MAIN RESULTS: In this update we identified no new RCT on the effectiveness of SGAs in SAD patients. We included 2 additional single-arm observational studies that reported on adverse events of SGAs.  For efficacy we included three RCTs of between five and eight weeks' duration with a total of 204 participants. For adverse events we included two RCTs and five observational (non-randomised) studies of five to eight weeks' duration with a total of 249 participants. All participants met the DSM (Diagnostic and Statistical Manual of Mental Disorders) criteria for SAD. The average age ranged from 34 to 42 years, and the majority of participants were female (66% to 100%). Results from one trial with 68 participants showed that fluoxetine (20/36) was numerically superior to placebo (11/32) in achieving clinical response; however, the confidence interval (CI) included both a potential benefit as well as no benefit of fluoxetine (risk ratio (RR) 1.62, 95% CI 0.92 to 2.83, very low-certainty evidence). The number of adverse events was similar in both groups (very low-certainty evidence). Two trials involving a total of 136 participants compared fluoxetine versus light therapy. Meta-analysis showed fluoxetine and light therapy to be approximately equal in treating seasonal depression: RR of response 0.98 (95% CI 0.77 to 1.24, low-certainty evidence), RR of remission 0.81 (95% CI 0.39 to 1.71, very low-certainty evidence). The number of adverse events was similar in both groups (low-certainty evidence). We did not identify any eligible study comparing SGA with another SGA or with psychotherapy. Two RCTs and five non-randomised studies reported adverse event data on a total of 249 participants who received bupropion, fluoxetine, escitalopram, duloxetine, nefazodone, reboxetine, light therapy, or placebo. We were only able to obtain crude rates of adverse events, therefore caution is advised regarding interpretation of this information. Between 0% and 100% of participants who received an SGA suffered an adverse event, and between 0% and 25% of participants withdrew from the study due to adverse events. AUTHORS' CONCLUSIONS: Evidence for the effectiveness of SGAs is limited to one small trial of fluoxetine compared with placebo showing a non-significant effect in favour of fluoxetine, and two small trials comparing fluoxetine against light therapy suggesting equivalence between the two interventions. The lack of available evidence precluded us from drawing any overall conclusions on the use of SGAs for SAD. Further, larger RCTs are required to expand and strengthen the evidence base on this topic, and should also include comparisons with psychotherapy and other SGAs. Data on adverse events were sparse, and a comparative analysis was not possible. The data we obtained on adverse events is therefore not robust, and our confidence in the data is limited. Overall, up to 25% of participants treated with SGAs for SAD withdrew from the study early due to adverse events.

Therapeutic interventions in in-person and remote psychotherapy: Survey with psychotherapists and patients experiencing in-person and remote psychotherapy during COVID-19.

OBJECTIVE: First, to investigate how psychotherapists and patients experience the change from in-person to remote psychotherapy or vice versa during COVID-19 regarding the therapeutic interventions used. Second, to explore the influence of therapeutic orientations on therapeutic interventions in in-person versus remote psychotherapy. METHOD: Psychotherapists (N = 217) from Austria were recruited, who in turn recruited their patients (N = 133). The therapeutic orientation of the therapists was psychodynamic (22.6%), humanistic (46.1%), systemic (20.7%) or behavioural (10.6%). All the data were collected remotely via online surveys. Therapists and patients completed two versions of the 'Multitheoretical List of Therapeutic Interventions' (MULTI-30) (version 1: in-person; version 2: remote) to investigate differences between in-person and remote psychotherapy in the following therapeutic interventions: psychodynamic, common factors, person-centred, process-experiential, interpersonal, cognitive, behavioural and dialectical-behavioural. RESULTS: Therapists rated all examined therapeutic interventions as more typical for in-person than for remote psychotherapy. For patients, three therapeutic interventions (psychodynamic, process-experiential, cognitive interventions) were more typical for in-person than for remote psychotherapy after correcting for multiple testing. For two therapeutic interventions (behavioural, dialectical-behavioural), differences between the four therapeutic orientations were more consistent for in-person than for remote psychotherapy. CONCLUSIONS: Therapeutic interventions differed between in-person and remote psychotherapy and differences between therapeutic orientations in behavioural-oriented interventions become indistinct in remote psychotherapy.

Effects of alliance ruptures and repairs on outcomes.

This study explored whether treatment outcomes in a trial on the Cognitive Behavioral Analysis System of Psychotherapy (CBASP) vs. Supportive Psychotherapy (SP) for patients with early-onset chronic depression differ between alliance patterns.Session-to-session ratings of the therapeutic alliance (Helping Alliance Questionnaire (HAQ)) from 254 outpatients with chronic depression (CBASP: 134; SP: 120) who took part in a multicenter randomized controlled trial of CBASP vs. SP were used to categorize patients into three alliance pattern categories for the patients' and therapists' rating separately. Based on the reliable change in the HAQ from one session to the next categories were: no rupture, unrepaired rupture, rupture-repair. Depression severity (24-item Hamilton Rating Scale for Depression) at post-treatment, at 12- and 24- months follow-up was the outcome.The alliance pattern categories for therapists and patients did not differ between CBASP and SP. Only the alliance patterns calculated for patients were associated with outcome: in the unrepaired rupture category, patients had higher HRSD-ratings across time points (p = 0.047).CBASP was not associated with more or fewer ruptures or repairs as compared to SP in the treatment of chronic depression. The study highlights the need to resolve ruptures to avoid poor outcomes.Trial registration: ClinicalTrials.gov identifier: NCT00970437.

Stress, depression, and the therapeutic alliance as mediators on the outcome of brief psychodynamic-interpersonal psychotherapy for multisomatoform disorder.

The aim of this study was to identify and explore mediators of psychodynamic-interpersonal psychotherapy (PIT) on treatment outcome in multisomatoform disorders (MSD).Data from 164 patients with MSD who took part in a randomized control trial of PIT (n = 88) vs. enhanced medical care (EMC; n = 76) were re-analyzed. A parallel mediation analysis was performed to investigate whether the beneficial effect of PIT vs. EMC on physical quality of life (physical component summary (PCS) of the SF-36 Health Survey) nine months post-treatment is mediated by post-treatment scores of stress, depression, and therapeutic alliance. The potential mediators were operationalized with the Helping Alliance Questionnaire (HAQ; therapeutic alliance), the Patient Health Questionnaire (PHQ)-stress module (perceived stress) and the PHQ-depression module (PHQ-9; depression).Stress partially mediated the effect of PIT vs. EMC on the follow-up outcome. PIT (as compared to EMC) led to lower post-treatment stress-levels, which in turn led to higher physical quality of life at follow-up. Neither depression nor the alliance had a mediating effect.Stress mediated the outcome of PIT for MSD. Future studies are needed to extend the scope of research regarding which specific psychotherapeutic mechanisms of change are beneficial in PIT treatment of MSD patients.

Coping strategies and mental health during COVID-19 lockdown.

BACKGROUND: COVID-19 pandemic lockdown measures changed the everyday lives of people around the world. AIMS: To evaluate the effects of different coping strategies on mental health during COVID-19 lockdown. METHODS: A representative sample for Austria was recruited through Qualtrics® in a period of 4 weeks after the lockdown started. Measurements were coping inventory (SCI), psychological quality of life (WHO-QOL BREF, psychological domain), well-being (WHO-5), depression (PHQ-9), anxiety (GAD-7), stress (PSS-10), and insomnia (ISI). Regression analyses were performed with coping strategies as predictors and mental health measures as dependent variables. RESULTS: The representative sample included N = 1,005 respondents (52.7% women). Positive thinking, active stress coping and social support were found to be positive predictors for psychological life quality, well-being, and negative predictors for perceived stress, depression, anxiety, and insomnia. Alcohol and cigarette consumption was a negative predictor for psychological life quality, and well-being, and a positive predictor for perceived stress, depression, anxiety, and insomnia. Support in faith was a positive predictor for perceived stress, depression, anxiety, and insomnia. CONCLUSIONS: Coping strategies are significant predictors for mental health measures. Education about positive thinking, active coping, and social support could be beneficial for dealing with a decrease in mental health due to COVID-19 pandemic.

Experiences of Psychotherapists With Remote Psychotherapy During the COVID-19 Pandemic: Cross-sectional Web-Based Survey Study.

BACKGROUND: The current situation around the COVID-19 pandemic and the measures necessary to fight it are creating challenges for psychotherapists, who usually treat patients face-to-face with personal contact. The pandemic is accelerating the use of remote psychotherapy (ie, psychotherapy provided via telephone or the internet). However, some psychotherapists have expressed reservations regarding remote psychotherapy. As psychotherapists are the individuals who determine the frequency of use of remote psychotherapy, the potential of enabling mental health care during the COVID-19 pandemic in line with the protective measures to fight COVID-19 can be realized only if psychotherapists are willing to use remote psychotherapy. OBJECTIVE: This study aimed to investigate the experiences of psychotherapists with remote psychotherapy in the first weeks of the COVID-19 lockdown in Austria (between March 24 and April 1, 2020). METHODS: Austrian psychotherapists were invited to take part in a web-based survey. The therapeutic orientations of the psychotherapists (behavioral, humanistic, psychodynamic, or systemic), their rating of the comparability of remote psychotherapy (web- or telephone-based) with face-to-face psychotherapy involving personal contact, and potential discrepancies between their actual experiences and previous expectations with remote psychotherapy were assessed. Data from 1162 psychotherapists practicing before and during the COVID-19 lockdown were analyzed. RESULTS: Psychotherapy conducted via telephone or the internet was reported to not be totally comparable to psychotherapy with personal contact (P<.001). Psychodynamic (P=.001) and humanistic (P=.005) therapists reported a higher comparability of telephone-based psychotherapy to in-person psychotherapy than behavioral therapists. Experiences with remote therapy (both web- and telephone-based) were more positive than previously expected (P<.001). Psychodynamic therapists reported more positive experiences with telephone-based psychotherapy than expected compared to behavioral (P=.03) and systemic (P=.002) therapists. In general, web-based psychotherapy was rated more positively (regarding comparability to psychotherapy with personal contact and experiences vs expectations) than telephone-based psychotherapy (P<.001); however, psychodynamic therapists reported their previous expectations to be equal to their actual experiences for both telephone- and web-based psychotherapy. CONCLUSIONS: Psychotherapists found their experiences with remote psychotherapy (ie, web- or telephone-based psychotherapy) to be better than expected but found that this mode was not totally comparable to face-to-face psychotherapy with personal contact. Especially, behavioral therapists were found to rate telephone-based psychotherapy less favorably than therapists with other theoretical backgrounds.

Applying Machine Learning to Daily-Life Data From the TrackYourTinnitus Mobile Health Crowdsensing Platform to Predict the Mobile Operating System Used With High Accuracy: Longitudinal Observational Study.

BACKGROUND: Tinnitus is often described as the phantom perception of a sound and is experienced by 5.1% to 42.7% of the population worldwide, at least once during their lifetime. The symptoms often reduce the patient's quality of life. The TrackYourTinnitus (TYT) mobile health (mHealth) crowdsensing platform was developed for two operating systems (OS)-Android and iOS-to help patients demystify the daily moment-to-moment variations of their tinnitus symptoms. In all platforms developed for more than one OS, it is important to investigate whether the crowdsensed data predicts the OS that was used in order to understand the degree to which the OS is a confounder that is necessary to consider. OBJECTIVE: In this study, we explored whether the mobile OS-Android and iOS-used during user assessments can be predicted by the dynamic daily-life TYT data. METHODS: TYT mainly applies the paradigms ecological momentary assessment (EMA) and mobile crowdsensing to collect dynamic EMA (EMA-D) daily-life data. The dynamic daily-life TYT data that were analyzed included eight questions as part of the EMA-D questionnaire. In this study, 518 TYT users were analyzed, who each completed at least 11 EMA-D questionnaires. Out of these, 221 were iOS users and 297 were Android users. The iOS users completed, in total, 14,708 EMA-D questionnaires; the number of EMA-D questionnaires completed by the Android users was randomly reduced to the same number to properly address the research question of the study. Machine learning methods-a feedforward neural network, a decision tree, a random forest classifier, and a support vector machine-were applied to address the research question. RESULTS: Machine learning was able to predict the mobile OS used with an accuracy up to 78.94% based on the provided EMA-D questionnaires on the assessment level. In this context, the daily measurements regarding how users concentrate on the actual activity were particularly suitable for the prediction of the mobile OS used. CONCLUSIONS: In the work at hand, two particular aspects have been revealed. First, machine learning can contribute to EMA-D data in the medical context. Second, based on the EMA-D data of TYT, we found that the accuracy in predicting the mobile OS used has several implications. Particularly, in clinical studies using mobile devices, the OS should be assessed as a covariate, as it might be a confounder.

Towards the Applicability of Measuring the Electrodermal Activity in the Context of Process Model Comprehension: Feasibility Study.

Process model comprehension is essential in order to understand the five Ws (i.e., who, what, where, when, and why) pertaining to the processes of organizations. However, research in this context showed that a proper comprehension of process models often poses a challenge in practice. For this reason, a vast body of research exists studying the factors having an influence on process model comprehension. In order to point research towards a neuro-centric perspective in this context, the paper at hand evaluates the appropriateness of measuring the electrodermal activity (EDA) during the comprehension of process models. Therefore, a preliminary test run and a feasibility study were conducted relying on an EDA and physical activity sensor to record the EDA during process model comprehension. The insights obtained from the feasibility study demonstrated that process model comprehension leads to an increased activity in the EDA. Furthermore, EDA-related results indicated significantly that participants were confronted with a higher cognitive load during the comprehension of complex process models. In addition, the experiences and limitations we learned in measuring the EDA during the comprehension of process models are discussed in this paper. In conclusion, the feasibility study demonstrated that the measurement of the EDA could be an appropriate method to obtain new insights into process model comprehension.

Efficient Processing of Geospatial mHealth Data Using a Scalable Crowdsensing Platform.

Smart sensors and smartphones are becoming increasingly prevalent. Both can be used to gather environmental data (e.g., noise). Importantly, these devices can be connected to each other as well as to the Internet to collect large amounts of sensor data, which leads to many new opportunities. In particular, mobile crowdsensing techniques can be used to capture phenomena of common interest. Especially valuable insights can be gained if the collected data are additionally related to the time and place of the measurements. However, many technical solutions still use monolithic backends that are not capable of processing crowdsensing data in a flexible, efficient, and scalable manner. In this work, an architectural design was conceived with the goal to manage geospatial data in challenging crowdsensing healthcare scenarios. It will be shown how the proposed approach can be used to provide users with an interactive map of environmental noise, allowing tinnitus patients and other health-conscious people to avoid locations with harmful sound levels. Technically, the shown approach combines cloud-native applications with Big Data and stream processing concepts. In general, the presented architectural design shall serve as a foundation to implement practical and scalable crowdsensing platforms for various healthcare scenarios beyond the addressed use case.

Metabolomic Biomarkers in Anxiety Disorders.

Anxiety disorders range among the most prevalent psychiatric disorders and belong to the leading disorders in the study of the total global burden of disease. Anxiety disorders are complex conditions, with not fully understood etiological mechanisms. Numerous factors, including psychological, genetic, biological, and chemical factors, are thought to be involved in their etiology. Although the diagnosis of anxiety disorders is constantly evolving, diagnostic manuals rely on symptom lists, not on objective biomarkers and treatment effects are small to moderate. The underlying biological factors that drive anxiety disorders may be better suited to serve as biomarkers for guiding personalized medicine, as they are objective and can be measured externally. Therefore, the incorporation of novel biomarkers into current clinical methods might help to generate a classification system for anxiety disorders that can be linked to the underlying dysfunctional pathways. The study of metabolites (metabolomics) in a large-scale manner shows potential for disease diagnosis, for stratification of patients in a heterogeneous patient population, for monitoring therapeutic efficacy and disease progression, and for defining therapeutic targets. All of these are important properties for anxiety disorders, which is a multifactorial condition not involving a single-gene mutation. This review summarizes recent investigations on metabolomics studies in anxiety disorders.

Patients' interpersonal problems as moderators of depression outcomes in a randomized controlled trial comparing mindfulness-based cognitive therapy and a group version of the cognitive-behavioral analysis system of psychotherapy in chronic depression.

OBJECTIVES: Interpersonal problems were examined as moderators of depression outcomes between mindfulness-based cognitive therapy (MBCT) and cognitive behavioral analysis system of psychotherapy (CBASP) in patients with chronic depression. METHODS: Patients received treatment-as-usual and, in addition, were randomized to 8-weeks of MBCT (n = 34) or 8-weeks of CBASP (n = 34). MBCT and CBASP were given in a group format. The Hamilton depression rating scale (HAM-D) was the primary and the Beck Depression Inventory (BDI-II) the secondary outcome. The subscales of the Inventory of interpersonal problems (IIP-32) were moderators. Multilevel models were performed. RESULTS: Higher scores on the "vindictive/self-centered" subscale were associated with a better outcome in MBCT than in CBASP (HAM-D: p < .01; BDI-II: p < .01). Higher scores on the "nonassertive" subscale were associated with a better outcome in CBASP than in MBCT (HAM-D: p < .01; BDI-II: p < .01). CONCLUSIONS: If these results can be replicated in larger trials, MBCT should be preferred to CBASP in chronically depressed patients being vindictive/self-centered, whereas CBASP should be preferred to MBCT in chronically depressed patients being nonassertive.

Why are some cases not on track? An item analysis of the Assessment for Signal Cases during inpatient psychotherapy.

Within the Routine Outcome Monitoring system "OQ-Analyst," the questionnaire "Assessment for Signal Cases" (ASC) supports therapists in detecting potential reasons for not-on-track trajectories. Factor analysis and a machine learning algorithm (LASSO with 10-fold cross-validation) were applied, and potential predictors of not-on-track classifications were tested using logistic multilevel modeling methods. The factor analysis revealed a shortened (30 items) version of the ASC with good internal consistency (α = 0.72-0.89) and excellent predictive value (area under the curve = 0.98; positive predictive value = 0.95; negative predictive value = 0.94). Item-level analyses showed that interpersonal problems captured by specific ASC items (not feeling able to speak about problems with family members; feeling rejected or betrayed) are the most important predictors of not-on-track trajectories. It should be considered that our results are based on analyses of ASC items only. Our findings need to be replicated in future studies including other potential predictors of not-on-track trajectories (e.g., changes in medication, specific therapeutic techniques, or treatment adherence), which were not measured this study.

Early developments in general change mechanisms predict reliable improvement in addition to early symptom trajectories in cognitive behavioral therapy.

General change mechanisms (GCMs) have been shown to predict treatment outcome in cognitive behavioral therapy (CBT). Early changes in GCMs (early-change-GCMs) and in symptom severity were also linked to treatment outcome, but evidence is still limited. We investigated whether early-change-GCMs from patients' and therapists' perspectives in addition to early changes in symptom severity predict treatment outcome. Data from a university-based outpatient clinic was analyzed (N = 911 completers). Most treatments were provided by therapists in CBT training. Outcomes were symptom severity and life satisfaction. Continuous post-treatment scores and categories of reliable improvement (improved vs. not improved) were investigated. Some patient-rated early-change-GCMs and early changes in symptom severity proved to be predictors for continuous outcomes (p < .05) in symptom severity and life satisfaction. In addition, some patient-rated early-change-GCMs predicted reliable improvement in life satisfaction. By contrast, therapist-rated early-change-GCMs and early symptom severity change predicted reliable improvement in symptom severity. Early-change-GCMs explained between two and four percent additional variance in outcomes. Thus, it is important to consider early changes in GCMs in addition to early changes in symptom severity in routine monitoring.

Differences in baseline and process variables between non-responders and responders in Internet-based cognitive behavior therapy for chronic tinnitus.

Although Internet-based cognitive behavior therapy (iCBT) is an effective treatment for chronic tinnitus, several patients do not improve. In the current study, baseline and process variables were compared between non-responders and responders. Data from patients participating in two randomized controlled trials on iCBT for chronic tinnitus were re-analyzed. Based on the literature, a pre-post difference on the "Tinnitus Handicap Inventory" (THI) of less than seven points improvement was used to operationalize non-response. Associations between non-response and baseline variables (age, gender, and questionnaire scores), patient progress (THI), the process of the therapeutic alliance ("Working Alliance Inventory-Short Revised"; WAI-SR), as well as other process variables (number of logins, amount of messages sent from therapists to patients) were investigated. The results showed that non-responders had a less favorable change on the THI than responders already at mid-treatment (p < .05). The alliance (WAI-SR) during iCBT was not associated with non-response. Non-responders showed more severe sleep disturbances, logged in less in the iCBT platform, and received fewer messages from the therapists than responders, but these differences were mostly not significant anymore when correcting for multiple testing. To conclude, no symptom change in the first half of iCBT for chronic tinnitus patients is a risk factor of not benefiting from iCBT.

Dimensionality Reduction and Subspace Clustering in Mixed Reality for Condition Monitoring of High-Dimensional Production Data.

Visual analytics are becoming increasingly important in the light of big data and related scenarios. Along this trend, the field of immersive analytics has been variously furthered as it is able to provide sophisticated visual data analytics on one hand, while preserving user-friendliness on the other. Furthermore, recent hardware developments such as smart glasses, as well as achievements in virtual-reality applications, have fanned immersive analytic solutions. Notably, such solutions can be very effective when they are applied to high-dimensional datasets. Taking this advantage into account, the work at hand applies immersive analytics to a high-dimensional production dataset to improve the digital support of daily work tasks. More specifically, a mixed-reality implementation is presented that will support manufacturers as well as data scientists to comprehensively analyze machine data. As a particular goal, the prototype will simplify the analysis of manufacturing data through the usage of dimensionality reduction effects. Therefore, five aspects are mainly reported in this paper. First, it is shown how dimensionality reduction effects can be represented by clusters. Second, it is presented how the resulting information loss of the reduction is addressed. Third, the graphical interface of the developed prototype is illustrated as it provides (1) a correlation coefficient graph, (2) a plot for the information loss, and (3) a 3D particle system. In addition, an implemented voice recognition feature of the prototype is shown, which was considered to be being promising to select or deselect data variables users are interested in when analyzing the data. Fourth, based on a machine learning library, it is shown how the prototype reduces computational resources using smart glasses. The main idea is based on a recommendation approach as well as the use of subspace clustering. Fifth, results from a practical setting are presented, in which the prototype was shown to domain experts. The latter reported that such a tool is actually helpful to analyze machine data daily. Moreover, it was reported that such a system can be used to educate machine operators more properly. As a general outcome of this work, the presented approach may constitute a helpful solution for the industry as well as other domains such as medicine.