Individual differences in everyday multitasking behavior and its relation to cognition and personality.

Our ability to multitask-focus on multiple tasks simultaneously-is one of the most critical functions of our cognitive system. This capability has shown to have relations to cognition and personality in empirical studies, which have received much attention recently. This review article integrates the available findings to examine how individual differences in multitasking behavior are linked with different cognitive constructs and personality traits to conceptualize what multitasking behavior represents. In this review, we highlight the methodological differences and theoretical conceptions. Cognitive constructs including executive functions (i.e., shifting, updating, and inhibition), working memory, relational integration, divided attention, reasoning, and prospective memory were investigated. Concerning personality, the traits of polychronicity, impulsivity, and the five-factor model were considered. A total of 43 studies met the inclusion criteria and entered the review. The research synthesis directs us to propose two new conceptual models to explain multitasking behavior as a psychometric construct. The first model demonstrates that individual differences in multitasking behavior can be explained by cognitive abilities. The second model proposes that personality traits constitute a moderating effect on the relation between multitasking behavior and cognition. Finally, we provide possible future directions for the line of research.

Predicting personality from patterns of behavior collected with smartphones.

Smartphones enjoy high adoption rates around the globe. Rarely more than an arm's length away, these sensor-rich devices can easily be repurposed to collect rich and extensive records of their users' behaviors (e.g., location, communication, media consumption), posing serious threats to individual privacy. Here we examine the extent to which individuals' Big Five personality dimensions can be predicted on the basis of six different classes of behavioral information collected via sensor and log data harvested from smartphones. Taking a machine-learning approach, we predict personality at broad domain ([Formula: see text] = 0.37) and narrow facet levels ([Formula: see text] = 0.40) based on behavioral data collected from 624 volunteers over 30 consecutive days (25,347,089 logging events). Our cross-validated results reveal that specific patterns in behaviors in the domains of 1) communication and social behavior, 2) music consumption, 3) app usage, 4) mobility, 5) overall phone activity, and 6) day- and night-time activity are distinctively predictive of the Big Five personality traits. The accuracy of these predictions is similar to that found for predictions based on digital footprints from social media platforms and demonstrates the possibility of obtaining information about individuals' private traits from behavioral patterns passively collected from their smartphones. Overall, our results point to both the benefits (e.g., in research settings) and dangers (e.g., privacy implications, psychological targeting) presented by the widespread collection and modeling of behavioral data obtained from smartphones.

Differential psychological response to the COVID-19 pandemic in psychiatric inpatients compared to a non-clinical population from Germany.

The COVID-19 pandemic is an inherently stressful situation, which may lead to adverse psychosocial outcomes in various populations. Yet, individuals may not be affected equally by stressors posed by the pandemic and those with pre-existing mental disorders could be particularly vulnerable. To test this hypothesis, we assessed the psychological response to the pandemic in a case-control design. We used an age-, sex- and employment status-matched case-control sample (n = 216) of psychiatric inpatients, recruited from the LMU Psychiatry Biobank Munich study and non-clinical individuals from the general population. Participants completed validated self-report measures on stress, anxiety, depression, paranoia, rumination, loneliness, well-being, resilience, and a newly developed index of stressors associated with the COVID-19 pandemic. Multiple linear regression analyses were conducted to assess the effects of group, COVID-19-specific stressors, and their interaction on the different psychosocial outcomes. While psychiatric inpatients reported larger mental health difficulties overall, the impact of COVID-19-specific stressors was lower in patients and not associated with worse psychological functioning compared to non-clinical individuals. In contrast, depressive symptoms, rumination, loneliness, and well-being were more strongly associated with COVID-19-specific stressors in non-clinical individuals and similar to the severity of inpatients for those who experienced the greatest COVID-19-specific stressor impact Contrary to expectations, the psychological response to the pandemic may not be worse in psychiatric inpatients compared to non-clinical individuals. Yet, individuals from the general population, who were hit hardest by the pandemic, should be monitored and may be in need of mental health prevention and treatment efforts.

Evidence-based Shared-Decision-Making Assistant (SDM-assistant) for choosing antipsychotics: protocol of a cluster-randomized trial in hospitalized patients with schizophrenia.

BACKGROUND: Choosing an antipsychotic medication is an important medical decision in the treatment of schizophrenia. This decision requires risk-benefit assessments of antipsychotics, and thus, shared-decision making between physician and patients is strongly encouraged. Although the efficacy and side-effect profiles of antipsychotics are well-established, there is no clear framework for the communication of the evidence between physicians and patients. For this reason, we developed an evidence-based shared-decision making assistant (SDM-assistant) that presents high-quality evidence from network meta-analysis on the efficacy and side-effect profile of antipsychotics and can be used as a basis for shared-decision making between physicians and patients when selecting antipsychotic medications. METHODS: The planned matched-pair cluster-randomised trial will be conducted in acute psychiatric wards (n = 14 wards planned) and will include adult inpatients with schizophrenia or schizophrenia-like disorders (N = 252 participants planned). On the intervention wards, patients and their treating physicians will use the SDM-assistant, whenever a decision on choosing an antipsychotic is warranted. On the control wards, antipsychotics will be chosen according to treatment-as-usual. The primary outcome will be patients' perceived involvement in the decision-making during the inpatient stay as measured with the SDM-Q-9. We will also assess therapeutic alliance, symptom severity, side-effects, treatment satisfaction, adherence, quality of life, functioning and rehospitalizations as secondary outcomes. Outcomes could be analysed at discharge and at follow-up after three months from discharge. The analysis will be conducted per-protocol using mixed-effects linear regression models for continuous outcomes and logistic regression models using generalised estimating equations for dichotomous outcomes. Barriers and facilitators in the implementation of the intervention will also be examined using a qualitative content analysis. DISCUSSION: This is the first trial to examine a decision assistant specifically designed to facilitate shared-decision making for choosing antipsychotic medications, i.e., SDM-assistant, in acutely ill inpatients with schizophrenia. If the intervention can be successfully implemented, SDM-assistant could advance evidence-based medicine in schizophrenia by putting medical evidence on antipsychotics into the context of patient preferences and values. This could subsequently lead to a higher involvement of the patients in decision-making and better therapy decisions. TRIAL REGISTRATION: German Clinical Trials Register (ID: DRKS00027316 , registration date 26.01.2022).

The COVID-19 Pandemic Mental Health Questionnaire (CoPaQ): psychometric evaluation and compliance with countermeasures in psychiatric inpatients and non-clinical individuals.

BACKGROUND: The COVID-19 pandemic has greatly impacted people's lives across a broad spectrum of psychosocial domains. We report the development and psychometric evaluation of the self-report COVID-19 Pandemic Mental Health Questionnaire (CoPaQ), which assesses COVID-19 contamination anxiety, countermeasure necessity and compliance, mental health impact, stressor impact, social media usage, interpersonal conflicts, paranoid ideations, institutional & political trust, conspiracy beliefs, and social cohesion. Further, we illustrate the questionnaire's utility in an applied example investigating if higher SARS-Cov-2 infection rates in psychiatric patients could be explained by reduced compliance with preventive countermeasures. METHODS: A group of 511 non-clinical individuals completed an initial pool of 111 CoPaQ items (Open Science Framework: https://osf.io/3evn9/ ) and additional scales measuring psychological distress, well-being, and paranoia to assess construct validity and lifetime mental health diagnosis for criterion validity. Factor structure was determined by exploratory factor analyses and validated by conducting confirmatory factor analysis in the accompanying longitudinal sample (n = 318) and an independent psychiatric inpatient sample primarily admitted for major depressive-, substance abuse-, personality-, and anxiety disorders (n = 113). Internal consistency was assessed by Cronbach's Alpha and McDonald's Omega. For the applied research example, Welch t-tests and correlational analyses were conducted. RESULTS: Twelve out of 16 extracted subscales were retained in the final questionnaire version, which provided preliminary evidence for adequate psychometric properties in terms of factor structure, internal consistency, and construct and criterion validity. Our applied research example showed that patients exhibited greater support for COVID-19 countermeasures than non-clinical individuals. However, this requires replication in future studies. CONCLUSIONS: We demonstrate that the CoPaQ is a comprehensive and valid measure of the psychosocial impact of the pandemic and could allow to a degree to disentangle the complex psychosocial phenomena of the pandemic as exemplified by our applied analyses.

Predicting instructed simulation and dissimulation when screening for depressive symptoms.

The intentional distortion of test results presents a fundamental problem to self-report-based psychiatric assessment, such as screening for depressive symptoms. The first objective of the study was to clarify whether depressed patients like healthy controls possess both the cognitive ability and motivation to deliberately influence results of commonly used screening measures. The second objective was the construction of a method derived directly from within the test takers' responses to systematically detect faking behavior. Supervised machine learning algorithms posit the potential to empirically learn the implicit interconnections between responses, which shape detectable faking patterns. In a standardized design, faking bad and faking good were experimentally induced in a matched sample of 150 depressed and 150 healthy subjects. Participants completed commonly used questionnaires to detect depressive and associated symptoms. Group differences throughout experimental conditions were evaluated using linear mixed-models. Machine learning algorithms were trained on the test results and compared regarding their capacity to systematically predict distortions in response behavior in two scenarios: (1) differentiation of authentic patient responses from simulated responses of healthy participants; (2) differentiation of authentic patient responses from dissimulated patient responses. Statistically significant convergence of the test scores in both faking conditions suggests that both depressive patients and healthy controls have the cognitive ability as well as the motivational compliance to alter their test results. Evaluation of the algorithmic capability to detect faking behavior yielded ideal predictive accuracies of up to 89%. Implications of the findings, as well as future research objectives are discussed. Trial Registration The study was pre-registered at the German registry for clinical trials (Deutsches Register klinischer Studien, DRKS; DRKS00007708).

The Role of Self-Esteem in Depression: A Longitudinal Study.

BACKGROUND: Based on the vulnerability model, several studies indicate that low self-esteem seems to contribute to depressive symptoms. AIMS: The aim of this study was to treat depressive symptoms in a cognitive behavioural group therapy, focusing on the enhancement of self-esteem, and to explore co-variation in depressive symptoms and the level of self-esteem. METHOD: The Multidimensional Self-esteem Scale (MSWS) and the Beck Depression Inventory (BDI) were administered to 147 psychiatric in-patients with current depressive symptoms due to an affective disorder (major depression, bipolar I, dysthymia). Self-esteem was measured pre-treatment (t0) and post-treatment (t4, after 5 weeks of eight group sessions); the BDI was applied weekly. A linear mixed growth analysis was conducted to estimate the change in depressive symptoms including interactions with self-esteem. RESULTS: Within the 5 weeks of group therapy, depressive symptoms showed a linear decline, which was stronger for patients with higher gains in self-esteem between t0 and t4. Self-esteem at t0 was unrelated to the change in depression but predicted self-esteem at t4. CONCLUSIONS: Treating depressive symptoms in a cognitive behavioural group therapy in a naturalistic setting might have a positive effect on the process of recovery. Moreover, depressive symptoms and level of self-esteem seemed to co-vary.

Clinically assessed posttraumatic stress in patients with breast cancer during the first year after diagnosis in the prospective, longitudinal, controlled COGNICARES study.

OBJECTIVE: There is ongoing debate whether cancer qualifies as traumatic stressor. We investigated prevalence and course of posttraumatic stress in patients with early breast cancer (BC) during their first year after diagnosis and determined effects of mastectomy and chemotherapy. METHODS: Patients with stage 0-III BC aged ≤65 years were evaluated with the Structured Clinical Interview for DSM-IV modules for acute and posttraumatic stress disorder (ASD and PTSD, respectively) before treatment, after chemotherapy, and 1 year after diagnosis. Matched controls were assessed at matched intervals. Effects of time, mastectomy, and chemotherapy on BC-related PTSD symptom severity were tested with linear mixed model analysis. RESULTS: Stress disorder (ASD or PTSD) related to BC was diagnosed in 6 (3.6%) of 166 patients before treatment and in 3 patients (2.0%) 1 year later. The rate of patients who experienced PTSD symptoms related to BC decreased from 82.5 to 57.3% (p < 0.001), and the mean of BC-related PTSD symptoms diminished from 3.1 to 1.7 (p < 0.001). Only university education significantly predicted the course of BC-related PTSD symptom severity (p = 0.009). In 60 controls, no diagnosis of stress disorder, a rate of 18% women experiencing PTSD symptoms, and a mean of 0.4 PTSD symptoms (p vs. patients <0.001) were found. CONCLUSIONS: Most newly diagnosed patients with BC experience PTSD symptoms, whereas full diagnoses of DSM-IV stress disorder are rare. Symptoms diminish somewhat within 1 year furthered by university education but independently from mastectomy and chemotherapy. Throughout the year after diagnosis, having BC entails markedly increased PTSD symptom burden. Copyright © 2016 John Wiley & Sons, Ltd.

The sex-dependent role of the glucocorticoid receptor in depression: variations in the NR3C1 gene are associated with major depressive disorder in women but not in men.

Genetic variations in the glucocorticoid receptor (GR) and the mineralocorticoid receptor (MR) have been associated with maladaptive stress responses and major depressive disorder (MDD). In a case-control study design, we examined whether single nucleotide polymorphisms (SNPs) and haploid genotype (haplotype) associations of MR gene NR3C2, GR gene NR3C1 and genes of GR chaperone molecules FK506 binding protein 5 (FKBP5) and corticotrophin-releasing hormone receptor 1 (CRHR1) differed between healthy subjects (n = 634) and inpatients with major depressive disorder (n = 412). All analyses were conducted for women and men separately. After conservative correction of Type-I-error to obtain reliable p values, one SNP in the NR3C1 gene, namely rs6195, showed a significant association with the presence of a major depression (p = 0.048) in females. In contrast, NR3C2, FKBP5 and CRHR1 polymorphisms were not significantly associated with MDD. No haplotype effects could be identified. Our results support the notion of an association between variants of GR-related genes in women and the pathophysiology of depression: females suffering from MDD showed a more than three times higher frequency of the T/C polymorphism compared to controls, which thus seems to increase the vulnerability to depression in females.

Three-month B vitamin supplementation in pre-school children affects folate status and homocysteine, but not cognitive performance.

BACKGROUND: Suboptimal vitamin B status might affect cognitive performance in early childhood. We tested the hypothesis that short-term supplementation with folic acid and selected B vitamins improves cognitive function in healthy children in a population with relatively low folate status. METHODS: We screened 1,002 kindergarten children for suboptimal folate status by assessing the total urinary para-aminobenzoylglutamate excretion. Two hundred and fifty low ranking subjects were recruited into a double blind, randomized, controlled trial to receive daily a sachet containing 220 µg folic acid, 1.1 mg vitamin B2, 0.73 mg B6, 1.2 µg B12 and 130 mg calcium, or calcium only for 3 months. Primary outcomes were changes in verbal IQ, short-term memory and processing speed between baseline and study end. Secondary outcomes were urinary markers of folate and vitamin B12 status, acetyl-para-aminobenzoylglutamate and methylmalonic acid, respectively, and, in a subgroup of 120 participants, blood folate and plasma homocysteine. RESULTS: Pre- and post-intervention cognitive measurements were completed by 115 children in the intervention and 122 in the control group. Compared to control, median blood folate increased by about 50% (P for difference, P < 0.0001). Homocysteine decreased by 1.1 µmol/L compared to baseline, no change was seen in the control group (P for difference P < 0.0001) and acetyl-para-aminobenzoylglutamate was 4 nmol/mmol higher compared to control at the end of the intervention (P < 0.0001). We found no relevant differences between the groups for the cognitive measures. CONCLUSION: Short-term improvement of folate and homocysteine status in healthy children does not appear to affect cognitive performance.

Neural efficiency as a function of task demands.

The neural efficiency hypothesis describes the phenomenon that brighter individuals show lower brain activation than less bright individuals when working on the same cognitive tasks. The present study investigated whether the brain activation-intelligence relationship still applies when more versus less intelligent individuals perform tasks with a comparable person-specific task difficulty. In an fMRI-study, 58 persons with lower (n = 28) or respectively higher (n = 30) intelligence worked on simple and difficult inductive reasoning tasks having the same person-specific task difficulty. Consequently, less bright individuals received sample-based easy and medium tasks, whereas bright subjects received sample-based medium and difficult tasks. This design also allowed a comparison of lower versus higher intelligent individuals when working on the same tasks (i.e. sample-based medium task difficulty). In line with expectations, differences in task performance and in brain activation were only found for the subset of tasks with the same sample-based task difficulty, but not when comparing tasks with the same person-specific task difficulty. These results suggest that neural efficiency reflects an (ability-dependent) adaption of brain activation to the respective task demands.

Development and psychometric evaluation of a questionnaire for the assessment of depression in primary care: a cross-sectional study.

OBJECTIVES: To develop a new questionnaire for the diagnostic assessment of depression adapted to the primary care setting by combining psychiatric criteria and heuristics of general practitioners (GPs). Psychometric evaluation of the new questionnaire and first validity evidence. DESIGN: The questionnaire was developed using cognitive interviews with think-aloud technique. Factorial validity was then examined in a cross-sectional study. SETTING: Primary care. Five general practices in Bavaria, Germany. PARTICIPANTS: 15 GPs, 4 psychiatrists/psychotherapists and 13 patients participated in cognitive expert interviews. A primary care sample of N=277 consecutive patients participated in the cross-sectional study. METHODS: After consultation with experts and literature research, the questionnaire contained a self-rating part for patients and an external part for GPs. Items were then iteratively optimised using cognitive interviews. Factorial validity was examined. To estimate internal consistency, Cronbach's α was calculated. Validity was assessed by correlating the new questionnaire and the Patient Health Questionnaire-9 (PHQ-9). RESULTS: The preliminary version of the two-part 'Questionnaire for the assessment of DEpression SYmptoms in Primary Care' (DESY-PC) comprised 52 items for patients (DESY-PAT-1: questions about patient's environment; DESY-PAT-2: questions about depression-specific symptoms) and 21 items for GPs (DESY-GP). The analysis of the DESY-PAT-1 revealed a one-factor solution ('environmental factors') with Cronbach's α of 0.55. The items of the DESY-PAT-2 were assigned to three factors, 'depressive cognitions', 'suicidality' and 'symptoms of fatigue', with Cronbach's α of 0.86, 0.79 and 0.85, respectively. Factorial analysis revealed two factors for the DESY-GP: 'depression symptoms' and 'medical history/external factors'. Cronbach's α was 0.90 and 0.59, respectively. After factorial analysis, the DESY-PAT was reduced to 28 items, and the DESY-GP was reduced to 15 items. Correlations of the DESY-PC with the PHQ-9 were high and significant, indicating convergent validity. CONCLUSIONS: The new questionnaire represents an innovative extension of depression questionnaires and could be particularly suitable for general practices.

Snapshots of daily life: Situations investigated through the lens of smartphone sensing.

Daily life unfolds in a sequence of situational contexts, which are pivotal for explaining people's thoughts, feelings, and behaviors. While situational data were previously difficult to collect, the ubiquity of smartphones now opens up new opportunities for assessing situations in situ, that is, while they occur. Seizing this opportunity, the present study demonstrates how smartphones can help establish associations between the psychological perception and physical reality of situations. We employed an intensive longitudinal sampling design and investigated 9,790 situational snapshots experienced by 455 participants for 14 consecutive days. These snapshots combined self-reported situation characteristics from experience samplings with their corresponding objective cues obtained via smartphone sensing. More precisely, we extracted a total of 1,356 granular cues from different sensing modalities to account for the complexity of real-world situations. We applied linear and nonlinear machine learning algorithms to examine how well these cues predicted the perceived characteristics in terms of the Situational Eight Duty, Intellect, Adversity, Mating, pOsitivity, Negativity, Deception, Sociality (DIAMONDS), finding significant out-of-sample predictions for the five dimensions reflecting the situations' Duty, Intellect, Mating, pOsitivity, and Sociality. In a series of follow-up analyses, we further explored the data patterns captured by our models, revealing, for example, that those cues related to time and location were particularly informative of the respective situation characteristics. We conclude by interpreting the mapping between cues and characteristics in real-world situations and discussing how smartphone-based situational snapshots may push the boundaries of psychological research on situations. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Limits of near transfer: Content- and operation-specific effects of working memory training.

Working memory (WM) training typically leads to large performance gains in the practiced tasks, but transfer of these gains to other contexts is elusive. One possible explanation for the inconsistent findings of past research is that transfer may only occur when cognitive strategies acquired during training can also be applied in the transfer tasks. Therefore, we systematically varied the content domains and WM operations assessed by training and transfer tasks and, thereby, the extent to which similar cognitive strategies could be applied. We randomly assigned 171 young adults to one of eight experimental groups who trained one of two WM operations (storage and processing or relational integration) with materials from one of four content domains (verbal, numerical, figural-icon, or figural-pattern) to an active or to a passive control group. Before and after 12 sessions of adaptive training within 2-3 weeks, performance was assessed in all eight WM tasks. Bayesian generalized linear mixed-effects models revealed improved performance in the trained tasks compared to the active control group. However, these improvements did not generalize to tasks measuring the same WM operation with different materials. Moreover, the comparison of the training groups with an active and a passive control group showed considerable differences, thus highlighting the importance of distinguishing between active and passive control groups. Overall, the findings revealed no evidence for transfer between tasks assumed to afford the same strategies. Therefore, the adoption of specific cognitive strategies alone is unlikely to be responsible for transfer of WM training gains between tasks. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Psychological Determinants of Vaccination Readiness against COVID-19 and Seasonal Influenza of the Chronically Ill in Primary Care in Germany-A Cross-Sectional Survey.

Vaccines against COVID-19 and influenza are highly recommended for the chronically ill. They often suffer from co-morbid mental health issues. This cross-sectional observational study analyzes the associations between depression (PHQ-9) and anxiety (OASIS) with vaccination readiness (5C) against COVID-19 and influenza in chronically ill adults in primary care in Germany. Sociodemographic data, social activity (LSNS), patient activation measure (PAM), and the doctor/patient relationship (PRA) are examined as well. Descriptive statistics and linear mixed-effects regression models are calculated. We compare data from n = 795 study participants. The symptoms of depression are negatively associated with confidence in COVID-19 vaccines (p = 0.010) and positively associated with constraints to get vaccinated against COVID-19 (p = 0.041). There are no significant associations between symptoms of depression and vaccination readiness against influenza. Self-reported symptoms of a generalized anxiety disorder seem not to be associated with vaccination readiness. To address confidence in COVID-19 vaccines among the chronically ill, targeted educational interventions should be elaborated to consider mental health issues like depression. As general practitioners play a key role in the development of a good doctor/patient relationship, they should be trained in patient-centered communication. Furthermore, a standardized implementation of digital vaccination management systems might improve immunization rates in primary care.

The cost-utility of a return-to-work intervention in comparison to routine care for patients with mental disorders in Germany: Results from the RETURN project.

BACKGROUND: Only two-thirds of patients admitted to psychiatric wards return to their previous jobs. Return-to-work interventions in Germany are investigated for their effectiveness, but information regarding cost-effectiveness is lacking. This study investigates the cost-utility of a return-to-work intervention for patients with mental disorders compared to treatment as usual (TAU). METHODS: We used data from a cluster-randomised controlled trial including 166 patients from 28 inpatient psychiatric wards providing data at 6- and 12-month follow-ups. Health and social care service use was measured with the Client Sociodemographic and Service Receipt Inventory. Quality of life was measured with the EQ-5D-3L questionnaire. Cost-utility analysis was performed by calculating additional costs per one additional QALY (Quality-Adjusted Life Years) gained by receiving the support of return-to-work experts, in comparison to TAU. RESULTS: No significant cost or QALY difference between the intervention and control groups has been detected. The return-to-work intervention cannot be identified as cost-effective in comparison to TAU. CONCLUSIONS: The employment of return-to-work experts could not reach the threshold of providing good value for money. TAU, therefore, seems to be sufficient support for the target group.

Supporting return to work after psychiatric hospitalization-A cluster randomized study (RETURN-study).

BACKGROUND: If people with episodic mental-health conditions lose their job due to an episode of their mental illness, they often experience personal negative consequences. Therefore, reintegration after sick leave is critical to avoid unfavorable courses of disease, longer inability to work, long payment of sickness benefits, and unemployment. Existing return-to-work (RTW) programs have mainly focused on "common mental disorders" and often used very elaborate and costly interventions without yielding convincing effects. It was the aim of the RETURN study to evaluate an easy-to-implement RTW intervention specifically addressing persons with mental illnesses being so severe that they require inpatient treatment. METHODS: The RETURN study was a multi-center, cluster-randomized controlled trial in acute psychiatric wards addressing inpatients suffering from a psychiatric disorder. In intervention wards, case managers (RTW experts) were introduced who supported patients in their RTW process, while in control wards treatment, as usual, was continued. RESULTS: A total of 268 patients were recruited for the trial. Patients in the intervention group had more often returned to their workplace at 6 and 12 months, which was also mirrored in more days at work. These group differences were statistically significant at 6 months. However, for the main outcome (days at work at 12 months), differences were no longer statistically significant (p = 0.14). Intervention patients returned to their workplace earlier than patients in the control group (p = 0.040). CONCLUSIONS: The RETURN intervention has shown the potential of case-management interventions when addressing RTW. Further analyses, especially the qualitative ones, may help to better understand limitations and potential areas for improvement.

How should patients behave to facilitate shared decision making--the doctors' view.

OBJECTIVE: To study how physicians feel about patients' efforts to be engaged in shared decision making (SDM). STUDY SETTING AND DESIGN: Survey of physicians from distinctly different medical disciplines (238 psychiatrists and 169 vascular surgeons). Participants were requested to judge which patient behaviours they find helpful and which behaviours detrimental for SDM. RESULTS: Psychiatrists and surgeons had rather positive attitudes about active patient behaviours. However, there were quite a few patient behaviours (e.g. searching the Internet, being assertive towards the doctor) which provoked ambivalent or negative attitudes. DISCUSSION AND CONCLUSIONS: Physicians are generally quite open towards active patient behaviour in the consultation. They, however, do consider it as less helpful and become more annoyed if patients insist on their preferences and doubt their doctors' recommendations. Physicians must realize that SDM implies giving up decisional power and try to be more flexible in their interactions with patients.

Do physicians' recommendations pull patients away from their preferred treatment options?

CONTEXT AND OBJECTIVE: Shared decision making is especially advocated for preference-sensitive decisions. We investigated whether physicians' recommendations pull patients away from their preferred treatment option when making a preference-sensitive decision. DESIGN, PARTICIPANTS AND METHODS: Inpatients (N = 102 with schizophrenia, N = 101 with multiple sclerosis) were presented with a hypothetical scenario (the choice between two drugs). They were first asked about their preferences concerning the two drugs and then they received a (fictitious) clinician's recommendation that was contrary to their preferences. Subsequently they made a final choice between the two drugs. MAIN OUTCOME MEASURES: The main outcome measure was whether the patient followed the physician's advice in the hypothetical scenario. Thereby patient's (pre-recommendation) preferences served as a baseline. RESULTS: In the decision scenario, about 48% of the patients with schizophrenia and 26% of the patients with multiple sclerosis followed the advice of their physician and thus chose the treatment option that went against their initial preferences. Patients who followed their physician's advice were less satisfied with their decision than patients not following their physician's advice (schizophrenia: t = 2.61, P = 0.01; multiple sclerosis: t = 2.67, P = 0.009). DISCUSSION AND CONCLUSIONS: When sharing decisions with patients, physicians should be aware that their advice might influence patients' decisions away from their preferred treatment option. They should encourage their patients to identify their own preferences and help to find the treatment option most consistent with them.

Factor Retention Using Machine Learning With Ordinal Data.

Determining the number of factors in exploratory factor analysis is probably the most crucial decision when conducting the analysis as it clearly influences the meaningfulness of the results (i.e., factorial validity). A new method called the Factor Forest that combines data simulation and machine learning has been developed recently. This method based on simulated data reached very high accuracy for multivariate normal data, but it has not yet been tested with ordinal data. Hence, in this simulation study, we evaluated the Factor Forest with ordinal data based on different numbers of categories (2-6 categories) and compared it to common factor retention criteria. It showed higher overall accuracy for all types of ordinal data than all common factor retention criteria that were used for comparison (Parallel Analysis, Comparison Data, the Empirical Kaiser Criterion and the Kaiser Guttman Rule). The results indicate that the Factor Forest is applicable to ordinal data with at least five categories (typical scale in questionnaire research) in the majority of conditions and to binary or ordinal data based on items with less categories when the sample size is large.