Effects of (de)motivating supervision styles on junior doctors' intrinsic motivation through basic psychological need frustration and satisfaction: an experimental vignette study.

In clinical practice, junior doctors regularly receive supervision from consultants. Drawing on Basic Psychological Needs Theory, consultants' supervision styles are likely to affect junior doctors' intrinsic motivation differently in terms of psychological need frustration and psychological need satisfaction. To examine the effects of (de)motivating supervision styles, we conducted two experimental vignette studies among junior doctors. In Study 1 (N = 150, 73.3% female), we used a 2 (need support: high vs. low) x 2 (directiveness: high vs. low) between-subjects design and, in Study 2, a within-subjects design with the same factors (N = 46, 71.7% female). Both studies revealed a consistent positive effect of need-supportive supervision styles on psychological need satisfaction (+), need frustration (-), and intrinsic motivation (+). Particularly in Study 2, the main effect of need-supportive styles was strengthened by supervisor's directiveness. Moreover, in both studies, the effects of supervision styles on intrinsic motivation were explained through psychological need frustration and psychological need satisfaction. We discuss the implications of these findings for postgraduate clinical training.

A multiverse analysis of early attempts to replicate memory suppression with the Think/No-think Task.

In 2001, Anderson and Green [2001. Suppressing unwanted memories by executive control. Nature, 410(6826), 366-369] showed memory suppression using a novel Think/No-think (TNT) task. When participants attempted to prevent studied words from entering awareness, they reported fewer of those words than baseline words in subsequent cued recall (i.e., suppression effect). The TNT literature contains predominantly positive findings and few null-results. Therefore we report unpublished replications conducted in the 2000s (N = 49; N = 36). As the features of the data obtained with the TNT task call for a variety of plausible solutions, we report parallel "universes" of data-analyses (i.e., multiverse analysis) testing the suppression effect. Two published studies (Wessel et al., 2005. Dissociation and memory suppression: A comparison of high and low dissociative individuals' performance on the Think-No think Task. Personality and Individual Differences, 39(8), 1461-1470, N = 68; Wessel et al., 2010. Cognitive control and suppression of memories of an emotional film. Journal of Behavior Therapy and Experimental Psychiatry, 41(2), 83-89. https://doi.org/10.1016/j.jbtep.2009.10.005, N = 80) were reanalysed in a similar fashion. For recall probed with studied cues (Same Probes, SP), some tests (sample 3) or all (samples 2 and 4) showed statistically significant suppression effects, whereas in sample 1, only one test showed significance. Recall probed with novel cues (Independent Probes, IP) predominantly rendered non-significant results. The absence of statistically significant IP suppression effects raises problems for inhibition theory and its implication that repression is a viable mechanism of forgetting. The pre-registration, materials, data, and code are publicly available (https://osf.io/qgcy5/).

Improving confidence intervals for normed test scores: Include uncertainty due to sampling variability.

Test publishers usually provide confidence intervals (CIs) for normed test scores that reflect the uncertainty due to the unreliability of the tests. The uncertainty due to sampling variability in the norming phase is ignored. To express uncertainty due to norming, we propose a flexible method that is applicable in continuous norming and allows for a variety of score distributions, using Generalized Additive Models for Location, Scale, and Shape (GAMLSS; Rigby & Stasinopoulos, 2005). We assessed the performance of this method in a simulation study, by examining the quality of the resulting CIs. We varied the population model, procedure of estimating the CI, confidence level, sample size, value of the predictor, extremity of the test score, and type of variance-covariance matrix. The results showed that good quality of the CIs could be achieved in most conditions. The method is illustrated using normative data of the SON-R 6-40 test. We recommend test developers to use this approach to arrive at CIs, and thus properly express the uncertainty due to norm sampling fluctuations, in the context of continuous norming. Adopting this approach will help (e.g., clinical) practitioners to obtain a fair picture of the person assessed.

No Menstrual Cyclicity in Mood and Interpersonal Behaviour in Nine Women with Self-Reported Premenstrual Syndrome.

BACKGROUND/AIMS: Before diagnosing premenstrual dysphoric disorder (PMDD), 2 months of prospective assessment are required to confirm menstrual cyclicity in symptoms. For a diagnosis of premenstrual syndrome (PMS), this is not required. Women with PMDD and PMS often report that their symptoms interfere with mood and social functioning, and are said to show cyclical changes in interpersonal behaviour, but this has not been examined using a prospective approach. We sampled cyclicity in mood and interpersonal behaviour for 2 months in women with self- reported PMS. METHODS: Participants met the criteria for PMS on the Premenstrual Symptoms Screening Tool (PSST), a retrospective questionnaire. For 2 menstrual cycles, after each social interaction, they used the online software TEMPEST to record on their smartphones how they felt and behaved. We examined within-person variability in negative affect, positive affect, quarrelsomeness, and agreeableness. RESULTS: Participants evaluated TEMPEST as positive. However, we found no evidence for menstrual cyclicity in mood and interpersonal behaviour in any of the individual women (n = 9). CONCLUSION: Retrospective questionnaires such as the PSST may lead to oversampling of PMS. The diagnosis of PMS, like that of PMDD, might require 2 months of prospective assessment.

Gender differences in Dutch research funding over time: A statistical investigation of the innovation scheme 2012-2021.

BACKGROUND: In 2015, the Dutch research council, NWO, took measures to combat gender bias disadvantaging female applicants in a popular three-tiered funding scheme called the Talent Programme. The innovation scheme consists of three grants for different career stages, called Veni, Vidi and Vici. OBJECTIVES: This paper studies the question whether or not NWO has been successful in removing gender differences in their funding procedure. METHODS: Using all available data from 2012 onwards of grant applications in the Talent Programme (16,249 applications of which 2,449 received funding), we study whether these measures had an effect using binomial generalized linear models. RESULTS: We find strong statistical evidence of a shift in gender effects in favour of female applicants in the first tier, the Veni (p < .001). Significant gender differences are not found in the two other tiers, the Vidi and Vici schemes. CONCLUSIONS: In recent years, female applicants are more likely to be awarded with a Veni grant than male applicants and this gender gap has increased over time. This suggests that gender differences still exist in the assessment of Talent Programme submissions, albeit in a different direction than a decade ago.

Mixture multilevel vector-autoregressive modeling.

With the rising popularity of intensive longitudinal research, the modeling techniques for such data are increasingly focused on individual differences. Here we present mixture multilevel vector-autoregressive modeling, which extends multilevel vector-autoregressive modeling by including a mixture, to identify individuals with similar traits and dynamic processes. This exploratory model identifies mixture components, where each component refers to individuals with similarities in means (expressing traits), autoregressions, and cross-regressions (expressing dynamics), while allowing for some interindividual differences in these attributes. Key issues in modeling are discussed, where the issue of centering predictors is examined in a small simulation study. The proposed model is validated in a simulation study and used to analyze the affective data from the COGITO study. These data consist of samples for two different age groups of over 100 individuals each who were measured for about 100 days. We demonstrate the advantage of exploratory identifying mixture components by analyzing these heterogeneous samples jointly. The model identifies three distinct components, and we provide an interpretation for each component motivated by developmental psychology. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A comprehensive model framework for between-individual differences in longitudinal data.

Across different fields of research, the similarities and differences between various longitudinal models are not always eminently clear due to differences in data structure, application area, and terminology. Here we propose a comprehensive model framework that will allow simple comparisons between longitudinal models, to ease their empirical application and interpretation. At the within-individual level, our model framework accounts for various attributes of longitudinal data, such as growth and decline, cyclical trends, and the dynamic interplay between variables over time. At the between-individual level, our framework contains continuous and categorical latent variables to account for between-individual differences. This framework encompasses several well-known longitudinal models, including multilevel regression models, growth curve models, growth mixture models, vector-autoregressive models, and multilevel vector-autoregressive models. The general model framework is specified and its key characteristics are illustrated using famous longitudinal models as concrete examples. Various longitudinal models are reviewed and it is shown that all these models can be united into our comprehensive model framework. Extensions to the model framework are discussed. Recommendations for selecting and specifying longitudinal models are made for empirical researchers who aim to account for between-individual differences. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Visualizing Uncertainty to Promote Clinicians' Understanding of Measurement Error.

Measurement error is an inherent part of any test score. This uncertainty is generally communicated in ways that can be difficult to understand for clinical practitioners. In this empirical study, we evaluate the impact of several communication formats on the interpretation of measurement accuracy and its influence on the decision-making process in clinical practice. We provided 230 clinical practitioners with score reports in five formats: textual, error bar, violin plot, diamond plot, and quantile dot plot. We found that quantile dot plots significantly increased accuracy in the assessment of measurement uncertainty compared with other formats. However, a direct relation between visualization format and decision quality could not be found. Although traditional confidence intervals and error bars were favored by many participants due to their familiarity, responses revealed several misconceptions that make the suitability of these formats for communicating uncertainty questionable. Our results indicate that new visualization formats can successfully reduce errors in interpretation.

An experience sampling study on the links between daily teacher self-efficacy, need-supportive teaching and student intrinsic motivation.

Introduction: Why are some teachers more successful at motivating students than others? We know from previous literature that teachers' self-efficacy relates to the extent in which they engage in need-supportive teaching in the classroom, which in turn relates to student intrinsic motivation. However, teachers' self-efficacy is hypothesized to be dependent on their previous mastery experiences, e.g., of engaging students in the classroom. This "feedback loop" where the teacher not only influences the student but also the other way around, in a process unfolding over time, can only be investigated empirically with an intensive longitudinal design. This is precisely what we did in the current study. Methods: Secondary school teachers (n = 4) and students (n = 90) participated in an experience sampling study throughout one school year, resulting in a unique dataset with 48-59 repeated measurement points per class. Results: Visual exploration of the time series revealed that teacher self-efficacy can vary substantially from lesson to lesson, with characteristic patterns of stabilization and de-stabilization. We conducted Vector Autoregressive Analysis (VAR) for each of the four cases to test whether, and how, the variables relate to each other over time. We found an "overspill effect" for student motivation, meaning that students' motivation in today's lesson predicts their motivation in tomorrow's lesson. Furthermore, in two cases we found that today's student motivation predicts tomorrow's teacher self-efficacy, but not the other way around.

Regaining control of your emotions? Investigating the mechanisms underlying effects of cognitive control training for remitted depressed patients.

Studies suggest that cognitive control training shows potential as a preventive intervention for depression. At the same time, little is known regarding the mechanisms underlying effects of cognitive control training. Informed by theoretical frameworks of cognitive risk for recurrent depression (De Raedt & Koster, 2010; Siegle et al., 2007), the current study sought to model direct effects of cognitive control training on the complex interplay between affect, emotion regulation, residual symptomatology, and resilience in a sample of remitted depressed patients (n = 92). Combining a 4-week experience sampling procedure with an experimental manipulation of cognitive control, we observed beneficial effects of cognitive control training on deployment of rumination. In addition, we obtained evidence for the causal involvement of cognitive control in efficacy of emotion regulation. In contrast to our expectations, cognitive control training did not exert immediate effects on residual symptomatology or resilience when compared with an active control condition, nor did cognitive control training impact the complex interplay between these variables. Overall, immediate effects of cognitive control training on functioning in daily life were limited. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A Network Approach to Trauma, Dissociative Symptoms, and Psychosis Symptoms in Schizophrenia Spectrum Disorders.

BACKGROUND: Dissociative experiences commonly occur in schizophrenia spectrum disorders (SSD). Yet little is known about how dissociative experiences in SSD are related to SSD symptoms. Accordingly, we investigated the relations between dissociative experiences and SSD symptoms, focusing on symptoms bridging these 2 symptom clusters as well as their relation to reported trauma history. STUDY DESIGN: Network analyses were conducted on the responses of 248 individuals with an SSD who enrolled from multiple mental health centers in The Netherlands. Dissociative experiences were assessed via the Dissociative Experience Scale, SSD symptoms using the Positive and Negative Syndrome Scale, and trauma history through the Trauma History Questionnaire. STUDY RESULTS: The results indicated that dissociative symptoms in SSD are mostly independent of other symptoms, but that emotional distress bridges between the dissociative and SSD symptom clusters. Furthermore, results revealed associations between positive and negative SSD symptoms and trauma through emotional distress, whereas dissociative symptoms remained relatively isolated. CONCLUSION: Because SSD symptoms and dissociative experiences clustered relatively independent from each other, our findings promote the idea of tailored treatment approaches for individuals with an SSD with frequent dissociative experiences, specifically targeting these symptoms.

Congruency of multimodal data-driven personalization with shared decision-making for StayFine: individualized app-based relapse prevention for anxiety and depression in young people.

Tailoring interventions to the individual has been hypothesized to improve treatment efficacy. Personalization of target-specific underlying mechanisms might improve treatment effects as well as adherence. Data-driven personalization of treatment, however, is still in its infancy, especially concerning the integration of multiple sources of data-driven advice with shared decision-making. This study describes an innovative type of data-driven personalization in the context of StayFine, a guided app-based relapse prevention intervention for 13- to 21-year-olds in remission of anxiety or depressive disorders (n = 74). Participants receive six modules, of which three are chosen from five optional modules. Optional modules are Enhancing Positive Affect, Behavioral Activation, Exposure, Sleep, and Wellness. All participants receive Psycho-Education, Cognitive Restructuring, and a Relapse Prevention Plan. The personalization approach is based on four sources: (1) prior diagnoses (diagnostic interview), (2) transdiagnostic psychological factors (online self-report questionnaires), (3) individual symptom networks (ecological momentary assessment, based on a two-week diary with six time points per day), and subsequently, (4) patient preference based on shared decision-making with a trained expert by experience. This study details and evaluates this innovative type of personalization approach, comparing the congruency of advised modules between the data-driven sources (1-3) with one another and with the chosen modules during the shared decision-making process (4). The results show that sources of data-driven personalization provide complementary advice rather than a confirmatory one. The indications of the modules Exposure and Behavioral Activation were mostly based on the diagnostic interview, Sleep on the questionnaires, and Enhancing Positive Affect on the network model. Shared decision-making showed a preference for modules improving positive concepts rather than combating negative ones, as an addition to the data-driven advice. Future studies need to test whether treatment outcomes and dropout rates are improved through personalization.

General Mental Health, Loneliness, and Life Satisfaction in the Context of COVID-19 Policies: A 2-Year Cohort Study in the Netherlands, April 2020-January 2022.

OBJECTIVE: Although the COVID-19 pandemic has affected mental health, understanding who has been affected most and why is incomplete. We sought to understand changes in mental health in the context of transmission numbers and pandemic (social) restrictions and whether changes in mental health varied among population groups. METHODS: We analyzed data from 92 062 people (aged ≥16 years and able to read Dutch) who participated in the Corona Behavioral Unit cohort study at the National Institute for Public Health and the Environment, the Netherlands, from April 17, 2020, through January 25, 2022. Participants self-reported mental well-being through multiple rounds of surveys. We used a multivariable linear mixed-effects model to analyze loneliness, general mental health, and life satisfaction. RESULTS: As strictness of pandemic prevention measures and social restrictions increased, people's feelings of loneliness increased and mental health and life satisfaction decreased. As restrictions were relaxed, loneliness decreased and general mental health improved. Younger people (aged 16-24 y) versus older people (aged ≥40 y), people with low (vs high) education levels, and people living alone (vs living together) were more likely to have negative well-being outcomes. We observed that trajectories over time differed considerably only by age, with participants aged 16-24 years affected substantially more than participants aged ≥40 years by pandemic social restrictions. These patterns were consistent across multiple waves of SARS-CoV-2 infection. CONCLUSIONS: Our findings suggest that the social restrictions imposed by the Dutch government during the study period were associated with reduced mental well-being, especially among younger people. However, people appeared resilient as they recovered during periods when restrictions were relaxed. Monitoring and supporting well-being, in particular to reduce loneliness, may help younger people during periods of intense social restrictions.

The dynamics of social activation and suspiciousness in individuals at ultra-high risk for psychosis.

INTRODUCTION: Social functioning is often impaired during the ultra-high risk (UHR) phase for psychosis, but group-level studies regarding the role of social functioning in transition to psychosis are inconsistent. Exploring the inter-individual differences which underlie the association between social functioning and psychotic symptoms in this phase could yield new insights. OBJECTIVE: To examine the idiographic and dynamic association between social activation and suspiciousness in individuals at UHR for psychosis using time-series analysis. METHODS: Twenty individuals at UHR for psychosis completed a diary application every evening for 90 days. Two items on social activation (quantity: 'time spent alone' and quality: 'feeling supported') and two items on suspiciousness ('feeling suspicious' and 'feeling disliked') were used. Time series (T = 90) of each individual were analyzed using vector auto regression analysis (VAR), to estimate the lagged (over 1 day) effect of social activation on suspiciousness, and vice versa, as well as their contemporaneous associations. RESULTS: Heterogeneous person-specific associations between social activation and suspiciousness were found in terms of strength, direction and temporal aspects. CONCLUSIONS: The association between social activation and suspiciousness differs amongst individuals who are at UHR for psychosis. These findings underline the importance of tailoring psychosocial interventions to the individual. Future studies may examine whether using results of single-subject studies in clinical practice to personalize treatment goals leads to better treatment outcomes.

Species identification skills predict in-depth knowledge about species.

To raise biodiversity awareness effectively, communicators should be aware of knowledge levels in their audiences. Species identification skills have been used in the past as a measure of what people know about species, yet it is not known whether they serve as good indicators. To study the link between species identification and in-depth species knowledge, we presented an animal knowledge test to an online audience of over 7,000 Dutch adults, and used correlation and regression analyses to determine the extent to which species identification predicts in-depth knowledge about species' origin, habitat, diet, and behavior. We found that in-depth knowledge was higher in those who correctly identified species as compared with those who did not correctly identify species, for all four types of in-depth knowledge. Moreover, as compared to alternative variables (work, age, gender, and educational level), species identification was by far the best predictor for in-depth knowledge about species. However, species identification levels were generally higher than levels of in-depth knowledge, and knowledge gaps and misconceptions were uncovered. The results confirm the value of species identification tests, but also highlight limitations and challenges that should be taken into account when establishing knowledge levels and communicating biodiversity.

Misleading graphs in context: Less misleading than expected.

Misleading graphs are a source of misinformation that worry many experts. Especially people with a low graph literacy are thought to be persuaded by graphs that misrepresent the underlying data. But we know little about how people interpret misleading graphs and how these graphs influence their opinions. In this study we focus on the effect of truncating the y-axis for a line chart which exaggerates an upgoing trend. In a randomized controlled trial, we showed participants either a normal or a misleading chart, and we did so in two different contexts. After they had seen the graphs, we asked participants their opinion on the trend and to give an estimation of the increase. Finally we measured their graph literacy. Our results show that context is the only significant factor in opinion-forming; the misleading graph and graph literacy had no effect. None of these factors had a significant impact on estimations for the increase. These results show that people might be less susceptible to misleading graphs than we thought and that context has more impact than a misleading y-axis.