Toward a formalized account of attitudes: The Causal Attitude Network (CAN) model

Are different countries equally green with envy? A comparison of the everyday concept of envy in the United States, Spain, and Germany

Using a prototype approach to emotion concepts, we mapped the internal structure and content of the everyday concept of envy (as used in the United States) and its translation equivalents of envidia in Spanish and Neid in German. In Study 1 (total N = 415), the features of the concept of envy, envidia, and Neid were generated via an open-ended questionnaire. In Study 2 (total N = 404), participants rated the degree of typicality of the constitutive features on a forced-choice questionnaire. The prototype analysis of envy, supplemented with network analyses, revealed that the largest connected set of features of envy, envidia, and Neid shared a group of central features, including features related to success or to people with a better appearance. Still, envy, envidia, and Neid did differ with respect to their constituent peripheral features as well as the density of their networks, their structure, and the betweenness centrality of the nodes. These results suggest that a prototype approach combined with network analysis is a convenient approach for studying the internal structure of everyday emotion concepts and the degree of overlap with respect to the translation equivalents in different countries.

Messaging about very low nicotine cigarettes (VLNCs) to influence policy attitudes, harm perceptions and smoking motivations: a discrete choice experiment

BACKGROUND

To reduce smoking and the harms it causes, countries, including the USA, are considering policies to reduce nicotine in combustible tobacco to minimally addictive levels. Effective messages about very low nicotine cigarettes (VLNCs) and this policy are crucial in combating misperceptions threatening the policy's effectiveness.

DATA AND METHODS

A discrete choice experiment assessed messages about VLNCs. Participants were 590 adults who smoked exclusively, 379 adults who both smoked and used e-cigarettes, 443 adults who formerly smoked and 351 young adults who never smoked (total n=1763). Seven message attributes were varied systematically (source, harm, chemicals, nicotine, satisfaction, addictiveness and quitting efficacy). Outcomes were selection of messages that generated the most positive attitude towards reduced nicotine policy, the greatest perceived harmfulness of VLNCs, and most strongly motivated quitting and initiating behaviour for VLNCs.

RESULTS

Information about specific harms and chemicals of VLNCs had the largest effects on selection of messages as eliciting more negative attitudes towards VLNCs policy, increasing perceived VLNC harmfulness, increasing motivation to quit VLNCs and decreasing motivation to try VLNCs. Messages with information about quitting efficacy were selected as more motivating to quit among those who smoke, but also more motivating to try VLNCs among those who do not smoke.

CONCLUSION

Harm and chemical information can be prioritised to ensure VLNCs are not misperceived as less harmful than regular cigarettes. Messages about increased quitting efficacy and reduced addictiveness associated with VLNCs may backfire if presented to those who do not smoke.

Climate change belief systems across political groups in the United States

Beliefs and attitudes form the core of public opinion about climate change. Network analysis can reveal the structural configuration of these beliefs and attitudes. In this research, we utilize a belief system framework to identify key psychological elements, track change in the density of these belief systems over time and across political groups, and analyze the structural heterogeneity of belief systems within and between political groups in the United States. Drawing on fifteen waves of nationally representative survey data from 2010 to 2021 (N = 16,742), our findings indicate that worry about climate change is the most central psychological element. Interestingly, we find that among politically unaffiliated individuals, the connections between psychological elements have strengthened over time, implying an increase in the consistency of belief systems within this group. Despite the political polarization in beliefs about climate change between Republicans and Democrats, our findings reveal that the ways these two groups organize and structure climate change beliefs systems are not markedly different compared to those of other groups. These findings provide theoretical and practical insights for climate change experts and communicators.

Toward Understanding of the Social Hysteresis: Insights From Agent-Based Modeling

Hysteresis has been used to understand various social phenomena, such as political polarization, the persistence of the vaccination-compliance problem, or the delayed response of employees in a firm to wage incentives. The aim of this article is to show the insights that can be gained from using agent-based models (ABMs) to study hysteresis. To build up an intuition about hysteresis, we start with an illustrative example from physics that demonstrates how hysteresis manifests as collective memory. Next, we present examples of hysteresis in psychology and social systems. We then present two simple ABMs of binary decisions-the Ising model and the q-voter model-to explain how hysteresis can be observed in ABMs. Specifically, we show that hysteresis can result from the influence of various external factors present in social systems, such as organizational polices, governmental laws, or mass media campaigns, as well as internal noise associated with random changes in agent decisions. Finally, we clarify the relationship between several closely related concepts such as order-disorder transitions or bifurcation, and we conclude the article with a discussion of the advantages of ABMs.

Recognize the Value of the Sum Score, Psychometrics' Greatest Accomplishment

The sum score on a psychological test is, and should continue to be, a tool central in psychometric practice. This position runs counter to several psychometricians' belief that the sum score represents a pre-scientific conception that must be abandoned from psychometrics in favor of latent variables. First, we reiterate that the sum score stochastically orders the latent variable in a wide variety of much-used item response models. In fact, item response theory provides a mathematically based justification for the ordinal use of the sum score. Second, because discussions about the sum score often involve its reliability and estimation methods as well, we show that, based on very general assumptions, classical test theory provides a family of lower bounds several of which are close to the true reliability under reasonable conditions. Finally, we argue that eventually sum scores derive their value from the degree to which they enable predicting practically relevant events and behaviors. None of our discussion is meant to discredit modern measurement models; they have their own merits unattainable for classical test theory, but the latter model provides impressive contributions to psychometrics based on very few assumptions that seem to have become obscured in the past few decades. Their generality and practical usefulness add to the accomplishments of more recent approaches.

A Network Approach to Investigate the Dynamics of Individual and Collective Beliefs: Advances and Applications of the BENDING Model

Changing entrenched beliefs to alter people's behavior and increase societal welfare has been at the forefront of behavioral-science research, but with limited success. Here, we propose a new framework of characterizing beliefs as a multidimensional system of interdependent mental representations across three cognitive structures (e.g., beliefs, evidence, and perceived norms) that are dynamically influenced by complex informational landscapes: the BENDING (Beliefs, Evidence, Norms, Dynamic Information Networked Graphs) model. This account of individual and collective beliefs helps explain beliefs' resilience to interventions and suggests that a promising avenue for increasing the effectiveness of misinformation-reduction efforts might involve graph-based representations of communities' belief systems. This framework also opens new avenues for future research with meaningful implications for some of the most critical challenges facing modern society, from the climate crisis to pandemic preparedness.

Dairy consumption and incident prediabetes: prospective associations and network models in the large population-based Lifelines Study

BACKGROUND

Evidence on associations between dairy consumption and incident prediabetes is inconsistent. One potential explanation for heterogeneity is that health behavior and food intake covary with the consumption of various high-fat and low-fat dairy types.

OBJECTIVE

The objective was to investigate the associations of total dairy and dairy types with incident prediabetes and to assess how dairy intake is linked with metabolic risk factors, lifestyle behaviors, and foods, as potential explanations for these associations.

METHODS

Overall, 74,132 participants from the prospective population-based Lifelines study were included (mean age, 45.5 ± 12.3 y; 59.7% female). Baseline dairy intake was measured using a validated food frequency questionnaire. Prediabetes at follow-up was defined based on the World Health Organization/International Expert Committee criteria as fasting plasma glucose of 110-125 mg/dL or glycated hemoglobin concentrations of 6.0%-6.5%. Associations were analyzed using Poisson regression models adjusted for social demographics, lifestyle behaviors, family history of diabetes, and food group intake. Interconnections were assessed with mixed graphical model networks.

RESULTS

At a mean follow-up of 4.1 ± 1.1 y, 2746 participants developed prediabetes (3.7%). In regression analyses, neutral associations were found for most dairy types. Intake of plain milk and low-fat milk were associated with a higher risk of prediabetes in the top compared with bottom quartiles (relative risk [RR]: 1.17; 95% confidence interval [CI]: 1.05, 1.30; P-trend = 0.04 and RR: 1.18; 95% CI: 1.06, 1.31; P-trend =0.01). Strong but nonsignificant effect estimates for high-fat yogurt in relation to prediabetes were found (RRservings/day: 0.80; 95% CI: 0.64, 1.01). The network analysis showed that low-fat milk clustered with energy-dense foods, including bread, meat, and high-fat cheese, whereas high-fat yogurt had no clear link with lifestyle risk factors and food intake.

CONCLUSIONS

In this large cohort of Dutch adults, low-fat milk intake was associated with higher prediabetes risk. Heterogeneous associations by dairy type and fat content might partly be attributed to confounding caused by behaviors and food intake related to dairy intake.

Exploring the efficacy of a low intensity psychological intervention for family members and carers of individuals with a first episode of psychosis in early intervention services

AIM

The study aimed to evaluate the efficacy, and explore carers' experience, of a brief carer focussed intervention in an Early Intervention in Psychosis (EIP) service using a mixed methods approach.

METHODS

Carers within EIP services were invited to have the intervention, comprising a psychoeducation and wellbeing component, and 153 carers completed routine outcome measures including the Brief Experience of Caregiving Inventory (BECI), The Warwick-Edinburgh Mental Well-being Scale (WEMWEBS) and the Hospital Anxiety and Depression Scale (HADS) at baseline and after the completion of the intervention. Separately, nine carers took part in semi-structured interviews about their experience of the intervention.

RESULTS

The intervention resulted in improvement of overall well-being, a reduction in self-reported anxiety and caregiving experience relating to difficult behaviours and stigma/effects on the family. Overall, the carers' subjective experiences of the intervention were positive. Thematic analysis indicated epistemic trust indexed by the connection carers achieved with the service, an experience of being valued and of experiencing change through the intervention.

CONCLUSION

A short, 8 weeks intervention delivered by assistant psychologists, may offer an effective method for facilitating understanding of the illness and acclimatizing to new challenges. Exploring the effectiveness of psychoeducation and capturing this with specific measures may allow the service to make meaningful adaptations to their intervention.

Understanding public perceptions toward sustainable healthcare through psychological network analysis of material preference and attitudes toward plastic medical devices

Recent and potential future health-care users (i.e., the public) are important stakeholders in the transition toward environmentally sustainable healthcare. However, it remains unclear whether, according to the public, there is room for sustainable innovations in materials for plastic medical devices (PMD). This study explores preferences regarding conventional or bio-based PMD, and psychological mechanisms underlying these preferences. We administered two surveys among Dutch adults from a research panel. Results from the first survey (i.e., open-text survey on attitude elements; NStudy1 = 66) served as input for the second survey (i.e., Likert-scale survey on beliefs, emotions, perceived control, social norms, trust, related to current and bio-based PMD, and health and age; NStudy2 = 1001; Mage = 47.35; 54.4% female). The second survey was completed by 501 participants who, in the last two years, received care in which PMD were used, and 500 participants who did not. Cross-sectional psychological networks were estimated with data from the second study using the EBICglasso method. Results showed that participants preferred bio-based over conventional PMD, and this applied regardless of whether devices are used inside or outside of the body. Results also showed emotions play an important role, with emotions regarding bio-based PMD being strongly related to preference. Furthermore, comparing recent and potential future receivers of PMD revealed differences in preference but comparable relations between preference and other psychological variables. This study shows that receivers' perspectives should not be seen as potential barriers, but as additional motivation for transitioning toward sustainable healthcare. Recommendations for implementation are discussed.

A psychosocial network approach studying biomedical HIV prevention uptake between 2017 and 2019

Biomedical HIV-prevention strategies (BmPS) among men who have sex with men (MSM), such as pre-exposure prophylaxis (PrEP) and viral load sorting (VLS), are essential but relatively new and their uptake gradual. Using an extension of the causal attitude network approach, we investigated which beliefs are related to uptake of PrEP and VLS at each time-point. We included 632 HIV-negative MSM from the Amsterdam Cohort Studies from four data-waves between 2017 and 2019. We estimated weighted, undirected networks for each time-point, where we included pairwise interactions of PrEP and VLS uptake and related beliefs. PrEP use increased from 10 to 31% (p < 0.001), while VLS was reported by 7-10% at each time-point. Uptake of both BmPS was directly related to the perceived positive impact of the strategy on one's quality of sex life and perceived supportive social norms. Overall network structure differed between time points, specifically in regard to PrEP. At earlier time points, perceptions of efficacy and affordability played an important role for PrEP uptake, while more recently social and health-related concerns became increasingly important.The network structure differed across data-waves, suggesting specific time changes in uptake motives. These findings may be used in communication to increase prevention uptake.

No brute facts: The Principle of Sufficient Reason in ordinary thought

The Principle of Sufficient Reason (PSR) has been an influential thesis since the earliest stages of western philosophy. According to a simple version of the PSR, for every fact, there must be an explanation of that fact. In the present research, we investigate whether people presuppose a PSR-like principle in ordinary judgment. Across five studies (N = 1121 in total, U.S., Prolific), we find that participants consistently make judgments that conform to the PSR. Such judgments predictably track the metaphysical aspects of explanation relevant to the PSR (Study 1) and diverge from related epistemic judgments about expected explanations (Study 2) and value judgments about desired explanations (Study 3). Moreover, we find participants' PSR-conforming judgments apply to a large set of facts that were sampled from random Wikipedia entries (Studies 4-5). Altogether, the present research suggests that a metaphysical presumption plays an important role in our explanatory inquiry, one that is distinct from the role of the epistemic and non-epistemic values that have been the focus of much recent work in cognitive psychology and philosophy of science.

Embedding Research on Emotion Duration in a Network Model

Contrary to early theorizing, emotions often last for longer periods of time. Variability in people's emotion duration contributes to psychopathologies. Therefore, emotion theories need to account for this variability. So far, reviews only list predictors of emotion duration without integrating them in a theoretical framework. Mechanisms explaining why these predictors relate to emotion duration remain unknown. I propose to embed research on emotion duration in a network model of emotions and illustrate the central ideas with simulations using a formal network model. In the network model, the components of an emotion have direct causal effects on each other. According to the model, emotions last longer (a) when the components are more strongly connected or (b) when the components have higher thresholds (i.e., they are more easily activated). High connectivity prolongs emotions because components are constantly reactivated. Higher thresholds prolong emotions because components are more easily reactivated even when connectivity is lower. Indirect evidence from research on emotion coherence and research on the relationship of predictors of emotion duration with components outside of emotional episodes supports the usefulness of the network model. I further argue and show in simulations that a common cause model, in which a latent emotion causes changes in emotion components, cannot account for research on emotion duration. Finally, I describe future directions for research on emotion duration and emotion dynamics from a network perspective.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42761-023-00203-3.

Organization of psychosocial factors associated with worry about acquiring SARS-CoV-2 among women undergoing cancer treatment: an empirical network comparison approach

OBJECTIVES

Pandemic-induced anxiety can have adverse mental and somatic health consequences on cancer patients (CP). This study aimed to (1) explore the intricate relationships between worry related to potential SARS-CoV-2 infection, COVID-19 perception, sociodemographic factors, and the perceived effectiveness of lockdown measures and (2) investigate if these relationships differ between cancer patients and individuals without a history of cancer (IWHC).

METHODS

We conducted a cross-sectional quantitative study in France between December 1 and 14, 2020. Network analysis was employed on a sample of 1889 women, including 282 cancer patients and 1607 noncancer individuals.

RESULTS

Our findings indicate that CP were 20% more likely to express worry than IWHC. Anxiety is embedded within a complex network involving sociodemographic, cognitive, and emotional factors. The emotional components related to COVID-19 perception were found to play a crucial role. The networks for both groups were observed to be identical.

CONCLUSIONS

Our study underscores the heightened vulnerability of cancer patients to pandemic-induced anxiety, emphasizing the crucial role of emotional components related to COVID-19 perception. The observed similarities in the anxiety network between cancer patients and those without a history of cancer suggest that universal approaches might be effective across groups.

IMPLICATIONS

Utilizing the Causal Attitude Network Model, we propose potential methods for managing and reducing individual anxiety levels.

Formalizing psychological interventions through network control theory

Despite the growing deployment of network representation to comprehend psychological phenomena, the question of whether and how networks can effectively describe the effects of psychological interventions remains elusive. Network control theory, the engineering study of networked interventions, has recently emerged as a viable methodology to characterize and guide interventions. However, there is a scarcity of empirical studies testing the extent to which it can be useful within a psychological context. In this paper, we investigate a representative psychological intervention experiment, use network control theory to model the intervention and predict its effect. Using this data, we showed that: (1) the observed psychological effect, in terms of sensitivity and specificity, relates to the regional network control theoretic metrics (average and modal controllability), (2) the size of change following intervention negatively correlates with a whole-network topology that quantifies the "ease" of change as described by control theory (control energy), and (3) responses after intervention can be predicted based on formal results from control theory. These insights assert that network control theory has significant potential as a tool for investigating psychological interventions. Drawing on this specific example and the overarching framework of network control theory, we further elaborate on the conceptualization of psychological interventions, methodological considerations, and future directions in this burgeoning field.

Investigation of the Relevant Factors in the Complexity of Chronic Low Back Pain Patients With a Physiotherapy Prescription: A Network Analysis Approach Comparing Chronic Pain-Free Individuals and Chronic Patients

OBJECTIVE

Chronic low back pain (CLBP) is the leading cause of disability worldwide, and several factors have been proposed as potential causes or cofactors. The aim of this study was to explore their direct and indirect relations to understand CLBP and identify relevant rehabilitation targets.

METHODS

A total of 119 patients with CLBP and 117 chronic pain-free individuals were assessed. A network analysis approach was used to explore the complexity of CLBP by assessing the relations between pain intensity, disability, functionality (physical, social, and psychological), age, body mass index, and education level.

RESULTS

The network analysis revealed the independence of pain and disability related to CLBP from age, sex, and body mass index. Crucially, pain intensity and disability are directly and strongly connected in chronic pain-free individuals, but not in patients with CLBP. Psychosocial functioning is related to pain intensity and disability indirectly through the mediation of one's general health perception and perceived physical functionality.

CONCLUSION

Clinicians should pay more attention to perceived physical functionality and psychosocial factors as they are tightly linked to CLBP. Indeed, pain intensity seems a suboptimal rehabilitation target. This study suggests that a biopsychosocial approach is much needed to investigate CLBP, but it also warns against overestimating the direct impact of each potential contributor.

TO CLAIM CME CREDITS

Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME.

CME OBJECTIVES

Upon completion of this article, the reader should be able to: (1) Recognize the relation of pain intensity, disability, and loss of function in patients with CLBP; (2) Determine the impact of the most common biological and psychosocial factors in addressing the assessment of chronic back pain patients; and (3) Enhance confidence in selecting the relevant outcomes for the assessment of patients with CLBP following a multidimensional assessment.

LEVEL

Advanced.

ACCREDITATION

The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™ . Physicians should only claim credit commensurate with the extent of their participation in the activity.

A 10-year prospectus for mathematical epidemiology

There is little significant work at the intersection of mathematical and computational epidemiology and detailed psychological processes, representations, and mechanisms. This is true despite general agreement in the scientific community and the general public that human behavior in its seemingly infinite variation and heterogeneity, susceptibility to bias, context, and habit is an integral if not fundamental component of what drives the dynamics of infectious disease. The COVID-19 pandemic serves as a close and poignant reminder. We offer a 10-year prospectus of kinds that centers around an unprecedented scientific approach: the integration of detailed psychological models into rigorous mathematical and computational epidemiological frameworks in a way that pushes the boundaries of both psychological science and population models of behavior.

A network approach to the relationship between career adaptability and starting salary among graduates

Career adaptability is a psychological resource for individuals to deal with career events, and it is a system of human-environment interaction. The components of the career adaptability concept are not independent of each other but rather an interactive network. The present study aims to shed light on the nomological network of career adaptability and the starting salary by investigating their indicators using network analysis to reveal their structural networks and interrelationships. In addition, we compared the similarities and differences between the networks of different gender groups. Results indicate that career adaptability directly connects to starting salary for graduates, and some indicators are the core factors that influence starting salary. Besides, the global structure of gender-specific networks is very similar. However, some differences have been detected, such as becoming curious about new opportunities is the male network's core, while the core of the female network is doing the right thing.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12144-023-04655-5.

The Structure of Compulsive Sexual Behavior: A Network Analysis Study

Compulsive sexual behavior is a phenomenon characterized by a persistent failure to control intense, repetitive sexual impulses or urges, resulting in repetitive sexual behavior that causes marked distress or impairment in personal, familial, social, educational, or occupational areas of functioning. Despite its major impact on mental health and quality of life, little is known about its internal structure and whether this phenomenon differs across genders, age groups, and risk status. By considering a large online sample (n = 3186; 68.3% males), ranging from 14 to 64 years old, compulsive sexual behavior was explored by means of network analysis. State-of-the-art analytical techniques were adopted to investigate the pattern of association among the different elements of compulsive sexual behavior, identify possible communities of nodes, pinpoint the most central nodes, and detect differences between males and females, among different age groups, as well as between individuals at low and high risk of developing a full-blown disorder. The analyses revealed that the network was characterized by three communities, namely Consequence, Preoccupation, and Perceived Dyscontrol, and that the most central node was related to (perceived) impulse dyscontrol. No substantial differences were found between males and females and across age. Failing to meet one's own commitments and responsibilities was more central in individuals at high risk of developing a full-blown disorder than in those at low risk.

Comparing the centrality symptoms of major depressive disorder samples across junior high school students, senior high school students, college students and elderly adults during city lockdown of COVID-19 pandemic-A network analysis

INTRODUCTION

Recently, in the view of network analysis, depression has been conceptualized as a complex and dynamic network model combining individual symptoms. To date, no studies have systematically examined and compared depressive symptom networks across different populations.

METHODS

A total of 36,105 participants were recruited and asked to complete the Patient Health Questionnaire-9 among junior high school students, senior high school students, college students, and elderly adults who were more susceptible to depression during the COVID-19 lockdown in China. In the analysis, we applied the optimal cutoff score ≥ 8 for students and a score ≥ 6 for elderly adults to identify 5830 participants who were likely to be depressed. The index of "strength" was used to identify central symptoms in the network structure.

RESULTS

The results showed that Sad Mood was the most central symptom among junior high school students, senior high school students, and college students, but the most central symptom in the elderly was Guilt. Among the top three central symptoms, Suicide Ideation was unique to senior high school students, while Anhedonia was most prevalent among college students. Guilt - Suicide Ideation, Anhedonia - Energy, Anhedonia - Sad Mood, and Sleep - Energy showed the strongest association among junior and senior high school students, college students, and elderly adults, respectively. NCT (i.e., Network Comparison Test) suggested that the network's global connectivity was ultimately inconsistent, but the network structure remained roughly intact.

CONCLUSION

In treatment, targeting central symptoms may be critical to alleviating depression.

Beyond collective intelligence: Collective adaptation

We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies, social environments and problem structures. Going beyond searching for 'intelligent' collectives, we integrate research from different disciplines and outline modelling approaches that can be used to begin answering questions such as why collectives sometimes fail to reach seemingly obvious solutions, how they change their strategies and network structures in response to different problems and how we can anticipate and perhaps change future harmful societal trajectories. We discuss the importance of considering path dependence, lack of optimization and collective myopia to understand the sometimes counterintuitive outcomes of collective adaptation. We call for a transdisciplinary, quantitative and societally useful social science that can help us to understand our rapidly changing and ever more complex societies, avoid collective disasters and reach the full potential of our ability to organize in adaptive collectives.

Spillover effects of anti-sugar-sweetened beverage messages: From consumption decisions to policy preferences

BACKGROUND

Intake of sugar-sweetened beverages (SSBs) is associated with many negative health outcomes. Efforts to curb consumption generally take one of two approaches: (a) Individual change based on the communication of personal risk information or (b) policies that limit or disincentivize the behavior, such as restricting access or implementing taxes.

METHODS AND RESULTS

Using samples of 2347 persons and 139 pro- and anti-SSB messages, this study tested whether individual-level persuasion attempts would spill over to voting intentions and whether that spillover would amplify or attenuate policy preferences. The influence of anti-SSB messages was seen in (a) direct, positive effects on intention to vote for restrictive policies and in (b) indirect, positive effects where change in intended consumption mediated message impact on change in voting intentions. Anti-SSB messages were generally more powerful than pro-SSB advertising at producing direct and indirect change. Yet, there was evidence of boomerang effects among small numbers of both SSB drinkers and nondrinkers.

CONCLUSIONS

Anti-SSB messages that target individual consumption bring about intentions to reduce consumption and increased receptivity to restrictive SSB policies.

Presenting wicked problems in a science museum: A methodology to study interest from a dynamic perspective

Science centers and science museums have an important social role in engaging people with science and technology relevant for complex societal problems-so called wicked problems. We used the case of personalized medicine to illustrate a methodology that can be used to inform the development of exhibitions on such wicked problems. The methodology that is presented is grounded in dynamic theories of interest development that define interest as a multidimensional construct involving knowledge, behavior (personal and general) value, self-efficacy, and emotion. The methodology uses a mixed method design that is able to (1) study the predictive effects of background variables on interest, (2) study the interest dimensions predicting individual interest, and (3) identify the most influential interest dimensions. We set up focus groups (N = 16, age = 20-74, low SES) to design a survey study (N = 341, age 19-89 years olds with a broad range of SES) about people's interest in personalized medicine. Results of a network analysis of the survey data show that despite the variety in emotions and knowledge about subtopics, these dimensions do not play a central role in the multidimensional interest construct. In contrast, general value and behavior (related to understanding scientific research) seem to be interesting candidates for eliciting situational interest that could have an effect on the more long term individual interest. These results are specific for the case of personalized medicine. We discuss ways in which results of studies with the presented methodology might be useful for exhibition development.

Auditing the research practices and statistical analyses of the group-level temporal network approach to psychological constructs: A systematic scoping review

Network analyses have become increasingly common within the field of psychology, and temporal network analyses in particular are quickly gaining traction, with many of the initial articles earning substantial interest. However, substantial heterogeneity exists within the study designs and methodology, rendering it difficult to form a comprehensive view of its application in psychology research. Since the field is quickly growing and since there have been many study-to-study variations in terms of choices made by researchers when collecting, processing, and analyzing data, we saw the need to audit this field and formulate a comprehensive view of current temporal network analyses. To systematically chart researchers' practices when conducting temporal network analyses, we reviewed articles conducting temporal network analyses on psychological variables (published until March 2021) in the framework of a scoping review. We identified 43 articles and present the detailed results of how researchers are currently conducting temporal network analyses. A commonality across results concerns the wide variety of data collection and analytical practices, along with a lack of consistency between articles about what is reported. We use these results, along with relevant literature from the fields of ecological momentary assessment and network analysis, to formulate recommendations on what type of data is suited for temporal network analyses as well as optimal methods to preprocess and analyze data. As the field is new, we also discuss key future steps to help usher the field's progress forward and offer a reporting checklist to help researchers navigate conducting and reporting temporal network analyses.

Effects of personal relative deprivation on the relationship between anger rumination and aggression during and after the COVID-19 pandemic lockdown: A longitudinal moderated network approach

INTRODUCTION

Several studies have demonstrated a directional link between rage rumination and aggression. However, recent research suggests that this relationship is bidirectional. The current study examined the complex relationships between anger rumination and aggression using a moderated network approach in a longitudinal design while considering personal relative deprivation.

METHOD

A total of 665 participants (59.25% female, age_mean±SD  = 19.01 ± 1.25) were enrolled at two-time points. Assessments included self-report measures of the Anger Rumination Scale, Buss-Perry Aggression Questionnaire, and Relative Deprivation Scale. A Moderated Network Model (MMN) was used to test the complex links among anger rumination, aggression, and personal relative deprivation.

RESULTS

The analysis revealed that the link between anger rumination and aggression was complex and bidirectional. Notably, as the level of personal relative deprivation increased, verbal aggression had a positive conditional effect on anger afterthoughts in Wave 2, and thoughts of revenge had a positive conditional effect on verbal aggression in Wave 2. Moreover, as the first discovery, anger afterthoughts and anger had a negative conditional effect on each other across levels of personal relative deprivation in Wave 2. In addition, network comparison indicates that the MNMs structure was significantly different across timepoints, implying that anger rumination and aggression were inextricably linked in college students during isolation and that this complicated relationship was weakened after isolation.

CONCLUSIONS

This study deepens our understanding of the bidirectional relationships between anger rumination and aggression and recognizes the moderating role of personal relative deprivation.

How compliance with behavioural measures during the initial phase of a pandemic develops over time: A longitudinal COVID-19 study

In this longitudinal research, we adopt a complexity approach to examine the temporal dynamics of variables related to compliance with behavioural measures during the COVID-19 pandemic. Dutch participants (N = 2399) completed surveys with COVID-19-related variables five times over a period of 10 weeks (23 April-30 June 2020). With these data, we estimated within-person COVID-19 attitude networks containing a broad set of psychological variables and their relations. These networks display variables' predictive effects over time between measurements and contemporaneous effects during measurements. Results show (1) bidirectional effects between multiple variables relevant for compliance, forming potential feedback loops, and (2) a positive reinforcing structure between compliance, support for behavioural measures, involvement in the pandemic and vaccination intention. These results can explain why levels of these variables decreased throughout the course of the study. The reinforcing structure points towards potentially amplifying effects of interventions on these variables and might inform processes of polarization. We conclude that adopting a complexity approach might contribute to understanding protective behaviour in the initial phase of pandemics by combining different theoretical models and modelling bidirectional effects between variables. Future research could build upon this research by studying causality with interventions and including additional variables in the networks.

ConNEcT: An R package to build contingency measure-based networks on binary time series

Dynamic networks are valuable tools to depict and investigate the concurrent and temporal interdependencies of various variables across time. Although several software packages for computing and drawing dynamic networks have been developed, software that allows investigating the pairwise associations between a set of binary intensive longitudinal variables is still missing. To fill this gap, this paper introduces an R package that yields contingency measure-based networks (ConNEcT). ConNEcT implements different contingency measures: proportion of agreement, corrected and classic Jaccard index, phi correlation coefficient, Cohen's kappa, odds ratio, and log odds ratio. Moreover, users can easily add alternative measures, if needed. Importantly, ConNEcT also allows conducting non-parametric significance tests on the obtained contingency values that correct for the inherent serial dependence in the time series, through a permutation approach or model-based simulation. In this paper, we provide an overview of all available ConNEcT features and showcase their usage. Addressing a major question that users are likely to have, we also discuss similarities and differences of the included contingency measures.

Mental health nurses' measured attitudes to people and practice: Systematic review of UK empirical research 2000-2019

WHAT IS KNOWN ON THE SUBJECT?: Many studies have investigated the attitudes of mental health nurses towards a range of targets. These targets are person-oriented (for example groups of people with a similar mental health diagnosis) or practice-oriented (for example practices such as seclusion or restraint). It is thought that attitudes contribute to the practice of mental health nurses because research suggests attitudes have a role in shaping behaviour. WHAT THE PAPER ADDS TO EXISTING KNOWLEDGE?: To date, research about mental health nurses' attitudes has examined different attitudes in isolation from one another. By demonstrating a lack of connectedness across studies this paper highlights the need for new theory-informed approaches to attitudinal research. By standardizing measurements across different studies this review demonstrates that the most negatively appraised attitudinal targets-indicated by large proportions of respondents who appraise negatively-concern people with diagnoses of borderline personality disorder, substance misuse, and acute mental health presentations. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: Significant numbers of mental health nurses may have attitudes, especially towards people with borderline personality diagnoses and those who misuse substances, that may not be concordant with good practice. There is insufficient evidence about what the actual implications this has for practice because the body of relevant research lacks coherence, interconnectedness and a grounding in contemporary theoretical developments. Training programmes that focus on attitudinal change need to be more rigorously evaluated. ABSTRACT: Introduction Attitudes are considered integral to mental health nursing practice. Aims To comprehensively describe the (i) measured attitudes of UK mental health nurses towards people and practice; (ii) effectiveness of interventions to change attitudes; and (iii) relationships between their attitudes, other variables/constructs and practice. Methods Using systematic review methodology, multiple databases (CINAHL, Scopus, PsycINFO, Web of Science Core Collection, Google Scholar) were searched. Eligible studies involved measurement of UK-based mental health nurses' attitudes with multi-item scales. Studies were quality appraised, mean (SD) attitudinal data were standardized, and other results converted to standardized effect sizes. Results N = 42 studies were included. Negatively appraised attitudinal targets were people with a borderline personality disorder diagnosis, substance misuse, and acute mental health presentations. Educational interventions were associated with immediate increases in positive appraisals but sustainability was poorly evidenced. There was very limited study of attitude-practice links. Discussion This review identifies priority attitudinal targets for action but also demonstrates that future work must consider the interconnectedness of attitudes and their relationship with practice. Implications for Practice Priority areas for consideration are attitudes to borderline personality disorder, substance misuse and mental health co-morbidity. Addressing disparities between nurses' attitudes and those of service users is important. More robust research is required into the effectiveness of interventions to change attitudes and into attitude-practice links.

Idiographic Ising and Divide and Color Models: Encompassing Networks for Heterogeneous Binary Data

The Ising model is a graphical model that has played an essential role in network psychometrics. It has been used as a theoretical model to conceptualize psychological concepts and as a statistical model to analyze psychological data. Using graphical models such as the Ising model to analyze psychological data has been heavily critiqued since these data often come from cross-sectional applications. An often voiced concern is the inability of the Ising model to express heterogeneity in the population. The idiographic approach has been posed as an alternative and aims to infer individual network structures. While idiographic networks overcome population heterogeneity, it is unclear how they aggregate into established cross-sectional phenomena. This paper establishes a formal bridge between idiographic and cross-sectional network approaches of the Ising model. We ascertain unique topological structures that characterize individuals and aggregate into an Ising model cross-sectionally. This new formulation supports population heterogeneity while being consistent with cross-sectional phenomena. The proposed theory also establishes a new statistical framework for analyzing populations of idiographic networks for binary variables. The Ising model and the divide and color model are special cases of this new framework. We introduce a Gibbs sampling algorithm to estimate models from this new framework.

Tailored interventions into broad attitude networks towards the COVID-19 pandemic

This study examines how broad attitude networks are affected by tailored interventions aimed at variables selected based on their connectiveness with other variables. We first computed a broad attitude network based on a large-scale cross-sectional COVID-19 survey (N = 6,093). Over a period of approximately 10 weeks, participants were invited five times to complete this survey, with the third and fifth wave including interventions aimed at manipulating specific variables in the broad COVID-19 attitude network. Results suggest that targeted interventions that yield relatively strong effects on variables central to a broad attitude network have downstream effects on connected variables, which can be partially explained by the variables the interventions were aimed at. We conclude that broad attitude network structures can reveal important relations between variables that can help to design new interventions.

Psychological network analysis of the relations between beliefs about smoking for smokers with and without a recent quit attempt

OBJECTIVE

Psychological network analysis was used to evaluate the relations between beliefs about cigarette smoking in current smokers with and without a recent quit attempt and determine if these networks differed in global strength (how strongly beliefs are related) or global structure (which beliefs are related).

DESIGN

Using two publicly available datasets, the California Smokers' Cohort (CSC; N = 933) and Wave 1 of the Population Assessment of Tobacco and Health (PATH; N = 7855), we evaluated differences in global strength and global structure of the beliefs held by current smokers with and without a recent quit attempt.

MAIN OUTCOME MEASURES

Strength and structure of networks generated for current smokers with and without a recent quit attempt.

RESULTS

In the CSC dataset there were differences between smokers with and without a recent quit attempt in global structure and marginal differences in global strength; the PATH dataset suggested small differences in global strength and structure.

CONCLUSION

The present study suggests that consideration of relations among smoking beliefs may be a valuable contribution to characterizing smoking beliefs when assessing smoking quit attempts.

Trust in scientists, risk perception, conspiratorial beliefs, and unrealistic optimism: A network approach to investigating the psychological underpinnings of COVID-19 vaccination intentions