Stability and variability of personality networks. A tutorial on recent developments in network psychometrics

The impact of antidepressant treatment on the network structure of neurocognition and core emotional depressive symptoms among depressed individuals with a history of suicide attempt: An 8-week clinical study

BACKGROUND

A more in-depth understanding of the relationship between depressive symptoms, neurocognition and suicidal behavior could provide insights into the prognosis and treatment of major depressive disorder (MDD) and suicide. We conducted a network analysis among depressed patients examining associations between history of suicide attempt (HSA), core emotional major depression disorder, and key neurocognitive domains.

METHOD

Depressed patients (n = 120) aged 18-65 years were recruited from a larger randomized clinical trial conducted at the Douglas Institute in Montreal, Canada. They were randomly assigned to receive one of two antidepressant treatments (i.e., escitalopram or desvenlafaxine) for 8 weeks. Core emotional MDD and key neurocognitive domains were assessed pre-post treatment.

RESULTS

At baseline, an association between history of suicide attempt (HSA) and phonemic verbal fluency (PVF) suggested that HSA patients reported lower levels of the latter. After 8 weeks of antidepressant treatment, HSA became conditionally independent from PVF. Similar results were found for both the HAM-D and the QIDS-SR core emotional MDD/neurocognitive networks.

CONCLUSION

Network analysis revealed a pre-treatment relationship between a HSA and decreased phonemic VF among depressed patients, which was no longer present after 8 weeks of antidepressant treatment.

Structure of resilience: A Machiavellian contribution or 'paddle your own canoe'

According to biobehavioral synchronicity model, empathy-a fundamental requirement for reciprocal and prosocial behavior-is at the core of rebound from stress, an essential feature of resilience. However, there are also reports on antagonistic traits-characterized by empathic deficit-bolstering immunity to stress. In the literature there is also inconclusive evidence regarding gender-related differences in resilience. In separate female and male subsamples we analyzed the network constellation entailing resilience (assessed as rebound from stress), empathic (cognitive empathy, affective resonance, and affective dissonance) and antagonistic personality traits (Machiavellianism, grandiose- and vulnerable narcissism). For both genders, Machiavellian agency instigated by narcissistic admiration occupied the central position in the network indicating that personality's resources for proactivity and control are essential for successful rebound. Empathy, and in particular its affective component, occupied only a peripheral position in the network. Machiavellian antagonism in men and grandiose narcissism in females bridged prosocial mechanism of resilience with antagonistic nodes of the network. In the female subsample both types of malign narcissism (rivalry and vulnerable narcissism) directly thwarted rebound. This process was not detected in the male subsample network dominated by antagonism. That is, gender-related differences were associated with the avoidance strategies rather than with the proactive strategies. Thus, resilience assessed as rebounding from stress primarily involves personality resources which modulate proactive- and prosocial- but not necessarily reciprocal behavior.

The impact of depressive and anxious symptoms on non-suicidal self-injury behavior in adolescents: a network analysis

PURPOSE

Conceptualizing adolescent NSSI and emotional symptoms as a system of causal elements could provide valuable insights into the development of non-suicidal self-injury (NSSI) in adolescent. This study aimed to explore the intricate relationship between NSSI, depressive symptoms, and anxious symptoms in adolescents, identifying key symptoms to establish a theoretical foundation for targeted and effective interventions addressing NSSI behaviors in this population.

METHODS

A total of 412 adolescents with NSSI behaviors were selected from outpatients. Generalized anxious disorder scale (GAD-7) and patient health questionnaire (PHQ-9) were employed to measure anxious symptoms and depressive symptoms, respectively. The adolescent non-suicidal self-injury assessment questionnaire (ANSSIAQ) was used to evaluate NSSI of adolescent. Using network analysis, the NSSI、depressive symptoms and anxious symptoms network were constructed to identify the most central symptoms and the bridge symptoms within the networks.

RESULTS

The findings revealed that the NSSI functional nodes "coping with sadness and disappointment" and "relieving stress or anxious" exhibited the strongest correlation, with a regularized partial correlation coefficient was 0.401. The symptoms "having a desire to harm oneself and unable to stop" and the node "depressive symptoms" had the highest strength centrality in the network, and their strength centrality indices were 1.267 and 1.263, respectively. The bridge nodes were "having a desire to harm oneself and unable to stop" and "expressing one's despair and hopelessness", with expected impact indices of 0.389 and 0.396, respectively.

CONCLUSION

In adolescents, the network revealed a closer connection between NSSI and depressive symptoms. "The desire to not stop hurting oneself" is not only broadly connected to other nodes but also could activate other nodes to maintain NSSI behavior. In light of these findings, precise targets for pharmacological treatment, psychotherapy, physical therapy, etc., are identified for adolescents with NSSI. Targeting this specific aspect in interventions may contribute to preventing and reducing NSSI behavior in adolescents.

A network model of depressive and anxiety symptoms: a statistical evaluation

BACKGROUND

Although network analysis studies of psychiatric syndromes have increased in recent years, most have emphasized centrality symptoms and robust edges. Broadening the focus to include bridge symptoms within a systematic review could help to elucidate symptoms having the strongest links in network models of psychiatric syndromes. We conducted this systematic review and statistical evaluation of network analyses on depressive and anxiety symptoms to identify the most central symptoms and bridge symptoms, as well as the most robust edge indices of networks.

METHODS

A systematic literature search was performed in PubMed, PsycINFO, Web of Science, and EMBASE databases from their inception to May 25, 2022. To determine the most influential symptoms and connections, we analyzed centrality and bridge centrality rankings and aggregated the most robust symptom connections into a summary network. After determining the most central symptoms and bridge symptoms across network models, heterogeneity across studies was examined using linear logistic regression.

RESULTS

Thirty-three studies with 78,721 participants were included in this systematic review. Seventeen studies with 23 cross-sectional networks based on the Patient Health Questionnaire (PHQ) and Generalized Anxiety Disorder (GAD-7) assessments of clinical and community samples were examined using centrality scores. Twelve cross-sectional networks based on the PHQ and GAD-7 assessments were examined using bridge centrality scores. We found substantial variability between study samples and network features. 'Sad mood', 'Uncontrollable worry', and 'Worrying too much' were the most central symptoms, while 'Sad mood', 'Restlessness', and 'Motor disturbance' were the most frequent bridge centrality symptoms. In addition, the connection between 'Sleep' and 'Fatigue' was the most frequent edge for the depressive and anxiety symptoms network model.

CONCLUSION

Central symptoms, bridge symptoms and robust edges identified in this systematic review can be viewed as potential intervention targets. We also identified gaps in the literature and future directions for network analysis of comorbid depression and anxiety.

A Network Analysis Approach to Understanding Centrality and Overlap of 21 Dark Triad Items in Adults of 10 Countries

Background

Previous research has suggested that manipulation and callousness are central to Dark Triad traits, but it has not identified which specific manifestations are expressed across various countries.

Objective

This study aimed to identify the core and overlapping manifestations of Dark Triad traits across 10 countries.

Methods

We used the Short Dark Triad (SD3) scale and assessed a sample of 8093 participants (59.7% women, M(age) = 32.68 years). For graphical representation, the spinglass algorithm was applied to understand the cluster distribution among Machiavellianism, psychopathy, and subclinical narcissism traits. Centrality indices were used to identify the most influential items, and the clique-percolation algorithm was employed to detect shared attributes among multiple Dark Triad items.

Results

Straightforward SD3-21 items demonstrated better interpretability as aversive traits within the broader system. Items with higher centrality values were those related to short-term verbal manipulation from the psychopathy domain, clever manipulation, strategic revenge-seeking from Machiavellianism, and narcissistic motivations for connecting with significant individuals. The most predicted items were linked to planned revenge, using information against others from Machiavellianism, short-term psychopathic verbal manipulation, and narcissistic belief of specialness based on external validation. Items like short-term verbal manipulation had overlaps with both psychopathy and narcissism clusters, while clever manipulation overlapped with Machiavellianism and psychopathy.

Conclusion

This cross-cultural study highlights the central role of verbal manipulation within the Dark Triad traits, along with identifying overlapping items among traits measured using straightforward SD3 scale items. In line with our findings, future research that incorporates a wide range of cultural contexts is encouraged to establish the consistency of these findings with the SD3 Scale or alternative measures.

Depressive symptoms and loneliness among early adolescents: a psychometric network analysis approach

BACKGROUND

Previous studies demonstrate a high prevalence of depression and loneliness among adolescents. Although they often co-occur, the relationship between symptoms of depression and loneliness remains poorly understood. This study investigates: (a) the symptoms of depression that are connected to loneliness; (b) the role played by loneliness in the network of depression symptoms; and (c) whether the method used to measure loneliness (single-item direct or multi-item indirect) affects the relationship of loneliness with depressive symptoms.

METHODS

Participants were 496 Polish adolescents (50.8% girls) aged 11 to 13, who completed: (a) the 10-item Major Depressive Disorder subscale of the Revised Child Anxiety and Depression Scale; (b) the 11-item De Jong Gierveld Loneliness Scale (indirect loneliness), and (c) a single direct question evaluating loneliness: 'I'm lonely'. Networks were estimated using a Gaussian Graphical Model.

RESULTS

Loneliness shows a direct relationship with three affective symptoms of depression: sadness, worthlessness, and anhedonia, which mediate relationships with somatic symptoms. In contrast to previous studies, loneliness has the lowest level of centrality among all elements of the network. The method used to assess loneliness did not significantly affect the connections between loneliness and depressive symptoms.

CONCLUSIONS

Loneliness and depression overlap since they are formed by the same cognitive biases and deficits in emotion regulation but differ in the level of generality. In loneliness, they have an interpersonal context, while symptoms of depression can be intrapersonal. This helps us to understand why cognitive interventions, as compared to those which are social, are more effective in reducing loneliness.

Network Analysis of Comorbid Depressive and Anxious Symptoms in Family Caregivers of People with Dementia

OBJECTIVES

The aim of this study is an in-depth approach to depressive-anxious comorbidity in caregivers according to stress reactivity to disruptive behaviors using network analysis.

METHODS

The sample was composed of 317 primary family caregivers recruited through Day Care Centers and Neurology Services. The sample was split into low and high stress reactivity groups, based on their reports of reaction to disruptive behaviors. Depressive and anxious symptoms, daily hours dedicated to caregiving, time of caring, frequency of disruptive behaviors, co-residence, and kinship were also cross-sectionally measured.

RESULTS

The sample had a mean age of 62.38 years (SD = 12.97) and 68.5% were women. Regarding the network analysis, while the low reactivity group presents a sparse network, with no connection between anxious and depressive symptoms, the high reactivity group shows a high connection of intra and intercategory symptoms, with apathy, sadness, feeling depressed, and tension being the bridge symptoms between disorders.

CONCLUSIONS

Caregivers' stress reaction to disruptive behaviors might be a key factor for understanding comorbidity between depressive and anxious symptoms.

CLINICAL IMPLICATIONS

Tension, apathy, sadness, and feeling depressed should be clinical targets in the interventions, as they act as bridge symptoms between anxious and depressive symptomatology.

Fantasy Made Flesh - A Network Analysis of the Reciprocal Relationship between Sexual Fantasies, Pornography Usage, and Sexual Behavior

Based on different theories in media research (3AM, catalyst model of violent crime, reinforcing spirals model), we further explore the relationship between pornography use, sexual fantasy, and behavior. We suggest that pornography use appears so persistent across time and culture because it is related to a human universal, the ability to fantasize. Consequently, pornography use seems to be an opportunity to acquire media-mediated sexual fantasies, and we believe that pornography use interacts with sexual fantasies and, to a much weaker extent, with sexual behavior. To assess our assumptions, we conducted a network analysis with a large and diverse sample of N = 1338 hetero- and bisexual participants from Germany. Analyses were done separately for men and women. Our network analysis clustered parts of the psychological processes around the interaction of sexual fantasies, pornography use, and behavior into communities of especially strong interacting items. We detected meaningful communities (orgasm-centered intercourse, BDSM) consisting of sexual fantasies and behavior, with some containing pornography. However, pornography use was not part of communities we perceive to account for mainstream/everyday sexuality. Instead, our results show that non-mainstream behavior (e.g., BDSM) is affected by pornography use. Our study highlights the interaction between sexual fantasies, sexual behavior, and (parts of) pornography use. It advocates for a more interactionist view of human sexuality and media use.

Daily Functioning of Veterans With Type 2 Diabetes: Protocol for an Ambulatory Assessment Study

BACKGROUND

Diabetes impacts nearly 25% of veterans. Many veterans do not engage in recommended physical activity and other diabetes self-management behaviors. Type 2 diabetes is generally asymptomatic; as such, the long-term consequences of inadequate self-management and benefits of consistent self-management are not salient in the short term. Furthermore, self-management behaviors typically take place outside of medical visits; however, self-management-related factors are only assessed during medical visits, likely missing large amounts of variability. Thus, ambulatory assessment methods such as ecological momentary assessment (EMA), accelerometry, and continuous glucose monitoring are needed to understand the dynamics of daily self-management and identify potential intervention targets.

OBJECTIVE

The overarching goal of this study is to understand daily, time-varying factors (comorbid affective symptoms and social context) that influence physical activity, diabetes self-management, glycemic management, daily functioning, and quality of life in participants' natural environments.

METHODS

We are recruiting veterans with type 2 diabetes (target N=100). Participants are required to complete a battery of baseline assessments related to mental health, psychosocial factors, and self-management behaviors. Participants then receive 5 momentary EMA surveys and 1 daily EMA survey per day, in which veterans report comorbid affective symptoms (mood, stress, and pain), social support, social interactions, physical activity, and other self-management behaviors. Momentary surveys are delivered randomly during daily preprogrammed intervals over a 14-day sampling period. Accelerometry and continuous glucose monitoring are also used to assess physical activity and blood glucose, respectively. The first 6 participants also completed interviews assessing their experience in the study and barriers to participation. These test participants informed modifications to the protocol for the remaining participants.

RESULTS

The project received funding in April of 2023. Enrollment began in March of 2023 and is planned to be completed in April 2025. Among the 6 test participants, the overall EMA response rate was 87% (range 74%-95%). The response rate for the EMA survey including daily items (67%, range 21%-93%) was lower than the earlier shorter EMA surveys (89%, range 81%-96%). The mean rate of valid accelerometer wear of at least 20 hours per day was 93% (SD 11%), and continuous glucose monitoring data were available for 91% (SD 17%) of days on average. Participants reported few barriers to completing EMA surveys but noted the random timing of questions made it difficult to plan around, and the end-of-day survey was long. Two participants reported survey items reminded or motivated them to engage in diabetes self-management behaviors.

CONCLUSIONS

Assessment tools developed from this study can inform clinical decision-making by considering barriers to self-management that occur in daily life. Clinical applications include tailored, adaptive technology-supported interventions to improve self-management that provide the right type and amount of support at the right time by adapting to an individual's changing internal and contextual state.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/53874.

Network Analysis of Sexual Sensation Seeking, Internalized Homophobia, and Social Norms Among Men Who Have Sex with Men with Different Sexual Partner Types

Men who have sex with men (MSM) are at disproportionate risk for developing sexually transmitted infections (STIs) such as HIV. Understanding the relationships among factors related to risky sexual behaviors, such as internalized homophobia, sexual sensation seeking, and individual and community norms, among MSM with different sexual partner types may contribute to designing targeted interventions for reducing risky sexual behaviors and STI transmission. We conducted a cross-sectional study recruiting 781 MSM in Sichuan Province, China. All participants were divided into groups with and without sexual partners, groups with regular and casual sexual partners, and groups with only male and both male and female partners in the past 6 months. Network analysis was used to analyze the relationships among dimensions of self-reported sexual sensation seeking, internalized homophobia, and social norms in different groups. Of 781 MSM, 606 (77.6%) had sexual partners in the past 6 months, and among these participants, 429 (70.8%) had casual sexual partners, and 103 (17.0%) had both male and female sexual partners. The complex and intensive relationships between dimensions were mainly observed in networks of MSM with any type of sexual partners, with individual norms (dimension of social norms) presenting strongly negative relationships with fresh feeling (dimension of sexual sensation seeking) and homosexuality morality (dimension of internalized homophobia). One dimension of sexual sensation seeking (i.e., fresh feeling) and two dimensions of internalized homophobia (i.e., homosexuality morality and self-identification) were relatively central variables in most groups, especially for those with casual sexual partners. Our study highlights the role of individual norms in restraining sensation seeking, internalized homophobia, especially among MSM with sexual partners. Intervention targeting these central variables may contribute to reduced risky sexual behaviors and further slow the spread of STIs in MSM.

Comparison of wellbeing structures based on survey responses and social media language: A network analysis

Wellbeing is predominantly measured through surveys but is increasingly measured by analysing individuals' language on social media platforms using social media text mining (SMTM). To investigate whether the structure of wellbeing is similar across both data collection methods, we compared networks derived from survey items and social media language features collected from the same participants. The dataset was split into an independent exploration (n = 1169) and a final subset (n = 1000). After estimating exploration networks, redundant survey items and language topics were eliminated. Final networks were then estimated using exploratory graph analysis (EGA). The networks of survey items and those from language topics were similar, both consisting of five wellbeing dimensions. The dimensions in the survey- and SMTM-based assessment of wellbeing showed convergent structures congruent with theories of wellbeing. Specific dimensions found in each network reflected the unique aspects of each type of data (survey and social media language). Networks derived from both language features and survey items show similar structures. Survey and SMTM methods may provide complementary methods to understand differences in human wellbeing.

Sex differences in depression, anxiety and health-promoting lifestyles among community residents: A network approach

BACKGROUND

Researchers have studied sex differences in typical depressive and anxiety symptoms and their cooccurrence. The World Health Organization (WHO) proposed a mental health promotion objective that suggests considering protective health-promoting factors when developing strategies for preventing mental disorders between sexes. From a network perspective, psychopathology is viewed as a result of interacting symptoms and influential factors. This study adopted network approach to investigate sex differences in health-promoting lifestyles (HPL) and the cooccurrence symptoms of communities in Shanghai. The aim is to provide health-promoting suggestions on better enhancing the life quality for community members.

METHODS

Depression, anxiety symptoms, and HPL were assessed with PHQ-9, GAD-7 and HPLP-II scales in 2420 adults (1411 females). Networks were constructed by Gaussian Graphical Models and the networks of two sexes using the Network Comparison Test.

RESULTS

Females scored significantly higher on PHQ-9 (p < 0.001) and GAD-7 (p < 0.001), and no differences were found between the two sexes in HPL scores. Restlessness and low energy yielded the highest strength centrality in the female network, while suicide ideation and restlessness were central in male network. Regarding protective HPL, physical activity and stress management were identified as the central mental health-promoting behaviours in female and male network, respectively. However, stress management was positively related to suicide ideation in the male network.

CONCLUSION

Communities should be aware of suicide ideation in males because of its high relationships with other symptoms and also provide stress management courses, especially for males. As for women, chronic energy deficiency deserves more attention for its high probability of cooccurrence with other symptoms in the network. Also, advocating physical activities may be particularly beneficial for the overall mental health among women. Future study should collect time-series data and analyze intraindividual networks to specify personalized health promoting strategies for each individual.

The general psychopathology factor (p) from adolescence to adulthood: Exploring the developmental trajectories of p using a multi-method approach

Considerable attention has been directed towards studying co-occurring psychopathology through the lens of a general factor (p-factor). However, the developmental trajectory and stability of the p-factor have yet to be fully understood. The present study examined the explanatory power of dynamic mutualism theory - an alternative framework that suggests the p-factor is a product of lower-level symptom interactions that strengthen throughout development. Data were drawn from a population-based sample of girls (N = 2450) who reported on the severity of internalizing and externalizing problems each year from age 14 to age 21. Predictions of dynamic mutualism were tested using three distinct complementary statistical approaches including: longitudinal bifactor models, random-intercept cross-lagged panel models (RI-CLPMs), and network models. Across methods, study results document preliminary support for mutualistic processes in the development of co-occurring psychopathology (that is captured in p). Findings emphasize the importance of exploring alternative frameworks and methods for better understanding the p-factor and its development.

Network analysis of physical activity and depressive and affective symptoms during COVID-19 home confinement

INTRODUCTION

The aim of this study was to analyze the network structure of physical activity, frequency, depressive, and affective symptoms in people under home isolation due to COVID-19.

METHOD

A longitudinal study was conducted in two phases (beginning (March 19, 2020) and end of home confinement (April 8, 2020)). The sample consisted of 579 participants from Spain (250 men and 329 women) aged 16 to 92 years (overall sample: M = 47.06, SD = 14.52). A network analysis was performed.

RESULTS

Four clusters emerged (PA, depressive symptoms, positive affect, and negative affect). A higher frequency of physical activity was related to better-sustained attention, increased alertness, and enthusiasm. In addition, feelings of guilt and shame were mitigated, and confinement distress and irritability were reduced. Physical activity also mitigated fatigue in women, whereas feelings of unhappiness were reduced in men.

CONCLUSION

Physical activity seems to be an effective option for mitigating the negative effects of the COVID-19 pandemic. Public health policymakers should develop programs to promote physical activity in order to be able to cope with confinement or similar scenarios in the future.

A Network Analysis Approach on the Psychological Flexibility/Inflexibility Model

Acceptance and Commitment Therapy (ACT) is purported to work via targeting six interrelated processes summarized as the Psychological Inflexibility/Psychological Flexibility (PI/PF) model. However, the theoretical structure and interconnections of this model have not been sufficiently explored. Lacking are examinations of the interrelations among its components. Network Analysis (NA) can model PI/PF as a system of interconnected variables. We aimed at exploring the role and associations of the PI/PF model's components using NA in two different samples and sets of scales, and compare its structure across sub-samples. Sample 1 consisted of 501 individuals, who completed an online battery of questionnaires including the Multidimensional Psychological Flexibility Inventory, and Sample 2 consisted of 428 people, who completed an online set of six ACT measures, each assessing a component of the PI/PF model. NA could not verify the six ACT dimensions as distinct components. Values and Committed Action components were found to be strongly associated and combined in a group in both sets of measures and samples. Interestingly, Acceptance and Defusion were not the most central components as purported in some ACT conceptualizations, whereas Self-as-Context had a key role on both sets of measures and its items were often merged with Present Moment Awareness items. No significant differences were found in the comparison of networks across different subsamples and sets of scales. After combining different sets of scales, the six ACT components could not be completely verified as distinct entities, which might reflect problems with the theoretical model, or with the scales used. All components had critical roles in the model, particularly Self-as-Context, which reflects the need to redirect research towards this understudied construct. Findings point towards considerations of a triflex instead of a hexaflex ACT model.

Bootstrap Exploratory Graph Analysis of the WISC-V with a Clinical Sample

One important aspect of construct validity is structural validity. Structural validity refers to the degree to which scores of a psychological test are a reflection of the dimensionality of the construct being measured. A factor analysis, which assumes that unobserved latent variables are responsible for the covariation among observed test scores, has traditionally been employed to provide structural validity evidence. Factor analytic studies have variously suggested either four or five dimensions for the WISC-V and it is unlikely that any new factor analytic study will resolve this dimensional dilemma. Unlike a factor analysis, an exploratory graph analysis (EGA) does not assume a common latent cause of covariances between test scores. Rather, an EGA identifies dimensions by locating strongly connected sets of scores that form coherent sub-networks within the overall network. Accordingly, the present study employed a bootstrap EGA technique to investigate the structure of the 10 WISC-V primary subtests using a large clinical sample (N = 7149) with a mean age of 10.7 years and a standard deviation of 2.8 years. The resulting structure was composed of four sub-networks that paralleled the first-order factor structure reported in many studies where the fluid reasoning and visual-spatial dimensions merged into a single dimension. These results suggest that discrepant construct and scoring structures exist for the WISC-V that potentially raise serious concerns about the test interpretations of psychologists who employ the test structure preferred by the publisher.

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.

Measurement Invariance of the Pathological Narcissism Inventory and Multimethod Examination of Narcissistic Presentations in Community and Clinical Samples

The Pathological Narcissism Inventory (PNI) is extensively used in recent empirical literature on pathological narcissism. However, most studies using the PNI are community-based, and no studies have used the PNI to investigate narcissistic presentations in personality disordered patients. This study investigates measurement invariance of the PNI in community participants and patients with personality disorders, and examines differences of narcissistic presentations in these samples through a multimethod approach. Results show that the PNI can be used reliably to measure and compare traits of pathological narcissism in community participants and patients with personality disorders. Personality disordered patients show higher traits reflecting vulnerable narcissism and overt manifestations of grandiose narcissism, compared with controls. Finally, network analysis indicates that traits of grandiose fantasies and entitlement rage have a central role in defining manifestations of PNI pathological narcissism, regardless of the presence of an underlying personality disorder. Research and clinical implications are discussed.

The role of anxiety and depression in suicidal thoughts for autistic and non-autistic people: A theory-driven network analysis

BACKGROUND

Autistic adults experience more frequent suicidal thoughts and mental health difficulties than non-autistic adults, but research has yet to explain how these experiences are connected. This study explored how anxiety and depression contribute to suicidal thoughts according to the Interpersonal Theory of Suicide for autistic and non-autistic adults.

METHODS

Participants (autistic adults n = 463, 61% female; non-autistic n = 342, 64% female) completed online measures of anxiety, depression, thwarted belonging, and perceived burdensomeness. Network analysis explored whether: (i) being autistic is a risk marker for suicide; and (ii) pathways to suicidal thoughts are consistent for autistic and non-autistic adults.

RESULTS

Being autistic connected closely with feeling like an outsider, anxiety, and movement, which connected to suicidal thoughts through somatic experiences, low mood, and burdensomeness. Networks were largely consistent for autistic and non-autistic people, but connections from mood symptoms to somatic and thwarted belonging experiences were absent for autistic adults.

CONCLUSION

Autistic people experience more life stressors than non-autistic people leading to reduced coping, low mood, and suicidal thoughts. Promoting belonging, reducing anxiety, and understanding the role of movement could inform suicide prevention for autistic people. Research should accurately capture autistic lived experience when modeling suicide to ensure suicide prevention meets autistic needs.

Cognitive Symptoms Link Anxiety and Depression Within a Validation of the German State-Trait Inventory for Cognitive and Somatic Anxiety (STICSA)

Background

In the present study we aimed to develop a German version of the State-Trait Inventory for Cognitive and Somatic Anxiety (STICSA) and evaluate the psychometric properties. Associations of cognitive and somatic anxiety with other measures of anxiety, depression, and stress, elucidating possible underlying functional connections, were also examined, as symptoms of anxiety, depression and stress often overlap.

Method

Two samples (n1 = 301; n2 = 303) were collected online and in the lab, respectively. Dynamic connections between somatic and cognitive anxiety, other measures of anxiety, depression, and stress, were analyzed using a network approach. Psychometric analyses were conducted using exploratory and confirmatory factor analyses.

Results

We replicated and validated the two-factorial structure of the STICSA with the German translation. Network analyses revealed cognitive trait anxiety as the most central node, bridging anxiety and depression. Somatic trait anxiety exhibited the highest discriminant validity for distinguishing anxiety from depression.

Conclusion

The central role of cognitive symptoms in these dynamic interactions suggests an overlap of these symptoms between anxiety and depression and that differential diagnostics should focus more on anxious somatic symptoms than on cognitive symptoms. The STICSA could therefore be useful in delineating differences between anxiety and depression and for differential assessment of mood and anxiety symptoms. Additional understanding of both cognitive and somatic aspects of anxiety might prove useful for therapeutic interventions.

Longitudinal PTSD network structure: measuring PTSD symptom networks over 5 years

BACKGROUND

Network modeling has been applied in a range of trauma-exposed samples, yet results are limited by an over reliance on cross-sectional data. The current analyses used posttraumatic stress disorder (PTSD) symptom data collected over a 5-year period to estimate a more robust between-subject network and an associated symptom change network.

METHODS

A PTSD symptom network is measured in a sample of military veterans across four time points (Ns = 1254, 1231, 1106, 925). The repeated measures permit isolating between-subject associations by limiting the effects of within-subject variability. The result is a highly reliable PTSD symptom network. A symptom slope network depicting covariation of symptom change over time is also estimated.

RESULTS

Negative trauma-related emotions had particularly strong associations with the network. Trauma-related amnesia, sleep disturbance, and self-destructive behavior had weaker overall associations with other PTSD symptoms.

CONCLUSIONS

PTSD's network structure appears stable over time. There is no single 'most important' node or node cluster. The relevance of self-destructive behavior, sleep disturbance, and trauma-related amnesia to the PTSD construct may deserve additional consideration.

Borderline personality disorder symptom networks across adolescent and adult clinical samples: examining symptom centrality and replicability

BACKGROUND

Numerous theories posit different core features to borderline personality disorder (BPD). Recent advances in network analysis provide a method of examining the relative centrality of BPD symptoms, as well as examine the replicability of findings across samples. Additionally, despite the increase in research supporting the validity of BPD in adolescents, clinicians are reluctant to diagnose BPD in adolescents. Establishing the replicability of the syndrome across adolescents and adults informs clinical practice and research. This study examined the stability of BPD symptom networks and centrality of symptoms across samples varying in age and clinical characteristics.

METHODS

Cross-sectional analyses of BPD symptoms from semi-structured diagnostic interviews from the Collaborative Longitudinal Study of Personality Disorders (CLPS), the Methods to Improve Diagnostic Assessment and Service (MIDAS) study, and an adolescent clinical sample. Network attributes, including edge (partial association) strength and node (symptom) expected influence, were compared.

RESULTS

The three networks were largely similar and strongly correlated. Affective instability and identity disturbance emerged as relatively central symptoms across the three samples, and relationship difficulties across adult networks. Differences in network attributes were more evident between networks varying both in age and in BPD symptom severity level.

CONCLUSIONS

Findings highlight the relative importance of affective, identity, and relationship symptoms, consistent with several leading theories of BPD. The network structure of BPD symptoms appears generally replicable across multiple large samples including adolescents and adults, providing further support for the validity of the diagnosis across these developmental phases.

An exploration of gender and prolonged grief symptoms using network analysis

BACKGROUND

Gender has been proposed as a potentially important predictor of bereavement outcomes. The majority of research in the field has explored this issue by examining gender differences in global grief severity. Findings have been mixed. In this study, we explore potential gender differences in grief using network analysis. This approach examines how individual symptoms relate to and reinforce each other, and so offers potential to shed light on novel aspects of grief expression across genders.

METHOD

Graphical lasso networks were constructed using self-report data from 839 spousally bereaved older participants (584 female, 255 male) collected at 2- and 11- months post-bereavement. Edge strength, node strength and global network strength were compared to identify similarities and differences between gender networks across time.

RESULTS

At both time points, the strongest connection for both genders was from yearning to pangs of grief. Yearning, pangs of grief, acceptance, bitterness and shock were prominent nodes at time 1. Numbness and meaninglessness emerged as prominent nodes at time 2. Males and females differed in the relative importance of shock at time 1, and the female network had greater overall strength than the male network at time 2.

CONCLUSIONS

This study identified many similarities and few differences in the relationships between prolonged grief symptoms for males and females. Findings suggest that future studies should examine alternate sources of variation in grief outcomes. Limitations are discussed.

A Smartphone Intervention to Promote a Sustainable Healthy Diet: Protocol for a Pilot Study

BACKGROUND

Changing current dietary patterns into sustainable healthy diets (ie, healthy diets with low environmental impact and socioeconomic fairness) is urgent. So far, few eating behavior change interventions have addressed all the dimensions of sustainable healthy diets at once and used cutting-edge methods from the field of digital health behavior change.

OBJECTIVE

The primary objectives of this pilot study were to assess the feasibility and effectiveness of an individual behavior change intervention toward the adoption of a more environmentally sustainable healthy diet as a whole and changes in specific relevant food groups, food waste, and obtaining food from fair sources. The secondary objectives included the identification of mechanisms of action that potentially mediate the effect of the intervention on behaviors, identification of potential spillover effects and covariations among different food outcomes, and identification of the role of socioeconomic status in behavior changes.

METHODS

We will run a series of ABA n-of-1 trials over a year, with the first A phase corresponding to a 2-week baseline evaluation, the B phase to a 22-week intervention, and the second A phase to a 24-week postintervention follow-up. We plan to enroll 21 participants from low, middle, and high socioeconomic statuses, with 7 from each socioeconomic group. The intervention will involve sending text messages and providing brief individualized web-based feedback sessions based on regular app-based assessments of eating behavior. The text messages will contain brief educational messages on human health and the environmental and socioeconomic effects of dietary choices; motivational messages to encourage the adoption of sustainable healthy diets by participants, providing tips to achieve their own behavioral goals; or links to recipes. Both quantitative and qualitative data will be collected. Quantitative data (eg, on eating behaviors and motivation) will be collected through self-reported questionnaires on several weekly bursts spread through the study. Qualitative data will be collected through 3 individual semistructured interviews before the intervention period, at the end of the intervention period, and at the end of the study. Analyses will be performed at both the individual and group levels depending on the outcome and objective.

RESULTS

The first participants were recruited in October 2022. The final results are expected by October 2023.

CONCLUSIONS

The results of this pilot study will be useful for designing future larger interventions on individual behavior change for sustainable healthy diets.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/41443.

Network-based validation of the psychometric questionnaire EDI-3 for the assessment of eating disorders

Assessing the validity of a psychometric test is fundamental to ensure a reliable interpretation of its outcomes. Few attempts have been made recently to complement classical approaches (e.g., factor models) with a novel technique based on network analysis. The objective of the current study is to carry out a network-based validation of the Eating Disorder Inventory 3 (EDI-3), a questionnaire designed for the assessment of eating disorders. Exploiting a reliable, open source sample of 1206 patients diagnosed with an eating disorder, we set up a robust validation process encompassing detection and handling of redundant EDI-3 items, estimation of the cross-sample psychometric network, resampling bootstrap procedure and computation of the median network of the replica samples. We then employed a community detection algorithm to identify the topological clusters, evaluated their coherence with the EDI-3 subscales and replicated the full validation analysis on the subpopulations corresponding to patients diagnosed with either anorexia nervosa or bulimia nervosa. Results of the network-based analysis, and particularly the topological community structures, provided support for almost all the composite scores of the EDI-3 and for 2 single subscales: Bulimia and Maturity Fear. A moderate instability of some dimensions led to the identification of a few multidimensional items that should be better located in the intersection of multiple psychological scales. We also found that, besides symptoms typically attributed to eating disorders, such as drive for thinness, also non-specific symptoms like low self-esteem and interoceptive deficits play a central role in both the cross-sample and the diagnosis-specific networks. Our work adds insights into the complex and multidimensional structure of EDI-3 by providing support to its network-based validity on both mixed and diagnosis-specific samples. Moreover, we replicated previous results that reinforce the transdiagnostic theory of eating disorders.

A general motivational architecture for human and animal personality

To achieve integration in the study of personality, researchers need to model the motivational processes that give rise to stable individual differences in behavior, cognition, and emotion. The missing link in current approaches is a motivational architecture-a description of the core set of mechanisms that underlie motivation, plus a functional account of their operating logic and inter-relations. This paper presents the initial version of such an architecture, the General Architecture of Motivation (GAM). The GAM offers a common language for individual differences in humans and other animals, and a conceptual toolkit for building species-specific models of personality. The paper describes the main components of the GAM and their interplay, and examines the contribution of these components to the emergence of individual differences. The final section discusses how the GAM can be used to construct explicit functional models of personality, and presents a roadmap for future research.

Predicting prognosis for adults with depression using individual symptom data: a comparison of modelling approaches

BACKGROUND

This study aimed to develop, validate and compare the performance of models predicting post-treatment outcomes for depressed adults based on pre-treatment data.

METHODS

Individual patient data from all six eligible randomised controlled trials were used to develop (k = 3, n = 1722) and test (k = 3, n = 918) nine models. Predictors included depressive and anxiety symptoms, social support, life events and alcohol use. Weighted sum scores were developed using coefficient weights derived from network centrality statistics (models 1-3) and factor loadings from a confirmatory factor analysis (model 4). Unweighted sum score models were tested using elastic net regularised (ENR) and ordinary least squares (OLS) regression (models 5 and 6). Individual items were then included in ENR and OLS (models 7 and 8). All models were compared to one another and to a null model (mean post-baseline Beck Depression Inventory Second Edition (BDI-II) score in the training data: model 9). Primary outcome: BDI-II scores at 3-4 months.

RESULTS

Models 1-7 all outperformed the null model and model 8. Model performance was very similar across models 1-6, meaning that differential weights applied to the baseline sum scores had little impact.

CONCLUSIONS

Any of the modelling techniques (models 1-7) could be used to inform prognostic predictions for depressed adults with differences in the proportions of patients reaching remission based on the predicted severity of depressive symptoms post-treatment. However, the majority of variance in prognosis remained unexplained. It may be necessary to include a broader range of biopsychosocial variables to better adjudicate between competing models, and to derive models with greater clinical utility for treatment-seeking adults with depression.

The Dynamic Interplay of Anxious and Depressive Symptoms in a Sample of Undergraduate Students

The network perspective on psychopathology suggests that mental disorders can be regarded as networks of elements that influence each other. In this study, we used network analysis to explore the temporal interactions of anxiety and depression symptoms at the level of day-to-day experiences and find potential explanatory pathways for their comorbidity. We collected intensive longitudinal data from a sample of undergraduate students and fitted a Multilevel Vector Autoregressive model on GAD and MDD DSM-5 symptoms. “Sad mood” and “Concentration difficulties” were responsible for the most connections between anxiety and depression symptoms and were also among the most central symptoms. It is possible that anxio-depressive comorbidity can be explained by the presence of “Sad mood” and “Concentration difficulties” and targeting these two symptoms in therapy can lead to beneficial effects in comorbid cases.

Analysis of dynamic psychological processes to understand and promote physical activity behaviour using intensive longitudinal methods: a primer

Physical activity behaviour displays temporal variability, and is influenced by a range of dynamic psychological processes (e.g., affect) and shaped by various co-occurring events (e.g., social/environmental factors, interpersonal dynamics). Yet, most physical activity research tends not to examine the dynamic psychological processes implicated in adopting and maintaining physical activity. Intensive longitudinal methods (ILM) represent one particularly salient means of studying the complex psychological dynamics that underlie and result from physical activity behaviour. With the increased recent interest in using intensive longitudinal data to understand specific dynamic psychological processes, the field of exercise and health psychology is well-positioned to draw from state-of-the-art measurement and statistical approaches that have been developed and operationalised in other fields of enquiry. The purpose of this review is to provide an overview of some of the fundamental dynamic measurement and modelling approaches applicable to the study of physical activity behaviour change, as well as the dynamic psychological processes that contribute to such change.

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.

Enneagram typologies and healthy personality to psychosocial stress: A network approach

Introduction

Enneagram typologies may impact psychological well-being and stressful situations in college students. However, the literature is still limited in the study of dynamic personality models such as the Enneagram in Spanish-speaking university students, and a better understanding is needed.

Objective

To analyze network associations and centrality measures of Enneagram personality typologies in Peruvian university students.

Methods

A total of 859 Peruvian university students responded to two instruments assessing: The Pangrazzi's Enneagram personality types and healthy personality to psychosocial stress. All instruments showed good psychometric values (validity and consistency). A regularized cross-sectional network structure was estimated with Gaussian graphical model and the graphical LASSO.

Results

Enneagram types 4, 5, and 6 presented the highest and positive associations in the network structure. Type 6 emerged as the node with the highest predictability. The healthy personality and type 7 acted as bridges between the communities, with types 6, 7, and 8 being the most central nodes.

Conclusion

The findings suggest that Enneagram type 7 with healthy personality to psychosocial stress plays an important role in the development of the causal activation of the network model. The network shows causal associations between psychosocial stress and types 6, 7, 8, and 9.

Exploring the longitudinal clustering of lifestyle behaviors, social determinants of health, and depression

Lifestyle behaviors such as exercise, sleep, smoking, diet, and social interaction are associated with depression. This study aimed to model the complex relationships between lifestyle behaviors and depression and among the lifestyle behaviors. Data from three waves of the Midlife in the United States study were used, involving 6898 adults. Network models revealed associations between the lifestyle behaviors and depression, with smoker status being strongly associated with depression. Depression, smoker status, age, time, and exercise were some of the most central components of the networks. Future lifestyle intervention research might prioritize specific behaviors based on these associations and centrality indices.

Network-based methods for psychometric data of eating disorders: A systematic review

BACKGROUND

Network science represents a powerful and increasingly promising method for studying complex real-world problems. In the last decade, it has been applied to psychometric data in the attempt to explain psychopathologies as complex systems of causally interconnected symptoms. One category of mental disorders, relevant for their severity, incidence and multifaceted structure, is that of eating disorders (EDs), serious disturbances that negatively affect a person's eating behavior.

AIMS

We aimed to review the corpus of psychometric network analysis methods by scrutinizing a large sample of network-based studies that exploit psychometric data related to EDs. A particular focus is given to the description of the methodologies for network estimation, network description and network stability analysis providing also a review of the statistical software packages currently used to carry out each phase of the network estimation and analysis workflow. Moreover, we try to highlight aspects with potential clinical impact such as core symptoms, influences of external factors, comorbidities, and related changes in network structure and connectivity across both time and subpopulations.

METHODS

A systematic search was conducted (February 2022) on three different literature databases to identify 57 relevant research articles. The exclusion criteria comprehended studies not based on psychometric data, studies not using network analysis, studies with different aims or not focused on ED, and review articles.

RESULTS

Almost all the selected 57 papers employed the same analytical procedures implemented in a collection of R packages specifically designed for psychometric network analysis and are mostly based on cross-sectional data retrieved from structured psychometric questionnaires, with just few exemptions of panel data. Most of them used the same techniques for all phases of their analysis. In particular, a pervasive use of the Gaussian Graphical Model with LASSO regularization was registered for in network estimation step. Among the clinically relevant results, we can include the fact that all papers found strong symptom interconnections between specific and nonspecific ED symptoms, suggesting that both types should therefore be addressed by clinical treatment.

CONCLUSIONS

We here presented the largest and most comprehensive review to date about psychometric network analysis methods. Although these methods still need solid validation in the clinical setting, they have already been able to show many strengths and important results, as well as great potentials and perspectives, which have been analyzed here to provide suggestions on their use and their possible improvement.

Network analysis of the relationships between conspiracy beliefs towards COVID-19 vaccine and symptoms of fear of COVID-19 in a sample of latin american countries

The present study examined how conspiracy beliefs about COVID-19 vaccines specifically relate to symptoms of fear of COVID-19 in a sample of four South American countries. A total of 1785 people from Bolivia, Colombia, Ecuador, and Peru participated, responding to a sociodemographic survey, the Fear of COVID-19 scale (FCV-19 S) and the Vaccine Conspiracy Beliefs Scale-COVID-19 (VCBS-COVID-19). Network analysis identified the most important symptoms of fear and conspiracy beliefs about COVID-19 vaccines (nodes) and the associations between them (edges). In addition, the robustness of the network of these indicators of centrality and the possible differences in the structure and connectivity of the networks between the four countries were evaluated. The results suggest that the nodes with the highest centrality were items 2 and 5 of the FCV-19 S and item 2 of the VCBS-COVID-19. Likewise, item 6 is the belief that most predicts conspiracy beliefs about vaccines against COVID-19; while item 6 was the symptom that most predicts fear of COVID-19. The findings strongly support cross-cultural similarities in the networks across the four countries rather than differences. Although it was expected that a higher presence of symptoms of fear of COVID-19 may lead people to compensate for their fear by believing in conspiratorial ideas about vaccines and, consequently, rejecting the COVID-19 vaccine, the results do not clearly show this relationship. This could lead other researchers to generate evidence to explain the differences between Latin American countries and countries in other contexts in terms of vaccination rates. This evidence could be useful to develop policies favoring vaccination against COVID-19 that are more contextualized to the Latin American region, characterized by social instability and economic recession during the pandemic.

Network and Exploratory Factorial Analysis of the Depression Clinical Evaluation Test

Depression is a highly prevalent disorder with a wide range of symptomatology. Existing instruments for its assessment have only a few items for each factor. The Depression Clinical Evaluation Test (DCET) has been created to cover all depression symptoms at different times (month, year, and always) with several items for each facet. The content validity of this instrument has been judged by experts and, in this paper, we analyse its factorial structure and make a network analysis of it. The test (196 items) was administered to 602 adults without psychological disorders (M_age = 24.7, SD = 8.38, 72% women) both online and on paper. A network was estimated for each time point, using the absolute minimum selection and shrinkage operator. From the factor analysis, 12 factors were established for month, 11 for year, and 10 for always, leaving 94 items. The network analysis showed that the facets of depressive mood, anhedonia, and thoughts of Death, are central to all the estimated networks. The DCET is proposed as a valid and reliable multifactorial instrument to detect the variability of depressive symptoms in adults, guaranteeing its diagnostic usefulness.

This is the way: Network perspective on targets for spatial ability development programmes

BACKGROUND

Spatial ability (SA) was shown to be important for success in different fields, including STEM. Recent research suggested that SA is a unitary construct, rather than a set of related skills. However, it is not clear how individual differences in different facets of SA emerge, and how they relate to variance in general cognitive ability.

AIMS

The aim of the present study was threefold: 1) to examine the structure of SA testing nine theoretical models; 2) to explore the relation between 16 different facets of SA with general cognitive ability; and 3) to identify central facet(s) within the network of SA - with most links and/or strongest links to other facets.

SAMPLE

The study participants were 958 university students from Russia.

METHODS

The study used a comprehensive battery of 16 SA tests and a verbal ability measure.

RESULTS

Results supported previous research, suggesting moderate overlap between all SA facets. Factor analysis suggested several potential structures, with similar fit indices for five different theoretically driven models, including split into small- and large scale; partially independent manipulation, visualization and navigation facets. Confirmatory factor analysis, mediation and network analyses showed spatial ability being largely independent from verbal ability. In addition, network analysis showed that navigation according to directions is in the centre of the network, potentially linking all SA facets.

CONCLUSION

The results have potential implications for identifying the best targets for SA interventions. The next step in research is conducting experimental studies to evaluate effectiveness of interventions targeting navigation in comparison with other facets of SA.

Taking Stock and Moving Forward: A Personalized Perspective on Mixed Emotions

Research on mixed emotions is flourishing but fractured. Several psychological subfields are working in parallel and separately from other disciplines also studying mixed emotions, which has led to a disorganized literature. In this article, we provide an overview of the literature on mixed emotions and discuss factors contributing to the lack of integration within and between fields. We present an organizing framework for the literature of mixed emotions on the basis of two distinct goals: solving the bipolar-bivariate debate and understanding the subjective experience of mixed emotions. We also present a personalized perspective that can be used when studying the subjective experience of mixed emotions. We emphasize the importance of assessing both state and trait emotions (e.g., momentary emotions, general levels of affect) alongside state and trait context (e.g., physical location, culture). We discuss three methodological approaches that we believe will be valuable in building a new mixed-emotions literature-inductive research methods, idiographic models of emotional experiences, and empirical assessment of emotion-eliciting contexts. We include recommendations throughout on applying these methods to research on mixed emotions, and we conclude with avenues for future interdisciplinary research. We hope that this perspective will foster research that results in the organized accumulation of knowledge about mixed emotions.

Coexisting service-related factors preceding suicide: a network analysis

OBJECTIVES

The overall objective was to analyse service-related factors involved in the complex processes that precede suicide in order to identify potential targets for intervention.

DESIGN AND SETTING

Explorative network analysis study of post-suicide root cause analysis data from Swedish primary and secondary healthcare.

PARTICIPANTS

217 suicide cases reported to the Swedish national root cause analysis database between 2012 and 2017.

PRIMARY AND SECONDARY OUTCOME MEASURES

A total of 961 reported incidents were included. Demographic data and frequencies of reported deficiencies were registered. Topology, centrality indices and communities were explored for three networks. All networks have been tested for robustness and accuracy.

RESULTS

Lack of follow-up, evaluations and insufficient documentation issues emerged as central in the network of major themes, as did the contributing factors representing organisational problems, failing procedures and miscommunication. When analysing the subthemes of deficiencies more closely, disrupted treatments and staffing issues emerged as prominent features. The network covering the subthemes of contributing factors also highlighted discontinuity, fragile work structures, inadequate routines, and lack of resources and relevant competence as potential triggers. However, as the correlation stability coefficients for this network were low, the results need further investigation. Four communities were detected covering nodes for follow-up, evaluation, cooperation, and procedures; communication, documentation and organisation; assessments of suicide risk and psychiatric status; and staffing, missed appointments and declined treatment.

CONCLUSION

The results of this study suggest that healthcare providers may improve patient safety in suicide preventive pathways by taking active measures to provide regular follow-ups to patients with elevated suicide risk. In some cases, declined or cancelled appointments could be a warning sign. Tentative results show organisational instability, in terms of work structure, resources and staffing, as a potential target for intervention, although this must be more extensively explored in the future.

The Place of Gender Stereotypes in the Network of Cognitive Abilities, Self-Perceived Ability and Intrinsic Value of School in School Children Depending on Sex and Preferences in STEM

Adolescents face many barriers on the path towards a STEM profession, especially girls. We examine the gender stereotypes, cognitive abilities, self-perceived ability and intrinsic values of 546 Russian school children from 12 to 17 years old by sex and STEM preferences. In our sample, STEM students compared to no-STEM have higher cognitive abilities, intrinsic motivation towards math and science, are more confident in their math abilities and perceive math as being easier. Boys scored higher in science, math and overall academic self-efficacy, intrinsic learning motivation and math’s importance for future careers. Meanwhile, girls displayed higher levels of gender stereotypes related to STEM and lower self-efficacy in math. A network analysis was conducted to identify the structure of psychological traits and the position of the stem-related stereotypes among them. The analysis arrived at substantially different results when adolescents were grouped by sex or preference towards STEM. It also demonstrated that gender stereotypes are connected with cognitive abilities, with a stronger link in the no-STEM group. Such stereotypes play a more important role for girls than boys and, jointly with the general self-efficacy of cognitive and academic abilities, are associated with the factors that distinguish groups of adolescents in their future careers.

Meta-analytic Gaussian Network Aggregation

A growing number of publications focus on estimating Gaussian graphical models (GGM, networks of partial correlation coefficients). At the same time, generalizibility and replicability of these highly parameterized models are debated, and sample sizes typically found in datasets may not be sufficient for estimating the underlying network structure. In addition, while recent work emerged that aims to compare networks based on different samples, these studies do not take potential cross-study heterogeneity into account. To this end, this paper introduces methods for estimating GGMs by aggregating over multiple datasets. We first introduce a general maximum likelihood estimation modeling framework in which all discussed models are embedded. This modeling framework is subsequently used to introduce meta-analytic Gaussian network aggregation (MAGNA). We discuss two variants: fixed-effects MAGNA, in which heterogeneity across studies is not taken into account, and random-effects MAGNA, which models sample correlations and takes heterogeneity into account. We assess the performance of MAGNA in large-scale simulation studies. Finally, we exemplify the method using four datasets of post-traumatic stress disorder (PTSD) symptoms, and summarize findings from a larger meta-analysis of PTSD symptom.

Objective Bayesian Edge Screening and Structure Selection for Ising Networks

The Ising model is one of the most widely analyzed graphical models in network psychometrics. However, popular approaches to parameter estimation and structure selection for the Ising model cannot naturally express uncertainty about the estimated parameters or selected structures. To address this issue, this paper offers an objective Bayesian approach to parameter estimation and structure selection for the Ising model. Our methods build on a continuous spike-and-slab approach. We show that our methods consistently select the correct structure and provide a new objective method to set the spike-and-slab hyperparameters. To circumvent the exploration of the complete structure space, which is too large in practical situations, we propose a novel approach that first screens for promising edges and then only explore the space instantiated by these edges. We apply our proposed methods to estimate the network of depression and alcohol use disorder symptoms from symptom scores of over 26,000 subjects.

Perfectionism dimensions: A network analysis of their relationships with affect and obsessive-compulsive pathological personality traits

This study investigated the associations of multidimensional perfectionism with positive affect and negative outcomes (affect and Obsessive-Compulsive Personality Disorder [OCPD] pathological traits) through network analysis. The sample consisted of 604 Brazilian adults aged 18-74 years. The network analysis showed that perfectionistic concerns (PC) is strongly and positively associated with negative outcomes, while perfectionistic strivings (PS) maintain positive associations with positive affect, but not negative affect. Negative affect seems to operate as a bridge between perfectionism and OCPD pathological traits, raising crucial questions about the antecedent and consequential role of affect for understanding perfectionism's development and the traits observed in individuals with OCPD. We discuss the limitations and strengths of the study.

Multisource Longitudinal Network and Latent Variable Model Analyses of ADHD Symptoms in Children

Objective: Multisource longitudinal network analysis was used to determine if between-child and within-child variance of attention-deficit/hyperactivity disorder (ADHD) symptoms provided unique findings of ADHD relative to latent variable model (LVM) analyses.Method: Mothers and fathers of 802 Spanish first-grade children (54% boys) provided ratings of ADHD symptoms at two time points six weeks apart (assessment 1: 723 mothers and 603 fathers; assessment 2: 667 mothers and 584 fathers). Network and latent variable models were applied to the ratings.Results: Inattention, hyperactivity, and mixed hyperactive/impulsive symptom communities occurred for the within- and between-children's symptom networks with the results being consistent across mothers and fathers, especially for the between-children's symptom networks. LVM analyses identified three factors with the same symptoms on each factor as in the symptom communities. These models also showed invariance across mothers and fathers as well as assessments.Conclusions: Longitudinal networks provided several useful insights for ADHD, including centrality symptoms that differed across between- and within-child levels. However, many findings were also largely consistent with the LVM analyses. Future studies should use novel methods (e.g., intensive longitudinal measurement) and analytic tools to determine if more unique theoretical and clinical findings emerge when applying network analysis to longitudinally measured ADHD symptoms.

Network Analysis of Depressive Symptomatology in Underweight and Obese Adults

BACKGROUND

Depressive symptoms can affect people's quality of life and social environment. In addition, in severe situations, they can lead to suicidal behaviors.

OBJECTIVE

This study aimed to analyze the differences in depressive symptoms in underweight and obese Peruvian adults.

METHODS

A cross-sectional study was carried out based on secondary data obtained from the Instituto Nacional de Estadística e Informática (INEI), Lima, Peru. A sample of 10 053 participants was considered, of which 55.96% were women. Two Gaussian plot models were estimated and the levels of depressive symptomatology were compared between the 2 groups (adults with underweight and obese).

RESULTS

A total of 1510 (15.02%) were underweight adults and 8543 (84.98%) were obese adults. There were differences in the reporting of depressive symptoms in the underweight group; the most central items were "Depressed mood" (PH2), "Tiredness/low energy" (PH4), and "Psychomotor difficulties" (PH8).

CONCLUSION

This study provides new evidence on the dynamic relationship between depressive symptoms according to the body mass index categories (underweight and obese) assessed.

Publishing quantitative careers research: challenges and recommendations

Purpose

This article aims to provide prospective authors guidelines that will hopefully enable them to submit more competitive manuscripts to journals publishing careers research.

Design/methodology/approach

Based on their experience as an author, reviewer and editorial team member, the authors identify the main criteria that a quantitative study must meet to be considered for publication in international peer-reviewed journals covering career-related topics. They emphasize the importance of contributing to the careers literature and of designing the study in accordance with the research question.

Findings

Manuscripts are rejected because they are insufficiently innovative, and/or because sample, instruments and design are not appropriate to answer the research question at hand. Cross-sectional designs cannot be used to answer questions of mediation but should not be discarded automatically since they can be used to address other types of questions, including questions about nesting, clustering of individuals into subgroups, and to some extent, even causality.

Originality/value

The manuscript provides an insight into the decision-making process of reviewers and editorial board members and includes recommendations on the use of cross-sectional data.

Direct and Indirect Relationships Between Physical Activity, Fitness Level, Kinesiophobia, and Health-Related Quality of Life in Patients with Rheumatic and Musculoskeletal Diseases: A Network Analysis

Introduction

Using a network analysis, the present study investigated the extent to which physical activity (PA), objective fitness level, kinesiophobia, and health-related quality of life (HRQoL) interact in patients with rheumatic and musculoskeletal diseases. The objectives were twofold: 1) to clarify the direct and indirect relationships between these variables while controlling for the shared variance between them, and 2) to establish a potential ranking of influence among them.

Methods

This cross-sectional design study involved patients recruited from a rheumatology unit. One hundred and twenty patients completed self-reported measures of PA, the Tampa scale of kinesiophobia and the 36-item Short-Form Health Survey, and ninety-seven of those patients performed the six-minute walking test and the thirty-second sit-to-stand test. Network analyses were conducted using bootnet and qgraph packages.

Results

Weekly time spent on PA, as well as physical fitness measures, were directly linked to kinesiophobia and the HRQoL physical dimension, but indirectly linked to HRQoL mental dimension through the mediation of kinesiophobia. Specifically, weekly PA time had direct relationships to physical functioning, vitality, and role limitations due to physical and emotional problems. Fitness measures had direct relationships with physical functioning, bodily pain, and mental health. The analyses did not clearly highlight one variable as the most influential in the network.

Discussion

The study highlights the complexities of direct and indirect biopsychosocial relationships that are at the core of patients’ daily functioning. Measurement of PA, use of a longitudinal design, and interventions are discussed.

Exploring the Complexity of Aphasia With Network Analysis

Purpose Aphasia is a complex, neurogenic language disorder, with different aphasia syndromes hallmarked by impairment in fluency, auditory comprehension, naming, and/or repetition. Broad, standardized assessments of language domains and specific language and cognitive assessments provide a holistic impairment profile of a person with aphasia. While many recognize the correlations between assessments, there remains a need to continue understanding the complexity of relationships between assessments for the purpose of better characterization of language impairment profiles of persons with aphasia. We explored the use of network analysis to identify the complex relationships between a variety of language assessments. Method We computed a regularized partial correlation network and a directed acyclic graph network to estimate the relations between different aphasia assessments in 128 persons with aphasia. Results Western Aphasia Battery-Revised Comprehension subtest was the most central assessment in the aphasia symptom network, whereas the Philadelphia Naming Test had the most putative causal influence on other assessments. Additionally, the language assessments segregated into three empirically derived communities denoting phonology, semantics, and syntax. Furthermore, several assessments, including the Philadelphia Naming Test, belonged to multiple communities, suggesting that certain assessments may capture multiple language impairments. Conclusion We discuss the implications of using a network analysis approach for clinical intervention and driving forward novel questions in the field of clinical aphasiology. Supplemental Material https://doi.org/10.23641/asha.16620229.