Correction: An n=1 Clinical Network Analysis of Symptoms and Treatment in Psychosis

Temporal network of experience sampling methodology identifies sleep disturbance as a central symptom in generalized anxiety disorder

BACKGROUND

A temporal network of generalized anxiety disorder (GAD) symptoms could provide valuable understanding of the occurrence and maintenance of GAD. We aim to obtain an exploratory conceptualization of temporal GAD network and identify the central symptom.

METHODS

A sample of participants (n = 115) with elevated GAD-7 scores (Generalized Anxiety Disorder 7-Item Questionnaire [GAD-7] ≥ 10) participated in an online daily diary study in which they reported their GAD symptoms based on DSM-5 diagnostic criteria (eight symptoms in total) for 50 consecutive days. We used a multilevel VAR model to obtain the temporal network.

RESULTS

In temporal network, a lot of lagged relationships exist among GAD symptoms and these lagged relationships are all positive. All symptoms have autocorrelations and there are also some interesting feedback loops in temporal network. Sleep disturbance has the highest Out-strength centrality.

CONCLUSIONS

This study indicates how GAD symptoms interact with each other and strengthen themselves over time, and particularly highlights the relationships between sleep disturbance and other GAD symptoms. Sleep disturbance may play an important role in the dynamic development and maintenance process of GAD. The present study may develop the knowledge of the theoretical model, diagnosis, prevention and intervention of GAD from a temporal symptoms network perspective.

Using network models in person-centered care in psychiatry: How perspectivism could help to draw boundaries

In this paper, we explore the conceptual problems that arise when using network analysis in person-centered care (PCC) in psychiatry. Personalized network models are potentially helpful tools for PCC, but we argue that using them in psychiatric practice raises boundary problems, i.e., problems in demarcating what should and should not be included in the model, which may limit their ability to provide clinically-relevant knowledge. Models can have explanatory and representational boundaries, among others. We argue that perspectival reasoning can make more explicit what questions personalized network models can address in PCC, given their boundaries.

A network analysis of female sexual function: comparing symptom networks in women with decreased, increased, and stable sexual desire

Problems related to low sexual desire in women are common clinical complaints, and the aetiology is poorly understood. We investigated predictors of change in levels of sexual desire using a novel network approach, which assumes that mental disorders arise from direct interactions between symptoms. Using population-based data from 1,449 Finnish women, we compared between-subject networks of women whose sexual desire decreased, increased, or remained stable over time. Networks were estimated and analyzed at T1 (2006) and replicated at T2 (2013) using R. Domains included were, among others, sexual functions, sexual distress, anxiety, depression, body dissatisfaction, and relationship status. Overall, networks were fairly similar across groups. Sexual arousal, satisfaction, and relationship status were the most central variables, implying that they might play prominent roles in female sexual function; sexual distress mediated between general distress and sexual function; and sexual desire and arousal showed different patterns of relationships, suggesting that they represent unique sexual function aspects. Potential group-differences suggested that sex-related pain and body dissatisfaction might play roles in precipitating decreases of sexual desire. The general network structure and similarities between groups replicated well; however, the potential group-differences did not replicate. Our study sets the stage for future clinical and longitudinal network modelling of female sexual function.

Psychotic Experiences and Related Distress: A Cross-national Comparison and Network Analysis Based on 7141 Participants From 13 Countries

Psychotic experiences (PEs) are common in the general population but do not necessarily reflect a risk status if they occur in relative isolation or are not distressing. Emerging evidence suggests that PEs might be experienced as more benign for individuals from collectivistic low- and middle-income countries (LAMIC) compared with individualistic high-income countries (HIC). The aim of this study was to determine whether: (1) self-reported PEs are less distressing in community samples from LAMIC than from HIC; (2) the network of PEs is significantly less connected in a sample from LAMIC than from HIC. Adults from 8 HIC (n = 4669) and 5 LAMIC (n = 2472) were compared. The lifetime frequency of PEs and related distress were assessed with the Community Assessment of Psychic Experiences. We analyzed the associations of PEs with distress and country type. The interconnection of PEs was visualized by a network analysis and tested for differences in global connection strengths. The average endorsement rates of PEs were significantly higher in LAMIC than in HIC (χ2 = 1772.87, P < .01, Φcramer = 0.50). There was a universal positive correlation between higher frequency of PEs and more distress, but the distress levels controlled for frequency were significantly higher in HIC (R2 = 0.11; b = 0.26; SE = 0.01; T = 17.68; P < .001). Moreover, the network of PEs was significantly less connected in LAMIC (S = 0.40, P < .05). The findings indicate that PEs are of less clinical relevance in LAMIC compared with HIC. The universal use of current high-risk criteria might thus not be adequate without consideration of associated distress and cultural values.