Personalized networks of psychological symptoms aim to advance therapy by identifying treatment targets for specific patients. Statistical relations in such networks can be estimated from intensive ...longitudinal data, but their causal interpretation is limited by strong statistical assumptions. An alternative is to create networks from patient perceptions, which comes with other limitations such as retrospective bias. We introduce the Longitudinal Perceived Causal Problem Networks (L-PECAN) approach to address both these concerns. 20 participants screening positive for depression completed 4 weeks day of brief daily assessments of perceived symptom interactions. Quality criteria of this new method are introduced, answering questions such as "Which symptoms should be included in networks?", "How many datapoints need to be collected to achieve stable networks?", and "Does the network change over time?". Accordingly, about 40% of respondents achieved stable networks and only few respondents exhibited network structure that changed during the assessment period. The method was time-efficient (on average 7.4 min per day), and well received. Overall, L-PECAN addresses several of the prevailing issues found in statistical networks and therefore provides a clinically meaningful method for personalization.
Summary
Sleep bruxism (SB) is a repetitive jaw‐muscle activity characterised by clenching or grinding of the teeth and/or by bracing or thrusting of the mandible. Sleep bruxism has been linked with ...insomnia symptoms. Moreover, it has been suggested that there is a positive association between distress and the occurrence of sleep bruxism. However, the occurrence of sleep bruxism and its association with distress have not been studied in patients with insomnia. Therefore, we hypothesised that: (1) the occurrence of sleep bruxism is higher in patients with insomnia than in healthy controls; and (2) the occurrence of sleep bruxism in insomnia patients with moderate to high distress (IMHD) is higher than that in insomnia patients with slight distress (ISD). A total of 44 controls (34 females, 10 males, mean ± SD age = 46.8 ± 14.4 years) and 42 participants with insomnia (35 females, 7 males, mean ± SD age = 51.3 ± 12.1 years) were enrolled in this study. Among 42 participants with insomnia, 20 participants were subtyped as IMHD, 17 participants as ISD. Another five participants were not subtyped due to insufficient information. Group differences in rhythmic masticatory muscle activity (RMMA), a biomarker of sleep bruxism, were evaluated with Mann–Whitney U tests. The medians and interquartile ranges of the RMMA indices were 0.8|1.8|3.3 in controls, 1.1|1.6|2.3 in IMHD and 1.2|1.9|2.9 in ISD. There was no significant difference in the RMMA index, neither between participants with insomnia and controls (P = 0.514) nor between IMHD versus ISD (P = 0.270). The occurrence of RMMA indicators of possible sleep bruxism is not significantly different between individuals with insomnia and controls, nor between IMHD versus ISD.
Abstract
Study Objectives
Major depressive disorder (MDD) is the leading cause of disability worldwide. Its high recurrence rate calls for prevention of first-onset MDD. Although meta-analysis ...suggested insomnia as the strongest modifiable risk factor, previous studies insufficiently addressed that insomnia might also occur as a residual symptom of unassessed prior depression, or as a comorbid complaint secondary to other depression risks.
Methods
In total, 768 participants from the Netherlands Study of Depression and Anxiety who were free from current and lifetime MDD were followed-up for four repeated assessments, spanning 6 years in total. We performed separate Cox proportional hazard analyses to evaluate whether baseline insomnia severity, short-sleep duration, and individual insomnia complaints prospectively predicted first-onset MDD during follow-up. The novel method of network outcome analysis (NOA) allowed us to sort out whether there is any direct predictive value of individual insomnia complaints among several other complaints that are associated with insomnia.
Results
Over 6-year follow-up, 141 (18.4%) were diagnosed with first-onset MDD. Insomnia severity but not sleep duration predicted first-onset MDD (HR = 1.11, 95% CI: 1.07–1.15), and this was driven solely by the insomnia complaint difficulty initiating sleep (DIS) (HR = 1.10, 95% CI: 1.04–1.16). NOA likewise identified DIS only to directly predict first-onset MDD, independent of four other associated depression complaints.
Conclusions
We showed prospectively that DIS is a risk factor for first-onset MDD. Among the different other insomnia symptoms, the specific treatment of DIS might be the most sensible target to combat the global burden of depression through prevention.
Objective:
Cognitive therapy (CT) and behavior therapy (BT) are both effective for insomnia but are expected to work via different pathways. Empirically, little is known about their symptom-specific ...effects.
Method:
This was a secondary analysis of a randomized controlled trial of online treatment for insomnia disorder (N = 219, 72.9% female, mean age = 52.5 years, SD = 13.9). Participants were randomized to CT (n = 72), BT (n = 73), or wait-list (n = 74). Network Intervention Analysis was used to investigate the symptom-specific treatment effects of CT and BT throughout treatment (wait-list was excluded from the current study). The networks included the Insomnia Severity Index items and the sleep diary-based sleep efficiency and were estimated biweekly from Week 0 until Week 10.
Results:
Participants in the BT condition showed symptom-specific effects compared to CT on "sleep efficiency" (Week 4-8, post-test), "difficulty maintaining sleep" (Week 4), and "dissatisfaction with sleep" (post-test). Participants in the CT showed symptom-specific effects compared to BT on "interference with daily functioning" (Week 8, post-test), "difficulty initiating sleep", "early morning awakenings," and "worry about sleep" (all post-test).
Conclusions:
This is the first study that observed specific differential treatment effects for BT and CT throughout the course of their treatment. These effects were more pronounced for BT than for CT and were in line with the theoretical background of these treatments. We think the embedment of the theoretical background of CT and BT in empirical data is of major importance to guide further treatment development.
What is the Public Health Significance of this Article?
Cognitive therapy and behavior therapy are both effective for insomnia in a stand-alone format. In this study, we showed that over the course of treatment, cognitive therapy and behavior therapy have different symptom-specific effects. These differences are in line with the theoretical backgrounds of the treatments. Knowledge on these different points of engagement may guide further treatment development.
Insomnia and chronic pain are highly prevalent conditions and are often comorbid. Somatic complaints other than pain are also often observed in insomnia. Poor sleep and pain are known to mutually ...reinforce each other. However, it is unknown whether the habitual severity of insomnia modulates the acute effect of a particularly bad night's sleep on the next day's pain severity, and whether it modulates the acute effect of pain on the following night's sleep quality. Using data from 3,508 volunteers (2,684 female, mean age 50.09 y), we addressed these questions in addition to the associations between the habitual severity of insomnia, somatic complaints, and pain. Results indicated that people suffering from more severe habitual insomnia showed stronger mutual acute within-day reactivity of pain and poor sleep quality. The same increased reactivity was found in people with more severe habitual pain. Interestingly, the acute within-day mutual reactivity of pain and sleep quality showed consistent asymmetry. Pain worsened more after a particularly bad night's sleep than it improved after a particularly good night's sleep. Likewise, sleep worsened more after a day with more-than-usual pain than it improved after a day with less-than-usual pain. Future interventions may profit from addressing this asymmetric mutual reactivity especially in people with severe comorbid insomnia and chronic pain.
Human social behavior plays a crucial role in how pathogens like SARS-CoV-2 or fake news spread in a population. Social interactions determine the contact network among individuals, while spreading, ...requiring individual-to-individual transmission, takes place on top of the network. Studying the topological aspects of a contact network, therefore, not only has the potential of leading to valuable insights into how the behavior of individuals impacts spreading phenomena, but it may also open up possibilities for devising effective behavioral interventions. Because of the temporal nature of interactions-since the topology of the network, containing who is in contact with whom, when, for how long, and in which precise sequence, varies (rapidly) in time-analyzing them requires developing network methods and metrics that respect temporal variability, in contrast to those developed for static (i.e., time-invariant) networks. Here, by means of event mapping, we propose a method to quantify how quickly agents mingle by transforming temporal network data of agent contacts. We define a novel measure called contact sequence centrality, which quantifies the impact of an individual on the contact sequences, reflecting the individual's behavioral potential for spreading. Comparing contact sequence centrality across agents allows for ranking the impact of agents and identifying potential 'behavioral super-spreaders'. The method is applied to social interaction data collected at an art fair in Amsterdam. We relate the measure to the existing network metrics, both temporal and static, and find that (mostly at longer time scales) traditional metrics lose their resemblance to contact sequence centrality. Our work highlights the importance of accounting for the sequential nature of contacts when analyzing social interactions.
To investigate the association between self-reported sleep bruxism and insomnia and their potential risk factors (eg, depression and anxiety), and to construct a network model with all these factors.
...We recruited 2251 participants from the Netherlands Sleep Registry. All participants completed questionnaires on self-reported sleep bruxism, insomnia, depression, anxiety, smoking frequency, and alcohol and caffeine consumption. The associations between self-reported sleep bruxism and other variables were analyzed by univariate analysis, multivariate logistic regression, and network analysis.
Although univariate analysis showed that there was a positive association between sleep bruxism and insomnia (P < 0.001), this association disappeared in the multivariate logistic regression model (P = 0.258). However, multivariate logistic regression did show an association between self-reported sleep bruxism and anxiety (OR = 1.087, 95% CI 1.041–1.134). The network model showed that there was no direct link between self-reported sleep bruxism and insomnia. However, there was an indirect link between self-reported sleep bruxism and insomnia via anxiety.
Although self-reported sleep bruxism has no direct association with insomnia, anxiety is a bridging factor between these variables.
•Anxiety is a bridging factor between self-reported sleep bruxism and insomnia.•Self-reported sleep bruxism is associated with psychological factors.•Multidisciplinary approach is needed for sleep bruxism and insomnia management.
Network theory, as a theoretical and methodological framework, is energizing many research fields, among which clinical psychology and psychiatry. Fundamental to the network theory of psychopathology ...is the role of specific symptoms and their interactions. Current statistical tools, however, fail to fully capture this constitutional property. We propose community detection tools as a means to evaluate the complex network structure of psychopathology, free from its original boundaries of distinct disorders. Unique to this approach is that symptoms can belong to multiple communities. Using a large community sample and spanning a broad range of symptoms (Symptom Checklist-90-Revised), we identified 18 communities of interconnected symptoms. The differential role of symptoms within and between communities offers a framework to study the clinical concepts of comorbidity, heterogeneity and hallmark symptoms. Symptoms with many and strong connections within a community, defined as stabilizing symptoms, could be thought of as the core of a community, whereas symptoms that belong to multiple communities, defined as communicating symptoms, facilitate the communication between problem areas. We propose that defining symptoms on their stabilizing and/or communicating role within and across communities accelerates our understanding of these clinical phenomena, central to research and treatment of psychopathology.