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Wang X, McGowan AL, Fosco GM, Falk EB, Bassett DS, Lydon-Staley DM. A socioemotional network perspective on momentary experiences of family conflict in young adults. FAMILY PROCESS 2024. [PMID: 38529525 DOI: 10.1111/famp.12995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 01/29/2024] [Accepted: 03/11/2024] [Indexed: 03/27/2024]
Abstract
Family conflict is an established predictor of psychopathology in youth. Traditional approaches focus on between-family differences in conflict. Daily fluctuations in conflict within families might also impact psychopathology, but more research is needed to understand how and why. Using 21 days of daily diary data and 6-times a day experience-sampling data (N = 77 participants; mean age = 21.18, SD = 1.75; 63 women, 14 men), we captured day-to-day and within-day fluctuations in family conflict, anger, anxiety, and sadness. Using multilevel models, we find that days of higher-than-usual anger are also days of higher-than-usual family conflict. Examining associations between family conflict and emotions within days, we find that moments of higher-than-usual anger predict higher-than-usual family conflict later in the day. We observe substantial between-family differences in these patterns with implications for psychopathology; youth showing the substantial interplay between family conflict and emotions across time had a more perseverative family conflict and greater trait anxiety. Overall, findings indicate the importance of increases in youth anger for experiences of family conflict during young adulthood and demonstrate how intensive repeated measures coupled with network analytic approaches can capture long-theorized notions of reciprocal processes in daily family life.
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Affiliation(s)
- Xinyi Wang
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Amanda L McGowan
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Gregory M Fosco
- Human Development & Family Studies, The Pennsylvania State University, State College, Pennsylvania, USA
- The Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, State College, Pennsylvania, USA
| | - Emily B Falk
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Marketing Department, Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Dani S Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Physics & Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Electrical & Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Santa Fe Institute, Santa Fe, New Mexico, USA
| | - David M Lydon-Staley
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Astle DE, Bassett DS, Viding E. Understanding divergence: Placing developmental neuroscience in its dynamic context. Neurosci Biobehav Rev 2024; 157:105539. [PMID: 38211738 DOI: 10.1016/j.neubiorev.2024.105539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 01/13/2024]
Abstract
Neurodevelopment is not merely a process of brain maturation, but an adaptation to constraints unique to each individual and to the environments we co-create. However, our theoretical and methodological toolkits often ignore this reality. There is growing awareness that a shift is needed that allows us to study divergence of brain and behaviour across conventional categorical boundaries. However, we argue that in future our study of divergence must also incorporate the developmental dynamics that capture the emergence of those neurodevelopmental differences. This crucial step will require adjustments in study design and methodology. If our ultimate aim is to incorporate the developmental dynamics that capture how, and ultimately when, divergence takes place then we will need an analytic toolkit equal to these ambitions. We argue that the over reliance on group averages has been a conceptual dead-end with regard to the neurodevelopmental differences. This is in part because any individual differences and developmental dynamics are inevitably lost within the group average. Instead, analytic approaches which are themselves new, or simply newly applied within this context, may allow us to shift our theoretical and methodological frameworks from groups to individuals. Likewise, methods capable of modelling complex dynamic systems may allow us to understand the emergent dynamics only possible at the level of an interacting neural system.
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Affiliation(s)
- Duncan E Astle
- Department of Psychiatry, University of Cambridge, United Kingdom; MRC Cognition and Brain Sciences Unit, University of Cambridge, United Kingdom.
| | - Dani S Bassett
- Departments of Bioengineering, Electrical & Systems Engineering, Physics & Astronomy, Neurology, and Psychiatry, University of Pennsylvania, United States; The Santa Fe Institute, United States
| | - Essi Viding
- Psychology and Language Sciences, University College London, United Kingdom
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Schumacher L, Klein JP, Elsaesser M, Härter M, Hautzinger M, Schramm E, Kriston L. Implications of the Network Theory for the Treatment of Mental Disorders: A Secondary Analysis of a Randomized Clinical Trial. JAMA Psychiatry 2023; 80:1160-1168. [PMID: 37610747 PMCID: PMC10448377 DOI: 10.1001/jamapsychiatry.2023.2823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/07/2023] [Indexed: 08/24/2023]
Abstract
Importance Conceptualizing mental disorders as latent entities has been challenged by the network theory of mental disorders, which states that psychological problems are constituted by a network of mutually interacting symptoms. While the implications of the network approach for planning and evaluating treatments have been intensively discussed, empirical support for the claims of the network theory regarding treatment effects is lacking. Objective To assess the extent to which specific hypotheses derived from the network theory regarding the (interindividual) changeability of symptom dynamics in response to treatment align with empirical data. Design, Setting, and Participants This secondary analysis entails data from a multisite randomized clinical trial, in which 254 patients with chronic depression reported on their depressive symptoms at every treatment session. Data collection was conducted between March 5, 2010, and October 14, 2013, and this analysis was conducted between November 1, 2021, and May 31, 2022. Intervention Thirty-two sessions of either disorder-specific or nonspecific psychotherapy for chronic depression. Main Outcomes and Measures Longitudinal associations of depressive symptoms with each other and change of these associations through treatment estimated by a time-varying longitudinal network model. Results In a sample of 254 participants (166 [65.4%] women; mean [SD] age, 44.9 [11.9] years), symptom interactions changed through treatment, and this change varied across treatments and individuals. The mean absolute (ie, valence-ignorant) strength of symptom interactions (logarithmic odds ratio scale) increased from 0.40 (95% CI, 0.36-0.44) to 0.60 (95% CI, 0.52-0.70) during nonspecific psychotherapy and to 0.56 (95% CI, 0.48-0.64) during disorder-specific psychotherapy. In contrast, the mean raw (ie, valence-sensitive) strength of symptom interactions decreased from 0.32 (95% CI, 0.28-0.36) to 0.26 (95% CI, 0.20-0.32) and to 0.09 (95% CI, 0.02-0.16), respectively. Changing symptom severity could be explained to a large extent by symptom interactions. Conclusions and Relevance These findings suggest that specific treatment-related hypotheses of the network theory align well with empirical data. Conceptualizing mental disorders as symptom networks and treatments as measures that aim to change these networks is expected to give further insights into the working mechanisms of mental health treatments, leading to the improvement of current and the development of new treatments. Trial Registration ClinicalTrials.gov Identifier: NCT00970437.
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Affiliation(s)
- Lea Schumacher
- Department of Medical Psychology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jan Philipp Klein
- Department of Psychiatry, Psychosomatics and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Moritz Elsaesser
- Department of Psychiatry and Psychotherapy, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Martin Härter
- Department of Medical Psychology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Martin Hautzinger
- Department of Psychology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Elisabeth Schramm
- Department of Psychiatry and Psychotherapy, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Levente Kriston
- Department of Medical Psychology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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Shaikh S, McGowan A, Lydon-Staley D. Associations between valenced news and affect in daily life: Experimental and ecological momentary assessment approaches. MEDIA PSYCHOLOGY 2023; 27:455-478. [PMID: 38919709 PMCID: PMC11196022 DOI: 10.1080/15213269.2023.2247320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/27/2024]
Abstract
In 203 (mean age = 38.04 years, SD=12.05) participants, we tested the association between valenced news and affect using a 14-day, smartphone-based ecological momentary assessment protocol consisting of two components: 1) a once-per-day experimental protocol in which participants were exposed to good news and bad news stories and 2) a four-times-per-day protocol capturing ecological fluctuations in news consumption. Across both protocols, we replicate findings that consumption of positively valenced news is associated with increased positive affect and decreased negative affect while consumption of negatively valenced news is associated with increased negative affect and decreased positive affect. By integrating the ecological momentary assessment data with network science methodologies, news selection and news effects were modeled simultaneously, uncovering selection processes whereby current positive affect, but not negative affect, predicted future valenced news consumption. Altogether, findings indicate that everyday news consumption influences positive and negative affect and may serve mood management functions for positive but not negative affect.
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Affiliation(s)
- S.J. Shaikh
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA
- Amsterdam School of Communication Research, University of Amsterdam, Amsterdam
| | - A.L. McGowan
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA
- Department of Psychology, Concordia University, Montréal, QC, Canada
| | - D.M. Lydon-Staley
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
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Aslan M, Sala M, Gueorguieva R, Garrison KA. A Network Analysis of Cigarette Craving. Nicotine Tob Res 2023; 25:1155-1163. [PMID: 36757093 PMCID: PMC10202645 DOI: 10.1093/ntr/ntad021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 01/25/2023] [Accepted: 02/06/2023] [Indexed: 05/24/2023]
Abstract
INTRODUCTION Craving is considered a central process to addictive behavior including cigarette smoking, although the clinical utility of craving relies on how it is defined and measured. Network analysis enables examining the network structure of craving symptoms, identifying the most central symptoms of cigarette craving, and improving our understanding of craving and its measurement. AIMS AND METHODS This study used network analysis to identify the central symptoms of self-reported cigarette craving as measured by the Craving Experience Questionnaire, which assesses both craving strength and craving frequency. Data were obtained from baseline of a randomized controlled trial of mindfulness training for smoking cessation. RESULTS The most central symptoms in an overall cigarette craving network were the frequency of imagining its smell, imagining its taste, and intrusive thoughts. The most central symptoms of both craving frequency and craving strength sub-networks were imagining its taste, the urge to have it, and intrusive thoughts. CONCLUSIONS The most central craving symptoms reported by individuals in treatment for cigarette smoking were from the frequency domain, demonstrating the value of assessing craving frequency along with craving strength. Central craving symptoms included multisensory imagery (taste, smell), intrusive thoughts, and urge, providing additional evidence that these symptoms may be important to consider in craving measurement and intervention. Findings provide insight into the symptoms that are central to craving, contributing to a better understanding of cigarette cravings, and suggesting potential targets for clinical interventions. IMPLICATIONS This study used network analysis to identify central symptoms of cigarette craving. Both craving frequency and strength were assessed. The most central symptoms of cigarette craving were related to craving frequency. Central symptoms included multisensory imagery, intrusive thoughts, and urge. Central symptoms might be targeted by smoking cessation treatment.
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Affiliation(s)
- Mihaela Aslan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA CT Healthcare System, West Haven, CT, USA
- Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Margaret Sala
- Ferkauf Graduate School of Psychology, Yeshiva University, The Bronx, NY, USA
| | - Ralitza Gueorguieva
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
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McGowan AL, Sayed F, Boyd ZM, Jovanova M, Kang Y, Speer ME, Cosme D, Mucha PJ, Ochsner KN, Bassett DS, Falk EB, Lydon-Staley DM. Dense Sampling Approaches for Psychiatry Research: Combining Scanners and Smartphones. Biol Psychiatry 2023; 93:681-689. [PMID: 36797176 PMCID: PMC10038886 DOI: 10.1016/j.biopsych.2022.12.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 11/22/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022]
Abstract
Together, data from brain scanners and smartphones have sufficient coverage of biology, psychology, and environment to articulate between-person differences in the interplay within and across biological, psychological, and environmental systems thought to underlie psychopathology. An important next step is to develop frameworks that combine these two modalities in ways that leverage their coverage across layers of human experience to have maximum impact on our understanding and treatment of psychopathology. We review literature published in the last 3 years highlighting how scanners and smartphones have been combined to date, outline and discuss the strengths and weaknesses of existing approaches, and sketch a network science framework heretofore underrepresented in work combining scanners and smartphones that can push forward our understanding of health and disease.
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Affiliation(s)
- Amanda L McGowan
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychology, Concordia University, Montréal, Québec, Canada
| | - Farah Sayed
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Zachary M Boyd
- Department of Mathematics, Brigham Young University, Provo, Utah
| | - Mia Jovanova
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Yoona Kang
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Megan E Speer
- Department of Psychology, Columbia University, New York, New York
| | - Danielle Cosme
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Peter J Mucha
- Department of Mathematics, Dartmouth College, Hanover, New Hampshire
| | - Kevin N Ochsner
- Department of Psychology, Columbia University, New York, New York
| | - Dani S Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Physics & Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Electrical & Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Santa Fe Institute, Santa Fe, New Mexico
| | - Emily B Falk
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania; Marketing Department, Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania; Operations, Information and Decisions, Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania
| | - David M Lydon-Staley
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania.
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Brinberg M, Lydon-Staley DM. Conceptualizing and Examining Change in Communication Research. COMMUNICATION METHODS AND MEASURES 2023; 17:59-82. [PMID: 37122497 PMCID: PMC10139745 DOI: 10.1080/19312458.2023.2167197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Communication research often focuses on processes of communication, such as how messages impact individuals over time or how interpersonal relationships develop and change. Despite their importance, these change processes are often implicit in much theoretical and empirical work in communication. Intensive longitudinal data are becoming increasingly feasible to collect and, when coupled with appropriate analytic frameworks, enable researchers to better explore and articulate the types of change underlying communication processes. To facilitate the study of change processes, we (a) describe advances in data collection and analytic methods that allow researchers to articulate complex change processes of phenomena in communication research, (b) provide an overview of change processes and how they may be captured with intensive longitudinal methods, and (c) discuss considerations of capturing change when designing and implementing studies. We are excited about the future of studying processes of change in communication research, and we look forward to the iterations between empirical tests and theory revision that will occur as researchers delve into studying change within communication processes.
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