Network Analyses of the Symptoms in the Coronavirus Anxiety Scale (CAS) and its Associations with Depression, Anxiety, Stress and Alcohol Use

Abstract Background The Covid-19 Pandemic and subsequent actions taken by national/international organizations has generated a large amount of anxiety which may roam into the realm of pathology – COVID Anxiety. In order to measure this phenomenon, measures such as the CAS have been developed. The CAS being a self-report measure of anxiety-related physiologically symptoms that are aroused by information and thoughts related to COVID-19. However, as the CAS is fairly new tit requires validation and examination. This study fulfils this need through the use of Network Analysis. Methods The study used regularized partial correlation network analysis (EBICglasso) to examine the network structure of ratings of COVID anxiety symptoms as presented in the Coronavirus Anxiety Scale (CAS) and how these symptoms are related to distress (combination of depression, anxiety, stress) and alcohol use. A total of 968 adults from an Australian community sample completed the CAS, and measures of depression, anxiety, stress and alcohol use. Results The findings showed that the most central CAS symptom was abdominal distress, followed by tonic immobility. The symptom with the lowest strength centrality value was dizziness. Also, the network revealed at least moderate effect size connections for tonic immobility with dizziness, sleep disturbances abdominal distress, and for abdominal distress with appetite loss. Additionally, distress was associated positively with dizziness, tonic immobility and appetitive loss. Alcohol use was associated positively with dizziness and abdominal distress, and negatively with tonic immobility and appetitive loss. Conclusions Overall, the findings showed a novel understanding of the structure of the COVID anxiety symptoms in the CAS, and how these symptoms are associated with distress and alcohol use. The clinical implications of the findings for assessment and treatment of COVID anxiety and its comorbidity with distress and alcohol use are discussed.

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Comparison of self-report versus agency records of service utilization in a community sample of individuals with alcohol use disorders

Drug and Alcohol Dependence ◽

10.1016/j.drugalcdep.2003.09.006 ◽

2004 ◽

Vol 73 (2) ◽

pp. 141-147 ◽

Cited By ~ 56

Author(s):

Therese K Killeen ◽

Kathleen T Brady ◽

Paul B Gold ◽

Clare Tyson ◽

Kit N Simpson

Keyword(s):

Alcohol Use ◽

Service Utilization ◽

Community Sample ◽

Alcohol Use Disorders ◽

Self Report

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Development and validation of a short form of the Geriatric Anxiety Inventory – the GAI-SF

International Psychogeriatrics ◽

10.1017/s1041610210001237 ◽

2010 ◽

Vol 23 (1) ◽

pp. 125-131 ◽

Cited By ~ 87

Author(s):

Gerard J. Byrne ◽

Nancy A. Pachana

Keyword(s):

Primary Care ◽

Older People ◽

Short Form ◽

Community Sample ◽

Anxiety Symptoms ◽

Self Report ◽

Cross Sectional ◽

Medical Settings ◽

Epidemiological Surveys ◽

Dsm Iv

ABSTRACTBackground: Anxiety symptoms and anxiety disorders are highly prevalent among older people and are associated with considerable disability burden. While several instruments now exist to measure anxiety in older people, there is a need for a very brief self-report scale to measure anxiety symptoms in epidemiological surveys, in primary care and in acute geriatric medical settings. Accordingly, we undertook the development of such a scale, based on the Geriatric Anxiety Inventory.Methods: This is a cross-sectional study of randomly selected, community-residing, older women (N = 284; mean age 72.2 years) using receiver operating characteristic (ROC) analyses. DSM-IV diagnostic interviews were undertaken using the Mini International Diagnostic Interview, fifth edition (MINI-V).Results: We developed a 5-item version of the Geriatric Anxiety Inventory, which we have termed the Geriatric Anxiety Inventory – Short Form (GAI-SF). We found that a score of three or greater was optimal for the detection of DSM-IV Generalized Anxiety Disorder (GAD) in this community sample. At this cut-point, sensitivity was 75%, specificity was 87%, and 86% of participants were correctly classified. GAI-SF score was not related to age, MMSE score, level of education or perceived income adequacy. Internal consistency was high (Cronbach's α = 0.81) and concurrent validity against the State-Trait Anxiety Inventory was good (rs = 0.48, p < 0.001).Conclusions: The GAI-SF is a short form of the Geriatric Anxiety Inventory, which we recommend for use in epidemiological studies. It may also be useful in primary care and acute geriatric medical settings.

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Problematic Internet Use in Children and Adolescents: Associations with psychiatric disorders and impairment

10.21203/rs.2.17146/v1 ◽

2019 ◽

Author(s):

Anita Restrepo ◽

Tohar Scheininger ◽

Jon Clucas ◽

Lindsay Alexander ◽

Giovanni Salum ◽

...

Keyword(s):

Children And Adolescents ◽

Sleep Disturbances ◽

Large Scale ◽

Internet Use ◽

Depressive Disorders ◽

Community Sample ◽

Total Sample ◽

Brain Network ◽

Self Report ◽

Problematic Internet Use

Abstract Background Problematic internet use (PIU) is an increasingly worrisome issue, as youth population studies are establishing links with internalizing and externalizing problems. There is a need for a better understanding of psychiatric diagnostic profiles associated with this issue, as well as its unique contributions to impairment. Here, we leveraged the ongoing, large-scale Child Mind Institute Healthy Brain Network, a transdiagnostic self-referred, community sample of children and adolescents (ages 5-21), to examine the associations between PIU and psychopathology, general impairment, physical health and sleep disturbances.Methods A total sample of 564 (190 female) participants between the ages of 7-15 (mean = 10.80, SD = 2.16), along with their parents/guardians, completed diagnostic interviews with clinicians, answered a myriad of self-report questionnaires, and underwent physical testing as part of the Healthy Brain Network protocol.Results PIU was positively associated with depressive disorders (aOR = 2.34; CI: 1.18-4.56; p = .01), the combined subtype of ADHD (aOR = 1.79; CI: 1.08-2.98; p = .02), greater levels of impairment (Standardized Beta = 4.79; CI: 3.21-6.37; p < .01) and increased sleep disturbances (Standardized Beta = 3.01; CI: 0.58-5.45; p = .02), even when accounting for demographic covariates and psychiatric comorbidity.Conclusions The association between PIU and psychopathology, as well as its impact on impairment and sleep disturbances, highlight the urgent need to gain an understanding of mechanisms in order to inform public health recommendations on internet use in U.S. youth.

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Adolescent psychopathology and psychological wellbeing: A network analysis approach

10.21203/rs.3.rs-32270/v1 ◽

2020 ◽

Author(s):

Tom Osborn ◽

Stephanie Campbell

Keyword(s):

Network Analysis ◽

Emotional Disorders ◽

Low Income ◽

Adolescent Psychopathology ◽

Community Sample ◽

Sub Saharan Africa ◽

Psychological Wellbeing ◽

Cross Sectional ◽

Network Analyses ◽

The Relationship

Abstract Background The extent to which psychological wellbeing may play a preventive and therapeutic role in the development and maintenance of adolescent emotional disorders depends, in part, on the nature of the overlap between these two constructs. We used network analysis to examine the relationship between adolescent psychopathology (measured by depression and anxiety symptoms) and psychological wellbeing (measured by happiness, optimism, social support, perceived control, and gratitude). Methods This was a cross-sectional study with a in a large community sample of Kenyan adolescents (N = 2,192, ages 13-to-18). Network analyses was conducted to examine the topology, stability, centrality, and bridge nodes of a network of psychopathology and psychological wellbeing measures. Results Two distinct community clusters emerged, one for psychopathology nodes and another for wellbeing nodes, suggesting that these are two distinct but connected concepts. Central and bridge nodes of the wellbeing and psychopathology network are identified. The most central nodes in the network were general gratefulness and worry; the strongest negative edges between psychopathology and psychological wellbeing were depressed mood—I love life and irritability—I am a joyful person; the main bridge nodes were optimistic about future and special person around for me. Conclusions Our findings expand understanding of the relationship between wellbeing and psychopathology in an understudied population and are suggestive of how psychological wellbeing can inform psychopathological treatment/preventive efforts in low-income regions such as those in Sub Saharan Africa.

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Adolescent psychopathology and psychological wellbeing: a network analysis approach

BMC Psychiatry ◽

10.1186/s12888-021-03331-x ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Stephanie Campbell ◽

Tom L. Osborn

Keyword(s):

Network Analysis ◽

Emotional Disorders ◽

Low Income ◽

Adolescent Psychopathology ◽

Community Sample ◽

Sub Saharan Africa ◽

Psychological Wellbeing ◽

Cross Sectional ◽

Network Analyses ◽

The Relationship

Abstract Background The extent to which psychological wellbeing may play a preventive and therapeutic role in the development and maintenance of adolescent emotional disorders depends, in part, on the nature of the overlap between these two constructs. We estimated network analysis to examine the relationship between adolescent psychopathology (measured by depression and anxiety symptoms) and psychological wellbeing (measured by happiness, optimism, social support, perceived control, and gratitude). Methods This was a cross-sectional study with a large community sample of Kenyan adolescents (N = 2192, aged 13–18). Network analyses were conducted to examine the topology, stability, centrality, and bridge nodes of a network of psychopathology and psychological wellbeing measures. Results Two distinct community clusters emerged, one for psychopathology nodes and another for wellbeing nodes, suggesting that these are two distinct but connected concepts. Central and bridge nodes of the wellbeing and psychopathology network were identified. The most central nodes in the network were family provides emotional help and support and self-blame; the strongest negative edges between psychopathology and psychological wellbeing were depressed mood—I love life and irritability—I am a joyful person; the main bridge nodes were family helps me and I can talk to family about problems. Conclusions Our findings expand understanding of the relationship between psychopathology and wellbeing in an understudied population and are suggestive of how psychological wellbeing can inform psychopathological treatment and preventive efforts in low-income regions such as those in Sub Saharan Africa.

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Network Analysis and Health and Risk Messaging

Oxford Research Encyclopedia of Communication ◽

10.1093/acrefore/9780190228613.013.361 ◽

2017 ◽

Author(s):

Frank Tutzauer ◽

Thomas Hugh Feeley

Keyword(s):

Network Analysis ◽

Risk Communication ◽

Self Report ◽

Massachusetts Institute Of Technology ◽

Network Analyses ◽

Level Of Activity ◽

Patterns Of Communication ◽

Central Interest ◽

Institute Of Technology ◽

Work Done

A network is a collection of nodes that are somehow connected to each other. Typically, the pattern of ties among nodes is of central interest to scholars in communication and the allied social sciences, with particular salience for health and risk communication. Network analyses of patterns of communication began in the 1940s in work done at the Massachusetts Institute of Technology (MIT) and was popularized in the early 1980s in the communication discipline with the work of Everett Rogers, Larry Kincaid, and others. Networks are measured by using self-report or observational procedures to determine the presence and/or strength among nodes in a given structure. If there is a tie or relation between a pair of nodes, it is said that the two are adjacent to one another or that the two nodes are neighbors, and the neighborhood of a node consists of all nodes adjacent to this first node. Several measures describe networks, including measures of position and measures of the entire network. Positional measures consider the position of any given node in relation to others in the network, and centrality is a popular measure to account for one’s level of influence in a network. Density is an overall network measure of level of activity among network pairs. Finally, network measures allow researchers to compare dependent and independent networks. Network analysis represents one of the more powerful and elegant procedures for measuring small-group, organizational, and international communication patterns among nodes or actors of interest in health and risk communication.

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Self-Report of Alcohol Use for Pain in a Multi-Ethnic Community Sample

Journal of Pain ◽

10.1016/j.jpain.2009.03.005 ◽

2009 ◽

Vol 10 (9) ◽

pp. 944-952 ◽

Cited By ~ 91

Author(s):

Joseph L. Riley III ◽

Christopher King

Keyword(s):

Alcohol Use ◽

Community Sample ◽

Ethnic Community ◽

Self Report

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Preprint: Alcohol's effects during uncertain and uncontrollable stressors in the laboratory

10.31234/osf.io/uvwqr ◽

2021 ◽

Author(s):

Daniel E. Bradford ◽

Jack Michael Shireman ◽

Sarah June Kittleson Sant'Ana ◽

Gaylen Fronk ◽

Susan E. Wanta (Schneck) ◽

...

Keyword(s):

Alcohol Use ◽

Electric Shock ◽

Stress Reactivity ◽

Negative Reinforcement ◽

Community Sample ◽

Self Report ◽

Chronic Alcohol ◽

Affective Components ◽

Negative Impacts ◽

Startle Potentiation

Alcohol’s effects on reactivity to stressors depend on the nature of the stressor and the reactivity being assessed. Research identifying characteristics of stressors that modulate reactivity and clarifies the neurobehavioral, cognitive, and affective components of this reactivity may help prevent, reduce or treat the negative impacts of acute and chronic alcohol use with implications for other psychopathology involving maladaptive reactivity to stressors. We used a novel, multi-measure, cued electric shock stressor paradigm in a greater university community sample of adult recreational drinkers to test how alcohol (N=64), compared to No-alcohol (N=64), affects reactivity to stressors that vary in both their perceived certainty and controllability. Preregistered analyses suggested alcohol significantly dampened subjective anxiety (self-report) and defensive reactivity (startle potentiation) more during uncertain than during certain stressors regardless of controllability, suggesting that stressor uncertainty —but not uncontrollability— may be sufficient to enhance alcohol’s stress reactivity dampening and thus negative reinforcement potential.

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Psychometric properties of the Sleep Hygiene Index in a large Italian community sample.

10.1101/2021.05.26.21257845 ◽

2021 ◽

Author(s):

Andrea Zagaria ◽

Andrea Ballesio ◽

Alessandro Musetti ◽

Vittorio Lenzo ◽

Maria C. Quattropani ◽

...

Keyword(s):

Mental Health ◽

Psychometric Properties ◽

Emotional Distress ◽

Sleep Disturbances ◽

Sleep Problems ◽

Community Sample ◽

Sleep Hygiene ◽

Self Report ◽

Poor Sleep ◽

Emotional Symptoms

Objective/Background: Poor sleep hygiene is considered an exacerbating and perpetuating factor of sleep disturbances and is also associated with poor mental health. The Sleep Hygiene Index (SHI) is a self-report measure assessing adherence to sleep hygiene practices. The aim of this study was to estimate the psychometric properties of the SHI in an Italian representative sample of the general population, following a formative measurement approach. Patients/Methods: Participants (n=6276; M=33.62, SD=13.45) completed the SHI alongside measures of sleep disturbance, depression, anxiety, and stress. To consider the item formative nature, sets of item-composites weighted by means of canonical correlation analysis was created and a confirmatory factor analysis (CFA) was implemented. Factorial invariance tests were computed considering both presence of sleep problems and presence of emotional distress symptoms as grouping variables. Results and Conclusions: CFA confirmed the unidimensional structure of SHI. Internal consistency was acceptable (ω=0.752). Test-retest reliability at 8-10 months presented an ICC of 0.666. SHI significantly correlated with sleep, depression, anxiety and stress symptoms (r range from 0.358 to 0.500). Configural and metric invariance were reached for both grouping variables. Partial scalar invariance was obtained only across emotional distress groups. People with emotional symptoms reported higher latent means on the sleep hygiene dimension. Findings support the validity and reliability of the Italian version of the SHI. Importantly, the SHI showed robust psychometric properties both in healthy individuals and in individual reporting mental health symptoms. Thus, it is advisable to use this version of the SHI in both research and clinical practice.

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Problematic Internet Use in Children and Adolescents: Associations with psychiatric disorders and impairment

10.21203/rs.2.17146/v3 ◽

2020 ◽

Author(s):

Anita Restrepo(Former Corresponding Author) ◽

Tohar Scheininger ◽

Jon Clucas ◽

Lindsay Alexander ◽

Giovanni Salum ◽

...

Keyword(s):

Children And Adolescents ◽

Sleep Disturbances ◽

Large Scale ◽

Internet Use ◽

Community Sample ◽

Autism Spectrum ◽

Brain Network ◽

Self Report ◽

Problematic Internet Use ◽

Wide Range

Abstract Background: Problematic internet use (PIU) is an increasingly worrisome issue, as youth population studies are establishing links with internalizing and externalizing problems. There is a need for a better understanding of psychiatric diagnostic profiles associated with this issue, as well as its unique contributions to impairment. Here, we leveraged the ongoing, large-scale Child Mind Institute Healthy Brain Network, a transdiagnostic self-referred, community sample of children and adolescents (ages 5-21), to examine the associations between PIU and psychopathology, general impairment, physical health and sleep disturbances.Methods: A total sample of 564 (190 female) participants between the ages of 7-15 (mean = 10.80, SD = 2.16), along with their parents/guardians, completed diagnostic interviews with clinicians, answered a wide range of self-report (SR) and parent-report (PR) questionnaires, including the Internet Addiction Test (IAT) and underwent physical testing as part of the Healthy Brain Network protocol. Results: PIU was positively associated with depressive disorders (SR: aOR = 2.43, CI: 1.22-4.74, p = .01; PR: aOR = 2.56, CI: 1.31-5.05, p = .01), the combined presentation of ADHD (SR: aOR = 1.91, CI: 1.14-3.22, p = .01; PR: n.s.), Autism Spectrum Disorder (SR: n.s.; PR: aOR = 2.24, CI: 1.34-3.73, p < .001), greater levels of impairment (SR: Standardized Beta = 4.63, CI: 3.06-6.20, p < .001; PR: Standardized Beta = 5.05, CI: 3.67-6.42, p < .001) and increased sleep disturbances (SR: Standardized Beta = 3.15, CI: 0.71-5.59, p = .01; PR: Standardized Beta = 3.55, CI: 1.34-5.75, p < .001), even when accounting for demographic covariates and psychiatric comorbidity.Conclusions: The association between PIU and psychopathology, as well as its impact on impairment and sleep disturbances, highlight the urgent need to gain an understanding of mechanisms in order to inform public health recommendations on internet use in U.S. youth.

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