Adult attachment, intimacy and psychological distress in a clinical and community sample

2005 ◽  
Vol 12 (6) ◽  
pp. 455-464 ◽  
Author(s):  
Suzanne B. Pielage ◽  
Frans Luteijn ◽  
Willem A. Arrindell
Keyword(s):  
Psychological Distress ◽  
Adult Attachment ◽  
Community Sample

Mothers’ Personal and Interpersonal Function as Potential Mediators Between Maternal Maltreatment History and Child Behavior Problems

2017 ◽  
Vol 23 (2) ◽  
pp. 147-156 ◽  
Author(s):  
Jessica Pereira ◽  
Jaclyn A. Ludmer ◽  
Andrea Gonzalez ◽  
Leslie Atkinson
Keyword(s):  
Social Support ◽  
Depressive Symptoms ◽  
Child Behavior ◽  
Adult Attachment ◽  
Childhood Maltreatment ◽  
Community Sample ◽  
Maternal Sensitivity ◽  
Behavioral Observation ◽  
Maternal Depressive Symptoms ◽  
Avoidant Attachment

This study examined maternal depressive symptoms, social support, parenting, and adult attachment as mediators explaining the relation between maternal childhood maltreatment and child behavior in offspring. We assessed a community sample of 96 mother–child dyads. At child age 16 months, mothers self-reported maltreatment history, adult attachment, depressive symptoms, and social support, and maternal sensitivity was assessed via 2 hr of direct behavioral observation. Maternal reports of child behavior were collected at 5 years. Single and parallel mediation models were constructed. Only maternal depressive symptoms mediated the relation between maternal maltreatment history and children’s internalizing problems. Maternal sensitivity emerged as a suppressor variable. With respect to the relation between maternal maltreatment history and children’s externalizing problems, when entered singly, maternal depressive symptoms, social support, and avoidant attachment emerged as mediators. When examined in parallel, only maternal depressive symptoms and avoidant attachment accounted for unique mediating variance. Findings have implications with respect to important maternal factors that might be targeted to reduce the probability of maladaptive child behavior.

scholarly journals Confirmatory Factor Analysis of the Depression, Anxiety, and Stress Scale amongst Indian Adults

2020 ◽  
Author(s):  
Manoj Kumar Sharma ◽  
David John Hallford ◽  
Nitin Anand
Keyword(s):  
Psychological Distress ◽  
Factor Model ◽  
Community Sample ◽  
Mental Health Research ◽  
Emotional States ◽  
Strongly Correlated ◽  
Confirmatory Factor Analyses ◽  
Stress Scale ◽  
Confirmatory Factor ◽  
General Psychological Distress

Background: The Depression, Anxiety, and Stress Scale (DASS) is a widely used measure of negative emotional states. While the DASS is increasingly used in mental health research in India, to date no study has examined the factor structure among Indian adults. Methods: A large community sample of English-speaking Indian adults completed the DASS 21-item version, and confirmatory factor analyses were conducted. Results: The results indicated a good fit for a three factor (depression, anxiety, and stress) and a one-factor model (general psychological distress). There was no substantial difference between the fit of the models, and the DASS subscales were very strongly correlated with one another (r ≥ .80). Conclusion: The findings from this sample suggest that the DASS-21 items appear to assess general psychological distress, with little evidence that the items assess three distinct subscales.

scholarly journals Profiling Suicide Exposure Risk Factors for Psychological Distress: An Empirical Test of the Proposed Continuum of Survivorship Model

2021 ◽  
Vol 12 ◽  
Author(s):  
Navjot Bhullar ◽  
Rebecca L. Sanford ◽  
Myfanwy Maple
Keyword(s):  
Risk Factors ◽  
Psychological Distress ◽  
Latent Profile Analysis ◽  
Community Sample ◽  
Exposure Risk ◽  
Suicide Death ◽  
Proposed Model ◽  
Survivorship Model ◽  
The Continuum

The Continuum of Survivorship proposes a way in which individuals may experience the suicide death of someone known to them along a continuum from being exposed to the death through to long-term bereavement. The present study provides a first empirical testing of the proposed model in an Australian community sample exposed to suicide. Using a Latent Profile Analysis, we tested the suicide exposure risk factors (time since death, frequency of pre-death contact, reported closeness, and perceived impact) to map to the Continuum of Survivorship model. Results revealed identification of five profiles, with four ranging from suicide exposed to suicide bereaved long-term broadly aligning with the proposed model, with one further profile being identified that represented a discordant profile of low closeness and high impact of suicide exposure. Our findings demonstrate that while the proposed model is useful to better understand the psychological distress related to exposure to suicide, it cannot be used as “shorthand” for identifying those who will be most distressed, nor those who may most likely need additional support following a suicide death. Implications and future research directions are discussed.

scholarly journals Subtyping psychological distress in the population: a semi-parametric network approach

2019 ◽  
Vol 29 ◽  
Author(s):  
S. de Vos ◽  
S. Patten ◽  
E. C. Wit ◽  
E. H. Bos ◽  
K. J. Wardenaar ◽  
...  
Keyword(s):  
Psychological Distress ◽  
Community Sample ◽  
A Priori ◽  
Network Models ◽  
Optimal Choice ◽  
Data Driven ◽  
Network Density ◽  
Parametric Network ◽  
Distress Scale ◽  
Non Parametric

Abstract Aims The mechanisms underlying both depressive and anxiety disorders remain poorly understood. One of the reasons for this is the lack of a valid, evidence-based system to classify persons into specific subtypes based on their depressive and/or anxiety symptomatology. In order to do this without a priori assumptions, non-parametric statistical methods seem the optimal choice. Moreover, to define subtypes according to their symptom profiles and inter-relations between symptoms, network models may be very useful. This study aimed to evaluate the potential usefulness of this approach. Methods A large community sample from the Canadian general population (N = 254 443) was divided into data-driven clusters using non-parametric k-means clustering. Participants were clustered according to their (co)variation around the grand mean on each item of the Kessler Psychological Distress Scale (K10). Next, to evaluate cluster differences, semi-parametric network models were fitted in each cluster and node centrality indices and network density measures were compared. Results A five-cluster model was obtained from the cluster analyses. Network density varied across clusters, and was highest for the cluster of people with the lowest K10 severity ratings. In three cluster networks, depressive symptoms (e.g. feeling depressed, restless, hopeless) had the highest centrality. In the remaining two clusters, symptom networks were characterised by a higher prominence of somatic symptoms (e.g. restlessness, nervousness). Conclusion Finding data-driven subtypes based on psychological distress using non-parametric methods can be a fruitful approach, yielding clusters of persons that differ in illness severity as well as in the structure and strengths of inter-symptom relationships.

scholarly journals Should Psychological Distress Screening in the Community Account for Self-Perceived Health Status?

2009 ◽  
Vol 54 (8) ◽  
pp. 526-533 ◽  
Author(s):  
Norbert Schmitz ◽  
Alain Lesage ◽  
JianLi Wang
Keyword(s):  
Mental Health ◽  
Psychological Distress ◽  
Health Status ◽  
Sensitivity And Specificity ◽  
Community Sample ◽  
Strong Association ◽  
Perceived Health ◽  
Well Being ◽  
Perceived Health Status ◽  
Screening Performance

Objective: Psychological distress questionnaires are often used as screening instruments for mental disorders in clinical and epidemiologic settings. Poor physical health may affect the screening properties of a questionnaire. We evaluate the effect of self-perceived health status on the screening performance of the Kessler K10 and K6 scales in a community sample. Methods: We used data from the Canadian Community Health Survey: Mental Health and Well-Being (CCHS 1.2). Psychological distress was measured by the 6–item (K6) and the 10–item (K10) Kessler instrument. Depression and anxiety disorders were assessed using the World Mental Health Composite International Diagnostic Interview (1–month estimates). Optimal cut-off points regarding health status were determined by finding the K6 and K10 values that allowed for the best balance between sensitivity and specificity. Stratum-specific likelihood ratios (SSLRs) were computed to define strata with discriminating power. Results: There was a strong association between the screening performance of the K6 and K10 scales and self-perceived health status: for the K10 scale, a cut-off point of 5/6 yielded the best balance between sensitivity and specificity for subjects with excellent or very good health status, while a cut-off point of 14/15 yielded the best balance between sensitivity and specificity for subjects with poor health status. Conclusions: The combination of the K6 and K10 scales, with a self-rated health status item, may improve screening properties of the 2 scales.

Predicting loneliness in old people living in the community

2009 ◽  
Vol 19 (1) ◽  
pp. 53-60 ◽  
Author(s):  
Constança Paúl ◽  
Oscar Ribeiro
Keyword(s):  
Psychological Distress ◽  
Social Network ◽  
Social Relationships ◽  
Human Life ◽  
Community Sample ◽  
Health Condition ◽  
Psychological Interventions ◽  
Old People ◽  
General Health Condition ◽  
Core Concepts

SummaryLoneliness and social isolation are two core concepts regarding social relationships in human life that are particularly relevant in old age. This article focuses on the prevalence of loneliness in a community sample of 1266 autonomous people aged 50 or more and on the structural circumstances (demographic social network and general health condition) that could better contribute to its experience. The prevalence of loneliness was 16.3% (n = 206) and a small number of people presented low social network (7%). Predictors of loneliness (explaining 29% of variance) were being widowed, perceiving own health as poor or very poor, and having psychological distress and cognitive impairment. The authors emphasize the importance of psychological distress as a predictor of loneliness and the need for social and psychological interventions to prevent its consequences in morbidity and mortality.

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