Depressive Symptoms in Low-Income, Urban Adolescents: Cognitive and Contextual Factors

Background: Prior network analyses demonstrated that the death of a loved one potentially precedes specific depression symptoms, primarily loneliness, which in turn links to other depressive symptoms. In this study, we extend prior research by comparing depression symptom network structures following two types of marital disruption: bereavement versus separation. Methods: We fitted two Gaussian Graphical Models to cross-sectional data from a Swiss survey of older persons (145 bereaved, 217 separated, and 362 married controls), and compared symptom levels across bereaved and separated individuals. Results: Separated compared to widowed individuals were more likely to perceive an unfriendly environment and oneself as a failure. Both types of marital disruption were linked primarily to loneliness, from where different relations emerged to other depressive symptoms. Amongst others, loneliness had a stronger connection to perceiving oneself as a failure in separated compared to widowed individuals. Conversely, loneliness had a stronger connection to getting going in widowed individuals. Limitations: Analyses are based on cross-sectional between-subjects data, and conclusions regarding dynamic processes on the within-subjects level remain putative. Further, some of the estimated parameters in the network exhibited overlapping confidence intervals and their order needs to be interpreted with care. Replications should thus aim for studies with multiple time points and larger samples. Conclusions: The findings of this study add to a growing body of literature indicating that depressive symptom patterns depend on contextual factors. If replicated on the within-subjects level, such findings have implications for setting up patient-tailored treatment approaches in dependence of contextual factors.

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Maternal adverse childhood experiences and postpartum depressive symptoms in young, low-income women

Psychiatry Research ◽

10.1016/j.psychres.2020.113679 ◽

2021 ◽

Vol 296 ◽

pp. 113679

Author(s):

Sunny H. Shin ◽

Gabriela Ksinan Jiskrova ◽

Tiffany Kimbrough ◽

Karen Tabb Dina ◽

Elizabeth Overall Lee ◽

...

Keyword(s):

Depressive Symptoms ◽

Low Income ◽

Adverse Childhood Experiences ◽

Childhood Experiences ◽

Postpartum Depressive Symptoms ◽

Adverse Childhood ◽

Low Income Women

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Multiple domains of stress predict postpartum depressive symptoms in low-income Mexican American women: the moderating effect of social support

Archives of Women s Mental Health ◽

10.1007/s00737-016-0649-x ◽

2016 ◽

Vol 19 (6) ◽

pp. 1009-1018 ◽

Cited By ~ 13

Author(s):

Shayna S. Coburn ◽

N. A. Gonzales ◽

L. J. Luecken ◽

K. A. Crnic

Keyword(s):

Social Support ◽

Depressive Symptoms ◽

Low Income ◽

Mexican American ◽

Moderating Effect ◽

Mexican American Women ◽

American Women ◽

Postpartum Depressive Symptoms ◽

Multiple Domains

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Effects of a Multicomponent Life-Style Intervention on Weight, Glycemic Control, Depressive Symptoms, and Renal Function in Low-Income, Minority Patients With Type 2 Diabetes

Psychosomatic Medicine ◽

10.1097/psy.0000000000000348 ◽

2016 ◽

Vol 78 (7) ◽

pp. 851-860 ◽

Cited By ~ 9

Author(s):

Ashley E. Moncrieft ◽

Maria M. Llabre ◽

Judith Rey McCalla ◽

Miriam Gutt ◽

Armando J. Mendez ◽

...

Keyword(s):

Type 2 Diabetes ◽

Renal Function ◽

Depressive Symptoms ◽

Glycemic Control ◽

Low Income ◽

Life Style ◽

Life Style Intervention

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Depressive Symptoms and Its Associated Factors in 13-Year-Old Urban Adolescents

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph10105026 ◽

2013 ◽

Vol 10 (10) ◽

pp. 5026-5038 ◽

Cited By ~ 7

Author(s):

Cláudia Bulhões ◽

Elisabete Ramos ◽

Jutta Lindert ◽

Sónia Dias ◽

Henrique Barros

Keyword(s):

Depressive Symptoms ◽

Associated Factors ◽

Urban Adolescents

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Disparities in the use of a mHealth medication adherence promotion intervention for low-income adults with type 2 diabetes

Journal of the American Medical Informatics Association ◽

10.1093/jamia/ocv082 ◽

2015 ◽

Vol 23 (1) ◽

pp. 12-18 ◽

Cited By ~ 46

Author(s):

Lyndsay A Nelson ◽

Shelagh A Mulvaney ◽

Tebeb Gebretsadik ◽

Yun-Xian Ho ◽

Kevin B Johnson ◽

...

Keyword(s):

Type 2 Diabetes ◽

Depressive Symptoms ◽

Medication Adherence ◽

Health Literacy ◽

Low Income ◽

Mhealth Intervention ◽

Lower Health ◽

The Relationship ◽

Lower Health Literacy

Abstract Objective Mobile health (mHealth) interventions may improve diabetes outcomes, but require engagement. Little is known about what factors impede engagement, so the authors examined the relationship between patient factors and engagement in an mHealth medication adherence promotion intervention for low-income adults with type 2 diabetes (T2DM). Materials and Methods Eighty patients with T2DM participated in a 3-month mHealth intervention called MEssaging for Diabetes that leveraged a mobile communications platform. Participants received daily text messages addressing and assessing medication adherence, and weekly interactive automated calls with adherence feedback and questions for problem solving. Longitudinal repeated measures analyses assessed the relationship between participants’ baseline characteristics and the probability of engaging with texts and calls. Results On average, participants responded to 84.0% of texts and participated in 57.1% of calls. Compared to Whites, non-Whites had a 63% decreased relative odds (adjusted odds ratio [AOR] = 0.37, 95% confidence interval [CI], 0.19-0.73) of participating in calls. In addition, lower health literacy was associated with a decreased odds of participating in calls (AOR = 0.67, 95% CI, 0.46-0.99, P = .04), whereas older age ( Pnonlinear = .01) and more depressive symptoms (AOR = 0.62, 95% CI, 0.38-1.02, P = .059) trended toward a decreased odds of responding to texts. Conclusions Racial/ethnic minorities, older adults, and persons with lower health literacy or more depressive symptoms appeared to be the least engaged in a mHealth intervention. To facilitate equitable intervention impact, future research should identify and address factors interfering with mHealth engagement.

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