Developing programs to support low-income married couples requires an accurate understanding of the challenges they face. To address this question, we assessed the salience and severity of relationship problems by asking 862 Black, White, and Latino newlywed spouses (N = 431 couples) living in low-income neighborhoods to (a) free list their 3 biggest sources of disagreement in the marriage, and (b) rate the severity of the problems appearing on a standard relationship problem inventory. Comparing the 2 sources of information revealed that, although relational problems (e.g., communication and moods) were rated as severe on the inventory, challenges external to the relationship (e.g., children) were more salient in the free listing task. The pattern of results is robust across couples of varying race/ethnicity, parental status, and income levels. We conclude that efforts to strengthen marriages among low-income couples may be more effective if they address not only relational problems, but also couples' external stresses by providing assistance with child care, finances, or job training.
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http://dx.doi.org/10.1037/fam0000158 | DOI Listing |
Biomed Phys Eng Express
January 2025
Department of Ophthalmology, Hospital Universitario de Canarias, Carretera Ofra S/N, La Laguna, Santa Cruz de Tenerife, 38320, SPAIN.
This paper systematically evaluates saliency methods as explainability tools for convolutional neural networks trained to diagnose glaucoma using simplified eye fundus images that contain only disc and cup outlines. These simplified images, a methodological novelty, were used to relate features highlighted in the saliency maps to the geometrical clues that experts consider in glaucoma diagnosis. Despite their simplicity, these images retained sufficient information for accurate classification, with balanced accuracies ranging from 0.
View Article and Find Full Text PDFEur J Neurosci
January 2025
Department of Psychology, University of Georgia, Athens, Georgia, USA.
Resting-state functional connectivity analyses have been used to examine synchrony in neural networks in substance use disorders (SUDs), with the default mode network (DMN) one of the most studied. Prior research has generally found less DMN synchrony during use and greater synchrony during cessation, although little research has utilized this method with opioid use. This study examined resting brain activity in treatment-seeking persons who use opioids at two points-when using opioids and when opioid-free-to determine whether the DMN exhibits different levels of connectivity during opioid use and cessation and whether differences in connectivity predict subsequent relapse.
View Article and Find Full Text PDFBehav Sci (Basel)
November 2024
Children's Specialized Hospital-Rutgers University Center for Autism Research, Education, and Services (CSH-RUCARES), Somerset, NJ 08873, USA.
For some individuals, rates of destructive behavior change in a predictable manner, irrespective of the contingencies programmed. Identifying such cyclical patterns can lead to better prediction of destructive behavior and may allow for the identification of relevant biological processes. However, identifying cyclical patterns of behavior can be difficult when using traditional methods of visual analysis.
View Article and Find Full Text PDFPsychiatry Res Neuroimaging
December 2024
Department of Electrical Engineering, Eindhoven University of Technology, Groene Loper 19, 5612 AE, Eindhoven, Netherlands; Department of Research and Development, Epilepsy Centre Kempenhaeghe, Sterkselseweg 65, 5590 AB, Heeze, Netherlands.
Research Purpose: Subjective clinical decision-making in major depressive disorder (MDD) may result in low treatment effectiveness. This study aims to identify objective predictors of MDD outcome using resting-state functional MRI scans, acquired from 25 MDD patients at baseline. Over a year, patients were assessed every 3 months, labeled as positive or negative outcome (change in depression severity).
View Article and Find Full Text PDFPsychoradiology
November 2024
Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.
Background: The lack of clearly defined neuromodulation targets has contributed to the inconsistent results of real-time fMRI-based neurofeedback (rt-fMRI-NF) for the treatment of chronic pain. Functional neurosurgery (funcSurg) approaches have shown more consistent effects in reducing pain in patients with severe chronic pain.
Objective: This study aims to redefine rt-fMRI-NF targets for chronic pain management informed by funcSurg studies.
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