scholarly journals Depression predicts chronic pain interference in racially-diverse, low-income patients

2021 ◽  
Author(s):  
Benjamin C Nephew ◽  
Angela C Incollingo Rodriguez ◽  
Veronica Melican ◽  
Justin J Polcari ◽  
Kathryn E Nippert ◽  
...  
Keyword(s):  
Machine Learning ◽  
Clinical Trial ◽  
Chronic Pain ◽  
Low Income ◽  
Pain Interference ◽  
Medical Group ◽  
Regression Analyses ◽  
Racially Diverse ◽  
Group Visits ◽  
Predictive Relationship

ABSTRACT Background Chronic pain is one of the most common reasons adults seek medical care in the US, with estimates of prevalence ranging from 11% to 40%. Mindfulness meditation has been associated with significant improvements in pain, depression, physical and mental health, sleep, and overall quality of life. Group medical visits are increasingly common and are effective at treating myriad illnesses including chronic pain. Integrative Medical Group Visits (IMGV) combine mindfulness techniques, evidence based integrative medicine, and medical group visits and can be used as adjuncts to medications, particularly in diverse underserved populations with limited access to non-pharmacological therapies. Objective and Design The objective of the present study was to use a blended analytical approach of machine learning and regression analyses to evaluate the potential relationship between depression and chronic pain in data from a randomized clinical trial of IMGV in socially diverse, low income patients suffering from chronic pain and depression. Methods This approach used machine learning to assess the predictive relationship between depression and pain and identify and select key mediators, which were then assessed with regression analyses. It was hypothesized that depression would predict the pain outcomes of average pain, pain severity, and pain interference. Results Our analyses identified and characterized a predictive relationship between depression and chronic pain interference. This prediction was mediated by high perceived stress, low pain self-efficacy, and poor sleep quality, potential targets for attenuating the adverse effects of depression on functional outcomes. Conclusions In the context of the associated clinical trial and similar interventions, these insights may inform future treatment optimization, targeting, and application efforts in racially diverse, low income populations, demographics often neglected in studies of chronic pain.

Lessons Learned and Strategies for Recruitment of Diverse, Low-income Patients into an Integrative Medical Group Visit Clinical Trial

EXPLORE ◽  
2019 ◽  
Vol 15 (3) ◽  
pp. 215-221
Author(s):  
Paula Gardiner ◽  
Anna Sophia Lestoquoy ◽  
N. Lily Negash ◽  
Man Luo ◽  
Katherine Gergen-Barnett ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Low Income ◽  
Lessons Learned ◽  
Medical Group ◽  
Group Visit

Design of the integrative medical group visits randomized control trial for underserved patients with chronic pain and depression

2017 ◽  
Vol 54 ◽  
pp. 25-35 ◽  
Author(s):  
Paula Gardiner ◽  
Anna Sophia Lestoquoy ◽  
Katherine Gergen-Barnett ◽  
Brian Penti ◽  
Laura F. White ◽  
...  
Keyword(s):  
Chronic Pain ◽  
Randomized Control Trial ◽  
Medical Group ◽  
Group Visits ◽  
Underserved Patients ◽  
Randomized Control

Predictors of Father Investment of Time and Finances: The Specificity of Resources, Relationships, and Parenting Beliefs

2017 ◽  
Vol 38 (18) ◽  
pp. 2642-2662 ◽  
Author(s):  
Tamarie A. Macon ◽  
Catherine S. Tamis-LeMonda ◽  
Natasha J. Cabrera ◽  
Karen E. McFadden
Keyword(s):  
Low Income ◽  
Father Involvement ◽  
Gender Norms ◽  
Regression Analyses ◽  
Racially Diverse ◽  
Parenting Beliefs ◽  
Financial Investment ◽  
Negatively Associated ◽  
Cognitive Activities ◽  
Multiple Domains

The present study examined multiple domains of father involvement and their correlates in a sample of 478 ethnically and racially diverse low-income fathers of 24-month-old children. Regression analyses revealed that paternal resources related to most forms of involvement: Education was related to caregiving and cognitive activities, and income was associated with financial provision. Resident fathers spent more time with their children across several activities, and father–mother disagreements were negatively associated with financial provision. Fathers who believed their role as financial provider to be highly important reported more financial provision, whereas fathers who reported investment in their children’s development to be highly important were more involved in caregiving. Fathers who endorsed traditional gender norms participated in less caregiving and cognitive activities. Findings indicate the specificity of correlates of involvement and the need to consider resources, relationships, and parenting beliefs in interventions that support fathers’ physical and financial investment in their children.

scholarly journals Good Sleep Quality Improves the Relationship Between Pain and Depression Among Individuals With Chronic Pain

2021 ◽  
Vol 12 ◽  
Author(s):  
Zoe Zambelli ◽  
Elizabeth J. Halstead ◽  
Antonio R. Fidalgo ◽  
Dagmara Dimitriou
Keyword(s):  
Chronic Pain ◽  
Sleep Quality ◽  
Sleep Problems ◽  
Pain Severity ◽  
Pain Interference ◽  
Poor Sleep ◽  
Regression Analyses ◽  
Cross Sectional Survey ◽  
The Relationship ◽  
Good Sleep

Individuals with chronic pain often experience co-existing sleep problems and depression-related states. Chronic pain, sleep problems, and depression interrelate, and have been shown to exacerbate one another, which negatively impacts quality of life. This study explored the relationships between pain severity, pain interference, sleep quality, and depression among individuals with chronic pain. Secondly, we tested whether sleep quality may moderate the relationship between pain and depression. A cross-sectional survey was completed by 1,059 adults with non-malignant chronic pain conditions (Mage 43 years, 88% identified as women) and collected measures related to pain severity, pain interference, sleep quality, and depression. Multiple regression analyses found that pain severity, pain interference, and sleep quality are all significantly associated with depression. Secondly, moderated regression analyses revealed that sleep quality moderates the relationship between pain interference and depression among individuals with chronic pain such that good sleep quality attenuates the effect of pain interference on depression, and poor sleep quality amplifies the effect of pain interference on depression. These findings suggest that sleep quality may be a relevant therapeutic target for individuals with chronic pain and co-existing depression.

scholarly journals The Role of Pain-Related Cognitions in the Relationship Between Pain Severity, Depression, and Pain Interference in a Sample of Primary Care Patients with Both Chronic Pain and Depression

Pain Medicine ◽  
2020 ◽  
Vol 21 (10) ◽  
pp. 2200-2211
Author(s):  
Elisabet Sánchez-Rodríguez ◽  
Enric Aragonès ◽  
Mark P Jensen ◽  
Catarina Tomé-Pires ◽  
Concepció Rambla ◽  
...  
Keyword(s):  
Primary Care ◽  
Chronic Pain ◽  
Pain Catastrophizing ◽  
Positive Association ◽  
Pain Severity ◽  
Pain Interference ◽  
Regression Analyses ◽  
Depression Severity ◽  
Cross Sectional ◽  
The Relationship

Abstract Objective The aims of this study were twofold: 1) to better understand the associations between pain-related cognitions and pain severity, and psychological and physical function, and 2) to determine the extent to which these cognitions function as mediators in the association between pain severity and depression in a sample of primary care adult patients with chronic pain and depression. Design Cross-sectional design. Methods Three hundred twenty-eight patients with both depression and chronic pain from primary care centers responded to measures of pain severity, pain interference, depression severity, and pain-related cognitions (including measures of catastrophizing and other pain-related beliefs). We performed three hierarchical regression analyses and two multiple regression analyses. Results The helplessness domain of pain catastrophizing was positively associated with pain severity, depression severity, and pain interference and mediated the relationship between depression and pain severity and vice versa. Beliefs about disability showed a positive association with pain severity, pain interference, and depression severity, and also mediated the relationship between pain severity and depression. Believing in a medical cure was positively associated with pain interference and negatively associated with depression; emotion beliefs were positively associated with pain severity. Conclusions These findings provide important new information about the associations between several pain-related cognitions and pain severity, depression, and pain interference and the potential mediating roles that these cognitions play in the associations between pain severity and depression in patients with both chronic pain and depression in the primary care setting.

scholarly journals Medical Group Visits: A Feasibility Study to Manage Patients with Chronic Pain in an Underserved Urban Clinic

2014 ◽  
Vol 3 (4) ◽  
pp. 20-26 ◽  
Author(s):  
Paula Gardiner ◽  
Danielle Dresner ◽  
Katherine Gergen Barnett ◽  
Ekaterina Sadikova ◽  
Robert Saper
Keyword(s):  
Chronic Pain ◽  
Feasibility Study ◽  
Medical Group ◽  
Group Visits ◽  
Urban Clinic

More than hurt feelings: The wear and tear of day-to-day discrimination in adults with chronic pain

Pain Medicine ◽  
2021 ◽  
Author(s):  
Anthony D Ong ◽  
Selin Goktas ◽  
M Carrington Reid
Keyword(s):  
Chronic Pain ◽  
Psychological Factors ◽  
The United States ◽  
Pain Interference ◽  
Regression Analyses ◽  
Cross Sectional ◽  
Functional Interference ◽  
Wear And Tear ◽  
Hurt Feelings ◽  
Everyday Discrimination

Abstract Objective To examine the extent to which self-reported experiences of discrimination are associated with pain interference among men and women with chronic non-cancer pain. Methods Data are from the Study of Midlife in the United States (MIDUS) Refresher Cohort. The analytic sample consisted of 207 adults with chronic pain (54.2 ± 12.8 years; 53.6% female) who completed the Major Experiences of Discrimination and Everyday Discrimination scales. Regression analyses examined cross-sectional relations between discrimination and pain interference. Results On average, the level of pain interference was moderate in the sample (M = 3.46, SD = 2.66; observed range 0 - 10). Approximately a third of respondents reported at least one major discriminatory event in their lifetime, while 22% reported 3 or more discriminatory lifetime events. Everyday discrimination scores averaged 14.19 ± 5.46 (observed range 0 - 33). Adjusting for sociodemographics, physical health, cognitive and psychological factors, social isolation, and loneliness, everyday discrimination was associated with increased pain interference (B = .099; 95% confidence interval [CI], .02 to .17). Conclusion These findings add weight to the importance of day-to-day experiences of interpersonal discrimination by documenting independent associations with functional interference in adults with chronic pain.

scholarly journals Identifying Urban Poverty Using High-Resolution Satellite Imagery and Machine Learning Approaches: Implications for Housing Inequality

Land ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 648
Author(s):  
Guie Li ◽  
Zhongliang Cai ◽  
Yun Qian ◽  
Fei Chen
Keyword(s):  
Machine Learning ◽  
High Resolution ◽  
Satellite Imagery ◽  
Low Income ◽  
Urban Poverty ◽  
Image Features ◽  
Housing Affordability ◽  
Learning Approaches ◽  
Housing Inequality ◽  
High Resolution Satellite Imagery

Enriching Asian perspectives on the rapid identification of urban poverty and its implications for housing inequality, this paper contributes empirical evidence about the utility of image features derived from high-resolution satellite imagery and machine learning approaches for identifying urban poverty in China at the community level. For the case of the Jiangxia District and Huangpi District of Wuhan, image features, including perimeter, line segment detector (LSD), Hough transform, gray-level cooccurrence matrix (GLCM), histogram of oriented gradients (HoG), and local binary patterns (LBP), are calculated, and four machine learning approaches and 25 variables are applied to identify urban poverty and relatively important variables. The results show that image features and machine learning approaches can be used to identify urban poverty with the best model performance with a coefficient of determination, R2, of 0.5341 and 0.5324 for Jiangxia and Huangpi, respectively, although some differences exist among the approaches and study areas. The importance of each variable differs for each approach and study area; however, the relatively important variables are similar. In particular, four variables achieved relatively satisfactory prediction results for all models and presented obvious differences in varying communities with different poverty levels. Housing inequality within low-income neighborhoods, which is a response to gaps in wealth, income, and housing affordability among social groups, is an important manifestation of urban poverty. Policy makers can implement these findings to rapidly identify urban poverty, and the findings have potential applications for addressing housing inequality and proving the rationality of urban planning for building a sustainable society.

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