Evaluation of neighborhood resources and mental health in American military Veterans using geographic information systems

Park, Young S.; Wyman, Jean F.; McMorris, Barbara J.; Pruinelli, Lisiane; Song, Ying; Kaas, Merrie J.; Sherman, Scott E.; Fu, Steven S.

doi:10.1016/j.pmedr.2021.101546

Cited by 3 publications

(4 citation statements)

References 42 publications

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“…Studies have found a strong correlation between area deprivation and poor mental health outcomes, such as depression and anxiety. 14,31 Factors that contribute to this correlation include limited access to mental health services, social isolation, financial stress, and exposure to violence and crime. Living in an area with a high ADI can also lead to increased levels of chronic stress, which can negatively affect mental health.…”

Section: Discussionmentioning

confidence: 99%

Use of Area Deprivation Index to Predict Minimal Clinically Important Difference for Patient Reported Outcomes Measurement Information System After Arthroscopic Rotator Cuff Repair

et al. 2023

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Background: Socioeconomic disparities correlate with worse outcomes after arthroscopic rotator cuff repair. However, use of a surrogate to describe socioeconomic disadvantage has been a challenge. The Area Deprivation Index (ADI) is a tool that encompasses 17 socioeconomic variables into a single metric based on census location. Hypothesis: Higher ADI would result in a worse minimal clinically important difference (MCID) for the Patient Reported Outcomes Measurement Information System (PROMIS) and have less improvement in range of motion (ROM) following arthroscopic rotator cuff repair (ARCR). Study Design: Cohort study; Level of evidence, 3. Method: A retrospective review was performed for patients who underwent arthroscopic rotator cuff repair. Patients in the most socioeconomically disadvantaged quartile (ADIHigh) were compared with the least disadvantaged quartile (ADILow) in the ability to reach MCID. Demographic and surgical features were assessed for attainment of MCID. Results: In total 1382 patients were identified who underwent ARCR, of which a total of 306 patients met final inclusion criteria. A higher percentage of patients within the ADIHigh cohort identified as “Black” or “other” race and had government-issued insurance compared with the ADILow cohort ( P < .05). The ADIHigh cohort had significantly worse postoperative forward flexion compared with the ADILow cohort (145.0°± 32.5° vs 156.3°± 23.4°; P = .001) despite starting with comparable preoperative ROM ( P = .17). Logistic regression showed that ADI was the only variable significant for predicting achievement of MCID for all 3 PROMIS domains, with the ADIHigh cohort having significantly worse odds of achieving MCID Physical Function (odds ratio [OR], 0.31; P = .001), Pain Interference (OR, 0.21; P = .001), and Depression (OR, 0.28; P = .001). Meanwhile, age, sex, body mass index, and smoking history were nonsignificant. Moreover, “other” for race and Medicare insurance were significant for achievement of MCID Depression but not Physical Function or Pain Interference. Finally, ADI was the main feature for predictive logistic regression modeling. Conclusion: ADI served as the only significant predictor for achieving MCID for all 3 PROMIS domains after arthroscopic rotator cuff repair. Patients who face high levels of socioeconomic disadvantage have lower rates of achieving MCID. In addition, patients with greater neighborhood disadvantage demonstrated significantly worse improvement in active forward flexion. Further investigation is required to understand the role of ADI on physical therapy compliance and to identify the barriers that prevent equitable postoperative care.

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Section: Discussionmentioning

confidence: 99%

Use of Area Deprivation Index to Predict Minimal Clinically Important Difference for Patient Reported Outcomes Measurement Information System After Arthroscopic Rotator Cuff Repair

et al. 2023

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“…At the broader environmental level, resilience training and mental health screenings with access to mental health treatment provided by the military can also influence outcomes (Britt et al., 2013). Neighbourhood‐level social determinants (e.g., living in alcohol‐permissive neighbourhood) are increasingly recognised as influencing mental health (Park et al., 2021) and may have important implications for the resilience of MSMs.…”

Section: Conceptualising Resilience In a Military Contextmentioning

confidence: 99%

A dynamic, multilevel approach to conceptualising and designing resilience research in the context of military stress

Polusny

Erbes

2023

Stress and Health

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Challenges in conceptualising resilience have impeded advancements in resilience science. In response, the National Institutes of Health (NIH) developed a general framework for harmonising the conceptualisation of resilience as a dynamic process determined by multiple systems and levels of analysis. Consistent with the NIH Resilience Framework, this paper presents a conceptual model of resilience applied to military service members. This model encompasses four core components necessary for resilience research: (1) the presence of significant challenge, (2) successful adaptation in response to the challenge, (3) the capacity for resilience (i.e., protective factors), and (4) the processes (i.e., mechanisms) by which protective factors exert positive effects on an individual's response. Guided by this conceptual model, we outline key methodological recommendations to advance resilience research and illustrate each using the Advancing Research on Mechanisms of Resilience study as an exemplar. We emphasise the need for future research to examine resilience as a dynamic process and apply a multilevel approach. We hope to provide a basic road map to those interested in improving the rigour of future research on resilience in a military context, the results of which can inform the development of interventions.

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“…Public health experts and policymakers use SV to identify neighborhoods requiring additional resources to reduce their risk of experiencing negative physical health outcomes . SVs have more recently been used to study community mental health (MH) and substance use disorders (SUDs) . Because SV is often context dependent, empirical research is needed to guide selection of SV indices to inform community-level interventions.…”

Section: Introductionmentioning

confidence: 99%

“…6 SVs have more recently been used to study community mental health (MH) and substance use disorders (SUDs). [7][8][9][10][11][12][13] Because SV is often context dependent, empirical research is needed to guide selection of SV indices to inform community-level interventions.…”

mentioning

confidence: 99%

Social Vulnerability and Prevalence and Treatment for Mental Health and Substance Use Disorders

Gibbons,

Olfson,

Saulsberry

et al. 2024

JAMA Psychiatry

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ImportanceCommunity-level social vulnerability (SV) is associated with physical illness and premature mortality. Its association with mental health (MH) and substance use disorders (SUDs) needs further study.ObjectiveTo study associations of SV with clinical diagnoses of MH disorders, SUDs, and related treatments in the US noninstitutionalized population of adults aged 18 years and older.Design, Setting, and ParticipantsA survey of adults in a national sample of US households between October 2020 and October 2022. Participants drawn from a multistage, clustered, and stratified area probability sample of US households were included, excluding adults older than 65 years because of the difficulty of differentiating mental disorders from symptoms of dementia. The sample also included adults living in prisons, state psychiatric hospitals, and homeless shelters who were excluded from the sample of US households used in these analyses. Each sample household was sent a letter explaining the study and offering the option to complete the household roster online, by phone, or by email. Of the 12 906 adults selected for clinical interviewing in the household sample, 4674 completed clinical interviews.Main Outcomes and MeasuresMain outcomes were Structured Clinical Interview for DSM-5 past-year diagnoses of MH disorders and SUDs and responses to survey questions regarding treatment received. The Social Vulnerability Metric (SVM) and the Area Deprivation Index (ADI) were used to determine SV at the residential zip code level.ResultsThe analysis involved 4674 participants (2904 [62.13%] female and 1770 [37.87%] male; mean [SD] age, 41.51 [13.41] years). Controlling for measured confounders, the SVM was significantly associated with diagnoses of schizophrenia spectrum disorder (SSD; adjusted odds ratio [aOR], 17.22; 95% CI, 3.05-97.29), opioid use disorder (OUD; aOR, 9.47; 95% CI, 2.30-39.02), stimulant use disorder (aOR, 6.60; 95% CI, 2.01-21.67), bipolar I disorder (aOR, 2.39; 95% CI, 1.19-4.80), posttraumatic stress disorder (aOR, 1.63; 95% CI, 1.06-2.50), and any MH disorder (aOR, 1.44; 95% CI, 1.14-1.83), but not major depressive disorder (MDD), generalized anxiety disorder (GAD), or any SUD. Results were similar for the ADI but generally of lower magnitude (SSD aOR, 11.38; 95% CI, 1.61-80.58; OUD aOR, 2.05; 95% CI, 0.30-14.10; stimulant use disorder aOR, 2.18; 95% CI, 0.52-9.18). Among participants with SSDs, SV was associated with reduced MH treatment (aOR, 0.001; 95% CI, 0.00-0.18) and reduced SUD treatment in participants with OUD or stimulant use disorder (aOR, 0.24; 95% CI, 0.02-2.80).Conclusions and RelevanceIn contrast to previous studies using nonclinical symptom-based survey data, we found no association between SV and GAD or MDD. By contrast, there were associations of SV with prevalence of SSD, stimulant use disorder, and OUD with corresponding decreases in treatment. These results suggest that the SVM might assist in developing more comprehensive care models that integrate medical and social care for MH disorders and SUDs.

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Evaluation of neighborhood resources and mental health in American military Veterans using geographic information systems

Abstract: Highlights Four meaningful neighborhood resource groups were identified by clustering. Living in alcohol-permissive/tobacco-restrictive neighborhoods had negative impacts. Place of residence and distance to the closest VA care facility were not significant.

Cited by 3 publications

References 42 publications

Use of Area Deprivation Index to Predict Minimal Clinically Important Difference for Patient Reported Outcomes Measurement Information System After Arthroscopic Rotator Cuff Repair

Use of Area Deprivation Index to Predict Minimal Clinically Important Difference for Patient Reported Outcomes Measurement Information System After Arthroscopic Rotator Cuff Repair

A dynamic, multilevel approach to conceptualising and designing resilience research in the context of military stress

Social Vulnerability and Prevalence and Treatment for Mental Health and Substance Use Disorders

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