Monica Dimambro
Biographic Data
| ID | 9772814 |
|---|---|
| NAME | Monica Dimambro |
| GIVEN NAMES | Monica |
| FAMILY NAME | Dimambro |
| SIGNATURE | DIMAMBRO M |
| AFFILIATIONS | White River Junction VA Medical Center |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2026 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Evaluating chaplaincy utilization in a suicide-risk-stratified Veterans Affairs patient sample
Although chaplaincy is a key part of the Department of Veterans Affairs' (VA) healthcare services, few studies have investigated how classified suicide risk impacts this service utilization. Filling this gap, this study evaluates utilization patterns in a suicide-risk-stratified national sample of VA patients who died by suicide (cases), as well as suicide risk-matched patients (controls) who did not die by suicide in 2017-2018. Given overdispers…
Using natural language processing to inform targeted rural and urban Hispanic U.S. Department of Veterans Affairs suicide prediction models
Objective: Rural Hispanic Veterans experience elevated suicide rates when compared to urban counterparts. Group differences remain poorly understood. This study evaluates a rurality-stratified sample of Hispanic Veterans Affairs (VA)-patients, leveraging unstructured electronic health record (EHR) data to refine population-specific suicide risk prediction metrics. Method: The study utilized a rural and urban Hispanic VA-patient dataset, including…
No prominent works on this page.
Evaluating chaplaincy utilization in a suicide-risk-stratified Veterans Affairs patient sample
Although chaplaincy is a key part of the Department of Veterans Affairs' (VA) healthcare services, few studies have investigated how classified suicide risk impacts this service utilization. Filling this gap, this study evaluates utilization patterns in a suicide-risk-stratified national sample of VA patients who died by suicide (cases), as well as suicide risk-matched patients (controls) who did not die by suicide in 2017-2018. Given overdispers…
Using natural language processing to inform targeted rural and urban Hispanic U.S. Department of Veterans Affairs suicide prediction models
Objective: Rural Hispanic Veterans experience elevated suicide rates when compared to urban counterparts. Group differences remain poorly understood. This study evaluates a rurality-stratified sample of Hispanic Veterans Affairs (VA)-patients, leveraging unstructured electronic health record (EHR) data to refine population-specific suicide risk prediction metrics. Method: The study utilized a rural and urban Hispanic VA-patient dataset, including…
Suicide and Self-Harm Studies (2 works) · Veterans Affairs (2 works) · Human Factors and Ergonomics (1 work) · Injury prevention (1 work) · Machine Learning in Healthcare (1 work) · MEDLINE (1 work) · Mental Health Treatment and Access (1 work) · Mental Health via Writing (1 work) · Occupational safety and health (1 work) · Pastoral care (1 work)