| Literature DB >> 34405198 |
Luz M Garcini1, Ryan Daly2, Nellie Chen3, Justin Mehl4, Tommy Pham4, Thuy Phan5, Brittany Hansen4, Aishwarya Kothare4.
Abstract
This study reviewed the methodology and findings of 44 peer-reviewed studies on psychosocial risk factors associated with mental health outcomes among undocumented immigrants (UIs) in the United States. Findings showed a considerable advancement over the past seven years in the methods and measures used in the included studies. Nonetheless, there is a need for continued methodological rigor, innovative study designs, greater diversity of samples, and in-depth exploration of constructs that facilitate resilience. Identifying avenues to reduce risk in this population is essential to inform intervention and advocacy efforts aimed at overcoming distress from the current U.S. anti-immigrant and socio-political climate.Entities:
Keywords: Immigrant; Latinxs; Mental health; Stress; Undocumented
Year: 2021 PMID: 34405198 PMCID: PMC8352099 DOI: 10.1016/j.jmh.2021.100058
Source DB: PubMed Journal: J Migr Health ISSN: 2666-6235
Fig. 1Summary of article screening and eligibility
Study design characteristics
| Quantitative Studies | ||||||
|---|---|---|---|---|---|---|
| Study | Study Design | Recruitment | Mode of Data Collection | Data Source | Year of Data Collection & Location | Response/ Retention/ Cooperation Rate |
| Beatrice et al., 2016 ( | Retrospective | Existing records | Existing records | Secondary (Pima County Office of Medical Examiner) | NR Southwest & Central U.S. | NR |
| Berger Cardoso et al., 2016 ( | Longitudinal | RDS | Face to face individual interviews | Secondary (Recent Latino Immigrant Study) | NR Southeast U.S. | 91%* |
| Cano et al., 2017 ( | Cross-sectional | RDS | Face to face individual interviews | Primary | NR Southeast U.S. | NR |
| Cerezo et al., 2016 ( | Cross-sectional | Community events | Face to face individual interviews & internet | Primary | NR Southwest U.S. | 60% |
| Cesario et al., 2014 ( | Prospective | Legal centers & shelters | Face to face individual interviews | Primary | NR Midwest U.S. | 96%* |
| Cobb et al., 2016 ( | Cross-sectional | Churches & community venues | Face to face individual interviews | Primary | NR Midwest U.S. | NR |
| Cobb et al., 2017 ( | Cross-sectional | Churches & community venues | Face to face individual interviews | Primary | NR Midwest U.S. | NR |
| Cobb et al., 2019 ( | Cross-sectional | Churches & community venues | Face to face individual interviews | Primary | 2016 Midwest U.S. | NR |
| Cyrus et al., 2015 ( | Prospective Longitudinal | RDS | Face to face individual interviews | Secondary | NR Southeast U.S. | 90%* |
| DaSilva et al., 2017 ( | Cross-sectional | RDS | Face to face individual interviews | Secondary | NR Southeast U.S. | NR |
| Dillon et al., 2018 ( | Cross-sectional | Community centers, social media & health fairs | Face to face individual interviews | Primary | 2014 Southeast U.S. | NR |
| Finno-Velasquez et al., 2016 ( | Cross-sectional | Child welfare agency records | Face to face individual interviews | Secondary (National Survey of Child & Adolescent Wellbeing) | 2009 Nationwide | 35% |
| Galvan et al., 2015 ( | Cross-sectional | Randomly from day labor sites | Face to face individual interviews | Primary | 2012 Southwest U.S. | 35% |
| Garcini, Peña, Gutierrez et al., 2017 ( | Cross-sectional | RDS | Face to face individual interviews | Primary | 2015 Southwest U.S. | NR |
| Garcini, Peña, Galvan et al., 2017 ( | Cross-sectional | RDS | Face to face individual interviews | Primary | 2015 Southwest U.S. | NR |
| Garcini, Renzaho et al., 2018 ( | Cross-sectional | Stratified Sampling from neighborhoods | Face to face individual interviews | Secondary (San Diego Prevention Community Survey) | 2009 Southwest U.S. | 23% |
| Garcini, Chen et al., 2018 ( | Cross-sectional | RDS | Face to face individual interviews | Primary | 2015 Southwest U.S. | NR |
| Hainmueller et al., 2017 ( | Cross-sectional | Existing records | Existing records | Secondary (Medicaid Claims Oregon Health Authority) | 2003-2015 Northwest U.S. | N/A |
| Lee et al., 2019 ( | Cross-sectional | Door to door recruitment in randomly selected zones | Face to face individual interviews | Primary | 2017 Northeast U.S. | NR |
| Levitt et al., 2019 ( | Longitudinal | RDS | Face to face individual interviews | Secondary (The Recent Latino Immigrant Study) | 2008-2010 Southeast U.S. | NR |
| Organista et al., 2019 ( | Cross-sectional | Day Laborer sites & Businesses | Internet survey | Primary | 2014 Southwest U.S. | 100% |
RDS = Respondent Driven Sampling; CR=Cooperation rate; NS=Not specified; NR=Not reported
*Retention rate
Participant Characteristics
| Quantitative Studies | ||||
|---|---|---|---|---|
| Study | Total sample size% UIs | Characteristics of UIs*(Age, Sex, Race/Ethnicity) | Socio-economic Status (Income, Education) | Setting |
| Beatrice et al., 2016 ( | Mean Age= NR ( | Income: NR | Rural | |
| Berger Cardoso et al., 2016 ( | Mean Age= 27.0 years ( | Income: $ 5,042 Mean Annual | Urban & Rural | |
| Cano et al., 2017 ( | Mean Age= 27.0 years ( | Income: NR | Urban | |
| Cerezo et al., 2016 ( | Mean Age= 30.9 years ( | Income: NR | NR | |
| Cesario et al., 2014 ( | Mean Age= 32.9 years ( | Income: NR | Urban | |
| Cobb et al., 2016 ( | Mean Age= 33.7 years ( | Income: NR | Urban | |
| Cobb et al., 2017 ( | Mean Age= 34.8 years ( | Income: $ 28,785 Mean Annual | Urban | |
| Cobb et al., 2019 ( | Mean Age= 34.8 years ( | Income: $ 28,785 Mean Annual | NR | |
| Cyrus et al., 2015 ( | Mean Age= 27.4 years ( | Income: $ 10,117 Mean Annual | NR | |
| DaSilva et al., 2017 ( | Mean Age= 28.8 years ( | Income: NR | NR | |
| Dillon et al., 2018 ( | Mean Age= 20.8 years ( | Income: NR | NR | |
| Finno-Velasquez et al., 2016 ( | Mean Age= 32.2 years ( | Income: NR | Urban & Rural | |
| Galvan et al., 2015 ( | Mean Age= 38.5 years ( | Income: 70% < $10,000 year | Urban | |
| Garcini, Peña, Gutierrez et al., 2017 ( | Mean Age= 38.0 years ( | Income: 66% < $24,000 year | Urban | |
| Garcini, Peña, Galvan et al., 2017 ( | Mean Age= 38.0 years ( | Income: 66% < $24,000 year | Urban | |
| Garcini, Renzaho et al., 2018 ( | Mean Age= 43.7 years ( | Income: NR | Urban | |
| Garcini, Chen et al., 2018 ( | Mean Age= 38.0 years ( | Income: 66% < $ 24,000 year | Urban | |
| Hainmueller et al., 2017 ( | Mean Age= NR ( | Income: NR | NR | |
| Lee et al., 2019 ( | Mean Age= 38.0 ( | Income: 76% < $ 29,000 year | Urban | |
| Levitt et al., 2019 ( | Mean Age= 27.0 ( | Income: NR | NR | |
| Organista et al., 2019 ( | Mean Age= 40.5 ( | Income: NR | Urban | |
| Patler et al., 2017 ( | Mean Age= 24.2 ( | Income: NR | NR | |
| Rodriguez et al., 2017 ( | Mean Age= NR ( | Income: NR | NR | |
| Rodriguez et al., 2019 ( | Mean Age= NR ( | Income: NR | Urban | |
| Romano et al., 2016 ( | Mean Age= NR ( | Income: NR | Urban | |
| Ross et al., 2019 ( | Mean Age= NR ( | Income: 55.3% < $ 30,000 year | Urban | |
| Sanchez et al., 2016 ( | Mean Age= 31.8 ( | Income: $ 19,962 Mean Annual | NR | |
| Young et al., 2017 ( | Mean Age= 37.4 years ( | Income: NR | Urban | |
| Zapata et al., 2017 ( | Mean Age= 37.3 ( | Income: NR | NR | |
NR= Not reported
Fig. 2Themes and outcomes of interest in the included studies
Stress disorders including PTSD, acute stress disorder, adjustment disorder.
Other including Health Related Quality of Life (HRQoL), shame, despair