https://orcid.org/0000-0003-4979-6620
ABSTRACT
Background
People experiencing homelessness (PEH) are vulnerable to COVID-19 transmission due to substance use, congregate living conditions, and underlying medical conditions. Yet, little is known about factors impacting drug use disorder among PEH during COVID-19 pandemic. The purpose of this study was to identify correlates associated with substance use disorder among PEH, both those who were diagnosed with COVID-19 and those who tested negative or never tested.
Methods
A cross-sectional, structured survey was administered to PEH (N = 102) who were recruited from sheltered and unsheltered settings. Descriptive analysis, t-tests, Fisher’s exact test or chi-squared test, and bivariate and multiple linear regression were conducted.
Results
PEH with a COVID-19 diagnosis included male gender, and Latino race/ethnicity (p < .05). Moreover, substance use disorder scores (p - .037) and days on the street were negatively associated with COVID-19 (p < .001). Multivariable analyses revealed a significant positive relationship between days slept on the street and substance use disorder (p < .001), and a significant negative relationship with alcohol use (p < .05); COVID-19 remained negatively associated with substance use disorder, but it was not significant.
Conclusions
This study provides evidence about correlates of drug use disorder among PEH. More studies are needed to understand successful individual and system-level strategies for reducing drug-related problems during COVID-19.
Introduction
In Los Angeles (LA), it has been estimated that more than 41,000 people are living on the streets or in shelters at any night (Los Angeles Homeless Service Authority [LAHSA], Citation2020). As crowded housing presented a significant risk for COVID-19 among PEH, many PEH were shifted into hotel rooms to promote physical distancing and self-isolation. Some PEHs, however, continued to remain on the streets in their tents or in encampments.
Despite the strategies in place, it is estimated that in LA County, more than 9,000 PEHs have tested positive for COVID-19 since September 2021, while more than 200 PEHs who tested positive for COVID-19 have died since the beginning of the pandemic (Los Angeles County Department of Public Health [LADPH], Citation2021). Of the PEH testing positive for COVID-19, 42% identified as Latinx and 27% identified as Black. Additionally, men constituted most of the COVID-19 positive cases (66%) and deaths (82%) (LADPH, Citation2021).
It is suspected that closures and limited resources also negatively impact PEH who experience substance uses disorders through compounded stress that may lead to overconsumption of drugs and alcohol (Perri et al., Citation2020). PEHs who are in recovery may also experience greater challenges to mitigating urges to use and risk relapse (Volkow, Citation2020). In a recent study, hospitalizations and testing positive for COVID-19 have each been positively associated with opioid use disorder and history of overdose (Allen et al., Citation2021).
During periods of isolation or quarantine, persons who use opioids and are also homeless may also have experienced challenges in receiving medications for opioid addiction during COVID-19, which could result in an increase in overdoses (Perri et al., Citation2020; Volkow, Citation2020). Greater numbers of overdoses are also more likely as fewer people are available to deliver Naloxone (Volkow, Citation2020). Over the first seven months of 2020, 273 PEH died of an overdose with an estimated 33% increase from 2019. These deaths were closely related to fentanyl (Los Angeles County Department of Public Health, Center for Health Impact Evaluation, Citation2021). Overdose may also occur among persons who use opioids due to intermittent use and loss of drug tolerance over time and limited access to naloxone (Perri et al., Citation2020). In terms of alcohol use, similar challenges regarding access to alcohol were experienced during the stay-at-home mandate period.
Guiding theoretical framework
This study was guided by the Comprehensive Health Seeking and Coping Paradigm (A. Nyamathi, Citation1989), originating from a Stress and Coping (Lazarus & Folkman, Citation1984) and Health Seeking and Coping perspective (Schlotfeldt, Citation1981) to provide a biopsychosocial view of factors impacting the health of vulnerable populations. Based on the CHSCP, several constructs should be considered as factors that may impact health outcomes: in this case, use of drugs and alcohol. These include sociodemographic, environmental, and psychosocial factors. Socio-demographic Factors include age, race/ethnicity, history of substance use and current use status, county of origin, education, etc. Environmental Factors: Structural factors such as stable housing are critical to address as part of the disproportionate burden of disease among the homeless population and are defined as sheltered housing or living on the streets. Psychosocial Factors: mental distress is associated with risky behaviors, such as drug and alcohol use among PEHs (Farhoudian et al., Citation2020), and among people who use drugs, stress and crisis often trigger or exacerbate mental health issues (Wang et al., Citation2019). Among people who use substances, mental health issues, such as anxiety, depression, and irritability may be the cause for concern of drug relapse (Farhoudian et al., Citation2020).
Furthermore, lack of social support is another factor that may worsen mental health, and subsequently, increase substance use (Garfin et al., Citation2022). During COVID-19, sudden closure of drop-in services and community centers, coupled with a disruption in social relationships and support, has also led to deterioration in mental health (Perri et al., Citation2020). Several PEHs reported that social isolation exacerbated their mental illness, as social support was oftentimes unavailable (Fitzpatrick, Citation2017). In another study, adults with mental illness reported that access to social media or text messaging via personal cell phones could somewhat alleviate the feelings of loneliness during the pandemic (Costa et al., Citation2020); however, many PEHs do not have access to a working cell phone or internet.
Purpose
Currently, no studies have yet articulated an understanding of various correlates with substance use disorder in PEH during the COVID-19 pandemic. This knowledge would be quite helpful in promoting the health and safety of PEH. Thus, the purpose of this study was to identify correlates associated with substance use disorder in PEH during the COVID-19 pandemic.
Methods
Design
We conducted a cross-sectional structured survey study among PEHs residing in Central East Los Angeles (Skid Row) during the COVID-19 pandemic, with data collected between April and July 2021. The study was approved by the Institutional Review Board (IRB) Human Subjects Protection Committees
Sample & setting
In total, 104 PEHs were screened and 102 were enrolled. Two PEHs were ineligible as they did not report substance use in the past year. Among these 102, a little over half (n = 52, 50%) had past COVID-19 diagnosis and 50 never had a COVID-19 diagnosis, including three who were never tested for COVID-19. Participants were included if they met the following criteria: 1) age 18 and older; 2) self-reported homelessness (last night), 3) self-reported history of substance use (i.e., heroin, crack/cocaine, etc. and alcohol use) in the past year; 4) classified as either diagnosed as COVID-19 positive versus never diagnosed vs diagnosed as COVID-19 negative and 5) willing to provide verbal informed consent. Exclusion criteria included: 1) speaking languages other than English and Spanish; and 2) being cognitively impaired, as assessed by the interviewer. Participants were recruited from the Skid Row area of LA, and from three homeless shelters, two drug treatment sites in Skid Row, as well as from tents on the street.
Procedures
After receiving approval from site directors, research staff posted flyers in the designated sites, with contact information provided. In addition, research staff offered brief presentations about the study in an open forum. Interested PEH contacted the research staff in person or by phone. Subsequently, among PEH screened out as repeaters by the research staff, the research staff and PEH met in a private, pre-arranged location to hear more about the study, address questions, and, if interested, undergo verbal informed consent using the study information sheet and signed a HIPAA-Permission to Use Personal Health Information for Research.
Participants were then administered a structured questionnaire by trained research staff, using REDCap, assessing socio-demographics, mental health, drug and alcohol use, healthcare access, and general health questions and COVID-19-specific questions. The mean time to complete the questionnaire was 45 min. All participants were paid $3 for the screening questionnaire and if eligible, $30 for the structured questionnaire.
Measures
Sociodemographic and environmental characteristics
Age, gender, race/ethnicity, county of birth, history of substance use, personal health, known or suspected exposure to COVID-19, and days slept on the street/shelter.
Level of Housing Stability was measured by type of housing in the last month. This included living in a shelter, on the streets, or in transitional housing.
Psychosocial and behavioral factors
Anxiety was measured by the Generalized Anxiety Disorder −7, a self-report 7-item measure (Spitzer et al., Citation2006). Example items include “worrying too much about different things,” and “trouble relaxing.” (Endpoint 0 = not at all; 3 = nearly every day). Scores were summed up. Severity of anxiety was determined with cutoff scores 5 (mild anxiety), 10 (moderate anxiety), and 15 (severe anxiety). Reliability was very good, α = 0.87.
Depression was measured by the Patient Health Questionnaire, a 9-item self-administered version of the PRIME-MD diagnostic instrument for mental disorders (Kroenke et al., Citation2001). The PHQ-9 is a brief, 9-item depression module that scores each of the 9 DSM-IV criteria as “0” (not at all) to “3” (nearly every day). PHQ-9 makes criteria-based diagnoses of depressive disorders and can determine severity, with scoring cutoffs for minimal (1–4), mild (5–9), moderate (10–14), moderately severe (15–19) and severe (20–27) depression. Reliability of the PHQ-9 in the PHQ Primary Care study was excellent, α = 0.89.
Post-Traumatic Stress Disorder (PTSD) was assessed by the Primary Care PTSD Screen for DSM-5 (PC-PTSD). This 5-item questionnaire is designed to screen for probable PTSD in primary care settings (Prins et al., Citation2016) and reflects DSM-5 criteria for PTSD (Prins et al., Citation2016). Participants were asked an initial “yes” or “no” question regarding prior traumas, with examples. If a participant answers “yes” to the initial question, they then answer 5 “yes” or “no” questions pertaining to how the trauma has affected them in the past month. A positive screening is determined by a “yes” response to any 3 of the 5 items. The PC-PTSD-5 showed high diagnostic accuracy (AUC = 0.941; 95% C.I.: 0.912–0.969).
Social Isolation was measured by the Social Interaction Anxiety Scale (SIAS) (Mattick & Clarke, Citation1998), and is a validated measure of social phobia constructed from existing social anxiety inventories and fear survey schedules. The SIAS assesses fears of general social interaction in a 38-item questionnaire using a 4-point Likert scale. The scale has been shown to be sensitive to treatment effects and remain stable with no treatment (α = 0.94).
Social Support was measured by the Medical Outcome Study (MOS) Social Support Survey (Sherbourne & Stewart, Citation1991). The MOS is a 19-item instrument with endpoints 1 (none of the time) to 5 (all of the time) that assesses the availability of social support. Four subscales are included: emotional/informational support (eight items, α = 0.95); tangible support (four items, α = 0.94); positive support (three items, α = 0.98); and affectionate support (three items, α = 0.96). An overall support index was also calculated. We have labeled the scores as high, moderate, and low social support.
Drug and Alcohol Use was measured by the Texas Christian University (TCU) Screen V (Knight et al., Citation2018). It is a 17-item measure screening for mild to severe substance use disorder (SUD). Participants indicated “yes” or “no” responses to substance dependency questions and the frequency of drug use based on a 5-point scale from 1 (never) to 5 (daily). The TCU Screen V is scored on a point-system ranging from 0 to 11. Participant scores correspond to the number of symptoms endorsed by the participant and the severity of substance use disorder (SUD): mild disorder (2–3 points), moderate disorder (4–5 points), or severe disorder (6 or more points). The reliability of TCU was excellent.
Statistical analysis
We investigated whether sociodemographic, environmental, psychosocial, and behavioral factors were associated with the primary outcome of interest, drug use disorder, in PEH during the COVID-19 pandemic. Participants were categorized into two exposure groups: a history of COVID-19 positive test and no history of COVID-19 positive test. We calculated the means and frequencies for descriptive analysis. We compared continuous variables using a t-test. For categorical variables, we used Fisher’s exact test or chi-squared test. We also performed a bivariate analysis by specifying the TCU drug use score as a dependent variable. Variables with p-value <0.1 in bivariate analysis were further evaluated using multiple linear regression.
In the final model, we kept the COVID-19 diagnosis variables and all other variables with p-values <0.05. The initial model did not meet the assumptions of constant variance and normal distribution of residuals, so we performed a log10 transformation of the TCU substance use score to improve model fit and satisfy model assumptions. No formal sample size calculations were performed for this exploratory study, which was not designed to detect statistically significant differences between variables. R version 4.1.2 was used for all analyses.
Results
Sample characteristics
As displayed in , a total of 102 participants were included in the study; the majority were male (70.6%; n = 72), and the mean age was 47 years. Most participants identified as Latino (50%; n = 51) or Black (28.4%; n = 29) and were born in the US (82.4%).
Table 1. Sample characteristics of people experiencing homelessness with and without a diagnosis of COVID-19.
While 70.6% (n = 72) of the sample denied any substance use disorder, 90.2% (n = 92) admitted to using drugs or alcohol, while 63.7% (n = 65) of people admitted to drug use only. Marijuana use was the most used among all substances used (49%; n = 50), followed by alcohol (44.1%; n = 45) and cocaine (9.8%; n = 10).
Correlates of COVID-19 (unadjusted)
Compared to those without a history of COVID-19, those with a COVID-19 diagnosis were more likely to be male (88.5%; n = 46; p < .001) and Latino (63.5%; n = 33; p < .05). Additionally, compared to those without a history of COVID-19, those with COVID-19 were less likely to spend time on the street (p < 0.001).
Those who were identified as having COVID-19 in the past were less likely to report a substance use disorder (80.8%; 42; p < .05). Finally, average scores for psychosocial factors including depression (3.2), anxiety (3.9), and post-traumatic stress disorder (0.6) were on the low range of the scales (Kroenke et al., Citation2001; Prins et al., Citation2016), regardless of history of COVID-19.
Unadjusted and adjusted correlates of drug use
As depicted in , in the unadjusted analysis, substance use scores were positively associated with identifying as female or transgender (vs. male; p < 0.01), and the number of days slept in the street (p < 0.001). However, a history of having COVID-19 (p < 0.01) and problematic alcohol use (p < 0.05) were negatively associated with drug use scores.
Table 2. Correlates of substance use score (log-transformed) among people experiencing homelessness in Los Angeles (N = 102).
In the adjusted model, substance use scores remained positively associated with days slept in the street (p < 0.001) and negatively associated with problematic alcohol use (p < 0.05). The prior history of COVID-19 was still negatively associated with drug use scores but did not reach statistical significance (NS), while no other variable reached statistical significance.
Discussion
While PEHs are at risk for COVID-19, no studies have reported correlates of substance use disorder among this under-resourced population. Our study identified the correlates of substance use disorder among PEHs living in Los Angeles during the COVID-19 pandemic. In unadjusted analyses, our major findings revealed that a positive relationship was found with substance use disorder and being female/transgender as well as having slept on the streets. In addition, a negative relationship was found with substance use disorder and being diagnosed with COVID-19 and reporting alcohol use. In adjusted analyses, a positive relationship was found with substance use disorder and days slept on the street, while a negative relationship was found with alcohol use. These associations provide support that sociodemographic, environmental, and behavioral factors impact substance use among PEHs during the COVID-19 pandemic.
One consistent finding in both unadjusted and adjusted analyses was that the number of days PEH slept in the street was positively associated with substance use. In one of the few papers comparing sheltered vs unsheltered PEH, our survey findings of a sample of 1051 PEH, revealed that PEHs who were unsheltered were significantly more likely to use alcohol and non-injection drugs as compared with sheltered PEH (A. M. Nyamathi et al., Citation2000). It is possible that PEHs who sleep on the street may have knowledge about the whereabouts of drug dealers and have easier access to drugs than PEH who resided in shelters. An alternative explanation is that as shelter staff will often not admit PEHs who are actively using drugs, active drug users may have preferred to stay on the streets rather than shelters. Furthermore, PEHs who were isolated or quarantined in shelters were unable to leave; thus, limiting their access to drugs or alcohol.
The negative relationships between alcohol use and COVID-19 diagnosis were informative. In the literature, there is increasing evidence that alcohol use has been increasing since COVID-19 pandemic erupted (Tucker et al., Citation2020). In recent qualitative interviews, PEH reported that alcohol was often consumed due to the belief that it was effective in killing the COVID-19 virus. Other PEHs felt safer in purchasing alcohol rather than having to find drug dealers during the COVID pandemic (A. M. Nyamathi et al., Citation2022). Binging on alcohol was often reported as a coping mechanism, particularly when drugs were harder to find.
Similarly, we also found that a history of having COVID-19 was negatively associated with drug use scores. It can be argued that PEH who were isolated may have reduced their drug use due to inability to purchase drugs. Stay-at-home restrictions may have been a major contributing factor to decreasing drug use among PEH, even if temporarily.
In the unadjusted analysis, being female or transgender (vs. male) was positively associated with substance use. Given this investigation has found that there are gender differences in substance use, a greater understanding of reasons for substance use is needed. Women and transgendered populations may have continued to use drugs and alcohol on the streets for a variety of reasons, including the need to stay awake for safety reasons and/or using substances to cope with unresolved trauma.
We also found that those reported to have COVID-19 were more likely to have spent time in a shelter compared with non-COVID-19 positive PEH. Importantly, the CDC has issued guidance for PEHs living in congregate living centers as they may be at increased risk for COVID-19 (Centers For Disease Control [CDC], Citation2021). However, this association between COVID-19 and residing in a shelter may also be due to higher frequency of testing among PEH sleeping in shelters.
Interestingly, average scores for psychosocial factors including depression, anxiety, and PTSD remained low regardless of the history of COVID-19. Future research needs to examine the protective factors for mental health as well as the negative impact of loneliness and isolation.
Considering the findings of the negative relationship between drug use and alcohol use and increasing consumption of alcohol use reported in the literature (Tucker et al., Citation2020), greater harm reduction policies focusing on alcohol consumption is needed. Thus, development and investigation of managed alcohol programs would be timely to extend the evidence base of this model of alcohol harm reduction for PEH (Parkes et al., Citation2021).
The generalizability of these results has limitations. Firstly, these findings are relevant to a sample within sheltered and unsheltered settings within Skid Row, Los Angeles, during the COVID-19 pandemic. Secondly, we may not have had the power to detect all differences in the study variables. Thirdly, the gender distribution of the sample is not equivalent as women and transgendered participants composed a minority of respondents. Thus, impacting our understanding of gender differences. Notwithstanding these limitations and despite its exploratory nature, this study offers some insight into correlates of COVID-19 infection among PEH, a hard-to-reach population.
A natural progression of this work is to gain a greater understanding of the lessons learned on how COVID-19 social distancing practices altered drug use patterns among PEHs. Further, a greater understanding of successful individual and system-level strategies, which aid in reducing COVID-19 transmission and harm reduction practices would be helpful.
CRediT authorship contribution statement
All authors contributed to the article. AN served as Principal Investigator of the study, lead author of the manuscript, and led the conceptualization, development, interpretation, and final preparation of the manuscript. SS conducted data analyses. BES worked on the implementation, wrote some aspects of the methods and discussion sections, and provided an iterative review. NA contributed to writing a section of the introduction. KY contributed to the data management and data analyses. All authors reviewed iterative drafts of the manuscript prior to submission and contributed to its completion.
Ethical conduct of research
The study was approved by the Institutional Review Board (IRB) Human Subjects Protection Committee at the University of California, Irvine, and acted as the IRB of record for the University of California, Los Angeles.
Acknowledgments
We thank the dedicated and committed community-based organizations, providers, participants, and research team who helped us to successfully complete this study.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data that support the findings of this study are available from the corresponding author, [AN] upon reasonable request.
Additional information
Funding
References
- Allen, B., El Shahawy, O., Rogers, E. S., Hochman, S., Khan, M. R., & Krawczyk, N. (2021). Association of substance use disorders and drug overdose with adverse COVID-19. Outcomes in New York City: January-October 2020: Journal of Public Health (Oxford, England), 43(3), 462–465. https://doi.org/10.1093/pubmed/fdaa241
- Centers For Disease Control. (2021). People experiencing homelessness. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/homelessness.html
- Costa, M., Pavlo, A., Reis, G., Ponte, K., & Davidson, L. (2020). COVID-19 concerns among persons with mental illness. Psychiatric Services (Washington, DC), 71(11), 1188–1190. https://doi.org/10.1176/appi.ps.202000245
- Farhoudian, A., Baldacchino, A., Clark, N., Gerra, G., Ekhtiari, H., Dom, G., Mokri, A., Sadeghi, M., Nematollahi, P., Demasi, M., Schütz, C. G., Hash-Emian, S. M., Tabarsi, P., Galea-Singer, S., Carrà, G., Clausen, T., Kouimtsidis, C., Tolomeo, S., Radfar, S. R., & Razaghi, E. M. (2020). COVID-19 and substance use disorders: Recommendations to a comprehensive healthcare response. An International Society of Addiction Medicine Practice and Policy Interest Group Position Paper: Basic and Clinical Neuroscience, 11(2), 133–150. https://doi.org/10.32598/bcn.11.covid19.1
- Fitzpatrick, K. M. (2017). How positive is their future? Assessing the role of optimism and social support in understanding mental health symptomatology among homeless adults. Stress and Health: Journal of the International Society for the Investigation of Stress, 33(2), 92–101. https://doi.org/10.1002/smi.2676
- Garfin, D. R., Morisky, D., Shin, S. S., Salem, B., Yadav, K., Deguzman, R., Harvey, G., Adams, I., Halas, K., Chang, A., White, K., Wu, J., & Nyamathi, A. M. (2022). Correlates of depression and anxiety among homeless adults with latent tuberculosis infection. Journal of Health Psychology, 27(2), 494–501. https://doi.org/10.1177/1359105320956693
- Knight, D. K., Blue, T. R., Flynn, P. M., & Knight, K. (2018). The TCU drug screen 5: Identifying justice-involved individuals with substance use disorders. Journal of Offender Rehabilitation, 57(8), 525–537. https://doi.org/10.1080/10509674.2018.1549180
- Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606–613. https://doi.org/10.1046/j.1525-1497.2001.016009606.x
- Lazarus, R., & Folkman, S. (1984). Stress, appraisal and coping. Springer.
- Los Angeles County Department of Public Health. (2021). Summary report of COVID-19 in people experiencing homelessness (9/20/21-9/26/21). http://publichealth.lacounty.gov/media/coronavirus/docs/SummaryReport_People_Experiencing_Homelessness.pdf
- Los Angeles County Department of Public Health, Center for Health Impact Evaluation. (2021) Recent Trends in mortality rates and causes of death among people experiencing homelessness in Los Angeles County, January 2021. http://www.publichealth.lacounty.gov/chie/reports/HomelessMortality2020_CHIEBrief_Final.pdf
- Los Angeles Homeless Service Authority. (2020). 2020 Greater Los Angeles Homeless Count Results. https://www.lahsa.org/news?article=726-2020-greater-los-angeles-homeless-count-results
- Mattick, R. P., & Clarke, J. C. (1998). Development and validation of measures of social phobia scrutiny fear and social interaction anxiety. Behaviour Research and Therapy, 36(4), 455–470. https://doi.org/10.1016/s0005-7967(97)10031-6
- Nyamathi, A. (1989). Comprehensive health seeking and coping paradigm. Journal of Advanced Nursing, 14(4), 281–290. https://doi.org/10.1111/j.1365-2648.1989.tb03415.x
- Nyamathi, A. M., Gelberg, L., Lee, D., Arce, N., Patten-Jones, A., Yadav, K., Goodwine, M., Alikhani, M., Yao, M., Chang, A. H., & Salem, B. E. (2022). Perceptions of homeless adults and their providers on coping with the impact of COVID-19 pandemic on mental health, substance use, and harm reduction services. Global Qualitative Nursing Research, 9, 23333936221108712. https://doi.org/10.1177/23333936221108712
- Nyamathi, A. M., Leake, B., & Gelberg, L. (2000, August). Sheltered versus nonsheltered homeless women differences in health, behavior, victimization, and utilization of care. Journal of General Internal Medicine, 15(8), 565–572. PMID: 10940149; PMCID: PMC1495574. https://doi.org/10.1046/j.1525-1497.2000.07007.x
- Parkes, T., Carver, H., Masterton, W., Booth, H., Ball, L., Murdoch, H., Falzon, D., Pauly, B. M., & Matheson, C. (2021). Exploring the potential of implementing managed alcohol programmes to reduce risk of COVID-19 infection and transmission, and wider harms, for people experiencing alcohol dependency and homelessness in Scotland. International Journal of Environmental Research and Public Health, 18(23), 12523. https://doi.org/10.3390/ijerph182312523
- Perri, M., Dosani, N., & Hwang, S. W. (2020). COVID-19 and people experiencing homelessness: Challenges and mitigation strategies. CMAJ: Canadian Medical Association Journal = Journal de l’Association Medicale Canadienne, 192(26), E716–719. https://doi.org/10.1503/cmaj.200834
- Prins, A., Bovin, M. J., Smolenski, D. J., Marx, B. P., Kimerling, R., Jenkins-Guarnieri, M. A., Kaloupek, D. G., Schnurr, P. P., Kaiser, A. P., Leyva, Y. E., & Tiet, Q. Q. (2016). The primary care PTSD screen for DSM-5 (PC-PTSD-5): Development and evaluation within a Veteran primary care sample. Journal of General Internal Medicine, 31(10), 1206–1211. https://doi.org/10.1007/s11606-016-3703-5
- Schlotfeldt, R. M. (1981). Nursing in the future. Nursing Outlook, 29(5), 295–301.
- Sherbourne, C. D., & Stewart, A. L. (1991). The MOS social support survey. Social Science & Medicine, 32(6), 705–714. 1982. https://doi.org/10.1016/0277-9536(91)90150-b
- Spitzer, R. L., Kroenke, K., Williams, J. B., & Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092–1097. https://doi.org/10.1001/archinte.166.10.1092
- Tucker, J. S., D’amico, E. J., Pedersen, E. R., Garvey, R., Rodriguez, A., & Klein, D. J. (2020). Behavioral health and service usage during the COVID-19 pandemic among emerging adults currently or recently experiencing homelessness. The Journal of Adolescent Health: Official Publication of the Society for Adolescent Medicine, 67(4), 603–605. https://doi.org/10.1016/j.jadohealth.2020.07.013
- Volkow, N. D. (2020). Collision of the COVID-19 and addiction epidemics. Annals of Internal Medicine, 173(1), 61–62. https://doi.org/10.7326/M20-1212
- Wang, J. Z., Mott, S., Magwood, O., Mathew, C., Mclellan, A., Kpade, V., Gaba, P., Kozloff, N., Pottie, K., & Andermann, A. (2019). The impact of interventions for youth experiencing homelessness on housing, mental health, substance use, and family cohesion: A systematic review. BMC Public Health, 19(1), 1528. https://doi.org/10.1186/s12889-019-7856-0