Quality of Life During COVID-19

Individuals with Intellectual and Developmental Disabilities and Direct Support Professionals

Erin Vinoski Thomas
Georgia State University

Rachel Odunlami
Georgia State University

Sombal Bari
University of Georgia

Bridgette M. Schram
Georgia State University

Publication Date: 2020


People with intellectual and developmental disabilities (PWIDD) and the direct support professionals (DSPs) who support them have faced unique risks throughout the COVID-19 pandemic. We used a rapid mixed methods approach to understand how COVID-19 has impacted overall quality of life (QoL) among these populations. We quantitatively assessed changes in QoL among a sample of PWIDD and DSPs (n = 137) using a retrospective pretesting approach. We then conducted a rapid qualitative inquiry study with a sample of survey respondents (n = 12) to gain deeper perspective. Findings suggested that participants experienced significant decreases (p < .001) in all four measured domains of QoL. Participants qualitatively described that decreases in QoL were influenced primarily by reduced socialization and impacts on health and independence; however, participants also described the ways their interactions and mutual support for each other helped to preserve some aspects of QoL. Participants described numerous ways race and racism contributed to their COVID-19 experiences, and offered descriptions of resources they benefited from, and those they lacked, during this time. Study findings have the potential to inform development of policies and best practices that support PWIDD and DSPs during and following similar infectious disease emergencies.


Between 7 and 8 million people in the United States have some type of intellectual and/or developmental disability (Larson et al., 20181). People with intellectual and developmental disabilities (PWIDD) face unique and substantial risks during disasters and emergencies (Centers for Disease Control and Prevention, 20152). Due to increased prevalence of secondary health conditions such as heart disease and diabetes, as well as reduced access to health care (Krahn et al., 20153), PWIDD are at increased risk for contracting COVID-19 and an increased risk of death if they do contract the virus. PWIDD may experience difficulties implementing basic hygiene measures, like handwashing, that are known to reduce illness, and may require direct support services to maintain their health and independence, which precludes their ability to practice adequate social distancing (UN News, 20204). Further, ableism, which is the pervasive devaluation of people with disabilities, may influence medical triaging decisions during the pandemic that discriminate against people with disabilities and older adults (Ne’eman, 20205).

Beyond the immediate risks to their health and civil rights, PWIDD may also be at risk for negative social and behavioral outcomes, like diminished quality of life (QoL), resulting from the pandemic and guidelines in place to help reduce its spread. Having adequate professional support enhances QoL and overall well-being for PWIDD (Friedman, 20186). However, support may be reduced in times of social distancing and may negatively impact independence, well-being, and overall QoL in this population.

Professional support may also be reduced as direct support professionals (DSPs) become ill due to their heightened risk for contracting the virus (National Association of Direct Support Professionals (NADSP), 20207). Indeed, DSPs are considered another at-risk population due to their ‘front-lines’ contact with others at high risk, and because many DSPs receive inadequate pay, lack adequate sick and family leave, and are likely to be un- or under-insured (President’s Committee for People with Intellectual Disabilities, 20178). DSPs may also be under substantial stress as the pandemic unfolds, as they recognize their high risk and face uncertainty about their hours and pay.Careworker stress is an under-evaluated and undertreated health risk that can lead to negative outcomes for the professional and the individuals they support (Zwerling et al., 20169; Gray-Stanley et al., 201010). Lastly, although relationships between PWIDD and their DSPs are primarily professional, NADSP recognizes that a strong bond and mutually beneficial partnership often arises between PWIDD and their DSPs (Raffaele, 201911). Particularly during times of forced isolation, PWIDD and DSPs may increasingly rely on each other for socialization, support, and assistance in navigating general uncertainty (LaLiberte et al., 200712). Understanding how these relationships shape outcomes for PWIDD and DSPs is important to inform emergency preparedness and response efforts at the local, state, and national levels.

Research Questions

PWIDD and DSPs are at increased risk for negative outcomes resulting from the COVID-19 pandemic. Given this heightened risk, and the complex nature of the relationships between PWIDD and their DSPs, our study sought to evaluate changes in various domains of QoL among both PWIDD and their DSPs resulting from the COVID-19 pandemic, and to understand how PWIDD and their DSPs are seeking and receiving support from each other and other resources during this time.

We used an explanatory sequential mixed methods design (Creswell & Plano Clark, 201113) to address the following research questions:

  • RQ1: Are PWIDD and DSPs living in the US experiencing changes in QoL resulting from the COVID-19 pandemic?
  • RQ2: How do PWIDD and their DSPs describe their experiences during the COVID-19 pandemic that affect QoL?
  • RQ3: How do PWIDD and their DSPs work together during emergencies like COVID-19 to maximize and preserve QoL?
  • RQ4: What strategies and resources to preserve QoL do PWIDD and DSPs use, and what strategies and resources do they need during this type of emergency?

Study 1: Retrospective Pretest Survey

Study 1 Methods

We conducted a retrospective pretest study using a validated measure to assess changes in QoL among PWIDD and DSPs that occurred during the period of time from immediately before the pandemic was introduced in the US (February 2020) until the end of May 2020 (RQ1). Retrospective pretesting is a unique way of gathering pretest data, as it is administered during or after an event and asks participants to assess their degree of knowledge, skill, or disposition both prior to the event and during or after the event (Vinoski Thomas et al., 201914). Retrospective pretesting is particularly effective when the collection of pretest data is infeasible or the need for such data goes unanticipated, such as during emergencies and disasters (North & Norris, 200615).

Survey Sampling. We sampled PWIDD and DSPs for the quantitative study using announcements on Facebook and Twitter that were subsequently shared by reposts and retweets from other individuals and organizations. All survey participants resided in the US, were able to express themselves using standard English, were 18 or older, and identified as a PWIDD or as a DSP. When completing the survey, respondents indicated if they would be willing to participate in a follow-up interview.

Data Collection and Instrumentation. We collected quantitative data using a web-based survey hosted on our university’s Qualtrics platform. The survey was accessible using desktop, laptop, and mobile devices and was tested for accessibility prior to its release. Data collected through this survey included: (a) demographic information (e.g., race, ethnicity, gender, disability); (b) self-rated QoL at present (during the pandemic); (c) retrospective self-rated QoL before the pandemic arrived in the US; and (d) email address (to receive the $15 study incentive and to be contacted for participation in the qualitative study, where applicable).

We assessed QoL among PWIDD and DSPs using the Quality of Life Questionnaire ([QoL-Q], Schalock and Keith, 1993a16). This 40-item questionnaire was originally designed to measure QoL among people with intellectual disabilities. It covers four domains: Personal Life Satisfaction (10 questions); Work Competence and Productivity (10 questions); Empowerment and Independence (10 questions); and Social Belonging and Community Integration (10 questions). The measure demonstrates good reliability and validity in populations with intellectual disabilities and within the general population (Schalock & Keith,1993b17). In the present study, Cronbach’s alpha for the full sample and separately for PWIDD and DSPs showed high internal consistency ( α = .89 for the full sample, and for each population separately).

Data Analysis. Data were exported from Qualtrics into SPSS version 25 (IBM Corp., 2015) for analysis. An initial set of 139 eligible participants consented to participate. Cases with 50% or more missing data were removed from the sample (n = 2; Papageorgioua et al., 201818), resulting in the final analytic sample (n = 137). Remaining missing data were determined missing completely at random (p = .991; Little, 198819). Frequencies and descriptives were calculated to assess distribution of the data, participant demographics, and mean QoL scores on the whole measure and for each domain, and for the full sample and separately for PWIDD and DSPs. We then conducted paired t-tests to assess changes in QoL in both population groups from retrospective pretest to posttest. Effect sizes were calculated using Cohen’s d to assess the magnitude of the changes in QoL resulting from COVID-19.

Study 1 Results

Participants. The final survey sample was comprised of 137 participants, including 44.5% PWIDD and 55.5% DSPs. Women comprised 35.8% and men comprised 56.9% of the survey sample; no participants identified as transgender or opted to describe their gender identity (note that not all demographics add up to 100% due to missing demographic data). About half of the survey sample (49.6%) were White, 30.7% were Black, and 12.5% of the sample identified as another race or multiple races. About 11% of the survey sample identified as Hispanic or Latinx. The survey sample included individuals representing both urban and rural locales, with 18.2% representing rural ZIP codes. Just over 10 % of the sample reported that they had been exposed to COVID. Just under 10% also reported to have had symptoms of COVID, and 19% reported that they were tested for COVID.

Survey Findings. Each domain of the QoL-Q showed a statistically significant negative difference from pretest to posttest for each group (p ≤ .001 for all domains; see Table 2). We followed the paired t-test analysis with an analysis of effect size using Cohen’s d. As shown in Table 2, the domains of Work Competence and Productivity and Belonging and Community Integration showed very high effect sizes among PWIDD, indicating a steep decline in scores on those subscales from pretest to posttest. Among DSPs, the decrease in QoL scores for each domain was less pronounced than the effects observed among PWIDD, yet still indicated medium to large effect sizes. Among DSPs, the two steepest declines were observed in the domains of Personal Life Satisfaction and Belonging and Community Integration.

Table 2. Survey results by population and QoL-Q dimension.

Population/Dimension of QoL t df Sig. (2-tailed) d
Personal Life Satisfaction 4.72 58 <.001 .84
Work Competence & Productivity 4.65 57 <.001 4.53
Empowerment & Indep. Living 4.40 59 <.001 .59
Belonging & Comm. Integration 7.16 58 <.001 2.28
Personal Life Satisfaction 5.06 73 <.001 .67
Work Competence & Productivity 4.16 75 <.001 349
Empowerment & Indep. Living 3.54 73 .001 .59
Belonging & Comm. Integration 5.65 72 <.001 .91

Study 2: Rapid Qualitative Inquiry Study

Following the collection and analysis of the quantitative data, a select sample of PWIDD and DSPs participated in a rapid qualitative inquiry (RQI) study to further uncover the perspectives and needs of PWIDD and their DSPs during the COVID-19 pandemic (RQ2-RQ4). Qualitative methods are particularly suitable when research questions attempt to (a) understand contextualized processes, relationships, and specific experiences (Morrow, 200720), and (b) develop substantive conceptualizations of specific phenomena (Smith et al., 200921). RQI is an applied research method designed to quickly develop, usually in less than several weeks, a preliminary understanding of a complex and often rapidly changing situation (Beebe, 201422) and as such was well suited to this investigation.

Study 2 Methods

Qualitative Sampling. Out of those survey respondents who indicated a willingness to be interviewed, we purposively sampled participants to represent the heterogeneity of the population of individuals with disabilities and DSPs and allow us to access “information-rich cases” (Patton, 200223, p. 230). Specifically, interviewees from underrepresented racial and ethnic communities and rural areas were contacted first to join the interview study. The final sample of interviewees (n = 12, including 8 DSP and 4 PWIDD) represented perspectives from people with various types of disabilities and individuals representing other diverse identities (e.g., those who identified with races other than White). Despite our attempts to over-sample individuals residing in rural areas, most who responded to our recruitment requests lived in non-rural locations.

Qualitative Data Collection. In the second phase of study, the research team conducted rapid semi-structured interviews to gather participants’ perspectives. The study design was conceptualized to maximize safety; therefore, interviews were conducted using video conferencing so that the PWIDDs, DSPs, and interviewers did not need to be in the same physical location to engage with each other. Processes recommended for RQI studies, such as team immersion, team-based interviewing, and regular peer debriefing were integrated at all phases (Beebe, 2014).

Two interviewers were present for each interview. Although we originally planned to conduct interviews with PWIDD/DSP dyads, we learned early on that this would not be possible in most cases due to confidentiality concerns. The majority of interviews were conducted with individual participants; two participants, a young man with an intellectual or developmental disorder (IDD) and his mother who works professionally as a DSP and also supports him, opted to interview as a dyad. Two participants with disabilities opted to communicate responses through or be represented by a family member. Interviews lasted 30 minutes on average (interview length ranged from 18:57 to 36:38; see Table 2). The full interview guide is available as a supplement to this report.

As is required for RQI studies, all team members met weekly throughout the data collection process to debrief interviews and discuss any changes to the interview guide based on data collected. Following the second interview, during which the participant discussed at length the challenges he faced as a member of a racial minority group during COVID-19, the research team collaboratively decided to add two interview questions specifically related to race and racism to the interview guide.

Qualitative Coding and Analysis. Qualitative interviews were analyzed using a qualitative content analysis approach (Mayring, 200024). The study PI and one graduate research assistant each independently open coded the first five interview transcripts. These two study team members engaged in peer debriefing (Lincoln & Guba, 198525) to determine a final set of codes and develop the study codebook. The study PI then coded all interviews based on the codebook. Once all data were coded, the PI used focused and descriptive coding (Saldaña, 201626) and engaged in a diagramming process (Buckley & Waring, 201327) to condense and combine codes that linked with each other across interviews, and to eliminate codes that faded out over time (Charmaz, 200828).

Qualitative Rigor. We applied a number of techniques to enhance the study’s methodological and interpretive rigor (Lincoln & Guba, 1985). We used a member checking process to improve the study’s credibility; within one week following each interview, a study team member emailed a two- to three-paragraph summary of the interview to each participant and asked the participant to confirm or correct it to ensure it accurately reflected the perspectives they shared during the interview. Summaries were generated from interview transcripts and the interview team’s detailed field notes. All summaries were verified by participants without revision. We also enhanced the study’s credibility by using multiple coders; however, due to the rapid nature of the study timeline, a majority of the qualitative coding and analysis was performed by the PI.

Study 2 Results

Participants. The sample of qualitative interview participants was drawn from the overall survey sample. The interview sample included 12 individuals, 4 of whom identified as PWIDD and 8 of whom identified as DSPs. Demographic information for the qualitative participants is found in Table 1, below.

Table 1. Demographic data about qualitative interview participants.

 Participant ID  Gender Age  Race/ Ethnicity   DSP or PWIDD Geographic Locale   Interview Length
 001  F  34  Black DSP  Rural  18:57
002  24   Asian DSP   Non-rural  34:55
003  60  White DSP   Non-rural  34:15
004  24  White  PWIDD   Non-rural  34:15
005  39  Black  DSP   Non-rural  33:28
006  38  White  DSP   Non-rural  34:24
007  48  Black DSP   Non-rural  25:06
008  23  Latinx PWIDD   Non-rural  27:19
009  25  White  DSP   Non-rural  26:28
010  24  White  PWIDD   Non-rural  36:38
011  28  Latinx  PWIDD   Non-rural  31:58
012 F 29 White DSP Non-rural 23:58

Interview Findings. Five major themes emerged from the interviews, including: QoL Definitions, Impacts of COVID-19 on QoL, Relationships and Mutual Support, A Dual Pandemic, and Resources and Supports. Each major theme also had subthemes, as described and italicized below. Illustrative participant quotes are included under each theme or subtheme.

Theme 1: QoL Definitions. Participants defined QoL differently. Some participants provided broad definitions, using terms like “the day to day things we do” (Participant 001, DSP) and “it relates to everything, really” (Participant 008, PWIDD). Other participants provided deeper definitions. For example, Participant 003, a DSP and mother of a son with autism, described QoL as, “Having a social life, feeling fulfilled in work, and being able to have family and friends.” Another DSP described QoL as being tied to different domains of health: “[it includes] physical health, emotional health, mental health, you know” (Participant 009, DSP). These more in-depth definitions loosely aligned with definitions and domains of QoL that exist in the research literature, including the domains measured through the survey used in Study 1. When asked where participants thought their definitions came from or what informed their definitions, they described being informed by prior training in psychology and sociology, by their spiritual lives and belief systems, by their culture, and by their families. None of the participants described their definitions as being informed by the survey they took just weeks prior.

Theme 2: Impacts of COVID-19 on QoL. Participants described a number of ways they felt COVID-19 impacted their QoL and that of others they have relationships with. Participants with disabilities and DSPs alike described the general impacts that they were feeling regarding their overall wellbeing. Nearly all participants expressed feeling uncertainty, which was a major contributor to their increased stress and frustration, and perhaps particularly among PWIDD. One DSP commented:

I think there’s just a lot of confusion. I feel confused and don’t really know the right answers, um, and the right things to do. We don’t know when this is gonna be over, and I think that’s amplified for some of the folks that I work with that process things differently (Participant 012, DSP).

Similarly, a participant with IDD expressed needing to “know how long it is, or something. ‘Cause I’m very picky about that lasting forever” (Participant 004, PWIDD).

Two participants with IDD described that they were experiencing reduced wellbeing, and that they found themselves spending time primarily on “video games” and “sleeping” because there is “nothing else to do” (Participant 004, PWIDD). DSPs described feeling stressed and “very tired” (Participant 001, DSP). Interestingly, many participants also expressed a common humanity and recognized that even though they were feeling negative impacts, they recognized their privilege compared to many other people. For example, one participant described, “Physically and mentally, I’m in a better place than a lot of people” (Participant, 002, DSP). A DSP who manages other DSPs mentioned:

I feel guilty at times because of what [other] DSPs are doing day to day. They’re doing much more work than I am and carrying much more stress than I am… it’s been a guilty time and a lot of that guilt is rooted in maleness, and cisgender, and Whiteness—all of those things.

Other common subthemes associated with Theme 2 included impacts on socialization, recreation, and relationships, and impacts on health and independence. Every participant described not having access to the same level of socialization (e.g., “missing friends” [Participant 011, PWIDD]; “not being able to visit my family” [Participant 007, DSP]) and recreation (e.g., “I miss going out to dinner” [Participant 003, DSP]). All participants also described effects on their mental health, and many mentioned the need for emotional support resources (described further under Theme 5).

Theme 3: Relationships and Mutual Support. Participants were asked about how their relationships with each other had changed during the pandemic, and how they found themselves providing and receiving mutual support. Many participants described that they felt their relationships had not changed. Some reported positive changes, such as deepening relationships with the families they work with. One DSP described:

Talking to this other person about their loved one’s health complications has just gotten me more involved in the families in a way I had not been in the past. Even though some of those things have been frustrating, the experiences have all been positive relationship-building experiences (Participant 006, DSP).

Other participants talked about changes in their relationships they found challenging. For example, one participant with IDD described that due to the nature of moving to virtual supports and meetings, he felt like his “case manager’s barely there” and that his “mom helps a lot more than [his] case manager” (Participant 004, IDD). This participant also mentioned that he feels like his mom is around more because she is working from home, but she’s “always working all the time and [he feels] more lonely.”

Participants described how they have found mutual support with each other (i.e., between PWIDD and DSPs). The DSP who is also a parent of an individual with IDD described how technology has been a barrier for her during the pandemic, but that her son with autism has been able to help her navigate technology while she has been helping him to keep a schedule and a positive mood.

Participant 004 (IDD): [Participant 003] tells me to get up sometimes… when it’s like something important.
Participant 003 (DSP): And [Participant 004] helps me tremendously with the technology.

Many participants explained that at the foundation of this mutual support has been “working together and learning together” (Participant 001, DSP). As Participant 007 (DSP) described, “You’re probably gonna hear this a million times… We are all in this together.”

Theme 4: A Dual Pandemic. One of the most profound findings from the study was that most participants openly engaged in discussions about, in the words of one participant, the “two pandemics” of COVID-19 and racial injustice co-occurring in the US (Participant 005, DSP). For the first few interviews, these discussions emerged unprompted by researchers; the team later added two questions to the interview guide to ask participants explicitly about how they perceived race and racism to play into their pandemic experiences. One participant, an Asian-American man working as a DSP, described how the pandemic has been racialized publicly and at the national level as a “Chinese and Asian virus,” and, after hearing “stories and concerns of his Chinese and Asian-American friends,” being in a constant state of “fear for [his] physical safety… fear of being attacked, of being called racialized, disease-related slurs” (Participant 002, DSP). This DSP described a time when one of the individuals he supports (a White male with IDD) asked him questions about whether he has ever traveled to China and commenting that he loves to eat Chinese food, which he perceived as a racial microaggression and felt detracted from his professional relationship with that particular individual.

One Black participant described how the dual pandemic has impacted him personally and professionally; he expressed wishing he could “go out there and protest,” but did not feel comfortable doing so knowing that Black individuals experienced higher risk (Participant 005, DSP). He also expressed that he informed his supervisor he could not perform a job task (i.e., conducting face-to-face visits) because he knew his risk was heightened and he did “not want to put the other person at risk.”

A participant who identified as Puerto Rican described that she had thought about the stress of navigating the dual pandemics of COVID-19 and police brutality. She expressed knowing that “half of police killings are people with disabilities,” and that “it’s different for Black people, you know, because they have to worry about police brutality and worry about the police” (Participant 008, PWIDD). Lastly, several White participants expressed that this has been a time of learning and education about Whiteness, privilege, and racism for them: “I am slowly learning about White privilege” (Participant 010, PWIDD).

Theme 5: Resources and Supports. Participants identified a number of resources they have used, and a number they have needed, during the first four months of the COVID-19 pandemic. Technology was the most frequently mentioned resource that almost all participants found helpful toward maintaining their work, social life, and “sense of normalcy” (Participant 011, PWIDD). Technology, though, was also perceived as a challenge, in that it is “a big learning curve” for people who are not frequent users and some individuals with IDD (Participant 003, DSP). It was also mentioned that many people lack access to technology, which could exacerbate issues in communities that are already experiencing increased risk during the pandemic. Another resource that was considered both a benefit and a challenge for participants (particularly DSPs) was personal protective equipment (PPE). Participants 002 and 006 mentioned how important it was to have access to adequate PPE; however, these participants as well as Participants 009 and 011 mentioned that there were shortages of PPE in their areas and that this situation was really stressful for them to navigate.

Resources that participants mentioned using frequently included the Centers for Disease Control and Prevention/World Health Organization COVID safety guidelines (Participants 001, 003, 006, and 012); informational webinars for DSPs and PWIDD (Participants 005, 008, and 010); financial assistance through government and other formal supports (002 and 008); relying on other people, including friends, family, coworkers, and counselors for emotional support (Participants 002, 005, 006, 008, 009, and 011); social media (003 and 004); and food and hygiene supply delivery services (Participants 007 and 009).

Resources that participants mentioned they needed or wished they could access included a “well-funded federal pandemic response team” (Participant 002), and relatedly, better preparedness services, warnings, and procedures to help ease uncertainty (Participants 001, 002, 004 and 008); and additional supports/hotlines for mental health and emotional support (Participants 002, 005 and 008). Lastly, participants were asked to identify resources they thought might be specifically beneficial for PWIDD. Responses included access to financial support (including federal pandemic unemployment and webinars about savings accounts to prepare for emergencies in the future; Participants 005, 008, and 011); access to safe and reliable transportation (Participant 003); and news and other information presented in more accessible or universally designed ways so that it is easier for PWIDD to understand (Participant 012).

Potential Applications and Future Directions

The findings from this study have the potential to broadly impact policies at the local, state, and federal levels that determine how resources and supports are allocated during emergencies to vulnerable populations, including PWIDD and DSPs. The findings will also inform best practices for researchers, clinicians, advocates, PWIDD, and DSPs to advocate for supports during future emergency situations.

Shortly after we received funding from the Natural Hazards Center to carry out our proposed quick response research activities in April, we received additional funding from our state developmental disabilities agency to extend and expand the project. We used this additional funding to double the number of survey respondents we initially proposed to recruit for Study 1. We are in the process of expanding the interview sample to reach up to 24 participants, and we will also extend the study by conducting second interviews with the interview participants in September and October of 2020 to understand more about how their QoL has continued to change throughout the pandemic.

Lastly, we aim to leverage our additional funding to expand this research by conducting a knowledge translation study. The knowledge translation study will ensure the information gained through the study can be adapted to inform and outline actionable steps for the IDD community, DSPs, other providers, researchers, and legislators. The intended outcome of this phase of the research will be to translate the data collected and knowledge gained into usable information that will support advocacy to improve the emergency preparedness and health care policies that place PWIDD and DSPs at higher risk in the first place. Knowledge translation will involve creating data briefs and infographics that are informative to PWIDD and DSPs and systematically collecting input from Development Disabilities councils, University Centers for Excellence in Developmental Disabilities, and Protection and Advocacy organizations to inform future legislative advocacy.


  1. Larson, S.A., Eschenbacher, H.J., Anderson, L.L., Taylor, B., Pettingell, S., Hewitt, A., Sowers, M., & Bourne, M.L. (2018). In-home and residential long-term supports and services for persons with intellectual or developmental disabilities: Status and trends through 2016. Minneapolis, MN: University of Minnesota, Research and Training Center on Community Living, Institute on Community Integration. https://ici.umn.edu/products/1005 

  2. Centers for Disease Control and Prevention (2015). Planning for an emergency: Strategies for identifying and engaging at-risk groups (1st ed.). Centers for Disease Control and Prevention. 

  3. Krahn, G. L., Klein Walker, D., & Correa-de-Araujo, R. (2015). Persons with disabilities as an unrecognized health disparity population. American Journal of Public Health, 105, S198-S206. https://doi.org/10.2105/AJPH.2014.302182 

  4. UN News (2020). (2020, March 19). Preventing discrimination against people with disabilities in COVID-19 response. https://news.un.org/en/story/2020/03/1059762 

  5. Ne’eman, A. (2020). (2020, March 23). ‘I will not apologize for my needs.’ New York Times. https://www.nytimes.com/2020/03/23/opinion/coronavirus-ventilators-triage-disability.html?campaignId=7JFJX 

  6. Friedman, C. (2018). Direct support professionals and quality of life of people with intellectual and developmental disabilities. Journal of Intellectual and Developmental Disability, 56(4), 234-250. doi: 10.1352/1934-9556-56.5.234 

  7. National Association of Direct Support Professionals (2020). Coronavirus 101: Info for direct support professionals. https://nadsp.org/wp-content/uploads/2020/03/CDC-One-sheet-2.pdf 

  8. President’s Committee for People with Intellectual Disabilities. (2017). America’s direct support workforce crisis: Effects on people with intellectual disabilities, families, communities and the U.S. economy. National Alliance for Direct Support Professionals. https://www.nadsp.org/wp-content/uploads/2018/02/PCPID-2017_-Americas-Direct-Support-Workforce-Crisis-low-res.pdf 

  9. Zwerling, J. L., Cohen, J. A., & Verghese, J. (2016). Dementia and caregiver stress. Neurodegenerative Disease Management, 6(2), 69-72. 

  10. Gray-Stanley, J. A., Muramatsu, N., Heller, T., Hughes, S., Johnson, T. P., & Ramirez-Valles, J. (2010). Work stress and depression among direct support professionals: the role of work support and locus of control. Journal of Intellectual Disability Research, 54(8), 749-761. doi: 10.1111/j.1365-2788.2010.01303.x. 

  11. Raffaele, J. (2019). Beyond the paid relationship: Embracing the NADSP competency of building and maintaining friendships and relationships. National Alliance for Direct Support Professionals. https://nadsp.org/beyond-the-paid-relationship/ 

  12. LaLiberte, T., Hewitt, A., Lande, J.H., & Larson, S.A. (2007). You know that it’s got to be dedication that I am still here: The experiences of direct support professionals during Hurricanes Katrina and Rita and the aftermath. University of Minnesota, Research and Training Center on Community Living. http://rtc.umn.edu/docs/NOLAFinalReport.pdf 

  13. Creswell, J. W., & Plano Clark, V. L. (2011). Designing and conducting mixed methods research. (2nd ed.). Sage. 

  14. Vinoski Thomas, E., Wells, R., Baumann, S. D., Graybill, E., Roach, A. T., Truscott, S. D., Crenshaw, M., & Crimmins, D. (2019). Comparing traditional vs. retrospective pre-/post-assessment in an interdisciplinary leadership training program. Maternal and Child Health Journal, 23(2), 191-200. doi: 10.1007/s10995-018-2615-x 

  15. North, C. S., & Norris, F. H. (2006). Choosing research methods to match research goals in studies of disaster or terrorism. In F. H. Norris, S. Galea, M. J. Friedman, and P. J. Watson (Eds.), Methods for disaster mental health research. Guilford Press. 

  16. Schalock, R. L., & Keith, K. D. (1993a). Quality of Life Questionnaire [Database record]. Retrieved from PsycTESTS. doi: https://dx.doi.org/10.1037/t10624-000 

  17. Schalock, R. L., & Keith, K. D. (1993b). Quality of Life Questionnaire manual. IDS Publishing Corporation. 

  18. Papageorgiou, G., Grant, S. W., Takkenberg, J. J. M., & Mokhles, M. M. (2018). Statistical primer: How to deal with missing data in scientific research? Interactive Cardiovascular Thoracic Surgery, 27(2), 153-158. doi:10.1093/icvts/ivy102 

  19. Little, R. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(404),1198-1202. doi:10.2307/2290157 

  20. Morrow, S. L. (2007). Qualitative research in counseling psychology: Conceptual foundations. The Counseling Psychologist, 35(2), 209-235. doi:10.1177/0011000006286990 

  21. Smith, J. A., Flowers, P., & Larkin, M. (2009). Interpretive phenomenological analysis: Theory, method, and research. Sage. 

  22. Beebe, J. (2014). Rapid qualitative inquiry: A field guide to team-based assessment (2nd. ed.). Rowman & Littlefield. 

  23. Patton, M. Q. (2002). Qualitative research and evaluation methods (3rd ed.). Sage. 

  24. Mayring, P. (2000). Qualitative content analysis. Forum: Qualitative Social Research, 1, Art. 20. http://www.qualitative-research.net/index.php/fqs/article/view/1089/2385 

  25. Lincoln, Y. S. & Guba, E. G. (1985). Naturalistic inquiry. Sage. 

  26. Saldaña, J. (2016). The coding manual for qualitative researchers. Sage. 

  27. Buckley, C. A., & Waring, M. J. (2013). Using diagrams to support the research process: Examples from grounded theory. Qualitative Research, 13(2), 148-172. doi: 10.1177/1468794112472280 

  28. Charmaz, K. (2008). Constructionism and the grounded theory. In J. A. Holstein & J. F. Gubrium (Eds.), Handbook of constructionist research (pp. 397-412). Guilford Press. 

Suggested Citation:

Vinoski Thomas, Erin, Rachel Odunlami, Sombal Bari, & Bridgette M. Schram. 2020. COVID-19: Quality of Life among Individuals with Intellectual and Developmental Disabilities and Direct Support Professionals. Natural Hazards Center Quick Response Grant Report Series, 308. Boulder, CO: Natural Hazards Center, University of Colorado Boulder. Available at: https://hazards.colorado.edu/quick-response-report/covid-19

Vinoski Thomas, Erin, Rachel Odunlami, Sombal Bari, & Bridgette M. Schram. 2020. COVID-19: Quality of Life among Individuals with Intellectual and Developmental Disabilities and Direct Support Professionals. Natural Hazards Center Quick Response Grant Report Series, 308. Boulder, CO: Natural Hazards Center, University of Colorado Boulder. Available at: https://hazards.colorado.edu/quick-response-report/covid-19