Abstract
This article provides information on multiple interventions related to occupational therapy to improve QoL among autistic people.
Quality of life (QoL) is at the core of occupational therapy (American Occupational Therapy Association [AOTA], 2020b). Occupational therapy providers are well suited to address the potential QoL issues experienced by autistic people, 1 particularly adolescents and adults. However, the majority of studies of QoL among people with autism have focused on parent or proxy reporting and have not always emphasized the inclusion of autistic women and girls. These are key gaps, because self-reported QoL should be the basis on which occupational therapy practitioners approach clients and design interventions, and women and girls likely represent a larger proportion (1:3–4) of people on the autism spectrum than previously suggested (Loomes et al., 2017; Maenner et al., 2020). With occupational therapy’s principles of beneficence, autonomy, and justice (AOTA, 2015), an emphasis on autistic women and girls encourages equitable opportunities for both genders, and an emphasis on self-reports allows the autistic person’s voice to be heard rather than that of a reporter. The purpose of this rapid review is to provide a better understanding of the QoL and needs of autistic adolescents and adults and of the malleability of QoL in response to intervention, particularly with respect to autistic women and girls, allowing occupational therapy providers to more effectively implement therapeutic interventions for autistic people across the lifespan.
QoL is a multidimensional construct that includes the domains of emotional well-being, interpersonal relationships, material well-being, personal development, physical well-being, self-determination, social inclusion, and rights (Schalock, 2000). Gauging a client’s current and ideal QoL is an important part of the occupational profile (AOTA, 2020b). Not only do occupations, client factors, performance skills, performance patterns, and context and environment influence overall QoL, but QoL is a designated outcome of occupational therapy.
Occupational therapy practitioners should also consider the QoL of autistic people in the development of assessment and intervention tools. Occupational therapy–relevant interventions that address QoL have recently emerged in the literature (Curtin et al., 2016; García-Villamisar & Dattilo, 2010; Hesselmark et al., 2014; Holmefur et al., 2019; Jamison & Schuttler, 2017; Nadig et al., 2018; Siew et al., 2017; Wentz et al., 2012), but converging evidence across studies is needed to determine the degree to which QoL can be improved through intervention with autistic adolescents and adults. Occupational therapy practitioners have the potential to fulfill societal needs through a focus on education and supports that might improve QoL among autistic people with services provided across settings and ages. Specific education and program development is necessary for autistic people across the lifespan. Research on autistic adolescents and adults is clearly lacking, despite the fact that autism is a lifelong condition (Roux et al., 2015).
Many girls do not receive an autism diagnosis as a result of diagnostic methodology that uses a male sample for standardization and male bias in research samples (Frazier et al., 2014; Halladay et al., 2015; Hiller et al., 2014; Ratto et al., 2018). There are sex differences 2 in self-reported QoL for the nonautistic population, with women and girls typically demonstrating decreased QoL in comparison with male counterparts (da Rocha et al., 2014; Lee et al., 2020). However, less is known about discrepancies in QoL between genders in the autistic population, although research suggests that autistic people demonstrate decreased QoL in comparison with nonautistic people (Ayres et al., 2018).
When research does include autistic women, it does not always include the self-reports of autistic adolescents and adults. Emphasizing the need for self-reports, whether in isolation or in conjunction with proxy reports, prioritizes client autonomy and personal perception (AOTA, 2015; Erez & Gal, 2020; Fujiura & RRTC Expert Panel on Health Measurement, 2012). This rapid review contributes to the profession’s understanding of the needs of both male and female autistic adolescents and adults and how to design interventions that promote QoL for all autistic people.
Previous systematic reviews of QoL among autistic adolescents and adults (Ayres et al., 2018; Tobin et al., 2014; van Heijst & Geurts, 2015) have concluded that they demonstrate lower QoL in comparison with their nonautistic counterparts. Another review (Kim & Bottema-Beutel, 2019) found that social functioning was most correlated with QoL, whereas Tobin et al. (2014) focused on the interaction between social functioning and QoL among autistic adolescents and adults. However, these reviews did not always include self-report measures or a specific percentage of female participants, or they did not make conclusions related to occupational therapy practice.
To fill this key gap, our review emphasizes the use of self-reports and the inclusion of autistic females in the context of occupational therapy practice. Specifically prioritizing the inclusion of autistic females emphasizes the value of their voice in autism research, which has not always been intentionally amplified. As such, their inclusion allows for a better understanding of well-being on the autism spectrum across the sexes. Self-reported and perceived QoL is important in gauging someone’s viewpoint and can be obtained through subjective QoL measures, rather than objective QoL measures that focus more on external factors such as physical health, neighborhood quality, or other predictors (Bishop-Fitzpatrick et al., 2016; Fakhoury & Priebe, 2002; Hong et al., 2016). However, self-reported subjective QoL is an identified issue in autism research (Hong et al., 2016), with some studies indicating that autistic people experience difficulties that make it challenging to obtain accurate information related to symptoms and experiences (Mazefsky et al., 2011) and other findings indicating that autistic people respond accurately on self-report measures (Ozsivadjian et al., 2014).
Current Centers for Disease Control and Prevention (CDC) data (Maenner et al., 2020) indicate that 33% of children with autism also have an intellectual disability (ID). When research involves people with ID, self-reports are often avoided to accommodate difficulties with reliability and validity, particularly considering the high amount of meta-cognition needed for self-report (Fujiura & RRTC Expert Panel on Health Measurement, 2012). However, these challenges can be accommodated, including modification of question structure, length, and response type and ensuring comprehension, although these modifications lead to the conclusion that a general, unmodified “one-size-fits-all” measure is inadequate and may not apply to everyone in the world (Fujiura & RRTC Expert Panel on Health Measurement, 2012). Therefore, this review includes studies with participants with both autism and ID.
The objectives of this review were to (1) identify QoL differences between autistic and nonautistic samples on the basis of self-report; (2) investigate the existing literature on whether there are sex differences in the QoL of autistic people; (3) review the currently available literature related to consistency of QoL when considering age, presence of ID, and use of self- versus self- and proxy-reported QoL; and (4) review currently available interventions in the domain of occupational therapy practice to address QoL among autistic adolescents and adults. We hypothesized that self-reported QoL scores of autistic adolescents and adults will be lower than those of nonautistic adolescents and adults; autistic females will experience lower QoL in comparison with autistic males; QoL will be consistent across age, IQ, and report method; and interventions applicable to occupational therapy practice will improve QoL among autistic adolescents and adults.
Method
Search Strategy
We performed a rapid review of the literature to identify QoL differences in the autistic population. In contrast to lengthier systematic reviews, rapid reviews focus on a timely and targeted topic, and typically fewer databases are searched to produce a review in shorter amount of time (Dobbins, 2017; Haby et al., 2016; Harker & Kleijnen, 2012). However, whenever possible, we made an effort to conform to systematic review guidelines. We included peer-reviewed articles published in English between January 2010 and April 2020. Figure 1 shows the flow of articles that were identified, screened, and deemed eligible for inclusion in the review. Under the guidance of a university-affiliated research librarian, the team conducted a search of Academic Search Ultimate, PubMed, and OTseeker, along with journal-based searches of the American Journal of Occupational Therapy, British Journal of Occupational Therapy, Canadian Journal of Occupational Therapy, and Australian Occupational Therapy Journal. Searching occupational therapy–specific journals separately ensured that any information disseminated via these resources was included in the review. These journals were selected because of their lifespan focus, in contrast with journals geared to the pediatric population. Academic Search Ultimate, OTseeker, and all journal searches used the following search terms: “autis*” (to include both autism and autistic) and “quality of life” or “autis*” and “well-being.” PubMed searches used MeSH terms: “Self Report,” “Female,” “Autism Spectrum Disorder” OR “Autistic Disorder” OR “Asperger Syndrome.” To further narrow the search, a peer-reviewed filter was used where available. Because of the interchangeable nature of quality of life and well-being in the early stages of the research, we used both terms. Emails to corresponding authors and interlibrary loan were used to provide access to articles as needed.
Flow diagram of articles identified, screened, eligible for, and included in the review.
Selection Criteria
To advance beyond the title phase of screening, an article needed to have autis* (autism or autistic) in its title. If it did not, then the abstract was reviewed for explicit mention of autism. If the title or abstract did not include autis*, the article was excluded. Similarly, for the abstract phase of screening, the article needed to include autis* and quality of life or well-being in the title or abstract. If there was no mention of quality of life or well-being in the abstract, the article was reviewed to determine whether the text included a clear mention of them. If there was no clear reference to these terms, the article was excluded. To be included in the final phase of screening (full-text articles), articles needed to have an autistic sample that was at least 20% female, included adolescents and adults (age of all participants ≥13 yr), and included at least one self-reported measure of QoL. The 20% female threshold was selected conservatively on the basis of the lowest current estimated male-to-female prevalence figures (Maenner et al., 2020), although the current estimated male-to-female prevalence of autism can vary greatly (Fombonne, 2009). Proxy reports were included if the study also included self-reports. Self-report measures could be performed in addition to parent or proxy reports.
Data Extraction
Initial article data (from the beginning of search through total articles included) were extracted by one of two authors (Emily C. Skaletski or Laura Bradley). This information included the author names, title, DOI, source (database or journal), year, whether the article included self-reported QoL measures, and whether the article’s autistic sample consisted of 20% or more women or girls. When unsure whether an article should be included, these authors reached consensus, with Brittany G. Travers serving as a final reviewer for articles as needed. Appendix Tables A.1, A.2, and A.3 include information extracted by the authors. All information from the included articles was coded by at least two authors.
Risk-of-Bias Assessment
Risk of bias was assessed at the study level. The Oxford Levels of Evidence (Oxford Centre for Evidence-Based Medicine Levels of Evidence Working Group, 2011) were used to determine the level of evidence (1–5) for each article (AOTA, 2020a). Level 1 indicates the most rigorous study design and Level 5 the least rigorous. In the process of considering study design, a key step before assessing risk of bias, 3 articles were determined to be Level 1B (well-designed randomized controlled trials [RCTs]); the remaining articles were Level 3B or 4 (case–control, cohort, and cross-sectional studies).
Articles were assessed with one of two risk-of-bias criteria sets: (1) RCT or non-RCT or (2) pretest–posttest uncontrolled, which was also used for studies that were descriptive in nature. The use of pretest–posttest uncontrolled criteria for descriptive studies poses a potential issue with risk-of-bias assessment, but this category was decidedly the best fit for these types of studies, which are already higher in bias and do not fit many of the categories of the RCT and non-RCT criteria. Risk of bias is an important consideration in determining the generalizability, reliability, and validity of studies because it determines whether a study was well constructed and whether the results are truly a result of the intervention or experience of those with a diagnosis. Further discussion of risk of bias can be found in the Results section.
Results
From the original search, we identified 1,070 studies. After removing duplicates, 803 articles remained. Of these studies, 220 were excluded because they did not have autis* (autism or autistic) in the title or abstract. Next, 57 were excluded because they did not have quality of life or well-being in the abstract or full article. The full text of the 526 remaining articles was reviewed, and 499 were excluded (Figure 1). A total of 27 articles were included in the final review (Table A.1). Sixteen did not mention IQ or include participants with co-occurring ID. Seven articles excluded participants with a co-occurring ID or an IQ < 70. Only 4 studies included participants with co-occurring ID, so generalizing to the autistic population with a co-occurring ID should be done with caution.
Risk of Bias
Tables A.2 and A.3 indicate the risk of bias for each of the studies included in the rapid review. Included articles were primarily low in risk of bias, with some moderate in risk. Most studies were case–control, case series, or cohort studies, which are lower in overall quality and have different standards for risk of bias. As such, these types of studies with low risk of bias should not be considered to have the same level of generalizability, reliability, and validity as an RCT systematic review with low risk of bias. The average sample size for included articles was 336 (range = 9–2,341); 7 studies had a sample sizes of <50, and 13 had a sample size <100. Convenience sampling was predominantly used as a recruitment method, which further increases the risk of bias.
Measurement
A wide range of QoL instruments were used in the included studies, but three instruments were used in 4 or more studies: the Quality of Life Questionnaire (QOL; Schalock & Keith, 1993), Satisfaction With Life Scale (SWLS; Diener et al., 1985), and the World Health Organization Quality of Life–Brief Version (WHOQOL–BREF; WHOQOL Group, 1998). The SWLS has not been validated with the autistic population. The QOL was validated with the intellectual and developmental disabilities population, although whether participants had an autism diagnosis was not discussed and thus cannot be assumed (Caballo et al., 2005). The WHOQOL–BREF has been validated with the autistic population (α = .93; McConachie et al., 2018).
Findings
Nonintervention Studies
Nineteen articles were exploratory and descriptive in nature. Of these 19 studies, 3 had samples whose mean age was <20 yr. Jamison and Schuttler (2015) used self-reports of QoL, and Franke et al. (2019) and Mahfouda et al. (2019) used both self- and proxy reports of QoL. Autistic adolescents experience reduced QoL and life satisfaction compared with their peers, which was found with a male and female sample, a female-only sample, and a gender-diverse sample (Jamison & Schuttler, 2015; Franke et al., 2019; Mahfouda et al., 2019, respectively).
Seven nonintervention studies included participants whose mean age was in the 20s. Four studies used self-report QoL measures (Lin, 2014; Lin & Huang, 2017; Rodgers et al., 2018; White et al., 2018). The remaining 3 articles used self- and proxy reports (Kamio et al., 2013; Knüppel et al., 2018; Pearlman-Avnion et al., 2017). In Lin’s (2014) study, autistic adults demonstrated lower QoL than a nonautistic control group and a Taiwanese health population reference group. Knüppel et al. (2018) specifically reported that self-reported QoL tended to be slightly higher than proxy-reported QoL.
Seven nonintervention studies included participants whose mean age was in the 30s. Four of these articles solely used self-reported measures of QoL (Hull et al., 2019; Leader et al., 2018; Mazurek, 2014; McDonald, 2017). The 3 remaining articles used proxy- and self-reported measures of QoL (Deserno et al., 2017; Hong et al., 2016; McConachie et al., 2018). Autistic adults demonstrated decreased QoL compared with the general population (McConachie et al., 2018) and reliably rated their QoL (Hong et al., 2016).
Two nonintervention articles included participants whose average age was in the 40s. Grove et al. (2018) examined QoL using self-reports exclusively, whereas Mason et al. (2018) used both self- and proxy reports of QoL. Autistic adults experienced lower QoL than nonautistic peers, with female sex being a predictor of reduced QoL (Mason et al., 2018).
Intervention Studies
Eight studies examined the effectiveness of an intervention, typically in an effort to improve QoL. Nearly all of these studies used different QoL outcome measures, which poses some difficulty in considering the results collectively. Of the 8 studies, 3 were appraised as Level 1B (RCTs; García-Villamisar & Dattilo, 2010; Hesselmark et al., 2014; Nadig et al., 2018). However, Nadig et al. (2018) elected not to complete statistical analysis because of their small sample size (n = 26). Three studies included participants with a mean age <20 yr (Curtin et al., 2016; Jamison & Schuttler, 2017; Siew et al., 2017). Curtin et al. (2016) had a small sample size (n = 9), so interpretation of inference tests of QoL changes was not possible. In addition, this study used both self- and proxy reports of QoL, the only intervention study to use both reporting methods. The remaining intervention studies solely used self-reports of QoL.
Three studies used informal or formal mentoring (Curtin et al., 2016; Jamison & Schuttler, 2017; Nadig et al., 2018). QoL was significantly improved postintervention (social and self-care skills group, Girls Night Out; Jamison & Schuttler, 2017), as was perceived social support (Nadig et al., 2018). The remaining 5 studies included participants whose mean ages were in the 20s and 30s; each study used a specific tool or program: customized leisure programming (García-Villamisar & Dattilo, 2010), an organization and executive functioning program (Let’s Get Organized; Holmefur et al., 2019), cognitive–behavioral therapy and recreational activity (Hesselmark et al., 2014), a college mentoring program (Siew et al., 2017), and an online support and coaching program (Wentz et al., 2012). Collectively, these studies suggest that QoL can be improved in the autistic population across a variety of programs and interventions and for a wide range of ages.
Discussion
The objectives of this rapid review were to identify differences in QoL between autistic and nonautistic people, determine any discrepancies in QoL between the sexes, evaluate whether these results are consistent across age and IQ and between self- and proxy-reported QoL, and examine interventions applicable to occupational therapy to address QoL among autistic people. Similar to previous research (Ayres et al., 2018; Kim & Bottema-Beutel, 2019; Tobin et al., 2014; van Heijst & Geurts, 2015) and supporting our first hypothesis, we found that QoL was lower among autistic compared with nonautistic adolescents and adults (Franke et al., 2019; Jamison & Schuttler, 2015; Lin, 2014; Lin & Huang, 2019; Mahfouda et al., 2019; Mason et al., 2018; McConachie et al., 2018). However, our review expands on this previous research, finding that decreased QoL was consistent across self-reported or a combination of self- and proxy-reported QoL, with samples including autistic females and participants with ID. As mentioned previously, although these results indicate that autistic participants with ID reported decreased QoL similar to that of autistic participants without ID, only 4 articles explicitly included participants with ID, which limits the generalizability of the results to participants with ID.
In an effort to get a representative sample of autistic women and girls, all studies included in the review had to have an autistic sample consisting of 20% or more female participants. However, we could not specifically determine whether QoL is decreased among autistic women and girls, because only 1 study directly compared sex differences in QoL among autistic people. To be specific, 1 Level 4 study determined that being female was a predictor of lower QoL among autistic adults (Mason et al., 2018), which is consistent with findings with nonautistic samples (da Rocha et al., 2014; Lee et al., 2020). However, a finding from a single study that used a convenience sample is insufficient to make conclusions about the impact of sex on self-reported QoL, particularly given this study’s high risk of bias.
Notably, of all the included studies, just 3 had only female participants, which did not allow for analysis of the differences in QoL between the sexes (Jamison & Schuttler, 2015, 2017). As such, there remains a key gap in the literature regarding whether autistic females experience reduced QoL in comparison with autistic males. A critical area of future research will be to examine QoL among autistic females, with an emphasis on large sample sizes and random sampling from the population of autistic people. Direct comparison of QoL between autistic females and males is essential because of the documented decreased QoL among nonautistic women (da Rocha et al., 2014; Lee et al., 2020) and the corresponding health-related consequences (CDC, 2018).
Our findings indicate that QoL is malleable, with numerous previously studied interventions applicable to occupational therapy that improved QoL among autistic adolescents and adults. These interventions include in-person and online mentoring and support, leisure programming, cognitive–behavioral therapy, cognitive strategy education (Let’s Get Organized), social and self-care skills development (Girls Night Out), and recreational activity (Curtin et al., 2016; García-Villamisar & Dattilo, 2010; Hesselmark et al., 2014; Holmefur et al., 2019; Jamison & Schuttler, 2017; Nadig et al., 2018; Siew et al., 2017; Wentz et al., 2012). Mentoring programs integrated the use of nonautistic peers as mentors, which may be a method to improve social participation while influencing QoL outcomes. Two intervention studies had authors who were either occupational therapists or affiliated with an occupational therapy program: a mentoring program (Siew et al., 2017) and a cognitive strategies program, Let’s Get Organized (Holmefur et al., 2019), that emphasizes the value of QoL intervention in occupational therapy practice.
Ultimately, QoL for autistic adolescents and adults is poorer than for their nonautistic counterparts, which is consistent across age, presence of ID, and self-report. QoL is a significant predictor of current and future health (CDC, 2018), and its consideration for the autistic population is critical, given known health disparities among autistic people (Bishop-Fitzpatrick & Kind, 2017). This rapid review indicates that multiple occupational therapy–related interventions can improve QoL among autistic people (Curtin et al., 2016; García-Villamisar & Dattilo, 2010; Hesselmark et al., 2014; Holmefur et al., 2019; Jamison & Schuttler, 2017; Nadig et al., 2018; Siew et al., 2017; Wentz et al., 2012).
Limitations
The main limitation of this review is the streamlined process of a rapid review in comparison with a more comprehensive systematic review. However, rapid reviews allow for a more efficient dissemination of information to stakeholders, which is critical in the current health care climate. In addition, the majority of the articles were Level 3B and 4, although this was expected given the descriptive nature of our objectives. The majority of articles either excluded people with ID or with an IQ <70 or did not consider or mention the number of those with ID or an IQ <70, which is a limitation to generalizability across the autism spectrum. There is a high risk of bias because of convenience sampling, small sample sizes, and flaws in study protocol and development. However, the lower QoL experienced by the autistic population is clear and has been demonstrated in numerous studies.
Implications for Occupational Therapy Practice
Occupational therapy practitioners must promote the autonomy of their clients and justice in practice. This emphasizes the need for integration of QoL into assessment and intervention. It is clear that autistic people have reduced QoL in comparison with nonautistic population, which places them at risk for additional health concerns. Recommendations for occupational therapy practice include the following:
Emphasize QoL when gathering an occupational profile, as recommended in the Occupational Therapy Practice Framework: Domain and Process—Fourth Edition (AOTA, 2020b), and whenever a plan of care or service reevaluation occurs.
Use outcome measures that are current, evidence based, reliable, and valid and, whenever possible, provide an opportunity for self-reporting.
Proactively consider QoL impacts when working with autistic individuals, groups, and populations, including consideration of client age and lifespan priorities.
Implement evidence-based treatment approaches for improvement in QoL, such as mentoring, leisure programming, cognitive–behavioral therapy, and recreational activity; programs for education on the use of cognitive strategies (Let’s Get Organized), social skills and self-care programming (Girls Night Out), and online support and coaching programming may be suitable for clinical occupational therapy practice.
Conclusion
Future research must address the knowledge gap related to self-reported QoL of autistic girls and women to promote autonomy and beneficence. These findings are valuable for a variety of stakeholders, including health care professionals, policy makers, and funders. Health care providers (including occupational therapy practitioners) should place QoL at the forefront when caring for autistic clients. This QoL assessment should, whenever possible, be done with specific questions and use of self-report measures. Policy makers and funders need to consider the expansion of autistic supports throughout the lifespan, particularly for those people who may not qualify for established federal and state support systems.
Footnotes
Acknowledgments
We acknowledge Mary Hitchcock of the Ebling Library for the Health Sciences at the University of Wisconsin–Madison for her assistance in the article search process for this review. This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD; U54 HD090256 to the Waisman Center) and the National Center for Advancing Translational Sciences (NCATS; UL1TR002373, KL2TR002374, and KL2TR00428). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NICHD or NCATS.
Appendix
Risk-of-Bias Table for Before–After (Pretest–Posttest) Studies With No Control Group and Other Designs
| Citation | Study Question or Objective Clear | Eligibility or Selection Criteria Clearly Described | Participants Representative of Real-World Patients | All Eligible Participants Enrolled | Sample Size Appropriate for Confidence in Findings | Intervention Clearly Described and Delivered Consistently | Outcome Measures Prespecified, Defined, Valid/Reliable, and Assessed Consistently | Assessors Blinded to Participant Exposure to Interventions | Loss to Follow-Up After Baseline 20% or less | Statistical Methods Examined Changes in Outcome Measures From Before to After intervention | Outcome Measures Were Collected Multiple Times Before and After Intervention | Overall Risk-of-Bias Assessment (Low, Moderate, High Risk) |
| Curtin et al. (2016) | Y | Y | N | N | N | Y | Y | N | NR | Y | Y | M |
| Deserno et al. (2017) | Y | Y | N | N | Y | NR | Y | NR | NR | NR | NR | L |
| Franke et al. (2019) | Y | Y | Y | Y | N | NR | Y | NR | Y | Y | NR | L |
| Grove et al. (2018) | Y | N | N | N | Y | NR | Y | NR | NR | NR | NR | L |
| Holmefur et al. (2019) | Y | Y | N | N | N | Y | Y | N | Y | Y | Y | M |
| Hong et al. (2016) | Y | Y | N | N | Y | NR | Y | NR | NR | NR | NR | L |
| Hull et al. (2019) | Y | Y | Y | Y | Y | NR | Y | NR | Y | Y | NR | L |
| Jamison & Schuttler (2015) | Y | Y | Y | Y | N | NR | Y | NR | Y | Y | NR | L |
| Jamison & Schuttler (2017) | Y | Y | Y | NR | Y | NR | Y | NR | Y | Y | NR | L |
| Kamio et al. (2013) | Y | Y | N | N | Y | NR | Y | NR | NR | NR | NR | L |
| Knüppel et al. (2018) | Y | Y | Y | NR | Y | NR | NR | NR | NR | NR | NR | L |
| Leader et al. (2018) | Y | Y | NR | Y | Y | NR | Y | NR | NR | Y | NR | L |
| Lin (2014) | Y | Y | Y | Y | Y | NR | NR | NR | NR | NR | NR | L |
| Lin & Huang (2019) | Y | Y | Y | Y | Y | NR | Y | NR | NR | Y | NR | L |
| Mahfouda et al. (2019) | Y | Y | N | N | Y | NR | Y | NR | NR | NR | NR | L |
| Mason et al. (2018) | Y | Y | Y | Y | Y | NR | Y | NR | Y | Y | NR | L |
| Mazurek (2014) | Y | Y | N | NR | Y | NR | Y | NR | NR | NR | NR | L |
| McConachie et al. (2018) | Y | Y | Y | Y | Y | NR | Y | NR | Y | Y | NR | L |
| McDonald (2017) | Y | Y | Y | N | Y | NR | Y | NR | NR | Y | NR | L |
| Pearlman-Avnion et al. (2017) | Y | Y | NR | N | N | NR | Y | NR | NR | Y | NR | L |
| Rodgers et al. (2018) | Y | Y | N | NR | Y | NR | Y | NR | NR | Y | NR | L |
| Siew et al. (2017) | Y | Y | Y | Y | N | N | Y | N | Y | Y | NR | L |
| Wentz et al. (2012) | Y | Y | Y | Y | N | N | Y | N | Y | Y | NR | L |
| White et al. (2018) | Y | Y | N | Y | N | NR | Y | NR | NR | Y | NR | L |
Note. N = no; NR = not reported; Y = yes. Scoring for overall risk-of-bias assessment is as follows: 0–3 N, low risk of bias (L); 4–8 N, moderate risk of bias (M); 9–11 N, high risk of bias. Risk-of bias table format adapted from National Heart Lung and Blood Institute. (2014). Quality assessment tool for before-after (prepost) studies with no control group. Retrieved from https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools
Copyright © 2021 by the American Occupational Therapy Association. This table may be freely reproduced for personal use in clinical or educational settings as long as the source is cited. All other uses require written permission from the American Occupational Therapy Association. To apply, visit www.copyright.com.
Suggested citation: Skaletski, E. C., Bradley, L., Taylor, D., Travers, B. G., & Bishop, L. (2021). Quality-of-life discrepancies among autistic adolescents and adults: A rapid review (Table A.3). American Journal of Occupational Therapy, 75, 7503180090. https://doi.org/10.5014.ajot.2021.046391
In consideration of the preference of those in this diagnostic population, we primarily use identity-first language (e.g., autistic) in this article (Kenny et al., 2016). Quality of life and well-being are used interchangeably.
In this article, we use sex differences, except when articles have used gender differences, in consideration of gender-diverse samples.
*
Indicates articles included in the rapid review.