Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2025 Nov 1.
Published in final edited form as: J Intellect Disabil Res. 2024 Aug 12;68(11):1316–1330. doi: 10.1111/jir.13182

Description and Predictors of Self-Determination in Males and Females with Fragile X Syndrome on the Verge of Adulthood

Laura Friedman 1, Carly Moser 1, Angela John Thurman 2, Julie Lounds Taylor 3, Leonard Abbeduto 2, Jessica Klusek 1
PMCID: PMC11881981  NIHMSID: NIHMS2053855  PMID: 39134393

Abstract

Background

Self-determination refers to setting goals and making decisions regarding one’s own life with support from others as needed. Research on people with intellectual and developmental disabilities (IDDs) has established the importance of self-determination for quality of life outcomes, such as increased independence and life satisfaction. However, self-determination has not been characterized specifically in fragile X syndrome (FXS), the leading inherited cause of intellectual disability. Relative to youth with other forms of IDDs, youth with FXS may face exceptional barriers to the development of self-determined behaviour. In addition to intellectual disability, the FXS behavioural profile is characterized by high rates of autism and anxiety that may further limit opportunities for youth with FXS. The heritable nature of the condition can also yield a distinctive family environment, with siblings and parents also living with fragile X or its associated conditions. Considering these unique challenges, the present study examined self-determination in young adult males and females with FXS, and explored whether factors such as language skills, adaptive behaviour, and autism traits were associated with self-determination capacity and opportunities.

Methods

The present study included nine females and 36 males with FXS between the ages of 17 and 25 years. Caregivers (mothers or fathers) completed the AIR Self-Determination Assessment, which is a questionnaire that yields three scores: self-determination capacity, opportunities for self-determination at home, and opportunities for self-determination at school.

Results

Caregivers endorsed a wide range of self-determination capacity and opportunities, with ratings for opportunities at home and school exceeding ratings of capacity. Better adaptive behaviour skills were associated with more self-determination capacity, and the presence of more autism traits was associated with fewer opportunities at school.

Conclusions

Results from this study contribute to our understanding of avenues to best support young adults with FXS as they transition to adulthood. Our findings also have implications for practice, such that intervention targeting adaptive behaviours and self-determination may be an effective approach for promoting autonomy and independence for young adults with FXS. Additionally, caregivers and educators should continue to provide opportunities to practice self-determination, regardless of their perception of capacity.

Keywords: fragile X syndrome, self-determination, intellectual disability, FMR1, transition to adulthood, autism

Background

According to Causal Agency Theory, self-determination is characterized by a person (a causal agent) making and acting on self-chosen goals (Shogren et al., 2015). Being a causal agent requires that one develop the capacity to perform self-determined actions as well as be provided with opportunities and supports to express self-determination and make autonomous decisions (Shogren et al., 2015). Self-determination is one of the most important predictors of quality of life for individuals with intellectual and developmental disabilities (IDDs) with links to employment outcomes, access to healthcare, and financial and residential independence (Wehmeyer and Palmer, 2003; Wehmeyer, 2015; White, Flanagan and Nadig, 2018). For individuals without IDDs, the transition from high school to adult life is a critical time for developing self-determination skills, which include problem-solving, goal setting, and self-monitoring, so that one can play an active role in planning one’s future. However, youth with IDDs are often excluded from discussions and decisions about their future after high school, including from whether they would like to participate in vocational training, post-secondary education, or pursuit of employment. Excluding youth with IDDs from these conversations can limit their opportunities to learn and practice self-determination skills (Knox and Bigby, 2007; Leonard et al., 2016). The development of self-determination can support self-advocacy, which not only impacts participation in transition planning, but also promotes community participation and the development of a positive self-identity (Anderson and Bigby, 2017). Despite the importance of self-determination for those with IDDs, we lack data on self-determination and the factors that predict self-determination in individuals with fragile X syndrome (FXS), which is the leading inherited cause of intellectual disability (ID). Exploring self-determination in those with FXS is a key step toward identifying whether current systems in the adult transition period are adequately supporting their preparation for an adult life of their choosing. The present study sought to fill this gap in knowledge by describing the self-determination skills of young adults with FXS, as well as identify the factors that influence self-determination for individuals with this condition.

FXS affects 1 in 3,600 males and 1 in 4,000–6,000 females and is caused by an expansion of trinucleotide CGG repeats on the fragile X messenger ribonucleoprotein-1 (FMR1) gene on the X-chromosome (Verkerk et al., 1991; Crawford, Acuña and Sherman, 2001; Oostra and Willemsen, 2003; Coffee et al., 2009). This repeat expansion (200+) reduces the production of FMRP, which is necessary for brain development (Verkerk et al., 1991). Because of the higher levels of FMRP resulting from possession a second, unaffected, X-chromosome in females, they are differentially affected compared to males. The vast majority of males with FXS have moderate to severe ID (IQ < 55), and approximately 11% of males with FXS score in the mild ID range on full-scale IQ assessments (Hessl et al., 2009). Most females have borderline-average IQ scores, whereas only 20–25% have IQs below 55 (Hagerman et al., 1992; Hessl et al., 2009). Similarly, most males and some females with FXS have limitations in language, such as challenges with vocabulary and grammar production and comprehension (Roberts, Mirrett and Burchinal, 2001; Roberts et al., 2007; Brady et al., 2020). Additionally, up to 75% of males and 25% of females meet criteria for co-occurring autism spectrum disorder (Clifford et al., 2007; Klusek, Martin and Losh, 2014; Haebig et al., 2020; Klusek et al., 2023).

Researchers have worked to characterize the phenotypic profile of children with FXS over the last three decades. However, our knowledge of adult outcomes remains limited. A 2011 survey of caregivers found that up to 90% of men and 55% of women with FXS do not live independently, and 40% of men and 27% of women are unemployed (Hartley et al., 2011). Despite its known association with outcomes such as independence and employment status (Wehmeyer and Palmer, 2003; Wehmeyer, 2015; White, Flanagan and Nadig, 2018), the nature of self-determination in young adults with FXS remains largely unexplored. Information on self-determination in FXS is necessary to determine the nature and extent of interventions needed to promote better adult outcomes (Shogren et al., 2018, 2019).

Self-determination can be conceptualized as consisting of two components: capacity and opportunities (Wolman et al., 1994). Capacity includes the actions one takes to demonstrate self-determination (e.g., identifying likes and dislikes, setting goals, monitoring progress toward goals). Opportunities are the chances provided to use self-determination abilities (e.g., encouragement to set own goals, freedom to act on goals), whether at home, school, or other contexts. Often, more opportunities to exercise self-determination ultimately yields increased capacity (Wehmeyer et al., 2013; Vicente et al., 2020). This indicates the need for educators and caregivers to provide ample and appropriately scaffolded opportunities to practice self-determination, regardless of their perceived level of one’s capacity. Interventions, such as the Self-Determined Learning Model of Instruction (SDLMI; Wehmeyer, Palmer, Agran, Mithaug, & Martin, 2000), have been developed based on this premise (see Burke et al., 2020 for a meta-analysis on self-determination intervention research). The SDLMI is an evidence-based, educator-delivered intervention that is designed to expand opportunities for self-determination in school settings, resulting in increased self-determination capacity for young adults with ID (Shogren et al., 2012; Wehmeyer et al., 2013). An important consideration for intervention is the set of factors that have been found to be related to self-determination capacity and opportunities in adolescents and young adults with autism and/or ID. For example, autism traits (Cheak-Zamora et al., 2020; Tomaszewski et al., 2020), challenging behaviours, poorer adaptive behaviours (Carter et al., 2009, 2013; Tomaszewski et al., 2020), and lower verbal communication skills (Cheak-Zamora et al., 2020) all predict both decreased capacity and opportunities for self-determination. Understanding variables that might support the development of self-determination can inform which personal aspects to consider when developing intervention goals.

Despite this robust body of research on self-determination in people with IDDs in general, only one study has started to describe self-determination in young adults with FXS (Abbeduto et al., 2021a). This paper presented early findings from the first 12 young adults with FXS who contributed data to the larger sample described in the present study. That study aimed to determine whether expressive language skills in young adults with FXS were associated with several concurrently measured indicators of independence, including self-determination. Expressive language skills, as indicated by syntactic skills and lexical diversity measured from a conversational language sample, were associated with self-determination in the youth with FXS. These findings are consistent with research in other individuals with IDDs (Cheak-Zamora et al., 2020), though further research is needed to fully understand the profile and predictors of self-determination in youth with FXS, which may show syndrome-specific patterns that are relevant for intervention. FXS has a distinct behavioural profile relative to other IDD groups, and is characterized by increased autism traits, anxiety, and challenging behaviours which could affect self-directed behaviour as well as opportunities provided in school settings (Kaufmann et al., 2004; Tsiouris and Brown, 2004; Carter et al., 2009; Tomaszewski et al., 2020). Additionally, youth with FXS have a unique home environment, as families often have multiple affected children due to the heritability of FXS, and mothers carry the FMR1 genetic premutation, which presents with its own set of clinical and psychological features (Wheeler et al., 2014; Abbeduto et al., 2021b; Bangert et al., 2021). These factors may yield fewer opportunities to practice self-determination at home, due to increased demands on time for those with multiple affected children, as well as potential executive function challenges mothers may be experiencing.

The present study extends the earlier report (Abbeduto et al., 2021a) through more focused investigation of self-determination in the full study sample of 45 young adults with FXS, including analysis of both capacity and opportunities as well as the exploration of concurrent associations between self-determination and adaptive behaviours, autism traits, and expressive language ability. Given that those with FXS experience poor adult outcomes such as limited rates of employment and independence, and that self-determination is a known predictor of adulthood outcomes in other populations, self-determination is an important construct to carefully study in young adults with FXS (Hartley et al., 2011; Thurman et al., 2022). Moreover, understanding self-determination and the factors associated with self-determination in young adults with FXS can help highlight areas in which caregivers and providers need to construct more opportunities to develop this skill, which could have broader downstream impacts on quality of life and later adulthood outcomes. Therefore, the present study addressed two aims:

  1. Describe the profile of self-determination capacity, as well as opportunities to practice self-determination, in young adult men and women with FXS.

  2. Examine concurrent associations between self-determination, adaptive behaviours, autism traits, and expressive vocabulary to gain insight into which skills may support self-determination. We hypothesized that more mature adaptive behaviours, fewer autism traits, and better expressive vocabulary would be associated with self-determination capacity and opportunities.

Methods

Participants

The present sample was comprised of 45 young adults with FXS (36 males, 9 females) between 17 and 25 years of age, who were drawn from the baseline timepoint of a larger longitudinal study with annual assessments. The larger study was focused on language in transition-age youth with FXS that overlaps with the sample from the prior report on self-determination skills (Abbeduto et al., 2021a). The present study includes a subset of measures that were administered within the larger study battery. Those with completed AIR Self-Determination Assessment questionnaires (Wolman et al., 1994) at the baseline timepoint of the larger study were included in the present study. Participants were recruited nationally through the National Fragile X Foundation, the research participant registries of the University of California Davis Mind Institute Intellectual and Developmental Disabilities Research Center (P50HD103526), the Vanderbilt University Medical Center, and the Carolina Center for Developmental Disabilities, as well as through social media posts. The inclusionary criteria for the larger study were that participants were: 1) previously diagnosed with the FMR1 full mutation (with or without mosaicism); 2) in their final year of high school, including the summer before or up to six months following their final year (this includes either grade 12 or their final year of participation in a school-based transition program, which are available for students with disabilities until they age-out at 21 to 26 years of age depending on state law); 3) living with their participating caregiver at the baseline assessment; 4) using English as their primary language; and 5) using speech as their primary method of communication with at least some spontaneous three-word phrases according to parent report, which was required given the larger study’s focus on language skills. Table 1 includes participant characteristics and demographic information.

Table 1.

Participant Descriptive Information

Males n=36 Females n=9 Total Sample n=45
Age 20.84 (1.67)
[18.04 – 25.89]		 19.40 (1.65)
[17.80 – 22.17]		 20.55 (1.74)
[17.80 – 25.89]
Stanford-Binet 5th Edition – Brief IQ scorea 48.70 (5.86)
[47–73]		 63.20 (22.14)
[47–100]		 51.60 (12.00)
[47–100]
Race (%)
 Asian
 African-American
 Caucasian
 More than one race
6%
0%
86%
8%
0%
13%
87%
0%
5%
2%
86%
7%
Ethnicity (%)
 Hispanic or Latino
 Non-Hispanic or Latino
9%
91%
0%
100%
7%
93%
Household Income (%)
 $0-$50,000
 $50,001-$100,000
 $100,001-$150,000
 >$150,000
6%
36%
15%
43%
0%
13%
37%
50%
5%
32%
19%
44%
Caregiver Education - % with Bachelor’s degree 78% 88% 80%
Self-Determination Total Score 57.25 (12.56)
[27–81]		 62.44 (10.44)
[41–74]		 58.29 (12.24)
[27–81]
Vineland Adaptive Behavior Scales 3rd Edition – Scaled Score 38.43 (15.35)
[20–70]		 65.67 (19.10)
[38–99]		 44.00 (19.43)
[20–99]
Expressive Vocabulary Test 3rd Edition – Standard Score 66.06 (11.91)
[40–93]		 79.50 (11.45)
[62–93]		 68.82 (12.09)
[40–93]
Social Responsiveness Scale 2nd Edition – t-score 60.22 (9.33)
[45–83]		 62.50 (11.22)
[44–83]		 60.64 (9.60)
[44–83]
Open in a new tab
a

The Stanford-Binet 5th-Edition is provided for descriptive information, but please note that this was only collected for a subset of participants (n=25; 20 males) due to COVID-19 and telehealth administration.

Procedures

Participants either completed assessments in person (n=27) or via telehealth, which was introduced during the COVID-19 pandemic (n=18). Participants who completed in-person assessments travelled to university laboratories at the University of California Davis MIND Institute, University of South Carolina, or Vanderbilt University Medical Center. Caregivers, who were mothers or fathers of the participant, completed all questionnaires either before or during the assessment on paper or online via REDCap (Harris et al., 2009, 2019). For the young adults with FXS, the in-person battery lasted between 6–8 hours and the virtual battery lasted about 1.5 hours. The parent interview took approximately 3 hours. If families participated in person, travel costs were reimbursed. For those who participated via telehealth, steps were taken to ensure a controlled remote testing environment. Caregivers were instructed to set up a computer in a quiet room to minimize distractions. Caregivers remained present throughout the assessment with the youth with FXS, with the instructions that they should not prompt or make corrections but be available to help the participant stay focused and on task. All families received monetary compensation for their time. All procedures were approved by all university Institutional Review Boards. Written consent from the caregivers of participants was obtained; all youth with FXS provided oral assent.

Measures

Self-Determination

Self-determination was assessed using the AIR Self-Determination Assessment (Wolman et al., 1994), which was completed by the caregiver. The AIR yields three scores: self-determination capacity, opportunities (for self-determination) at home, and opportunities (for self-determination) at school, each of which has a possible score range of 6–30. Self-determination capacity refers to the abilities, knowledge, and perceptions that allow one to be self-determined, whereas self-determination opportunity refers to chances available to use one’s knowledge and abilities. Using a Likert scale that ranges from “never” (1) to “always” (5), caregivers rated six items about their child’s capacity, (e.g., “my child knows what (s)he needs, likes, and is good at), six items about their opportunities at home (e.g., “at home, my child is allowed to act on his/her own plans right away”), and six parallel items about their opportunities at school (e.g., “at school, my child is allowed to act on his/her own plans right away”). Higher scores reflect greater capacity and opportunity for self-determination. This measure has excellent internal consistency (0.95; Wolman et al., 1994) and has been used frequently in populations with IDDs (Carter et al., 2009, 2013; Cheak-Zamora et al., 2020; Tomaszewski et al., 2020)

Adaptive Behaviour

The Vineland Adaptive Behavior Scales-3 (VABS-3; Sparrow et al., 2016) Comprehensive Interview version was administered to the caregiver via the publisher’s web-based platform, Pearson Q-Global. The VABS-3 assesses adaptive behaviour, which is a central area of impairment in individuals with ID. The VABS-3 Comprehensive Interview requires examiners to ask open-ended questions to assess three domains of adaptive behaviour: Communication, Daily Living Skills, and Socialization. The Adaptive Behavior Composite score is a standard score comprised of these three domains, with a mean of 100 and a standard deviation of 15. The VABS-3 was normed on individuals between birth and 90 years of age, including individuals with ID. The Adaptive Behavior Composite score has excellent internal consistency (r=.98) and inter-interviewer reliability (r=.79; Sparrow et al., 2016).

Expressive Language

Expressive language was measured using the Expressive Vocabulary Test-3 (EVT-3; Williams, 2019). The EVT-3 is a norm-referenced measure in which the participant is asked to label or provide a synonym for a picture. All participants were administered the EVT-3 via Q-Interactive, which is Pearson Assessments web-based system online administration platform for administering, scoring, and reporting assessments. In-person participants viewed stimuli on an iPad; remote participants viewed stimuli via a shared computer screen. We used standard scores in the analysis, which did not display substantial floor effects in the present sample. The EVT-3 has excellent internal consistency (r=.97) and good construct validity (r=.86).

Autism Traits

The Social Responsiveness Scale-2 Adult Form (SRS-2) was completed by caregivers as a measure of autism traits (Constantino and Gruber, 2012). This questionnaire includes 65 items about social awareness, social cognition, social communication, social motivation, and autistic mannerisms. Items are rated on a scale from 1 (not true) to 4 (almost always true). The T-scores for Social Communication and Interaction (SCI; comprised of social awareness, social cognition, social communication, and social motivation) and Restricted and Repetitive Behaviours (RRB; autistic mannerisms), as well as the total T-score, were used in the analyses. For participants under the age of 19 (n=16), which is the youngest norming age for the SRS-2 Adult Form, T-scores were based on the lowest age band in the norming manual. The SRS-2 has high internal consistency (alpha = .94-.96). Higher scores reflect higher levels of autism traits.

Approach to Analysis

Analyses were conducted in R (R Core Team, 2020). The first research question sought to describe the variation in self-determination capacity and opportunities in young adults with FXS. Therefore, descriptive statistics (means, standard deviations) were calculated for the sample as a whole, and for males and females separately. To examine factors associated with self-determination, a series of linear regressions were conducted. Each factor (i.e., adaptive behaviour, expressive vocabulary, and autism traits) was included as a singular independent variable in models predicting self-determination capacity, opportunities at home, and opportunities at school. To assess autism traits, we examined all three T-scores from the SRS-2 (total, SCI, and RRB). In total, we conducted 15 linear regression models. Due to the exploratory nature of this study, we did not correct for multiple tests. For all models with opportunities at home and opportunities at school as dependent variables, residuals were not normally distributed. Therefore, the Box-Cox transformation (Box and Cox, 1964) was applied to all models to determine the optimal normalizing transformation. All models predicting opportunities at home were transformed by λ=2.00. Models predicting opportunities at school underwent the following transformations: adaptive behaviour λ=1.72; expressive vocabulary λ=1.64; total autism traits –λ=1.76; SCI autism traits λ=1.76; RRB autism traits λ=1.72. We collapsed males and females into a single group for these analyses given the limited number of females in this study (n=9). Sex (as assigned at birth) was included as a covariate for all models. Chronological age was not associated with any self-determination outcome variable, and so age was not included as a covariate. Partial-eta squared effect sizes were calculated for all models and were interpreted as 0.01=small effect, 0.06=medium effect, 0.14=large effect (Cohen, 1988).

Results

Description of Self-Determination Capacity and Opportunities in Young Adults with FXS

To address our first research question, we examined mean scores and standard deviations for each subscale of the AIR: capacity, opportunities at home, and opportunities at school.

Capacity Scores

Capacity scores (“things my child does”) ranged from 7–21 for males (M=12.67, SD=4.27) and 9–20 for females (M=13.89, SD=4.23; see Figure 1). This indicates that both males and females had relatively low capacity scores, considering the maximum possible score on this subscale is 30. Caregivers reported that 47% of males and 44% of females were reported to “always” or “almost always” know their own needs, likes, and strengths. However, caregivers reported that 61% of males and 55% of females “never” or “almost never” set their own goals to satisfy their wants and needs. Moreover, 72% of males and 67% of females “never” or “almost never” figure out how to meet their goals independently according to caregivers.

Figure 1.

Figure 1

Open in a new tab

Average Capacity Scores with Standard Error Bars

Opportunities at Home

Scores for opportunities at home ranged from 10–30 for males (M=22.50, SD=5.19) and 22–30 for females (M=26.22, SD=2.39; see Figure 2), with the maximum score possible again being 30. This finding suggests that young adults with FXS were receiving many opportunities to practice self-determination in the home environment. At home, 72% of males and 100% of females “always” or “almost always” had people who would listen to them talk about his/her wants according to caregivers. Additionally, most caregivers reported that the youth with FXS “always” or “almost always” (72% of males, 100% of females) had someone at home to tell him/her when he/she was meeting goals.

Figure 2.

Figure 2

Open in a new tab

Average Opportunities at Home Scores with Standard Error Bars

Opportunities at School

Scores for opportunities at school ranged from 6–30 for males (M=22.08, SD=6.15) and 6–30 for females (M=22.33, SD=7.68; see Figure 3), with 30 being the maximum score possible. Thus, young adults with FXS were receiving a wide range of opportunities to practice self-determination at school, with some participants “never” receiving these opportunities. Most caregivers reported that at school, the young adult “almost always” or “always” (61% of males, 78% of females) had people who would listen to them talk about his/her wants, though caregivers of two males and one female reported that people at school “never” or “almost never” listened to their child about his/her wants. Additionally, 69% of males and 56% of females “always” or “almost always” had someone at school to tell him/her when he/she was meeting goals according to caregivers.

Figure 3.

Figure 3

Open in a new tab

Average Opportunities at School Scores with Standard Error Bars

Predictors of Self-Determination Capacity and Opportunities

To address our second research question, we explored whether adaptive behaviours, expressive vocabulary, and autism traits were associated with self-determination capacity and opportunities at home and at school.

Predictors of Capacity

Results indicated that capacity scores were significantly related to adaptive behaviour, p = .008, such that lower adaptive skills were associated with reduced capacity for self-determination. We conducted post-hoc analyses to explore whether different domains from the VABS-3 (communication, daily living skills, and socialization) were more associated with self-determination capacity than others via regression models with a Box-Cox transformation. We found that all three domains were associated with self-determination capacity (ps < .039). Expressive vocabulary, p = .095, total autism traits, p = .101, SCI autism traits, p = .114, or RRB autism traits, p = .148, were not associated with capacity scores. Table 2 contains all model statistics.

Table 2.

Regression coefficients testing self-determination capacity

Estimate SE F p ηp2 R2
Model 1: Adaptive behaviour
 Intercept 6.64 2.81 5.57 .023* 0.12 0.18
 Sex 0.11 1.80 1.17 .285 0.03
 Adaptive behaviour 1.95 0.04 8.84 .006* 0.17
Model 2: Expressive language
 Intercept 6.81 4.71 2.09 .156 0.06 0.10
 Sex -0.43 1.78 0.06 .812 0.00
 Expressive language 0.10 0.06 2.94 .095 0.08
Model 3: Autism Traits – Total
 Intercept 20.34 4.41 21.25 <.001* 0.34 0.07
 Sex -0.96 1.64 0.35 .560 0.01
 Autism traits - Total -0.11 0.07 2.81 .101 0.06
Model 4: Autism Traits – Social Communication and Interaction
 Intercept 20.58 4.70 19.20 <.001* 0.32 0.06
 Sex -1.10 1.65 0.45 .508 0.01
 Autism traits -0.11 0.07 2.61 .114 0.06
Model 3: Autism Traits – Restricted and Repetitive Behaviours
 Intercept 17.88 3.40 27.69 <.001* 0.40 0.05
 Sex -0.53 1.65 0.10 .748 0.00
 Autism traits -0.08 0.05 2.17 .148 0.05
Open in a new tab

Note: Males are the reference group for all sex estimates.

*

p < .050

Predictors of Opportunities at Home

Scores for opportunities at home were not associated with any variables: adaptive behaviour, p = .815, expressive vocabulary, p = .524, total autism traits, p = .462, SCI autism traits, p = .396, RRB autism traits, p = .735. See Table 3 for all model statistics.

Table 3.

Regression coefficients testing opportunities at home

Estimate SE F p ηp2 R 2
Model 1: Adaptive behaviour
 Intercept 330.65 72.87 20.59 <.001* 0.33 0.09
 Sex -68.65 46.68 2.16 .149 0.05
 Adaptive behaviour 0.23 0.98 0.06 .815 0.00
Model 2: Expressive language
 Intercept 279.62 109.62 6.51 .015 0.15 0.15
 Sex -80.27 41.42 3.76 .061 0.09
 Expressive language 0.85 1.31 0.42 .524 0.01
Model 3: Autism Traits – Total
 Intercept 425.16 111.94 14.43 <.001* 0.26 0.10
 Sex -84.03 41.52 4.10 .049* 0.10
 Autism traits -1.25 1.69 0.55 .462 0.01
Model 4: Autism Traits – Social Communication and Interaction
 Intercept 443.41 118.62 13.97 <.001* 0.25 0.10
 Sex -86.46 41.71 4.30 .045* 0.09
 Autism traits -1.52 1.77 0.74 .396 0.02
Model 5: Autism Traits – Restricted and Repetitive Behaviours
 Intercept 373.21 86.04 18.82 <.001* 0.31 0.09
 Sex -80.15 41.67 3.70 .061 0.08
 Autism traits -0.46 1.35 0.12 .735 0.00
Open in a new tab

Note: Males are the reference group for all sex estimates.

*

p < .050

Predictors of Opportunities at School

Scores for opportunities at school were related to total autism traits, p = .040, and more specifically SCI autism traits, p = .020, such that worse social communication scores were associated with reduced opportunities for self-determination in school settings. Adaptive behaviours, p = .736, expressive vocabulary, p = .658, and RRB autism traits, p = .260 were not associated with opportunities at school. See Table 4.

Table 4.

Regression coefficients testing opportunities at school

Estimate SE F p ηp2 R 2
Model 1: Adaptive behaviour
 Intercept 116.90 37.79 9.57 .004* 0.19 0.00
 Sex 3.08 24.21 0.02 .899 0.00
 Adaptive behaviour 0.17 0.51 0.12 .736 0.00
Model 2: Expressive language
 Intercept 96.39 44.17 4.76 .036* 0.12 0.03
 Sex -11.35 16.69 0.46 .501 0.01
 Expressive language 0.24 0.53 0.20 .658 0.01
Model 3: Autism Traits – Total
 Intercept 257.00 62.22 17.06 <.001* 0.29 0.10
 Sex 0.04 23.08 0.00 .999 0.00
 Autism traits -1.99 0.94 4.50 .040* 0.10
Model 4: Autism Traits – Social Communication and Interaction
 Intercept 281.99 65.12 18.75 <.001* 0.31 0.13
 Sex -3.59 22.90 0.03 .876 0.00
 Autism traits -2.35 0.97 5.84 .020* 0.12
Model 5: Autism Traits – Restricted and Repetitive Behaviours
 Intercept 164.15 43.64 14.15 <.001* 0.26 0.03
 Sex 5.89 21.14 0.08 .782 0.00
 Autism traits -0.78 0.68 1.34 .260 0.03
Open in a new tab

Note: Males are the reference group for all sex estimates.

*

p < .050

Discussion

The present study explored self-determination skills and opportunities among young adults with FXS, as well as factors that were associated with self-determination (i.e., adaptive behaviours, expressive language, and autism traits). We found that parent-reported self-determination skills were variable across domains for both males and females, with youth with FXS being provided with more opportunities at home and school relative to their capacity for self-determination. Lower adaptive skills were related to reduced capacity scores. Autism traits, and specifically social communication skills, were associated with opportunities at school, which suggests that educators may be underestimating the abilities of some young adults with FXS who express more autism traits; thus, providing them with fewer opportunities to practice these skills. These findings provide a description of self-determination skills in young adults with FXS, which is foundational for supporting young adults to become causal agents of their own lives and to increase their autonomy during this transitional period.

Self-Determination Capacity and Opportunities

Caregivers endorsed a wide range of self-determination capacities and opportunities among their young adult children with FXS and indicated that opportunities exceed capacity. This pattern is similarly reported by parents of children with other IDDs (Cheak-Zamora et al., 2020; Tomaszewski et al., 2020). Specifically, half the caregivers in the present study reported that their adult child with FXS knew their own wants likes and needs, but rarely or never acted on achieving that goal by identifying necessary steps as well as monitoring progress and adjusting goals or approaches. Despite this, many caregivers were supporting this area of capacity by indicating that someone was always available to let their adult child know that they were making progress. Increased opportunities for self-determination have been found to mediate capacity in populations with IDDs (Vicente et al., 2020), which would suggest that those with more opportunities would have higher capacity scores, and this is the basis for interventions such as SDLMI (Wehmeyer et al., 2000, 2013; Shogren et al., 2012). Thus, caregivers and teachers should continue providing opportunities to develop self-determination with scaffolding as needed, as well as consider implementation of programs such SDLMI, to help adult youth with FXS develop and reach their goals.

Adaptive Behaviour was Associated with Capacity for Self-Determination

For caregivers and educators to effectively scaffold the capacity for self-determination, it is important to understand which factors are associated with capacity to identify possible intervention co-targets. We found that the capacity for self-determination was related to adaptive behaviours according to caregiver report. Challenges with adaptive behaviours are a defining aspect of ID, and research in other populations suggests that adaptive behaviours and level of ID are related to self-determination capacity (Nota et al., 2007; Tomaszewski et al., 2020). This also aligns with research that indicates that adaptive behaviours are associated with adult outcomes in individuals with autism and/or IDD populations (Taylor and Mailick, 2014; Simões et al., 2016). In addition to the adaptive behaviour composite score, we found that communication, daily living skills, and socialization sub-scores from the VABS-3 were associated with capacity, which suggests that this finding was not driven by adaptive skills within a single domain. Findings highlight the importance of monitoring and promoting all domains of adaptive behaviour. One evidenced-based program that targets adaptive behaviours among transition-age youth is Surviving and Thriving in the Real World (Duncan et al., 2023). This is an effective intervention for autistic young adults without ID and could be a future avenue for research and treatment for young adults with FXS. It is also recommended that therapists (e.g., speech-language, occupational, or ABA therapists) identify functional treatment goals, such as adaptive behaviours (Houtrow et al., 2019). Additionally, providing opportunities for and reinforcing self-determination early in an intervention can help youth with IDDs self-choose their own functional goals (Schwartz and Kelly, 2021).

Social Communication Differences Associated with Autism May Reduce Opportunities for Self-Determination in School Settings

Our findings in young adults with FXS suggest that those with more autism traits, and specifically poorer social communication skills, receive fewer opportunities to develop and meet self-determined goals in educational settings. This finding is concerning and highlights an opportunity for change. Teacher-student relationships, and particularly closeness (i.e., teacher feelings of affection and open communication), are affected by social difficulties within children with IDDs (Blacher, Baker and Eisenhower, 2009; Blacher et al., 2014) and these patterns may extend to FXS. If so, reduced open communication may result in the student being less likely to express their wants and needs. Moreover, affected teacher-student relationships may result in teachers having greater difficulty identifying possible goals that are motivating to the student. Our findings suggest that it may be particularly important for educators working with youth with FXS who struggle with social communication to focus on building relationships with these students and using the resources available to them to facilitate these relationships, such as collaborating with the student’s family to gain additional insight into how to best support them.

Notably, previous research focused on autistic individuals who did not have FXS found that increased autism traits were associated with lower capacity, but not fewer opportunities (Cheak-Zamora et al., 2020; Tomaszewski et al., 2020). Perhaps this difference is because the young adults in the present study are diagnosed with a known genetic syndrome, which may lead to a level of presumed incompetence that does not come inherently with an idiopathic autism diagnosis. Thus, young adults with FXS who also present with more autism traits are given fewer opportunities to practice self-determination. Intervention research demonstrates that increased opportunities result in increased capacity, providing evidence that in order to support students becoming causal agents for their choices and actions, educators should provide high levels of opportunity regardless of their perception of one’s capacity (Shogren et al., 2012; Wehmeyer et al., 2013). It is important to note that the association between autism traits and opportunities for self-determination at school is based on the caregiver’s perception of these opportunities. Further research with educator- and self-report is critical to fully understanding this relationship and the opportunities provided in school settings.

Interestingly, no factors were associated with opportunities at home, and neither adaptive behaviours nor language skills were related to the opportunities provided in schools. Though the number of opportunities at home has been found to be associated with adaptive behaviours and autism traits in other populations, it is possible that other factors, such as caregiving burden or parent-child closeness, account for the variability in this domain (Tomaszewski et al., 2020). Language skills were not associated with self-determination in the present study, which was surprising considering prior findings (Abbeduto et al., 2021a). However, we used a norm-referenced standardised measure of expressive vocabulary, whereas (Abbeduto et al., 2021a) reported correlations with naturalistic expressive language sampling indices of syntax and lexical diversity. These language assessment methods may tap different aspects of language ability; standardized assessment imposes fewer social demands, focuses on language knowledge as opposed to use, and does not require responses in real time, whilst the expressive language sample consists of a back-and-forth social exchange with an unfamiliar examiner and thus may provide a more accurate measure of actual language produced in everyday contexts but may also be more influenced by factors such as anxiety and social motivation (Tager-Flusberg et al., 2009; Barokova and Tager-Flusberg, 2020).

Strengths, Limitations, and Future Directions

This study has several strengths. Our findings build on existing knowledge regarding self-determination in young adults with FXS (Abbeduto et al., 2021a), which contributes to our understanding of how to support the tumultuous transitional period between high school and young adulthood. We also used a well-validated caregiver-report measure of self-determination. Investigations of self-determination could be enhanced by including other reporters, as findings in autistic young adults (both with and without ID) have been found to differ between self-report, caregiver-report, and teacher-report. Specifically, when those with autism report on self-determination, they indicate fewer opportunities and higher capacity relative to caregiver- or educator-report (Tomaszewski et al., 2020). We did not collect self-report of self-determination in this study due wide range of functioning within our sample. There were some youths who were unable to self-report and thus we relied on a well-validated parent-report measure to have consistency across participants. Nonetheless, measuring self-determination from varying perspectives can help us gain a more well-rounded understanding of this skill in young adults with FXS. An additional strength of this study was our inclusion of females with FXS, who are often underrepresented in research. However, due to the sample size we were not able to statistically examine sex differences. This is a weakness that should be addressed in future research. Overall, caregivers reported similar self-determination scores for males and females, which is interesting to consider given the differing severity of their phenotypes. Perhaps females are at unique risk for low levels of self-determination despite their higher average IQ and adaptive behaviour scores relative to males. Statistically examining the differences or similarities in self-determination between males and females as well as individual contributors for each group would be an informative follow-up given the known phenotypic differences. Our study was also limited by the lack of racial and ethnic diversity in our sample, which thereby limits the generalizability of our findings. Future work with under-represented groups is warranted, as young adults in these groups may have different experiences regarding the opportunities provided to practice self-determination.

Conclusions

Targeting the development of self-determination, even from a young age, has the potential to positively impact later life outcomes for young adults with FXS. This may be particularly helpful for those in the transitional period between high school and young adulthood, who are beginning to make major life decisions. Supporting a skill that promotes autonomy is key for young adults to seek opportunities that align with their own interests and goals. This present study also has potential implications for future intervention research, such that targeting self-determination and adaptive behaviours simultaneously may be a productive approach to help promote independence in young adults with FXS. Future research should determine the efficacy of established treatments such as the SDLMI in this population. For young adults with FXS, it is also important for families and educators to provide ample opportunities to practice self-determination, regardless of their perception of capacity.

Acknowledgments

We would like to thank the families who participated in this research, as well as members of our research teams for their roles in recruitment and data collection.

Source of Funding

This work was supported by the National Institutes of Health (R01HD024356, PI: Leonard Abbeduto; P50HD103526, PI: Leonard Abbeduto; R21DC017804, PI: Jessica Klusek; R01AG073374, PI: Jessica Klusek; F32AG079615, PI: Laura Friedman) and the Research Participant Registry Core of the Carolina Institute for Developmental Disabilities (P50HD103573).

Footnotes

Conflict of interest

No conflicts of interest have been declared.

Ethics Approval Statement

Ethical review and approval were granted by the Institutional Review Boards at the University of South Carolina, University of California Davis, and Vanderbilt University Medical Center

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available because of privacy or ethical restrictions.

References

  1. Abbeduto L et al. (2021a) ‘Concurrent associations between expressive language ability and independence in adolescents and adults with fragile x syndrome’, Brain Sciences, 11, pp. 1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Abbeduto L et al. (2021b) ‘Fragile X syndrome and associated disorders’. In: APA Handbook of Intellectual and Developmental Disabilities (eds Glidden LM, Abbeduto L, McIntyre LL & Tasse MJ). American Psychological Association, pp. 151–185. [Google Scholar]
  3. Anderson S and Bigby C (2017) ‘Self-Advocacy as a Means to Positive Identities for People with Intellectual Disability: “We Just Help Them, Be Them Really”‘, Journal of Applied Research in Intellectual Disabilities, 30(1), pp. 109–120. doi: 10.1111/jar.12223. [DOI] [PubMed] [Google Scholar]
  4. Bangert K et al. (2021) ‘Family as a Context for Child Development: Mothers with the FMR1 Premutation and Their Children with Fragile X Syndrome’, Seminars in Speech and Language, 42(4), pp. 277–286. doi: 10.1055/s-0041-1730988. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Barokova M and Tager-Flusberg H (2020) ‘Commentary: Measuring Language Change Through Natural Language Samples’, Journal of Autism and Developmental Disorders. Springer US, 50(7), pp. 2287–2306. doi: 10.1007/s10803-018-3628-4. [DOI] [PubMed] [Google Scholar]
  6. Blacher J et al. (2014) ‘Autism spectrum disorder and the student teacher relationship: A comparison study with peers with intellectual disability and typical development’, Research in Autism Spectrum Disorders. Elsevier Ltd, 8(3), pp. 324–333. doi: 10.1016/j.rasd.2013.12.008. [DOI] [Google Scholar]
  7. Blacher J, Baker BL and Eisenhower AS (2009) ‘Student–Teacher Relationship Stability Across Early School Years for Children With Intellectual Disability or Typical Development’, American Journal on Intellectual and Developmental Disabilities, 114(5), pp. 322–339. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Box GEP and Cox DR (1964) ‘An Analysis of Transformations’, Journal of the Royal Statistical Society Series B, 26(2), pp. 211–252. [Google Scholar]
  9. Brady N et al. (2020) ‘Language Development From Early Childhood to Adolescence in Youths With Fragile X Syndrome’, Journal of Speech, Language, and Hearing Research, 63, pp. 3727–3742. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Burke KM et al. (2020) ‘A Meta-Analysis of Interventions to Promote Self-Determination for Students With Disabilities’, Remedial and Special Education, 41(3), pp. 176–188. doi: 10.1177/0741932518802274. [DOI] [Google Scholar]
  11. Carter EW et al. (2009) ‘Self-determination skills and opportunities of adolescents with severe intellectual and developmental disabilities’, American Journal on Intellectual and Developmental Disabilities, 114(3), pp. 179–192. doi: 10.1352/1944-7558-114.3.179. [DOI] [PubMed] [Google Scholar]
  12. Carter EW et al. (2013) ‘Parent assessments of self-determination importance and performance for students with autism or intellectual disability’, American Journal on Intellectual and Developmental Disabilities, 118(1), pp. 16–31. doi: 10.1352/1944-7558-118.1.16. [DOI] [PubMed] [Google Scholar]
  13. Cheak-Zamora NC et al. (2020) ‘Self-determination in young adults with autism spectrum disorder’, Autism, 24(3), pp. 605–616. doi: 10.1177/1362361319877329. [DOI] [PubMed] [Google Scholar]
  14. Clifford S et al. (2007) ‘Autism spectrum phenotype in males and females with fragile X full mutation and premutation’, Journal of Autism and Developmental Disorders, 37, pp. 738–747. doi: 10.1007/s10803-006-0205-z. [DOI] [PubMed] [Google Scholar]
  15. Coffee B et al. (2009) ‘Incidence of Fragile X Syndrome by Newborn Screening for Methylated FMR1 DNA’, American Journal of Human Genetics. The American Society of Human Genetics, 85(4), pp. 503–514. doi: 10.1016/j.ajhg.2009.09.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Cohen J (1988) Statistical power analysis for the behavioral sciences. Mahwah, NJ: Lawrence Erlbaum Associates. [Google Scholar]
  17. Constantino JN and Gruber CP (2012) ‘Social Responsiveness Scale, Second Edition’. Los Angeles, CA: Western Psychological Services. [Google Scholar]
  18. Crawford DC, Acuña JM and Sherman SL (2001) ‘FMR1 and the fragile X syndrome: Human genome epidemiology review’, Genetics in Medicine, 3(5), pp. 359–371. doi: 10.1097/00125817-200109000-00006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Duncan A et al. (2023) ‘A Randomized Clinical Trial Targeting Daily Living Skills in Autistic Adolescents Without an Intellectual Disability before the Transition to Adulthood’, Journal of Developmental and Behavioral Pediatrics, 44(9), pp. E590–E596. doi: 10.1097/DBP.0000000000001222. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Haebig E et al. (2020) ‘Rates and predictors of co-occurring autism spectrum disorder in boys with fragile X syndrome’, Autism and Developmental Language Impairments, 5. doi: 10.1177/2396941520905328. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Hagerman RJ et al. (1992) ‘Girls with fragile X syndrome: Physical and neurocognitive status and outcome’, Pediatrics, 89(3 SUPPL.), pp. 395–400. doi: 10.1542/peds.89.3.395. [DOI] [PubMed] [Google Scholar]
  22. Harris PA et al. (2009) ‘Research electronic data capture (REDCap)-A metadata-driven methodology and workflow process for providing translational research informatics support’, Journal of Biomedical Informatics. Elsevier Inc., 42(2), pp. 377–381. doi: 10.1016/j.jbi.2008.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Harris PA et al. (2019) ‘The REDCap consortium: Building an international community of software platform partners’, Journal of Biomedical Informatics. Elsevier, 95(April), p. 103208. doi: 10.1016/j.jbi.2019.103208. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Hartley SL et al. (2011) ‘Exploring the adult life of men and women with fragile X syndrome: Results from a national survey’, American Journal on Intellectual and Developmental Disabilities, 116(1), pp. 16–35. doi: 10.1352/1944-7558-116.1.16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Hessl D et al. (2009) ‘A solution to limitations of cognitive testing in children with intellectual disabilities: The case of fragile X syndrome’, Journal of Neurodevelopmental Disorders, 1(1), pp. 33–45. doi: 10.1007/s11689-008-9001-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Houtrow A et al. (2019) ‘Prescribing physical, occupational, and speech therapy services for children with disabilities’, Pediatrics, 143(4). doi: 10.1542/peds.2019-0285. [DOI] [PubMed] [Google Scholar]
  27. Kaufmann WE et al. (2004) ‘Autism spectrum disorder in fragile X syndrome: Communication, social interaction, and specific behaviors’, American Journal of Medical Genetics, 129 A(December 2003), pp. 225–234. doi: 10.1002/ajmg.a.30229. [DOI] [PubMed] [Google Scholar]
  28. Klusek J et al. (2023) ‘Predictors, Parental Views, and Concordance Across Diagnostic Sources of Autism in Male Youth with Fragile X Syndrome: Clinical Best Estimate and Community Diagnoses’, Research on Child and Adolescent Psychopathology, 51(7), pp. 1067–1068. doi: 10.1007/s10802-023-01059-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Klusek J, Martin GE and Losh M (2014) ‘Consistency between research and clinical diagnoses of autism among boys and girls with fragile X syndrome’, Journal of Intellectual Disability Research, 58(10), pp. 940–952. doi: 10.1111/jir.12121. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Knox M and Bigby C (2007) ‘Moving towards midlife care as negotiated family business: Accounts of people with intellectual disabilities and their families “Just getting along with their lives together”‘, International Journal of Disability, Development and Education, 54(3), pp. 287–304. doi: 10.1080/10349120701488749. [DOI] [Google Scholar]
  31. Leonard H et al. (2016) ‘Transition to adulthood for young people with intellectual disability: the experiences of their families’, European Child and Adolescent Psychiatry. Springer Berlin Heidelberg, 25(12), pp. 1369–1381. doi: 10.1007/s00787-016-0853-2. [DOI] [PubMed] [Google Scholar]
  32. Nota L et al. (2007) ‘Self-determination, social abilities and the quality of life of people with intellectual disability’, Journal of Intellectual Disability Research, 51(11), pp. 850–865. doi: 10.1111/j.1365-2788.2006.00939.x. [DOI] [PubMed] [Google Scholar]
  33. Oostra BA and Willemsen R (2003) ‘A fragile balance: FMR1 expression levels’, Human Molecular Genetics, 12(REV. ISS. 2), pp. 249–257. doi: 10.1093/hmg/ddg298. [DOI] [PubMed] [Google Scholar]
  34. R Core Team (2020) ‘R: A language and environment for statistical computing’. Vienna, Austria: R Foundation for Statistical Computing. Available at: https://www.r-project.org/. [Google Scholar]
  35. Roberts JE et al. (2007) ‘Receptive Vocabulary, Expressive Vocabulary, and Speech Production of Boys With Fragile X Syndrome in Comparison to Boys With Down Syndrome’, American Journal on Mental Retardation, 112(3), p. 177. doi: 10.1352/0895-8017(2007)112[177:RVEVAS]2.0.CO;2. [DOI] [PubMed] [Google Scholar]
  36. Roberts JE, Mirrett P and Burchinal M (2001) ‘Receptive and Expressive Communication Development of Young Males With Fragile X Syndrome’, American Journal on Mental Retardation, 106(3), p. 216. doi: . [DOI] [PubMed] [Google Scholar]
  37. Schwartz IS and Kelly EM (2021) ‘Quality of Life for People with Disabilities: Why Applied Behavior Analysts Should Consider This a Primary Dependent Variable’, Research and Practice for Persons with Severe Disabilities, 46(3), pp. 159–172. doi: 10.1177/15407969211033629. [DOI] [Google Scholar]
  38. Shogren KA et al. (2012) ‘Effect of Intervention with the Self-Determined Learning Model of Instruction on Access and Goal Attainment’, Remedial and Special Education, 33(5), pp. 320–330. doi: 10.1177/0741932511410072.Effect. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Shogren KA et al. (2015) ‘Causal agency theory: Reconceptualizing a functional model of self-determination’, Education and Training in Autism and Developmental Disabilities, 50(3), pp. 251–263. [Google Scholar]
  40. Shogren KA et al. (2018) ‘Evaluating the Differential Impact of Interventions to Promote Self-Determination and Goal Attainment for Transition-Age Youth with Intellectual Disability’, Research and Practice for Persons with Severe Disabilities, 43(3), pp. 165–180. doi: 10.1177/1540796918779775. [DOI] [Google Scholar]
  41. Shogren KA et al. (2019) ‘Impact of the Self-Determined Learning Model of Instruction on Self-Determination and Goal Attainment in Adolescents With Intellectual Disability’, Journal of Disability Policy Studies, 30(1), pp. 22–34. doi: 10.1177/1044207318792178. [DOI] [Google Scholar]
  42. Simões C et al. (2016) ‘Understanding the Relationship between Quality of Life, Adaptive Behavior and Support Needs’, Journal of Developmental and Physical Disabilities. Journal of Developmental and Physical Disabilities, 28(6), pp. 849–870. doi: 10.1007/s10882-016-9514-0. [DOI] [Google Scholar]
  43. Sparrow SS, Cicchetti DV and Saulnier CA (2016) ‘Vineland Adaptive Behavior Scales, third edition’. Bloomington, MN: Pearson Assessments. [Google Scholar]
  44. Tager-Flusberg H et al. (2009) ‘Defining Spoken Language Benchmarks and Selecting Measures of Expressive Language Development for Young Children With Autism Spectrum Disorders’, Journal of Speech, Language, and Hearing Research, 52(June), pp. 643–652. Available at: http://jslhr.highwire.org/cgi/content/abstract/52/3/643. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Taylor JL and Mailick MR (2014) ‘A Longitudinal Examination of 10-Year Change in Vocational and Educational Activities for Adults With Autism Spectrum Disorders’, Developmental Psychology, 50(3), pp. 699–708. doi: 10.1037/a0034297. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Thurman AJ et al. (2022) ‘Daily Living Skills in Adolescent and Young Adult Males With Fragile X Syndrome’, American Journal on Intellectual and Developmental Disabilities, 127(1), pp. 64–83. doi: 10.1352/1944-7558-127.1.64. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Tomaszewski B et al. (2020) ‘Student, Educator, and Parent Perspectives of Self-Determination in High School Students with Autism Spectrum Disorder’, Autism Research, 13(12), pp. 2164–2176. doi: 10.1002/aur.2337. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Tsiouris JA and Brown WT (2004) ‘Neuropsychiatric symptoms of fragile X syndrome: Pathophysiology and pharmacotherapy’, CNS Drugs, 18(11), pp. 687–703. doi: 10.2165/00023210-200418110-00001. [DOI] [PubMed] [Google Scholar]
  49. Verkerk AJM et al. (1991) ‘Identification of a gene (FMR-1) containing a CGG repeat coincident with a breakpoint cluster region exhibiting length variation in fragile X syndrome.’, Cell, 65, pp. 905–914. doi: 10.1016/0092-8674(91)90397-H. [DOI] [PubMed] [Google Scholar]
  50. Vicente E et al. (2020) ‘Self-determination in people with intellectual disability: The mediating role of opportunities’, International Journal of Environmental Research and Public Health, 17(17), pp. 1–15. doi: 10.3390/ijerph17176201. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Wehmeyer ML et al. (2000) ‘Promoting Causal Agency: The self-determined learning model of instruction’, Exceptional Children, 66(4), pp. 439–453. doi: 10.1177/001440290006600401. [DOI] [Google Scholar]
  52. Wehmeyer ML et al. (2013) ‘Establishing a Causal Relationship Between Intervention to Promote Self-Determination and Enhanced Student Self-Determination’, Journal of Special Education, 46(4), pp. 195–210. doi: 10.1177/0022466910392377. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Wehmeyer ML (2015) ‘Framing the Future: Self-Determination’, Remedial and Special Education, 36(1), pp. 20–23. doi: 10.1177/0741932514551281. [DOI] [Google Scholar]
  54. Wehmeyer ML and Palmer SB (2003) ‘Adult Outcomes for Students with Cognitive Disabilities Three-Years After High School: The Impact of Self-Determination’, Education and Training in Developmental Disabilities, 38(2), pp. 130–144. [Google Scholar]
  55. Wheeler AC et al. (2014) ‘Associated features in females with an FMR1 premutation’, Journal of Neurodevelopmental Disorders, 6(1), pp. 1–14. doi: 10.1186/1866-1955-6-30. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. White K, Flanagan TD and Nadig A (2018) ‘Examining the Relationship Between Self-Determination and Quality of Life in Young Adults with Autism Spectrum Disorder’, Journal of Developmental and Physical Disabilities. Journal of Developmental and Physical Disabilities, 30(6), pp. 735–754. doi: 10.1007/s10882-018-9616-y. [DOI] [Google Scholar]
  57. Williams KT (2019) ‘Expressive Vocabulary Test, Third Edition’. Bloomington, MN: NCS Pearson. [Google Scholar]
  58. Wolman J et al. (1994) ‘AIR Self-Determination Scale and User Guide’. Palo Alto, CA: American Institute for Research. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available because of privacy or ethical restrictions.

RESOURCES