Smithetal.2012.pdf

20 Apr,2022

NEW RESEARCH

Developmental Trajectories inAdolescents and Adults With Autism:

The Case of Daily Living SkillsLeann E. Smith, Ph.D., Matthew J. Maenner, Ph.D., Marsha Mailick Seltzer, Ph.D.

Objective: This study aimed to investigate the longitudinal course of daily living skills in alarge, community-based sample of adolescents and adults with autism spectrum disorders(ASD) over a 10-year period. Method: Adolescents and adults with ASD (n � 397) weredrawn from an ongoing, longitudinal study of individuals with ASD and their families. Acomparison group of 167 individuals with Down syndrome (DS) were drawn from a linkedlongitudinal study. The Waisman Activities of Daily Living Scale was administered four timesover a 10-year period. Results: We used latent growth curve modeling to examine change indaily living skills. Daily living skills improved for the individuals with ASD duringadolescence and their early 20s, but plateaued during their late 20s. Having an intellectualdisability was associated with lower initial levels of daily living skills and a slower change overtime. Individuals with DS likewise gained daily living skills over time, but there was nosignificant curvature in the change. Conclusions: Future research should explore whatenvironmental factors and interventions may be associated with continued gains in dailyliving skills for adults with ASD. J. Am. Acad. Child Adolesc. Psychiatry, 2012;51(6):622– 631. Key Words: daily living skills, autism, adolescence, adulthood, trajectories

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A utism spectrum disorders (ASDs) are life-long developmental disabilities that af-fect an estimated 1 in 110 children in theUnited States.1 ASDs are characterized by im-pairments in communication and social interac-tion as well as the presence of repetitive behav-iors. In recent years, increasing attention hasbeen given to understanding the behavioral phe-notype of ASD during adolescence and adult-hood. For instance, researchers have exploredhow autism symptoms and behavior problemschange across adolescence and adulthood.2-4

Other work has focused on measuring educa-tional and occupational outcomes for adults withASD, with results indicating that few individualsreach high levels of independence.5,6 Virtually nostudies, however, have explored the develop-ment of independence in daily living skills inadolescents and adults with ASD, even thoughsuch abilities are often cited as important factors

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for successful outcomes for adults with intellec-tual and developmental disabilities (IDD).7,8 The

resent study addressed this gap by examiningrajectories of daily living skills over a 10-yeareriod in a large, community sample of adoles-ents and adults with ASD.

aily Living Skills in Individuals With ASDaily living skills constitute a critical domain of

daptive behaviors, which are defined as behav-ors necessary for age-appropriate, independentunctioning in social, communication, daily liv-ng, or motor areas. Past research suggests thathe development of daily living skills may bearticularly challenging for individuals withSD. Children with autism often have significant

mpairments in daily living skills compared withell-matched controls,9,10 and as early as 36

months of age such children display a greaterdiscrepancy between their adaptive behavior andmental age than children with other develop-mental delays.11 These delays in daily livingkills may become more pronounced over time.

n a validation study of the Vineland Adaptive

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Behavior Scales’ supplemental norms for autism,younger children with ASD had higher standardscores than older children with ASD in all adap-tive behavior domains, including daily livingskills, suggesting that as children with ASDgrow, they increasingly lag behind their same-age peers.12 Similarly, in sample of 1,089 childrenand adolescents with ASD, Kanne et al.13 recentlyfound that adolescents had a greater gap be-tween their mental age and adaptive skills thanyounger children, suggesting that individualswith ASD may gain daily living skills at a paceslower than the rate of their intellectual growth.These cross-sectional findings highlight the needfor longitudinal studies to elucidate how dailyliving skills change over time for individualswith ASD and what factors are associated withimprovements in these skills.

Most studies that have examined within-personchange in daily living skills for individuals withautism notably have focused on early childhood.For instance, Freeman et al.14 explored change inthe Vineland Adaptive Behavior Scales in chil-dren with ASD and found that daily living skillsimproved with age. In addition, results indicatedthat children with IQs at or above 70 improved ata faster rate than children whose IQs were below70.14 Similarly, in a longitudinal study of dailyliving skills in preschoolers with ASD, Green andCarter15 found a linear increase in daily livingskills over a 3-year period, with lower IQ scoresand higher levels of autism symptoms associatedwith slower gains. In a recent study of childrenwith high-functioning autism, daily living skillsimproved over time, although the rate of changeslowed as children entered adolescence.16 Takentogether, these studies suggest that daily livingskills improve during early childhood and intoadolescence, although the rate of change slowsover time, and that the presence of an intellectualdisability (ID) further slows the rate of growth.Questions remain, however, regarding whetherdaily living skills continue to improve through ado-lescence and adulthood and the extent to which IDmay influence these later-life trajectories.

The literature on daily living skills for adultswith other types of IDD may offer insights intopossible patterns of change in daily living skillsfor those with ASD. For example, Esbensen etal.17 explored functional abilities (housekeeping,personal care, meal-related activities, and mobil-ity domains) over a nine-year period in a sample

of individuals with IDD, including a large sub-

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sample of individuals with Down syndrome(DS). Results indicated that housekeeping skillsimproved over time, whereas personal care andmobility skills declined over the same period.Improvements in housekeeping skills were fast-est for younger individuals and declines in per-sonal care skills were fastest for older individu-als.17 However, this study did not examine the

ossibility of curvilinear change. It may be thataily living skills improve for individuals with

DD during adolescence and early adulthood butecline later in adulthood. The present studyxamined this hypothesis by using latent growthurve modeling to test for linear and curvilinearhange in daily living skills for adolescents anddults with ASD as well as for similarly agedndividuals with DS.

resent Studyhe primary aim of the present study was to

nvestigate the longitudinal course of daily livingkills in a large, community sample of adoles-ents and adults with ASD. Daily living skillsere measured on four occasions over a 10-yeareriod, allowing for an examination of linear andurvilinear change. Furthermore, due to the wideange of ages of participants in our study (10 –52ears at Time 1), we were able to explore theffects of the age of the individual with ASDtermed “child age”) in addition to ID status onnitial level of daily living skills as well as changen daily living skills over time. Residential statusf the individual with ASD (living with parents. not living with parent) also was examined astime-varying covariate. To provide a bench-ark for interpreting trends among the adoles-

ents and adults with ASD, a secondary aim ofhe present study was to examine change in dailyiving skills among similarly aged individuals

ith DS, again measured on four occasions over10-year period. Although we did not conduct airect comparison given differences in the ageetween samples, we explored change in the DSample to provide additional context for inter-reting scores in the ASD group.

Based on past studies documenting that au-ism symptoms and behavior problems tend toecome less severe during adolescence anddulthood,2 we hypothesized that there woulde concomitant improvements in daily livingkills over the course of the study. However,ased on recent work by Taylor and Seltzer3

indicating that the rate of improvement in autism

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SMITH et al.

symptoms and behavior problems slows afterentering adulthood, we also hypothesized thatthe change in daily living skills would be curvi-linear; that is, that the rate of change woulddecrease over time. Next, consistent with paststudies showing that daily living skills improvewith age for children with ASD,14,15 we hypoth-esized that there would be a significant associa-tion between age and initial level of daily livingskills. Given the association between intelligenceand daily living skills in other samples,10,13,18 wehypothesized that having an ID would be associ-ated with a lower initial level of daily living skills.Based on the association between ID and growth indaily living skills in studies of younger childrenwith ASD,14,15 we hypothesized that having an IDwould be associated with slower change in dailyliving skills for adolescents and adults with ASD.

Regarding our secondary aim, based on pastwork showing gains over time in functionalabilities for individuals with ID,17 we hypothe-sized that there would be improvements in dailyliving skills for individuals with DS. We alsohypothesized that individuals with DS would dis-play curvilinear change, or a slowing of improve-ment, consistent with findings that individualswith DS are at risk for dementia as they age.19,20

METHODAutism Sample ParticipantsParticipants were drawn an ongoing, multi-wave, lon-gitudinal study of 406 individuals with ASD and theirfamilies, the Adolescents and Adults with Autismstudy (AAA).21 The present study focused on four ofeight points of data collection, Times 1, 4, 7, and 8.Families were recruited via agencies, schools, diagnos-tic clinics, and media announcements. At entry into theAAA study, families met three criteria: the familyincluded a child 10 years of age or older; the child hadreceived a diagnosis of ASD from a medical, psycho-logical, or educational professional; and scores on theAutism Diagnostic Interview—Revised (ADI-R)22

were consistent with the parental report of an ASD.Of the original sample of 406 individuals, nine

were excluded from the present study, as they didnot have complete data on activities of daily living atTime 1. Excluded cases were not significantly differ-ent from the full sample in child age, sex, familyincome, or parental education. The individuals withASD in the present study ranged from 10 to 52 yearsof age at the beginning of the study (Time 1: mean �21.84 years, SD � 9.32 years; Time 4: mean � 26.25 years,SD � 9.36 years; Time 7: mean � 29.87 years, SD � 9.19

years; and Time 8: mean � 31.23 years, SD � 9.02). The

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ajority of the sample was male (73%) and 70% of theample had a comorbid diagnosis of ID.

When the AAA study began in 1998, 65% of thendividuals with ASD lived with their families and5% lived away from home. An increasing proportionf individuals moved away from the family home atach subsequent point of data collection, such that atimes 4, 7, and 8, 56%, 45%, and 47% were co-residingith their families, respectively. About half (52.2%) ofarent respondents had at least a bachelor’s degree,nd the median annual household income was $50,000o $59,000 in 1998 to 1999. The majority of participants93%) were white. Most respondents were mothers96.5%), with 14 fathers participating (3.5%).

There were no significant differences between fami-ies who participated in all waves of data collection andamilies with missing data in child sex or ID status.owever, consistent with age-related morbidity andortality, families of older individuals were more likely

o end study participation than were their youngerounterparts (F � 3.78, p � .05). Importantly, there were

no significant associations between complete study par-ticipation and daily living skill scores at Time 1.

Down Syndrome Sample ParticipantsTo benchmark changes in daily living skills in individ-uals with ASD, a sample of individuals with DS wasdrawn from a linked longitudinal study of 461 indi-viduals with ID.23 Families were included in the studyf they met two criteria: the mother was between 55nd 85 years of age and the son or daughter lived atome with her. Of the 461 target children in the study,69 of the sons or daughters had a diagnosis of DS. Ofhese cases, 2 were excluded from the present study ashey had missing data on activities of daily living at Time. The individuals with DS in the present study rangedrom 15 to 56 years of age at Time 1 (mean � 31.61 years,D � 7.19 years). The majority were daughters (60.5%),nd 28.8% of mothers had at least a bachelor’s degree.he majority of participants (92%) were white.

When this longitudinal study began, all of thendividuals with DS lived at home with their families.

owever, some individuals changed residences atach subsequent point in data collection, such that atimes 4, 7, and 8, 94%, 81%, and 92% were co-residingith their families, respectively. Families who partici-ated in all waves of data collection were not signifi-antly different from families with missing data on childex, but families of older individuals were more likely tond study participation than families of younger individ-als (F � 6.94, p � .05). As with the ASD sample, thereas no association between complete study participation

nd Time 1 daily living skills scores.

Procedure and MeasuresProcedures and measures were identical for both the

ASD and DS samples. At each time point (Times 1, 4,

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7, and 8), mothers completed self-administered ques-tionnaires and participated in a 2- to 3-hour in-homeinterview. For the ASD sample, data collection be-tween Times 1 and 4 occurred an average of 5.00 yearsapart. Approximately 3.45 years occurred betweenTimes 4 and 7, and 1.99 years occurred between Times7 and 8. For the DS sample, an average of 4.44 yearselapsed between Times 1 and 4, 4.47 years betweenTimes 4 and 7, and 1.72 years between Times 7 and 8.

Independence in activities of daily living was mea-sured using the Waisman Activities of Daily LivingScale (W-ADL; Maenner, Smith, Hong, Makuch,Greenberg, and Seltzer, unpublished data, 2011) (Table1). Parent respondents rated their son or daughter’slevel of independence on 17 items covering the do-mains of personal care, housekeeping, and meal-related activities. Each item was rated on a three-pointscale of independence 0 (does not perform the task atall), 1 (performs the task with help), or 2 (performs thetask independently); and items were summed. Coeffi-

TABLE 1 Waisman Activities of Daily Living Scale

1. Making his/her own bed2. Doing household tasks, including picking up around the

house, putting things away, light housecleaning, etc.3. Doing errands, including shopping in stores4. Doing home repairs, including simple repairs around

the house, non-technical in nature; for example,changing light bulbs or repairing a loose screw

5. Doing laundry, washing and drying6. Washing/bathing7. Grooming, brushing teeth, combing and/or brushing

hair8. Dressing and undressing9. Toileting

10. Preparing simple foods requiring no mixing or cooking,including sandwiches, cold cereal, etc.

11. Mixing and cooking simple foods, fry eggs, makepancakes, heat food in microwave, etc.

12. Preparing complete meal13. Setting and clearing table14. Drinking from a cup15. Eating from a plate16. Washing dishes (including using a dishwasher)17. Banking and managing daily finances, including

keeping track of cash, checking account, paying bills,etc. (Note: if he/she can do a portion but not all circle‘1’ with help.)

Note: Instructions that accompanied the items: “Next we would like toknow about your son or daughter’s current level of independence inperforming activities of daily living. For each activity please tell me thenumber which best describes your son/daughter’s ability to do thetask. For example, Independent would mean your son/daughter isable to do the task without any help or assistance.”2 � independent or does on own; 1 � does with help; 0 � does not

do at all.

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cient � values for the total score in the ASD sampleranged from 0.90 to 0.94 for Times 1, 4, 7, and 8; for theDS sample, the � values ranged from 0.91 to 0.93.

Child characteristics of age (continuous) and IDstatus (1 � yes, 0 � no) were included as predictors of

aily living skills scores in the ASD sample analyses.rocedures for assessing the presence of ID in ourample have been reported in detail in previous stud-es24 and involved a clinical consensus process usingnformation drawn from sources including direct cog-itive testing and educational records. Residential sta-

us (0 � co-residing with parent, 1 � not co-residingith parent) was also included as a time-varying

ovariate.

Data AnalysisTo address our primary aim, we used latent growthcurve (LGC) modeling to examine daily living skillsover a 10-year period. LGC modeling integrates indi-vidual growth modeling (i.e., hierarchical linear mod-eling) and structural equation modeling (SEM) ap-proaches25 and provides estimates of mean structureintercept and slope), reflecting the average startingoint for all individuals and average rate of change.26

It is also possible to model nonlinear change; byadding a quadratic parameter to a model that alreadyincludes an intercept and linear slope, the growthtrajectory becomes curvilinear. In a purely linearmodel, the rate of change is presumed to be constantover time; in contrast, a quadratic latent curve modelallows the rate of change either to increase or decreaseover time. As an example, the magnitude of change inrepeated measures may be larger in earlier years thanin later years.26 The addition of a quadratic trend alsolters the interpretation of the linear slope, such thathe linear slope coefficient is changed to reflect thenstantaneous rate of change at a specific point inime.25 If the coefficient for the quadratic factor isegative, then the trajectory is concave to the time axis.onversely, the presence of a positive quadratic trend

ndicates that the trajectory is convex to the time axis.25

After preliminary analyses of variance confirmedthe presence of change over time in daily living skillswithout controlling for age and ID status, a multivar-iate LCG model was assessed in which age and IDstatus were included as time-invariant predictors andresidential status was included as a time-varying co-variate. To address our secondary aim of providing anillustrative benchmark for interpreting the patterns ofdaily living skills observed in our ASD sample, weused LGC modeling to assess change in daily livingskills in a sample of individuals with DS over a similarperiod of time. All models were evaluated in terms ofmeasures of goodness-of-fit using the Mplus modelingprogram.27 A satisfactory fit is indicated by a compar-ative fit index (CFI) close to one and a root meansquare error of approximation (RMSEA) less than or

equal to 0.08.

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RESULTSPrimary Aim: Daily Living Skills in Adolescentsand Adults With ASDActivities of daily living were assessed at 4 timepoints (Times 1, 4, 7, and 8) in the ASD sample.We present means, standard deviations, ranges,and intercorrelations among study variables inTable 2. Figure 1 depicts a mixed-effects regres-sion model showing individual scores by age andintellectual disability status. By the end of thestudy, the average score for the group was 20.59(SD � 8.08) on a scale in which a score of 34reflects complete independence. Only 16.5% ofthe sample had scores of 30 or above at Time 8.Scores at each time point were significantly cor-related with scores at all other time points.

We evaluated an LGC model of daily livingskills that specified quadratic growth over timeand included age and ID status as predictors ofall latent factors. Residential status (co-residingvs not co-residing) also was included as a time-varying covariate (Figure 2). In this model, thelatent intercept, linear slope, and quadratic trendwere indicated by daily living scores at Times 1,4, 7, and 8. The factor loadings for the interceptfactor were all set to 1. The loadings for the linearslope factor were fixed at 0, 5.0, 8.45, and 10.44,reflecting the average length of time betweenwaves of data collection. The loadings for thequadratic slope factor were the linear valuessquared.

This model displayed excellent fit [�2 (15, n �406)� 12.69, p � .63; RMSEA� 0.00; CFI � 1.0].There was a significant positive linear slope (est. �1.25, SE� 0.19, p�.001) and a significant negativequadratic trend (est.� �0.07, SE� 0.02, p � .001).However, the linear trend in a model that in-cludes a quadratic trend is interpreted as theinstantaneous rate of change. This means that fordifferent snapshots of time, the rate of changemay be different. As such, to determine howdaily living skills were changing across time, wealso examined the values for the linear slopewhen time was centered at Times 4, 7, and 8,respectively. At Time 4, the linear trend waspositive (est.� 0.56, SE� 0.07, p�.001), but atTime 7 the linear trend was nonsignificant (est. �0.07, SE �0.15, p � .57). At Time 8, however,there was a significant negative linear trend(est.� �0.89, SE� 0.27, p � .001). Taken together,these findings suggest that, on average, scoreswere increasing at Times 1 and 4 but were no

longer significantly changing at Time 7. By Time

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T T T T C ID M R N *

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8, scores were beginning to decrease. In otherwords, daily living skills were improving duringadolescence and the early 20s, plateaued aroundthe time of the late 20s, and started to declineduring the early 30s. However, we encouragesome caution in interpreting the exact nature ofchange for older individuals, as the majorityof the sample was under the age of 30 at the endof the study.

There also were significant relationships be-tween age, ID status, and the latent factors. Agewas positively associated with the intercept ofdaily living skills, with older individuals havinghigher scores at the start of the study (��0.24, p� .001). Age also was associated with the linearfactor (� � �0.31, p � .01) and the quadraticfactor (� � 0.22, p � .10), although this associa-tion with the quadratic factor was not significantat the .05 level. These age effects suggest thatolder individuals displayed a faster rate of cur-vature; that is, they were declining at a faster

FIGURE 1 Change in Waisman Activities of Daily Livinsample, individual and group trajectories. Note: Quadrat

rate. In addition, ID status was a significant s

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predictor of the intercept of daily living skills,with individuals with ID having lower initiallevels of daily living skills at the start of the study(�� 0.52, p � .001). Having an ID was also

egatively associated with the linear factor (� ��0.20, p � .01), suggesting that individuals withD were gaining skills at a slower rate thanndividuals without ID. Residential status was atatistically significant covariate of daily livingkills at Times 1 and 8, with coresidence betweenarent and child associated with lower scores.

econdary Aim: Daily Living Skills in Individualsith Down Syndrome

o explore trajectories of daily living skills in theS sample, daily living skills were assessed at

our time points (Times 1, 4, 7, and 8). We presenteans, standard deviations, ranges, and intercor-

elations among study variables in Table 3. Fig-re 3 depicts a mixed-effects regression model

-ADL) scores over time for autism spectrum disorderge2) mixed-model paramaterizations displayed.

g (Wic (a

howing individual scores by age. By the end of

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SMITH et al.

the study, the average score for the group was23.83 (SD � 6.33) on a scale in which a score of 34reflects complete independence. Only 19.6% ofthe sample had scores of 30 or above at Time 8.Scores at each time point were significantly cor-related with scores at all other time points.

FIGURE 2 Latent growth curve model of WaismanActivities of Daily Living (ADL) scores for individuals withautism spectrum disorders (N � 397). Note: ID �intellectual disability. *p � .05, ��p � .01, ��p �.001, †p � .10.

TABLE 3 Descriptive Statistics and Intercorrelations Amo

Time 1 W-ADL Time 4 W-ADL

Time 1 W-ADL 1 (n � 166)Time 4 W-ADL 0.88*** (n � 124) 1 (n � 125)Time 7 W-ADL 0.83*** (n � 98) 0.88*** (n � 92Time 8 W-ADL 0.85*** (n � 66) 0.86*** (n � 63Child age 0.12 (n � 166) 0.03 (n � 125)Mean (SD) 22.55 (6.37) 23.69 (6.56)Range 3–33 2–33

Note: W-ADL � Waisman Activities of Daily Living.

***p � .001.

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We evaluated a LGC model of daily livingskills that specified linear and quadratic growthover time and included age as a predictor of alllatent factors and residential status included as atime-varying covariate. Since all individuals inthe DS sample had a diagnosis of ID, disabilitystatus was not included in this model. In thismodel, the latent intercept and linear slope wereindicated by daily living scores at Times 1, 4, 7,and 8. The factor loadings for the intercept factorwere all set to 1. The loadings for the linear slopefactor were fixed at 0, 4.44, 8.91, and 10.63,reflecting the average length of time betweenwaves of data collection. The loadings for thequadratic slope factor were the linear valuessquared.

This model displayed good fit (�2 (11, N �67) � 16.84, p � .11; RMSEA � 0.06; CFI � 0.99).here was a positive linear slope (est.� 0.86,E � 0.45), indicating improvement in dailyiving skills over time, although this effect onlypproached statistical significance (p � .058).mportantly, the average increase of 0.86 pointer year is a clinically significant change. Theuadratic slope factor was nonsignificant (est.�0.04, SE � 0.04, p � .42), indicating that thereas no curvature in the change in daily living

kills over time. There was a trend for age to beositively associated with the intercept of daily

iving skills (p � .10). There were no significantssociations between age and the other latentactors. Residential status was not a significantovariate at any of the time points.

DISCUSSIONThe present study used LGC modeling to inves-tigate trajectories of daily living skills for ado-lescents and adults with ASD. Past research

tudy Variables for Down Syndrome Sample

Time 7 W-ADL Time 8 W-ADL Child Age

(n � 99)0.92*** (n � 60) 1 (n � 66)

�0.02 (n � 99) 0.01 (n � 66) 1 (n � 167)23.37 (7.41) 23.83 (6.33) 31.61 (7.19)1–32 5–33 15–56

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examined trajectories of daily living skills forindividuals with ASD during childhood andearly adolescence but not across adolescence andadulthood. In contrast, the present study in-cluded a large, community-based sample of indi-viduals with ASD with a wide age range (10 –52years), which enabled us to examine the influ-ence of age as well as ID status on change in dailyliving skills well into adulthood. The longitudi-nal design of the current study addressed an-other gap in the literature by allowing for anexamination of curvilinear change over a 10-yearperiod. Finally, the present study included anadditional analysis of trajectories of daily livingskills in a linked longitudinal study of individu-als with DS, providing a unique opportunity tounderstand patterns of change in two differentgroups of individuals with IDD.

Most notably, the present study found signif-icant quadratic change in daily living skills for

FIGURE 3 Change in Waisman Activities of Daily Livinindividual and group trajectories. Note: Linear mixed–mo

individuals with ASD, indicating that skills im- o

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proved during adolescence and the early 20s,plateaued around the late 20s, and began todecline in the early 30s. This is consistent withour hypothesis that there would be improve-ments in skills for individuals with ASD but thatthe rate of change would slow as individualsaged. Recently, Taylor and Seltzer3 documentedhat the rate of improvement in autism symp-oms and behavior problems for adolescents withSD slowed down (or even stopped) after the

ndividuals with ASD exited the secondarychool system (typically during the early 20s).aken together, these findings suggest that ado-

escence is a time of growth and improvement forndividuals with ASD in a variety of domains,ut that, on average, the period of improvementnds by the time such individuals reach 30 yearsf age. The slowing of improvement in daily

iving skills is particularly concerning given thathe plateau in gains was not due to ceiling effects

-ADL) scores over time for Down syndrome sample;aramaterization displayed.

g (Wdel p

r a mastery of skills (Maenner et al., unpub-

629www.jaacap.orgsortium from ClinicalKey.com by Elsevier on January 04, 2018.

loonsllowecwibms

SMITH et al.

lished data, 2011). In fact, by the end of the studyperiod, on average, the individuals with ASDwere failing to perform more than one-third ofthe measured daily living skills independently.

Consistent with our hypothesis and with otherstudies demonstrating an association betweenage and daily skills,14,15 we found that beingolder at the start of the study was associated withhigher levels of initial daily living skills. Findingsalso indicated that older individuals displayed afaster rate of curvature; that is, the older anindividual was at the start of the study, thesooner he or she started to display a plateau andeventual decline in daily living skills. Also con-sistent with past studies of daily living skills inchildren with ASD,14,15 having an ID was associ-ated with lower initial levels of daily living skillsand with slower rates of change.

A secondary aim of the present study was toexamine the pattern of change in daily livingskills among individuals with DS to provide acontext for interpreting the pattern of changeobserved in our ASD sample. Past research hasshown that adults with DS have higher levels ofdaily living skills than individuals with otherintellectual disabilities,17,16 including individualswith ASD and ID.7,28 Findings from the presentstudy indicated that individuals with DS show adifferent pattern of change in daily living skills,with these adults continuing to gain skills acrossadulthood. The slowing of improvement in dailyliving skills for adults with ASD may contributeto the poorer adult outcomes observed in indi-viduals with ASD compared with peers with DSwho had similar levels of intellectual functioning.7

The limitations of the present study point toareas for future research. The majority of individ-uals in our sample were white and middle-class,highlighting a need to examine these skills inmore diverse groups. Similarly, although wecontrolled for residential status, it may be thatother environmental contexts (e.g., type of dayactivity) also influence change in daily livingskills. It also is important to note that the samplesize for the DS group was small for conductinggrowth curve analyses, which leaves the possi-bility that more nuanced patterns of change maybe observed in larger groups of adults with DS.In addition, the majority of the DS sample werealready adults at the start of the study, thuslimiting the extent to which direct comparisons

between the two samples would be informative;

JOURN630 www.jaacap.org

Downloaded for Anonymous User (n/a) at Florida International University – FFor personal use only. No other uses without permissi

a sharper increase in skills may have been ob-served in the DS group, had we measured theseskills earlier in development. Although our ob-servation of differences between the ASD and DSgroups was entirely exploratory and descriptive,it does raise an intriguing question for futureinvestigation. Finally, the present study is limitedby the use of use of a categorical variable mea-suring ID status, as IQ scores were not availablefor all participants.

This study has important implications for fu-ture research and clinical practice. By the end ofthe study period, all individuals with ASD wereadults but, on average, these adults had notachieved independence in many of the dailyliving skills that we measured. However, as otherresearchers have noted,13,29 daily living skills areess tied to the core symptoms of autism thanther aspects of functioning, such as socializationr communication, and thus may be more ame-able to change. The improvement in daily livingkills for individuals with ASD into the late 20sikewise suggests that it may be possible for dailyiving skills to be gained at later points in devel-pment, even as skills in other areas plateau. Itill be critical for future research to explore what

nvironmental factors may be associated withontinued gains of daily living skills for adultsith ASD as well as the best practices for teach-

ng these skills. Although some attention haseen given to developing behavioral and phar-acological interventions to improve daily living

kills in younger children with ASD,30,31 newresearch is needed to develop strategies for sup-porting gains in daily living skills for individualswith ASD at later points in the life course. &

Accepted March 7, 2012.

Drs. Smith, Maenner, and Seltzer are with the Waisman Center,University of Wisconsin–Madison.

This research was supported by National Institute of Health (NIH)grants R01 AG08768 (M.M.S.), T32 HD07489 (M.M.S.), and P30HD03352 (M.M.S.).

The authors are extremely grateful to the families who participated inthis study; without their generous commitment, this research would nothave been possible.

Disclosure: Drs. Smith, Maenner, and Seltzer report no biomedicalfinancial interests or potential conflicts of interest.

Correspondence to: Leann E. Smith, Ph.D.,1500 Highland Avenue,Waisman Center, Madison, WI 53705; e-mail: lsmith@waisman.wisc.edu

DOI: 10.1016/j.jaac.2012.03.001

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DEVELOPMENTAL TRAJECTORIES AND AUTISM

Downloa

REFERENCES1. Prevalence of autism spectrum disorders—Autism and Develop-

mental Disabilities Monitoring Network, United States, 2006.Surveillance summaries. MMWR. 2009;58:1-20.

2. Shattuck PT, Seltzer MM, Greenberg JS, et al. Change in autismsymptoms and maladaptive behaviors in adolescents and adultswith an autism spectrum disorder. J Autism Dev Disord. 2007;37:1735-1747.

3. Taylor JL, Seltzer MM. Changes in the autism behavioral pheno-type during the transition to adulthood. J Autism Dev Disord.2010;40:1431-1446.

4. Anderson DK, Maye MP, Lord C. Changes in maladaptivebehaviors from midchildhood to young adulthod in autismspectrum disorder. Am J Intellect Dev Disabil. 2011;116:381-397.

5. Howlin P, Goode S, Hutton J, Rutter M. Adult outcome forchildren with autism. J Child Psychol Psychiatry. 2004;45:212-229.

6. Taylor JL, Seltzer MM. Employment and post-secondary educa-tional activities for young adults with autism spectrum disordersduring the transition to adulthood. J Autism Dev Disord. 2011;41:566-574.

7. Esbensen AJ, Bishop S, Seltzer MM, Greenberg JS, Taylor JL.Comparisons between individuals with autism spectrum disor-ders and individuals with Down syndrome in adulthood. Am JIntellect Dev Disabil. 2010;115:277-290.

8. Woolf S, Woolf CM, Oakland T. Adaptive behavior among adultswith intellectual disabilities and its relationship to communityindependence. Intellect Dev Disabil. 2010;48:209-215.

9. Liss M, Harel B, Fein D, et al. Predictors and correlates of adaptivefunctioning in children with developmental disorders. J AutismDev Disord. 2001;31:219-230.

10. Perry A, Flanagan HE, Dunn Geier J, Freeman NL. Brief report:the Vineland Adaptive Behavior Scales in young children withautism spectrum disorders at different cognitive levels. J AutismDev Disord. 2009;39:1066-1078.

11. Stone WL, Ousley OY, Hepburn SL, Hogan KL, Brown CS.Patterns of adaptive behavior in very young children withautism. Am J Ment Retard. 1999;104:187-199.

12. Carter AS, Volkmar FR, Sparrow SS, et al. The Vineland AdaptiveBehavior Scales: supplementary norms for individuals with au-tism. J Autism Dev Disord. 1998;28:287-302.

13. Kanne SM, Gerber AJ, Quirmbach LM, Sparrow SS, Cicchetti DV,Saulnier CA. The role of adaptive behavior in autism spectrumdisorders: implications for functional outcome. J Autism DevDisord. 2011;41:1007-1018.

14. Freeman BJ, Del’Homme M, Guthrie D, Zhang F. VinelandAdaptive Behavior Scale scores as a function of age and initial IQin 210 autistic children. J Autism Dev Disord. 1999;29:379-384.

15. Green SA, Carter AS. Predictors and course of daily living skillsdevelopment in toddlers with autism spectrum disorders [pub-lished online ahead of print May 2011]. J Autism Dev Disord. DOI10.1007/s10803-011-1275-0.

16. Szatmari P, Bryson S, Duku E, et al. Similar developmentaltrajectories in autism and Asperger syndrome: from early child-

JOURNAL OF THE AMERICAN ACADEMY OF CHILD & ADOLESCENT PSYCHIATRYVOLUME 51 NUMBER 6 JUNE 2012

ded for Anonymous User (n/a) at Florida International University – Florida state conFor personal use only. No other uses without permission. Copyright

hood to adolescence. J Child Psychol Psychiatry AlliedDisciplines. 2009;50:1459-1467.

17. Esbensen AJ, Seltzer MM, Krauss MW, MacLean JWE. Stabilityand change in health, functional abilities, and behavior problemsamong adults with and without Down syndrome. Am J MentRetard. 2008;113:263-277.

18. Ray-Subramanian CE, Huai N, Ellis Weismer S. Brief report:adaptive behavior and cognitive skills for toddlers on the autismspectrum. J Autism Dev Disord. 2011;41:679-684.

19. Holland AJ, Hon J, Huppert FA, Stevens F. Incidence and courseof dementia in people with Down’s syndrome: findings from apopulation-based study. J Intellect Disabil Res. 2000;44:138-146.

20. Zigman WB, Schupf N, Sersen E, Silverman W. Prevalence ofdementia in adults with and without Down syndrome. Am JMent Retard. 1996;100:403-412.

21. Seltzer MM, Greenberg JS, Hong J, et al. Maternal cortisol levelsand behavior problems in adolescents and adults with ASD. JAutism Dev Disord. 2010;40:457-469.

22. Lord C, Rutter M, Le Couteur A. Autism Diagnostic Interview—Revised: a revised version of a diagnostic interview for caregiversof individuals with possible pervasive developmental disorders. JAutism Dev Disord. 1994;24:659-685.

23. Krauss MW, Seltzer, MM. An unanticipated life: the impact oflifelong caregiving. In: Bersani H, ed. Responding to the Chal-lenge: International Trends and Current Issues in DevelopmentalDisabilities. Brookline, MA: Brookline Books; 1999.

24. Smith LE, Greenberg JS, Seltzer MM, Hong J. Symptoms andbehavior problems of adolescents and adults with autism: effectsof mother-child relationship quality, warmth, and praise. Am JMent Retard. 2008;113:387-402.

25. Willett JB, Sayer AG. Using covariance structure-analysis todetect correlates and predictors of individual change over time.Psychol Bull. 1994;116:363-381.

26. Bollen KA, Curran PJ. Latent Curve Models: a Structural EquationPerspective. Hoboken, NJ: Wiley; 2006.

27. Muthen LK, Muthen BO. Mplus User’s Guide. 2nd ed. LosAngeles, CA: Muthen and Muthen; 2001.

28. Matson JL, Dempsey T, Fodstad JC. The effect of autism spectrumdisorders on adaptive independent living skills in adults withsevere intellectual disability. Res Develop Disabil. 2009;30:1203-1211.

29. Kraijer D. Review of adaptive behavior studies in mentallyretarded persons with autism/pervasive developmental disorder.J Autism Dev Disord. 2000;30:39-47.

30. Drahota A, Wood J, Sze K, Van Dyke M. Effects of cognitivebehavioral therapy on daily living skills in children with high-functioning autism and concurrent anxiety disorders. J AutismDev Disord. 2011;41:257-265.

31. Williams SK, Scahill L, Vitiello B, et al. Risperidone and adaptive

behavior in children with autism. J Am Acad Child AdolescPsychiatry. 2006;45:431-439.

631www.jaacap.orgsortium from ClinicalKey.com by Elsevier on January 04, 2018.

Developmental Trajectories in Adolescents and Adults With Autism: The Case of Daily Living Skills

Daily Living Skills in Individuals With ASD
Present Study
Method

Autism Sample Participants
Down Syndrome Sample Participants
Procedure and Measures
Data Analysis

Results

Primary Aim: Daily Living Skills in Adolescents and Adults With ASD
Secondary Aim: Daily Living Skills in Individuals With Down Syndrome

Discussion
References