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The Floor Effect on the ABAS-II in Adolescents with Autism Spectrum Disorder

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Title: The Floor Effect on the ABAS-II in Adolescents with Autism Spectrum Disorder
Language: English
Authors: Laghi, Fiorenzo, Ferri, Rosa, Caramuscio, Elvira, Lonigro, Antonia, Rea, Monica, Pezzuti, Lina (ORCID 0000-0001-5810-4185)
Source: Journal of Autism and Developmental Disorders. Nov 2022 52(11):4975-4985.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 11
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Descriptors: Adolescents, Autism Spectrum Disorders, Behavior, Daily Living Skills, Evaluation Methods
Assessment and Survey Identifiers: Adaptive Behavior Scale
DOI: 10.1007/s10803-021-05369-y
ISSN: 0162-3257
1573-3432
Abstract: The present study aimed at enhancing the assessment of adaptive behavior in adolescents with Autism Spectrum Disorder through the Adaptive Behavior Assessment System-Second Edition. To overcome the limits underpinning floor effect, which are commonly observed with the traditional methods, the statistical Hessl method and its revision by Orsini, Pezzuti and Hulbert was adopted. The results showed a more variation using the former method compared to the latter: a greater impairment in Social versus Leisure skills emerged. Regarding the Conceptual domain, a greater deficit in Functional Academics was observed. In the Practical domain, we found a greater impairment in Self-Care skills. Conversely, Home Living skills appeared as a strength compared to other skills. The results are discussed in reference to literature.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1351531
Database: ERIC
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  Value: <anid>AN0159632202;aut01nov.22;2022Oct14.07:07;v2.2.500</anid> <title id="AN0159632202-1">The Floor Effect on the ABAS-II in Adolescents with Autism Spectrum Disorder </title> <p>The present study aimed at enhancing the assessment of adaptive behavior in adolescents with Autism Spectrum Disorder trough the Adaptive Behavior Assessment System-Second Edition. To overcome the limits underpinning floor effect, which are commonly observed with the traditional methods, the statistical Hessl method and its revision by Orsini, Pezzuti and Hulbert was adopted. The results showed a more variation using the former method compared to the latter: a greater impairment in Social versus Leisure skills emerged. Regarding the Conceptual domain, a greater deficit in Functional Academics was observed. In the Practical domain, we found a greater impairment in Self-Care skills. Conversely, Home Living skills appeared as a strength compared to other skills. The results are discussed in reference to literature.</p> <p>Keywords: Autism spectrum disorder; Floor effect; Adaptive behavior; ABAS-II; Adolescence</p> <hd id="AN0159632202-2">Introduction</hd> <p>Adaptive behavior is a set of skills that allows people to meet age-related societal expectations and standards of personal independence and social responsibility. Specifically, adaptive behavior encompasses conceptual, social and practical skills that are necessary to perform independently during daily activities across different settings, as at home, at school/work and within the community (Schalock et al., [<reflink idref="bib42" id="ref1">42</reflink>]; Sparrow et al., [<reflink idref="bib46" id="ref2">46</reflink>]; Tassé & Grover, [<reflink idref="bib48" id="ref3">48</reflink>]). These skills are learned throughout development, and they become more advanced with age (Harrison, [<reflink idref="bib15" id="ref4">15</reflink>]; Widaman et al., [<reflink idref="bib52" id="ref5">52</reflink>]).</p> <p>Interest in adaptive behavior began growing at the end of 1950s, when it was first included among criteria for intellectual disability (Heber, [<reflink idref="bib17" id="ref6">17</reflink>]). While it remains fundamental in the diagnosis of the severity of intellectual disability (APA, [<reflink idref="bib1" id="ref7">1</reflink>]), impairments in adaptive behavior may also be observed in other neurodevelopmental disorders, as Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD), as well as in other behavioral, emotional and learning difficulties with partially intact cognitive functions (Ditterline & Oakland, [<reflink idref="bib9" id="ref8">9</reflink>]; Tasse et al., [<reflink idref="bib49" id="ref9">49</reflink>]).</p> <p>The assessment of adaptive behavior appears very complex for a variety of reasons. First, it must evaluate level, quality, fluency and pattern across different domains (e.g., communication, socialization, school, free time, motor), in order to produce a comprehensive report of strengths and weaknesses. It is important to distinguish what a person can do from what they really do in everyday living situations. Second, the direct observation of adaptive behavior is seldom practical, considering one would have to observe a person in a wide variety of settings attempting many different skills. Thus, indirect methods are usually preferred and include interviews—unstructured, semi-structured or structured—and checklists. These measures are administered or completed by parents, teachers or other caregivers who live in close contact with the person being evaluated (Ferri et al., [<reflink idref="bib12" id="ref10">12</reflink>]; Sparrow et al., [<reflink idref="bib45" id="ref11">45</reflink>]). Third, it is not unusual to observe a floor effect—the lowest level of behavioral performance assessed—when raw scores are converted into standard scores. This effect may determine a flat profile, thus obscuring some strengths (Fenton et al., [<reflink idref="bib11" id="ref12">11</reflink>]).</p> <p>In Italy, only three instruments are norm-referenced scores, have good psychometric proprieties, and allow to evaluate multiple domains of adaptive behavior: The Adaptive Behavior Assessment System-Second Edition (ABAS-2; Harrison & Oakland, [<reflink idref="bib16" id="ref13">16</reflink>]; Ferri et al., [<reflink idref="bib12" id="ref14">12</reflink>]), the Vineland Adaptive Behavior Scales-Second Edition (VABS-II; Balboni et al., [<reflink idref="bib3" id="ref15">3</reflink>]; Sparrow et al., [<reflink idref="bib46" id="ref16">46</reflink>]), and the Adaptive Behavior Inventory (ABI; Brown & Dario, [<reflink idref="bib5" id="ref17">5</reflink>]; Brown & Leigh, [<reflink idref="bib6" id="ref18">6</reflink>]). In a study comparing adaptive behavior measures for children with ASD (Lopata et al., [<reflink idref="bib27" id="ref19">27</reflink>]), scores on social domain derived from the ABAS-II and the VABS-II did not significantly differ each other. However, the ABAS-II showed a higher sensitivity compared to the VABS-II, capturing lower-level adaptive skills underpinning other domains (e.g., daily living skills, communication). For this reason, we focused on the ABAS for our study.</p> <p>The ABAS allows a comprehensive evaluation of adaptive functioning in the home and community. It is available in different versions according to age: Parent/Primary Caregiver Form (0–5 years), Parent Form (5–21 years), Teacher/Day Care Provider Form (2–5 years), Teacher Form (5–21 years), Adult Form (16–89 years). The Parent Form—which was used in the current study—includes the assessment of ten skill areas (Communication, Community Use, Functional Academics, Home Living, Health and Safety, Leisure, Self-Care, Self-Direction, Social, and Work) and an overall adaptive functioning, namely the General Adaptive Composite. Ten skills are combined to form three broad domains of adaptive behavior: Conceptual, Social and Practical. The Conceptual domain includes Communication, Functional Academics, and Self-Direction. The Social domain encompasses Social and Leisure. The Practical domain includes Community Use, Home Living, Health and Safety, and Self-Care.</p> <hd id="AN0159632202-3">Autism Spectrum Disorder and Adaptive Behavior</hd> <p>ASD is a neurodevelopmental disorder whose prevalence is estimated to vary from 1.9/10,000 to 72.6/10,000 in Europe (for systematic review, see Elsabbagh et al., [<reflink idref="bib10" id="ref20">10</reflink>]), with a male-to-female ratio of 4:1 (Baio, [<reflink idref="bib2" id="ref21">2</reflink>]; Rapporti ISTISAN, [<reflink idref="bib19" id="ref22">19</reflink>]). ASD is characterized by deficits in social communication and social interactions as well as the presence of restricted and repetitive behaviors and interests. The latter refers to stereotypical or repetitive motor movements, rigid routines, difficulties in coping with change, and narrow interests, whereas deficits in social communication and interactions include impairments in social-emotional reciprocity, non-verbal communication behaviors and interpersonal relationships (APA, [<reflink idref="bib1" id="ref23">1</reflink>]).</p> <p>There is a wide variability in the diagnostic characteristics of people with ASD that concerns the type of symptoms experienced, the onset and duration of symptoms, and which areas of functioning are compromised (Volkmar et al., [<reflink idref="bib51" id="ref24">51</reflink>]; Wozniak et al., [<reflink idref="bib53" id="ref25">53</reflink>]). Furthermore, cognitive functioning contributes to variability within the group of individuals with ASD, with about 44% of children with ASD having a medium or medium–high intelligence quotient (IQ; Christensen et al., [<reflink idref="bib7" id="ref26">7</reflink>]; Pugliese et al., [<reflink idref="bib37" id="ref27">37</reflink>]). Beyond intelligence quotient and cognitive abilities, the variability of autism symptoms is also associated with linguistic and adaptive behavior, and this phenotypic variability tends to change over time (Billstedt et al., [<reflink idref="bib4" id="ref28">4</reflink>]; Georgiades et al., [<reflink idref="bib13" id="ref29">13</reflink>]). Caregivers report more severe symptoms of autism in early childhood than they do in adolescence and adulthood (Billstedt et al., [<reflink idref="bib4" id="ref30">4</reflink>]; Taylor & Selzer, [<reflink idref="bib50" id="ref31">50</reflink>]). Billstedt et al. ([<reflink idref="bib4" id="ref32">4</reflink>]) suggest that adults with ASD are less likely to have serious communication problems (e.g., delayed echolalia) than younger people. However, in adolescence it is possible to observe marked regressions in cognitive and behavioral domains (Périsse et al., [<reflink idref="bib34" id="ref33">34</reflink>]).</p> <p>The link between adaptive functioning and variables like age, IQ and ASD symptoms has not been fully understood perhaps due to mixed results provided by studies, where different measurements and sampling techniques were used (Lopata et al., [<reflink idref="bib26" id="ref34">26</reflink>]; McDonald et al., [<reflink idref="bib32" id="ref35">32</reflink>], [<reflink idref="bib31" id="ref36">31</reflink>]). In general, positive relations between IQ and adaptive functioning, as evaluated through the VABS, have been confirmed in different studies (Kanne et al., [<reflink idref="bib20" id="ref37">20</reflink>]; Klin et al., [<reflink idref="bib22" id="ref38">22</reflink>]; McDonald et al., [<reflink idref="bib32" id="ref39">32</reflink>]; Perry et al., [<reflink idref="bib35" id="ref40">35</reflink>]; Saulnier & Klin, [<reflink idref="bib41" id="ref41">41</reflink>]). In particular, adaptive behavior impairments are more evident in people with low-functioning ASD (LFASD), in which adaptive behavior appears consistent with cognitive level. However, these impairments are also present among people with high-functioning ASD (HFASD), in which there is a gap between IQ and adaptive functioning that increases with age (Kanne et al., [<reflink idref="bib20" id="ref42">20</reflink>]; Klin et al., [<reflink idref="bib22" id="ref43">22</reflink>]; Liss et al., [<reflink idref="bib25" id="ref44">25</reflink>]; Matthews et al., [<reflink idref="bib30" id="ref45">30</reflink>]; Szatmari et al., [<reflink idref="bib47" id="ref46">47</reflink>]). Conversely, Liss et al. ([<reflink idref="bib25" id="ref47">25</reflink>]) suggest that, while IQ is predictive of adaptive behavior in people with LFASD, other characteristics in people with HFASD, such as autism symptoms, language and verbal memory, affect adaptive behavior, and may explain the presence of a gap in people with HFASD.</p> <p>Some studies have documented a negative correlation between age and adaptive functioning (Kanne et al., [<reflink idref="bib20" id="ref48">20</reflink>]; Klin et al., [<reflink idref="bib22" id="ref49">22</reflink>]; Perry et al., [<reflink idref="bib35" id="ref50">35</reflink>]; Saulnier & Klin, [<reflink idref="bib41" id="ref51">41</reflink>]). However, this trend conflicts with longitudinal studies, which suggest that greater autonomy in daily life skills as people age (Green & Carter, [<reflink idref="bib14" id="ref52">14</reflink>]; Smith et al., [<reflink idref="bib44" id="ref53">44</reflink>]).</p> <p>Studies using the ABAS have indicated that there is no relationship between either age or IQ and adaptive behavior (Kenworthy et al., [<reflink idref="bib21" id="ref54">21</reflink>]; Lopata et al., [<reflink idref="bib26" id="ref55">26</reflink>]). In particular, Kenworthy et al. ([<reflink idref="bib21" id="ref56">21</reflink>]) found a positive relation only between IQ and the Conceptual domain of the ABAS-II in HFASD adolescents aged from 12 to 22 years. However, they did not find a significative relationship between age and adaptive skills. The same results are confirmed by Lopata et al ([<reflink idref="bib26" id="ref57">26</reflink>]). It is important to note that these studies, which are among the few to use ABAS-II scales, both utilized homogeneous HFASD samples. More recently, McDonald et al. ([<reflink idref="bib31" id="ref58">31</reflink>]) investigated adaptive functioning in two groups aged 7–12 with HFASD and LFASD. In contrast with results found by Kenworthy et al. ([<reflink idref="bib21" id="ref59">21</reflink>]) and Lopata et al. ([<reflink idref="bib26" id="ref60">26</reflink>]), their study found that in children with HFASD, adaptive skills were significantly related to age whereas no relationship was found with IQ. In children with LFASD, no significant relationship between adaptive functioning and age was found, but IQ was significantly related to overall adaptive ability and all domains of the ABAS-II. These findings appear to suggest that as cognitive ability increases, the adaptive skills of a child with LFASD are also expected to increase.</p> <p>More mixed results have been obtained when the relationship between adaptive functioning and ASD symptoms was analyzed (Lopata et al., [<reflink idref="bib26" id="ref61">26</reflink>]; McDonald et al., [<reflink idref="bib32" id="ref62">32</reflink>]), especially when the VABS had been used. While some studies reported a negative correlation between adaptive behavior and ASD symptoms (Liss et al., [<reflink idref="bib25" id="ref63">25</reflink>]; Perry et al., [<reflink idref="bib35" id="ref64">35</reflink>]), others did not confirm this relationship, suggesting that adaptive behaviors could be relatively independent of ASD clinical symptoms (Kanne et al., [<reflink idref="bib20" id="ref65">20</reflink>]; Klin et al., [<reflink idref="bib22" id="ref66">22</reflink>]; Saulnier & Klin, [<reflink idref="bib41" id="ref67">41</reflink>]). However, the results are homogenous in studies where the ABAS-II was used, confirming a negative relationship between adaptive functioning and ASD symptoms (Kenworthy et al., [<reflink idref="bib21" id="ref68">21</reflink>]; Lopata et al., [<reflink idref="bib26" id="ref69">26</reflink>]). In particular, Kenworthy et al. ([<reflink idref="bib21" id="ref70">21</reflink>]) found that the ABAS-II overall adaptive functioning (e.g., General Adaptive Composite) and domains are negatively associated with the scores derived from the Autistic Diagnostic Observation Schedule (ADOS; Lord et al., [<reflink idref="bib29" id="ref71">29</reflink>]), addressing communication and social interaction areas. No relationship emerged between ADOS stereotyped behavior and ABAS-II scores. Different results were found when the Autism Diagnostic Interview-Revised (ADI-R; Le Couteur et al., [<reflink idref="bib24" id="ref72">24</reflink>]) was used. In the study carried out by Lopata et al. ([<reflink idref="bib26" id="ref73">26</reflink>]), the total score on the ABAS-II are negatively associated with the total score on ADI-R. Moreover, a negative relationship was found between the area of restricted, repetitive, and stereotyped patterns of behavior, derived from the ADI-R and ABAS-II social and practical domains.</p> <p>These mixed results are probably due to variations in the different tools used to assess ASD symptoms in different studies, such as the ADOS (Lord et al., [<reflink idref="bib28" id="ref74">28</reflink>]), ADI-R (Rutter et al., [<reflink idref="bib40" id="ref75">40</reflink>]), the Wing Autism Diagnostic Interview Checklist (WADIC; Rapin, [<reflink idref="bib38" id="ref76">38</reflink>]) and the Childhood Autism Rating Scale (CARS; Kanne et al., [<reflink idref="bib20" id="ref77">20</reflink>]; Kenworthy et al., [<reflink idref="bib21" id="ref78">21</reflink>]; Klin et al., [<reflink idref="bib22" id="ref79">22</reflink>]; Liss et al., [<reflink idref="bib25" id="ref80">25</reflink>]; Lopata et al., [<reflink idref="bib26" id="ref81">26</reflink>]; Perry et al., [<reflink idref="bib35" id="ref82">35</reflink>]; Saulnier & Klin, [<reflink idref="bib41" id="ref83">41</reflink>]; Schopler et al., [<reflink idref="bib43" id="ref84">43</reflink>]). Nevertheless, in most of these studies homogeneous samples HFASD were enrolled. This issue might contribute to the mixed findings among studies (Lopata et al., [<reflink idref="bib26" id="ref85">26</reflink>]; McDonald et al., [<reflink idref="bib31" id="ref86">31</reflink>]). Klin et al. ([<reflink idref="bib23" id="ref87">23</reflink>]) observed that the typical VABS profile for ASD individuals is characterized by weaknesses in socialization and, although to a lesser extent, communication. On the other hand, there are strengths in the skills needed for everyday life (e.g. personal care and care living in the community). McDonald et al. ([<reflink idref="bib32" id="ref88">32</reflink>]) confirmed this results in a sample of children with HFASD.</p> <p>Beyond the VABS/VABS-2, little research has been carried out using the ABAS-II, although it is the only adaptive functioning measure developed according to the definition of the American Association on Intellectual and Developmental Disabilities (AAIDD,), addressing three broad domains of adaptive behavior: Conceptual, Social and Practical (Kenwhorty et al., [<reflink idref="bib21" id="ref89">21</reflink>]; Lopata et al., [<reflink idref="bib26" id="ref90">26</reflink>]; McDonald et al., [<reflink idref="bib32" id="ref91">32</reflink>]).</p> <p>Kenworthy et al. ([<reflink idref="bib21" id="ref92">21</reflink>]) examined the adaptive functioning profiles of adolescents with HFASD, as assessed by the ABAS-II. They found a general impairment in all three ABAS-II domains. Specifically, Social and Home living scales arose as weaknesses, whereas the Functional Academics scale scores showed a strength. Similar results emerged in Lopata et al. ([<reflink idref="bib26" id="ref93">26</reflink>]), examining the ABAS-II adaptive functioning profile in youth with HFASD aged 7–12 years. Specifically, they found significant deficits on General Adaptive Composite and all three adaptive composites, with the lowest scores in Social, Home living and Self-Direction. In a subsequent study, Lopata et al. ([<reflink idref="bib27" id="ref94">27</reflink>]) compared the profile yielded from the VABS-II, the ABAS-II with the BASC-II (Reynolds & Kamphaus, [<reflink idref="bib39" id="ref95">39</reflink>]) parent-rated adaptive behavior of 6- to 11-year-olds with HFASD. The three adaptive measures revealed significant deficits, with the VABS-II and the ABAS-II indicating relative weaknesses in social skills and strengths in academic-related skills.</p> <p>In study by McDonald et al. ([<reflink idref="bib31" id="ref96">31</reflink>]) comparing children aged 6–12 years with HFASD and LFASD, the authors showed that the first group had cognitive strengths and adaptive deficits, while children with LFASD had better adaptive skills than cognitive abilities. This contrasts with studies using VABS-II that suggest a congruence between cognitive level and adaptive functioning (Kanne et al., [<reflink idref="bib20" id="ref97">20</reflink>]; Klin et al., [<reflink idref="bib22" id="ref98">22</reflink>]).</p> <hd id="AN0159632202-4">The Object of the Current Study</hd> <p>As a whole, the evaluation of adaptive behavior is far from easy, especially in people with low skill levels, who are more likely to be subject to a floor effect. Consequently, it is very common to find flat profiles that emphasize weaknesses and obscure strengths. The current study aims to counteract the floor effect in the assessment of adaptive behavior of adolescents with ASD, as derived by the Italian version of ABS-II (Ferri et al., [<reflink idref="bib12" id="ref99">12</reflink>]). In reaching this goal, the statistical Hessl method (Hessl et al., [<reflink idref="bib18" id="ref100">18</reflink>]) and its revision by Orsini et al. ([<reflink idref="bib33" id="ref101">33</reflink>]) were used.</p> <hd id="AN0159632202-5">Method</hd> <p></p> <hd id="AN0159632202-6">Participants and Procedure</hd> <p>The group included 47 mothers (Mean Age = 54.61; SD = 4.63) of adolescents (13 girls and 34 boys) with ASD who were attending public middle and high schools in Rome. The adolescents ranged in age from 12 to 18 years (Mean Age = 15.87; SD = 1.68) and met DSM-IV-TR criteria for ASD (Autism or Pervasive Developmental Disorder Not Otherwise Specified), confirmed prior to their participation in the study by experienced psychiatrists and psychologists (IQ total score, M = 63.57, SD = 14.02). Among mothers, 38.3% (n = 18) had attended high school, 46.81% university (n = 22), and 14.89% (n = 7) had completed a PhD course or other advanced specialization.</p> <p>Caregivers, who provided informed consent, were asked to complete the Italian version of the ABAS-II (Ferri et al., [<reflink idref="bib12" id="ref102">12</reflink>]) to assess the adaptive functioning of their daughters and sons. The administration took approximately 30 min to complete. To ensure higher reliability, the Italian version of ABAS-II was administered to each participant's parent by the same professional.</p> <p>This study was reviewed and approved by the Ethics Commission of <emph>XXX (Blinded for review).</emph> For clarity, we will refer to the adolescents themselves as "participants" throughout this paper, although their mothers completed the measures.</p> <hd id="AN0159632202-7">Instruments</hd> <p>The Italian version of the Adaptive Behavior Assessment System—Second Edition (ABAS-II) Parent Form (5–21 years; Ferri et al., [<reflink idref="bib12" id="ref103">12</reflink>]) is a comprehensive measure of adaptive functioning at home and within the community. It consists of 232 items, each rated on a scale from 0 (not able) to 3 (always/almost always).</p> <p>The parental form includes 10 skill areas—Communication, Community Use, Functional Academics, Home Living, Health and Safety, Leisure, Self-Care, Self-Direction, Social, and Work [Work is only completed for individuals ≥ 17]—which are combined to form three composite indices, including Conceptual (CON; Communication, Functional Academics, Self-Direction), Social (SOC; Leisure, Social), and Practical (PRAC; Self-Care, Home Living, Community Use, and Health and Safety), as well as an overall General Adaptive Composite (GAC). The ABAS-II composite scores have a mean of 100 (SD = 15), while scores for each skill area have means of 10 (SD = 3). Higher scores represent better adaptive functioning. For details about the psychometric properties of the Italian version of the ABAS-II, see Ferri et al. ([<reflink idref="bib12" id="ref104">12</reflink>]).</p> <hd id="AN0159632202-8">Data Analysis</hd> <p></p> <hd id="AN0159632202-9">Step 1: Canonical Transformation of Raw Scores</hd> <p>Raw scores on the ABAS-II subtests were converted into weighted scores (mean = 10 and standard deviation = 3, with a range from 1 to 19) according to the conversion tables of the Italian ABAS-II standardization. Domain and composite scores have a norm-referenced M = 100 and SD = 15. In the Italian ABAS-II standardization sample, the lower adaptive domain scores are on Conceptual Index (<reflink idref="bib57" id="ref105">57</reflink>), Social Index (<reflink idref="bib50" id="ref106">50</reflink>), Practical Index (<reflink idref="bib44" id="ref107">44</reflink>) and General Adaptive Composite (<reflink idref="bib40" id="ref108">40</reflink>). Then, the percentage of adolescents with ASD who achieved a weighted score of 1 on nine subtests was calculated.</p> <hd id="AN0159632202-10">Step 2: New Transformation as Proposed by Hessl et al. (2009) and Orsini et al. (2015)</hd> <p>Using the method proposed by Hessl et al. ([<reflink idref="bib18" id="ref109">18</reflink>]) and extended by Orsini et al. ([<reflink idref="bib33" id="ref110">33</reflink>]), the raw scores of subtests that correspond to a weighted score (ws) of 1 were transformed into <emph>z</emph>-scores using means and standard deviations of the raw scores of the subtests for each age group. All other weighted scores higher than 1 were transformed into <emph>z</emph>-scores using the inverse formula of their composition in the standardization process: <emph>z</emph> = (ws − 10)/3. The sums of the <emph>z</emph>-score components of the three indices (Conceptual, Social, Practical) and the General Adaptive Composite Index, were calculated, transforming these sums into new <emph>z</emph>-scores and later into standard scores with a mean of 100 and a standard deviation of 15. In this way, the resulting measures of indices are expressed in <emph>z</emph>-scores, and therefore, the floor effect presented by a minimum score of 40 is overcome. For more detailed information about this statistical method, see Orsini et al. ([<reflink idref="bib33" id="ref111">33</reflink>]) and Pezzuti et al. ([<reflink idref="bib36" id="ref112">36</reflink>]). In summary, in order to overcome the floor effect, while Hessl's method explains how to convert the raw scores into the weighted scores, Orsini's method goes a step further in calculating the indices.</p> <p>Consider, for example, the raw scores of an 18-year-old male on the three subtests (Communication, Functional Academics and Self-Direction) of the Conceptual Index, reported in column A of Table 1, Using the canonical method, such raw scores would be all converted to a weighted point of 1 (see column b) corresponding to a normalized <emph>z</emph>-score of − 3 (see column c), corresponding (after appropriate psychometric transformations) to an adaptive domain score of 57. If instead one uses the means and standard deviations of the age-relevant reference sample of the subject (see column d), the new <emph>z</emph>-scores are lower (see column e). Then, the <emph>z</emph>-scores (column f) are converted to a new <emph>z</emph>-score by the means and standard deviations of the weighted scores of the entire standardization sample (column H) and finally converted to adaptive domain score (M = 100; SD = 15) by the formula Z (<reflink idref="bib15" id="ref113">15</reflink>) + 100 (see column I) to obtain the new Conceptual Index. We can see that the new Conceptual Index value drops to 10 points, which is lower than the 57 points obtained using the canonical method.</p> <p>Table 1 Example of computing new conceptual index on data of one boy of 18 years of age</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"><p>Subtest</p></th><th align="left"><p>A</p></th><th align="left"><p>B</p></th><th align="left"><p>C</p></th><th align="left"><p>d</p></th><th align="left"><p>e</p></th><th align="left"><p>f</p></th><th align="left"><p>g</p></th><th align="left"><p>h</p></th><th align="left"><p>i</p></th></tr><tr><th align="left"><p>Raw score</p><p>(x)</p></th><th align="left"><p>Range of raw score corresponding to a weighted score (ws) of 1</p></th><th align="left"><p>Normalized x scores = (ws − 10)/3</p></th><th align="left"><p>Mean (M) and standard deviation (sd) of the raw scores of the subtests on group of 18 years of age</p></th><th align="left"><p>z new points (z<sub>n</sub>) with Orsini et al. (<xref ref-type="bibr" rid="bibr33">2015</xref>) method:</p><p>z = (x − M)/sd</p></th><th align="left"><p>Sum of the z<sub>n</sub> points about Conceptual Index</p></th><th align="left"><p>Mean (M<sub>w</sub>) and standard deviation (sd<sub>w</sub>) of weighted scores about Conceptual Index (in Italian standardization)</p></th><th align="left"><p>Z = (z<sub>n</sub> − M<sub>w</sub>)/sd<sub>w</sub></p></th><th align="left"><p>IQ<sub>Conc</sub> = Z (15) + 100</p></th></tr></thead><tbody><tr><td align="left"><p>Communication</p></td><td align="left"><p><bold>32</bold></p></td><td align="left"><p><bold>0–50</bold></p></td><td align="left"><p> − 3</p></td><td align="left"><p>65.83 (5.31)</p></td><td align="left"><p> − 6.37</p></td><td align="left"><p> − 14.47</p></td><td align="left"><p> − 0.03 (2.4)</p></td><td align="left"><p> − 6.02</p></td><td align="left"><p>10</p></td></tr><tr><td align="left"><p>Functional academics</p></td><td align="left"><p><bold>35</bold></p></td><td align="left"><p><bold>0–46</bold></p></td><td align="left"><p> − 3</p></td><td align="left"><p>62.31 (5.94)</p></td><td align="left"><p> − 4.60</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left"><p>Self-direction</p></td><td align="left"><p><bold>34</bold></p></td><td align="left"><p><bold>0–40</bold></p></td><td align="left"><p> − 3</p></td><td align="left"><p>63.43 (8.40)</p></td><td align="left"><p> − 3.50</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr></tbody></table> </ephtml> </p> <hd id="AN0159632202-11">Results</hd> <p></p> <hd id="AN0159632202-12">Step 1: Analysis of Canonical Scores on the ABAS-II for the ASD Sample</hd> <p>Using the canonical transformation of the raw scores according to the conversion tables of the ABAS-II Italian standardization (Ferri et al., [<reflink idref="bib12" id="ref114">12</reflink>]), a very high percentage of subtests with a weighted score of 1 occurred in the sample. Table 2 shows the percentage of adolescents with ASD who achieved a weighted score of 1 on nine of the ABAS-II subtests. In detail, there were subtests that, more than others, had a weighted score of 1, such as Social, (74.5%), followed by Functional Academics (61.7%), Communication (59.6%), Community Use and Self-Direction (both 57.4%), and Leisure (55.3%). So, the three subtests of Conceptual and the two subtests of Social each had a higher frequency of weighted scores of 1. The smallest proportion occurred in Home Living (25.5%).</p> <p>Table 2 Percentage of adolescents with ASD with weighted score of 1 to 9 core ABAS-II subtest</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Subtest</p></th><th align="left"><p>F</p></th><th align="left"><p>f%</p></th></tr></thead><tbody><tr><td align="left"><p>Communication</p></td><td align="left"><p>28</p></td><td char="." align="char"><p>59.6</p></td></tr><tr><td align="left"><p>Community use</p></td><td align="left"><p>27</p></td><td char="." align="char"><p>57.4</p></td></tr><tr><td align="left"><p>Functional academics</p></td><td align="left"><p>29</p></td><td char="." align="char"><p>61.7</p></td></tr><tr><td align="left"><p>Home living</p></td><td align="left"><p>12</p></td><td char="." align="char"><p>25.5</p></td></tr><tr><td align="left"><p>Health and safety</p></td><td align="left"><p>18</p></td><td char="." align="char"><p>38.3</p></td></tr><tr><td align="left"><p>Leisure</p></td><td align="left"><p>26</p></td><td char="." align="char"><p>55.3</p></td></tr><tr><td align="left"><p>Self-care</p></td><td align="left"><p>18</p></td><td char="." align="char"><p>38.3</p></td></tr><tr><td align="left"><p>Self-direction</p></td><td align="left"><p>27</p></td><td char="." align="char"><p>57.4</p></td></tr><tr><td align="left"><p>Social</p></td><td align="left"><p>35</p></td><td char="." align="char"><p>74.5</p></td></tr></tbody></table> </ephtml> </p> <p>There was a total of 423 scores on the subtests (47 subjects × 9 subtests); 220 scores (52%) correspond to a weighted score of 1 (Table 3). This data confirmed the level of impairments in adolescents with ASD.</p> <p>Table 3 Percentage and cumulative (cum) percentage of weighted scores in the sample</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Weighted score</p></th><th align="left"><p>Number of subtests</p></th><th align="left"><p>Percentage</p></th><th align="left"><p>Cum %</p></th></tr></thead><tbody><tr><td align="left"><p>1</p></td><td align="left"><p>220</p></td><td char="." align="char"><p>52.0</p></td><td char="." align="char"><p>52.0</p></td></tr><tr><td align="left"><p>2</p></td><td align="left"><p>18</p></td><td char="." align="char"><p>4.3</p></td><td char="." align="char"><p>56.3</p></td></tr><tr><td align="left"><p>3</p></td><td align="left"><p>20</p></td><td char="." align="char"><p>4.7</p></td><td char="." align="char"><p>61.0</p></td></tr><tr><td align="left"><p>4</p></td><td align="left"><p>18</p></td><td char="." align="char"><p>4.3</p></td><td char="." align="char"><p>65.2</p></td></tr><tr><td align="left"><p>5</p></td><td align="left"><p>26</p></td><td char="." align="char"><p>6.1</p></td><td char="." align="char"><p>71.4</p></td></tr><tr><td align="left"><p>6</p></td><td align="left"><p>21</p></td><td char="." align="char"><p>5.0</p></td><td char="." align="char"><p>76.4</p></td></tr><tr><td align="left"><p>7</p></td><td align="left"><p>11</p></td><td char="." align="char"><p>2.6</p></td><td char="." align="char"><p>79.0</p></td></tr><tr><td align="left"><p>8</p></td><td align="left"><p>24</p></td><td char="." align="char"><p>5.7</p></td><td char="." align="char"><p>84.6</p></td></tr><tr><td align="left"><p>9</p></td><td align="left"><p>20</p></td><td char="." align="char"><p>4.7</p></td><td char="." align="char"><p>89.4</p></td></tr><tr><td align="left"><p>10</p></td><td align="left"><p>19</p></td><td char="." align="char"><p>4.5</p></td><td char="." align="char"><p>93.9</p></td></tr><tr><td align="left"><p>11</p></td><td align="left"><p>4</p></td><td char="." align="char"><p>0.9</p></td><td char="." align="char"><p>94.8</p></td></tr><tr><td align="left"><p>12</p></td><td align="left"><p>8</p></td><td char="." align="char"><p>1.9</p></td><td char="." align="char"><p>96.7</p></td></tr><tr><td align="left"><p>13</p></td><td align="left"><p>5</p></td><td char="." align="char"><p>1.2</p></td><td char="." align="char"><p>97.9</p></td></tr><tr><td align="left"><p>14</p></td><td align="left"><p>5</p></td><td char="." align="char"><p>1.2</p></td><td char="." align="char"><p>99.1</p></td></tr><tr><td align="left"><p>15</p></td><td align="left"><p>2</p></td><td char="." align="char"><p>0.5</p></td><td char="." align="char"><p>99.5</p></td></tr><tr><td align="left"><p>16</p></td><td align="left"><p>1</p></td><td char="." align="char"><p>0.2</p></td><td char="." align="char"><p>99.8</p></td></tr><tr><td align="left"><p>17</p></td><td align="left"><p>1</p></td><td char="." align="char"><p>0.2</p></td><td char="." align="char"><p>100.0</p></td></tr></tbody></table> </ephtml> </p> <p>47 adolescents × 9 subtests = 423 subtest scores</p> <p>Table 4 shows the means and standard deviations of weighted scores (ws) for the nine ABAS-II subtests and the values expressed into <emph>z</emph>-scores using the inverse formula of their transformation: <emph>z</emph> = (ws − 10)/3. These means are 2 to 2.5 standard deviations below the mean. This transformation in <emph>z</emph>-scores is necessary to compare them with the results of the method proposed by Hessl et al. ([<reflink idref="bib18" id="ref115">18</reflink>]) and Orsini et al. ([<reflink idref="bib33" id="ref116">33</reflink>]), which were shown in Step 2.</p> <p>Table 4 Means and standard deviations (SDs) of the weighted scores of nine subtests calculated according to traditional method and their transformation into z points</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"><p>Subtest</p></th><th align="left" colspan="2"><p>Weighted scores</p></th><th align="left" colspan="2"><p>Normalized z scores</p></th></tr><tr><th align="left"><p>M</p></th><th align="left"><p>SD</p></th><th align="left"><p>M</p></th><th align="left"><p>SD</p></th></tr></thead><tbody><tr><td align="left"><p>Communication</p></td><td char="." align="char"><p>3.62</p></td><td char="." align="char"><p>3.75</p></td><td align="left"><p> − 2.13</p></td><td char="." align="char"><p>1.25</p></td></tr><tr><td align="left"><p>Community use</p></td><td char="." align="char"><p>3.77</p></td><td char="." align="char"><p>4.16</p></td><td align="left"><p> − 2.08</p></td><td char="." align="char"><p>1.39</p></td></tr><tr><td align="left"><p>Functional academics</p></td><td char="." align="char"><p>4.30</p></td><td char="." align="char"><p>4.95</p></td><td align="left"><p> − 1.90</p></td><td char="." align="char"><p>1.65</p></td></tr><tr><td align="left"><p>Home living</p></td><td char="." align="char"><p>5.36</p></td><td char="." align="char"><p>3.81</p></td><td align="left"><p> − 1.55</p></td><td char="." align="char"><p>1.27</p></td></tr><tr><td align="left"><p>Health and safety</p></td><td char="." align="char"><p>4.79</p></td><td char="." align="char"><p>3.83</p></td><td align="left"><p> − 1.74</p></td><td char="." align="char"><p>1.28</p></td></tr><tr><td align="left"><p>Leisure</p></td><td char="." align="char"><p>2.66</p></td><td char="." align="char"><p>2.60</p></td><td align="left"><p> − 2.45</p></td><td char="." align="char"><p>0.87</p></td></tr><tr><td align="left"><p>Self-care</p></td><td char="." align="char"><p>4.19</p></td><td char="." align="char"><p>3.50</p></td><td align="left"><p> − 1.94</p></td><td char="." align="char"><p>1.17</p></td></tr><tr><td align="left"><p>Self-direction</p></td><td char="." align="char"><p>3.40</p></td><td char="." align="char"><p>3.23</p></td><td align="left"><p> − 2.20</p></td><td char="." align="char"><p>1.08</p></td></tr><tr><td align="left"><p>Social</p></td><td char="." align="char"><p>2.40</p></td><td char="." align="char"><p>2.95</p></td><td align="left"><p> − 2.53</p></td><td char="." align="char"><p>0.98</p></td></tr></tbody></table> </ephtml> </p> <p>The means of the three indices computed using the canonical method for our participants were 66.81 (SD = 17.57) for Conceptual, 58.55 (SD = 14.16) for Social, and 64.45 (SD = 19.90) for Practical, with a range between averages of 5.5 points and with Social emerging as lower than the other two indices. When the pairs of indices were compared, ANOVAs showed significant differences only for Conceptual/Social (F<subs>(<reflink idref="bib1" id="ref117">1</reflink>,<reflink idref="bib92" id="ref118">92</reflink>)</subs> = 6.29; p = 0.01; eta<sups>2</sups> = 0.06). In summary, a fairly flat pattern of scores was observed.</p> <hd id="AN0159632202-13">Step 2: Use of Raw Scores with New Method and Comparison with the Canonical Method</hd> <p>A second transformation of the raw scores was carried out using the method proposed by Hessl et al. ([<reflink idref="bib18" id="ref119">18</reflink>]) and extended by Orsini et al. ([<reflink idref="bib33" id="ref120">33</reflink>]) to allow the calculation of indices, as described in the Method section. The steps are shown in Table 1 from column F to column I. Table 5 shows means and standard deviation of the <emph>z</emph>-scores of the nine ABAS-II subtests calculated using the two methods.</p> <p>Table 5 Means and standard deviation (SD) of z points to subtests calculated with the traditional method and that developed by Orsini et al. ([<reflink idref="bib33" id="ref121">33</reflink>]) methods</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"><p>Subtest</p></th><th align="left" colspan="2"><p>Normalized z scores</p></th><th align="left" colspan="2"><p>Z points with the Orsini et al. (<xref ref-type="bibr" rid="bibr33">2015</xref>) method</p></th><th align="left" rowspan="2"><p>F<sub>(1,92)</sub></p></th><th align="left" rowspan="2"><p><italic>p</italic></p></th><th align="left" rowspan="2"><p>Partial eta<sup>2</sup></p></th></tr><tr><th align="left"><p>M</p></th><th align="left"><p>SD</p></th><th align="left"><p>M</p></th><th align="left"><p>SD</p></th></tr></thead><tbody><tr><td align="left"><p>Communication</p></td><td align="left"><p> − 2.13</p></td><td char="." align="char"><p>1.25</p></td><td align="left"><p> − 4.10</p></td><td char="." align="char"><p>3.56</p></td><td char="." align="char"><p>12.81</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.12</p></td></tr><tr><td align="left"><p>Community use</p></td><td align="left"><p> − 2.08</p></td><td char="." align="char"><p>1.39</p></td><td align="left"><p> − 3.17</p></td><td char="." align="char"><p>2.50</p></td><td char="." align="char"><p>06.82</p></td><td char="." align="char"><p> < 0.01</p></td><td char="." align="char"><p>0.07</p></td></tr><tr><td align="left"><p>Functional academics</p></td><td align="left"><p> − 1.90</p></td><td char="." align="char"><p>1.65</p></td><td align="left"><p> − 4.95</p></td><td char="." align="char"><p>4.59</p></td><td char="." align="char"><p>18.38</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.17</p></td></tr><tr><td align="left"><p>Home living</p></td><td align="left"><p> − 1.55</p></td><td char="." align="char"><p>1.27</p></td><td align="left"><p> − 1.66</p></td><td char="." align="char"><p>1.47</p></td><td char="." align="char"><p>00.16</p></td><td char="." align="char"><p> < 0.680</p></td><td char="." align="char"><p>0.00</p></td></tr><tr><td align="left"><p>Health and safety</p></td><td align="left"><p> − 1.74</p></td><td char="." align="char"><p>1.28</p></td><td align="left"><p> − 2.79</p></td><td char="." align="char"><p>3.02</p></td><td char="." align="char"><p>04.90</p></td><td char="." align="char"><p> < 0.030</p></td><td char="." align="char"><p>0.05</p></td></tr><tr><td align="left"><p>Leisure</p></td><td align="left"><p> − 2.45</p></td><td char="." align="char"><p>0.87</p></td><td align="left"><p> − 3.52</p></td><td char="." align="char"><p>2.04</p></td><td char="." align="char"><p>10.89</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.11</p></td></tr><tr><td align="left"><p>Self-care</p></td><td align="left"><p> − 1.94</p></td><td char="." align="char"><p>1.17</p></td><td align="left"><p> − 6.22</p></td><td char="." align="char"><p>8.44</p></td><td char="." align="char"><p>11.85</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.11</p></td></tr><tr><td align="left"><p>Self-direction</p></td><td align="left"><p> − 2.20</p></td><td char="." align="char"><p>1.08</p></td><td align="left"><p> − 3.31</p></td><td char="." align="char"><p>2.27</p></td><td char="." align="char"><p>09.22</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.09</p></td></tr><tr><td align="left"><p>Social</p></td><td align="left"><p> − 2.53</p></td><td char="." align="char"><p>0.98</p></td><td align="left"><p> − 5.44</p></td><td char="." align="char"><p>3.70</p></td><td char="." align="char"><p>27.28</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.22</p></td></tr></tbody></table> </ephtml> </p> <p>Partial eta-squared values were calculated as a measure of effect size, and results were interpreted using Cohen's ([<reflink idref="bib8" id="ref122">8</reflink>]) guidelines for determining small (0.01), medium (0.06), and large (0.14) effects</p> <p>Compared with the canonical method, the method developed by Orsini et al. ([<reflink idref="bib33" id="ref123">33</reflink>]) allowed a greater decrease in means, a significant increase in standard deviations and essentially a much larger interindividual variability. A similar result emerged for the indices (Table 6), where a wider variability of scores is obtained with Orsini et al.'s ([<reflink idref="bib33" id="ref124">33</reflink>]) method compared to the traditional method.</p> <p>Table 6 Means and standard deviation of z points to indices calculated with the traditional and the Orsini et al.'s ([<reflink idref="bib33" id="ref125">33</reflink>]) methods respectively</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"><p>Indices</p></th><th align="left" colspan="2"><p>Normalized z scores</p></th><th align="left" colspan="2"><p>Z points with the Orsini et al.'s (<xref ref-type="bibr" rid="bibr33">2015</xref>) method</p></th><th align="left" rowspan="2"><p>F<sub>(1,92)</sub></p></th><th align="left" rowspan="2"><p><italic>p</italic></p></th><th align="left" rowspan="2"><p>Partial eta<sup>2</sup></p></th></tr><tr><th align="left"><p>M</p></th><th align="left"><p>SD</p></th><th align="left"><p>M</p></th><th align="left"><p>SD</p></th></tr></thead><tbody><tr><td align="left"><p>Conceptual</p></td><td align="left"><p> − 6.23</p></td><td char="." align="char"><p>3.60</p></td><td align="left"><p> − 12.37</p></td><td char="." align="char"><p>09.96</p></td><td char="." align="char"><p>15.80</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.15</p></td></tr><tr><td align="left"><p>Social</p></td><td align="left"><p> − 4.98</p></td><td char="." align="char"><p>1.69</p></td><td align="left"><p> − 8.96</p></td><td char="." align="char"><p>05.55</p></td><td char="." align="char"><p>22.11</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.19</p></td></tr><tr><td align="left"><p>Practical</p></td><td align="left"><p> − 7.30</p></td><td char="." align="char"><p>4.50</p></td><td align="left"><p> − 13.84</p></td><td char="." align="char"><p>14.26</p></td><td char="." align="char"><p>08.98</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.09</p></td></tr></tbody></table> </ephtml> </p> <p>Partial eta-squared values were calculated as a measure of effect size, and results were interpreted using Cohen's ([<reflink idref="bib8" id="ref126">8</reflink>]) guidelines for determining small (0.01), medium (0.06), and large (0.14) effects</p> <p>As shown in Table 7, the new adaptive domain scores are lower than the means calculated with the traditional method, however the differences between the new pairs of means are not statistically significant (see Table 8). Analysis of pairs of subtests on each index were performed, resulting in the following (see Table 8): In the pair comparison between Community Use, Home Living, Health and Safety and Self-Care of participants there were more weaknesses in Self-Care. In the comparison between Community Use and Home Living there were more weaknesses in Community Use. In the comparison between Leisure and Social there were more weaknesses in Social.</p> <p>Table 7 Means and standard deviation of adaptive domain scores to indices calculated with the traditional and the Orsini et al's ([<reflink idref="bib33" id="ref127">33</reflink>]) methods respectively</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"><p>Indices</p></th><th align="left" colspan="4"><p>Traditional method</p></th><th align="left" colspan="4"><p>Method of Orsini et al. (<xref ref-type="bibr" rid="bibr33">2015</xref>)</p></th><th align="left" rowspan="2"><p>F<sub>(1,92)</sub></p></th><th align="left" rowspan="2"><p><italic>p</italic></p></th><th align="left" rowspan="2"><p>Partial eta<sup>2</sup></p></th></tr><tr><th align="left"><p>Min</p></th><th align="left"><p>Max</p></th><th align="left"><p>M</p></th><th align="left"><p>SD</p></th><th align="left"><p>Min</p></th><th align="left"><p>Max</p></th><th align="left"><p>M</p></th><th align="left"><p>SD</p></th></tr></thead><tbody><tr><td align="left"><p>Conceptual</p></td><td char="." align="char"><p>57.0</p></td><td char="." align="char"><p>117.0</p></td><td char="." align="char"><p>66.81</p></td><td char="." align="char"><p>17.56</p></td><td align="left"><p> − 96.5</p></td><td char="." align="char"><p>116.9</p></td><td char="." align="char"><p>22.92</p></td><td char="." align="char"><p>62.23</p></td><td char="." align="char"><p>21.65</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.19</p></td></tr><tr><td align="left"><p>Social</p></td><td char="." align="char"><p>50.0</p></td><td char="." align="char"><p>100.0</p></td><td char="." align="char"><p>58.55</p></td><td char="." align="char"><p>14.16</p></td><td align="left"><p> − 58.9</p></td><td char="." align="char"><p>100.0</p></td><td char="." align="char"><p>23.90</p></td><td char="." align="char"><p>47.16</p></td><td char="." align="char"><p>23.29</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.20</p></td></tr><tr><td align="left"><p>Practical</p></td><td char="." align="char"><p>44.0</p></td><td char="." align="char"><p>111.0</p></td><td char="." align="char"><p>64.45</p></td><td char="." align="char"><p>19.89</p></td><td align="left"><p> − 193.3</p></td><td char="." align="char"><p>118.3</p></td><td char="." align="char"><p>29.47</p></td><td char="." align="char"><p>73.78</p></td><td char="." align="char"><p>09.85</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.09</p></td></tr></tbody></table> </ephtml> </p> <p>Partial eta-squared values were calculated as a measure of effect size, and results were interpreted using Cohen's ([<reflink idref="bib8" id="ref128">8</reflink>]) guidelines for determining small (0.01), medium (0.06), and large (0.14) effects</p> <p>Table 8 Comparisons between pairs of subtests and indices using the Orsini et al.'s ([<reflink idref="bib33" id="ref129">33</reflink>]) method</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"><p>Adaptive domain indices</p></th><th align="left" rowspan="2"><p>Comparison between subtest (in z means points)</p></th><th align="left"><p>M</p></th><th align="left"><p>SD</p></th><th align="left"><p>M</p></th><th align="left"><p>SD</p></th><th align="left" rowspan="2"><p>F</p></th><th align="left" rowspan="2"><p><italic>p</italic></p></th><th align="left" rowspan="2"><p>Partial Eta<sup>2</sup></p></th></tr><tr><th align="left" colspan="2"><p>Subtest 1</p></th><th align="left" colspan="2"><p>Subtest 2</p></th></tr></thead><tbody><tr><td align="left" rowspan="3"><p>Conceptual</p></td><td align="left"><p>Communication vs. Functional academics</p></td><td align="left"><p> − 4.10</p></td><td align="left"><p>3.56</p></td><td align="left"><p> − 4.95</p></td><td char="." align="char"><p>4.59</p></td><td char="." align="char"><p>1.01</p></td><td char="." align="char"><p>0.310</p></td><td char="." align="char"><p>0.01</p></td></tr><tr><td align="left"><p>Communication vs. Self-direction</p></td><td align="left"><p> − 4.10</p></td><td align="left"><p>3.56</p></td><td align="left"><p> − 3.31</p></td><td char="." align="char"><p>2.27</p></td><td char="." align="char"><p>1.63</p></td><td char="." align="char"><p>0.200</p></td><td char="." align="char"><p>0.02</p></td></tr><tr><td align="left"><p>Functional academics vs. Self-direction</p></td><td align="left"><p> − 4.95</p></td><td align="left"><p>4.59</p></td><td align="left"><p> − 3.31</p></td><td char="." align="char"><p>2.27</p></td><td char="." align="char"><p>4.82</p></td><td char="." align="char"><p>0.030</p></td><td char="." align="char"><p>0.05</p></td></tr><tr><td align="left"><p>Social</p></td><td align="left"><p>Leisure vs. Social</p></td><td align="left"><p> − 3.52</p></td><td align="left"><p>2.04</p></td><td align="left"><p> − 5.44</p></td><td char="." align="char"><p>3.70</p></td><td char="." align="char"><p>9.81</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.09</p></td></tr><tr><td align="left" rowspan="6"><p>Practical</p></td><td align="left"><p>Community use vs. Home living</p></td><td align="left"><p> − 3.17</p></td><td align="left"><p>2.50</p></td><td align="left"><p> − 1.66</p></td><td char="." align="char"><p>1.47</p></td><td char="." align="char"><p>12.70</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.12</p></td></tr><tr><td align="left"><p>Community use vs. Health and safety</p></td><td align="left"><p> − 3.17</p></td><td align="left"><p>2.50</p></td><td align="left"><p> − 2.79</p></td><td char="." align="char"><p>3.02</p></td><td char="." align="char"><p>0.42</p></td><td char="." align="char"><p>0.520</p></td><td char="." align="char"><p>0.01</p></td></tr><tr><td align="left"><p>Community use vs. Self-care</p></td><td align="left"><p> − 3.17</p></td><td align="left"><p>2.50</p></td><td align="left"><p> − 6.22</p></td><td char="." align="char"><p>8.44</p></td><td char="." align="char"><p>5.64</p></td><td char="." align="char"><p>0.020</p></td><td char="." align="char"><p>0.06</p></td></tr><tr><td align="left"><p>Home living vs. Health and safety</p></td><td align="left"><p> − 1.66</p></td><td align="left"><p>1.47</p></td><td align="left"><p> − 2.79</p></td><td char="." align="char"><p>3.02</p></td><td char="." align="char"><p>5.37</p></td><td char="." align="char"><p>0.020</p></td><td char="." align="char"><p>0.05</p></td></tr><tr><td align="left"><p>Home living vs. Self-care</p></td><td align="left"><p> − 1.66</p></td><td align="left"><p>1.47</p></td><td align="left"><p> − 6.22</p></td><td char="." align="char"><p>8.44</p></td><td char="." align="char"><p>13.28</p></td><td char="." align="char"><p> < 0.001</p></td><td char="." align="char"><p>0.13</p></td></tr><tr><td align="left"><p>Health and safety vs. Self-care</p></td><td align="left"><p> − 2.79</p></td><td align="left"><p>3.02</p></td><td align="left"><p> − 6.22</p></td><td char="." align="char"><p>8.44</p></td><td char="." align="char"><p>6.84</p></td><td char="." align="char"><p> < 0.010</p></td><td char="." align="char"><p>0.07</p></td></tr></tbody></table> </ephtml> </p> <p>Table 8 Comparisons between pairs of subtests and indices using the Orsini et al.'s ([<reflink idref="bib33" id="ref130">33</reflink>]) method</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Adaptive Domain Indices</p></th><th align="left"><p>Comparison between indices (in standardized points)</p></th><th align="left" colspan="2"><p>Index 1</p></th><th align="left" colspan="2"><p>Index 2</p></th><th align="left" colspan="3" /></tr></thead><tbody><tr><td align="left" rowspan="3" /><td align="left"><p>Conceptual vs. Social</p></td><td align="left"><p>22.92</p></td><td align="left"><p>62.23</p></td><td align="left"><p>23.90</p></td><td align="left"><p>47.16</p></td><td align="left"><p>0.01</p></td><td align="left"><p>0.930</p></td><td align="left"><p>0.00</p></td></tr><tr><td align="left"><p>Conceptual vs. Practical</p></td><td align="left"><p>22.92</p></td><td align="left"><p>62.23</p></td><td align="left"><p>29.47</p></td><td align="left"><p>73.78</p></td><td align="left"><p>0.21</p></td><td align="left"><p>0.640</p></td><td align="left"><p>0.00</p></td></tr><tr><td align="left"><p>Social vs. Practical</p></td><td align="left"><p>23.90</p></td><td align="left"><p>47.16</p></td><td align="left"><p>29.47</p></td><td align="left"><p>73.78</p></td><td align="left"><p>0.19</p></td><td align="left"><p>0.660</p></td><td align="left"><p>0.00</p></td></tr></tbody></table> </ephtml> </p> <p>Partial eta<sups>2</sups> values were calculated as a measure of effect size, and results were interpreted using Cohen's ([<reflink idref="bib8" id="ref131">8</reflink>]) guidelines for determining small (0.01), medium (0.06), and large (0.14) effects</p> <p>Finally, when we analyzed the Adaptive Domain Index calculated with the new method, they ranged between 1 and 112, but there are 14 adaptive domain scores (30%) off the scale, i.e. with <emph>z</emph> < − 6.66 points (i.e. 14 Adaptive Domain Index scores are below 1).</p> <hd id="AN0159632202-14">Discussion and Conclusion</hd> <p>ASD is a long-life disorder characterized by social and communication deficits with narrow and repetitive behaviors and interests (APA, [<reflink idref="bib1" id="ref132">1</reflink>]). The assessment of adaptive behavior is central to identify the severity of impairments in self-sufficiency, independence and daily functioning (Klin et al., [<reflink idref="bib23" id="ref133">23</reflink>]) as well as to plan goals in clinical, family and school settings (Tasse et al., [<reflink idref="bib49" id="ref134">49</reflink>]). However, the evaluation of adaptive behavior may be challenging with people who have lower levels of abilities. The main problem is linked to the floor effect, which produces flat profiles. Consequently, strengths are often concealed, and weaknesses appear predominant.</p> <p>The aim of this study is to counteract floor effects in the evaluation of adaptive behavior in adolescents with ASD, as derived from the Italian version of the ABAS-II (Ferri et al., [<reflink idref="bib12" id="ref135">12</reflink>]). Specifically, we compared the profiles yielded by the traditional method—transformation of raw scores into weighted scores—with those computed through the statistical Hessl method (Hessl et al., [<reflink idref="bib18" id="ref136">18</reflink>]) and its extension developed by Orsini et al. ([<reflink idref="bib33" id="ref137">33</reflink>]). Previous studies (Orsini et al., [<reflink idref="bib33" id="ref138">33</reflink>]; Pezzuti et al., [<reflink idref="bib36" id="ref139">36</reflink>]) demonstrated that the latter method overcomes the limits underpinning floor effect problems through <emph>z</emph>-score normalization.</p> <p>As hypothesized, a higher variation in adaptive behavior in adolescents with ASD was found with Orsini et al.'s ([<reflink idref="bib33" id="ref140">33</reflink>]) method compared to the traditional method. In particular, there was a general impairment across all three domains (Conceptual, Social, and Practical domains) of the ABAS-II and there is no greater impairment of Social domain than the other two—Conceptual and Practical. Moreover, within the Social domain, we found a greater impairment in Social than Leisure skills. These results are consistent with study by Kenworthy et al. ([<reflink idref="bib21" id="ref141">21</reflink>]) and they can be explained if we analyze the items of Leisure and Social subscales. The Social subscale is characterized by items that assess purely social skills, such as the ability to relate to others, awareness of their own and other people's emotions, friendship, respect for shared social rules, courtesy skills (e.g. saying "thank you," "please," "sorry"). The items of the Leisure subscale, instead, involve questions that concern many skills and activities that are "non-social," such as playing solitaire, listening to music, reading a book, organization skills and free time planning (Kenworthy et al., [<reflink idref="bib21" id="ref142">21</reflink>]). Thus, it could be hypothesized that the inclusion of these "non-social" elements in the Social composite score leads to an underestimation of social deficits in ASD (Kenworthy et al., [<reflink idref="bib21" id="ref143">21</reflink>]).</p> <p>The results concerning the Conceptual and Practical domains conflict with evidence provided by the literature (Kenworthy et al., [<reflink idref="bib21" id="ref144">21</reflink>]; Lopata et al., [<reflink idref="bib26" id="ref145">26</reflink>]). Regarding the Conceptual domain, our results seem to suggest a greater weakness in Functional Academics, in contrast with previous studies that found both a strength in these abilities together and a positive correlation between IQ levels and Conceptual scores (Kenworthy et al., [<reflink idref="bib21" id="ref146">21</reflink>]; Lopata et al., [<reflink idref="bib26" id="ref147">26</reflink>]). These results could be explained by focusing on IQ levels. In studies carried out by Kenworthy et al. ([<reflink idref="bib21" id="ref148">21</reflink>]) and Lopata et al. ([<reflink idref="bib26" id="ref149">26</reflink>]), the HFASD participants had IQs > 100, whereas in our study, the LFASD adolescents were enrolled.</p> <p>When the subscales of the Practical domain were analyzed, we found a greater impairment of Self-Care skills. Conversely, Home Living skills appeared as a strength compared to other skills. These results disagree with Kenworthy et al. ([<reflink idref="bib21" id="ref150">21</reflink>]), who suggested a greater weakness in Home living than Community Use, Self-Care and Health and Safety abilities. This may be due to a cultural difference between American and Italian families, but further research would be needed to explore the role of cultural differences in the development of adaptive behavior.</p> <p>During adolescence, adult-mediated social relationships tend to diminish compared to childhood and the need for adolescents to be able to relate to others independently increases. The typical characteristics of ASD make the development of this social autonomy even more complicated, so it is essential to design interventions aimed at maximizing the opportunities for socialization. By increasing social opportunities, the adolescent with ASD will have more opportunities to engage with peers and this engagement may be helpful in improving other aspects related to autonomy in daily life.</p> <p>As a whole, the current study confirms the goodness of the procedure developed by Hessl et al. ([<reflink idref="bib18" id="ref151">18</reflink>]) and revised by Orsini et al. ([<reflink idref="bib33" id="ref152">33</reflink>]) to overcome floor effect problems in the evaluation of adaptive behaviors in adolescents with ASD, especially those with LFASD. In light of this issue, we recommend the use of renormalized scores in both research and clinical areas for its practical implications. From a research perspective, the renormalization and improved sensitivity of adaptive behavior testing for individuals with ASD, especially those with low functioning, may allow for more powerful research designs, contributing to further understanding of the interplay between behavioral, biological and cognitive phenotypes. From a clinical point of view, the renormalized scores can provide a more accurate profile of strengths and weaknesses, allowing clinicians and educators to plan intervention programs and monitor progress over time.</p> <p>Despite these appreciable results and implications, this study has some limitations. First, the low number of participants in the current study necessitates caution in interpreting the results. Second, our assessment of adaptive behavior is limited to the use of the ABAS-II. This is a reliable and valid tool; however, the comparison between performances obtained by different instruments may be informative regarding the validity of this approach to overcome flooring problems. Moreover, a restricted age range was considered, although the ABAS allows to evaluate adaptive behavior from childhood to adulthood. Future research could expand the age range or consider different age groups to study any differences in adaptive skills of the population with ASD.</p> <p>Finally, all of our participants were adolescents with ASD, future investigations should examine the sensitivity of adaptive behavior testing in other neurodevelopmental disorders at different ages.</p> <hd id="AN0159632202-15">Authors Contributions</hd> <p>The authors discussed the contents of this article together. Fiorenzo Laghi, Rosa Ferri and Lina Pezzuti conceptualized the study elaborated on the research design and hypotheses, and contributed to the interpretation of research findings. Elvira Caramuscio, Antonia Lonigro, and Monica Rea collected data and contributed to writing and editing of this paper and collected the references and carried out management activities to scrub and maintain research data. Lina Pezzuti and Fiorenzo Laghi devised the methodological content, analyzed the data, and contributed to the interpretation of research findings. Fiorenzo Laghi, Rosa Ferri, and Lina Pezzuti wrote the final version of this paper.</p> <hd id="AN0159632202-16">Declarations</hd> <p></p> <hd id="AN0159632202-17">Conflict of interest</hd> <p>We confirm that we have not conflict of interest in this research.</p> <hd id="AN0159632202-18">Ethical Approval</hd> <p>The research has been approved by the ethical committee of the Department of Dynamic and Clinical Psychology, and Health Studies of the Faculty of Medicine and Psychology of the Sapienza University of Rome.</p> <hd id="AN0159632202-19">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0159632202-20"> <title> References </title> <blist> <bibl id="bib1" idref="ref7" type="bt">1</bibl> <bibtext> American Psychiatric Association. 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  Data: The Floor Effect on the ABAS-II in Adolescents with Autism Spectrum Disorder
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  Data: <searchLink fieldCode="AR" term="%22Laghi%2C+Fiorenzo%22">Laghi, Fiorenzo</searchLink><br /><searchLink fieldCode="AR" term="%22Ferri%2C+Rosa%22">Ferri, Rosa</searchLink><br /><searchLink fieldCode="AR" term="%22Caramuscio%2C+Elvira%22">Caramuscio, Elvira</searchLink><br /><searchLink fieldCode="AR" term="%22Lonigro%2C+Antonia%22">Lonigro, Antonia</searchLink><br /><searchLink fieldCode="AR" term="%22Rea%2C+Monica%22">Rea, Monica</searchLink><br /><searchLink fieldCode="AR" term="%22Pezzuti%2C+Lina%22">Pezzuti, Lina</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-5810-4185">0000-0001-5810-4185</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Autism+and+Developmental+Disorders%22"><i>Journal of Autism and Developmental Disorders</i></searchLink>. Nov 2022 52(11):4975-4985.
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Data: 11
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  Data: 2022
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="DE" term="%22Adolescents%22">Adolescents</searchLink><br /><searchLink fieldCode="DE" term="%22Autism+Spectrum+Disorders%22">Autism Spectrum Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Behavior%22">Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Daily+Living+Skills%22">Daily Living Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+Methods%22">Evaluation Methods</searchLink>
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  Data: 10.1007/s10803-021-05369-y
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  Data: 0162-3257<br />1573-3432
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  Data: The present study aimed at enhancing the assessment of adaptive behavior in adolescents with Autism Spectrum Disorder through the Adaptive Behavior Assessment System-Second Edition. To overcome the limits underpinning floor effect, which are commonly observed with the traditional methods, the statistical Hessl method and its revision by Orsini, Pezzuti and Hulbert was adopted. The results showed a more variation using the former method compared to the latter: a greater impairment in Social versus Leisure skills emerged. Regarding the Conceptual domain, a greater deficit in Functional Academics was observed. In the Practical domain, we found a greater impairment in Self-Care skills. Conversely, Home Living skills appeared as a strength compared to other skills. The results are discussed in reference to literature.
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  Data: 2022
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        PageCount: 11
        StartPage: 4975
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      – SubjectFull: Adolescents
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      – SubjectFull: Autism Spectrum Disorders
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      – SubjectFull: Behavior
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      – SubjectFull: Daily Living Skills
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      – SubjectFull: Evaluation Methods
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      – SubjectFull: Adaptive Behavior Scale
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      – TitleFull: The Floor Effect on the ABAS-II in Adolescents with Autism Spectrum Disorder
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