I’m a fan of the ATEC. Not only because it was one of the first instruments specifically devised to look at measuring changes to autistic symptom. The Autism Treatment Evaluation Checklist (ATEC) was designed nearly two decades ago to provide such a tool, but the norms on the. The Autism Treatment Evaluation Checklist (ATEC) is a great tool for clinicians and parents to evaluate treatments based on autistic symptoms. ATEC scores.
|Published (Last):||5 April 2004|
|PDF File Size:||4.39 Mb|
|ePub File Size:||8.62 Mb|
|Price:||Free* [*Free Regsitration Required]|
If parents could administer regular psychometric evaluations of their children, then the cost of clinical trials will be reduced, enabling longer clinical trials with the larger number of participants.
Here we report the norms of the observational ayec who voluntarily completed ATEC evaluations over the period of four years from to The regular assessment of symptom dynamics in children with Autism Spectrum Disorder ASD participating in a ahec trial has been a long-standing challenge.
A common hurdle in these efforts is the availability of trained technicians needed to conduct rigorous and consistent assessment of children at multiple time points [ 12 ]. Importantly, ATEC was not designed for diagnostic purposes; only to measure changes in ASD severity, making it useful in tracking the ate of a treatment.
Autism Treatment Evaluation Checklist – Wikipedia
This paper reports the norms for the longitudinal changes auhism ATEC scores amongst participants from various countries undergoing a variety of treatments and seeks to develop an outline for tracking developmental changes in individuals with ASD. ATEC is comprised of four subscales: These four subscales are used to calculate auttism total score that ranges from 0 to A lower score indicates less severe symptoms of ASD and a higher score correlates with more severe symptoms of ASD [ 3 ].
The subscales provide survey takers information about specific areas of behavior which may change over time. A trial conducted by Magiati et al. The study utilized ATEC to monitor the progress of 22 schoolchildren over a five-year period. This trial was conducted over a six-month time frame, with outcome assessments at the 3-month and 6-month time xutism.
These studies support the viability of ATEC as a tool for longitudinal measurement of ASD severity that can be a vital instrument in tracking symptom changes during a clinical trial. The current observational study was initiated nearly two decades ago when one of the authors Dr. Initially, ATEC evaluations were distributed as hard copy. In the online version of ATEC autsm developed. The participant responses to the online version of ATEC are presented in this manuscript.
Autism Treatment Evaluation Checklist
A total score and four subscale scores are reported. Questions in the first xtec subscales are scored using a 0—2 scale. ATEC can be accessed online or in hard-copy format. The Sociability subscale contains 20 items and participants can score from 0— The scores from each subscale are combined in order to calculate a Total Score, which ranges 0— points.
A lower score indicates a lower severity of ASD symptoms.
In order to generate ATEC norms, changes in score from one whole-year age to another were calculated for each participant Figure 1.
For these calculations, participants who had completed at least atsc evaluation at two consecutive year-age time-points were selected. For example, in the 2 to 3 age-pair norms calculation, a participant must have completed their first evaluation anytime between the ages 1. When more than one evaluation was completed by a participant at any given age, the evaluations were afec. Note that most participants did not complete ATEC over multiple years and thus provided only a single pair of data points.
Participants were then sorted by their initial ATEC auitsm score into bins in point increments. The lines in Figure 1 connect the average scores in each pair of these observations. Each point represents an average of all participants who completed their first evaluation at one whole-year age and their second evaluation at a following whole-year age. For example, in the 2 to 3 age-pair calculation norms vertical arrowa participant must have completed their first evaluation anytime between the ages 1.
For example, participants with an initial ATEC total score of 64 at the age of 2 years had on average reduced their score to 48 by the age of 3 years Figure 1vertical taec.
The change in the score from the age of 3 years to the age of 4 years in participants with the average score of 48 at the age of 3 years, however, is unknown. To mitigate this uncertainty, a statistical inference was made utilizing the two numerically closest observations at a given age. In this example, the two closest defined values to the score of 48 at the age of 3 years are 55 and The participants with initial score of 55 at the age of 3 years have on average reduced their score to 41 by the age of 4 years.
Those participants with initial score of 45 at the age of 3 years have on average reduced their score to 36 by the age of 4 years. Thus, a corresponding ATEC total score value at the age of 4 years was generated to link the score 48 at the age of 3 years to the inferred score of 37 at the age of 4. For example, a typical child with ATEC total score of at age 2 is expected to reduce ATEC total score to 86 at age 3; 68 at age 4; 56 at age 5; 48 at age 6; 39 at age 7; 36 at age 8; 32 at age 9; 27 at age 10; 26 at age 11; and 28 at age After excluding participants that did not meet the aforementioned criteria for the study, there were total participants.
Mathematically, the decrease of the ATEC total score is best described by an exponent with a time constant of 3. The constant baseline scores were proportional to ATEC total score at the age of 2 years, indicating predictive power of this score for ASD symptom severity later in life.
The score for each subscale as a function of age was calculated using a procedure identical to that used for calculating ATEC total score, Figure 3Figure 4Figure 5 and Figure 6. Table 2Table 3Table 4 and Table 5 present the developmental norms for each subscale. Sociability subscale score norms as a function of the initial score and age from Figure 4. Design considerations for an early-intervention clinical trial for ASD must take into account 1 the trial duration, 2 number of participants, and 3 the quality of participant assessment.
About the Autism Treatment Evaluation Checklist (ATEC)
A short clinical trial of an early therapeutic intervention in two- to three-year-old children can easily miss a target, as an improvement of symptoms may not emerge until children reach the school age.
Small numbers of participants can easily skew the data as ASD is known to be a highly heterogeneous disorder. Trial duration and numbers of participants both serve as key measures of the rigor of a clinical trial for any therapeutic intervention. Increasing the clinical trial duration and the number of trial participants, however, raises the demand for regular assessment of participants by trained psychometric technicians.
Furthermore, to attain a larger aurism of trial participants, clinical trials must accept participants across a large geographical region. The logistical issues associated with such an endeavor come at immense cost. As a result, large numbers of ASD clinical trials working under a limited budget suffer from short duration and low participant number, often compromising the trial objectives e.
ATEC was in part designed to circumvent these problems. If caregivers could serve as psychometric technicians and conduct regular evaluations of their children, the cost of clinical trials will be substantially reduced while simultaneously allowing for longer trial duration.
This manuscript attempts to characterize the typical changes in ATEC score over time as a function of children initial age and ASD severity in a large and diverse group of participants. In doing so, it lends support to the efficacy of caregiver-driven psychometric observation, which when applied at scale, may be a viable alternative to using licensed technicians to assess the children. A primary goal in developing the continuous distribution charts in this paper is to provide a basis for tracking development in individuals with ASD.
Currently no easily accessible atsc metric for ASD development exists. All of these tools are expensive aktism, designed to be administered by a trained examiner, and not readily available to caregivers. Furthermore, none of these tools have agec developmental norms [ 15 ]. When tracked annually, these distributions may function much like childhood growth charts utilized by physicians to track childhood physical development.
Caregivers will also be able to engage in informed discussion with therapists with regard to therapy effectiveness. A similar trend is observed in all subscales and may indicate normal developmental changes. Participants exhibiting an ATEC total score above 70 at the age of two years improve their symptoms exponentially but seem to reach a constant baseline around the age of The score at the baseline is proportional to the Total score at the age of two.
In other words, the ATEC total score at the age of 12 zutism be predicted from the total score at the age of two years. Surprisingly, for participants with an ATEC total score below 70 at the age of two years the ATEC total score increases after the age of 7 indicating deterioration of symptoms. This increase in the score is observed in the Communication subscale Figure 3the Sociability subscale Figure 4and the Sensory subscale Figure 5but is absent in the Physical subscale Figure 6.
This deterioration of symptoms may be attributed to different interpretation of ATEC questions at different ages. Consider the Sociability subscale, which shows most significant deterioration of symptoms Figure 4. Other symptoms described in the Sociability subscale, such as questions 6: Participant selection presents a novel challenge in a study focused on caregiver-administered assessments.
Thus, some of the participants may have been lacking ASD diagnosis altogether. As neurotypical children develop faster, the presence of neurotypical children in the dataset would have artificially increased the magnitude of annual changes of ATEC scores, predominantly for younger participants with mild ASD.
A requirement for ASD diagnosis, however, would have presented its own set of challenges. Notably, as ASD diagnoses are not apparent for many years, any potential data that could have been gathered from younger individuals would need to be eliminated until the confirmation of the diagnosis.
This issue is compounded by diagnostic recommendations that are geographically inconsistent, resulting in variable selection criteria. For multiple reasons, it is unlikely that there were many neurotypical participants in the database utilized for this paper.
First, the ATEC questionnaire is virtually unknown outside the autism community. Second, there is little incentive for the parents of neurotypical children to complete multiple exhaustive ATEC questionnaires unless one of the children was previously diagnosed with ASD.
Despite this effort, the reported data may over-approximate the magnitude of annual changes of ATEC scores, especially in the younger participants with mild ASD. Another limitation is associated with the wide definition of a whole-year age established to assess pair-wise changes in the ATEC score from one age to another. For example, it is possible that a parent s administered the checklist at 2.
Further studies with larger number of participants should be able to shorten the age group definition from whole-year to six months and possibly even three months. There is an understanding in the psychology community that parents cannot be trusted with an evaluation of their own children. However, by measuring the change in score over multiple assessments, pattern of changes could be extracted. When a single parent completes the same evaluation every three months over multiple years, changes in the score become meaningful.
As noted previously by other groups [ 108 ], the use of ATEC as a primary outcome measure has some inherent drawbacks. While the ATEC is capable of delineating incremental differences in ASD severity amongst participants, the variety of measures amongst its subscales fails to differentiate developmental-specific from symptom-specific changes.
This aspect of the ATEC may introduce a confounding variable when participants are at different developmental stages and on unique developmental trajectories during a study. As noted previously, certain phenomena observed in ATEC score changes may be an artifact of different caregiver interpretations of behaviors at different ages. To mitigate these effects, trial designs must accurately separate participants based on developmental stage. This is most often accomplished by using age as a proxy for developmental stage.
The model showed no difference in improvement between the two sex groups [ 16 ]. One surprising finding was that children from developed English-speaking countries improved less than children from the rest of the world [ 16 ].
Accordingly, an attempt was made to generate norms separately for developed English-speaking countries and the rest of the world.