- Email: [email protected]
Interventions used with an Australian sample of preschool children with autism spectrum disorders
Research in Autism Spectrum Disorders 5 (2011) 1033–1041
Contents lists available at ScienceDirect
Research in Autism Spectrum Disorders Journal homepage: http://ees.elsevier.com/RASD/default.asp
Interventions used with an Australian sample of preschool children with autism spectrum disorders Mark Carter a,*, Jacqueline Roberts b, Katrina Williams c, David Evans d, Trevor Parmenter e, Natalie Silove f, Trevor Clark g, Anthony Warren g a
Macquarie University Special Education Centre, Macquarie University, NSW 2109, Australia Faculty of Education, University of Canberra, Australia Faculty of Medicine, University of New South Wales, Australia d Faculty of Education, University of Sydney, Australia e Sydney School of Medicine, University of Sydney, Australia f The Children’s Hospital at Westmead, Australia g Autism Spectrum Australia (Aspect), Australia b c
A R T I C L E I N F O
A B S T R A C T
Article history: Received 16 November 2010 Accepted 29 November 2010 Available online 30 December 2010
This study examined the previous and current range of educational, therapy, medical and CAM interventions used by a clearly described Australian sample of 84 families of preschool-aged children with autism spectrum disorders who were enrolled in a controlled trial of early intervention services. With regard to educational and therapy interventions, the most frequently used services were speech–language pathology, preschool and childcare, generic early intervention, and occupational therapy. With the exception of preschool and childcare, the access frequency for most of these services indicated they were used at relatively low intensity. Exclusion diets, oils/fatty acids and vitamin and mineral supplements were the primary CAM interventions used by families. There was no clear evidence of a relationship between the number of interventions used by families and developmental status although this may have been due to the relatively recent diagnoses. Implications of these findings and directions for future research are discussed. Crown Copyright ß 2010 Published by Elsevier Ltd. All rights reserved.
Keywords: Autism Parents Survey Treatment Education Complementary and alternative medicine
1. Introduction There has been substantial interest in autism spectrum disorders (ASDs) over recent years, probably associated with reports of increase in prevalence (Thomas, Morrissey, & McLaurin, 2007). The development of the Internet over the past decade and a half has provided parents with unprecedented access to largely unfiltered information on ASD and a wide array of treatments. These include conventional education, therapy, medical and complementary and alternative medicine (CAM) interventions. These treatments range from theoretically plausible interventions with supporting empirical evidence to implausible interventions that have been substantively disproved or may even be dangerous (Metz, Mulick, & Butter, 2005). Further, some interventions entail substantial financial and time costs to families. Consequently, there has been interest in the treatment options selected by families of children with ASD.
* Corresponding author. Tel.: +61 0 2 9850 7880; fax: +61 0 2 9850 8254. E-mail address: [email protected] (M. Carter). 1750-9467/$ – see front matter . Crown Copyright ß 2010 Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.rasd.2010.11.009
1034
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
Green et al. (2006) conducted an Internet survey of interventions used by parents of children with ASD. Information about the survey was distributed through autism associations and colleagues of the researchers. A total of 552 usable responses were obtained and 80% of these were from the USA. Approximately one-third of the children were of preschool age, a further third were 6–10 years, 18% were 11–14 years and 12% were 15 years or older. Parents reported they were currently using a mean of seven treatments compared with a mean of eight treatments in the past (i.e., those that were not currently used). Younger children used a greater number of interventions, as did those with more severe autistic symptomatology. Interventions were analyzed according to type/severity of disability and there were large and significant differences in several broad classes of intervention but no such analysis was conducted for age. A number of limitations of the Green et al. (2006) study should be noted. Given the methodology employed, both the response rate and representativeness of the sample remain unknown. The researchers noted that occupational and physical therapies were mistakenly left off the survey and they may have been under-reported. In addition, information regarding the diagnosis of ASD and the level of disability was necessarily based on parent report. Goin-Kochel, Myers, and Mackintosh (2007) extended the study of Green et al. (2006) with an Internet survey of drug, diet and behavioral/educational/alternative interventions that parents of children with ASD, including pervasive developmental disability-not otherwise specified (PDD-NOS), had tried or were currently using. A range of interventions was listed and respondents were given a limited option of adding treatments. The survey was advertised through autism support organizations. Responses were obtained worldwide although 77.5% of the 479 usable responses were from the USA. Again, given the methodology employed, both the response rate and representativeness of the sample remain unknown. Results were analyzed in terms of parent reported diagnosis as well as age. On average, children were currently receiving between four and six treatments and had received between seven and nine in the past. There were a number of distinctive and significant age-related patterns in treatment usage. Younger children tended to use more dietary and behavioral/educational/alternative interventions, while pharmacological intervention was most prominent for adolescents. These differences may have reflected both a changing pattern in parent preferences over time (e.g., exhausting educational treatments before considering medication) as well as cohort effects as some types of services were not available when adolescents were younger (Goin-Kochel et al., 2007). Nevertheless, the study does illustrate that patterns of service access may change very considerably over time. A number of earlier studies have focused on younger children. Kohler (1999) conducted telephone surveys of 25 families with children aged 3–9 years who were diagnosed with autism or pervasive developmental disabilities, although it was unclear how these diagnoses were obtained and confirmed. The children were serviced by four organizations in Pennsylvania and the response rate to invitation to participate in the study was 83%. Parents were asked to provide information on types and amounts of services they had received in the past 6 months. School or preschool placements were used most frequently (all children) while speech therapy (88%) and occupational therapy (56%) were also ranked highly. For preschool children, a mean of approximately six services were received and these children received a mean of 33 h of service per week but, presumably, much of this was associated with the preschool placements. Smith and Antolovich (2000) surveyed 290 families enrolled in a consultation-based intervention service based on the UCLA behavior analytic program. Families were asked about non-behavioral supplementary interventions they were receiving or had received in the past. Families self-referred to the program and children were under 5 years of age at the point of program commencement. The response rate was 42% and all children were reported as having a diagnosis of autism from an unaffiliated psychologist or physician although further detail of diagnostic protocols was not provided. Parents were provided with a list of therapies, which the researchers regarded as ‘‘unvalidated’’, and had the option of adding additional interventions. Parents were asked to identify the interventions they had used with their child at any point and reported an average of seven interventions (range 0–15) in addition to the behavior analytic program. Smith and Antolovich (2000) noted that, given the nature of the program they provided, participating parents were likely to be atypical in both their level of motivation to provide assistance and family income. Thomas et al. (2007) used a combined telephone and self-administered survey on a self-selected sample of families living in North Carolina who had a child with ASD under 9 years of age. Participants were obtained from both a subject registry and through direct recruitment in 2003–4. Information on diagnosis and presence of intellectual disability was provided via parental report and not verified. No specific information was provided about the developmental status of children. Overall, families were using a mean of seven services. The use of CAM interventions by families of children with ASD has been examined in several recent studies (Hanson et al., 2007; Levy, Mandell, Merhar, Ittenbach, & Pinto-Martin, 2003; Wong & Smith, 2006; Wong, 2009) in Canada, the United States and Hong Kong, using clearly described samples and diagnostic verification. While the details varied considerably across study (and geographical region), there was evidence that a substantial proportion of parents of children with ASD use at least one CAM intervention. Thus, there is an increasing amount of information on the types of educational and CAM interventions employed by parents of children with ASD. While studies of CAM intervention have typically used well defined and described samples, studies of educational interventions have been hampered by uncertain representativeness, low response rate for defined samples and a lack of verification of diagnoses and developmental level. In addition, few studies have provided extractable data on preschool aged children and there is no specific information on children in Australia. The present study examined the previous and current range of educational, therapy, medical and CAM interventions used by families of preschool aged children with ASD who were enrolled in a controlled trial of educational interventions.
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
1035
2. Methods The research was conducted as part of a larger randomized trial that compared two models of delivery of early intervention (home and center-based) and included a wait list control arm (Roberts et al., 2010). As part of the data collection for the controlled trial, information was obtained on the previous and current educational and therapy interventions, as well as medication and CAM interventions used by the families. 2.1. Participants 2.1.1. Recruitment Recruitment for the intervention arms was conducted in two intakes over two years (2006–2007) with target enrolment of 30 children in each arm of the trial. Families were registered with Autism Spectrum Australia (Aspect) and were awaiting early intervention services in the Sydney metropolitan area. Aspect is the largest provider of autism specific early intervention services in New South Wales. The total pool of potential participants for the intervention arms was 127 in 2006 and 141 in 2007. Criteria for inclusion included the child being of preschool age at the start of the program, a diagnosis of autistic disorder, Asperger’s disorder or PDD-NOS according to DSM IV (American Psychiatric Association, 2000) made by a referring clinician (medical practitioner and/or psychologist), and consent to be involved. Children whose parents did not agree to participate in the study were allocated to the service of their choice (center-based or home-based program) as per the usual procedure for Aspect. Following consent, children and their families were randomized to either home-based or center-based interventions. All families who chose to participate (and accepted randomization) were offered a place in the trial. In addition, families who could not be offered a place in a program during 2006 or 2007 were invited to participate in the wait list control group. These families were offered places in the program of their choice the following year. A total of 67 children were randomized to the treatment groups with 11 children withdrawing from the study, 10 of these prior to the commencement of intervention. Twenty-eight families agreed to participate in the wait-listed control group with no attrition. Thus, post assessments were completed for 27 participants in the home-based program, 29 in the center-based programs and 28 participants in the wait list control group, resulting in a total of 84 participants completing the study. Only participants who completed the trial were included in the present study. 2.1.2. Families Family background information was obtained through pre-test administration of the Beach Center Family Quality of Life Scale (Summers et al., 2005), which was returned by post. This was completed by 78 families. As informants providing information on interventions were almost always mothers, additional information was extracted for the 75 mothers who completed the Family Quality of Life Scale. Information about families is provided in Table 1. Most families reported an income of over $75,000 per year and the mean number of family members supported by this income was 4.0. In 2006, the mean total household income in Australia was approximately $81,000 (Australian Bureau of Statistics, 2007). Residential postcodes were examined using the 2006 Postal Area Index of Relative Socio-economic Advantage and Disadvantage (Australian Bureau of Statistics, 2008) and ranking within NSW was determined. The mean ranking indicated a higher than average socio-economic rank for the participating families. 2.1.3. Children At the commencement of the trial, the mean age of children was 3.5 years (range 2.2–5.0, SD = 0.61) and 90.5% were male. Children were assessed on the Autism Diagnostic Observation Schedule (Lord, Rutter, DiLavore, & Risi, 1999; Lord et al., Table 1 Demographic characteristics. N
Characteristic
78
Language spoken at home
78
Household income
73
Mothers’ education
Number (%) Language other than English spoken exclusively A language in addition to English More than $75,000 per year Between $60,000 and $75,000 Between $50,000 and $60,000 Between $40,00 and $50,000 Less than $40,000 High school College or post-high school training Bachelors degree Postgraduate education
2 12 45 10 11 4 8 10 28 23 12
(2.6%) (15.4%) (57.7%) (12.8%) (14.1%) (5.1%) (10.3%) (13.7%) (38.4%) (31.5%) (16.4%)
Mean (SD) 78 80 75
Family members supported by income SESa Mothers’ age
Number Ranking within NSW Years
4.0 (SD = 1.2) 73.0 (SD = 23.0) 36.6 (SD = 4.3)
a SES was determined according to the 2006 Postal Area Index of Relative Socio-economic Advantage and Disadvantage (Australian Bureau of Statistics, 2008).
1036
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
2000) and Griffiths Mental Developmental Scales-Extended Revised (Luiz et al., 2006) at the beginning of the research year. The mean Griffiths developmental quotient was 62.4 (SD = 15.5, n = 80). Of the 82 completed ADOS assessments, 59 children were classified with autistic disorder, 13 autism spectrum disorder and 10 tested as not being on the autism spectrum. The latter children were included in the study as the inclusion criteria for the trial was a diagnosis of autistic disorder, Asperger’s disorder or PDD-NOS according to DSM IV and the ADOS was intended as a supplementary measure. 2.2. Procedure Parents were initially interviewed either in person or by phone in the 8-week period before treatment group interventions were scheduled to commence. Parents were also contacted by phone in the middle of the year and again at the end of the year to determine if any interventions had been commenced since the original interview. A formal record was not kept of which parent or parents were interviewed but anecdotally, the interviewee was almost always the mother. Responses were recorded into data collection verbatim by the interviewer. The first set of questions addressed educational and therapy interventions. Parents were first asked to provide a list of intervention or therapy services that they had used previous to the current year (i.e., not currently used). Subsequently, participants were asked to provide a list of the interventions they were currently using and, in the case of the second and third interview, those that were started in the research year. In addition, for interventions that were being currently used and those that were started in the research year, parents were asked to indicate the frequency of the service. No restrictions were placed on the types of interventions parents could nominate. The second part of the interview addressed medication, dietary supplements and alternative therapies. Parents were asked to list medications that they were currently using (i.e., during the research year). They were then asked to indicate if they were currently using (1) a gluten-free diet, (2) a casein-free diet and (3) any other forms of dietary modification. Finally, parents were asked to list any other alternative therapies they were currently using. Again, no restrictions were placed on the types of interventions parents could nominate. 2.3. Coding Information supplied by parents was entered verbatim into a database and exported into a spreadsheet for analysis. Parents sometimes recorded medical, dietary and CAM interventions in response to questions about educational and therapy interventions, so both sections were examined in all data coding. A preliminary examination of (1) educational and therapy interventions and (2) medication, dietary and alternative therapies was conducted by two researchers to identify the types of services and interventions used and a coding scheme was developed. Previous and current educational and therapy interventions were classified as: applied behavior analysis (ABA), childcare, Floortime, generic early intervention program (those that were not autism specific), Giant Steps, Hanen, music therapy, occupational therapy, playgroup, preschool, Relationship Development Intervention (RDI), speech/language therapy, and swimming. Medical, supplements and CAM interventions were similarly classified as: medication unrelated to ASD (e.g., Ventolin), mood or behavior modifying medication, oils/fatty acids, vitamins, chelation therapy, other diet restriction (not gluten or casein), auditory/sound treatment, biomedical treatment, homeopathy, chiropractic, kinesiology, vaccine withdrawal, naturopathy and other. The number of parents who stated they used gluten-free diets and casein-free diets was tallied. Data were then coded to identify the extent of use of each intervention. If necessary, coders were permitted to conduct Internet searches via the Google search engine to assist in identifying or clarifying the nature of specific interventions (e.g., searching the name of an early intervention program to determine the nature of the service). A small number of educational interventions could not be classified from the information provided by parents or via an Internet search and so were not included in the analysis. Parent provided data on frequency of services was typically specific and unambiguous (e.g., weekly, fortnightly, 5 days per week). In a small number of instances, however, some conventions were necessary in coding these data. Where parents indicated that they were using two sources of the same intervention (e.g., seeing two speech pathologists) the combined frequency of service was used. Where parents indicated a service was delivered in a block (e.g., a block of 8 weekly sessions), the frequency of service delivery was averaged over the year. In occasional cases parents gave a number of hours per week a service was accessed (e.g., 20 h per week) and for coding purposes, it was assumed that one day equated to 5 h of access. Finally, in instances where parents indicated a range of frequency of service access (e.g., 2–4 times a week), the midpoint of this range was used for analysis. Frequency of access was coded as (1) 4 days a week, (2) 2 and <4 days per week, (3) 1 and <2 days per week, (4) 0.5 and <1 days per week, (5) <0.5 days per week and (6) information not provided. 2.4. Reliability Data were coded by the first author with an additional author independently coding the previous and current educational and therapy interventions. The medical and CAM interventions were similarly independently coded. Reliability was estimated by dividing agreements by agreements and disagreements on coded categories and multiplying by 100. Inter-rater reliability was 82.0% for previous educational and therapy interventions and 84.6% for current educational and therapy interventions. Reliability was 90.1% for medical, dietary and CAM interventions.
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
1037
Table 2 Number of families using previous and current educational and therapy interventions and access frequency for current interventions (N = 84). Intervention
Used previously
Used currently
Access frequency for current interventions (days per week)
ABA Childcare Floortime Generic early intervention program (not autism specific) Giant Steps Hanen Music therapy Occupational therapy Playgroup Preschool RDI Speech/language therapy Swimming
3 9 1 26
10 29 3 28
7 3
4 0 1 18 10 6 0 36 0
4 4 6 28 10 46 4 52 5
4
4
2 and <4 16 12
1 5 1
34 3
1 and <2 2 9 2 14
1 5 11 9 7 27 5
0.5 and <1
<0.5
NA 1 1 1
2
1 9 1
3
2 1 4
16
4
3 2
NA = not available.
3. Results Initially, overall patterns in the use of interventions will be examined. Subsequently, differences in interventions across developmental status will be considered. Finally, differences in interventions used by families across the three groups in the randomized control trial will be addressed. 3.1. Educational and therapy interventions Table 2 provides details of the number of families that had previously used each educational or therapeutic intervention as well as the number who used these services during the research year. In addition, the frequency of service access is provided for services that were used over the year of the research. With regard to previously used interventions, the mean number of interventions employed was 1.4 (range 0–4, SD = 1.3, Mdn = 1). The most commonly reported service was speech/language pathology with 43% of families indicating they had used this intervention in the past. Generic early intervention (31%) was the next most frequently used previous service, followed by occupational therapy (21%) with each of the remaining services being accessed by less than 15% of families. Parents used a mean of 2.6 (range 0–7, SD = 1.5, Mdn = 2) educational and therapy interventions in the year they were involved in the research (in addition to the home-based and center-based treatments in the trial). Speech/language therapy was the most frequently accessed intervention with 62% of families using this service. Preschool was the next most accessed service (55%) followed by generic early intervention (34%), childcare and occupational therapy (33% each). Both speech/ language therapy and occupational therapy were typically accessed on a weekly or fortnightly basis while children attending preschool and childcare typically did so for two or more days per week. Most families reporting they used ABA programs indicated that they accessed services for 4 or more days per week (20+ h) and all parents accessing Giant Steps reported the same. 3.2. Medical, dietary and CAM interventions Overall, 53 families (62%) used some form of medication, dietary or CAM intervention and detail is presented in Table 3. A total of 24 (29%) of parents reported that they were currently using a gluten and casein-free diet with a further 2 (2%) using a gluten-free diet alone and 1 (1%) using a casein-free diet alone. Vitamins were used by 32% of families, followed by oils/fatty acids (24%) and non-gluten or casein diet restrictions (e.g., sugar-free, preservative-free) (19%). Remaining interventions were each used by less than 10% of families. In both cases where chelation therapy was used, parents reported it was ‘‘natural’’ or ‘‘homeopathic’’. Gluten and casein-free diets were almost exclusively used in combination. Thus, for the purpose of calculating the mean number of interventions per child, they were counted as a single intervention when used in combination. A mean of 1.6 (range 0–13, SD = 2.2, Mdn = 1) interventions were used with each child. 3.3. Developmental status Relationships between the Griffith developmental quotient and the number of interventions used with each child were also examined. A Pearson correlation was calculated between Griffith developmental quotient and the total number of educational and therapy interventions revealing a non-significant relationship (r = 0.17, df = 80, t = 1.53, p = 0.13). A parallel analysis of medical, supplements and alternative interventions produced a small and non-significant positive correlation (r = 0.21, df = 78, t = 1.94, p = 0.06).
1038
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
Table 3 Reported number of children receiving medical, dietary and CAM interventions (N = 84). Intervention
n
Vitamins Gluten and casein-free diet Gluten-free diet alone Casein-free diet alone Oils/fatty acids Dietary restriction (not gluten or casein) Homeopathy Kinesiology Medication unrelated (e.g., Ventolin) Biomedical Rx (non-specific) Naturopathy Chiropractic Auditory/sound treatment Chelation Vaccination withdrawal Mood or behavior medication Other
27 24 2 1 20 16 6 6 5 5 5 5 3 2 1 0 6
3.4. Trial groups It was anticipated that the wait list group might attempt to access additional services so groups were compared in terms of the total number of services accessed, number of ASD specific interventions and number of medical, dietary or CAM interventions. The mean number of educational interventions, not including the intervention offered for the trial for the two treatment groups, was 3.11 (SD = 1.64) for children in the wait list group, 2.41 (SD = 1.50) for children in the center-based group and 2.37 (SD = 1.28) for children in the home-based group. A one-way ANOVA was conducted on the total number of interventions used across the 3 groups and this indicated that these differences did not reach significance (F[2,81] = 2.17, p = 0.12). The mean number of autism specific educational interventions (i.e., ABA, Hanen, Floortime, Giant Steps, RDI) was 0.54 (SD = 0.79) for children in the wait list group, 0.14 (SD = 0.35) for children in the center-based group and 0.22 (SD = 0.42) for children in the home-based group. A one-way ANOVA was conducted on the total number of autism specific interventions used across the 3 groups and this indicated that a significant difference was present (F[2,81] = 4.01, p = 0.02). Tukey post hoc comparisons indicated that the wait list group accessed significantly more autism specific services than the center-based group (p = 0.02). There were no significant differences between the wait list group and home-based group (p = 0.1) or between the home and center-based groups (p = 0.84). The level of medication, dietary or CAM intervention did not vary greatly between the groups. The mean number of interventions was 1.50 (SD = 2.74) for children with in the wait list group, 1.76 (SD = 2.25) for children in the center-based group and 1.59 (SD = 1.44) for children in the home-based group. A one-way ANOVA was conducted on the total number of interventions used across the 3 groups and this indicated no significant differences (F[2,81] = 0.1, p = 0.91). 4. Discussion The present study examined patterns of conventional and CAM intervention use with 84 children with ASD involved in a randomized control trial of early intervention. In interpreting this study, it should be noted that the mean age of children was approximately 3.5 years, with this research conducted relatively soon after diagnosis (see MacDermott, Williams, Ridley, Glasson, & Wray, 2006; Nassar et al., 2009; Williams et al., 2005). With regard to educational and therapy interventions, families had used an average of 1.4 services in the past and were currently accessing 2.6 services. For two-thirds of the children, this was in addition to the trial treatment. Direct comparison of the reported total numbers of interventions accessed in previous research is problematic as it is dependent on how interventions are grouped and classified. Speech and language therapy was the most widely accessed service with 43% of parents reporting they had previously used this service and 62% reporting current access. This was consistent with the high level of use of speech and language therapy in previous research. It is notable that the combined previous and current speech/language pathology services totaled more than 100%. This may reflect a misunderstanding of the question by some parents but two other explanations are possible. Parents typically listed specific service providers and sometimes had changed speech/language therapists. Thus, they listed the original therapist as a previous service provider and the present therapist as the current provider. In addition, probably as a result of service rationing to address long waiting lists, public speech/language therapists often provide services in short-term blocks, without a firm commitment to future service provision. In these instances it is possible that blocks of services may have been listed in both previous and current categories. Occupational therapy was also currently being used by approximately a third of families and had been previously used by 21%. The reported level of use of both of these therapies was broadly consistent with previous studies including preschool children with samples drawn either
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
1039
largely (Goin-Kochel et al., 2007) or entirely (Kohler, 1999; Smith & Antolovich, 2000; Thomas et al., 2007) from North America. With regard to frequency of service access, speech/language and occupational therapy were typically accessed on a weekly or fortnightly basis. Generic early intervention had been used by approximately a third of families and was currently being used by a similar proportion. Preschool (55%) and/or childcare (33%) was currently accessed by a substantial proportion of families. While preschool and childcare services are likely to provide an environment to allow the development of a range of skills and abilities, these services may not have available the necessary expertise and resources to address the needs of children with ASD. In this context, the low level of use of autism specific services, particularly more intensive options, is notable. For example, ABA programs were accessed by 12% currently and 4% previously in the present study. In contrast, data from primarily North American respondents provided by Goin-Kochel et al. (2007) indicated that 56% of children aged under 6 years had or were using ABA and this corresponds well with Green et al. (2006) who reported 36% current and 23% previous use across all ages. It is possible that parents involved in intensive autism specific interventions did not access the relatively low intensive programs offered by Aspect. The study of Smith and Antolovich (2000), however, indicates that even parents involved in a consultative ABA program accessed a wide variety of other services. It therefore seems more likely that the low level of use in this Australian sample may reflect the high cost of such programs, and the fact that at the time of this study, no government funding was available for such services. Autism interventions in Australia are not covered by private health insurance. Since the time of this study there has been a substantial increase in funding for ASD early intervention by the Federal Government under the Helping Children With Autism (HCWA) package (2008–2012). Nevertheless, this falls well short of funding the minimum 15–25 h of intervention per week that is typically recommended (see National Research Council, 2001; Roberts, 2004). CAM interventions were used at a relatively lower level than education and therapy interventions. Overall, a total of 62% of families in the current study used some form of CAM intervention over the research year. By comparison, Wong and Smith (2006) reported that 52% and Hanson et al. (2007) reported 75% of families had used a CAM intervention, but this was lifelong use. Levy et al. (2003) reported a lower 30% level of current use and these data would be more directly comparable with that collected in this study. CAM interventions were dominated by dietary restrictions and supplementation. Dietary restriction mainly consisted of gluten and/or casein restriction (32%), although 19% of families reported other dietary restrictions. Interestingly, the use of gluten and casein-free diets appeared to be higher in the current study than some previous research. For example, Wong and Smith (2006) reported that 12% of families were currently using casein-free diets and 16% were currently using gluten-free diets. Similarly, Levy et al. (2003) reported approximately 16% of families were currently using gluten and casein-free diets. These differences may reflect a change in the use of gluten and casein-free diets over time, local variations or variations due to study methods. Supplementation primarily took the form of vitamins (32%) and oils and fatty acids 24%. To date there is insufficient evidence to demonstrate effectiveness or efficacy of any of these dietary interventions (see Bent, Bertoglio, & Hendren, 2009; Millward, Ferriter, Calver, & Connell-Jones, 2008; Mulloy et al., 2010; Nye & Brice, 2005). Further, some interventions have associated problems and risks. For example, children with ASD often have highly idiosyncratic food preferences (Ledford & Gast, 2006) and there is potential for nutritional deficiencies (Herndon, DiGuiseppi, Johnson, Leiferman, & Reynolds, 2009). While some studies report broadly similar nutritional status for children on gluten and/or casein-free diets (Cornish, 2002; Herndon et al., 2009), others have reported additional nutritional risk (Arnold, Hyman, Mooney, & Kirby, 2003) or potential health problems that may be exacerbated by the diet, specifically reduced bone cortical thickness (Hediger et al., 2008). In addition, dietary restriction may place additional financial and other stress on families. According to the Raising Children Network (n.d. a) the cost of using gluten and casein-free diets fall in the range of $30–120 per week and parents will need to spend between 10 and 20 h per week buying and preparing food for the diet. Even if the cost and time involved fall at the bottom end of these ranges, they still represent a significant impost on families. The level of use of unproven and biologically implausible interventions, such as chiropractic, cranial osteopathy and homeopathy, was relatively low. Nevertheless, these interventions are of concern as they incur financial cost to families and involve investment of time, which could be better directed to interventions with a greater probability of benefiting the child. Interestingly, there was no significant relationship between developmental status and the number of interventions accessed. As many children in the present study were recently diagnosed, differences in patterns of service access may have had insufficient time to become established. Thus, it remains possible that differential service use may have developed over time. Consistent with the findings of Smith and Antolovich (2000), the present research suggested that parents used a range of plausible interventions, often in conjunction with unproven and implausible interventions. While several papers addressing CAM interventions (e.g., Hanson et al., 2007; Wong & Smith, 2006) have considered the issue of parental motivations for choosing these interventions, there remains very little data on sources of information and factors affecting decision-making with regard to educational and therapy interventions (one exception being Green, 2007). Existing researchers have provided some cross-sectional evidence of changes in patterns of service use over time (Goin-Kochel et al., 2007; Green et al., 2006). Longitudinal research may give better insight into these changes in service use and may better allow understanding of factors that affect parental decision-making. Recently, the Australian Government has sponsored the Raising Children Network Guide to Therapies (Raising Children Network, n.d. b), which provides summaries to parents on the research base for a range of interventions used with ASD. At this stage the impact of this source of information remains uncertain. It is also incongruous that an Australian Government
1040
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
website identifies some interventions that have limited or no evidence, yet the government does little to interact with those providing these treatments, which sometimes incur a government cost (i.e., Medicare billing or HCWA funding). In addition, biologically implausible interventions such as chiropractic may be supported by the private healthcare sector. In an environment where resources to support autism intervention are clearly limited, continued support of unproven and implausible interventions by both the government and private healthcare sector must be questioned. This study extends extant research in that it was the first of this nature conducted in Australia and one of a limited number of studies that provide data on preschool children who were relatively newly diagnosed at the time of data collection. In addition, all children were clinically diagnosed according to DSM IV criteria by a medical practitioner and/or psychologist and the sample characteristics were clearly described. 4.1. Limitations Several limitations of the current research need to be acknowledged. While this represents the first specific study of services accessed by Australian children with ASD, the sample was modest and the research was limited to one geographic area. In addition, willingness to participate in the RCT was a criterion for the study for the two treatment groups so there is sample bias. Demographic data suggested families lived in postcode areas with above average socio-economic status. In addition, data were collected on the frequency of access to educational and therapy services but it should be acknowledged that this does not necessarily reflect intensity for programs that are primarily parent administered. 5. Conclusion This research has provided preliminary insight into the interventions used by parents of children with ASD in an Australian sample. Parents used a range of validated, plausible and biologically implausible interventions. Many interventions employed by parents were not autism specific and many services were delivered at relatively low intensity. Future research needs to explore the factors that influence parents’ decisions regarding educational and therapy interventions, as well as other therapies, and how parents may be provided with information to facilitate decision-making. Acknowledgements We would like to gratefully acknowledge the assistance of Susan Dodd, Alison Parsons, Emma Pierce and Rebecca Sutherland in the conduct of this research. This research was funded by an Australian Research Council Linkage Projects grant (No. LP0562663) in conjunction with Autism Spectrum Australia (Aspect). References American Psychiatric Association (APA). (2000). DSM-IV: Diagnostic and statistical manual of mental disorders (Revised 4th ed.). Washington, DC: American Psychiatric Association. Arnold, G., Hyman, S., Mooney, R., & Kirby, R. (2003). Plasma amino acids profiles in children with autism: Potential risk of nutritional deficiencies. Journal of Autism and Developmental Disorders, 33, 449–454doi:10.1023/A:1025071014191. Australian Bureau of Statistics. (2007). General Social Survey: Summary Results, Australia, 2006. From February 10, 2010 http://www.abs.gov.au/AUSSTATS/ [email protected]/Latestproducts/4159.0Appendix42006?opendocument&tabname=Notes&prodno=4159.0&issue=2006&num=&view=. Australian Bureau of Statistics. (2008). Census of population and housing: Socio-economic indexes for areas (SEIFA), Australia – Data only, 2006. From January 28, 2010 http://www.abs.gov.au/AUSSTATS/[email protected]/Lookup/2033.0.55.001Main+Features12006?OpenDocument. Bent, S., Bertoglio, K., & Hendren, R. L. (2009). Omega-3 fatty acids for autistic spectrum disorder: A systematic review. Journal of Autism and Developmental Disorders, 39, 1145–1154doi:10.1007/s10803-009-0724-5. Cornish, E. (2002). Gluten and casein free diets in autism: A study of the effects on food choice and nutrition. Journal of Human Nutrition and Dietetics, 15, 261– 269doi:10.1046/j.1365-277X.2002.00372.x. Goin-Kochel, R. P., Myers, B. J., & Mackintosh, V. H. (2007). Parental reports on the use of treatments and therapies for children with autism spectrum disorders search in autism spectrum disorders. Research in Autism Spectrum Disorders, 1, 195–209doi:10.1016/j.rasd.2006.08.006. Green, V. A., Pituch, K. A., Itchon, J., Choi, A., O’Reilly, M., & Sigafoos, J. (2006). Internet survey of treatments used by parents of children with autism. Research in Developmental Disabilities, 27, 70–84doi:10.1016/j.ridd.2004.12.002. Green, V. A. (2007). Parental experience with treatments for autism. Journal of Developmental and Physical Disabilities, 19, 91–101doi:10.1007/s10882-007-9035-y. Hanson, E., Kalish, L. A., Bunce, E., Curtis, C., McDaniel, S., Ware, J., et al. (2007). Use of complementary and alternative medicine among children diagnosed with autism spectrum disorder. Journal of Autism and Developmental Disorders, 37, 628–636doi:10.1007/s10803-006-0192-0. Hediger, M. L., England, L. J., Molloy, C. A., Yu, K. F., Manning-Courtney, P., & Mills, J. L. (2008). Reduced bone cortical thickness in boys with autism or autism spectrum disorder. Journal of Autism and Developmental Disorders, 38, 848–856doi:10.1007/s10803-007-0453-6. Herndon, A. C., DiGuiseppi, C., Johnson, S. L., Leiferman, J., & Reynolds, A. (2009). Does nutritional intake differ between children with autism spectrum disorders and children with typical development? Journal of Autism and Developmental Disorders, 39, 212–222doi:10.1007/s10803-008-0606-2. Kohler, F. W. (1999). Examining the services received by young children with autism and their families: A survey of parent responses. Focus on Autism and Other Developmental Disabilities, 14, 150–158doi:10.1177/108835769901400304. Ledford, J. R., & Gast, D. L. (2006). Feeding problems in children with autism spectrum disorders: A review. Focus on Autism and Other Developmental Disabilities, 21, 153–166doi:10.1177/10883576060210030401. Levy, S. E., Mandell, D. S., Merhar, S., Ittenbach, R. F., & Pinto-Martin, J. A. (2003). Use of complementary and alternative medicine among children recently diagnosed with autistic spectrum disorder. Developmental and Behavioral Pediatrics, 26, 418–423doi:10.1097/00004703-200312000-00003. Lord, C., Risi, S., Lambrecht, L., Cook, E. H., Leventhal, B. L., DiLavore, P. C., et al. (2000). The Autism Diagnostic Observation Schedule—Generic: A standard measure of social and communication deficits associated with the spectrum of autism. Journal of Autism and Developmental Disorders, 30, 205–223doi:10.1023/ A:1005592401947. Lord, C., Rutter, M., DiLavore, P. C., & Risi, S. (1999). Autism diagnostic observation schedule. Los Angeles, CA: Western Psychological Services.
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
1041
Luiz, D., Faragher, B., Barnard, A., Knoesen, N., Kotras, N., Burns, L. E., et al. (2006). Griffiths Mental Development Scales – Extended Revised: 2 to 8 years. Oxford, UK: Hogrefe. MacDermott, S., Williams, K., Ridley, G., Glasson, E., & Wray, J. (2006). The prevalence of autism in Australia: Can it be established from existing data? Australian Advisory Board on Autism Spectrum Disorders Retreived from http://www.autismaus.com.au/index.php?page=research. Metz, B., Mulick, J. A., & Butter, E. M. (2005). Autism: A late-20th-century fad magnet. In J. W. Jacobson, R. M. Foxx, & J. A. Mulick (Eds.), Controversial therapies for developmental disabilities: Fad, fashion, and science in professional practice (pp. 237–263). Mahwah, NJ: Lawrence Erlbaum. Millward, C., Ferriter, M., Calver, S. J., & Connell-Jones, G. G. (2008). Gluten- and casein-free diets for autistic spectrum disorder. Cochrane Database of Systematic Reviews 2doi:10.1002/14651858.CD003498.pub3. Mulloy, A., Lang, R., O’Reilly, M., Sigafoos, J., Lancioni, G., & Rispoli, M. (2010). Gluten-free and casein-free diets in the treatment of autism spectrum disorders: A systematic review. Research in Autism Spectrum Disorders, 4, 328–339doi:10.1016/j.rasd.2009.10.008. Nassar, N., Dixon, G., Bourke, J., Bower, C., Glasson, E., de Klerk, N., et al. (2009). Autism spectrum disorders in young children: Effect of changes in diagnostic practices. International Journal of Epidemiology, 38, 1245–1254 10.1093/ije/dyp260. National Research Council (Ed.). (2001). Educating children with autism. Washington, DC: National Academy Press. Nye, C., & Brice, A. (2005). Combined vitamin B6-magnesium treatment in autism spectrum disorder. Cochrane Database of Systematic Reviews 4doi:10.1002/ 14651858.CD003497.pub2. Raising Children Network. (n.d. a). Elimination diet. Retrieved from http://raisingchildren.net.au/articles/diet_th.html. Raising Children Network. (n.d. b). Guide to therapies. Retrieved from http://raisingchildren.net.au/parents_guide_to_therapies/parents_guide_to_therapies. html. Roberts, J., Williams, K., Carter, M., Evans, D., Parmenter, T., & Silove, N., et al. (2010). A randomised controlled trial of two early intervention programs for young children with autism: Centre-based with parent program and home-based, in preparation. Roberts, J. M. (2004). A review of the research to identify the most effective models of best practice in the management of children with autism spectrum disorders. Sydney, Australia: Centre for Developmental Disability Studies. Smith, T., & Antolovich, M. (2000). Parental perceptions of supplemental interventions received by young children with autism in intensive behavior analytic treatment. Behavioral Interventions, 15, 83–97. Summers, J. A., Poston, D. J., Turnbull, A. P., Marquis, J., Hoffman, L., Mannan, H., et al. (2005). Conceptualizing and measuring family quality of life. Journal of Intellectual Disability Research, 49, 777–783doi:10.1111/j.1365-2788.2005.00751.x. Thomas, K. C., Morrissey, J. P., & McLaurin, C. (2007). Use of autism-related services by families and children. Journal of Autism and Developmental Disorders, 37, 818–829doi:10.1007/s10803-006-0208-9. Williams, K., Glasson, E. J., Wray, J., Tuck, M., Helmer, M., Bower, C. I., et al. (2005). Incidence of autism spectrum disorders in children in two Australian states. Medical Journal of Australia, 182, 108–111. Wong, H., & Smith, R. (2006). Patterns of complementary and alternative medical therapy use in children diagnosed with autism spectrum disorders. Journal of Autism and Developmental Disorders, 36, 901–909doi:10.1007/s10803-006-0131-0. Wong, V. C. (2009). Use of complementary and alternative medicine (CAM) in autism spectrum disorder (ASD): Comparison of Chinese and western culture (Part A). Journal of Autism and Developmental Disabilities, 39, 454–463doi:10.1007/s10803-008-0644-9.
Contents lists available at ScienceDirect
Research in Autism Spectrum Disorders Journal homepage: http://ees.elsevier.com/RASD/default.asp
Interventions used with an Australian sample of preschool children with autism spectrum disorders Mark Carter a,*, Jacqueline Roberts b, Katrina Williams c, David Evans d, Trevor Parmenter e, Natalie Silove f, Trevor Clark g, Anthony Warren g a
Macquarie University Special Education Centre, Macquarie University, NSW 2109, Australia Faculty of Education, University of Canberra, Australia Faculty of Medicine, University of New South Wales, Australia d Faculty of Education, University of Sydney, Australia e Sydney School of Medicine, University of Sydney, Australia f The Children’s Hospital at Westmead, Australia g Autism Spectrum Australia (Aspect), Australia b c
A R T I C L E I N F O
A B S T R A C T
Article history: Received 16 November 2010 Accepted 29 November 2010 Available online 30 December 2010
This study examined the previous and current range of educational, therapy, medical and CAM interventions used by a clearly described Australian sample of 84 families of preschool-aged children with autism spectrum disorders who were enrolled in a controlled trial of early intervention services. With regard to educational and therapy interventions, the most frequently used services were speech–language pathology, preschool and childcare, generic early intervention, and occupational therapy. With the exception of preschool and childcare, the access frequency for most of these services indicated they were used at relatively low intensity. Exclusion diets, oils/fatty acids and vitamin and mineral supplements were the primary CAM interventions used by families. There was no clear evidence of a relationship between the number of interventions used by families and developmental status although this may have been due to the relatively recent diagnoses. Implications of these findings and directions for future research are discussed. Crown Copyright ß 2010 Published by Elsevier Ltd. All rights reserved.
Keywords: Autism Parents Survey Treatment Education Complementary and alternative medicine
1. Introduction There has been substantial interest in autism spectrum disorders (ASDs) over recent years, probably associated with reports of increase in prevalence (Thomas, Morrissey, & McLaurin, 2007). The development of the Internet over the past decade and a half has provided parents with unprecedented access to largely unfiltered information on ASD and a wide array of treatments. These include conventional education, therapy, medical and complementary and alternative medicine (CAM) interventions. These treatments range from theoretically plausible interventions with supporting empirical evidence to implausible interventions that have been substantively disproved or may even be dangerous (Metz, Mulick, & Butter, 2005). Further, some interventions entail substantial financial and time costs to families. Consequently, there has been interest in the treatment options selected by families of children with ASD.
* Corresponding author. Tel.: +61 0 2 9850 7880; fax: +61 0 2 9850 8254. E-mail address: [email protected] (M. Carter). 1750-9467/$ – see front matter . Crown Copyright ß 2010 Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.rasd.2010.11.009
1034
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
Green et al. (2006) conducted an Internet survey of interventions used by parents of children with ASD. Information about the survey was distributed through autism associations and colleagues of the researchers. A total of 552 usable responses were obtained and 80% of these were from the USA. Approximately one-third of the children were of preschool age, a further third were 6–10 years, 18% were 11–14 years and 12% were 15 years or older. Parents reported they were currently using a mean of seven treatments compared with a mean of eight treatments in the past (i.e., those that were not currently used). Younger children used a greater number of interventions, as did those with more severe autistic symptomatology. Interventions were analyzed according to type/severity of disability and there were large and significant differences in several broad classes of intervention but no such analysis was conducted for age. A number of limitations of the Green et al. (2006) study should be noted. Given the methodology employed, both the response rate and representativeness of the sample remain unknown. The researchers noted that occupational and physical therapies were mistakenly left off the survey and they may have been under-reported. In addition, information regarding the diagnosis of ASD and the level of disability was necessarily based on parent report. Goin-Kochel, Myers, and Mackintosh (2007) extended the study of Green et al. (2006) with an Internet survey of drug, diet and behavioral/educational/alternative interventions that parents of children with ASD, including pervasive developmental disability-not otherwise specified (PDD-NOS), had tried or were currently using. A range of interventions was listed and respondents were given a limited option of adding treatments. The survey was advertised through autism support organizations. Responses were obtained worldwide although 77.5% of the 479 usable responses were from the USA. Again, given the methodology employed, both the response rate and representativeness of the sample remain unknown. Results were analyzed in terms of parent reported diagnosis as well as age. On average, children were currently receiving between four and six treatments and had received between seven and nine in the past. There were a number of distinctive and significant age-related patterns in treatment usage. Younger children tended to use more dietary and behavioral/educational/alternative interventions, while pharmacological intervention was most prominent for adolescents. These differences may have reflected both a changing pattern in parent preferences over time (e.g., exhausting educational treatments before considering medication) as well as cohort effects as some types of services were not available when adolescents were younger (Goin-Kochel et al., 2007). Nevertheless, the study does illustrate that patterns of service access may change very considerably over time. A number of earlier studies have focused on younger children. Kohler (1999) conducted telephone surveys of 25 families with children aged 3–9 years who were diagnosed with autism or pervasive developmental disabilities, although it was unclear how these diagnoses were obtained and confirmed. The children were serviced by four organizations in Pennsylvania and the response rate to invitation to participate in the study was 83%. Parents were asked to provide information on types and amounts of services they had received in the past 6 months. School or preschool placements were used most frequently (all children) while speech therapy (88%) and occupational therapy (56%) were also ranked highly. For preschool children, a mean of approximately six services were received and these children received a mean of 33 h of service per week but, presumably, much of this was associated with the preschool placements. Smith and Antolovich (2000) surveyed 290 families enrolled in a consultation-based intervention service based on the UCLA behavior analytic program. Families were asked about non-behavioral supplementary interventions they were receiving or had received in the past. Families self-referred to the program and children were under 5 years of age at the point of program commencement. The response rate was 42% and all children were reported as having a diagnosis of autism from an unaffiliated psychologist or physician although further detail of diagnostic protocols was not provided. Parents were provided with a list of therapies, which the researchers regarded as ‘‘unvalidated’’, and had the option of adding additional interventions. Parents were asked to identify the interventions they had used with their child at any point and reported an average of seven interventions (range 0–15) in addition to the behavior analytic program. Smith and Antolovich (2000) noted that, given the nature of the program they provided, participating parents were likely to be atypical in both their level of motivation to provide assistance and family income. Thomas et al. (2007) used a combined telephone and self-administered survey on a self-selected sample of families living in North Carolina who had a child with ASD under 9 years of age. Participants were obtained from both a subject registry and through direct recruitment in 2003–4. Information on diagnosis and presence of intellectual disability was provided via parental report and not verified. No specific information was provided about the developmental status of children. Overall, families were using a mean of seven services. The use of CAM interventions by families of children with ASD has been examined in several recent studies (Hanson et al., 2007; Levy, Mandell, Merhar, Ittenbach, & Pinto-Martin, 2003; Wong & Smith, 2006; Wong, 2009) in Canada, the United States and Hong Kong, using clearly described samples and diagnostic verification. While the details varied considerably across study (and geographical region), there was evidence that a substantial proportion of parents of children with ASD use at least one CAM intervention. Thus, there is an increasing amount of information on the types of educational and CAM interventions employed by parents of children with ASD. While studies of CAM intervention have typically used well defined and described samples, studies of educational interventions have been hampered by uncertain representativeness, low response rate for defined samples and a lack of verification of diagnoses and developmental level. In addition, few studies have provided extractable data on preschool aged children and there is no specific information on children in Australia. The present study examined the previous and current range of educational, therapy, medical and CAM interventions used by families of preschool aged children with ASD who were enrolled in a controlled trial of educational interventions.
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
1035
2. Methods The research was conducted as part of a larger randomized trial that compared two models of delivery of early intervention (home and center-based) and included a wait list control arm (Roberts et al., 2010). As part of the data collection for the controlled trial, information was obtained on the previous and current educational and therapy interventions, as well as medication and CAM interventions used by the families. 2.1. Participants 2.1.1. Recruitment Recruitment for the intervention arms was conducted in two intakes over two years (2006–2007) with target enrolment of 30 children in each arm of the trial. Families were registered with Autism Spectrum Australia (Aspect) and were awaiting early intervention services in the Sydney metropolitan area. Aspect is the largest provider of autism specific early intervention services in New South Wales. The total pool of potential participants for the intervention arms was 127 in 2006 and 141 in 2007. Criteria for inclusion included the child being of preschool age at the start of the program, a diagnosis of autistic disorder, Asperger’s disorder or PDD-NOS according to DSM IV (American Psychiatric Association, 2000) made by a referring clinician (medical practitioner and/or psychologist), and consent to be involved. Children whose parents did not agree to participate in the study were allocated to the service of their choice (center-based or home-based program) as per the usual procedure for Aspect. Following consent, children and their families were randomized to either home-based or center-based interventions. All families who chose to participate (and accepted randomization) were offered a place in the trial. In addition, families who could not be offered a place in a program during 2006 or 2007 were invited to participate in the wait list control group. These families were offered places in the program of their choice the following year. A total of 67 children were randomized to the treatment groups with 11 children withdrawing from the study, 10 of these prior to the commencement of intervention. Twenty-eight families agreed to participate in the wait-listed control group with no attrition. Thus, post assessments were completed for 27 participants in the home-based program, 29 in the center-based programs and 28 participants in the wait list control group, resulting in a total of 84 participants completing the study. Only participants who completed the trial were included in the present study. 2.1.2. Families Family background information was obtained through pre-test administration of the Beach Center Family Quality of Life Scale (Summers et al., 2005), which was returned by post. This was completed by 78 families. As informants providing information on interventions were almost always mothers, additional information was extracted for the 75 mothers who completed the Family Quality of Life Scale. Information about families is provided in Table 1. Most families reported an income of over $75,000 per year and the mean number of family members supported by this income was 4.0. In 2006, the mean total household income in Australia was approximately $81,000 (Australian Bureau of Statistics, 2007). Residential postcodes were examined using the 2006 Postal Area Index of Relative Socio-economic Advantage and Disadvantage (Australian Bureau of Statistics, 2008) and ranking within NSW was determined. The mean ranking indicated a higher than average socio-economic rank for the participating families. 2.1.3. Children At the commencement of the trial, the mean age of children was 3.5 years (range 2.2–5.0, SD = 0.61) and 90.5% were male. Children were assessed on the Autism Diagnostic Observation Schedule (Lord, Rutter, DiLavore, & Risi, 1999; Lord et al., Table 1 Demographic characteristics. N
Characteristic
78
Language spoken at home
78
Household income
73
Mothers’ education
Number (%) Language other than English spoken exclusively A language in addition to English More than $75,000 per year Between $60,000 and $75,000 Between $50,000 and $60,000 Between $40,00 and $50,000 Less than $40,000 High school College or post-high school training Bachelors degree Postgraduate education
2 12 45 10 11 4 8 10 28 23 12
(2.6%) (15.4%) (57.7%) (12.8%) (14.1%) (5.1%) (10.3%) (13.7%) (38.4%) (31.5%) (16.4%)
Mean (SD) 78 80 75
Family members supported by income SESa Mothers’ age
Number Ranking within NSW Years
4.0 (SD = 1.2) 73.0 (SD = 23.0) 36.6 (SD = 4.3)
a SES was determined according to the 2006 Postal Area Index of Relative Socio-economic Advantage and Disadvantage (Australian Bureau of Statistics, 2008).
1036
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
2000) and Griffiths Mental Developmental Scales-Extended Revised (Luiz et al., 2006) at the beginning of the research year. The mean Griffiths developmental quotient was 62.4 (SD = 15.5, n = 80). Of the 82 completed ADOS assessments, 59 children were classified with autistic disorder, 13 autism spectrum disorder and 10 tested as not being on the autism spectrum. The latter children were included in the study as the inclusion criteria for the trial was a diagnosis of autistic disorder, Asperger’s disorder or PDD-NOS according to DSM IV and the ADOS was intended as a supplementary measure. 2.2. Procedure Parents were initially interviewed either in person or by phone in the 8-week period before treatment group interventions were scheduled to commence. Parents were also contacted by phone in the middle of the year and again at the end of the year to determine if any interventions had been commenced since the original interview. A formal record was not kept of which parent or parents were interviewed but anecdotally, the interviewee was almost always the mother. Responses were recorded into data collection verbatim by the interviewer. The first set of questions addressed educational and therapy interventions. Parents were first asked to provide a list of intervention or therapy services that they had used previous to the current year (i.e., not currently used). Subsequently, participants were asked to provide a list of the interventions they were currently using and, in the case of the second and third interview, those that were started in the research year. In addition, for interventions that were being currently used and those that were started in the research year, parents were asked to indicate the frequency of the service. No restrictions were placed on the types of interventions parents could nominate. The second part of the interview addressed medication, dietary supplements and alternative therapies. Parents were asked to list medications that they were currently using (i.e., during the research year). They were then asked to indicate if they were currently using (1) a gluten-free diet, (2) a casein-free diet and (3) any other forms of dietary modification. Finally, parents were asked to list any other alternative therapies they were currently using. Again, no restrictions were placed on the types of interventions parents could nominate. 2.3. Coding Information supplied by parents was entered verbatim into a database and exported into a spreadsheet for analysis. Parents sometimes recorded medical, dietary and CAM interventions in response to questions about educational and therapy interventions, so both sections were examined in all data coding. A preliminary examination of (1) educational and therapy interventions and (2) medication, dietary and alternative therapies was conducted by two researchers to identify the types of services and interventions used and a coding scheme was developed. Previous and current educational and therapy interventions were classified as: applied behavior analysis (ABA), childcare, Floortime, generic early intervention program (those that were not autism specific), Giant Steps, Hanen, music therapy, occupational therapy, playgroup, preschool, Relationship Development Intervention (RDI), speech/language therapy, and swimming. Medical, supplements and CAM interventions were similarly classified as: medication unrelated to ASD (e.g., Ventolin), mood or behavior modifying medication, oils/fatty acids, vitamins, chelation therapy, other diet restriction (not gluten or casein), auditory/sound treatment, biomedical treatment, homeopathy, chiropractic, kinesiology, vaccine withdrawal, naturopathy and other. The number of parents who stated they used gluten-free diets and casein-free diets was tallied. Data were then coded to identify the extent of use of each intervention. If necessary, coders were permitted to conduct Internet searches via the Google search engine to assist in identifying or clarifying the nature of specific interventions (e.g., searching the name of an early intervention program to determine the nature of the service). A small number of educational interventions could not be classified from the information provided by parents or via an Internet search and so were not included in the analysis. Parent provided data on frequency of services was typically specific and unambiguous (e.g., weekly, fortnightly, 5 days per week). In a small number of instances, however, some conventions were necessary in coding these data. Where parents indicated that they were using two sources of the same intervention (e.g., seeing two speech pathologists) the combined frequency of service was used. Where parents indicated a service was delivered in a block (e.g., a block of 8 weekly sessions), the frequency of service delivery was averaged over the year. In occasional cases parents gave a number of hours per week a service was accessed (e.g., 20 h per week) and for coding purposes, it was assumed that one day equated to 5 h of access. Finally, in instances where parents indicated a range of frequency of service access (e.g., 2–4 times a week), the midpoint of this range was used for analysis. Frequency of access was coded as (1) 4 days a week, (2) 2 and <4 days per week, (3) 1 and <2 days per week, (4) 0.5 and <1 days per week, (5) <0.5 days per week and (6) information not provided. 2.4. Reliability Data were coded by the first author with an additional author independently coding the previous and current educational and therapy interventions. The medical and CAM interventions were similarly independently coded. Reliability was estimated by dividing agreements by agreements and disagreements on coded categories and multiplying by 100. Inter-rater reliability was 82.0% for previous educational and therapy interventions and 84.6% for current educational and therapy interventions. Reliability was 90.1% for medical, dietary and CAM interventions.
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
1037
Table 2 Number of families using previous and current educational and therapy interventions and access frequency for current interventions (N = 84). Intervention
Used previously
Used currently
Access frequency for current interventions (days per week)
ABA Childcare Floortime Generic early intervention program (not autism specific) Giant Steps Hanen Music therapy Occupational therapy Playgroup Preschool RDI Speech/language therapy Swimming
3 9 1 26
10 29 3 28
7 3
4 0 1 18 10 6 0 36 0
4 4 6 28 10 46 4 52 5
4
4
2 and <4 16 12
1 5 1
34 3
1 and <2 2 9 2 14
1 5 11 9 7 27 5
0.5 and <1
<0.5
NA 1 1 1
2
1 9 1
3
2 1 4
16
4
3 2
NA = not available.
3. Results Initially, overall patterns in the use of interventions will be examined. Subsequently, differences in interventions across developmental status will be considered. Finally, differences in interventions used by families across the three groups in the randomized control trial will be addressed. 3.1. Educational and therapy interventions Table 2 provides details of the number of families that had previously used each educational or therapeutic intervention as well as the number who used these services during the research year. In addition, the frequency of service access is provided for services that were used over the year of the research. With regard to previously used interventions, the mean number of interventions employed was 1.4 (range 0–4, SD = 1.3, Mdn = 1). The most commonly reported service was speech/language pathology with 43% of families indicating they had used this intervention in the past. Generic early intervention (31%) was the next most frequently used previous service, followed by occupational therapy (21%) with each of the remaining services being accessed by less than 15% of families. Parents used a mean of 2.6 (range 0–7, SD = 1.5, Mdn = 2) educational and therapy interventions in the year they were involved in the research (in addition to the home-based and center-based treatments in the trial). Speech/language therapy was the most frequently accessed intervention with 62% of families using this service. Preschool was the next most accessed service (55%) followed by generic early intervention (34%), childcare and occupational therapy (33% each). Both speech/ language therapy and occupational therapy were typically accessed on a weekly or fortnightly basis while children attending preschool and childcare typically did so for two or more days per week. Most families reporting they used ABA programs indicated that they accessed services for 4 or more days per week (20+ h) and all parents accessing Giant Steps reported the same. 3.2. Medical, dietary and CAM interventions Overall, 53 families (62%) used some form of medication, dietary or CAM intervention and detail is presented in Table 3. A total of 24 (29%) of parents reported that they were currently using a gluten and casein-free diet with a further 2 (2%) using a gluten-free diet alone and 1 (1%) using a casein-free diet alone. Vitamins were used by 32% of families, followed by oils/fatty acids (24%) and non-gluten or casein diet restrictions (e.g., sugar-free, preservative-free) (19%). Remaining interventions were each used by less than 10% of families. In both cases where chelation therapy was used, parents reported it was ‘‘natural’’ or ‘‘homeopathic’’. Gluten and casein-free diets were almost exclusively used in combination. Thus, for the purpose of calculating the mean number of interventions per child, they were counted as a single intervention when used in combination. A mean of 1.6 (range 0–13, SD = 2.2, Mdn = 1) interventions were used with each child. 3.3. Developmental status Relationships between the Griffith developmental quotient and the number of interventions used with each child were also examined. A Pearson correlation was calculated between Griffith developmental quotient and the total number of educational and therapy interventions revealing a non-significant relationship (r = 0.17, df = 80, t = 1.53, p = 0.13). A parallel analysis of medical, supplements and alternative interventions produced a small and non-significant positive correlation (r = 0.21, df = 78, t = 1.94, p = 0.06).
1038
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
Table 3 Reported number of children receiving medical, dietary and CAM interventions (N = 84). Intervention
n
Vitamins Gluten and casein-free diet Gluten-free diet alone Casein-free diet alone Oils/fatty acids Dietary restriction (not gluten or casein) Homeopathy Kinesiology Medication unrelated (e.g., Ventolin) Biomedical Rx (non-specific) Naturopathy Chiropractic Auditory/sound treatment Chelation Vaccination withdrawal Mood or behavior medication Other
27 24 2 1 20 16 6 6 5 5 5 5 3 2 1 0 6
3.4. Trial groups It was anticipated that the wait list group might attempt to access additional services so groups were compared in terms of the total number of services accessed, number of ASD specific interventions and number of medical, dietary or CAM interventions. The mean number of educational interventions, not including the intervention offered for the trial for the two treatment groups, was 3.11 (SD = 1.64) for children in the wait list group, 2.41 (SD = 1.50) for children in the center-based group and 2.37 (SD = 1.28) for children in the home-based group. A one-way ANOVA was conducted on the total number of interventions used across the 3 groups and this indicated that these differences did not reach significance (F[2,81] = 2.17, p = 0.12). The mean number of autism specific educational interventions (i.e., ABA, Hanen, Floortime, Giant Steps, RDI) was 0.54 (SD = 0.79) for children in the wait list group, 0.14 (SD = 0.35) for children in the center-based group and 0.22 (SD = 0.42) for children in the home-based group. A one-way ANOVA was conducted on the total number of autism specific interventions used across the 3 groups and this indicated that a significant difference was present (F[2,81] = 4.01, p = 0.02). Tukey post hoc comparisons indicated that the wait list group accessed significantly more autism specific services than the center-based group (p = 0.02). There were no significant differences between the wait list group and home-based group (p = 0.1) or between the home and center-based groups (p = 0.84). The level of medication, dietary or CAM intervention did not vary greatly between the groups. The mean number of interventions was 1.50 (SD = 2.74) for children with in the wait list group, 1.76 (SD = 2.25) for children in the center-based group and 1.59 (SD = 1.44) for children in the home-based group. A one-way ANOVA was conducted on the total number of interventions used across the 3 groups and this indicated no significant differences (F[2,81] = 0.1, p = 0.91). 4. Discussion The present study examined patterns of conventional and CAM intervention use with 84 children with ASD involved in a randomized control trial of early intervention. In interpreting this study, it should be noted that the mean age of children was approximately 3.5 years, with this research conducted relatively soon after diagnosis (see MacDermott, Williams, Ridley, Glasson, & Wray, 2006; Nassar et al., 2009; Williams et al., 2005). With regard to educational and therapy interventions, families had used an average of 1.4 services in the past and were currently accessing 2.6 services. For two-thirds of the children, this was in addition to the trial treatment. Direct comparison of the reported total numbers of interventions accessed in previous research is problematic as it is dependent on how interventions are grouped and classified. Speech and language therapy was the most widely accessed service with 43% of parents reporting they had previously used this service and 62% reporting current access. This was consistent with the high level of use of speech and language therapy in previous research. It is notable that the combined previous and current speech/language pathology services totaled more than 100%. This may reflect a misunderstanding of the question by some parents but two other explanations are possible. Parents typically listed specific service providers and sometimes had changed speech/language therapists. Thus, they listed the original therapist as a previous service provider and the present therapist as the current provider. In addition, probably as a result of service rationing to address long waiting lists, public speech/language therapists often provide services in short-term blocks, without a firm commitment to future service provision. In these instances it is possible that blocks of services may have been listed in both previous and current categories. Occupational therapy was also currently being used by approximately a third of families and had been previously used by 21%. The reported level of use of both of these therapies was broadly consistent with previous studies including preschool children with samples drawn either
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
1039
largely (Goin-Kochel et al., 2007) or entirely (Kohler, 1999; Smith & Antolovich, 2000; Thomas et al., 2007) from North America. With regard to frequency of service access, speech/language and occupational therapy were typically accessed on a weekly or fortnightly basis. Generic early intervention had been used by approximately a third of families and was currently being used by a similar proportion. Preschool (55%) and/or childcare (33%) was currently accessed by a substantial proportion of families. While preschool and childcare services are likely to provide an environment to allow the development of a range of skills and abilities, these services may not have available the necessary expertise and resources to address the needs of children with ASD. In this context, the low level of use of autism specific services, particularly more intensive options, is notable. For example, ABA programs were accessed by 12% currently and 4% previously in the present study. In contrast, data from primarily North American respondents provided by Goin-Kochel et al. (2007) indicated that 56% of children aged under 6 years had or were using ABA and this corresponds well with Green et al. (2006) who reported 36% current and 23% previous use across all ages. It is possible that parents involved in intensive autism specific interventions did not access the relatively low intensive programs offered by Aspect. The study of Smith and Antolovich (2000), however, indicates that even parents involved in a consultative ABA program accessed a wide variety of other services. It therefore seems more likely that the low level of use in this Australian sample may reflect the high cost of such programs, and the fact that at the time of this study, no government funding was available for such services. Autism interventions in Australia are not covered by private health insurance. Since the time of this study there has been a substantial increase in funding for ASD early intervention by the Federal Government under the Helping Children With Autism (HCWA) package (2008–2012). Nevertheless, this falls well short of funding the minimum 15–25 h of intervention per week that is typically recommended (see National Research Council, 2001; Roberts, 2004). CAM interventions were used at a relatively lower level than education and therapy interventions. Overall, a total of 62% of families in the current study used some form of CAM intervention over the research year. By comparison, Wong and Smith (2006) reported that 52% and Hanson et al. (2007) reported 75% of families had used a CAM intervention, but this was lifelong use. Levy et al. (2003) reported a lower 30% level of current use and these data would be more directly comparable with that collected in this study. CAM interventions were dominated by dietary restrictions and supplementation. Dietary restriction mainly consisted of gluten and/or casein restriction (32%), although 19% of families reported other dietary restrictions. Interestingly, the use of gluten and casein-free diets appeared to be higher in the current study than some previous research. For example, Wong and Smith (2006) reported that 12% of families were currently using casein-free diets and 16% were currently using gluten-free diets. Similarly, Levy et al. (2003) reported approximately 16% of families were currently using gluten and casein-free diets. These differences may reflect a change in the use of gluten and casein-free diets over time, local variations or variations due to study methods. Supplementation primarily took the form of vitamins (32%) and oils and fatty acids 24%. To date there is insufficient evidence to demonstrate effectiveness or efficacy of any of these dietary interventions (see Bent, Bertoglio, & Hendren, 2009; Millward, Ferriter, Calver, & Connell-Jones, 2008; Mulloy et al., 2010; Nye & Brice, 2005). Further, some interventions have associated problems and risks. For example, children with ASD often have highly idiosyncratic food preferences (Ledford & Gast, 2006) and there is potential for nutritional deficiencies (Herndon, DiGuiseppi, Johnson, Leiferman, & Reynolds, 2009). While some studies report broadly similar nutritional status for children on gluten and/or casein-free diets (Cornish, 2002; Herndon et al., 2009), others have reported additional nutritional risk (Arnold, Hyman, Mooney, & Kirby, 2003) or potential health problems that may be exacerbated by the diet, specifically reduced bone cortical thickness (Hediger et al., 2008). In addition, dietary restriction may place additional financial and other stress on families. According to the Raising Children Network (n.d. a) the cost of using gluten and casein-free diets fall in the range of $30–120 per week and parents will need to spend between 10 and 20 h per week buying and preparing food for the diet. Even if the cost and time involved fall at the bottom end of these ranges, they still represent a significant impost on families. The level of use of unproven and biologically implausible interventions, such as chiropractic, cranial osteopathy and homeopathy, was relatively low. Nevertheless, these interventions are of concern as they incur financial cost to families and involve investment of time, which could be better directed to interventions with a greater probability of benefiting the child. Interestingly, there was no significant relationship between developmental status and the number of interventions accessed. As many children in the present study were recently diagnosed, differences in patterns of service access may have had insufficient time to become established. Thus, it remains possible that differential service use may have developed over time. Consistent with the findings of Smith and Antolovich (2000), the present research suggested that parents used a range of plausible interventions, often in conjunction with unproven and implausible interventions. While several papers addressing CAM interventions (e.g., Hanson et al., 2007; Wong & Smith, 2006) have considered the issue of parental motivations for choosing these interventions, there remains very little data on sources of information and factors affecting decision-making with regard to educational and therapy interventions (one exception being Green, 2007). Existing researchers have provided some cross-sectional evidence of changes in patterns of service use over time (Goin-Kochel et al., 2007; Green et al., 2006). Longitudinal research may give better insight into these changes in service use and may better allow understanding of factors that affect parental decision-making. Recently, the Australian Government has sponsored the Raising Children Network Guide to Therapies (Raising Children Network, n.d. b), which provides summaries to parents on the research base for a range of interventions used with ASD. At this stage the impact of this source of information remains uncertain. It is also incongruous that an Australian Government
1040
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
website identifies some interventions that have limited or no evidence, yet the government does little to interact with those providing these treatments, which sometimes incur a government cost (i.e., Medicare billing or HCWA funding). In addition, biologically implausible interventions such as chiropractic may be supported by the private healthcare sector. In an environment where resources to support autism intervention are clearly limited, continued support of unproven and implausible interventions by both the government and private healthcare sector must be questioned. This study extends extant research in that it was the first of this nature conducted in Australia and one of a limited number of studies that provide data on preschool children who were relatively newly diagnosed at the time of data collection. In addition, all children were clinically diagnosed according to DSM IV criteria by a medical practitioner and/or psychologist and the sample characteristics were clearly described. 4.1. Limitations Several limitations of the current research need to be acknowledged. While this represents the first specific study of services accessed by Australian children with ASD, the sample was modest and the research was limited to one geographic area. In addition, willingness to participate in the RCT was a criterion for the study for the two treatment groups so there is sample bias. Demographic data suggested families lived in postcode areas with above average socio-economic status. In addition, data were collected on the frequency of access to educational and therapy services but it should be acknowledged that this does not necessarily reflect intensity for programs that are primarily parent administered. 5. Conclusion This research has provided preliminary insight into the interventions used by parents of children with ASD in an Australian sample. Parents used a range of validated, plausible and biologically implausible interventions. Many interventions employed by parents were not autism specific and many services were delivered at relatively low intensity. Future research needs to explore the factors that influence parents’ decisions regarding educational and therapy interventions, as well as other therapies, and how parents may be provided with information to facilitate decision-making. Acknowledgements We would like to gratefully acknowledge the assistance of Susan Dodd, Alison Parsons, Emma Pierce and Rebecca Sutherland in the conduct of this research. This research was funded by an Australian Research Council Linkage Projects grant (No. LP0562663) in conjunction with Autism Spectrum Australia (Aspect). References American Psychiatric Association (APA). (2000). DSM-IV: Diagnostic and statistical manual of mental disorders (Revised 4th ed.). Washington, DC: American Psychiatric Association. Arnold, G., Hyman, S., Mooney, R., & Kirby, R. (2003). Plasma amino acids profiles in children with autism: Potential risk of nutritional deficiencies. Journal of Autism and Developmental Disorders, 33, 449–454doi:10.1023/A:1025071014191. Australian Bureau of Statistics. (2007). General Social Survey: Summary Results, Australia, 2006. From February 10, 2010 http://www.abs.gov.au/AUSSTATS/ [email protected]/Latestproducts/4159.0Appendix42006?opendocument&tabname=Notes&prodno=4159.0&issue=2006&num=&view=. Australian Bureau of Statistics. (2008). Census of population and housing: Socio-economic indexes for areas (SEIFA), Australia – Data only, 2006. From January 28, 2010 http://www.abs.gov.au/AUSSTATS/[email protected]/Lookup/2033.0.55.001Main+Features12006?OpenDocument. Bent, S., Bertoglio, K., & Hendren, R. L. (2009). Omega-3 fatty acids for autistic spectrum disorder: A systematic review. Journal of Autism and Developmental Disorders, 39, 1145–1154doi:10.1007/s10803-009-0724-5. Cornish, E. (2002). Gluten and casein free diets in autism: A study of the effects on food choice and nutrition. Journal of Human Nutrition and Dietetics, 15, 261– 269doi:10.1046/j.1365-277X.2002.00372.x. Goin-Kochel, R. P., Myers, B. J., & Mackintosh, V. H. (2007). Parental reports on the use of treatments and therapies for children with autism spectrum disorders search in autism spectrum disorders. Research in Autism Spectrum Disorders, 1, 195–209doi:10.1016/j.rasd.2006.08.006. Green, V. A., Pituch, K. A., Itchon, J., Choi, A., O’Reilly, M., & Sigafoos, J. (2006). Internet survey of treatments used by parents of children with autism. Research in Developmental Disabilities, 27, 70–84doi:10.1016/j.ridd.2004.12.002. Green, V. A. (2007). Parental experience with treatments for autism. Journal of Developmental and Physical Disabilities, 19, 91–101doi:10.1007/s10882-007-9035-y. Hanson, E., Kalish, L. A., Bunce, E., Curtis, C., McDaniel, S., Ware, J., et al. (2007). Use of complementary and alternative medicine among children diagnosed with autism spectrum disorder. Journal of Autism and Developmental Disorders, 37, 628–636doi:10.1007/s10803-006-0192-0. Hediger, M. L., England, L. J., Molloy, C. A., Yu, K. F., Manning-Courtney, P., & Mills, J. L. (2008). Reduced bone cortical thickness in boys with autism or autism spectrum disorder. Journal of Autism and Developmental Disorders, 38, 848–856doi:10.1007/s10803-007-0453-6. Herndon, A. C., DiGuiseppi, C., Johnson, S. L., Leiferman, J., & Reynolds, A. (2009). Does nutritional intake differ between children with autism spectrum disorders and children with typical development? Journal of Autism and Developmental Disorders, 39, 212–222doi:10.1007/s10803-008-0606-2. Kohler, F. W. (1999). Examining the services received by young children with autism and their families: A survey of parent responses. Focus on Autism and Other Developmental Disabilities, 14, 150–158doi:10.1177/108835769901400304. Ledford, J. R., & Gast, D. L. (2006). Feeding problems in children with autism spectrum disorders: A review. Focus on Autism and Other Developmental Disabilities, 21, 153–166doi:10.1177/10883576060210030401. Levy, S. E., Mandell, D. S., Merhar, S., Ittenbach, R. F., & Pinto-Martin, J. A. (2003). Use of complementary and alternative medicine among children recently diagnosed with autistic spectrum disorder. Developmental and Behavioral Pediatrics, 26, 418–423doi:10.1097/00004703-200312000-00003. Lord, C., Risi, S., Lambrecht, L., Cook, E. H., Leventhal, B. L., DiLavore, P. C., et al. (2000). The Autism Diagnostic Observation Schedule—Generic: A standard measure of social and communication deficits associated with the spectrum of autism. Journal of Autism and Developmental Disorders, 30, 205–223doi:10.1023/ A:1005592401947. Lord, C., Rutter, M., DiLavore, P. C., & Risi, S. (1999). Autism diagnostic observation schedule. Los Angeles, CA: Western Psychological Services.
M. Carter et al. / Research in Autism Spectrum Disorders 5 (2011) 1033–1041
1041
Luiz, D., Faragher, B., Barnard, A., Knoesen, N., Kotras, N., Burns, L. E., et al. (2006). Griffiths Mental Development Scales – Extended Revised: 2 to 8 years. Oxford, UK: Hogrefe. MacDermott, S., Williams, K., Ridley, G., Glasson, E., & Wray, J. (2006). The prevalence of autism in Australia: Can it be established from existing data? Australian Advisory Board on Autism Spectrum Disorders Retreived from http://www.autismaus.com.au/index.php?page=research. Metz, B., Mulick, J. A., & Butter, E. M. (2005). Autism: A late-20th-century fad magnet. In J. W. Jacobson, R. M. Foxx, & J. A. Mulick (Eds.), Controversial therapies for developmental disabilities: Fad, fashion, and science in professional practice (pp. 237–263). Mahwah, NJ: Lawrence Erlbaum. Millward, C., Ferriter, M., Calver, S. J., & Connell-Jones, G. G. (2008). Gluten- and casein-free diets for autistic spectrum disorder. Cochrane Database of Systematic Reviews 2doi:10.1002/14651858.CD003498.pub3. Mulloy, A., Lang, R., O’Reilly, M., Sigafoos, J., Lancioni, G., & Rispoli, M. (2010). Gluten-free and casein-free diets in the treatment of autism spectrum disorders: A systematic review. Research in Autism Spectrum Disorders, 4, 328–339doi:10.1016/j.rasd.2009.10.008. Nassar, N., Dixon, G., Bourke, J., Bower, C., Glasson, E., de Klerk, N., et al. (2009). Autism spectrum disorders in young children: Effect of changes in diagnostic practices. International Journal of Epidemiology, 38, 1245–1254 10.1093/ije/dyp260. National Research Council (Ed.). (2001). Educating children with autism. Washington, DC: National Academy Press. Nye, C., & Brice, A. (2005). Combined vitamin B6-magnesium treatment in autism spectrum disorder. Cochrane Database of Systematic Reviews 4doi:10.1002/ 14651858.CD003497.pub2. Raising Children Network. (n.d. a). Elimination diet. Retrieved from http://raisingchildren.net.au/articles/diet_th.html. Raising Children Network. (n.d. b). Guide to therapies. Retrieved from http://raisingchildren.net.au/parents_guide_to_therapies/parents_guide_to_therapies. html. Roberts, J., Williams, K., Carter, M., Evans, D., Parmenter, T., & Silove, N., et al. (2010). A randomised controlled trial of two early intervention programs for young children with autism: Centre-based with parent program and home-based, in preparation. Roberts, J. M. (2004). A review of the research to identify the most effective models of best practice in the management of children with autism spectrum disorders. Sydney, Australia: Centre for Developmental Disability Studies. Smith, T., & Antolovich, M. (2000). Parental perceptions of supplemental interventions received by young children with autism in intensive behavior analytic treatment. Behavioral Interventions, 15, 83–97. Summers, J. A., Poston, D. J., Turnbull, A. P., Marquis, J., Hoffman, L., Mannan, H., et al. (2005). Conceptualizing and measuring family quality of life. Journal of Intellectual Disability Research, 49, 777–783doi:10.1111/j.1365-2788.2005.00751.x. Thomas, K. C., Morrissey, J. P., & McLaurin, C. (2007). Use of autism-related services by families and children. Journal of Autism and Developmental Disorders, 37, 818–829doi:10.1007/s10803-006-0208-9. Williams, K., Glasson, E. J., Wray, J., Tuck, M., Helmer, M., Bower, C. I., et al. (2005). Incidence of autism spectrum disorders in children in two Australian states. Medical Journal of Australia, 182, 108–111. Wong, H., & Smith, R. (2006). Patterns of complementary and alternative medical therapy use in children diagnosed with autism spectrum disorders. Journal of Autism and Developmental Disorders, 36, 901–909doi:10.1007/s10803-006-0131-0. Wong, V. C. (2009). Use of complementary and alternative medicine (CAM) in autism spectrum disorder (ASD): Comparison of Chinese and western culture (Part A). Journal of Autism and Developmental Disabilities, 39, 454–463doi:10.1007/s10803-008-0644-9.