Comparison of Two Tools to Assess Sensory Features in Children With Autism Spectrum Disorder

Abstract

OBJECTIVE. This article documents the convergent validity of the Sensory Profile (SP) and the Sensory Processing Measure (SPM)–Home Form for children with autism spectrum disorder (ASD).

METHOD. Parents of 34 children with ASD between ages 5 and 8 yr filled out both measures. Through correlations, χ² tests, and levels of agreement between classifications, the results for the SP and the SPM–Home Form were compared.

RESULTS. The raw scores were correlated for some sensory domains (hearing, vision, touch, and proprioception) and for social functioning. The classifications showed a significant level of agreement for most scales (κs = .247–.589, p ≤ .05) and for the total scores (κ = .324, p ≤ .01).

CONCLUSION. This study provides further evidence of convergent validity between both tools. The SPM–Home Form identifies more children with ASD who present with sensory features for every domain measured by both tools.

Autism spectrum disorder (ASD) affects roughly 1% of children (Frieden, Jaffe, Cono, Richards, & Iademarco, 2014). The disorder is characterized by difficulties in communication and social interaction, along with behavioral rigidity and repetitiveness (American Psychiatric Association, 2013). According to several authors, these characteristics can be partly explained by the sensory features found in 69%–95% of children with ASD (Baranek, David, Poe, Stone, & Watson, 2006; Glod, Riby, Honey, & Rodgers, 2015; Hazen, Stornelli, O’Rourke, Koesterer, & McDougle, 2014; Schaaf & Lane, 2015; Tomchek & Dunn, 2007). The high prevalence of these sensory features has led to their inclusion in the ASD diagnostic criteria in the most recent edition of the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; American Psychiatric Association, 2013).

In a recent review of the literature, Schaaf and Lane (2015) described sensory reactivity and unusual sensory interest as sensory features in children with ASD. Previous studies have found that children with ASD can present a significant amount of variability in the sensory domains involved in those types of sensory features (Baranek et al., 2006; Schaaf & Lane, 2015). Nonetheless, some of the most frequently cited features include atypical hearing reactivity, tactile hyperreactivity, gustatory and olfactory hyperreactivity, and a weakness of endurance and tonicity that could indicate atypical proprioceptive reactivity. Evidence has also suggested that hyporeactivity, or sensory seeking, may characterize a generalized profile of children with ASD (Baranek et al., 2006; Ben-Sasson et al., 2009; Lane, Molloy, & Bishop, 2014; Schaaf & Lane, 2015; Schoen, Miller, Brett-Green, & Nielsen, 2009; Tomchek & Dunn, 2007). Together, these sensory features may be responsible for characteristic ASD behavior, including mouthing, staring, self-stimulating, and low propensity to respond when one’s name is called (Hazen et al., 2014; Kirby, Little, & Baranek, 2015; Miller-Kuhaneck, 2015).

Sensory features of children with ASD may also hinder their emotional regulation and willingness to perform tasks (Samson et al., 2014; Tomchek & Case-Smith, 2009). As a result, these features may increase the children’s difficulty with social interaction (Watson et al., 2011). The impact may also extend to families, who are required to organize day-to-day routines in response to the children’s sensory needs (Marquenie, Rodger, Mangohig, & Cronin, 2011).

The important repercussions of these sensory features are a key area of interest in occupational therapy (Henry & Miller-Kuhaneck, 2009; Tomchek & Case-Smith, 2009). Occupational therapy practitioners use various methods to assess sensory features, including interviews with parents, behavioral observations of children, and questionnaires filled out by significant adults in the children’s lives (Schaaf & Lane, 2015; Tomchek & Case-Smith, 2009; Watling, Koenig, Davies, & Schaaf, 2011).

The Sensory Profile (SP; Dunn, 1999) and the Short Sensory Profile (SSP; McIntosh, Miller, Shyu, & Dunn, 1999) are among the clinical and research tools most often used by occupational therapy practitioners (Ashburner, Rodger, Ziviani, & Jones, 2014; Glod et al., 2015; Tomchek & Case-Smith, 2009). Using Dunn’s (1999) model of sensory processing, these questionnaires are intended to identify the sensory processing patterns associated with children’s functional performance. The SSP was developed from the SP by retaining and refining a pool of items that assess sensory features. Items measuring social and emotional abilities and fine motor development were removed because they are related to but not products of sensory features (McIntosh et al., 1999). Both instruments collect information that describes the children’s behavioral tendencies when responding to various sensory stimuli (Dunn, 1999). Unlike the SP, a total score can be calculated for the SSP (McIntosh et al., 1999).

Another useful tool is the Sensory Processing Measure (SPM), based on Ayres’ sensory integration theory and also standardized for children (Parham, Ecker, Miller-Kuhaneck, Henry, & Glennon, 2007; Tomchek & Case-Smith, 2009). This assessment tool is intended to document behavior associated with day-to-day sensory features.

Three studies have addressed the convergent validity between the SPM–Home Form and either the SP or the SSP with various populations of school-age children (Brown, Morrison, & Stagnitti, 2010a; Hansen & Jirikowic, 2013; Parham & Ecker, 2007). The first study was conducted during the validation process for the SPM–Home Form, before its publication, using 182 children with various diagnoses who were receiving occupational therapy (Parham & Ecker, 2007). Parham and Ecker (2007) documented the correlations between the SPM–Home Form scales and each of the SP and SSP scales. The results supported the convergent validity of the total scores between the SPM–Home Form and the SSP (r = .72, p ≤ .005). Among all sensory domains compared between the SPM–Home Form and the SP, the hearing, vision, vestibular, and tactile domains showed the strongest correlations (rs = .48–.56, p ≤ .005; Parham & Ecker, 2007). In the second study, the targeted population was typically developing children (N = 30; Brown et al., 2010a). Brown et al. (2010a) created an SP total score by adding the results obtained from every scale to compare them with the SPM–Home Form total score. The results revealed a correlation of .86 (p < .01) between the two scores. Finally, Hansen and Jirikowic (2013) studied the correlation between the SSP and SPM–Home Form total scores for children with fetal alcohol spectrum disorder (N = 11). In this study, the tools were highly correlated (r = –.93, p < .001). In addition, this study found a 90.9% level of agreement regarding the presence or the absence of sensory features. The authors did, however, report a 36.6% level of agreement when the sensory features were classified within each tool’s three categories of performance. The results of these studies suggest that both the SP, or its shorter version, the SSP, and the SPM–Home Form assess similar constructs.

However, no study has been conducted to determine the convergent validity between the SP or the SSP and the SPM–Home Form specifically with children with ASD. Given the high prevalence of sensory features in children with ASD and their considerable impact on the day-to-day lives of families, assessing these features with this population is essential. Occupational therapists must choose the most relevant tool available for the population with ASD. The objective of this study was to compare the SSP total score and SP subscales scores with scores on the SPM–Home Form for a cohort of children with ASD to determine the extent to which both tools identify the same sensory features.

Method

Three interrelated studies formed the basis of the current study. First, in 2007–2008, parents of children at the autism clinic at the Montreal Children’s Hospital were invited to participate in a major pan-Canadian longitudinal study, “Pathways for Better Outcomes” (funded by the Canadian Institute of Health Research). If they accepted, participation in an ancillary study conducted only in Montreal was proposed to document sensory–motor difficulties and their effect on daily functioning. Finally, a Fonds de Recherche du Québec–Culture et Société grant was obtained to do a 2-yr follow-up on the children from the sensory–motor study in 2010. The current study involves a secondary analysis of the untreated data collected at Time 2 of the sensory–motor study.

Participants

To be included in the longitudinal study, the children had to meet the diagnostic criteria associated with autism, Asperger’s syndrome, or pervasive developmental disorder–not otherwise specified, according to the Diagnostic and Statistical Manual (4th ed., text rev.; American Psychiatric Association, 2000) in effect at the time of the data collection. The diagnosis was made by a child psychiatrist on the basis of results obtained with the Autism Diagnostic Interview (Le Couteur, Lord, & Rutter, 2003) and the Autism Diagnostic Observation Schedule–Generic (Lord, Rutter, DiLavore, & Risi, 1999). Clinicians and research assistants with extensive experience had previously administered these tools; interrater reliability was estimated at .90. The remaining inclusion criteria were a mental age of ≥18 mo and parental ability to read and complete questionnaires in English. Excluded from the study were children who displayed one or more of the following: visual, hearing, or physical impairment; cerebral palsy; childhood disintegrative disorder; Rett syndrome; or genetic disease, such as fragile X syndrome.

Procedure

One parent of each child completed both the SP and the SPM–Home Form. The questionnaires were sent by mail or completed in the clinic during the assessment for the longitudinal study. After receiving the completed questionnaires, the research assistant verified that each question was answered. If data were missing, a phone call was made to the parent to complete the questionnaire. Only questionnaires that were entirely completed were kept for data analysis (N = 34). The questionnaires were then scored by an occupational therapist with the appropriate training. The project was approved by the McGill University Ethics Committee, and all parents signed a consent form before data collection.

Instruments

Sensory Profile.

The SP is a standardized parent-completed questionnaire that assesses sensory processing and its impact on the functioning of children ages 3–10 yr. The 125 items represent behaviors that can be interpreted as responses to sensory experiences. The parent rates the observed frequency of these behaviors on a 5-point Likert scale (ranging from 1 = always to 5 = never). The tool consists of 14 sections that refer to sensory processing, modulation, and behavioral and emotional responses. Each raw score is compared with a threshold value to determine a category of performance: typical performance, probable difference (1 standard deviation below the mean), and definite difference (2 standard deviations below the mean). A lower raw score means a greater difference.

The examiner can also explore the items to determine which of the four Dunn model quadrants the child falls into: sensory sensitivity, sensory avoidance, low registration, or sensory seeking. The tool takes approximately 30 min to complete, and scoring requires 20–30 min (Dunn, 1999). The tool’s psychometric values have been documented and deemed adequate (Brown, Morrison, & Stagnitti, 2010b; Dunn, 1999; Ohl et al., 2012). The SSP contains a subset of 38 items selected from the SP. These items are scored using the same method as the SP. An SSP total score can be calculated and interpreted according to norms (McIntosh et al., 1999).

Sensory Processing Measure.

The SPM is a standardized assessment tool based on Ayres’ sensory integration theory (Parham et al., 2007; Schaaf et al., 2010) that assesses the behaviors involved in sensory processing for children ages 5–12 yr. It combines several forms, including the Home Form, the Main Classroom Form, and various School Environments Forms. The SPM–Home Form was used in this study because it is most like the SP in terms of respondent and setting. On the SPM–Home Form, a parent rates the observed frequency of 75 behaviors on a 4-point Likert scale (never, occasionally, frequently, and always). Raw scores are calculated across eight scales: Social Participation, Vision, Hearing, Touch, Body Awareness, Balance and Motion, Planning and Ideas, and Total Sensory Systems. The child’s functioning is then classified according to three categories: typical, some problems (1 standard deviation below the mean), and definite dysfunction (2 standard deviations below the mean). A higher raw score means a greater difference. The tool can be filled out in 15–20 min, and the scoring can be completed in 5–10 min (Parham & Ecker, 2007). This tool also offers adequate psychometric properties (Brown et al., 2010b; Parham et al., 2007).

Data Analysis

Descriptive statistics were used to document the sociodemographic characteristics of the families involved in the study and to summarize the results obtained on each scale of the SP and SPM–Home Form. The SP and SPM–Home Form scales intended for comparison were chosen because of their similar content, in contrast to previous studies, which compared only the total scores or all the scales from each tool without any regard to their content. The selected scales were those that assess the sensory features involved in each sensory domain and those that assess the impact of sensory features on social functioning. We used the SSP total score for comparison with the SPM–Home Form Total Sensory Systems scale because it is derived from the SP and validated as a unidimensional construct (McIntosh et al., 1999).

Pearson correlation coefficients were used to measure the relationship between the scales’ raw scores. A χ² test on the proportion of children classified in each category was then conducted, and Cohen’s κ coefficient was calculated to determine the level of agreement between the classifications. Both tests were repeated while merging the “1 standard deviation below the mean” and “2 standard deviations below the mean” categories for both tools. All statistical analyses were conducted using IBM SPSS Statistics (Version 20; IBM Corp., Armonk, NY). The results were considered statistically significant using p ≤ .05.

Results

The sociodemographic characteristics of the participants are presented in Table 1. This study presents data for the 34 children who participated at Time 2 of the longitudinal study.

Table 1.

Sociodemographic Characteristics of Participants

Characteristic	n (%)
Child (N = 34)
Gender
Male	28 (82.4)
Female	6 (17.6)
Diagnosis
Autism	28 (82.4)
PDD–NOS	6 (17.6)
M age, mo (SD)	72.91 (4.50)
Parent (N = 34)
Gender: female (mothers)	34 (100)
Ethnicity
White	23 (67.6)
Other	11 (32.4)
Language
English	23 (67.6)
French	4 (11.8)
Other	7 (20.6)
Marital status
In a relationship	29 (85.3)
Single	5 (14.7)
Education: attended university	23 (67.6)
Income
<CAN$40,000	8 (23.5)
>CAN$40,000	26 (76.5)

Note. M = mean; PDD–NOS = pervasive developmental disorder–not otherwise specified; SD = standard deviation.

Results Obtained With the Assessment Tools for Sensory Features

The mean scores for each SP and SPM–Home Form scale are presented in Table 2, and the number of children per category is presented in Table 3. Compared with the SP, the SPM–Home Form classified more children as atypical in every domain assessed.

Table 2.

Descriptive Statistics for Raw Scores on the Sensory Profile and the Sensory Processing Measure–Home Form Scales

Scale	M (SD)	Range	Maximum Possible Score
Sensory Profile
Auditory Processing	29.91 (5.15)	18–39	40
Visual Processing	38.38 (5.12)	26–45	45
Vestibular Processing	47.50 (5.86)	35–55	55
Touch Processing	74.24 (10.64)	52–89	90
Oral Sensory Processing	44.68 (11.43)	17–60	60
Sensory Processing Related to Endurance/Tone	40.12 (5.53)	25–45	45
Modulation Related to Body Position and Movement	42.35 (5.63)	31–50	50
Emotional/Social Responses	64.56 (8.98)	41–83	85
SSP Total Score a	151.42 (16.40)	124–182	190
Sensory Processing Measure
Social Participation	24.32 (6.36)	11–38	40
Vision	16.24 (3.66)	11–27	44
Hearing	13.41 (4.77)	7–24	32
Touch	17.94 (6.74)	11–41	44
Body Awareness	18.03 (6.93)	10–39	40
Balance and Motion	18.50 (6.83)	11–44	44
Taste and Smell (Items 41–45)	8.56 (4.05)	5–20	20
Total Sensory Systems	93.71 (26.09)	59–167	224

Note. N = 34. SSP = Short Sensory Profile.

N = 33.

Table 3.

Participant Distribution According to the Sensory Profile and Sensory Processing Measure–Home Form Categorizations

SP	SPM
SP	Typical	−1 SD	−2 SD	Total
	Hearing
Auditory Processing
Typical	11	6	1	18
−1 SD	3	7	0	10
−2 SD	0	2	4	6
Total	14	15	5	34
	Vision
Visual Processing
Typical	26	5	0	31
−1 SD	1	1	0	2
−2 SD	1	0	0	1
Total	28	6	0	34
	Balance and Motion
Vestibular Processing
Typical	13	5	2	20
−1 SD	0	3	0	3
−2 SD	1	9	1	11
Total	14	17	3	34
	Touch
Touch Processing
Typical	13	6	2	21
−1 SD	1	5	0	6
−2 SD	1	4	2	7
Total	15	15	4	34
	Body Awareness
Sensory Processing Related to Endurance/Tone
Typical	14	3	5	22
−1 SD	2	1	0	3
−2 SD	2	5	2	9
Total	18	9	7	34
	Body Awareness
Modulation Related to Body Position and Movement
Typical	17	1	4	22
−1 SD	1	6	0	7
−2 SD	0	2	3	5
Total	18	9	7	34
	Social Participation
Emotional/Social Responses
Typical	8	11	3	22
−1 SD	2	6	0	8
−2 SD	0	1	3	4
Total	10	18	6	34
	Total Sensory Systems
SSP Total Score
Typical	9	4	1	14
−1 SD	2	6	1	9
−2 SD	0	7	3	10
Total	11	17	5	33

Note. SD = standard deviation; SP = Sensory Profile; SPM = Sensory Processing Measure; SSP = Short Sensory Profile.

Convergent Validity Between the Sensory Profile and the SPM–Home Form

Table 4 presents the correlations between the raw scores for the SP and SPM–Home Form scales. The pairs that were most strongly correlated were Visual Processing–Vision and SSP Total Score–Total Sensory Systems. All other significant correlations were moderate according to Cohen’s (1998) conventions of effect size interpretation. Three pairs of scales (Vestibular Processing–Balance and Motion, Oral Sensory Processing–Taste and Smell, and Sensory Processing Related to Endurance/Tone–Body Awareness) were not correlated.

Table 4.

Raw Scores Correlations and Levels of Agreement Between Classifications of the Sensory Profile and Sensory Processing Measure–Home Form

		Raw Score r	Classification
Fields			In 3 Categories a		In 2 Categories^b
SP	SPM		χ²	κ	χ²(1)	κ
Auditory Processing	Hearing	−.461**	20.17***	.436***	6.28*	.418*
Visual Processing	Vision	−.581***	1.70	.138	0.56	.119
Vestibular Processing	Balance and Motion	−.270	13.27**	.270**	11.38***	.544***
Touch Processing	Touch	−.459**	9.93*	.342**	7.05**	.428**
Oral Sensory Processing	Taste and Smell (Items 41–45)^b	−.270
Sensory Processing Related to Endurance/Tone	Body Awareness	−.244	7.16	.137	2.86	.282
Modulation Related to Body Position and Movement	Body Awareness	−.383*	25.98***	.589***	14.81***	.641***
Emotional/Social Responses	Social Participation	−.474**	12.02*	.247*	1.45	.160
SSP Total Score^c	Total Sensory Systems	−.533***	12.33*	.324**	10.43***	.553***

Note. SP = Sensory Profile; SPM = Sensory Processing Measure; SSP = Short Sensory Profile. N = 34.

The degree of freedom (df) for the χ² test for most scales is 4. The df for the Visual Processing–Vision pair is 2. ^bBecause of the impossibility of classifying this raw score in the performance categories, only the correlation was calculated with the SP scale. ^c N = 33.

p ≤ .05.

p ≤ .01.

***

p ≤ .001.

The χ² tests reveal that classifying children into three categories led to similar results for both tools for most pairs of scales, with the exception of Visual Processing–Vision and Sensory Processing Related to Endurance/Tone–Body Awareness (see Table 4). According to Landis and Koch’s (1977) interpretation of the κ coefficients, a moderate level of agreement emerged between the classifications of two scale pairs (Modulation Related to Body Position and Movement–Body Awareness, Auditory Processing–Hearing), and four pairs of scales had a fair or low level of agreement (Touch Processing–Touch, SSP Total Score–Total Sensory Systems, Vestibular Processing–Balance and Motion, and Emotional/Social Responses–Social Participation).

The level of agreement increased for most pairs of scales when combining the “1 standard deviation below the mean” and “2 standard deviations below the mean” categories (see Table 4). Only the κ coefficient for the Auditory Processing–Hearing pair decreased slightly, but its level of agreement remained moderate. The other pairs were not statistically similar.

Discussion

The objective of this study was to document the convergent validity of the SP and the SPM–Home Form using a sample of children with ASD. Because the SP and SPM–Home Form are largely used in clinics, these results could help occupational therapists make informed and evidence-based decisions about their evaluation practices with children with ASD. In fact, clinicians should be aware that their understanding of the sensory features of these children could differ depending on their choice of assessment tool. This could have an impact on the intervention plan for a specific child and on communication across sites using different assessment tools. Ultimately, these findings emphasize the importance of using several sources of information when documenting sensory features in children with ASD.

For 11 of 16 comparisons, the level of agreement between the SP and the SPM–Home Form scales was statistically significant (p ≤ .02) and varied from 24.7% to 58.9% when classifying the scores of children into three categories and from 41.8% to 64.1% when grouping them into two categories. A fair level of agreement emerged for the total scores (32.4%, p ≤ .01) in the three-category classification, and a moderate level of agreement emerged (55.3%, p ≤ .001) in the two-category classification. The SPM–Home Form appears to identify more children with ASD who display sensory features in every domain assessed by both tools. The overall results suggest moderate convergent validity between the SP and the SPM–Home Form for children with ASD. Moreover, the likelihood of obtaining the same conclusion for both tools increases when classifying children in only two categories.

The classification differences could be partly explained by certain differences in the tools’ characteristics. For instance, the Likert scales are not structured the same way—the SP has five levels and the SPM has four—which could have an impact on the scoring and interpretation of the results.

With that being said, the main difference remains the theoretical model used to construct the tools, which is reflected in the questions asked by each. The SP is based on Dunn’s (1999) model, which hypothesized that there is a relationship between a person’s responsivity and a person’s responding or self-regulation strategies and that the interaction of these functions creates four basic patterns of sensory processing. The SPM relies on Ayres’ sensory integration theory (Parham et al., 2007; Schaaf et al., 2010). Both models provide different insights into the understanding of sensory features of children with ASD. On one hand, Dunn’s model highlights the self-regulation strategies adopted by children on the basis of their neurological threshold for each sensory domain. These neurological thresholds can vary according to the child’s level of awareness throughout the day, but also according to the environmental stimuli involved. On the other hand, Ayres’ sensory integration theory was originally based strictly on neurological concepts such as perception, modulation, and integration to explain the concepts of praxis and motor learning as well as adaptive and maladaptive behavior (Ayres, 2005; Fisher, Murray, & Bundy, 2002). Over the years, the concept of social participation came to enhance Ayres’ theory and development of the SPM by taking the evolution of occupational therapy practices into account.

To understand the classification similarities and differences between the two tools for a given child, we analyzed the content of the scales for each sensory domain. First, the analysis of the hearing and touch items confirmed that the SP and SPM–Home Form assess similar content for both sensory domains. In addition, they include items that point to characteristic ASD behaviors, which supports their relevance to this specific population.

The SP and SPM–Home Form vision-related scales did not provide a statistically significant level of agreement. An analysis of the items highlights the differences that may explain the result: Most items on the SP Visual Processing scale assess hyperreactivity to visual stimuli, and the SPM Vision scale contains more items that represent behaviors associated with hyporeactivity or sensory seeking. Furthermore, these scales include items on visual perception, which could lead to confusion when identifying difficulties in processing visual information in children with ASD, because these children are known to display specificities regarding visual attention and discrimination skills (Simmons et al., 2009). Therefore, their visual–perceptual abilities could mask hypo- or hyperreactivity to visual stimuli.

Neither tool can provide a specific and comprehensive assessment for the gustatory and olfactory domains. The SP has a scale that measures oral sensory features, and the SPM–Home Form does not. For the SPM–Home Form, Items 41–45 were lumped together to create a score to compare with the SP scale. However, the SP Oral Sensory Processing scale includes items on texture reactivity, which is not specific to the gustatory and olfactory domains. Considering the significant impact of feeding difficulties in children with ASD, a more specific tool is required to assess gustative and olfactory hypersensitivity in children with ASD (Lane et al., 2014; Martins, Young, & Robson, 2008).

A significant but weak level of agreement was demonstrated between the SP’s Vestibular Processing and the SPM–Home Form’s Balance and Motion scales because of varying content. Unlike the SP’s Vestibular Processing scale, the SPM’s Balance and Motion scale includes some items that refer to motor responses such as balance and coordination.

The SPM–Home Form’s Body Awareness scale was compared with two SP scales, the Modulation Related to Body Position and Movement scale and the Sensory Processing Related to Endurance/Tone scale. The results show that only the Modulation Related to Body Position and Movement scale can be linked to the Body Awareness scale. These two scales have several items in common regarding behavior that seeks movement and proprioceptive stimulation. However, certain proprioceptive features of children with ASD are found in the items of the SP’s Sensory Processing Related to Endurance/Tone scale, as demonstrated in a study by Lane et al. (2014), in which a subgroup of children with ASD presented a significant difference in the SSP Low Energy Weak category that addresses low tonicity and lack of endurance. Considering that the SP’s Sensory Processing Related to Endurance/Tone scale was not correlated with the SPM–Home Form’s Body Awareness scale in the current study, it would therefore seem that the SPM–Home Form does not cover certain difficulties specific to children with ASD.

The SP’s Emotional and Social Responses scale mainly assesses aspects linked to the child’s temperament and emotional regulation, such as anxiety or tolerance of frustration. The SPM–Home Form’s Social Participation scale contains items that assess the child’s level of interaction and ability to participate in family conversations and other day-to-day activities. Despite two relatively different constructs, a moderate and significant correlation was observed between both scales. However, a low level of agreement was noted, which could be explained by their varying content.

Limitations and Future Research

This study compares two assessment tools completed by the same person at the same time. Responses given to the first questionnaire may have influenced responses given to the second. They were placed in the same order for each recipient, but the actual completion order was not controlled for. Also, the computation of the SSP total score may have introduced some bias, because it was never validated this way. However, the significant correlation between the two total scores seems to support its validity. Furthermore, the socioeconomic characteristics of the mothers who took part in the study may have limited the representativeness of the sample and influenced the generalizability of results. Indeed, most of the participants had a spouse, a postsecondary diploma, and middle to upper income. This profile, however, remains similar to that of mothers of children with ASD typically represented in past research (Baranek et al., 2006; Brown et al., 2010a; Watson et al., 2011).

The Sensory Profile 2 (SP2; Dunn, 2014) has been published since the data collection for this study. The main differences between the versions consist of a refinement of the items included in the sensory domains scales and a new classification of children into five categories of performance according to the normal distribution. This new classification has a minor impact on the results obtained by children with ASD because they are generally classified into the categories “more than others” or “much more than others” (Dunn, 2014), just as they are on the SP. Moreover, despite the changes made to the items, most of the sensory domain scales remain similar on the two versions. On this basis, occupational therapists could use the results of the current study to inform their choice between the SP2 and the SPM–Home Form while evaluating children with ASD. However, one important change in the SP2 is the creation of a scale specific to the sensory processing of proprioception. Some of the items used to create this scale were originally in the SP Modulation Related to Body Position and Movement and Sensory Processing Related to Endurance/Tone scales. It would be interesting in future studies to investigate the correlation and level of agreement between this new scale and the SPM–Home Form Body Awareness scale.

Implications for Occupational Therapy Practice

Regarding the assessment of sensory features in school-age children with ASD,

The SP and the SPM–Home Form have moderate convergent validity, and the level of agreement is greater when detecting only the presence or absence of sensory features. The SPM–Home Form seems to identify more children with ASD who display sensory features in every domain assessed by both tools.

Regardless of the tool used, occupational therapy practitioners must remain alert to the presence of certain sensory features specific to children with ASD, including hyporeactive and sensory-seeking profiles, along with difficulties in the hearing, tactile, gustatory, olfactory, and proprioceptive domains.

To complement the selected questionnaire, occupational therapy practitioners should use several other sources of information when documenting sensory features in children with ASD, including interviews with parents and teachers along with behavioral observations.

Conclusion

This cross-sectional study compared the use of the SP and the SPM–Home Form using a cohort of children with ASD. The results support the convergent validity of the SP with the SPM–Home Form. Although both tools are based on distinct theoretical models that explain sensory processing, neither tool targets every step involved in this processing. Thus, the identification of the basic phenomenon of sensory features remains limited. Consequently, occupational therapy interventions based on hypotheses that address the underlying causes of sensory features must be validated in the child’s day-to-day life. To better support these interventions, a tool must be developed to address every step involved in sensory processing.

Footnotes

Acknowledgments

The data were extracted from a longitudinal study funded by the Fonds de Recherche du Québec–Culture et Société (FRQSC-121463). We offer our sincere gratitude to the families who took part in the study, along with Natasha Rouleau, occupational therapist and lecturer at the Université de Montréal, for her comments.

References

American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author.

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.

Ashburner

Rodger

Ziviani

, & Jones

(2014). Occupational therapy services for people with autism spectrum disorders: Current state of play, use of evidence and future learning priorities. Australian Occupational Therapy Journal, 61, 110–120. https://doi.org/10.1111/1440-1630.12083

Ayres

(2005). Sensory integration and the child: Understanding hidden challenges (25th anniversary ed., rev. and updated). Los Angeles: Pediatric Therapy Network.

Baranek

G. T.

David

F. J.

Poe

M. D.

Stone

W. L.

, & Watson

L. R.

(2006). Sensory Experiences Questionnaire: Discriminating sensory features in young children with autism, developmental delays, and typical development. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 47, 591–601. https://doi.org/10.1111/j.1469-7610.2005.01546.x

Ben-Sasson

Hen

Fluss

Cermak

S. A.

Engel-Yeger

, & Gal

(2009). A meta-analysis of sensory modulation symptoms in individuals with autism spectrum disorders. Journal of Autism and Developmental Disorders, 39, 1–11. https://doi.org/10.1007/s10803-008-0593-3

Brown

Morrison

I. C.

, & Stagnitti

(2010a). The convergent validity of two sensory processing scales used with school-age children: Comparing the Sensory Profile and the Sensory Processing Measure. New Zealand Journal of Occupational Therapy, 57, 56–65.

Brown

Morrison

I. C.

, & Stagnitti

(2010b). The reliability of two sensory processing scales used with school-age children: Comparing the response consistency of mothers, fathers, and classroom teachers rating the same child. Journal of Occupational Therapy, Schools, and Early Intervention, 3, 331–347. https://doi.org/10.1080/19411243.2010.541775

Cohen

(1998). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.

10.

Dunn

(1999). Sensory Profile—User’s manual. Minneapolis: Pearson.

11.

Dunn

(2014). Sensory Profile 2—User’s manual. Minneapolis: Pearson.

12.

Fisher

A. G.

Murray

E. A.

, & Bundy

A. C.

(2002). Sensory integration: Theory and practice (2nd ed.). Philadelphia: F. A. Davis. https://doi.org/10.1007/978-3-662-09864-6

13.

Frieden

T. R.

Jaffe

H. W.

Cono

Richards

C. L.

, & Iademarco

M. F.

; Developmental Disabilities Monitoring Network Surveillance Year 2010 Principal Investigators; Centers for Disease Control and Prevention. (2014). Prevalence of autism spectrum disorder among children aged 8 years—Autism and developmental disabilities monitoring network, 11 sites, United States, 2010. MMWR Surveillance Summaries, 63, 1–21.

14.

Glod

Riby

D. M.

Honey

, & Rodgers

(2015). Psychological correlates of sensory processing patterns in individuals with autism spectrum disorder: A systematic review. Review Journal of Autism and Developmental Disorders, 2, 199–221. https://doi.org/10.1007/s40489-015-0047-8

15.

Hansen

K. D.

, & Jirikowic

(2013). A comparison of the Sensory Profile and Sensory Processing Measure Home Form for children with fetal alcohol spectrum disorders. Physical and Occupational Therapy in Pediatrics, 33, 440–452. https://doi.org/10.3109/01942638.2013.791914

16.

Hazen

E. P.

Stornelli

J. L.

O’Rourke

J. A.

Koesterer

, & McDougle

C. J.

(2014). Sensory symptoms in autism spectrum disorders. Harvard Review of Psychiatry, 22, 112–124. https://doi.org/10.1097/01.HRP.0000445143.08773.58

17.

Henry

D. A.

, & Miller-Kuhaneck

(2009). The Sensory Processing Measure (SPM): Meeting the needs of school-based practitioners part two: Case example and practical applications. Journal of Occupational Therapy, Schools, and Early Intervention, 2, 58–63. https://doi.org/10.1080/19411240902720288

18.

Kirby

A. V.

Little

L. M.

, & Baranek

G. T.

(2015). Observational characterization of sensory interests, repetitions, and seeking behaviors. American Journal of Occupational Therapy, 69, 6903220010. https://doi.org/10.5014/ajot.2015.015081

19.

Landis

J. R.

, & Koch

G. G.

(1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159–174. https://doi.org/10.2307/2529310

20.

Lane

A. E.

Molloy

C. A.

, & Bishop

S. L.

(2014). Classification of children with autism spectrum disorder by sensory subtype: A case for sensory-based phenotypes. Autism Research: Official Journal of the International Society for Autism Research, 7, 322–333. https://doi.org/10.1002/aur.1368

21.

Le Couteur

Lord

, & Rutter

(2003). The Autism Diagnostic Interview–Revised (ADI–R). Los Angeles: Western Psychological Services.

22.

Lord

Rutter

DiLavore

P. C.

, & Risi

(1999). Autism Diagnostic Observation Schedule–WPS (ADOS–WPS). Los Angeles: Western Psychological Services.

23.

Marquenie

Rodger

Mangohig

, & Cronin

(2011). Dinnertime and bedtime routines and rituals in families with a young child with an autism spectrum disorder. Australian Occupational Therapy Journal, 58, 145–154. https://doi.org/10.1111/j.1440-1630.2010.00896.x

24.

Martins

Young

R. L.

, & Robson

D. C.

(2008). Feeding and eating behaviors in children with autism and typically developing children. Journal of Autism and Developmental Disorders, 38, 1878–1887. https://doi.org/10.1007/s10803-008-0583-5

25.

McIntosh

D. N.

Miller

L. J.

Shyu

, & Dunn

(1999). Overview of the Short Sensory Profile Sensory Profile—User’s manual. Minneapolis: Pearson.

26.

Miller-Kuhaneck

(2015). Autism spectrum disorder. In Case-Smith

& O’Brien

J. C.

(Eds.), Occupational therapy for children and adolescents (7th ed., pp. 766–792). St. Louis: Mosby/Elsevier.

27.

Ohl

Butler

Carney

Jarmel

Palmieri

Pottheiser

, & Smith

(2012). Test–retest reliability of the Sensory Profile Caregiver Questionnaire. American Journal of Occupational Therapy, 66, 483–487. https://doi.org/10.5014/ajot.2012.003517

28.

Parham

L. D.

, & Ecker

(2007). Sensory Processing Measure (SPM) Home Form. Los Angeles: Western Psychological Services.

29.

Parham

L. D.

Ecker

Miller-Kuhaneck

Henry

D. A.

, & Glennon

T. J.

(2007). Sensory Processing Measure (SPM): Manual. Los Angeles: Western Psychological Services.

30.

Samson

A. C.

Phillips

J. M.

Parker

K. J.

Shah

Gross

J. J.

, & Hardan

A. Y.

(2014). Emotion dysregulation and the core features of autism spectrum disorder. Journal of Autism and Developmental Disorders, 44, 1766–1772. https://doi.org/10.1007/s10803-013-2022-5

31.

Schaaf

R. C.

, & Lane

A. E.

(2015). Toward a best-practice protocol for assessment of sensory features in ASD. Journal of Autism and Developmental Disorders, 45, 1380–1395. https://doi.org/10.1007/s10803-014-2299-z

32.

Schaaf

R. C.

Schoen

S. A.

Roley

S. S.

Lane

S. J.

Koomar

, & May-Benson

T. A.

(2010). A frame of reference for sensory integration. In Kramer

& Hinojosa

(Eds.), Frames of reference for p ediatric occupational therapy (3rd ed., pp. 99–186). Philadelphia: Lippincott Williams & Wilkins.

33.

Schoen

S. A.

Miller

L. J.

Brett-Green

B. A.

, & Nielsen

D. M.

(2009). Physiological and behavioral differences in sensory processing: A comparison of children with autism spectrum disorder and sensory modulation disorder. Frontiers in Integrative Neuroscience, 3, 29. https://doi.org/10.3389/neuro.07.029.2009

34.

Simmons

D. R.

Robertson

A. E.

McKay

L. S.

Toal

McAleer

, & Pollick

F. E.

(2009). Vision in autism spectrum disorders. Vision Research, 49, 2705–2739. https://doi.org/10.1016/j.visres.2009.08.005

35.

Tomchek

S. D.

, & Case-Smith

(2009). Occupational therapy practice guidelines for children and adolescents with autism. Bethesda, MD: AOTA Press.

36.

Tomchek

S. D.

, & Dunn

(2007). Sensory processing in children with and without autism: A comparative study using the Short Sensory Profile. American Journal of Occupational Therapy, 61, 190–200. https://doi.org/10.5014/ajot.61.2.190

37.

Watling

Koenig

K. P.

Davies

P. L.

, & Schaaf

R. C.

(2011). Occupational therapy practice guidelines for children and adolescents with challenges in sensory processing and sensory integration. Bethesda, MD: AOTA Press.

38.

Watson

L. R.

Patten

Baranek

G. T.

Poe

Boyd

B. A.

Freuler

, & Lorenzi

(2011). Differential associations between sensory response patterns and language, social, and communication measures in children with autism or other developmental disabilities. Journal of Speech, Language, and Hearing Research, 54, 1562–1576. https://doi.org/10.1044/1092-4388(2011/10-0029)