An exploratory study of the relationship between typically-developing school-age children’s sensory processing and their activity participation

Abstract

Introduction

Children encounter several types of sensory input from their daily living environments and take in and process this information using their sensory systems. Few studies have considered the impact of children’s sensory preferences on their activity participation. This study investigated the relationship between children’s sensory processing factors and the daily activities they chose to participate in.

Method

Twenty-three parents of typically developing school-aged children completed the Sensory Processing Measure Home Form and Children Participation Questionnaire-School. Spearman correlations were conducted between sensory preferences and participation, as measured by frequency, intensity, independence level, children’s enjoyment and parental satisfaction. Regression models were also completed between each of the participation measures and sensory processing factors.

Results

Sensory processing accounted for 69.8% (p = 0.001) of participation diversity’s total variance with unique contributions made by body awareness (proprioception) and planning and ideas (p = 0.040); 45.9% (p = 0.024) of participation intensity’s variance with touch made a unique contribution (p = 0.030) and 42.4% (p = 0.034) of participation independence’s variance with body awareness (proprioception) made a unique contribution (p = 0.038).

Conclusion

Considerations should be made for sensory processing screening for typically developing children and the impacts this could potentially have on their daily participation.

Keywords

participation activity sensory processing children occupational therapy

Introduction

Participation in meaningful day-to-day activities has a direct and significant impact on children’s health and well-being (Rosenberg and Bart, 2016). Gaining an understanding about the factors that support or inhibit the daily activity participation of children is therefore a crucial area for exploration. Sensory processing variables are one such potential factor impacting children’s participation. Defined by O’Donnel et al. (2012), sensory processing refers to the way children take in, interpret and appropriately use and respond to sensory-based information from their environment. Sensory inputs and responses impact the way children, both those with and without disabilities, participate in their different daily occupations, including self-care, play, leisure, education and social participation. The relationship between sensory processing preferences and participation has been widely researched within groups of children with known clinical diagnoses (Allen and Casey, 2017; Ashburner et al., 2008; Jirikowic et al., 2008; Kojovic et al., 2019). The aims of the current study are therefore to investigate the relationship between 6- to 12-year-old children’s sensory processing and their activity participation and explore the impact of sensory processing on participation in typically developing (TD) children. The findings will provide new insights and preliminary baseline evidence on this topic. This will provide additional information in relation to children’s activity participation that clinicians can refer to when working with children presenting with sensory processing challenges.

Literature review

Sensory processing

The importance of recognising sensory preferences as key factors impacting human behaviour and participation has been explored in the literature (Dunn, 2007). The impact of sensory processing on participation has been extensively studied among children with various diagnoses, with many studies focusing on conditions associated with sensory processing challenges, including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), sensory processing disorder (SPD) and developmental coordination disorder (DCD) (Allen and Casey, 2017; Jirikowic et al., 2008; Kojovic et al., 2019). Extreme sensory preferences, either seeking excessive input or avoiding input, were shown to influence participation in daily activities among children with known diagnoses (Allen and Casey, 2017; Ashburner et al., 2008). While some of these studies included control groups made up of TD children, very few of the authors examined the impact of sensory preferences on the daily activity participation of these children (Allen and Casey, 2017; Ashburner et al., 2008; Foitzik and Brown, 2018).

A cross-sectional study by Kojovic et al. (2019) found links suggesting that children with ASD and sensory processing challenges had decreased social and adaptive functioning compared to TD children. An Australian study found that the academic performance of children with ASD was impacted by sensory seeking behaviours, difficulties with auditory filtering or modulation of the tactile or vestibular systems (Ashburner et al., 2008). While restricted, repetitive behaviours have been linked to sensory processing challenges among children with ASD, they are not associated with cognitive factors (Chen et al., 2009). Chen et al. (2009) identified significant associations between repetitive behaviours and tactile, visual and auditory hyperresponsiveness. It is clear from these studies that the daily participation of children with ASD is significantly impacted by their sensory processing patterns.

One study found that 88% of children with DCD present with some sensory processing challenges, especially around auditory, proprioception and vestibular input (Allen and Casey, 2017). A recent systematic review determined that children who were born preterm were more likely to have sensory processing challenges related to tactile, vestibular, proprioceptive and visual sensory systems (Niutanen et al., 2019). Sensory challenges in relation to anxiety were also studied by Houghton et al. (2020) in a systematic review of studies investigating children with anxiety and obsessive-compulsive disorder (OCD). This review concluded that these children are more likely to be overresponsive to external stimuli to the level of a SPD than children in the control group (Houghton et al., 2020).

Participation

Participation is defined as involvement in a life situation (World Health Organization [WHO], 2002). Among the few tools developed to assess the activity participation of children, diversity, frequency, environment, independence, enjoyment and parental satisfaction are common categories that are measured. Factors impacting the diversity and frequency of participation have been widely researched in the occupational therapy literature (Eglison et al., 2017; Taheri et al., 2017; Williams et al., 2018). Research also suggests that children with ASD participate in fewer activities than their peers and in a narrower field of activities (Ratcliff et al., 2018).

Not only do internal factors, such as a condition including ASD and DCD, impact the frequency of participation but so do external environmental factors. One cross-sectional study found that children’s participation frequency was significantly impacted by maternal education and their parents’ perceptions of external barriers (e.g. physical layout of the external community and school environments; inadequate local and federal government policies and attitudes and perceptions of members of the community) (Guichard and Grande, 2019). Another cross-sectional study of children with developmental disabilities found that adaptive behaviours, parental socialisation and school integration programmes were predictors of increased activity participation (Taheri et al., 2017).

Enjoyment and value have also been linked to participation with research demonstrating that children participate in more choice activities than ‘must-do’ activities (Rosenberg et al., 2019). Children’s participation enjoyment has been linked to psychosocial functioning, while their parents’ satisfaction has been associated with performance skills and execution of daily activities (Rosenberg and Bart, 2016). An ethnographic study found that children with DCD placed importance on friendships, enjoyment and physical activity and experienced some challenges in leisure pursuits (Fernandez et al., 2018). Many of the factors influencing different areas of children’s daily participation have been published in the occupational therapy literature; however, few studies have specifically investigated sensory processing factors.

Impact of sensory processing on participation

It is known that diversity of participation in children is impacted by sensorimotor and environmental demands, and recent research has found that children with ASD, ADHD and SPD participate in fewer daily activities than their TD peers (Ismael et al., 2015; Mimouni-Bloch et al., 2018; Ricon et al., 2017). In one study that investigated leisure participation, it was observed that children who were sensory avoiding had decreased enjoyment in leisure participation, but there was no corresponding decrease in participation frequency compared to their TD peers (Ismael et al., 2015). However, other research investigating sensory processing challenges on participation levels reports decreased participation and associations between sensory modulation among children with ASD and reduced social and mealtime participation (Hertzog et al., 2019; Suarez, 2012).

Research that has investigated independence as a factor of participation found that children with ASD had lower levels of participation independence associated with SPD. Using a qualitative case-study approach involving six children with ASD, Eicher et al. (2018) investigated the impact of sensorimotor impairments on leisure participation. The findings indicated that children with sensorimotor challenges experienced interruptions to their daily routines, leisure and social activities, including independence in activities of daily living (ADLs).

The quality of participation in different activities has also been researched. An investigation into TD children’s pretend play participation found that the quality of pretend play was impacted by body awareness, balance and touch senses (Roberts et al., 2018). Similar findings were observed in Ismael et al.’s (2015) cross-sectional study involving 91 children, in which children who were sensory avoiding preferred leisure activities without stimulating actions or social interaction and displayed decreased participation frequency.

The interaction between environment and sensory processing plays a major role in participation among children with ASD, especially in relation to behavioural responses according to caregivers (Pfeiffer et al., 2017). For example, a case–control study by Hertzog et al. (2019) involving parents of 44 children, half of whom presented with sensory processing challenges, revealed that the sensorimotor and environmental demands of leisure activities decreased participation and enjoyment. Therefore, the interaction between environment and sensory processing plays a major role in participation among children with ASD, especially in relation to behavioural responses according to caregivers (Pfeiffer et al., 2017).

Purpose, research questions and hypotheses

The purpose of this study is to investigate the relationship between the sensory processing factors of TD primary school-aged children and the everyday activities they choose to participate in. The research questions posed were the following:

Are sensory factors and daily activities of TD school-age children significantly associated?

Is there a significant association between children’s sensory factors and their frequency and intensity of daily participation?

Is there a significant association between children’s sensory factors and the parental satisfaction of the children’s daily participation?

Method

Design

The study used a non-experimental cross-sectional design.

Participants

The participants were recruited from Victoria, Australia. Inclusion criteria included being a parent or carer of a TD primary school-aged child between 6 and 12 years, with no known physical, neurological, behavioural, intellectual, learning or psychological problems. Participants were also required to be able to read English to complete the parent-report scales. Participants were recruited from a variety of community settings including local sports clubs, children’s dance studio and library.

Instrumentation

Children’s sensory processing factors were measured by the Sensory Processing Measure Home Form (SPM-Home) (Parham et al., 2007). The SPM-Home is a norm-referenced, parent-report standardised assessment of sensory processing issues, praxis and social participation in primary school-aged children (Parham et al., 2007). The SPM-Home measures the following sensory processing factors: social participation, vision, hearing, taste and smell, touch, body awareness (proprioception), balance and motion and planning and ideation (Parham et al., 2007). Parents/caregivers answer 75 questions on a four-point Likert scale with response options of never, occasionally, frequently and always. The SPM-Home total score is the sum of all sections except social participation and planning and ideation as these are not considered to be direct measures of sensory processing.

The SPM-Home has established internal consistency and test–retest reliability data with documented coefficients of 0.77–0.95 and 0.94–0.98, respectively (Parham et al. 2007). The SPM-Home also has documented evidence of its concurrent, convergent and construct validity (Parham et al., 2007). Normative data for the SPM-Home was collected from respondents in the United States. The SPM-Home has been used in other cross-cultural contexts with success including the United Kingdom (Allen and Casey, 2017), Australia (Foitzik and Brown, 2018) and Israel (Hertzog et al., 2019). This provides evidence of its suitability for use in countries that are similar to the United States in culture, socio-economic factors, language and educational systems for children.

The Children Participation Questionnaire-School (CPQ-School) (Rosenberg and Bart, 2015) is an adapted version of the Child Participation Questionnaire (CPQ) which was originally designed for use with children aged four to 6 years old (Rosenberg et al., 2010). The CPQ-School is designed for use with children aged 6–12 years. The CPQ-School is a parent-report assessment designed to collect information about a child’s day-to-day participation habits in activities of daily living (ADLs), instrumental activities of daily living (IADLs), sleep, play, leisure, social participation and education (Rosenberg and Bart, 2015). There are 55 dimensions of daily activities which are rated on Likert scales to measure each of the following: (i) frequency (how often a child participates in an activity scored from 0 (never) to 5 (every day)); (ii) degree of assistance (how independent the child is in an activity scored from 1 (fully assisted) to 6 (independent)); (iii) child’s pleasure in participating (scored from 1 (does not enjoy at all) to 6 (enjoy very much)) and (iv) parental satisfaction from child’s participation (scored from 1 (not at all satisfied) to 6 (very satisfied)) (Rosenberg and Bart, 2015). In summary, the CPQ-School measures five child participation–related factors: participation diversity, participation intensity, participation independence, participation child enjoyment and parent satisfaction with child’s participation (Rosenberg and Bart, 2015).

The CPQ-School is a valid and reliable instrument for use with children aged 6 to 12 years, with and without developmental difficulties (Rosenberg and Bart, 2015), and has good internal reliability, with Cronbach’s alpha coefficients ranging from 0.79 and 0.90 for measures of participation. It also has documented convergent and divergent validity, with statistically significant Spearman correlations between all areas of occupation subcategories and measures (Rosenberg and Bart, 2015).

Standardisation data for the CPQ-School were collected from respondents in Israel. To determine the clinical utility and face validity of the CPQ-School for use in the cross-cultural context where the current study was conducted, the items for the CPQ-School were reviewed by three paediatric occupational therapists, each with five or more years of clinical experience working with children and families. It was determined that all of the CPQ-School items were appropriate for use in the cross-cultural setting and hence exhibited adequate clinical utility and face validity.

Data analyses

Data were exported from Qualtrics into the IBM Statistical Package for the Social Sciences (version 26; IBM Corp., 2019) for data analysis. Descriptive statistics including the mean, standard deviation (SD), range and interquartile ranges were reported for the SPM-Home Form and CPQ-School subscales. To answer the research questions and hypotheses, Spearman’s ρ correlations were calculated between the SPM-Home and the CPQ-School total and subscales. Due to the fact that higher levels of atypical sensory functions are reflected by higher scores on the SPM-Home subscales, in the present study, the SPM-Home items were reverse-scored to enable statistical calculations to be completed on the CPQ-School scores.

Linear regression analyses were completed where the SPM-Home scores were the independent variables and the CPQ-School scores were the dependent variables. Bootstrapping was used to increase the sample size to 500 participants to quality check that the levels of significance were valid and to offset the impact of the small sample size (Choi, 2016).

Procedures

Ethics approval was gained from Deakin University’s Ethics Committee, 2020. Before completing the scales, parents/caregivers were required to provide informed consent. This project was initially approved before the onset of the COVID-19 pandemic, and therefore, the study procedures underwent changes to receive ethics approval and comply with state government mandated COVID-19 restrictions. Initially, the SPM-Home and CPQ-School were to be completed face-to-face using hard copies of the scales, but this mode of data collection was changed to an online format to meet the social distancing rules. The online program Qualtrics was used to deliver the two scales to parent/caregiver respondents online.

An invitation to assist in recruitment was sent to a local dance academy owner in a regional city of Victoria, Australia, with the aim of recruiting 40 parents/caregivers of TD children aged between six and 12 years. The owner of the dance studio provided organisational consent and then sent an invitation to participate to parents through their email database. Two local sports clubs were also invited to assist with the recruitment of study participants. Parents/caregivers who responded to the invitation via email were provided with the plain language statement and link to the online surveys on Qualtrics, with consent built into the first question. All parent/caregiver participants provided consent before completing the online surveys. As parents/caregivers were proxy reporters for their child when completing the SPM-Home and CPQ-School instruments, children were not required to provide assent to participate.

Data from the completed surveys were automatically de-identified and stored on the Qualtrics website with only the researchers having access to it. Data were re-identifiable if parents consented to receive a feedback letter at the end of the study with their child’s raw score from the SPM-Home and CPQ-School and provided their email address as part of the online questionnaire completion.

The following items were revised to make them culturally appropriate for the local vernacular: (i) wording of item 56 in the SPM-Home was changed from ‘teeter-totter’ to ‘see-saw’ and (ii) item three under IADL of the CPQ-School was changed from ‘cellphone’ to ‘mobile phone’. The instructions in the initial CPQ-School ask participants to answer each question within the context of the last 3 months. Due to COVID-19 and restrictions placed on what children typically participate in, this was reworded to specify that it be based on an average 3-month period before the onset of the COVID-19 pandemic.

Results

Participants

Approximately 150 parents/caregivers of children were approached about taking part in the study. A total of 31 participants completed the Qualtrics questionnaire containing the SPM-Home and CPQ-School instruments. After screening for eligibility and removing incomplete surveys after follow-up was attempted, data from 23 participants were included in the analyses. Twenty-one mothers and two fathers were proxy reporters for their children (15 males and eight females) (see Table 1). The mean age for the children was 9.5 years (SD = 2.33 years; range 7.1 years).

Table 1.

Participants’ characteristics (frequencies).

		Frequency (n)	Percentage (%)
Relationship to child	Mother	21	91.30
Relationship to child	Father	2	8.70
Parents’ gender	Male	2	8.70
Parents’ gender	Female	21	91.30
Parents’ spoken language	English only	17	73.90
Parents’ spoken language	English and another language/s	6	26.10
Child’s gender	Male	15	65.20
Child’s gender	Female	8	34.80
Child’s spoken language	English only	17	73.90
Child’s spoken language	English and another language/s	6	26.10

Descriptive statistics

Table 2 presents the descriptive statistics for the SPM-Home and CPQ-School subscale results as means and SDs. Low scores on the SPM-Home indicate typical sensory processing preferences, and a high score on the CPQ-School suggests typical participation in different activities. In this study, the SPM-Home scores were reverse-scored to avoid negative relationships so that higher scores on the SPM-Home suggest typical sensory processing responses. The sample mean SPM-Home total score was 80 with a range of 61–73 (SD = 14.79) (see Table 2).

Table 2.

Descriptive statistics SPM-Home and CPQ-School total and subscale scores (n = 23).

				Percentiles
	Mean	Std deviation	Range	25	50	75
SPM social participation	16.00	5.17	19.00	13.00	15.00	18.00
SPM visual	13.30	3.93	17.00	11.00	12.00	14.00
SPM hearing	10.52	3.54	12.00	8.00	9.00	12.00
SPM touch	14.57	4.43	20.00	12.00	13.00	15.00
SPM taste and smell	14.39	7.25	20.00	6.00	19.00	20.00
SPM body awareness	13.52	4.61	16.00	10.00	12.00	15.00
SPM balance and motion	13.70	3.05	14.00	12.00	13.00	15.00
SPM planning and ideas	13.26	4.46	16.00	10.00	12.00	15.00
Total SPM scores	80.00	14.79	61.00	73.00	75.00	86.00
CPQ diversity score	47.91	6.09	26.00	44.00	48.00	53.00
CPQ intensity score	3.90	0.58	1.84	3.40	3.84	4.51
CPQ independence score	5.10	0.79	2.62	4.69	5.31	5.82
CPQ child enjoyment score	5.14	0.65	2.36	4.85	5.32	5.55
CPQ parent satisfaction score	5.27	0.63	2.01	4.81	5.52	5.76

Notes. SPM-Home: Sensory Processing Measure Home Form; CPQ-School: Children’s participation questionnaire-School; Std deviation: standard deviation.

Correlation results

Table 3 presents the correlation results between sensory processing factors as measured by the SPM-Home subscales and children’s daily activities and participation as measured by the CPQ-School subscales. None of the five CPQ-School participation variables significantly correlated with the SPM-Home social participation or touch factors. The CPQ-School participation independence variable had the largest number of SPM-Home sensory processing factors significantly correlate with it, those being vision, hearing, body awareness (proprioception), balance and motion, planning and ideas and SPM-Home total subscales (p < 0.05 and p < 0.01).

Table 3.

Spearman’s ρ correlation between SPM-Home Form and CPQ-School scores (n = 23; bootstrapped sample size = 500).

SPM-Home Form subscale				DIV	INT	IND	ENJ	SAT
SOC	Correlation coefficient			0.140	0.107	0.409	0.194	0.416
	P			0.525	0.626	0.052	0.374	0.049
	Bootstrap¹	Bias		−0.020	−0.009	−0.012	0.002	−0.007
		Std error		0.234	0.233	0.204	0.225	0.197
		BCa 95% CI	Lower	−0.316	−0.341	−0.053	−0.327	−0.091
			Upper	0.521	0.529	0.696	0.613	0.705
VIS	Correlation coefficient			0.103	0.001	0.457*	0.256	0.313
	P			0.641	0.996	0.028	0.238	0.146
	Bootstrap¹	Bias		−0.003	0.006	−0.012	0.005	−0.005
		Std error		0.247	0.255	0.201	0.242	0.228
		BCa 95% CI	Lower	−0.446	−0.529	0.010	−0.255	−0.196
			Upper	0.58	0.597	0.775	0.686	0.698
HEA	Correlation coefficient			0.233	0.154	0.631**	0.305	0.387
	P			0.285	0.483	0.001	0.158	0.068
	Bootstrap¹	Bias		−0.009	0.000	−0.030	−0.009	−0.019
		Std error		0.211	0.239	0.148	0.232	0.181
		BCa 95% CI	Lower	−0.288	−0.348	0.249	−0.244	−0.059
			Upper	0.641	0.639	0.825	0.719	0.703
TOU	Correlation coefficient			0.187	0.339	0.296	0.372	0.189
	P			0.393	0.113	0.171	0.080	0.388
	Bootstrap¹	Bias		0.002	0.007	−0.004	−0.005	0.007
		Std error		0.249	0.256	0.223	0.220	0.243
		BCa 95% CI	Lower	−0.404	−0.246	−0.17	−0.163	−0.363
			Upper	0.700	0.837	0.679	0.788	0.664
TAS	Correlation coefficient			0.281	0.420*	−0.174	0.04	−0.092
	P			0.194	0.046	0.428	0.857	0.677
	Bootstrap¹	Bias		0.005	−0.008	−0.023	−0.024	−0.018
		Std error		0.227	0.205	0.239	0.237	0.229
		BCa 95% CI	Lower	−0.140	0.026	−0.617	−0.426	−0.494
			Upper	0.7	0.803	0.249	0.482	0.268
BOD	Correlation coefficient			−0.168	−0.063	0.605**	0.523*	0.453
	P			0.444	0.774	0.002	0.010	0.030
	Bootstrap¹	Bias		0.009	0.006	−0.012	-0.004	0.005
		Std error		0.247	0.240	0.148	0.174	0.180
		BCa 95% CI	Lower	−0.710	−0.586	0.252	0.138	−0.011
			Upper	0.460	0.493	0.861	0.817	0.834
BAL	Correlation coefficient			−0.075	−0.183	0.511*	0.395	0.452*
	P			0.734	0.404	0.013	0.062	0.030
	Bootstrap¹	Bias		−0.015	−0.006	−0.015	−0.002	−0.014
		Std error		0.240	0.229	0.162	0.197	0.172
		BCa 95% CI	Lower	−0.521	−0.556	0.230	−0.031	0.111
			Upper	0.409	0.271	0.752	0.751	0.725
PLA	Correlation coefficient			0.234	0.087	0.496*	0.355	0.484*
	P			0.283	0.694	0.016	0.096	0.019
	Bootstrap¹	Bias		−0.019	−0.005	0.008	0.010	0.006
		Std error		0.228	0.235	0.203	0.208	0.200
		BCa 95% CI	Lower	−0.266	−0.458	0.049	−0.079	0.050
			Upper	0.649	0.604	0.862	0.772	0.839
TOT	Correlation coefficient			0.387	0.348	0.559**	0.388	0.41
	P			0.068	0.104	0.006	0.067	0.052
	Bootstrap¹	Bias		0.003	0.011	−0.030	−0.017	−0.013
		Std error		0.213	0.227	0.180	0.211	0.197
		BCa 95% CI	Lower	−0.096	−0.174	0.167	−0.112	−0.020
			Upper	0.785	0.818	0.806	0.713	0.757

Notes. *Correlation is significant at the 0.05 level (2-tailed); **Correlation is significant at the 0.01 level (2-tailed). CI: confidence intervals; Std error: standard error; BCa: bias-corrected and accelerated; SOC: social participation; VIS: visual; HEA: hearing; TOU: touch; TAS: taste and smell; BOD: body awareness (proprioception); BAL: balance and motion; PLA: planning and ideas; TOT: total SPM-Home Form score; DIV: diversity; INT: intensity; IND: independence level; ENJ: child enjoyment; SAT: parent satisfaction.

¹Unless otherwise noted, bootstrap results are based on 500 bootstrap samples.

Multiple linear regression

Table 4 outlines the results of the five regression model analyses completed. The subscale scores of the SPM-Home were entered as the independent variable in each of the five regression models and the dependent variables were the five CPQ-School subscale scores. The pre-bootstrapping results reported in Table 4 indicate the regression results completed with the sample size of 23 and the post-bootstrapping results indicate the regression analysis findings with the derived sample size of 500.

Table 4.

Linear regression between SPM-Home scores and CPQ-School scores (n = 23; bootstrapped n = 500).

		Before bootstrapping				After bootstrapping²
Predictors	B¹	SE B	β	t	P	SE B	p	BCa 95% CI lower	BCa 95% CI upper
Model 1: Diversity (r² = 0.808; r²_adj = 0.698; p = 0.001*)
(Constant)	−305.783	104.581		−2.924	0.011*	223.331	0.088	−711.485	12.84
SPM taste and smell	0.332	0.172	0.396	1.934	0.074	0.271	0.196	−0.05	0.921
SPM social participation	−0.399	0.269	−0.339	−1.485	0.16	0.402	0.257	−1.206	0.353
SPM visual	0.495	0.445	0.319	1.113	0.285	1.098	0.409	−1.653	1.465
SPM hearing	0.794	0.411	0.462	1.931	0.074	0.802	0.251	−1.308	4.717
SPM touch	0.754	0.412	0.548	1.832	0.088	0.688	0.242	−0.802	1.531
SPM body awareness	−0.825	0.365	−0.625	−2.258	0.04*	0.548	0.092	−1.675	−0.357
SPM balance and motion	−0.245	0.363	−0.123	−0.675	0.511	0.661	0.601	—	—
SPM planning and ideas	0.761	0.264	0.558	2.882	0.012*	0.428	0.084	0.342	1.425
Model 2: Intensity (r² = 0.655; r²_adj = 0.459; p = 0.024*)
(Constant)	−14.957	13.441		−1.113	0.285	24.95	0.445	−55.171	6.677
SPM taste and smell	0.03	0.022	0.366	1.339	0.202	0.036	0.273	−0.059	0.203
SPM social participation	−0.02	0.035	−0.173	−0.565	0.581	0.051	0.633	−0.117	0.112
SPM visual	−0.062	0.057	−0.416	−1.083	0.297	0.144	0.449	−0.335	0.145
SPM hearing	0.078	0.053	0.475	1.485	0.16	0.088	0.289	−0.192	0.328
SPM touch	0.127	0.053	0.965	2.407	0.03*	0.09	0.15	0.016	0.19
SPM body awareness	−0.086	0.047	−0.678	−1.831	0.088	0.063	0.152	−0.208	0.012
SPM balance and motion	−0.021	0.047	−0.111	−0.455	0.656	0.093	0.709	—	—
SPM planning and ideas	0.042	0.034	0.323	1.245	0.233	0.06	0.467	−0.038	0.157
Model 3: Independence (r² = 0.633; r²_adj = 0.424; p = 0.034*)
(Constant)	−22.198	18.763		−1.183	0.256	40.297	0.481	−97.88	5.073
SPM taste and smell	0.008	0.031	0.077	0.273	0.789	0.051	0.856	−0.074	0.154
SPM social participation	0.041	0.048	0.265	0.84	0.415	0.062	0.487	−0.04	0.101
SPM visual	−0.025	0.08	−0.123	−0.31	0.761	0.16	0.794	−0.376	0.28
SPM hearing	0.078	0.074	0.348	1.053	0.31	0.113	0.421	−0.151	0.371
SPM touch	−0.06	0.074	−0.334	−.807	0.433	0.119	0.537	−0.336	0.139
SPM body awareness	0.15	0.066	0.874	2.287	0.038*	0.086	0.16	−0.023	0.268
SPM balance and motion	−.106	0.065	−0.408	−1.627	0.126	0.141	0.379	—	—
SPM planning and ideas	0.042	0.047	0.239	0.893	0.387	0.085	0.533	−0.108	0.337
Model 4: Enjoyment (r² = 0.489; r²_adj = 0.197; p = 0.190)
(Constant)	−8.13	18.303		−0.444	0.664	50.89	0.782	−80.177	12.721
SPM taste and smell	0.012	0.03	0.131	0.395	0.699	0.079	0.77	−0.087	0.191
SPM social participation	0.025	0.047	0.194	0.522	0.61	0.06	0.619	−0.061	0.118
SPM visual	0.039	0.078	0.233	0.499	0.625	0.192	0.729	−0.516	0.483
SPM hearing	−0.069	0.072	−0.375	−0.964	0.351	0.126	0.511	−0.425	0.441
SPM touch	−0.037	0.072	−0.252	−0.517	0.613	0.126	0.743	−0.31	0.108
SPM body awareness	0.142	0.064	1.002	2.223	0.043*	0.096	0.176	−0.026	0.265
SPM balance and motion	−0.069	0.063	−0.32	−1.081	0.298	0.147	0.593	—	—
SPM planning and ideas	0.022	0.046	0.149	0.472	0.645	0.079	0.78	−0.074	0.277
Model 5: Satisfaction (r² = 0.413; r²_adj = 0.077; p = 0.351)
(Constant)	−11.721	18.929		−0.619	0.546	41.601	0.719	−86.212	20.604
SPM taste and smell	0.013	0.031	0.153	0.428	0.675	0.051	0.735	−0.081	0.219
SPM social participation	0.05	0.049	0.408	1.022	0.324	0.063	0.371	−0.057	0.136
SPM visual	0.035	0.081	0.215	0.428	0.675	0.219	0.749	−0.408	0.325
SPM hearing	−0.024	0.074	−0.135	−0.324	0.751	0.142	0.806	−0.338	0.336
SPM touch	−0.08	0.074	−0.561	−1.072	0.302	0.143	0.507	−0.451	0.106
SPM body awareness	0.115	0.066	0.844	1.746	0.103	0.1	0.285	−0.093	0.255
SPM balance and motion	−0.069	0.066	−0.336	−1.057	0.308	0.149	0.521	—	—
SPM planning and ideas	0.041	0.048	0.293	0.867	0.400	0.089	0.581	−0.08	0.331

Notes. *Represents statistically significant p-values (p < 0.05); Constant = y-intercepts of regression line; B = unstandardised beta coefficient; SE. B = standard error for the unstandardised beta; b = standardised beta; t = the t test statistic; CI: confidence interval; BCa: bias-corrected and accelerated; SPM-Home: Sensory Processing Measure Home Form; CPQ-School: Children’s Participation Questionnaire-School.

¹B remained unchanged after bootstrapping.

²unless otherwise noted, bootstrap results are based on 500 bootstrap samples.

Predictors of children’s participation diversity

There was a significant predictive relationship between sensory processing and participation diversity (r²_adj = 0.698; p = 0.001; BCa 95% CI = −711.485–12.84), accounting for nearly 70% of the CPQ-School participation diversity variable’s total variance. Two independent sensory processing variables made a unique contribution to the diversity regression model: SPM-Home body awareness (proprioception) (p = 0.040; BCa 95% CI = −1.675 to −0.357) and SPM-Home planning and ideas (p = 0.012; BCa 95% CI = 0.342–1.425) (see Table 4).

Predictors of children’s participation intensity

The model with participation intensity as the dependent variable accounted for 45.9% of the total variance (r²_adj = 0.459; p = 0.024; BCa 95% CI = −55.171–6.677). The SPM-Home touch subscale made a unique contribution to the overall CPQ-School participation intensity regression model (p = 0.03; BCa 95% CI = 0.016–0.19) (see Table 4).

Predictors of children’s participation independence

The regression results indicated that 42.4% of the variance of the CPQ-School participation independence dependent variable was accounted for by SPM-Home sensory processing factors (r²_adj = 0.424; p = 0.034; BCa 95% CI = −97.88–5.073) (see Table 4). The SPM-Home body awareness (proprioception) subscale made a unique contribution to the overall CPQ-School participation independence regression model (p = 0.038; BCa 95% CI = −0.023–0.268).

Predictors of children’s participation enjoyment

The regression model completed with CPQ-School child enjoyment as the dependent variable did not reach statistical significance with the SPM-Home subscales as the independent variables (p = 0.190; BCa 95% CI = −80.177–12.721).

Predictors of parent/caregiver satisfaction with child’s participation

Model 5 in Table 4 indicates that there was no significant relationship between the SPM-Home sensory processing factors and CPQ-School parent/caregiver satisfaction (p = 0.351; BCa 95% CI = −86.212–20.604).

Discussion

The findings from this study suggest that sensory processing significantly accounts for the variance seen in participation diversity, intensity and independence level. The terms ‘participation diversity’, ‘intensity’ and ‘independence level’ come from the CPQ-School instrument and refer to dimensions of a child’s participation. Diversity refers to how many different activities a child undertakes; participation intensity is how often a child does any given activity and participation independence describes the level of assistance or encouragement a child requires to participate (Rosenberg et al., 2010; Rosenberg and Bart, 2015).

Participation diversity

Sensory processing accounted for 69.8% (p = 0.001) of the variance seen in TD children’s participation diversity. This suggests that a typical intake and response to sensory information supports a child’s ability to participate in different daily activities. These findings are reflected in other participation studies which found that sensory demands are a barrier to both TD children and children with disabilities’ daily participation (Eglison et al., 2017; Mimouni-Bloch et al., 2018; Suarez, 2012). The present study found that proprioceptive input, as measured by the SPM-Home term ‘body awareness’, contributed uniquely to the variance seen in participation diversity (p = 0.04). No other studies have explored this relationship; however, one study found that children scoring in the low sensory registration quadrant on the Model of Sensory Processing (Dunn, 2007) were associated with the most significant impact on participation diversity (e.g. children who have a high sensory intake threshold and passive behavioural response). This may suggest that children who have a low registration to proprioceptive information are not having their input thresholds met quickly by an activity’s sensory demands and are less likely to seek out new activities, thereby decreasing participation diversity (Dunn, 2007).

Among 480 children in Israel, participation diversity for children with a disability such as a developmental delay was only significantly different to TD children’s participation diversity if both groups came from below-average economic status (Rosenberg et al., 2010). This indicated that family income as an environmental factor might also be a significant contributor to the participation diversity of children. The impact of internal factors on participation has also been studied, with one study reporting that among 197 Canadian children, internal factors such as age and diagnosis accounted for 22% of variance in participation diversity of children with ASD, compared to 7% attributed to family variables and 2% attributed to the school and community context (Taheri et al., 2017). The study specifically reported that adaptive behaviours and skill levels contributed to children’s greater participation, but the researchers did not look specifically at the impact of sensory processing on children’s participation (Taheri et al., 2017).

An Icelandic study involving 99 children with a diagnosis of ASD and 241 children without a diagnosis of ASD found that decreased participation among children with ASD was related to the social demands of recreational activities and the cognitive and physical environmental demands (Eglison et al., 2017). In addition, Eglison et al. (2017) reported that up to 36.8% of parents of children with ASD suggested that sensory demands from activities were a barrier to participation, compared to 7.8% of parents of TD children. This echoes the findings of the present study and demonstrates that sensory processing impacts the participation of TD children as well as children with various disabilities.

Participation intensity

The present study demonstrated that sensory processing accounted for 45.9% (p = 0.024) of the variance seen in participation intensity, suggesting a causal relationship between TD children’s responses to sensory input and the frequency with which they participate in daily activities. This variance was uniquely contributed to by a child’s response to tactile input (p = 0.030) so that a child who is sensitive to tactile information participates in fewer activities than children who seek tactile input. Other studies looking at factors impacting participation intensity have also found that an activity’s sensory demands can be a barrier to participation (Coster et al., 2013).

A previous study conducted in Israel found that children with ASD and tactile sensitivities had higher participation intensity than their TD peers (Hochhauser and Engel-Yeger, 2010). Children who are tactile sensitive may participate in activities that have low tactile demands at a higher frequency than children who are not tactile sensitive and are happy to participate in many different activities at a lower frequency (Hochhauser and Engel-Yeger, 2010). The study also found that children who were more sensitive to taste and smell input had lower participation frequency (Hochhauser and Engel-Yeger, 2010), which supports the finding in our study that the SPM-Home Touch subscale was the only category that made a statistically significant and unique contribution to the variance seen in participation intensity (see Table 3). The present study looked at typical and atypical sensory responses but did not differentiate between extreme sensory seeking and sensory avoiding responses, which may explain the differences in findings between the two studies.

Participation independence

The present study found that 42.4% (p = 0.034) of the variance of TD children’s participation independence was accounted for by their sensory processing patterns, with body awareness (proprioception) making the most significant contribution (p = 0.038). These results show that participation independence in TD children may be facilitated by their sense of where their body is in space and their ability to use this information to physically coordinate themselves during their participation. Interestingly, a study by Ricon et al. (2017) found similar links between sensory processing and independence, but with unique contributions from tactile, vestibular, visual and auditory processing among children with ASD. This highlights that for children from different population groups, participation independence is significantly impacted by sensory processing.

Children’s participation enjoyment

While the regression models found no statistically significant relationship between sensory processing and children’s enjoyment in their participation (p = 0.190), correlation analysis suggested that body awareness (proprioception) has a statistically significant association with the child enjoyment subscale of the CPQ-School (p = 0.523; p = 0.010). It should be noted that in the regression model, all of the SPM-Home subscale scores were included as independent variables in the regression model, and this may have accounted for the difference between the correlation and regression analysis outcomes. This is supported by findings from other studies in which children with ASD who had probable or definite sensory processing differences were found to have statistically significant lower levels of enjoyment in daily life participation than children who demonstrated typical sensory processing (Ismael et al., 2015). Further, Hochhauser and Engel-Yeger (2010) found that children with ASD who reported increased taste and smell sensitivity had lower reported levels of enjoyment.

Parents’/caregivers’ satisfaction with children’s participation

Although sensory processing did not significantly explain the variance of parental satisfaction with children’s participation observed in the present study, other studies have linked parental satisfaction of their child’s participation in daily activities with other factors such as their child’s ADL, socialisation, communication, process and motor skills (Rosenberg et al., 2010, 2011). No other studies, however, have linked satisfaction to a child’s sensory processing patterns. Williams et al. (2018) found that inclusive community initiatives with opportunities for environmental adaptations were linked to improved parent satisfaction, reporting that the most desire for change in their child’s participation related to home chores, personal care management and getting clean and social involvement with friends (Williams et al., 2018).

Implications for practice

This study has shown that several sensory processing factors are related to a child’s participation in daily activities; specifically, our results demonstrate that sensory processing as measured by the SPM-Home Form impacts the diversity, intensity and independence level of children’s participation (as measured by the CPQ-School). Practice implications from these research findings include the reinforcement of occupational therapists working with children, both with and without disabilities, to facilitate participation in day-to-day life by addressing limitations based on sensory processing challenges and utilising sensory preferences to enhance participation. Addressing suspected sensory processing problems in occupational therapy intervention is essential in achieving goals for children to participate and improve their health and well-being (Ricon et al., 2017).

Limitations

Noted limitations of this study include the small sample size which in turn limits generalisability of the findings. Convenience sampling was also utilised, and this can contribute to respondent and social desirability bias. There was also an uneven split between the genders of the children whose parents/caregivers completed the SPM-Home and CPQ-School. It should also be noted that the SPM-Home was based on a standardisation data from the United States, whereas this study was conducted in Australia.

One notable circumstantial factor about this study was the context and conditions under which it was completed. The onset of the COVID-19 pandemic had a direct impact on participant recruitment efforts as well as the mode of data collection. Due to state government mandated public health regulations, all state and private schools were closed and students were studying remotely from home at the commencement of data collection. Parents/caregivers of children were adapting to considerable domestic changes in needing to supervise their children’s studies at home while concurrently often working remotely from home themselves. This created a stressful and demanding situation for potential parent/caregiver respondents, and therefore, many eligible participants declined to take part in the study due to the additional demands already being placed on them in their parenting/caregiving roles and daily life requirements resulting from the COVID-19 restrictions. The move to online completion of the questionnaire also removed the ability of the researchers to oversee participants’ completion of the scale items. Hence, a number of incomplete questionnaires were received and had to be discarded.

Future research

The results and discussions presented in this study create multiple opportunities for future research. This study did not analyse the impact of sensory processing preferences on the different types of activities measured by the CPQ-School (e.g. ADLs, IADLs, sleep, play, leisure, social participation and education). Further research into the different activities children participate in will improve our understanding of the relationship between sensory processing and participation. The data presented in the present study can be used in future studies comparing the differences in ‘typical’ sensory processing responses and their impact on participation to children with different disabilities, with findings offering further support to occupational therapy interventions.

Given the gender imbalance in the study sample, it is recommended that future studies investigate whether there are differences between boys and girls in relation to sensory process and their activity participation. Further, the relation between sensory processing and participation in children presenting with extreme sensory responses (e.g. seeking and avoiding patterns) could also be examined. Research investigating groups from culturally and linguistically diverse backgrounds or children from various socio-economic backgrounds may highlight important factors that further impact children’s participation.

Conclusion

Researching the impact of sensory processing on children’s participation in different activities contributes to the literature base for evidence-based occupational therapy practice. The results indicated that none of the five CPQ-School participation variables significantly correlated with the SPM-Home social participation or touch factors. The CPQ-School participation independence variable had the largest number of SPM-Home sensory processing factors that were significantly associated with it (e.g. vision, hearing, body awareness (proprioception), balance and motion, planning and ideas and total subscales). The CPQ-School parent satisfaction variable was significantly correlated with the SPM-Home body awareness (proprioception) and balance and motion subscales. The preliminary findings of this study indicated that participation diversity, intensity and independence levels of TD children are impacted by their sensory processing preferences, particularly touch and body awareness (proprioception). Occupational therapists should therefore consider sensory processing factors when working with children to improve areas of their participation in daily activities.

Key findings

Typically developing children’s sensory processing factors significantly impact their participation diversity, intensity and independence.

Touch and body awareness (proprioception) are frequent unique contributors to TD children’s participation diversity, intensity and independence levels.

What the study has added

This study contributes to the occupational therapy evidence base on the significant relationship between TD children’s sensory processing factors and their daily participation diversity, intensity and independence levels.

Footnotes

Acknowledgements

The authors wish to acknowledge the 23 participants who made significant contributions by volunteering to take part in the study. The assistance of Associate Professor Genevieve Pepin in her role as academic supervisor is also acknowledged.

Author Contribution

Hannah RG Sleeman and Ted Brown researched the literature, applied for ethical approval and contributed to the development of the study design. Both authors contributed to the methodology of the project and the statistical analysis plan. Hannah RG Sleeman carried out the statistical analysis. Both authors interpreted the data analysis results and contributed to writing the manuscript as well as reviewing and editing the manuscript and approving the final version.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship and/or publication of this article.

Ethical approval

This study was approved by the Deakin University Human Ethics Advisory Group-Health (HEAG-H) No. 66_2020. Date of receipt of ethics committee approval was 16/07/2020.

Informed consent

All participants provided written informed consent prior to taking part in the study.

ORCID iD

Ted Brown

References

Allen

Casey

(2017) Developmental coordination disorders and sensory processing and integration: incidence, associations and co-morbidities. British Journal of Occupational Therapy 80(9): 549–557.

Ashburner

Ziviani

Rodger

(2008) Sensory processing and classroom emotional, behavioral, and educational outcomes in children with autism spectrum disorder. American Journal of Occupational Therapy 62(5): 564–573.

Chen

Y-H

Rodgers

McConachie

(2009) Restricted and repetitive behaviours, sensory processing and cognitive style in children with autism spectrum disorders. Journal of Autism and Developmental Disorders 39(4): 635–642.

Choi

B-s

(2016) An overview of bootstrapping method applicable to survey researches in Rehabilitation Science. Physical Therapy Korea 23(2): 93–99.

Coster

Law

Bedell

, et al. (2013) School participation, supports and barriers of students with and without disabilities. Child: Care, Health and Development 39(4): 535–543.

Dunn

(2007) Supporting children to participate successfully in everyday life by using sensory processing knowledge. Infants & Young Children 20(2): 84–101.

Eglison

Jakobsdottir

Olafsson

, et al. (2017) Community participation and environment of children with and without autism spectrum disorder: Parent perspectives. Scandinavian Journal of Occupational Therapy 24(3): 187–196.

Eicher

Skubik-Peplaski

O’Brien

, et al. (2018) Exploring parents’ experiences of raising a child with sensorimotor impairments and expectations for leisure participation. The Open Journal of Occupational Therapy 6(4): 1–11.

Fernandez

Ziviani

Cuskelly

, et al. (2018) Participation in community leisure programs: experiences and perspectives of children with developmental difficulties and their parents. Leisure Sciences 40(3): 110–130.

10.

Foitzik

Brown

(2018) Relationship between sensory processing and sleep in typically developing children. American Journal of Occupational Therapy 72(1): 7201195040p1–7201195040p9.

11.

Guichard

Grande

(2019) The role of environment in explaining frequency of participation of pre-school children in home and community activities. International Journal of Developmental Disabilities 65(2): 108–115.

12.

Hertzog

Cermak

Bar-Shalita

(2019) Sensory modulation, physical activity and participation in daily occupations in young children. Canadian Journal of Occupational Therapy 86(2): 106–113.

13.

Hochhauser

Engel-Yeger

(2010) Sensory processing abilities and their relation to participation in leisure activities among children with high-functioning autism spectrum disorder (HFASD). Research in Autism Spectrum Disorders 4: 746–754.

14.

Houghton

Stein

Cortese

(2020) Review: exteroceptive sensory abnormalities in childhood and adolescent anxiety and obsessive-compulsive disorder: A critical review. Journal of the American Academy of Child and Adolescent Psychiatry 59(1): 78–87.

15.

IBM Corp (2019) IBM SPSS Statistics for Windows, Version 26.0. Armonk: IBM Corp.

16.

Ismael

Lawson

LAM

Cox

(2015) The relationship between children's sensory processing patterns and their leisure preferences and participation patterns. Canadian Journal of Occupational Therapy 82(5): 316–324.

17.

Jirikowic

Olson

Kartin

(2008) Sensory processing, school performance, and adaptive behavior of young school-age children with fetal alcohol spectrum disorders. Physical & Occupational Therapy in Pediatrics 28(2): 117–136.

18.

Kojovic

Hadid

Franchini

, et al. (2019) Sensory processing issues and their association with social difficulties in children with autism spectrum disorders. Journal of Clinical Medicine 8(10): 1–16.

19.

Mimouni-Bloch

Offek

Rosenblum

, et al. (2018) Association between sensory modulation and daily activity function of children with attention deficit/hyperactivity disorder and children with typical development. Research in Developmental Disabilities 83(1): 69–76.

20.

Niutanen

Harra

Lano

, et al. (2019) Systematic review of sensory processing in preterm children reveals abnormal sensory modulation, somatosensory processing and sensory‐based motor processing. ACTA Paediatrica 109(1): 45–55.

21.

O’Donnel

Deitz

Kartin

, et al. (2012) Sensory processing, problem behaviour, adaptive behaviour, and cognition in preschool children with autism spectrum disorders. American Journal of Occupational Therapy 66(1): 586–594.

22.

Parham

Ecker

Kuhaneck

, et al. (2007) Sensory Processing Measure: Manual. Los Angeles: Western Psychological Services.

23.

Pfeiffer

Coster

Snethen

, et al. (2017) Caregivers’ perspectives on the sensory environment and participation in daily activities of children with autism spectrum disorder. American Journal of Occupational Therapy 71(4): 1–9.

24.

Ratcliff

Hong

Hilton

(2018) Leisure participation patterns for school age youth with autism spectrum disorders: findings from the 2016 national survey of children’s health. Journal of Autism and Developmental Disorders 48(11): 3783–3793.

25.

Ricon

Sorek

Engel Yeger

(2017) Association between sensory processing by children with high functioning autism spectrum disorder and their daily routines. The Open Journal of Occupational Therapy 5(4): 1–18.

26.

Roberts

Stagnitti

Brown

, et al. (2018) Relationship between sensory processing and pretend play in typically developing children. American Journal of Occupational Therapy 72: 1–8.1

27.

Rosenberg

Bart

(2015) Development and initial validation of the Children Participation Questionnaire-School (CPQ-School). Israeli Journal of Occupational Therapy 24(2–3): 70–87.

28.

Rosenberg

Bart

(2016) Different pathways to children's enjoyment of participation in daily activities. Scandinavian Journal of Occupational Therapy 23(5): 366–373.

29.

Rosenberg

Jarus

Bart

(2010) Development and initial validation of the Children Participation Questionnaire (CPQ). Disability and Rehabilitation 32(20): 1633–1644.

30.

Rosenberg

Jarus

Bart

, et al. (2011) Can personal and environmental factors explain dimensions of child participation?. Child: Care, Health and Development 37(2): 266–275.

31.

Rosenberg

Pade

Reizis

, et al. (2019) Associations between meaning of everyday activities and participation among children. American Journal of Occupational Therapy 73(6): 1–10.

32.

Suarez

(2012) Sensory processing in children with autism spectrum disorders and impact on functioning. Pediatric Clinics of North America 59(1): 203–214.

33.

Taheri

Perry

Minnes

, et al. (2017) Exploring factors that impact activity participation of children and adolescents with severe developmental disabilities. Journal of Intellectual Disability Research. 61(12): 1151–1161.

34.

Williams

Law

Hanna

, et al. (2018) Using the Young Children’s Participation and Environment Measure (YC-PEM) to describe young children’s participation and relationship to disability and complexity. Journal of Developmental and Physical Disabilities 31: 135–148.

35.

World Health Organization (2002) Towards a common language for functioning, disability and health. Available at: https://www.who.int/classifications/icf/icfbeginnersguide.pdf (accessed 29 June 2020).