Challenging behaviors among students with severe developmental disabilities in Saudi Arabia: Impact of socio-demographic differences

Abstract

This study aimed to explore the prevalence of challenging behaviors (CBs) associated with students with severe developmental disabilities (SDDs) as rated by their teachers. The study also attempted to examine whether the occurrence and intensity of CBs might depend on certain socio-demographic variables. Data was collected using a questionnaire to rate the prevalence of CBs in 687 students with SDDs. Results indicate that social problems, stereotypical behaviors, and disobedient behaviors were estimated to be the most prevalent of CBs among such students. Positive correlations were confirmed between the type of disability, gender, age, school grade, educational placement, and the prevalence of CBs among students with SDDs. Implications for educational practice and recommendations for future research are discussed.

Introduction

Previous research has established a consensus that individuals with severe developmental disabilities (SDDs) exhibit an increased rate of challenging behaviors (Esteves et al. 2021; Ruddick et al. 2015; Simó-Pinatella et al. 2019). According to Oliver et al. (2012), about 40% of children and adults with SDDs demonstrate one or more challenging behaviors. Challenging behaviors (CBs) is an umbrella term that refers to unusual conduct shown by individuals with SDDs, including aggression, destructive behaviors, self-injurious behaviors (SIBs), and stereotyped behaviors (SBs) (Emerson 2001). Such conduct in a student with SDDs can severely interfere with their education (Jang et al. 2011; Westling 2015; Westling et al. 2021) by restricting their access to the curriculum or even having them removed from the school (Male 2003; Male and Rayner 2007).

The defining features of SDDs are moderate, severe, or profound intellectual impairment in adaptive behaviors that persist throughout an individual’s life span (Kennedy et al. 2007; Westling et al. 2021), and they refer mostly to autism spectrum disorder (ASD), Down syndrome, and intellectual disability (ID). However, this research focuses on students with ASD, characterized by impairments in social abilities, impairments in communication skills, and unusual repetitive behaviors (Amr et al. 2012; Westling et al. 2021) and students with ID, characterized by limitations in mental abilities and adaptive behaviors (Salvador-Carulla et al., 2011). It also includes students with multiple disabilities (MDs) who have intellectual disabilities and another disability concurrently, such as intellectual disabilities-blindness or intellectual disabilities-orthopedic impairment, etc., that impact their learning (Westling et al. 2021; Epler 2019). Despite findings that students with MDs display behaviors similar to CBs (Poon 2012; Sartawi et al. 2011), they were frequently overlooked in CBs research. Conversely, students with SDDs will be more socially accepted and interact with their typical-developing peers when their behavioral and learning needs are addressed and provide them with meaningful, practical supports (Westling 2015; Westling et al. 2021). They are able to learn appropriate behaviors and skills when evidence-based practices are implemented in their educational programs (Westling 2015; Westling et al. 2021). Thus, addressing the CBs of students with SDDs would be the effective way to not only reduce the CBs but also increase their abilities (Westling et al. 2021).

Challenging behaviors in students with SDDs

Previous studies (Matson and Nebel-Schwalm 2007; McClintock et al. 2003, Richards et al. 2016) have found that subgroups of those with ASD consistently showed increased aggression, SIB, and destruction of property in comparison to other students with different types of disabilities. However, others (Emerson et al. 2014; Simó-Pinatella et al. 2017; Simó-Pinatella et al. 2019) found that the prevalence of CBs as aggression, destruction, and SIB was higher in individuals with ID compared to other disabilities. Further, CBs were positively associated with the degree of ID and increasing with the severity of ID (Holden and Gitlesen 2006; McClintock et al. 2003; Molteno et al. 2001; Rojahn et al. 2008). Aggression was found to be more common among individuals with mild and moderate ID, while SIB and SBs were most common in individuals with profound and severe ID (Holden and Gitlesen 2006; McClintock et al. 2003). Lastly, the prevalence of CBs in students with MDs was also found to be high in some studies (Poon 2012, Poppes et al. 2010, Richards et al. 2016) that reported SIB and SBs occurred in 82% of the samples, while aggressive/destructive behavior was found in 45% of the samples.

Furthermore, previous research has extended the investigation of the prevalence of CBs to include risk factors associated with their occurrence (Murphy et al. 2009). The occurrence of CBs was mostly examined in comparison with certain socio-demographic variables such as age and gender (Koritsas and Iacono 2012), while in this study, the investigation of CBs extends to school grade and educational placement. Considering gender, studies (Emerson et al. 2014; Molteno et al. 2001; Lowe et al. 2007) found males were associated with a higher prevalence of CBs; however, no gender differences were found (Holden and Gitlesen 2006; Poon 2012; Smith et al. 1996). Specifically, aggression was found more prevalent in males (McClintock et al. 2003) while social problems were found more often in females (Morán et al. 2019; Sedgewick et al. 2016). Other studies (Kuo et al. 2013; Shields et al. 2015) attributed this to the different socialization patterns in boys and girls.

Regarding the relationship between age and CBs, studies (Dekker et al. 2002; Emerson et al. 2014; Murphy et al. 2005; Shattuck et al. 2007) found that CBs abates with aging while Murphy et al. (2009) found no significant relationship. Furthermore, Crocker et al. (2006), Koritsas and Iacono (2012), Poon (2012), and Tyrer et al. (2006) reported that aggression and SIB were found more frequently in younger children. Though literature investigating differences in CBs among children in different school grades is limited, Alter et al. (2013) suggested that elementary-school students express physical and verbal aggression more frequently than students in middle and high-school, while middle-school students express aggression more frequently than high-school students.

Lastly, differences in students’ CBs based on their educational placement were also shown in a few studies (Parmenter et al. 1998; Westling 2010). These studies suggest that students attending segregated schools exhibited almost all types of CBs more frequently than students attending integrated schools (Parmenter et al. 1998) and that special education teachers perceive a higher prevalence of CBs in students with SDDs when compared to general education teachers (Westling, 2010). In sum, the literature review suggests that CBs have been rated high among students with SDDs across different contexts. The literature review also indicates there have been some factors (e.g. gender, age, type of disability, school grade, and educational placement) affecting occurrence and intensity of CBs among the students.

In Saudi Arabia, students with disabilities have been receiving special education services since 1960; however, those services were provided only for students with visual and hearing impairments (Aldabas 2015). Beginning in 1971, special education services have been provided for students with intellectual disabilities, including students with ASD, within intellectual education institutes (Aldabas 2015; Alnahdi 2014). At the end of the 1990s, students with disabilities (e.g. visual and hearing impairments, mild to moderate intellectual disabilities, and mild to moderate ASD) have been included in special education classrooms within public schools (Aldabas 2015; Alnahdi 2014). Yet, the category of students with SDDs (i.e. moderate to severe intellectual disabilities, ASD, and students with MD) have been educated in special education schools or intellectual education institutes (Aldabas 2015). The curriculum provided to students with SDDs was mostly concentrated on developing and improving behavioral, social, communication, and daily-life skills (Aldabas 2015; Ministry of Education 2015). Therefore, educational placement and curriculum have been determined for each student individually based on the student’s unique developmental needs, regardless of chronological age (Ministry of Education 2015).

Indeed, the Saudi government commits ongoing efforts in terms of providing free, appropriate education to all individuals with disabilities, regardless of severity of such disabilities, in order to support their independence and inclusion in society (Saudi Vision 2030, n.d.). This raises a need to find facilitators to provide inclusive education to students with SDDs by addressing their behavioral needs in order to socially integrate the individuals. Little knowledge has been obtained about the prevalence of CBs among students with SDDs since there have been approximately 4,075 students with SDDs in Riyadh, Saudi Arabia (Center for Education Statistics 2019). Accordingly, it was essential to investigate the prevalence of CBs among the students to outline existing gaps in the behavioral needs of the students and inclusive education. This would help to support inclusion of the students and provide them with unique educational and behavioral intervention in appropriate settings.

Therefore, the current study aimed towards better understanding the relationship between CBs in students with SDDs (i.e. ASD, moderate to severe ID [MSID], and MDs) attending schools in Riyadh, Saudi Arabia, and the factors that might influence their occurrence. The primary purpose of this study was to investigate the prevalence of the most common CBs associated with students with SDDs, as rated by their teachers, using a newly developed questionnaire that measures five domains of CBs (aggression, SIB, disobedience, social problems, and SBs). Another purpose was to examine the potential influence of gender, age, type of disability, school grade, and educational placement in occurrence and intensity of CBs in students with SDDs. In other words, this study attempted to examine whether occurrence and intensity of CBs might depend on certain socio-demographic variables. This study also tried to add to the previous research on CBs in students with SDDs by including a group of students with MDs, which further allowed direct comparison of their CBs. In addition, it proposed a new, shorter questionnaire for measuring the relevant five domains of CBs. Thus, this study attempted to answer the following research questions:

• What are the most common challenging behaviors associated with SDDs (i.e., ASD, MDs and ID) as rated by their teachers?

• What are the factors which may affect the intensity (rating) of challenging behaviors associated with SDDs?

Method

Research design

A descriptive correlational research design was used to achieve the aims of this study. This method gives descriptive data of the issue under investigation and an examination of the potential influence for related variables (Ary et al. 2010). Specifically, this study used a survey to collect data describing the study sample demographic information, CBs, and investigating the potential influence for demographic information on CBs. This methodological approach allowed researchers to gather data from a larger sample of the study population in order to produce an outcome with generalizable and transferable results (Ary et al. 2010).

Participants and setting

By using an opportunity sampling, special education teachers of 687 students diagnosed with ASD, ID, or MDs attending government or private special education institutes in Riyadh participated and completed the questionnaire. These teachers hold a bachelor's degree in special education with a focus on ID, ASD, or MDs as a minimum requirement to be a teacher of those students (Ministry of Education 2015), and had taught such students for at least one academic year, which were criterions to participate in this study. Riyadh is Saudi Arabia’s capital and the largest city in the country. Approximately 4,075 students diagnosed with ASD, ID or MDs migrated to Riyadh from different areas of the country seeking education and enrolling in private or government special education institutes for children with SDDs (Center for Education Statistics 2019). From the 4,075 students, 687 were assessed, indicating an adequate sample size (Krejcie and Morgan 1970). The special education teachers of these 687 students have taught girls and boys of different ages in different institutes and different grade levels (Table 1).

Table 1.

Sample characteristics (N = 687).

Variable	Category	N	%
Gender	Girls	321	46.7
	Boys	366	53.3
Age	4-7 years old	157	22.9
	8-12 years old	384	55.9
	older than 12 years	146	21.3
Student disability	Moderate to severe ID	327	47.60
	MDs	102	14.85
	ASD	258	37.55
Grade	Pre-school	120	17.47
	Elementary-school	360	52.40
	Middle-school	148	21.54
	High-school	59	8.59
Educational placement	Private institute	286	41.63
	Government institute	401	58.37

Instrument

A newly developed questionnaire for external assessment of CBs in students with SDDs was administered in this study. The questionnaire was developed based on previous literature (e.g. Alter et al. 2013; Oliver et al. 2012; Ruddick et al. 2015) that addressed challenging behaviors associated with SDDs. In the first stage of development, the questionnaire contained 40 items. Then, a face validity assessment was established by consulting six experts (Ary et al. 2010) who were professors of special education at the university. They have expertise on CBs and SDDs. The experts were asked to review the questionnaire to determine if it measured the content under consideration. Based on their suggestions, five items were deleted, and others were revised or reworded with an agreement of 90% before establishing the final questionnaire.

The final questionnaire is a two-part document. The first part collected students’ socio-demographics (gender, age, type of disability, school grade, educational placement; Table 1). The The second part is a 35-item checklist measuring different behavioral, emotional, and social domains of CBs with five subscales: eight items on aggressive and subversive behavior (e.g. damaging property, theft), five on self-injury (e.g. biting/head banging/punching, falling to self-harm), five on disobedient behavior (e.g. lack of remorse, careless/chaotic behavior), eight on social problems (e.g. preference for being alone, lack of respect for others’ feelings), and nine on stereotypical and repetitive behavior (e.g. hand flapping, echolalia). Teachers used a rating scale ranging from 1 – never to 4 – always to assess the prevalence of CBs in the assessed students.

Construct validity of instrument

It was assessed by performing exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The Kaiser-Meyer-Olkin (KMO) and Bartlett sphericity tests were applied to determine the appropriate data for factorial analysis. The values of KMO for the five subscales were 0.884, 0.756, 0.830, 0.887, and 0.882, respectively. The values of Bartlett’s test (Bartlett Chi-square approximation) for the five subscales were 3066.00, 1665.70, 2157.32, 3799.97, and 2760.23, with a statistical significance (p = 0.00), respectively. The values of KMO and Bartlett sphericity suggested that the sample of this study is adequate for performing factor analysis and there is a correlation between the five subscales of the instrument (Field 2013; Kaiser 1974, MacCallum et al. 1999). According to Pituch and Stevens (2016), an absolute value of 0.40 and explained 16% of the variance were used as a criterion for factor loading in EFA. Further, factors with eigenvalues greater than one were retained for determining the optimum number of factors that can be extracted for each subscale of the instrument (Kaiser 1960). Table 2 reveals that five factors had eigenvalues greater than one, according to Kaiser's criterion.

Table 2.

Item loadings in each component, eigenvalues and percentages of variance.

Items	Loading
	Factor 1	Factor 2	Factor 3	Factor 4	Factor 5
Item 1	.829
Item 2	.826
Item 3	.787
Item 4	.782
Item 5	.752
Item 6	.742
Item 7	.728
Item 8	.686
Item 9		.843
Item 10		.826
Item 11		.804
Item 12		.738
Item 13		.670
Item 14			.874
Item 15			.846
Item 16			.844
Item 17			.832
Item 18			.813
Item 19				.849
Item 20				.837
Item 21				.827
Item 22				.815
Item 23				.788
Item 24				.787
Item 25				.758
Item 26				.716
Item 27					.863
Item 28					.859
Item 29					.853
Item 30					.746
Item 31					.754
Item 32					.746
Item 33					.724
Item 34					.696
Item 35					.533
Eigenvalue	4.415	5.095	3.545	3.033	4.716
% of Variance	58.95%	60.67%	70.91%	63.69%	74.29%

Findings of EFA indicate that the first and second subscale (ASBs and SIBs) each had one factor which explained 58.95% and 60.67% of the variation in the first dimension, with factor loadings from 0.686 to 0.829 and 0.670 to 0.843, respectively. The latent root of the first factor was 4.415 and 5.095 for the second factor. Findings also show that there was one factor for the third subscale (DBs) which explained 70.91% of the variation in the third dimension with factor loadings from 0.813 to 0.874. The fourth subscale had one factor (SBs) which explained 63.69% of the variation in the dimension with factor loadings from 0.716 to 0.849. The latent roots for the third and fourth factor were 3.545 and 3.033, respectively. Findings also indicate that the fifth subscale (SRBs) had one factor which explained 74.29% of the variation with factor loadings from 0.533 to 0.863. The latent root of the fifth factor was 4.716. These values clearly indicate that each of the five subscales has a single factor.

Furthermore, CFA was performed to investigate whether each subscale of the second section of the instrument fits the data adequately (Schermelleh-Engel et al. 2003). The absolute fit indices were used to determine how well the model fits the data by conducting the following test statistics: Chi-square (χ 2), root mean square error of approximation (RMSEA), comparative fit index (CFI), and standardized root mean square residual (SRMR). The Chi-square (χ 2) was χ² (545) = 3057.75, p < .001 which indicates the model did not fit the data well because of χ 2 not close to zero (Kline 2015). However, this value is expected as the Chi-square is affected by the sample size (N = 687), whereby a larger sample would produce a higher value, so it is not recommended to depend on it (Kline 2015; Schermelleh-Engel et al. 2003). The values of RMSEA, TLI, CFI, and SRMR (i.e. 0.05, 0.95, 0.95 and 0.08; p < .001, respectively) indicate the model fits the data well (Hu and Bentler 1999; Kline 2015; Schermelleh-Engel et al. 2003). These values of CFA support the EFA findings. Accordingly, the construct validity and reliability of the instrument were confirmed, and the instrument was used in its final established form for analyzing the data.

Reliability of instrument

Pearson’s correlation coefficient was performed for each of the five subscales and the total questionnaire score. Table 3 shows that the correlations between the five subscales and the total score were statistically significant (p < .01), indicating that the questionnaire demonstrates internal consistency. Cronbach’s alpha coefficients for the five subscales ranged from .84 to .92 and 0.93 for the whole questionnaire, indicating a high reliability (Ary et al. 2010).

Table 3.

Means, standard deviations, normality indicators, and correlations of CB measures.

	Descriptive statistics							Correlations
Subscales	Min.	Max.	M	SD	Skew.	Kurt.	α	1	2	3	4	5	6
1 ASB	1	4	2.57	.86	.13	−1.12	.90	–	.52*	.25*	.20*	.09**	.57*
2 SIB	1	4	2.71	.88	−.25	−.86	.84		–	.65*	.52**	.19*	.81*
3  DB	1	4	2.83	.97	−.39	−1.00	.90			–	.72**	.29*	.83*
4 SP	1	4	2.85	.89	−.57	−.67	.92				–	.45*	.81*
5 SRB	1	4	2.85	.76	−.53	−.35	.87					–	.53*
6 Overall CB score	1	4	2.76	.63	−.35	−.43	.93						–

Note. N = 687.

^*p < .01;.

^**p < .05; Min. – minimum possible score; Max. – maximum possible score; M – mean; SD – standard deviation; Skew. – skewness; Kurt. – Kurtosis; α – Cronbach’s internal consistency; ASB - aggressive and subversive behavior; SIB - self-injurious behavior; DB - disobedient behavior; SP - social problems; SRB - stereotypical and repetitive behavior.

Procedures

After obtaining approval from the university and the Education Department of Riyadh to conduct the study, principals/directors of private and government special education institutes where students with SDDs are educated were contacted to schedule meetings with special education teachers. Special education teachers responsible for a total of 1,000 students with SDDs, scattered among 25 private and government special education institutes in Riyadh were recruited and invited to participate in the meetings. During these meetings, the purpose of the study, its importance, and instructions for completing the questionnaire were explained to the teachers. They were also provided with copies of an invitation letter, the Informed Consent form, and the questionnaire and instructions on how to complete and return it. A definition and an example of each item (i.e. challenging behavior) of section two of the questionnaire were provided in order to ensure each challenging behavior was clearly understood. Furthermore, it was explained to all potential participants that participation in the study was completely voluntary and each teacher could complete more than one questionnaire, based on the number of their students with SDDs. Each of the 25 private or government special education institutes held a meeting with a number of 10 special education teachers of students with SDDs and given 40 questionnaires to complete. From the 1000 questionnaires distributed, 687 (68.7%) were completed and returned.

Data analysis

Collected data was analyzed using SPSS, version 24 (IBM). Frequencies and percentages of responses were estimated to investigate the prevalence of the most common CBs in students with SDDs. In order to investigate the differences among students’ socio-demographics (gender, age, type of disability, school grade, educational placement) upon CBs, a series of t-tests for independent samples and one-way MANOVAs was conducted. Scheffe’s test was also utilized as an indicator of post-hoc differences between mean scores.

Results

Students characteristics

Table 1 summarizes the characteristics of the total sample group of students with SDDs for whom special education teachers completed and returned administered questionnaires, with a response rate of 68.7%. Information is included with reference to gender, age, type of disability, school grade, and educational placement of students. Approximately half of the overall sample were boys (53.3%), between 8-12 years of age (55.9%), with moderate to severe intellectual disabilities (47.6%), and who attended elementary school grade (52.4%), mostly in government special education institutions (58.37%).

Teachers’ assessment of CB prevalence in students with SDDs

Table 4 summarizes teachers’ prevalence ratings of different domains of five types of CBs: aggressive and subversive behaviors (ASBs), self-injurious behaviors (SIBs), disobedient behaviors (DBs), social problems (SPs), and stereotypical and repetitive behaviors (SRBs). The preliminary results revealed that the prevalence of SPs (M = 2.85, SD = .89) and SRB (M = 2.85, SD = .76) was estimated to be highest among students with SDDs, while ASB (M = 2.57, SD = .86) was assessed with the lowest prevalence ratings.

Table 4.

Frequency, mean, and standard deviations of prevalence of challenging behaviors (N = 687).

		Frequencies (percentages)
		1 Never	2 Rarely	3 Sometimes	4 Always	M	SD
Aggressive and Subversive Behaviors (ASBs)
1	Damaging the property of others (e.g. destroying books).	154 (22.4)	238 (34.6)	123 (17.9)	172 (25)	2.46	1.09
2	Theft of others' property.	168 (24.5)	206 (30)	148 (21.5)	165 (24)	2.45	1.10
3	Physically assaulting others (e.g. spitting).	174 (25.3)	205 (29.8)	137 (19.9)	171 (24.9)	2.44	1.12
4	Verbally assaulting others.	122 (17.8)	166 (24.2)	194 (28.2)	205 (29.8)	2.70	1.08
5	Threatening others.	128 (18.6)	214 (31.1)	121 (17.6)	224 (32.6)	2.64	1.12
6	Performing sudden tantrums on others.	155 (22.6)	209 (30.4)	99 (14.4)	224 (32.6)	2.57	1.16
7	Damaging of personal property (e.g. books).	147 (21.4)	192 (27.9)	118 (17.2)	230 (33.5)	2.63	1.15
8	Screaming.	155 (22.6)	153 (22.3)	124 (18)	255 (37.1)	2.70	1.19
	Total					2.57	.86
Self-injury behaviors (SIBs)
9	Self-harming physically (e.g. biting or head-banging).	102 (14.8)	236 (34.4)	112 (16.3)	237 (34.4)	2.70	1.09
10	Self-harming physically by using objects (e.g. scratching/cutting).	126 (18.3)	219 (31.9)	116 (16.9)	226 (32.9)	2.64	1.12
11	Inserting objects into the mouth.	132 (19.2)	237 (34.5)	96 (14)	222 (32.3)	2.59	1.13
12	Trichotillomania.	133 (19.4)	138 (20.1)	138 (20.1)	278 (40.5)	2.82	1.16
13	Falling down for self-harming physically.	133 (19.4)	147 (21.4)	130 (18.9)	277 (40.3)	2.80	1.16
	Total					2.71	.88
Disobedient behaviors (DBs)
14	Resistance to following school instructions.	135 (19.7)	142 (20.7)	145 (21.1)	265 (38.6)	2.79	1.16
15	Lack of remorse or guilt after behaving inappropriately.	152 (22.1)	144 (21)	140 (20.4)	251 (36.5)	2.71	1.17
16	Careless and chaotic behavior.	127 (18.5)	139 (20.2)	144 (21)	277 (40.3)	2.83	1.15
17	Cruelty in dealing.	118 (17.2)	126 (18.3)	149 (21.7)	294 (42.8)	2.90	1.14
18	Escape (e.g. refusing to complete tasks).	116 (16.9)	126 (18.3)	160 (23.3)	285 (41.5)	2.89	1.12
	Total					2.82	.97
Social problems (SPs)
19	Dependence on others.	119 (17.3)	139 (20.2)	147 (21.4)	282 (41)	2.86	1.14
20	Preference to being alone.	125 (18.2)	127 (18.5)	160 (23.3)	275 (40)	2.85	1.14
21	Lack of sharing feelings with others.	104 (15.1)	132 (19.2)	184 (26.8)	267 (38.9)	2.89	1.08
22	Feeling jealous of others quickly.	113 (16.4)	144 (21)	190 (27.7)	240 (34.9)	2.81	1.09
23	Preference to being and sharing with younger ones.	116 (16.9)	129 (18.8)	184 (26.8)	258 (37.6)	2.85	1.10
24	Lack of respect for the feelings of others.	120 (17.5)	127 (18.5)	145 (21.1)	295 (42.9)	2.90	1.14
25	Behaving strangely to get the attention of others.	107 (15.6)	137 (19.9)	190 (27.7)	253 (36.8)	2.86	1.08
26	Lying and deceitful behavior.	139 (20.2)	140 (20.4)	164 (23.9)	244 (35.5)	2.75	1.14
	Total					2.85	.89
Stereotypical and Repetitive Behaviors (SRBs)
27	Rocking or swinging the body.	123 (17.9)	158 (23)	176 (25.6)	230 (33.5)	2.75	1.10
28	Rotation around him/herself.	141 (20.5)	138 (20.1)	159 (23.1)	249 (36.2)	2.75	1.15
29	Hand flapping.	120 (17.5)	133 (19.4)	209 (30.4)	225 (32.8)	2.78	1.08
30	Head rocking	113 (16.4)	134 (19.5)	176 (25.6)	264 (38.4)	2.86	1.10
31	Interlocking hands or fingers.	100 (14.6)	132 (19.2)	212 (30.9)	243 (35.4)	2.87	1.05
32	Flapping objects.	87 (12.7)	136 (19.8)	185 (26.9)	279 (40.6)	2.95	1.05
33	Thumb sucking.	120 (17.5)	144 (21)	158 (23)	265 (38.6)	2.83	1.13
34	Humming noises.	90 (13.1)	155 (22.6)	166 (24.2)	276 (40.2)	2.91	1.07
35	Echolalia.	87 (12.7)	143 (20.8)	202 (29.4)	255 (37.1)	2.91	1.04
	Total					2.85	.76
	Overall CBs score					2.76	.63

Note. M = mean; SD = standard deviation.

When it comes to the prevalence of ASB, as the teachers reported, approximately one-third of students with SDDs always exhibited behaviors such as screaming (37.1%; M = 2.70, SD = 1.19), and verbally assaulting others (29.8%; M = 2.70, SD = 1.08). On the other hand, close to one-fourth of students with SDDs never physically assaulted others (25.3%; M = 2.44, SD = 1.12) and never stole from others (24.5%; M = 2.45, SD = 1.10).

Teachers assessed the highest prevalence of trichotillomania (40.5%; M = 2.82, SD = 1.16) and falling down (40.3%; M = 2.80, SD = 1.16) among other SIBs, while at the same time, these same behaviors had never occurred in approximately one-fifth of assessed students (19.4%). The prevalence of other estimated SIB, such as inserting objects into the mouth (32.3%; M = 2.59, SD = 1.13) and self-harming physically by using objects (32.9%; M = 2.64, SD = 1.12) was assessed as rarely occurring.

When assessing DBs in students with SDDs, in approximately two-fifths of the sample, teachers reported cruelty in dealing with others (42.8%; M = 2.90, SD = 1.14), refusal to complete tasks (41.5%; M = 2.89, SD = 1.12), and careless and chaotic behaviors (40.3%; M = 2.83, SD = 1.15) as always occurring and as the most prevalent CB. In more than one-fifth of the sample, lack of remorse or guilt after misconduct (22.1%; M = 2.71, SD = 1.17) was the least prevalent DBs, which never occurred, followed by resistance to following school regulations (19.7%; M = 2.79, SD = 1.16).

In regards to the assessed prevalence of SPs, in approximately two-fifths of students with SDDs, their teachers reported as most prevalent and always occurring: lack of respect for the feelings of others, dependence on others, and preference for being alone (ranging between 40 to 42.9%; M = 2.85 to 2.90, SD = 1.14). Among the evaluated SPs, lying and deceiving behavior (20.2%; M = 2.75, SD = 1.15) was assessed as least prevalent, whereas in about one-fifth of students, these behaviors had never occurred.

Lastly, among SRBs, flapping objects, humming noises, and thumb sucking were evaluated as always occurring and most prevalent in approximately two-fifths of assessed students with a mean ranging from 2.95 to 2.83 and 40.6 to 38.6%. The least prevalent SRBs, which never occurred in about one fifth of students, was rotation around themselves (20.5%; M = 2.75, SD = 1.15).

Associated factors with CBs in students with SDDs

Table 3 indicates the values of skewness (±2) and kurtosis (±7) were close to normal distribution of calculated mean scores (Kim 2013). Thus, mean scores for each of the original domains of CBs were compared on socio-demographic variables using a series of t-tests for independent samples, one-way MANOVAs, and Scheffe’s test to investigate differences among mean scores.

Gender differences

The findings in Table 5 revealed significant differences between boys and girls in their DBs [t(685) = 1.96, p < .05] and SPs [t(685) = 2.32, p < .05] mean scores. In both of these measures of CBs, girls achieved higher mean scores than boys (M_girls = 2.90, SD = .96 vs. M_boys = 2.76, SD = .97 and M_girls = 2.93 SD = .86 vs. M_boys = 2.77, SD = .91, respectively).

Table 5.

Gender differences in the prevalence of CBs.

Challenging behaviors	Gender	N	M	SD	df	t	p	95% CI
Aggressive and subversive behavior	Girls	321	2.60	.86	685	.86	.39	[−.07, .18]
	Boys	366	2.55	.87
Self-injurious behavior	Girls	321	2.77	.88	685	1.74	.08	[−.01, .24]
	Boys	366	2.66	.88
Disobedient behavior	Girls	321	2.90	.96	685	1.96*	.05	[.00, .29]
	Boys	366	2.76	.97
Social problems	Girls	321	2.93	.86	685	2.32*	.02	[.02, .29]
	Boys	366	2.77	.91
Stereotypical and repetitive behavior	Girls	321	2.83	.75	685	−.51	.61	[−.14, .08]
	Boys	366	2.86	.76
Overall CB score	Girls	321	2.81	.60	685	1.86	.06	[−.00, .18]
	Boys	366	2.72	.65

Note. N  =  687.

^*p < .01, M – mean, SD – standard deviation, df – degrees of freedom, t – t-statistic, 95% CI - Confidence Interval of the Difference.

Further, the independent sample t-test was conducted to investigate whether there was a significant difference between boys and girls in each school grade (i.e. pre-school, elementary, meddle, and high-school). Table 6 indicates a significant difference between boys and girls, but only in elementary-school grades. The statistical difference was observed in mean scores on SIBs (t [358] = −2.23, p < .01), DBs (t [358] = −2.53, p < .01), SPs (t [358] = −3.08, p < .01) and SRBs (t [358] = −2.37, p < .010). The girls who enrolled in elementary-school grades were rated higher on SIBs (M = 2.82, SD = .86), DBs (M = 2.99, SD = 93), SPs (M = 3.07, SD = .83) and SRBs (M = 2.97, SD = .76) than boys (i.e. M = 2.63, SD = .83; M = 2.73, SD = 1.00; M = 2.78, SD = .92 and M = 2.77, SD = .87, respectively).

Table 6.

Gender differences in the prevalence of CBs across school grades.

School grade	Challenging behaviours	Gender	N	M	SD	df	t		p	95% CI
Pre-school	ASBs.	Boys	41	2.49	0.99	118.00	−.230		0.82	[−0.39, 0.31]
		Girls	79	2.53	0.88
	SIBs.	Boys	41	2.80	0.94	118.00		0.60	0.55	[−0.24, 0.46]
		Girls	79	2.69	0.91
	DBs.	Boys	41	2.91	0.82	118.00	0.74		0.46	[−0.23, 0.51]
		Girls	79	2.77	1.04
	SPs.	Boys	41	2.85	0.78	118.00	1.30		0.20	[−0.11, 0.55]
		Girls	79	2.63	0.91
	SRBs.	Boys	41	2.79	0.72	118.00	1.55		0.13	[−0.07, 0.55]
		Girls	79	2.55	0.85
Elementary-school	ASBs.	Boys	185	2.54	0.84	358.00	−0.41		0.69	[−0.22, 0.14]
		Girls	175	2.57	0.89
	SIBs.	Boys	185	2.63	0.83	358.00	−2.23*		0.03	[−0.37, −0.02]
		Girls	175	2.82	0.86
	DBs.	Boys	185	2.74	1.00	358.00	−2.53*		0.01	[−0.46, −0.06]
		Girls	175	2.99	0.93
	SPs.	Boys	185	2.78	0.92	358.00	−3.08*		0.00	[−0.47, −0.10]
		Girls	175	3.07	0.83
	SRBs.	Boys	185	2.77	0.87	358.00	−2.37*		0.02	[−0.37, −0.04]
		Girls	175	2.97	0.76
Meddle-school	ASBs.	Boys	95	2.49	0.89	146.00	−1.06		0.29	[−0.42, 0.13]
		Girls	53	2.64	0.67
	SIBs.	Boys	95	2.56	0.87	146.00	−1.04		0.30	[−0.46, 0.14]
		Girls	53	2.71	0.91
	DBs.	Boys	95	2.66	0.94	146.00	−1.10		0.27	[−0.50, 0.14]
		Girls	53	2.84	0.97
	SPs.	Boys	95	2.66	0.93	146.00	−1.85		0.07	[−0.58, 0.02]
		Girls	53	2.94	0.80
	SRBs.	Boys	95	2.73	0.85	146.00	−1.59		0.12	[−0.50, 0.05]
		Girls	53	2.95	0.77
High-school.	ASBs.	Boys	45	2.75	0.81	57.00	−1.99		0.05	[−0.98, 0.00]
		Girls	14	3.24	0.77
	SIBs.	Boys	45	2.88	1.03	57.00	0.01		0.99	[−0.61, 0.62]
		Girls	14	2.87	0.91
	DBs.	Boys	45	2.91	1.02	57.00	0.61		0.55	[−0.42, 0.78]
		Girls	14	2.73	0.84
	SPs.	Boys	45	2.92	0.90	57.00	0.17		0.87	[−0.48, 0.57]
		Girls	14	2.88	0.70
	SRBs.	Boys	45	2.88	0.85	57.00	0.14		0.89	[−0.46, 0.53]
		Girls	14	2.85	0.67

Note. N = 687.

^*p < .01, M – mean, SD – standard deviation, df – degrees of freedom, t – t-statistic, 95% CI - Confidence Interval of the Difference, ASBs-Aggressive and Subversive Behaviours, SIBs-Self-injury Behaviours, DBs-Disobedient Behaviours, SPs-Social Problems, SRBs-Stereotypical and Repetitive Behaviours.

Age differences

By observing Table 7, the results of a one-way MANOVA suggested significant differences in the prevalence of several CBs, F (5, 680) = 3.66, p < .001; Wilk's Λ = .95, partial η² = .03. The Scheffe’s post-hoc tests indicated difference between students aged 8-12 years (M = 2.93, SD = .87) and students aged 4-7 years (M = 2.73, SD = .84) in mean score of SPs prevalence, where older students achieved higher means scores than younger ones (p=.016). Another difference between the same groups of students was indicated by the Scheffe’s post-hoc tests in the prevalence of SRBs, where older students, aged between 8-12 years (M = 2.95, SD = .69) achieved higher mean scores than younger students, aged between 4-7 years (M = 2.61, SD = .80), (p=.001).

Table 7.

F-tests and mean differences in the prevalence of CBs between students of different ages.

				Means and standard deviations
Challenging behaviors	F	Df	Partial η2	(1) 4 to 7-year olds (n = 157)	(2) 8 to 12-year olds (n = 354)	(3) older than 12 years (n = 146)
Aggressive behavior	.96	2, 684	.03	2.63 (.91)	2.53 (.84)	2.61 (.86)
Self-injurious	1.32	2, 684	.00	2.76 (.86)	2.73 (.87)	2.61 (.92)
Disobedient behavior	1.94	2, 684	.00	2.71 (1.00)	2.88 (.94)	2.77 (.99)
Social problems	4.48**	2, 684	.01	2.732 (.84)	2.931 (.87)	2.73 (.94)
Stereotypical behavior	11.39*	2, 684	.03	2.612 (.80)	2.951 (.69)	2.81 (.81)
Overall CB score	2.51	2, 684	.00	2.69 (.62)	2.81 (.61)	2.71 (.68)

Note. N = 687.

^*p < .01.

^**p < .05. Superscripts represent significant Scheffe’s post-hoc comparisons between mean scores.¹4 to 7-year olds²8 to 12-year olds

Type of disability

The one-way MANOVA indicated significant differences among students with SDDs (i.e. MSID, ASD and MD); F (5, 680) = 3.30, p < .001; Wilk's Λ = .95, partial η² = .02, while further Scheffe post-hoc comparisons indicated a significant difference in the prevalence of SPs, where students with MSID (M = 2.93, SD = .81) achieved higher mean scores than students with MDs (M = 2.69, SD = .88), (p=.011); see Table 8.

Table 8.

F-tests and mean differences in the prevalence of CBs between students with different types of disability.

				Means and standard deviations
Challenging behaviors	F	df	Partial η2	(1) ID (n = 327)	(2) MD (n = 102)	(3) ASD (n = 258)
Aggressive behavior	.97	2, 684	.00	2.56 (.87)	2.68 (.81)	2.54 (.87)
Self-injurious	.06	2, 684	.00	2.70 (.84)	2.73 (.88)	2.71 (.92)
Disobedient behavior	2.86	2, 684	.01	2.80 (.97)	2.65 (.89)	2.92 (.97)
Social problems	3.75**	2, 684	.01	2.932 (.81)	2.691 (.88)	2.79 (.96)
Stereotypical behavior	2.72	2, 684	.01	2.90 (.77)	2.72 (.84)	2.81 (.69)
Overall CB score	.74	2, 684	.00	2.78 (.60)	2.69 (.61)	2.76 (.66)

Note. N = 687. ¹students with moderate to severe intellectual disability.²students with multiple disabilities.

^**p < .05. Superscripts represent significant Scheffe’s post-hoc comparisons between mean scores. ID = moderate to severe intellectual disability; MD = multiple disabilities; ASD = autism spectrum disorder.

School grade

The results of one-way MANOVA in Table 9 showed a significant difference among students in different school grades (i.e. pre-school, elementary, middle and high-school), F (5, 679) = 1.80, p < .05; Wilk's Λ = .96, partial η² = .01. Scheffe’s post-hoc tests revealed a significant difference between students in middle-school grades (M = 2.92, SD = .72) and students in pre-school grades (M = 2.67, SD = .74), where older students were assessed with higher mean scores on an SRB subscale (p = .006).

Table 9.

F-tests and mean differences in the prevalence of CBs between students in different school grades.

				Means and standard deviations
				(1) Pre-school	(2) Elementay-school	(3) Middle- school	(4) High- school
Challenging behaviors	F	df	Partial η2	(n = 120)	(n = 360)	(n = 148)	(n = 59)
Aggressive behavior	2.57**	3, 683	.01	2.52 (.91)	2.56 (.87)	2.55 (.81)	2.87 (.82)
Self-injurious	1.33	3, 683	.00	2.73 (.91)	2.72 (.85)	2.61 (.88)	2.87 (.99)
Disobedient behavior	.76	3, 683	.00	2.82 (.97)	2.86 (.97)	2.72 (.95)	2.87 (.98)
Social problems	2.36	3, 683	.01	2.71 (.87)	2.92 (.89)	2.76 (.89)	2.91 (.85)
Stereotypical behavior	2.76*	3, 683	.04	2.673 (.74)	2.88 (.75)	2.921 (.72)	2.83 (.85)
Overall CB score	1.60	3, 683	.00	2.69 (.63)	2.79 (.62)	2.71 (.62)	2.87 (.69)

Note. N = 687.¹ Pre-school. ² Elementary school.³Middle school.

^*p < .01.

^**p < .05. Superscripts represent significant Scheffe’s post-hoc comparisons between mean scores. ID = intellectual disability; MD = multiple disabilities; ASD = autism spectrum disorder.

Educational placement

Finally, the results of series of t-tests revealed a significant difference in mean scores on ASB subscale only between students enrolled in private and government special education institutions, t(685) = −2.96, p < .01 (Table 10). It was observed that teachers assessed students from government institutions (M = 2.65, SD = .89) with higher ASB prevalence scores than did teachers who assessed students from private institutions (M = 2.46, SD = .82).

Table 10.

Differences in the prevalence of CBs based on educational placement.

Challenging behaviors		Educational placement	N	M	SD	df	t	p 95% CI
Aggressive and subversive behavior	Private	286	2.46	.82	685	–2.96*	.00	[−.32, −.06]
	Government	401	2.65	.89
Self-injurious behavior	Private	286	2.66	.85	685	−1.22	.22	[−.21, .05]
	Government	401	2.75	.90
Disobedient behavior	Private	286	2.86	.97	685	.74	.46	[-.09, .20]
	Government	401	2.80	.97
Social problems	Private	286	2.84	.92	685	–.26	.79	[-.15, .11]
	Government	401	2.85	.87
Stereotypical and repetitive behavior	Private	286	2.83	.68	685	–.37	.72	[-.13, .09]
	Government	401	2.86	.81
Overall CB score	Private	286	2.73	.61	685	−1.07	.28	[-.14, .04]
	Government	401	2.78	.64

Note. N = 687. M – mean, SD – standard deviation, df – degrees of freedom, t – t-statistic, 95% CI – Confidence Interval of the Difference.*p < .01.

Discussion

The main goal of the present study was to enhance understanding of different types of challenging behaviors among students with SDDs by providing both the prevalence rates of five types of challenging behaviors and the socio-demographic differences from a large sample of students from Saudi Arabia. To the researcher’s knowledge, this is the first study in Saudi Arabia that addressed the question of CBs prevalent in students with SDDs and their specific characteristics. The findings suggested that social problems, stereotypical and repetitive behaviors, and disobedient behavior were estimated as the highest prevalent CBs in students with SDDs, where more than half of students exhibited these behaviors sometimes or always, as reported by their teachers.

This study provided new insights about the relationship between students’ socio-demographic features and their prevalence of CBs within an educational context. Although the effect sizes were small, the statistical significances indicated a slightly positive correlation. Therefore, the students’ socio-demographics might be considered as influences on the prevalence of CBs among them. The results revealed that, when compared to boys, girls with SDDs tended to express social problems and disobedient behavior more frequently. Also, students aged 8-12 years were assessed with higher prevalence ratings of social problems and stereotypical and repetitive behaviors than students aged 4-7 years.

Teachers evaluated students in middle-school with higher prevalence ratings of stereotypical and repetitive behaviors than students in pre-school grades. It was also found that students with different types of disabilities had significantly different prevalence ratings of only social problems, where students with ID showed higher prevalence of social problems than students with MDs, while students with ASD did not show higher prevalence of any type of behaviors when compared to students with ID and MDs. Lastly, different prevalence ratings were found of aggressive and subversive behavior between students from government or private special education institutions, where students from government-held institutions were assessed with a higher prevalence of these behaviors than students from private institutions.

In the present study, girls obtained higher scores in social problems and disobedient behavior in comparison to boys, which might be explained by different types of socialization and roles by gender (Morán et al. 2019). For instance, boys appear to get involved in activities with low demands for communication (Morán et al. 2019; Shields et al. 2015), while girls’ socialization consists of having conversations with peers (Morán et al. 2019; Kuo et al. 2013). Thus, girls with SDDs could be confronted by distinct social challenges and difficulties (Sedgewick et al. 2016), which could result in further discouragement, frustration, and restriction of their social inclusion (Morán et al. 2019). However, this finding is inconsistent with previous findings (Emerson et al. 2014; Molteno et al. 2001; Lowe et al. 2007) which indicated boys were rated with a higher prevalence of CBs, whereas in other studies (Holden and Gitlesen 2006; Poon 2012; Smith et al. 1996) no gender differences were indicated.

Current findings also suggest that girls in elementary school-grades were observed to have a higher prevalence of CBs (self-injury, social problems, disobedient, stereotypical, and repetitive behaviors) compared to boys and other school grades. This is an important finding in the understanding of the effect of gender, culture, and transition from one school level to another in CBs. Culturally, some families could be afraid of stigma, especially in diagnosis stage for girls resulting in against the girls with SDDs from receiving early intervention services and heightened CBs in elementary-school girls compared to boys.

Further, because of differences between school grades in curricula and skills, in addition to the differences of development needs between boys and girls, SDDs may cause more difficulties for girls than boys. For example, girls in pre-school might be taught basic skills, while in elementary-school, the curricula is more focused on specific skills (e.g. daily-life skills), which could be a critical transition from early childhood to childhood for girls more than boys. Therefore, after successfully completing elementary-school grades, girls would obtain more appropriate behaviors and skills which shows assessments lower in CBs than boys in grades higher than elementary. This could be an explanation for girls in elementary-school grades being assessed higher in CBs.

In addition to girls, higher prevalence of social problems was assessed in students between 8-12 years of age in comparison to younger students, and in students with MSID when compared to students with ASD and MDs, which is in compliance with previous studies (Dekker et al. 2002; Smith et al. 1996; Simó-Pinatella et al. 2017). This indicates the level of ID’s influence in CBs. Therefore, students with MSID exhibited a high prevalence of CBs due to their low IQ scores and limitations in social and adaptive behaviors (Balboni et al. 2020; Jones et al. 2008; Westling et al. 2021).

Research on the social skills and acceptance of children with SDDs reported that children with SDDs, especially those with MSID, exhibit social skills deficits and are at risk of lower social status among their peers compared to those with ASD and MDs (Jacobs et al. 2002, Simó-Pinatella et al. 2017). According to Jacobs et al. (2002), social problem solving is highly important in children with ID because it is essential for exhibition of appropriate social behavior that leads to acceptance among peers. A social-cognitive perspective could be used to explain the higher prevalence of social problems in students with ID (Leffert et al. 2000). According to Leffert et al. (2000), two social perception processes of encoding and interpretation might be challenging for children with ID. This is also consistent with previous research indicating that severe ID is associated with a higher rate of CBs, especially in social problems (Balboni et al. 2020; Jones et al. 2008). Thus, it can be explained that a lower level of mental, motor, social, and adaptive abilities characterized in MSID is related to occurrence at a higher level of CBs in those students compared to others (Balboni et al. 2020; Makhluf et al. 2020; Westling et al. 2021).

In order to make plausible social inferences, students must coordinate and integrate information from different, often conflicting, social cues. Since students with MSID have certain deficits in their cognitive processing abilities, they might interpret the same social situation in different ways on different occasions, leading to inappropriate social responses (Balboni et al. 2020; Westling et al. 2021). Strategy generation, as the second key social-cognitive process, could also be challenging for students with ID because it requires the ability to think of different solutions for resolving social problems that fit the immediate situation (Leffert et al. 2000; Westling et al. 2021). Therefore, social perception skills and strategy generation skills are critical to the students’ capacity to respond appropriately to the dynamic social environment of the educational context (Leffert et al. 2000).

The findings that middle-school students between 8 and 10 years of age showed a higher prevalence of stereotypical behaviors than younger students are not in compliance with previous studies (e.g. Alter et al. 2013). Yet, a plausible explanation for these results might be found in behavioral perspective or in different types of reinforcement. Some authors showed that stereotypical behavior could be maintained by sensory reinforcement (Tang et al. 2006), as frequent occurrences of these behaviors in students who are left alone in a classroom would suggest that sensory reinforcement influences their occurrence. However, students might exhibit high rates of stereotypy to escape demands (Tang et al. 2006), as stereotypical behavior might serve as socially mediated positive reinforcement, as reported by Bihm et al. (1992), who found that social attentions were related to the occurrence of stereotypy. However, one must not forget that no conclusions apply to all individuals who exhibit stereotypical behaviors.

Finally, finding of a higher prevalence in aggressive and subversive behavior among students with SDDs enrolled in government special education institutions may indicate environmental factors and curricular influences in CBs levels. This could be explained by the differences in classroom constructs including curricular, instructional methods, classroom management, and number of students between government and private institutions. For example, a classroom construct not meeting the needs of students could be a role influence in challenging behaviors (Guardino and Fullerton 2010). This suggests that classrooms in private institutions were constructed in term of the needs of such students. Another explanation of this finding could be for the differences in curriculum provided in government to private institutions. The curriculum was focused on improving the students with SDDs’ behavioral and social abilities in government institutions (Aldabas 2015); however, the curriculum in the private institutions could move beyond that to focus more in developing appropriate behaviors and modification of inappropriate behaviors.

Limitations and future directions

This study has some limitations which should be addressed. First, the questionnaire used was distributed only to teachers who teach in Riyadh, Saudi Arabia. This could significantly lower the generalizability of the obtained results from teachers from other cities and countries. The sample size does not relatively represent students’ socio-demographics, even though it gave significant findings resulting in reducing the effect sizes of the differences and limiting the results’ generalizability. Therefore, future research should expand the recruitment of students to other cultural contexts and to those with different forms of SDDs in Saudi Arabia.

Second, the questionnaire used was developed only for the purpose of this study, and certain indicators of validity were omitted. However, since the questionnaire’s items resembled those used in more standardized and validated measures of CBs, some comparisons could be possible. Nonetheless, it should be noted that the statistical analyses in this study were conducted on the assumption that the factor structure of the newly developed questionnaire holds for the research purposes. Future research might provide a more detailed understanding of CBs in students with SDDs by attempting to examine the factor structure as used with other sample populations of students with SDDs.

Third, no control group of students, without any diagnosed type of SDDs, was enrolled in this study, which should be taken into consideration in future research. By including a control group of healthy students, without any diagnosed SDDs, a more direct comparison of CB prevalence ratings with students with SDDs would be possible. Lastly, the data was collected from school teachers, and they were mostly limited by their knowledge of particular students’ behavior outside classrooms. In addition, no inter-rater reliability tests on ratings of CBs were carried out, which might be overcome in future research. By obtaining data about CBs from different sources (parents, peers, self-reports), a more precise understanding of CB perception could be established, and the results could be used for planning classroom interventions.

Conclusion

A substantial number of studies clearly showed the higher prevalence of different types of CBs in children with SDDs. This study provided new insights about the prevalence of CBs in students with SDDs from a different cultural context than most studies have reported. Social problems, stereotypical behaviors, and disobedient behaviors were showed as the most prevalent of all measured CBs. Yet, as in previously conducted studies, mixed findings were uncovered, some of which were not in compliance with research literature. For example, previous studies found a clear distinction of students with ASD in terms of a higher prevalence of CBs (aggression, stereotypical behavior, self-injury), which was not confirmed in this study. Another example considers the prevalence of stereotypical behavior, which, according to the previous literature, should abate over time and age. This study did not find any confirmation for these findings. However, this study did emphasize the importance of one, frequently overseen, type of CBs, which concerned the prevalence of social problems in students with SDDs. Since a higher prevalence of social problems was found in different socio-demographic groups (in girls, students in middle-school, aged 8-12 years, with diagnosed ID), future research might focus on examining different types of social deficits in order to help teachers develop more structured and appropriate curricula when teaching their students necessary social skills. This could be particularly beneficial for students with ID, since previous literature has suggested a higher prevalence of problems in this population of students.