Application of the positive and negative affect scale in Chinese children with intellectual disability

Abstract

The purpose is to test the applicability of the Positive and Negative Affect Scale (PANAS) to Chinese children with intellectual disabilities. The study was done by distributing the questionnaire to the parents through teachers online. Asked the parents to fill out the scale based on their observations of their children's daily life. The correlation coefficients between each item and the total score of the corresponding dimension ranged from 0.52 to 0.77. Factor analysis confirmed the establishment of the PA-NA two-factor structure of affect. A significant positive correlation existed between the NA and the challenging behavior. The Cronbach's α coefficient and split-half reliability of the PA scale were 0.87 and 0.85, and the Cronbach's α coefficient and split-half reliability of the NA scale were 0.85 and 0.83, respectively, higher than 0.80. It was concluded that PANAS has good applicability in Chinese children with intellectual disabilities.

Keywords

children with intellectual disabilities negative emotions Positive and Negative Affect Scale positive emotions reliability and validity tests

Background

Being an essential part of individual psychological activities, affect varies according to daily life experiences (Xiong, 2016) and are crucial for survival and reproduction (Darwin, 2004). Increasing emotional awareness positively impacts children's social relationships and mental health (Katz et al., 2012; Lambie and Lindberg, 2016). Maintaining a healthy affect is fundamental for a beneficial standard of living. Therefore, affect measurement has long been a central component of emotion research (Diener, 1999; Mauss and Robinson, 2009).

Due to the complex and diverse nature of emotions dividing emotional dimensions is controversial. Several major lines of research on affective structure indicate the presence of two major bipolar dimensions (Green & Cliff, 1975; Russell, 1980, 1983; Averill, 1975). In these studies Pleasantness-Unpleasantness (terms such as happy, enthusiastic, content vs. afraid, upset, sad) and degree of Arousal or Activation (excited, astonished, tense vs. relaxed, sleepy) have consistently, although not invariably (Purcell, 1982), emerged as the two major dimensions of mood. Some investigators, in addition, extracted a third dimension that has been variously called Potency, Dominance, Aggression, or Attention-Rejection (Russell & Mehrabian, 1977). After that, Watson, Tellegen, and colleagues found that emotions were best expressed as two broad, separable factors known as positive affect (PA) and negative affect (NA) (Watson and Clark, 1984; Watson and Tellegen, 1985; Zevon and Tellegen, 1982). The academic community has widely recognized this two-dimensional model. While PA reflects pleasant engagement with the environment (e.g., being interested, strong, active), NA is a broad general factor of emotional distress that includes moods like being nervous, miserable, or upset.

Among typically developing children, negative affect, such as anxiety and depression, can affect parent–child and peer relationships and emotional experiences and reduce happiness (Fan et al., 2013), thereby inducing psychological disorders and increasing suicidal tendencies (Colder and Stice, 1998). The accumulation of negative affect may eventually lead to emotional and physical feelings and behavioral and cognitive disorders. Based on the organizational function of affect, the negative affect will interfere with and inhibit thinking processing (Meng, 1988), thereby interfering with, disintegrating or blocking some psychological activities. If individuals cannot effectively adjust, control and resolve negative emotions, they easily fall into anxiety and depression. Moreover, previous studies have confirmed that negative affect plays a negative role in health-related quality of life (Bujang et al., 2015). While negative affect may disturb functioning, the presence of positive affect can enhance psychological functioning. Instead, Russell & Barrett points out that positive affect refers to the comfort generated when the stimulus meets the physiological requirements and is conducive to achieving the goal (Russell and Barrett, 1999). Fredrickson pointed out that positive affect expands people's thinking and behavior scope and encourages people to explore new thinking and behaviors (Fredrickson, 2001). In addition, positive affect can somewhat reduce the risk of people's mental illness (Dong et al., 2012). Less is knowing about the relationships between affect and well-being in children with intellectual disability.

On the other hand, affected by physical and psychological conditions, children with intellectual disabilities are pretty different from those without intellectual disabilities in the expression of subjective affects, such as generally poor emotional management ability and slower development of emotional ability (Wimmer and Perner, 1983), and even some defects (Nader-Grosbois et al., 2013). People with intellectual disabilities are more vulnerable to mental health problems than the general population (Einfeld et al., 2011; Emerson, 2003; Matson et al., 1991). Ma et al. (2020) also showed that children with intellectual disabilities had significantly less positive affect than children with sensory speech disorders. And Lindauer et al. evaluated self-harm behavior in people with intellectual disabilities and found it to be highly associated with negative affect (Lindauer et al., 1999). Therefore, for children with intellectual disabilities, it is necessary to scientifically and accurately evaluate their positive and negative emotions to promote their physical and mental health development. But there is no comprehensive or standardized way to assess the affect on people with intellectual disabilities (Adams and Oliver, 2011). This necessitates the development of reliable assessment tools.

To facilitate effective sentiment assessment, Watson, Clark, and Tellegen compared numerous sentiment scales and developed the Positive and Negative Affect Scale (PANAS) (Watson et al., 1988). PANAS shows excellent psychometric properties (reliability, validity, and discrimination). PANAS shows high-reliability validity in different samples, time frames (e. g., present, past month), and languages (Crawford and Henry, 2004; Merz et al., 2013; Rush and Hofer, 2014; Terraciano et al., 2003). The scale's efficiency correlates with the Epidemiological Studies Depression Scale, the Emotion Regulation Questionnaire For Children and Adolescents, the Children's Depression Inventory, the Spence Children's Anxiety Scale, and the Personal Well-being Index - School Children, among others (Lotfi et al., 2020; Ortuño-Sierra et al., 2019; Terraciano et al., 2003). Thus, this scale has been widely adopted internationally. Later, various versions of the scale were developed, such as the expanded form of the PANAS (PANAS-X) (Watson and Clark, 1999), the Positive and Negative Affect Scale for Children (PANAS-C) (Laurent et al., 1999), and a shorter 10-item PANAS-C version developed by Ebesutani et al. (Ebesutani et al., 2012). These scales are also widely used.

The PANAS scale is widely used not only in the general population but also in special populations. For example, Batista's study used PANAS for athletes with intellectual and developmental difficulties (Batista et al., 2019). Eadeh demonstrated the benefits of using the PANAS-C scale to assess emotional differences between individuals with attention deficit/hyperactivity disorder (ADHD) (Eadeh et al., 2020). There are also some studies involving children with intellectual disabilities. For example, Rey et al. used the PANAS scale for assessing affect in children with intellectual disabilities. And through the assessment of emotion and other aspects to comprehensively assess the happiness of children with intellectual disabilities (Rey et al., 2013). Rey Peña and colleagues used the PANAS scale to explore the mediating role of affect in the relationship between core self-evaluation and life satisfaction in people with intellectual disabilities (Rey Peña and Extremera Pacheco, 2016).

The PANAS scale was unavailable for the Chinese population until 2003 (Huang et al., 2003). Other versions of PANAS were also applied late in China. For example, International Positive and Negative Affect Schedule Short Form (I-PANAS-SF) was only shown to be suitable for Hong Kong, China adolescents in 2020 (Liu et al., 2020). In 2015, we studied the applicability of the Positive and Negative Affect Scale for Children in Chinese children (Pan et al., 2015). Although the PANAS has been widely used in the Chinese context, most of its uses were for people with normative development (Bao et al., 2020; Wei et al., 2017; Zhangand Jing Diao, 2004). The only application of PANAS in intellectual disabilities groups has explored the relationship between affect and behavior in children with intellectual disabilities by Ma et al (Ma et al., 2022; Ma et al., 2020). However, there is no standardized test for the applicability of PANAS to Chinese children with intellectual disabilities. It may also be because children with intellectual disabilities are affected by their cognitive abilities and cannot complete the scale independently. Further validation and assessment of the utility of this instrument in Chinese children with intellectual disability is indicated. Measuring affect in children with intellectual disabilities is challenging given limited reading skills, thus parents, teachers, or guardians can be considered when children have cognitive disabilities (Wallander et al., 2001). And Golubovic's study also showed that parent assessment in children with intellectual disabilities is moderately associated with self-assessment (Golubović and Škrbić, 2013). Therefore, this study will test the applicability of the scale in groups with intellectual disabilities by letting parents evaluate it.

This study aims to test the applicability of PANAS in children with intellectual disabilities, in order to provide a scientific and effective measurement tool for affect measurement in children with intellectual disabilities in China. Therefore, the Chinese version of PANAS will be used in this study. We performed exploratory and confirmatory factor analyses, and examined the PANAS structure, further investigating the two-factor structure of PA-NA, so that the scale shows the same validity in groups with intellectual disabilities as in other contexts. Unlike other studies, the assessment of emotional and behavioral problems in children with intellectual disabilities has been a hot topic (Dekker et al., 2002) because the prevalence of such issues in children with intellectual disabilities is as high as 30% to 65% (Molteno et al., 2001). As emotional problems often accompany challenging behavior, we used the Challenging behavior questionnaire (according to the Aberrant Behavior Checklist dimensions) to measure negative affect factors in PANAS. Therefore, we test the correlation between the negative affect scale in the PANAS and the Challenging behavior questionnaire as an indicator of the efficiency of PANAS. Compared with previous studies, we applied this scale to children with intellectual disabilities, further expanding its scope, to adequately address their emotions and behaviors. The physiological development of children with intellectual disabilities in adolescence is gradually closer to that of ordinary adults. And their emotional problems are even more complex (Kim & Chung, 2023). Therefore, in this study, 384 children aged 13∼18 with intellectual disabilities from twenty-three provinces, one municipality, and one autonomous in China were given PANAS. Challenging behavior questionnaire, and the collected data were analyzed by item analysis, exploratory factor analysis, confirmatory factor analysis, reliability analysis, and correlation analysis of two scales, to achieve the purpose of this study.

Methods

Participants

To examine the applicability of PANAS in children with intellectual disabilities, this study finally included 384 children with intellectually disabilities aged 13-18 years. The emotional performance in children with intellectual disabilities of different etiologies may indeed vary. To avoid the effects of an overly complex etiology, specific disorders such as autism, Down syndrome, Prader-Willi syndrome, Williams syndrome or cerebral palsy were excluded. In this research, we contacted all accessible schools for children with intellectual disabilities in twenty-three provinces, one municipality, and one autonomous region in China. Our study was conducted in all the schools that agreed to and fully supported our research. All of the participants were from these schools. And, as approved by the Ethics Committee of Shaanxi Normal University. Informed consent was obtained from all subjects involved in the study. Written consent was obtained from parents or guardians of all participants under 16. Considering the loss of samples, we issued 513 scales and 429 final recovered scales, with a recovery rate of 83.63%. Of the 429 scales recovered, 384 were valid, with a response rate of 89.51%. There were 214 males (55.73%) and 170 females (44.27%) among the children who participated in the survey. According to 2018 China's disabled population data (male 58.59%), a binomial distribution test was performed on sex, p> .001, the null hypothesis was retained, and the sex distribution of the selected sample was in line with the proportion of the population with disabilities in China. In this sample, students in the lower grades of primary schools accounted for 13.80%, senior primary school students for 25.26%, junior high school students for 42.71%, and high school for 18.23% of the sample. Although our participants were aged 13-18 years old and should be admitted to the middle school according to the Chinese school system, 39.06% of the participants were still in primary school due to their physical disabilities (see Table 1).

Table 1.

Details of the participants.

Number	Sex		Age		Grade
Number	Female	Male	13–15	16–18	Lower grades of primary school	Senior primary school	Junior high school	High school
N = 384	170	214	203	181	53	97	164	70
N = 384	44.27%	55.73%	52.86%	47.14%	13.80%	25.26%	42.71%	18.23%

Measures

Positive and negative affect scale

Watson and Clark developed PANAS in 1988 (Watson et al., 1988) to assess its positive and negative affect of individuals. PANAS showed excellent psychometric properties (reliability, validity, and discrimination). It has been translated into multiple languages, including Estonian (Alllk and Realo, 1997), German (Krohne et al., 1996), Russian (Balatsky and Diener, 1993), Spanish (Joiner Jr et al., 1997), Swedish (Hilleras et al., 1998) and Turkish (Gençöz, 2000). Although the PANAS was mainly used to assess the positive and negative affect of adults (Crawford and Henry, 2004; Watson et al., 1988), Vera-Villarroel and colleagues had applied it to the adolescent population by selecting samples of different age groups (Vera-Villarroel et al., 2019).

This study used the Chinese version of PANAS revised by Huang Li and colleagues (Huang et al., 2003). The scale used a fully double-blind approach for English translation. The scale consists of 20 items, each is a word describing emotion in a two-factor scale, Positive (PA) and Negative Affect (NA), which are represented by ten items each. The two types of items appear alternately at random. This scale issues a 5-point Likert-type scale ranging from very slightly or not at all to extremely.

To ensure that parents of children with intellectual disabilities could understand each item in the scale when filling out the scale, 15 relevant experts, teachers, and parents of children with intellectual disabilities were consulted and some items were annotated. Restricted by subjective and objective conditions, most children with intellectual disabilities aged 13–18 years could not complete the questionnaire independently. To ensure consistency, all questionnaires were evaluated by parents based on their long-term observations of their children's daily life. Using the “excited” item in the PA scale, parents rated the emotion at levels 1-5 by recalling the number of times the emotion had occurred in the past month. The higher the score represented the more times the child has been excited over the past month.

Challenging behavior questionnaire

In this study, our challenging behavior questionnaire was adapted from the Abnormal Behavior Checklist (ABC) translated by Ma et al. (Ma et al, 2011). Based on the five dimensions of the original ABC scale and interviews with some parents of children with intellectual disabilities, we identified six major challenging behaviors: hyperactivity, stereotyped behavior, inappropriate speech, violent behavior, slow movement, and refusal to meet. The questionnaire only included the presence or absence of the above six challenging behaviors within the past month (0=absence, 1=existence).

Procedure

The study was conducted following an approved protocol, and the principals of each school and their key administrators allowed researchers to show it in the school grounds. The researchers obtained the parents' consent through the head teacher of each class and informed them of the purpose of the study, assuring that the data would be kept confidential. The online questionnaire was then distributed to parents through teachers. Since the participants in this study were all children with intellectual disabilities under the age of 18 years, all the scales included in the questionnaire were filled out by parents based on their observations of their children.

Data analysis

To test the discrimination of each scale item, an independent sample t-test was performed on the high and low groups of the total score of PA and NA of the overall sample. The critical ratio of each item was then calculated, and afterward, the correlation coefficient of each item of NA and PA with its total score.

First, to measure the construct validity of the scale, the sample was randomly divided into two groups, one for exploratory factor analysis (n=199; male: 119) and the other for confirmatory factor analysis (n=185; male: 95). Specifically, when performing exploratory factor analysis in SPSS, the principal component method was selected to extract factors with a characteristic root greater than 1. After examining the rubble plots, we determined the number of factors that were retained to test whether the PA-NA two-dimensional structure was accurate. To further explore the structure of PANAS, we performed confirmatory factor analysis using AMOS software. We set two latent variables, positive and negative emotion, and established a measurement model with ten items each of positive and negative affect as observed variables. To evaluate fit, we relied on the most commonly recommended metric: Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), and Root Mean Square Error of Approximation (RMSEA) (Jackson and Gillaspy, 2009). We used traditional cut-off values: CFI and TLI indices were greater than 0.90, and RMSEA was less than 0.08 (Marsh et al., 1996). To improve the model's fit, we used the correlation error for revisions. Then, to measure the scale's calibration validity, we calculated the Pearson correlation coefficient between the negative emotion scale and the Challenging behavior questionnaire for the overall sample.

After the validity test, we performed the reliability test on the overall sample, using Cronbach's coefficient and split-half reliability as reliability indicators. We used 0.70 as the critical value for acceptable reliability and 0.80 as the critical value for good reliability (Wróbe et al., 2019).

Results

Item analysis

To clearly show the scores of PA and NA, we performed descriptive statistics on the PANAS scale results, shown in Table 2.

Table 2.

Distribution of overall distribution of PANAS scores.

PA	M	SD	NA	M	SD
Item 1	2.85	0.96	Item 2	1.58	0.78
Item 3	2.55	0.95	Item 4	1.60	0.88
Item 5	3.11	0.95	Item 6	1.62	0.81
Item 9	3.08	0.97	Item 7	2.17	1.04
Item 10	2.88	0.94	Item 8	2.30	1.14
Item 12	2.50	0.88	Item 11	1.93	0.96
Item 13	2.84	0.94	Item 14	2.13	1.06
Item 16	2.15	0.92	Item 15	1.73	0.80
Item 7	2.34	0.91	Item 18	2.17	0.90
Item 19	2.15	0.86	Item 20	2.08	0.90

Ranking the total PA score to get the top 27% (high group) and the bottom 27% (low group), performing independent samples t-test for them, calculating the PA total score and the 10-item high and low group scores, the critical ratio (CR) value reached the significance level of 0.001. The same results were obtained for the NA total score and the 10-item high and low grouping tests.

The Pearson correlation coefficients of each item of PA and its total score were calculated, and they were all between 0.62 and 0.73, all reaching a significant level at p<.001. The results of NA and PA were similar. The Pearson correlation coefficients between each NA item and the total NA score were between 0.52 and 0.77, reaching a significant level at p<.001. Items have a better degree of discrimination.

Validity analysis

Exploratory factor analysis

Using random number selection, about half of the total sample (n=199) was selected for exploratory factor analysis and the other half (n=185) for confirmatory factor analysis.

Using Kaiser-Meyer-Olkin (KMO) and Bartlett spherical test, the KMO value was 0.85, p<.001. Results indicated that the 20 items of the scale had common factors, which was suitable for exploratory factor analysis. A principal component analysis was used to extract factors, and each item was subjected to a maximum variance orthogonal rotation. The results show five eigenvalues greater than 1; the variation of the first two common factors in the rubble graph decreases rapidly from high to low, and the decline after the third is slow and almost flat. Combined with the characteristic root and the rubble plot, the two common factors align with the data characteristics. This is also consistent with the conclusion that the original scale divides PANAS into two dimensions: PA and NA. So the number of common factors is set to 2 in the subsequent analysis.

After determining the two common factors, a second-factor analysis was performed. The variance contribution rates of the two common factors were 24.17% and 20.85%, respectively, and the cumulative variance contribution rate was 45.02%. The first common factor includes the 10 PA items in the scale, called the positive factor. The second common factor consists of the 10 NA items in the scale and is called the negative factor. The average loading of the ten items for the positive factor was 0.66, and the average loading of the ten items for the negative factor was 0.65. Correlations tested for the two factors showed no significant correlation between PA and NA (p> 0.05).

Confirmatory factor analysis

Two latent variables were set, PA and NA, and their corresponding items were developed as observation variables and imported to establish a first-order orthogonal initial model. Part of the fitting index of the initial model failed to meet the standard, and the revised index suggested that there was a covariant relationship among the residuals of the variables (Wu, 2010). In addition, the correlation between the various items of PANAS was strong, and the cumulative variance contribution of the exploratory factor analysis was 45.02%, just above the 40% threshold. It also shows that in addition to the two main factors, there are common factors that are excluded due to the low variance explained rate. Therefore, we modified the model through the relevant error terms, and the corrected model index was significantly improved.

Although there was no significant correlation between PA and NA in exploratory factor analysis (p>.05), in some studies, PA and NA were considered two emotions with a specific weak correlation (Crawford and Henry, 2004; Zheng et al., 2016). Therefore, two different correction models were established. The orthogonal model regarded PA and NA as independent variables and found a first-order orthogonal model. A first-order skew model was then built by establishing a correlation between PA and NA. The fitting indexes of the two models were similar (see Table 3).

Table 3.

Overall fitting of the positive and negative emotion model.

Fit metrics Reference	χ²/df (1-3)	SRMR (<0.08)	RMSEA (<0.08)	TLI (>0.9)	CFI (>0.9)
Initial model	2.53	0.09	0.09	0.80	0.82
Skew model	1.65	0.07	0.06	0.92	0.93
Orthogonal model	1.65	0.08	0.06	0.92	0.93

Table 4 lists the parameter estimates of the orthogonal model. The unstandardized factor loads of all observed variables reached a significant level, and normalized factor loads were all greater than 0.4.

Table 4.

Parameter estimation results of the positive-negative affect the orthogonal model.

PA	Normalized factor load	NA	Normalized factor load
Item 9	0.73	Item 15	0.76
Item 10	0.72	Item 11	0.76
Item 13	0.71	Item 14	0.71
Item 5	0.67	Item 20	0.65
Item 1	0.61	Item 4	0.59
Item 12	0.60	Item 18	0.56
Item 16	0.59	Item 7	0.56
Item 19	0.59	Item 6	0.55
Item 3	0.53	Item 2	0.52
Item 17	0.51	Item 8	0.49

Correlation between PANAS and challenging behavior

To provide evidence for the validity of the PANAS scale, we calculated the correlation between the NA scale and the Challenging behavior questionnaire. Negative emotion scores were significantly positively correlated with challenging behavior scores (p<.001), and the Pearson correlation coefficient was 0.31. We also performed a correlation analysis on the positive affect scale and challenging behavior scores, but the results were insignificant.

Reliability analysis

The reliability of this study uses Cronbach's α coefficient and split-half reliability indicators. For the two dimensions of PANAS, Cronbach's α coefficients of PA and NA were 0.87 and 0.85, respectively. The entries of PA and NA were divided into parity and even half, respectively, and the split-half reliability was measured. The correlation coefficient of PA's odd-numbered and even-numbered terms was 0.74, and the Guttman split-half reliability coefficient was 0.85. The correlation coefficient between odd and even terms of NA was 0.71, and the Guttman split-half reliability coefficient was 0.83. Because PANAS measures stateful emotions, multiple surveys also show low test-retest reliability, so this measurement does not test the test-retest reliability.

Discussion

The current study tested the applicability of the Chinese version of the PANAS scale for children with intellectual disabilities. The item analysis showed that the discrimination of the scale items is good. Exploratory factor analysis showed that the scale structure in children with intellectual disabilities is consistent with the original scale, which is a two factors structure of PA-NA. In confirmatory factor analysis, we improve the fitting of the test model by allowing correlation error among some items. Some studies also showed that the solution with correlation error is the most suitable for the data (Crawford and Henry, 2004; Merz et al., 2013; Terraciano et al., 2003). The modified model meets the original standards, and the abnormal behavior scale was significantly positively correlated with the negative emotional scale. This also indicates that the PANAS scale has good validity in children with intellectual disabilities. Cronbach's α coefficient and split reliability of PA and NA of the two dimensions are above 0.8, showing high homogeneity. This is consistent with the results of Watson and colleagues (Watson et al., 1988) in English and Huang Li and colleagues (Hang et al., 2003) in Chinese.

Items and two factors structure of PANAS in children with intellectual disabilities

This measurement found that PANAS was consistent with the application of the original scale in children with intellectual disabilities, and the positive factor corresponds to the ten entries of PA. The negative factor corresponds to the ten entries of NA. The correlation between the ten items of the PA and NA scale and the total score of PA and NA is more significant than 0.5. The factor loads of all items in exploratory factor analysis and confirmatory factor analysis are all greater than 0.4, which indicates that the items on the scale have the same applicability in children with intellectual disabilities.

Confirmatory factor analysis supported the PA-NA two-factor structure of PANAS in the emotional measurement of children with intellectual disabilities. The initial confirmatory factor analysis model is not satisfactory. In the initial model, the model fitting index TLI = 0.80 and CFI = 0.82, were not greater than 0.9. SRMR = 0.09, RMSEA = 0.09, none were less than 0.08 (see Table 3). This is because of the correlation between PANAS items. In the results of the validation factor analysis, the modified index suggests a covarying relationship between the residual terms of the variable. We correct the model according to the correction index.

After the amendment, it is obtained to get a correction model that meets the indicator (SRMR=0.08; RMSEA=0.06; TLI=0.92; CFI=0.93). Emotion is a complex psychological phenomenon, and there have been controversies about the number and types of fundamental dimensions of emotion. Some scholars have proposed a three-dimensional model of ‘‘pleasantness, arousal and dominance’’ (Mehrabian and Russell, 1974), but more studies have found that emotions have two independent and stable dimensions. PA-NA model is a very important one (Yinghong Dong, 2013). The results of this test also indicated that the application of PANAS in children with intellectual disabilities has the same two basic dimensions of PA and NA as that of the general population.

There is no significant correlation between PA and NA in children with intellectual disabilities (R =0.044, p>.05). In confirmatory factor analysis, the fitting indexes of the orthogonal model and diagonal model are consistent with factor loads, which also indicates that PA and NA are two relatively independent dimensions. This is consistent with partial results of previous domestic and foreign measurements (Watson et al., 1988; Huang et al., 2003; Qiu et al., 2008), but also different from some results (Crawford and Henry, 2004; Zheng et al., 2016). Specifically, PA and NA are two relatively independent dimensions of emotional performance for children with intellectual disabilities.

Positive and negative affect in children with intellectual disabilities

The result suggested that children with intellectual disabilities had better emotional states and that children with intellectual disabilities had much higher scores on PA than on NA. This is the same result as the corresponding study of ordinary children (Wróbe et al., 2019). It is also the same result as some studies on special children (Wróbe et al., 2019). In a 2009 study, Zhao clarified that children with intellectual disabilities could use positive emotion regulation strategies to adjust their affect, and their mastery of this ability improves with age (Wróbe et al., 2019). This may explain the much higher positive than negative affect in children with intellectual disabilities aged 13-18. Although children with intellectual disabilities had higher scores on PA, the mean was 2.65, still not reaching the moderate level. That is to say, compared with ordinary children, children with intellectual disabilities have lower positive affect, and the probability of emotional problems may be greater (Baker et al., 2002; Emerson, 2003; Linna et al., 1999). For children with intellectual disabilities, the two negative affect, ‘‘distressed’’ and ‘‘scared’’ appeared the least. That is, parents are less likely to recognize their children's feelings of distress and scare. This may be because distress and scare, as two extreme negative emotions, may be related to a specific environment or object. Children with intellectual disabilities will feel relaxed and safe when staying with their parents. And parents will try their best to avoid exposing their children to danger or harm. Parents will respond to some requirements of children with intellectual disabilities as soon as possible, and children with intellectual disabilities are more relaxed around their parents, so there is almost no distress affect. Therefore, this is not to say that parents are not aware of the distress and fear of children with intellectual disabilities, but that children with intellectual disabilities staying with their parents themselves have a lower frequency of these two emotions in the general context.

Correlation between NA scale and challenging behavior

The correlation test between NA Scale and the Challenging behavior questionnaire shows a significant positive correlation between the two scales. In other words, challenging behavior and negative affect tend to coincide. This is consistent with some previous studies. For instance, McBurnett experimentally demonstrated that behavioral problems in people aged 7-17 years were positively correlated with negative affect (McBurnett et al., 2005); Petry et al. have proved that there is a significant negative correlation between Mood, Interest, and Pleasure Questionnaire and the ABC for patients with intellectual disabilities (Petry et al., 2010). Challenging behaviors in children with intellectual disabilities are associated with multiple factors. Adams et al. suggested that challenging behaviors in children with intellectual disabilities are related to the frequency or duration of community healthcare access Petty et al. also showed that challenging behaviors in children with intellectual disabilities were significantly associated with social-communicative functioning (Petty et al., 2009). However, maybe self-hindrance is the major factor in challenging behaviors. For example, children with intellectual disabilities are prone to problem behaviors such as aggression (Estes et al., 2007). The results showed that there is a significant positive correlation between the Negative Affect Scale and the Challenging behavior questionnaire, indicating that there is a high scale validity between the two. The low correlation between the Challenging behavior questionnaire and Positive Affect Scale further shows the relative independence of the positive and negative affect scales.

Limitations of this study as well as the outlook for future research

Although the current study helps expand the scope of PANAS, there are still limitations. First, although the adequate amount recovered in this study expressed the statistical requirements, the overall number was still not large. This is also due to our strict constraints on the etiology and intelligence scores of the study participants. In addition, the PANAS was filled in by the parents of the participants according to their observations in daily life. Although other studies have shown that the self-report of adolescents with intellectual disabilities is correlated with their parents' proxy report to a certain extent (Janssen et al., 2005; McVilly et al., 2000), there are still differences. However, it is also noted that although self-assessment is the standard for assessing emotions, parents, teachers, and guardians can be considered when the child is too young or has cognitive or developmental disabilities (Wallander et al., 2001). In the future research, we can also ask parents and teachers to fill in the scale according to observation and improve the accuracy of the study through correlation comparison.

In future studies, we can extend this study to compensate for some of the limitations and deficiencies of this study. The PANAS can accurately assess the positive and negative emotions in children with intellectual disabilities. Meanwhile, the results indicated a significant correlation between NA and challenging behavior. Therefore, paying attention to the emotional changes of children with intellectual disabilities can predict possible problem behaviors and assist in carrying out suitable interventions (Dagnan et al., 2015).

Conclusions

To examine the applicability of PANAS in Chinese children with intellectual disabilities, we used PANAS to investigate 384 children with intellectual disabilities in 23 provinces, one municipality, and one autonomous region in China. Through the distribution of the scale to children with intellectual disabilities and the reliability and validity analysis of the collected effective scale by SPSS and AMOS, the following conclusions are drawn: PANAS has good reliability, validity, and discrimination in children with intellectual disabilities, and higher negative affect scores are related to challenging behaviors.

Footnotes

Acknowledgements

We would like to thank all participants of this study and the schools that helped us collect data, such as Xi’an Qizhi School, Xi’an; Special Education School of Jingbian country, Yulin; Special Education School of Mei country, Baoji; Shunde Qizhi School, Foshan; Wenzhou Special Education School, Wenzhou; Qinhuai Special Education School, Nanjing; Longquanyi Special Education School, Chengdu; Shahekou Qizhi School, Dalian.

Author’s contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by XS, MM and QW. The first draft of the manuscript was written by XS and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. All authors have read and agreed to the published version of the manuscript. All authors have read and approved the manuscript.

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by the the National Social Science Fund in China [grant number: 21&ZD293], the Humanities and Social Sciences Fund of Ministry of Education in China [grant number: 20YJA890019] and the Fundamental Research Funds For the Central Universities in China [grant number: 2019TS044]. The funders provided us with full research funding over the course of the study.

Ethical statement

Informed consent

Written informed consent was obtained from parents or guardians from all participants under 16 years of age.

ORCID iD

Tingzhao Wang

Appendix

References

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