Supporting Mindfulness With Technology in Students With Intellectual and Developmental Disabilities

Abstract

Young adults with intellectual and developmental disabilities (IDDs) are at an increased risk of developing mental health disorders. Mindfulness may be one strategy that can help support the mental health needs of this particular population; however, those with (IDDs) may need additional support in cultivating the practice. The purpose of this study was to investigate the use of a wearable device designed to provide neurofeedback to help promote state mindfulness in young adults with (IDDs). Additionally, attention and affect mechanisms were examined, as well as the social validity of using the wearable device. Using an A-B-A-B single-subject study design, five (age range = 18–25) students completed 20 sessions that consisted of listening and not listening to neurofeedback. Results provide some support for the positive effect of neurofeedback on state mindfulness, paying attention to the breath, and positive affect. All five students reported acceptability of using the device.

Keywords

meditation affect attention wearable devices self-regulation

The prevalence of individuals with intellectual and developmental disabilities (IDDs) varies between 1% and 3% globally, with a reported incidence of 9 and 13 per 1,000 in the world’s population (Harris, 2006; Katusic et al., 1996). Diagnostic criteria for an IDD include deficits in mental abilities and limitations in adaptive behavior that are observed before the age of 18 (American Psychiatric Association [APA], 2013). Individuals with IDD are at an increased risk of developing mental health disorders (APA, 2013; Dekker & Koot, 2003; Simonoff et al., 2008). One population-based study revealed a prevalence of 40.9% of those with IDD having a mental health disorder (Cooper et al., 2007), and a community-based study showed that 60.4% of individuals with IDD experienced at least one disorder (Deb et al., 2001). These mental health disorders can include behavioral, cognitive, and emotional disorders. Several of these disorders originate in early adulthood, which is why it is essential to support the mental health of young adults with IDD.

Mindfulness

One strategy that can be used to support mental health in young adults with IDD is the promotion of mindfulness in educational settings. Mindfulness is the ability to pay attention on purpose, in the present moment, and nonjudgmentally (Kabat-Zinn & Hanh, 2013), and state mindfulness refers to the quality of mindfulness at a particular point in time (Brown et al., 2015). Self-regulation theory is one framework that describes the processes by which mindfulness may support mental health outcomes. Baumeister et al. (1994) describe self-regulation as a multifaceted system of conscious personal control involving the ability to manage emotions and thoughts to achieve goals. The ability to be mindful at a particular moment in time can enhance self-regulation (Brown et al., 2015; Kabat-Zinn, 1994, 2003), which is a critical factor in supporting positive mental health (Baumeister & Vohs, 2003; Kabat-Zinn, 2003; Masicampo & Baumeister, 2007). Two ways that mindfulness may support self-regulation is by increasing attention (Holzel et al., 2007) and positive affect (Remmers et al., 2016). At its core, practicing mindfulness involves bringing awareness to current experiences and/or situations by way of regulating the focus of attention (Bishop et al., 2004). In addition, mindfulness is strongly linked with positive affect or pleasurable feelings, which also plays a key role in self-regulation (Tice et al., 2007). Thus, mindfulness may enhance self-regulation through a greater capacity for attentional focus and more positive affect.

Mindfulness-Based Interventions (MBIs)

MBIs have increasingly been used in samples of young adults with and without IDD. For example, a meta-analysis by Chiesa and Serretti (2009) identified 10 studies investigating mindfulness and mental health in young adults and found that the participants experienced significantly greater improvement in mental health outcomes (e.g., stress), compared to those who did not practice mindfulness. MBIs encompass self-regulatory strategies, such as focusing attention to the present moment, which can help promote positive mental health outcomes (Kabat-Zinn, 2003). Although studies often report lower levels of self-regulatory strategies in people with IDD (Nader-Grosbois, 2014), studies also discuss how self-regulation can be taught and how it can improve as the developmental age of the individual increases (Vieillevoye & Nader-Grosbois, 2008; Wehmeyer et al., 2003). As a result, young adulthood may be an ideal developmental period to implement self-regulation interventions, such as MBIs, for those with IDD.

Soles of the Feet is a common MBI designed specifically for those with IDD and has shown to be successful for this population by using simple self-regulatory strategies (Singh et al., 2003). Over the course of five 45-min sessions, individuals are taught to become aware of emotional precursors that can lead to aggressive or anxious behavior through mindful breathing and body awareness and learn to divert attention from the emotionally arousing thought or event to a neutral stimulus (i.e., soles of the feet; Felver et al., 2013; Singh et al., 2003). These self-regulation approaches can help the individual focus on sensations in the body and experience feelings of calmness (Felver et al., 2013; Singh et al., 2003). Studies that applied soles of the feet have shown improvements in mental health indicators such as aggressive behavioral disorders in young adults with IDD (Adkins et al., 2010; Singh et al., 2003; Singh, Lancioni, Winton, Adkins, Singh, & Singh, 2007; Singh, Lancioni, Winton, Adkins, Wahler, Sabaawi, & Singh, 2007; Singh et al., 2008). These studies highlight how an MBI that uses self-regulatory strategies can be used and be effective for those with IDD.

Other MBIs that use elements such as focusing on the breath and body scans, of mindfulness-based stress reduction (Kabat-Zinn, 2003) and mindfulness-based cognitive therapy (Segal et al., 2002) illustrate how valuable these interventions can be for those with IDD. Both types of mindfulness practice have shown promising results in improving mental health disorders in young adults with IDD (Harper et al., 2013; Idushohan-Moizer et al., 2015). In addition to the effectiveness of these MBIs, young adults with IDD report that they value mindfulness techniques that enable them to self-regulate their behaviors and emotions rather than having to be directed or managed by others (Chapman et al., 2013; Currie et al., 2019). Thus, there is evidence that a variety of mindfulness-based strategies can support the mental health needs of young adults with IDD.

With promising mental health benefits to be gained from the practice, more research is needed to effectively promote mindfulness in young adults with IDD. One reason for this is young adults with IDD are generally not mindful, due to lack of knowledge or awareness of the practice (Chapman & Mitchell, 2013). Another challenge that young adults with IDD may face when first learning about mindfulness is needing additional support to promote their practice (Chapman et al., 2013; Chapman & Mitchell, 2013; Hwang & Kearney, 2013). MBIs need to use innovative methods that are encouraging and motivating that can assist young adults with IDD to be mindful and cultivate the practice, thus integrating mindfulness within their lives (Chapman et al., 2013). Testing new methods for promoting mindfulness in young adults with IDD could help build upon existing strategies and perhaps increase their effectiveness.

Mindfulness Supported With Technology

A novel approach that can help address certain challenges in promoting mindfulness in young adults with IDD are MBIs supported with technology. Technology can include mobile and wearable devices and has been shown to support young adults with IDD in areas ranging from education (Blishchak & Schlosser, 2003) to employment (Wehmeyer et al., 2006), and more recently mental health (Luxton et al., 2011). Additionally, MBIs supported with technology are increasingly used to promote the practice of mindfulness. In a recent review of the literature, Plaza et al. (2013) discuss how mobile and wearable devices can support mindfulness daily practice and adherence due to the usability and ubiquity of these devices. Innovative methods of promoting mindfulness in young adults with IDD are needed, and MBIs supported with technology can address this need by furthering our understanding of how mindfulness can support this underserved population.

Research Questions

In this study, we addressed two main research questions: (1) Is state mindfulness present in students with IDD with the support of a wearable device that provides neurofeedback to help an individual be more mindful? and (2) Is there evidence that attention and affect may serve as mechanisms by which mindfulness facilitates self-regulation? We hypothesized that state mindfulness scores would be higher when receiving neurofeedback on the state of their mindfulness from a wearable device compared to not receiving feedback. We also hypothesized that students would pay more attention to their breath with the help of the neurofeedback compared to not receiving the feedback. Finally, we hypothesized that students’ affect would be more positive following the use of the neurofeedback compared to not receiving the feedback. Specifically, we expected their affect to be higher (i.e., more positive) after practicing mindfulness with neurofeedback than without. We also expected improvements in affect from before to after their mindfulness practice to be greater and in a positive direction when using neurofeedback compared to not using it. Through the use of interviews, we explored if an MBI supported with technology is socially valid for students with IDD.

Method

Participants

Following institutional review board approval, five students with IDD were recruited from a high school and a program at a postsecondary education institution for students with IDD in the United States. Inclusion criteria for the participants consisted of a diagnosis of a mild or moderate IDD and no comorbid mental health disorders. Prerequisite skills needed to participate in the study included being able to sit and complete the mindfulness session for 5 min and answer questions regarding the session as well. Individuals with a severe or profound severity level were not included in the study due to limited conceptual and communication skills (APA, 2013). Information regarding the IDD diagnoses was obtained from the special education teachers. The primary researcher asked the special education teachers to provide the severity levels, which came from the students’ school records. The following section includes a brief description of each student.

All five students were able to verbally communicate their responses to study questions and were able to independently ask questions before, during, and after the study. For example, saying “yes” or shaking their head and using direct eye contact when asked if they understood a question. The special education teachers reviewed the procedures and materials that the students would complete throughout the study. This was done to ensure that the students would be able to comprehend the procedures and materials and that it would be within their skill set to complete them. Any changes and suggestions from the special education teachers were incorporated into the procedures and materials. All five students were Caucasian. Two of the study participants, Luke and Hans, were both 18-year-old male students diagnosed with Down syndrome and autism spectrum disorder (ASD), respectively. Both participants were finishing their last year of high school. Another participant, Anakin was a 21-year-old male student diagnosed with Down syndrome and was finishing his first semester of a 2-year postsecondary education program for students with IDD. Leia and Kylo, two other participants were 22 and 25 years old. They were both diagnosed with ASD and were finishing their first semester in the postsecondary program.

Dependent Variables

State mindfulness

State mindfulness was assessed by the MUSE. The MUSE is a wearable electroencephalography (EEG) device that measures brain wave activity and provides continuous neurofeedback, which is displayed in a smartphone or tablet using Bluetooth connectivity (Krigolson et al., 2017). The MUSE detects individual brain waves to determine state mindfulness (Krigolson et al., 2017), which refers to the quality of mindfulness at a particular time (Brown et al., 2015). The MUSE provides calm, neutral, and active feedback regarding the mindfulness session. Calm feedback refers to the time spent being mindful (i.e., state mindfulness), and attention was focused on the breath. Neutral feedback refers to a person’s natural resting state. Active feedback refers to time spent not being mindful and not focused on the breath during the session. All three are reported in minutes and seconds per session, and the calm feedback represented the state mindfulness scores. Although the MUSE has not been tested on young adults with IDD, it has been tested against industry standard EEG systems including the Brain Vision actiCHamp system and the g.Tecg.USBamp system and has produced valid and reliable scores for detecting individual brain waves to determine state mindfulness (Hashemi et al., 2016; Kovacevic et al., 2015; Marcengo et al., 2017).

Attention

To assess attention, an adapted version of Tammen’s (1996) Attentional Focus Scale was administered. The original scale is a single-item bipolar scale with internal focus (e.g., breathing) and external focus (e.g., daydreaming) at either end of a 10-cm line. For this study, the anchors were modified to “paying attention to the breath” and “not paying attention to the breath.” The scale was administered immediately after each session by asking the students to mark an “X” or line to show, “how much you were paying attention or not paying attention to your breath during the MUSE session.” Attentional focus was scored by measuring the distance in centimeters and millimeters from the paying attention to the breath anchor on the left-hand side to the mark the student made and multiplying by 10 to obtain a score out of 100. Scores under 50 indicate a predominately focused attention to the breath, whereas scores over 50 indicate a predominantly unfocused attention to the breath. Previous research has provided evidence of score validity using this scale (Baden et al., 2005).

Affect

To assess the dependent variable affect, the Children’s Feeling Scale (CFS; Hulley et al., 2008) was administered. The CFS measures how one currently feels on an 11-point scale ranging from −5 (very bad) to +5 (very good), with smiley faces to help the individual understand the scale (Hulley et al., 2008). Students were asked before and immediately after the mindfulness session, “How do you feel right now? Circle a number.” Research has produced evidence of valid and reliable CFS scores for assessing current affect in children and adolescents (Hulley et al., 2008).

Social validity

Social validity of the MUSE was assessed by interviewing the students in a quiet meeting room at the school and were audio recorded using the Voice Memos application on an iPad. A total of five open-ended interview questions regarding the acceptability of and satisfaction with the MUSE intervention were asked at the end of the study by the primary researcher. These questions were developed in collaboration with the special education teachers to ensure that participants would be able to understand and respond to the questions. The five questions asked were (1) Do you think the feedback provided by the MUSE helped you pay attention to your breathing? (2) What did you like most about using the MUSE? (3) What did you not like about using the MUSE? (4) Is there anything that you would change about the MUSE that would make it better or easier for you to use? and (5) Would you recommend other students use the MUSE? The interviews included probing follow-up questions (e.g., Why do you think the feedback provided by the MUSE helped you pay attention to your breathing) to gather more specific data and field notes were taken. The interview questions were based on previous research assessing social validity in intervention studies (Wolf, 1978).

Study Design

An A-B-A-B design was used to examine the relationship between the use of the MUSE and dependent variables (Ledford & Gast, 2018). There were a total of four phases (i.e., A-B-A-B) with five data points per phase, and the independent variable (i.e., the MUSE neurofeedback) was systematically manipulated. Both of these standards meet the What Works Clearinghouse (WWC, 2017) single-case design standard without reservations. However, interobserver agreement was not collected and does not meet the WWC (2017) single-case standards and is a limitation of this study.

Procedures

Each mindfulness session was 5 min for students during baseline (A) and intervention (B) phases. Prior to each session, the primary researcher read a brief script to the students explaining what mindfulness is and how to be mindful. Please refer to Table 1 for the script used for the intervention phase. The script also contains details about the operationalized definitions of students demonstrating “understanding” and “paying attention.” The script used for baseline is the exact same script without the information regarding how to listen to the MUSE. A total of 20, five-min sessions (i.e., 10 baseline and 10 intervention) were conducted over the course of 6 weeks for each student. All sessions were conducted individually in a quiet meeting room in their respective schools with only the participant and primary researcher in the room. The lights were on during each session.

Table 1.

A Sample of the Procedures Followed for Intervention Phase (B).

Verbal Instructions	Additional Procedures to Follow
“Thank you for coming in today! We are going to have you pay attention to your breathing for 5 minutes with the help of a device called the MUSE.”	Direct the student to the chair and make sure he or she is comfortable. A response of “yes” or shaking their head with direct eye contact indicates they are comfortable. Ask if the student needs to use the bathroom or needs anything.
“One way to pay attention to your breathing, is by closing your eyes, if you feel comfortable, or you can softly gaze at the floor, and try to focus on your breath as you breathe in and fill up your lungs with air and when you exhale the air out of your lungs. Try to notice how it feels as you breathe in and out. Feel your breath entering and leaving your body. Let’s practice together.”	Practice the breathing exercise with the student by focusing on the breath.
“Remember this is how you can pay attention to your breathing during our session today. During our session, you might have thoughts cross your mind, such as needing to complete homework or something that is bothering you. This is completely normal and okay. If this does happen, you can return your attention to your breathing. Do you have any questions about how to pay attention to your breathing?”	Make sure the student understands how to pay attention to their breathing and if he or she has any questions. In order to ensure the student understands, an affirmative response of saying “yes” or shaking their head with direct eye contact is needed before moving on. If they do not say yes or shake their head yes with direct eye contact, repeat the breathing exercise with them and answer any questions.
“For this question, you will complete at the end of the session where you will mark an X or line on this scale to show how much you were paying attention or not paying attention to your breath. The scale ranges from paying attention to your breath to not paying attention to your breath. Do you have any questions about completing this scale?”	Go over the Attentional Focus Scale and make sure the student understands how to complete it. In order to ensure the student understands, an affirmative response of saying “yes” or shaking their head with direct eye contact is needed before moving on. If they do not demonstrate these behaviors, repeat the directions and answer any questions.

Note. This is a sample of the procedures that were read to the students. These procedures were read to each student for each intervention session. These procedures are the exact same procedures followed during the baseline sessions, except for the directions about listening to the MUSE feedback.

Baseline (A)

After students were given the general instructions, the MUSE headset was fitted for the student to wear while in a comfortable, seated position. Next, the MUSE was connected to the application on a smart phone or tablet via Bluetooth. During each baseline phase, students wore the MUSE for 5 min but with the neurofeedback cues on the device muted. Thus, the only direction students received about how to be mindful were the initial instructions to pay attention to their breath. This allowed us to obtain state mindfulness scores without providing feedback to the students.

Intervention (B)

In addition to the procedures used for the baseline phases, the students were able to hear the neurofeedback cues provided by the MUSE in the two intervention phases. All students listened to the “ocean” neurofeedback cues. During the mindfulness session, the MUSE translated brain signals into the sounds of wind, such as the ocean soundscape, and was heard from the smartphone or tablet. When the individual was focused on their breath, the wind sounds were calm and settled. If the individual’s mind began to wander and was not focused on the breath, the winds picked up and blew. Thus, the participants were cued to refocus on the breath and bring themselves back to the present moment.

Data Analysis

Means were calculated for study variables in each A and B phase using SPSS Version 25 for analyzing levels of the data. Additionally, a visual analysis procedure that is typically used in single-subject research (Ledford & Gast, 2018) was used to evaluate the state mindfulness and attention-dependent variables. To assess changes between baseline and intervention phases, two indicators were examined: trend and variability (Ledford & Gast, 2018). One way to determine the trend is the Nugent (2009) approach, where the researcher draws a straight line connecting the first and last data points in the baseline and intervention phases. A visual inspection of the data was conducted to determine whether the data were stable or varied in a particular phase.

Additionally, the immediacy of effect was evaluated, which refers to immediate changes from the introduction or withdrawal of the intervention (Ledford & Gast, 2018). Finally, the percent nonoverlapping data (PND) were assessed, which refers to the extent of the overlap between the baseline and intervention conditions (Ledford et al., 2018). The mean, trend, variability, immediacy of effect, and PND were the five analysis tools used to determine whether there was a functional relation between the neurofeedback cues provided by the MUSE and the state mindfulness and attention-dependent variables. The mean for postsession affect and the affect change scores from pre to post were used to determine any changes and/or differences in affect.

A content analysis was conducted on the student responses to assess the social validity of using the MUSE. The primary researcher followed the recommendations of Erlingsson and Brysiewicz (2017) to complete a content analysis. Steps included dividing up the interview texts into smaller parts, referred to as condensed meaning units, and labeling these units by formulating codes and grouping them into categories and themes (Erlingsson & Brysiewicz, 2017).

Results

State Mindfulness

Means for state mindfulness and attention during baseline (A₁ and A₂) and intervention (B₁ and B₂) phases for the students are displayed in Table 2. Overall, the state mindfulness mean scores for the B₁ phase were higher, compared to the A₁ phase for most of the students. Luke was the only student to have a higher state mindfulness mean score during the A₁ phase, compared to the B₁ phase (M = 2:27 vs. M = 2:04). Four of the students had higher state mindfulness mean scores for the B₂ phase, when compared to the A₂ phase. Hans was the only student who demonstrated a higher state mindfulness mean score (M = 2:27) in the A₂ phase, when compared to his mean score (M = 2:21) in B₂ phase. For consistency of effect (i.e., similar data paths for the phases), Anakin’s and Leia’s B₁ and B₂ conditions were similar. Variability of the data was evident for all four students, except for Anakin’s B₁ and B₂ phase. However, there was an immediacy of effect apparent across the phases for all the students, excluding the A₂ and B₂ phase for Hans. Figure 1 displays the visual results of the dependent variable state mindfulness, and Table 3 shows a summary of the criteria used to demonstrate a functional relation between state mindfulness and the neurofeedback.

Table 2.

Means for State Mindfulness and Attention.

Students	Phases	State Mindfulness M	Attention M
Luke	A₁	2:27	51.00
	B₁	2:04	55.60
	A₂	1:40	56.80
	B₂	2:25	48.00
Hans	A₁	1:52	46.60
	B₁	2:56	24.00
	A₂	2:27	37.60
	B₂	2:21	32.40
Anakin	A₁	1:48	51.40
	B₁	4:28	3.80
	A₂	2:55	34.40
	B₂	4:30	4.20
Leia	A₁	3:14	38.80
	B₁	3:50	15.40
	A₂	1:23	44.40
	B₂	3:04	14.60
Kylo	A₁	3:48	22.80
	B₁	4:02	5.40
	A₂	2:37	46.40
	B₂	3:48	4.40

Note. State mindfulness means are displayed in minutes and seconds. Range for attention is 0–100. A score below 50 indicates predominantly paying attention to the breath, and a score above 50 indicates predominantly not paying attention to the breath. A₁ = first baseline phase; B₁ = first intervention phase; A₂ = second baseline phase; B₂ = second intervention phase.

Figure 1.

State mindfulness scores as time being mindful for each MUSE session.

Table 3.

Summary of Criteria Used to Determine Functional Relation State Mindfulness.

Students	Phases	Trend	Variability	Immediacy of Effect (Yes or No)	PND (%)
Luke	A₁	Decreasing	Varied	Yes	20
	B₁	Increasing	Varied
	A₂	Decreasing	Varied	Yes	40
	B₂	Decreasing	Varied
Hans	A₁	Increasing	Varied	Yes	60%
	B₁	Decreasing	Varied
	A₂	Increasing	Varied	No	40
	B₂	Decreasing	Varied
Anakin	A₁	Decreasing	Varied	Yes	80
	B₁	Increasing	Stable
	A₂	Increasing	Varied	Yes	80
	B₂	Increasing	Stable
Leia	A₁	Increasing	Varied	Yes	40
	B₁	Decreasing	Varied
	A₂	Decreasing	Varied	Yes	60
	B₂	Increasing	Varied
Kylo	A₁	Increasing	Varied	Yes	80
	B₁	Decreasing	Varied
	A₂	Increasing	Varied	Yes	40
	B₂	Increasing	Varied

Note. Immediacy of effect is given between each baseline and intervention phases. PND is given as a percentage for the first baseline and intervention phases and for the second baseline and intervention phases. A₁ = first baseline phase; B₁ = first intervention phase; A₂ = second baseline phase; B₂ = second intervention phase; PND = percent nonoverlapping data. Trend options: increasing, decreasing, or stable. Variability options: stable or varied.

Attention

Attention mean scores were higher in A₁ phases than B₁ phases, suggesting that the students were paying attention to their breath more when listening to the neurofeedback cues in the intervention phase than the baseline phase (Table 2). Luke was the only student who had a lower attention mean score in the A₁ phase (M = 51.00) than B₁ phase (M = 55.60). This finding indicates that he was paying attention to his breath more during that particular baseline phase. This is consistent with his state mindfulness mean score where he was more mindful during the A₁ phase than the following B₁ phase. Consistency of effect was evident in Anakin’s, Leia’s, and Kylo’s A and B phases. This included higher scores (i.e., not paying attention to the breath) in A₁ and A₂ and lower scores (i.e., paying attention to the breath) in B₁ and B₂ phases. An immediacy of effect was seen between the A and B phases for Anakin, Leia, and Kylo, but not for Hans and only between A₂ and B₂ for Luke. The data were stable for the B phases for Anakin, Leia, and Kylo, but not for Luke and Hans. Figure 2 contains the visual results of the dependent variable attention, and Table 4 displays a summary of the criteria used to determine a functional relation between attention and the neurofeedback.

Figure 2.

Attention scores for each MUSE session.

Table 4.

Summary of Criteria used to Determine a Functional Relation for Attention.

Students	Phases	Trend	Variability	Immediacy of Effect (Yes or No)	PND (%)
Luke	A₁	Increasing	Varied	No	40
	B₁	Decreasing	Varied
	A₂	Increasing	Varied	Yes	0
	B₂	Increasing	Varied
Hans	A₁	Decreasing	Varied	No	60
	B₁	Increasing	Varied
	A₂	Increasing	Varied	No	20
	B₂	Decreasing	Varied
Anakin	A₁	Increasing	Varied	Yes	40
	B₁	Stable	Stable
	A₂	Decreasing	Varied	Yes	60
	B₂	Stable	Stable
Leia	A₁	Decreasing	Varied	Yes	0
	B₁	Increasing	Stable
	A₂	Increasing	Varied	Yes	60
	B₂	Stable	Stable
Kylo	A₁	Decreasing	Varied	Yes	20
	B₁	Stable	Stable
	A₂	Stable	Varied	Yes	100
	B₂	Decreasing	Stable

Affect

Means and standard deviations for presession affect, postsession affect, and affect change between baseline (A₁ and A₂) and intervention (B₁ and B₂) phases for the students are displayed in Table 5. Luke was the only student who reported a higher A₁ postsession affect mean (M = 3.40). This affect score is consistent with his state mindfulness and attention scores, where he was more mindful and paying more attention to his breath in the A₁ phase, compared to the B₁ phase. All postsession affect scores were higher in the B₂ phases than the A₂ phases, except for Luke where he selected +5 for all of his presession affect and postsession affect. This means there was no change in his affect between these particular phases. In addition, Luke was the only one who had a higher affect change in the A₁ phase than B₁ phase (M = 3.40 vs. M = 2.60), which is consistent with his previous mean scores for the other variables.

Table 5.

Means and Standard Deviations for Affect.

Students	Phases	Presession Affect M (SD)	Postsession Affect M (SD)	Affect Change M (SD)
Luke	A₁	1.40 (1.52)	3.40 (0.89)	2.00 (2.12)
	B₁	1.60 (1.34)	2.60 (0.89)	1.00 (1.41)
	A₂	2.00 (1.41)	2.60 (1.67)	0.60 (0.89)
	B₂	5.00 (0.00)	5.00 (0.00)	0.00 (0.00)
Hans	A₁	2.00 (2.00)	2.60 (1.67)	0.60 (1.34)
	B₁	2.40 (1.95)	3.40 (2.07)	1.00 (1.00)
	A₂	2.00 (2.00)	2.40 (1.95)	0.40 (0.89)
	B₂	1.20 (1.64)	4.20 (1.10)	3.00 (2.12)
Anakin	A₁	4.00 (1.00)	4.40 (0.89)	0.40 (0.55)
	B₁	2.60 (0.89)	5.00 (0.00)	2.40 (0.89)
	A₂	3.00 (0.00)	4.60 (0.89)	1.60 (0.89)
	B₂	3.00 (0.00)	5.00 (0.00)	2.00 (0.00)
Leia	A₁	3.00 (0.00)	3.80 (0.45)	0.80 (0.45)
	B₁	3.20 (1.10)	4.00 (0.71)	0.80 (0.45)
	A₂	3.40 (2.07)	3.80 (2.17)	0.40 (0.55)
	B₂	4.40 (0.55)	4.80 (0.45)	0.40 (0.55)
Kylo	A₁	3.40 (0.55)	4.20 (0.45)	0.80 (0.45)
	B₁	3.20 (1.79)	4.20 (0.84)	1.00 (1.22)
	A₂	3.80 (0.45)	4.80 (0.45)	1.00 (0.71)
	B₂	4.00 (0.00)	5.00 (0.00)	1.00 (0.00)

Note. Range for affect is −5 to 5. A₁ = first baseline phase; B₁ = first intervention phase; A₂ = second baseline phase; B₂ = second intervention phase.

Social Validity

Three themes emerged from the analysis of the participants’ responses: (1) students liked how the sounds (i.e., neurofeedback) from the MUSE helped them pay attention to their breathing, (2) the MUSE was easy to use, and (3) they would recommend the MUSE to other students. A […] in the quotations signifies text that was removed to increase clarity. Support for liking the MUSE sounds and how it helped them pay attention to their breathing can be seen in Kylo’s response.

Researcher:

“Do you think the feedback provided by the MUSE helped you pay attention to your breathing?”

Kylo:

“Yes.”

Researcher:

“Yes? Why do you think that?”

Kylo:

“The calm ocean waves made it so my mind did not wander.”

The ease of using the MUSE was the second theme seen across the students’ responses and is evident in their comments. For example, both Luke and Hans said, respectively: “I used the […] MUSE and it’s easy” and “I-I like easy, and to me […] the MUSE is easy to use for me.” The third theme, focused on student recommendation of the MUSE, was evident in all comments, including Leia’s “cause it, it would help, help’em [student], you know, help’em relax and if they’re stressed and stuff like that.”

Summary

Based on the mean, trend, variability, immediacy of effect, and PND, there is evidence that there was a functional relation between listening to the neurofeedback cues and state mindfulness for Anakin, Leia, and Kylo. However, this was not true for Luke and Hans. A functional relation between listening to the neurofeedback cues and paying attention to the breath was observed for Anakin, Leia, and Kylo. These students were able to pay more attention to their breath when using the neurofeedback cues, compared to no neurofeedback cues. Yet this did not occur for Luke and Hans. Except for Luke, all postsession affect scores were more positive or remained the same after listening to the neurofeedback cues for Hans, Anakin, Leia, and Kylo. In terms of social validity, all five students reported the acceptability and supported the social validity of using the MUSE to promote mindfulness.

Discussion

Based on the growing evidence of how practicing mindfulness can support positive mental health outcomes in young adults with IDD (e.g., Adkins et al., 2010; Harper et al., 2013), the current study investigated the use of a wearable EEG device to promote mindfulness in students with IDD. Specifically, a primary aim of this study was to determine if the use of neurofeedback cues, provided by the wearable EEG device called MUSE, could result in higher state mindfulness, attention, and positive affect. Qualitative data were also collected to explore the social validity of using the MUSE for students with IDD.

Overall, the data suggested that some of the students experienced higher state mindfulness when using the MUSE than when not using the MUSE. A functional relation between the use of the neurofeedback and higher state mindfulness was demonstrated for Anakin, Leia, and Kylo. For Luke and Hans, the state mindfulness scores were more variable, and the data did not show a clear and sustained increase in state mindfulness as predicted. Thus, the data provide partial support for the hypothesized relation between the use of the neurofeedback from the MUSE and improving state mindfulness in these students. Variability in the effectiveness of the MUSE may be explained by students’ level of functioning. Luke and Han’s levels of disability were labeled as moderate, whereas the other three were identified as having mild disabilities. Research has shown that differences in level of functioning can greatly influence the adaptive functioning of young adults with IDD, which can impact how they learn and react to certain situations (De Bildt et al., 2005). As a result of the severity differences, these students may have responded differently to using the neurofeedback from the MUSE.

Another possible reason why the neurofeedback did not work for these two students may be due to their developmental age. These two students were the youngest (i.e., 18 years old) and still in high school, while the other three were between the ages of 21 and 25 and were in college. The older students may have more pronounced self-regulatory skills that can help them practice mindfulness due to their age (Vieillevoye & Nader-Grosbois, 2008), compared to the younger students. Moreover, the students in college were at different phases in their lives, such as living independently on their own, compared to the high school students. Greater independence may provide more opportunities to develop self-regulatory skills, which could explain higher responsiveness to the MUSE intervention. Additionally, extending the condition lengths to obtain more stability for these two students may have been needed to observe effects. Conducting more sessions at baseline before introducing the MUSE could have provided more stability and less variability in these particular students.

Interestingly, all five students had surprisingly high state mindfulness scores in their first baseline (i.e., no neurofeedback) phase. In order to measure differences in state mindfulness between using the neurofeedback and not using the cues, the students were taught how to practice mindfulness before each session throughout the study. This may account for the higher than expected state mindfulness scores observed in baseline. Although the MUSE seemed to not be of added benefit for some of the students, introducing and explaining how to practice mindfulness helped the students be mindful even without the neurofeedback. This particular finding is consistent with empirical evidence from other MBIs that emphasize how individuals with IDD may not generally be mindful but can comprehend and learn the construct (Chapman & Mitchell, 2013). The high baseline state mindfulness scores support these previous findings, and the current study further highlights how students with IDD can learn how to practice mindfulness through support and guidance.

Similar to state mindfulness, attention scores were higher when using the neurofeedback compared to not using the cues for some of the students. These scores provide some validity evidence for using the MUSE to increase state mindfulness. A functional relation was shown between using the neurofeedback from the MUSE and higher attention scores for Anakin, Leia, and Kylo. However, again, this was not true for Luke and Hans. Their collected data did not display a continuous and well-defined pattern of paying attention to the breath as expected. Therefore, there is partial support for the hypothesized relationship between using the neurofeedback and paying more attention to the breath. Previous research shows how attention may be one mechanism that explains the relationship between mindfulness and heightened self-regulation (Holzel et al., 2011). However, the targeted samples in these studies have primarily been experienced meditators (Holzel et al., 2007), clinical (Kabat-Zinn et al., 1985), and general populations (Lutz et al., 2008). As for individuals with IDD, the majority of research is predominantly focused on examining outcomes and the effectiveness of MBIs and not investigating mechanisms (e.g., Hwang & Kearney, 2013). Those individuals with IDD are at an increased risk of developing mental health disorders (APA, 2013), and understanding the causal pathways that link mindfulness and enhanced self-regulation can provide insight into how to create the most effective MBIs for young adults with IDD.

In terms of affect, some of the students reported more positive postsession affect when using the neurofeedback to practice mindfulness. Postsession affect scores were more positive in the intervention phases for Hans, Anakin, Leia, and Kylo and provide partial support for the hypothesized relationship between using the neurofeedback cues from the MUSE and more positive affect for these students. Change in affect was either more positive or remained the same between the phases, which provides further support of the hypothesized relationship in these particular students. However, this was not true for Luke and the data does not support the predicted relationship of using the neurofeedback and positive affect for this student. It is important to note that none of his postsession affect scores were more negative than his presession affect scores for all of the phases. This is seen among the other students as well and suggests that practicing mindfulness can help improve affect in students with IDD, regardless of using neurofeedback or not. This finding is consistent with previous studies that show how MBIs can support positive affect and reduce negative affect in clinical populations (Tacón et al., 2003) and college students (Sears & Kraus, 2009). Similar to this study, even brief MBIs (e.g., 10-min or less of mindful practice) can support positive affect in general populations (Arch & Craske, 2006). The present study adds students with IDD as participants in a growing and promising list of how practicing mindfulness can cultivate positive affect.

The social validity interviews provide insight about how the students felt about using the MUSE to practice mindfulness and their responses support the social validity of using the device. Themes from the social validity interviews from the students reveal that the neurofeedback from the MUSE can help students with IDD practice mindfulness, the MUSE is easy to use, and all of the students would recommend the MUSE to other students. Traditionally, social validity is assessed via questionnaires (Carter, 2009); however, we wanted the opportunity to ask follow-up questions and obtain as much information as possible, especially since this is the first study evaluating the social validity of the MUSE for students with IDD. However, additional measures, such as the special education teachers completing a questionnaire to rate if the student was less anxious or more relaxed following a MUSE session, could provide further evidence of the effectiveness of using the MUSE. Although this intervention was not effective for all of the students, the students still expressed their satisfaction with the MUSE and how the device is a promising means of promoting mindfulness for students with IDD. These findings are consistent with other studies investigating the social validity of MBIs for individuals with IDD (Felver et al., 2017). The aforementioned studies together with the current study further highlight the acceptability of using a variety of mindfulness strategies with young adults with IDD.

Several studies highlight how individuals with IDD need continued support and innovative methods to help them cultivate the practice of mindfulness, especially when first being introduced to the practice (Chapman & Mitchell, 2013; Chapman et al., 2013; Hwang & Kearney, 2013). Although there is some evidence of promoting positive mental health outcomes using neurofeedback in youth with IDD (Kouijzer et al., 2009, 2010; Scolnick, 2005) and using neurofeedback to promote state mindfulness for general populations (Sas & Chopra, 2015), this was the first study to our knowledge to use a wearable EEG device to promote state mindfulness for students with IDD. Not only does this device help an individual to be mindful, it also provides an objective means of measuring mindfulness, which can provide more reliable and valid information than subjective measures, such as self-report (Greco et al., 2011). The results also have important implications for practitioners who work with individuals with IDD. The MUSE gives an objective measure of how mindful individuals are in real time, which can provide opportunities for practitioners and individuals to go over the results together. This may encourage and motivate individuals with IDD to practice more mindfulness, which may help them develop self-regulatory strategies that can promote positive mental health outcomes.

Limitations

There are several limitations of this study that need to be addressed in future research. Although the MUSE has shown to be valid and reliable in detecting state mindfulness in general populations, it has not been tested on young adults with IDD. Additionally, the reliability and validity of the Attentional Focus Scale and CFS have not been tested for young adults with IDD and is a further limitation. Participant information regarding intelligence and adaptive behavior measurements were not collected for this study, and the lack of these scores creates a serious limitation that future studies can consider. Another limitation is that all participants received the baseline and intervention in the same order. This makes the study vulnerable to the threat of sequence effects that could have influenced the students’ performance. Also, the absence of a maintenance phase does not provide information on lasting treatment effects. One last limitation is the lack of procedural fidelity or interobserver agreement that could help enhance the internal validity of this study.

Recommendations and Conclusion

Future recommendations include comparing the effects of using the MUSE in individuals with different IDD severity levels. This could enhance our understanding on how those with varying severity levels respond to using the MUSE. Additional future studies could investigate the effects of using different methods of guided mindfulness practice, such as a mindfulness app or another neurofeedback device, in young adults with IDD. This could provide insight into how young adults with IDD respond to various modes of the practice. One last recommendation is investigating how the use of the neurofeedback from the MUSE can promote positive mental health outcomes such as anxiety and depression. Young adults with IDD are at an increased risk of developing mental health disorders, and practicing mindfulness may be one approach that can address this issue. As a result, it is imperative to understand how the practice can benefit and be fostered among those with IDD. The findings from this study provide partial support for the use of a wearable EEG device designed to provide neurofeedback to help promote state mindfulness for students with IDD. The results of this study further suggest that students with IDD can learn and practice mindfulness, with or without the aid of neurofeedback. Thus, continuing to promote the practice of mindfulness for individuals with IDD is one way to support the unique needs of these individuals.

Footnotes

Declaration of Conflicting Interests

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

Funding

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

ORCID iD

Amanda K. McMahon

References

Adkins

A. D.

Singh

A. N.

Winton

A. S.

McKeegan

G. F.

Singh

(2010). Using a mindfulness-based procedure in the community: Translating research to practice. Journal of Child and Family Studies, 19(2), 175–183.

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

Arch

J. J.

Craske

M. G.

(2006). Mechanisms of mindfulness: Emotion regulation following a focused breathing induction. Behavior Research and Therapy, 44(12), 1849–1858. https://doi.org/10.1016/j.brat.2005.12.007

Baden

D. A.

McLean

T. L.

Noakes

T. D.

St. Clair Gibson

. (2005). Effect of anticipation during unknown or unexpected exercise duration on rating of perceived exertion, affect, and physiological function. British Journal of Sports Medicine, 39, 742–746. https://doi.org/10.1136/bjsm.2004.01.016980

Baumeister

R. F.

Heatherton

T. F.

Tice

D. M.

(1994). Losing control: How and why people fail at self-regulation. Academic press.

Baumeister

R. F.

Vohs

K. D.

(2003). Self-regulation and the executive functioning of the self. Guilford Press.

Bishop

S. R.

Lau

Shapiro

Carlson

Anderson

N. D.

Carmody

Segal

Z. V.

Abbey

Speca

Velting

Devins

(2004). Mindfulness: A proposed operational definition. Clinical Psychology: Science and Practice, 11(3), 230–241. https://doi.org/10.1093/clipsy/bph077

Blishchak

D. M.

Schlosser

R. W.

(2003). Use of technology to support independent spelling by students with autism. Topics in Language Disorders, 23(4), 293–304.

Brown

K. W.

Creswell

J. D.

Ryan

R. M.

(Eds.). (2015). Handbook of mindfulness: Theory, research, and practice. Guilford Publications.

10.

Carter

S. L.

(2009). The social validity manual: A guide to subjective evaluation of behavior interventions. Academic Press.

11.

Chapman

M. J.

Hare

D. J.

Caton

Donalds

McInnis

Mitchell

(2013). The use of mindfulness with people with intellectual disabilities: A systematic review and narrative analysis. Mindfulness, 4(2), 179–189. https://doi.org/10.1007/s12671-013-0197-7

12.

Chapman

M. J.

Mitchell

(2013). Mindfully valuing people now: An evaluation of introduction to mindfulness workshops for people with intellectual disabilities. Mindfulness, 4(2), 168–178. https://doi.org/10.1007/s12671-012-0183-5

13.

Chiesa

Serretti

(2009). Mindfulness-based stress reduction for stress management in healthy people: A review and meta-analysis. The Journal of Alternative and Complementary Medicine, 15(5), 593–600. https://doi.org/10.1089/acm.2008.0495

14.

Cooper

S. A.

Smiley

Morrison

Williamson

Allan

(2007). Mental ill-health in adults with intellectual disabilities: Prevalence and associated factors. The British Journal of Psychiatry, 190(1), 27–35. https://doi.org/10.1192/bjp.bp.106.022483

15.

Currie

T. L.

McKenzie

Noone

(2019). The experiences of people with an intellectual disability of a mindfulness-based program. Mindfulness, 1–11. https://doi.org/10.1007/s12671-019-1095-4

16.

Deb

Thomas

Bright

(2001). Mental disorder in adults with intellectual disability. 2: The rate of behavior disorders among a community-based population aged between 16 and 64 years. Journal of Intellectual Disability Research, 45(6), 506–514. https://doi.org/10.1046/j.1365-2788.2001.00373.x

17.

De Bildt

Systema

Kraijer

Sparrow

Minderaa

(2005). Adaptive functioning and behavior problems in relation to level of education in children and adolescents with intellectual disability. Journal of Intellectual Dsiability Research, 49(9), 672–681.

18.

Dekker

M. C.

Koot

H. M.

(2003). DSM-IV disorders in children with borderline to moderate intellectual disability: Prevalence and impact. Journal of the American Academy of Child & Adolescent Psychiatry, 42(8), 915–922. https://doi.org/10.1097/01.CHI.0000046892.27264.1A

19.

Erlingsson

Brysiewicz

(2017). A hands-on guide to doing content analysis. African Journal of Emergency Medicine, 7(3), 93–99. https://doi.org/10.1016/j.afjem.2017.08.001

20.

Felver

J. C.

Doerner

Jones

Kaye

N. C.

Merrell

K. W.

(2013). Mindfulness in school psychology: Applications for intervention and professional practice. Psychology in the Schools, 50(6), 531–547. https://doi.org/10.1002/pits.21695

21.

Felver

J. C.

Felver

S. L.

Margolis

K. L.

Ravitch

N. K.

Romer

Horner

R. H.

(2017). Effectiveness and social validity of the soles of the feet mindfulness-based intervention with special education students. Contemporary School Psychology, 21(4), 358–368.

22.

Greco

L. A.

Baer

R. A.

Smith

G. T.

(2011). Assessing mindfulness in children and adolescents: Development and validation of the Child and Adolescent Mindfulness Measure (CAMM). Psychological Assessment, 23(3), 606–614. https://doi.org/10.1037/a0022819

23.

Harper

S. K.

Webb

T. L.

Rayner

(2013). The effectiveness of mindfulness-based interventions for supporting people with intellectual disabilities: A narrative review. Behavior Modification, 37(3), 431–453. https://doi.org/10.1177/0145445513476085

24.

Harris

J. C.

(2006). Intellectual disability: Understanding its development, causes, classification, evaluation, and treatment. Oxford University Press.

25.

Hashemi

Pino

L. J.

Moffat

Mathewson

K. J.

Aimone

Bennett

P. J.

Schmidt

L. A.

Sekuler

A. B.

(2016). Characterizing population EEG dynamics throughout adulthood. eNeuro, 3(6), 1–23. https://doi.org/10.1523/ENEURO.0275-16.2016

26.

Holzel

B. K.

Lazar

S. W.

Gard

Schuman-Olivier

Vago

D. R.

Ott

(2011). How does mindfulness meditation work? Proposing mechanisms of action from a conceptual and neural perspective. Perspectives on Psychological Science, 6(6), 537–559.

27.

Hölzel

B. K.

Ott

Hempel

Hackl

Wolf

Stark

Vaitl

(2007). Differential engagement of anterior cingulate and adjacent medial frontal cortex in adept meditators and non-meditators. Neuroscience Letters, 421(1), 16–21. https://doi.org/10.1016/j.neulet.2007.04.074

28.

Hulley

Bentley

Clough

Fishlock

Morrell

O’Brien

Radmore

(2008). Active and passive commuting to school: Influences on affect in primary school children. Research Quarterly for Exercise and Sport, 79(4), 525–534. https://doi.org/10.1080/02701367.2008.10599519

29.

Hwang

Y. S.

Kearney

(2013). A systematic review of mindfulness intervention for individuals with developmental disabilities: Long-term practice and long lasting effects. Research in Developmental Disabilities, 34(1), 314–326. https://doi.org/10.1016/j.ridd.2012.08.008

30.

Idusohan-Moizer

Sawicka

Dendle

Albany

(2015). Mindfulness-based cognitive therapy for adults with intellectual disabilities: An evaluation of the effectiveness of mindfulness in reducing symptoms of depression and anxiety. Journal of Intellectual Disability Research, 59(2), 93–104. https://doi.org/10.1111/jir.12082

31.

Kabat-Zinn

(1994). Wherever you go, there you are: Mindfulness meditation in everyday life. Hyperion.

32.

Kabat-Zinn

(2003). Mindfulness-based interventions in context: Past, present, and future. Clinical Psychology: Science and Practice, 10(2), 144–156. https://doi.org/10.1093/clipsy.bpg016

33.

Kabat-Zinn

Hanh

T. N.

(2013). Full catastrophe living: Using the wisdom of your body and mind to face stress, pain, and illness. Delta.

34.

Kabat-Zinn

Lipworth

Burney

(1985). The clinical use of mindfulness meditation for the self-regulation of chronic pain. Journal of Behavioral Medicine, 8(2), 163–190.

35.

Katusic

S. K.

Colligan

R. C.

Beard

C. M.

O’Fallon

W. M.

Bergstralh

E. J.

Jacobsen

S. J.

Kurland

L. T.

(1996). Mental retardation in a birth cohort, 1976–1980, Rochester, Minnesota. American Journal of Mental Retardation, 100(4), 335–344.

36.

Kouijzer

M. E.

de Moor

J. M.

Gerrits

B. J.

Buitelaar

J. K.

van Schie

H. T.

(2009). Long-term effects of neurofeedback treatment in autism. Research in Autism Spectrum Disorders, 3(2), 496–501. https://doi.org/10.1016/j.rasd.2008.10.003

37.

Kouijzer

M. E.

van Schie

H. T.

de Moor

J. M.

Gerrits

B. J.

Buitelaar

J. K.

(2010). Neurofeedback treatment in autism: Preliminary findings in behavioral, cognitive, and neurophysiological functioning. Research in Autism Spectrum Disorders, 4(3), 386–399. https://doi.org/10.1016/j.rasd.2009.10.007

38.

Kovacevic

Ritter

Tays

Moreno

McIntosh

A. R.

(2015). “My virtual dream”: Collective neurofeedback in an immersive art environment. PloS One, 10(7), 1–18. https://doi.org/10.1371/journal.pone.013129

39.

Krigolson

O. E.

Williams

C. C.

Norton

Hassall

C. D.

Colino

F. L.

(2017). Choosing MUSE: Validation of a low-cost, portable EEG system for ERP research. Frontiers in Neuroscience, 11, 1–10. https://doi.org/10.3389/fnins.2017.00109

40.

Ledford

J. R.

Gast

D. L.

(2018). Single case research methodology: Applications in special education and behavioral sciences. Routledge.

41.

Ledford

J. R.

Lane

J. D.

Severini

K. E.

(2018). Systematic use of visual analysis for assessing outcomes in single case design studies. Brain Impairment, 19(1), 4–17. https://doi.org/10.1017/BrImp.2017.16

42.

Lutz

Slagter

H. A.

Dunne

J. D.

Davidson

R. J.

(2008). Attention regulation and monitoring in meditation. Trends in Cognitive Sciences, 12(4), 163–169. https://doi.org/10.1016/j.tics.2008.01.005

43.

Luxton

D. D.

McCann

R. A.

Bush

N. E.

Mishkind

M. C.

Reger

G. M.

(2011). mHealth for mental health: Integrating smartphone technology in behavioral healthcare. Professional Psychology: Research and Practice, 42(6), 505–512. https://doi.org/10.1037/a0024485

44.

Marcengo

Sabena

Crea

(2017). Mindfulness and asynchronous neurofeedback: Coping with mind wandering. In Editor

A. M.

Editor

S. C.

(Eds.), Universal access in human–computer interaction. Human and technological environments. Springer International Publishing. https://doi.org/10.1007/978-3-319-58700-4

45.

Masicampo

E. J.

Baumeister

R. F.

(2007). Relating mindfulness and self-regulatory processes. Psychological Inquiry, 18(4), 255–258. https://doi.org/10.1080/10478400701598363

46.

Nader-Grosbois

(2014). Self-perception, self-regulation and metacognition in adolescents with intellectual disability. Research in Developmental Disabilities, 35(6), 1334–1348. https://doi.org/10.1016/j.ridd.2014.03.033

47.

Nugent

(2009). Analyzing single system design data. Oxford University Press.

48.

Plaza

Demarzo

M. M. P.

Herrera-Mercadal

García-Campayo

(2013). Mindfulness-based mobile applications: Literature review and analysis of current features. JMIR mHealth and uHealth, 1(2), 1–16. https://doi.org/10.2196/mhealth.2733

49.

Remmers

Topolinski

Koole

S. L.

(2016). Why being mindful may have more benefits than you realize: Mindfulness improves both explicit and implicit mood regulation. Mindfulness, 7(4), 829–837. https://doi.org/10.1007/s12671-016-0520-1

50.

Sas

Chopra

(2015). MeditAid: A wearable adaptive neurofeedback-based system for training mindfulness state. Personal and Ubiquitous Computing, 19(7), 1169–1182. https://doi.org/10.1007/s00779-015-0870-z

51.

Scolnick

(2005). Effects of electroencephalogram biofeedback with Asperger’s syndrome. International Journal of Rehabilitation Research, 28(2), 159–163.

52.

Sears

Kraus

(2009). I think therefore I om: Cognitive distortions and coping style as mediators for the effects of mindfulness meditation on anxiety, positive and negative affect, and hope. Journal of Clinical Psychology, 65(6), 561–573. https://doi.org/10.1002/jclp.20543

53.

Segal

Z. V.

Teasdale

J. D.

Williams

J. M.

Gemar

M. C.

(2002). The mindfulness-based cognitive therapy adherence scale: Inter-rater reliability, adherence to protocol and treatment distinctiveness. Clinical Psychology and Psychotherapy, 9(2), 131–138. https://doi.org/10.1002/cpp.320

54.

Simonoff

Pickles

Charman

Chandler

Loucas

Baird

(2008). Psychiatric disorders in children with autism spectrum disorders: Prevalence, comorbidity, and associated factors in a population-derived sample. Journal of the American Academy of Child and Adolescent Psychiatry, 47(8), 921–929. https://doi.org/10.1097/CHI.0b013e318179964f

55.

Singh

N. N.

Lancioni

G. E.

Winton

A. S.

Adkins

A. D.

Singh

A. N.

(2007). Mindfulness training assists individuals with moderate mental retardation to maintain their community placements. Behavior Modification, 31(6), 800–814. https://doi.org/10.1177/0145445507300925

56.

Singh

N. N.

Lancioni

G. E.

Winton

A. S.

Adkins

A. D.

Wahler

R. G.

Sabaawi

Singh

(2007). Individuals with mental illness can control their aggressive behavior through mindfulness training. Behavior Modification, 31(3), 313–328. https://doi.org/10.1177/0145445506293585

57.

Singh

N. N.

Lancioni

G. E.

Winton

A. S.

Singh

A. N.

Adkins

A. D.

Singh

(2008). Clinical and benefit: Cost outcomes of teaching a mindfulness-based procedure to adult offenders with intellectual disabilities. Behavior Modification, 32(5), 622–637. https://doi.org/10.1177/0145445508315854

58.

Singh

N. N.

Wahler

R. G.

Adkins

A. D.

Myers

R. E.

, & Mindfulness Research Group. (2003). Soles of the Feet: A mindfulness-based self-control intervention for aggression by an individual with mild mental retardation and mental illness. Research in Developmental Disabilities, 24(3), 158–169. https://doi.org/10.1016/S0891-4222(03)00026-X

59.

Tacón

A. M.

McComb

Caldera

Randolph

(2003). Mindfulness meditation, anxiety reduction, and heart disease: A pilot study. Family & Community Health, 26(1), 25–33.

60.

Tammen

V. V.

(1996). Elite middle and long distance runners associative/dissociative coping. Journal of Applied Sport Psychology, 8, 1–8. https://doi.org/10.1080/10413209608406304

61.

Tice

D. M.

Baumeister

R. F.

Shmueli

Muraven

(2007). Restoring the self: Positive affect helps improve self-regulation following ego depletion. Journal of Experimental Social Psychology, 43(3), 379–384. https://doi.org/10.1016/j/jesp.2006.05.007

62.

Vieillevoye

Nader-Grosbois

(2008). Self-regulation during pretend play in children with intellectual disability and in normally developing children. Research in Developmental Disabilities, 29(3), 256–272. https://doi.org/10.1016/j.ridd.2007.05.003

63.

Wehmeyer

M. L.

Palmer

S. B.

Smith

S. J.

Parent

Davies

D. K.

Stock

(2006). Technology use by people with intellectual and developmental disabilities to support employment activities: A single-subject design meta-analysis. Journal of Vocational Rehabilitation, 24(2), 81–86. https://doi.org/1052-2263/06

64.

Wehmeyer

M. L.

Yeager

Bolding

Agran

Hughes

(2003). The effects of self-regulation strategies on goal attainment for students with developmental disabilities in general education classrooms. Journal of Developmental and Physical Disabilities, 15(1), 79–91.

65.

What Works Clearinghouse. (2017). Standards handbook version 4.0. https://ies.ed.gov/ncee/wwc/Docs/referenceresources/wwc_standards_handbook_v4.pdf

66.

Wolf

M. M.

(1978). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart. Journal of Applied Behavior Analysis, 11, 203–214. https://doi.org/10.1901/jaba.1978.11-203