Feasibility and Efficacy of the Alert Program® for Children with Attention-Deficit/Hyperactivity Disorder

Abstract

This study explored the feasibility and initial efficacy of a sensorimotor intervention to improve symptoms of attention-deficit/hyperactivity disorder (ADHD). Twenty-seven children (ages 8–12 years) with ADHD and their parents participated in an 8-week group intervention based on The Alert Program® for Self-Regulation (AP). Families were taught to recognize child arousal states and to use sensorimotor strategies to manage levels of alertness. Parent and teacher reports of child attention symptoms were collected at baseline, before and after intervention. Objective ratings of child problem behaviours and use of sensorimotor strategies during computerized tasks of visual and auditory attention were also coded before and after intervention. Parents and children endorsed high acceptability and satisfaction for the AP treatment. Parental ratings indicated increased knowledge and use of sensorimotor strategies, and decreased child ADHD symptoms at home from pre-AP to post-AP. However, no significant changes in child outcomes were reported by teachers. Unexpectedly, observed child problem behaviours during the visual attention task increased from pre-AP to post-AP. The AP was received positively by parents and children with improvements in regulation strategies and child attention at home, but more work needs to be done to generalize the effects to school and other peer settings.

Keywords

attention-deficit/hyperactivity disorder Alert Program attention regulation sensorimotor strategies group intervention

Attention-deficit/hyperactivity disorder (ADHD) is a childhood condition with significant difficulties in inattention and/or hyperactivity-impulsivity with daily impacts in multiple settings (American Psychiatric Association, 2013). Treatments for ADHD include pharmacological (e.g., stimulant medication) and psychosocial (e.g., behavioural parent training) approaches (Wolraich et al., 2019). Although these well-established treatments target the child’s neurochemistry and environmental supports, few interventions have successfully empowered children to regulate their own attention through direct skills training. Mindfulness-based interventions have shown some promise in improving ADHD symptoms in children, particularly with regards to inattention more than hyperactivity-impulsivity (Oliva et al., 2021). However, this top-down approach emphasizing cognitive control to impact behaviour may be more challenging for children with ADHD who suffer from executive dysfunction (Arnsten, 2009). Alternatively, a bottom-up approach targeting concrete sensory and/or motor inputs may be more engaging and readily implemented by children with ADHD. Moreover, the optimal stimulation theory has proposed that children with ADHD need to learn how to compensate for over- or under-stimulation in their environments to better manage their attentional and behavioural challenges (S. Zentall & T. Zentall, 1983). For instance, hand fidgets have been used to reduce hyperactivity and improve math task completion among children with attention problems (Kercood et al., 2007), and physical activity has been shown to reduce attentional symptoms in children with ADHD (Hoza et al., 2015; Ziereis & Jansen, 2015).

One program that focuses on self-regulation through bottom-up sensorimotor strategies is “How Does Your Engine Run?”® The Alert Program® for Self-Regulation (AP; Williams & Shellenberger, 1996). The AP teaches children to recognize their arousal states and to use sensorimotor strategies during sub-optimal levels of alertness. The AP has been used with a variety of populations including children with fetal alcohol spectrum disorders and emotional problems. Studies have shown that children who participate in the AP have improved regulation of emotion and impulses (Barnes et al., 2008; Mac Cobb et al., 2014; Nash et al., 2018; Wells et al., 2012). Few studies have used the AP for children with ADHD. Swaminathan and Nandgaonkar (2016) examined a 12-week program of biweekly therapy sessions using components from the AP with children who were diagnosed with ADHD, and found improvements in sensory processing, modulation, and behaviour/emotional responses. Mah and Doherty (2021) conducted a feasibility study examining the effects of the AP on children with comorbid ADHD and sensory processing difficulties. They found improved knowledge and use of sensorimotor strategies, as well as improvements in child ADHD symptoms after parent-child dyads participated in a 4-week AP group, with effects maintained at 3-month follow-up. However, these studies were limited by small sample sizes and/or narrow outcome measures (e.g., parent self-report only).

In this study, we examined the feasibility and efficacy of an 8-week AP group for clinically-referred children with ADHD. By doubling the treatment duration of the AP compared to Mah and Doherty (2021), we hoped the increased intervention dosage would contribute to better solidification and generalization of skills. Additionally, our study measured outcomes through both parent- and teacher-reports, and objective scoring of observed child behaviour by blinded coders. We expected that parents and children would find the AP acceptable and be satisfied with the intervention. We also predicted that families would have greater knowledge and show greater use of sensorimotor strategies after the program compared to before. Moreover, we hypothesized that children would show fewer ADHD symptoms and problem behaviours after the AP as reported by parents, teachers, and objective coders. Finally, we predicted that families who showed greater treatment engagement would have greater improvements post-treatment.

Methods

Participants

Children between the ages of 8 and 12 years who have an ADHD diagnosis participated, along with at least one parent/guardian (see Table 1 for demographic information). This study was conducted within the outpatient ADHD clinic at a tertiary children’s hospital. Families were referred by psychiatrists and psychologists within the clinic after confirming child ADHD diagnosis through a diagnostic assessment (consisting of a clinical interview and review of parent and teacher rating scales of child attention and behavior). To be eligible, children needed to be able to participate in a group setting (e.g., tolerate being in the same room with other children) and be stable on their ADHD medication (if taking any). Most children were taking medication during the study, with the over half (55.56%) on stimulants (e.g., Adderall), and the others on non-stimulants (Strattera, Intuniv, and Celexa). Families were excluded from the study if children had unmanaged ADHD symptoms, psychosis, an intellectual disability, or autism spectrum disorder. Those who did not speak and understand English, had previously completed an AP group, and/or were concurrently participating in behavioural parent interventions were also excluded.

Table 1.

Family Demographics.

Characteristic	%	Mean	SD	Range	Missing data
Child age (Years)		9.96	1.18	96.00 to 143.00
Child grade		4.56	1.23	3 to 7
Child gender	Male	Female
Child gender	81.48% (n = 22)	18.52% (n = 5)
Child on ADHD medication	Yes	No			7.41% (n = 2)
Child on ADHD medication	66.67% (n = 18)	25.93% (n = 7)
Parent age (Years)		43.17	4.01	28 to 52
Parent gender	Male	Female
Parent gender	18.52% (n = 5)	81.48% (n = 22)
Parent education	High school or equivalent	Some college/university	College/university	Graduate school	7.41% (n = 2)
Parent education	18.52% (n = 5)	14.81% (n = 4)	44.44% (n = 12)	14.81% (n = 4)
Parent employment	Not employed	Part-time	Full-time	Self-employed	7.41% (n = 2)
Parent employment	7.41% (n = 2)	14.81% (n = 4)	55.55% (n = 15)	14.81% (n = 4)
Parent income	$10,000-$49,999	$50,000-$99,999	$100,000-$149,999	$150,000+
Parent income	14.81% (n = 4)	18.52% (n = 5)	29.63% (n = 8)	18.52% (n = 5)	18.52% (n = 5)
Parent ethnicity	White	Asian	Aboriginal	Latinx	7.41% (n = 2)
	59.26% (n = 16)	11.11% (n = 3)	7.41% (n = 2)	7.41% (n = 2)
	Multiethnic
	7.41% (n = 2)
Marital status	Married	Separated/Divorced	Common-law		7.41% (n = 2)
Marital status	74.07% (n = 20)	14.81% (n = 4)	3.70% (n = 1)

Measures

Demographics and Background Questionnaire

This is a parent-report questionnaire which gathered information regarding demographic characteristics (e.g., parental age, child’s age, ethnicity) and the child’s developmental and treatment history (e.g., birth, speech/motor delays, previous/current therapies or medication).

Sensory Processing

The Short Sensory Profile 2 (SSP-2; Dunn, 2014) is a 34-item parent-report questionnaire which measures children’s sensory processing across six domains (auditory, visual, touch, movement, body position, and oral) and their behavioural responses associated with sensory processing. Parents respond using a 5-point Likert scale from 1 (almost never) to 5 (almost always). The child is then assigned scores across four domains: the degree to which they obtain sensory input (seeking), are bothered by sensory input (avoiding), detect sensory input (sensitivity), and miss sensory input (registration/bystander). These scores correspond with percentiles which illustrate how the child’s scores compare to others (much less than others, less than others, just like the majority of others, more than others, much more than others).

Sensory and Motor Strategies

The Sensory and Motor Strategies Questionnaire (SMSQ; Mah et al., 2021) is a 32-item parent-report measure that assesses a family’s knowledge about the eight sensorimotor strategies emphasized in the AP (i.e., engine levels, speedometers, tool kit, and tools for each of the five senses), as well as the frequency and level of independence with which they used each strategy. Each item is rated on a 5-point scale (0% or none to 100% or excellent/daily), with higher scores indicating greater knowledge, frequency or independence of use. Internal consistency of this measure was high (Cronbach’s α = .858).

Child Attention

Parent and teacher ratings of inattentive and hyperactive-impulsive symptoms were gathered using the 30-item ADHD Rating Scale-5 (DuPaul & Power, 2016). Items are rated on a 4-point Likert scale (0 - never to 3 – very often), with higher scores reflecting greater difficulties with attention.

Coding of Observed Child Behaviour

A behavior coding system was adapted from the Restricted Academic Situation (Barkley, 1990; refer to Appendix) and used to code child behaviour during the Attention Network Task for Children (ANT-C; refer to procedure for details). Problem behaviours and sensory-motor regulation behaviours were coded. Problem behaviours consisted of: off-task behaviours, fidgeting, vocalizing, plays with objects, and out of seat. Sensory-motor regulation behaviours consisted of using tools in each of the five sensorimotor categories: look, listen, mouth, move, and touch. Behaviour was coded as present if observed within every 15-second interval across the 15-minute observation period.

Three coders trained using the coding manual with video recordings from pilot cases, until independent coders consistently achieved agreement of 80% or above. After the initial training period, coders continued to meet on a weekly basis to ensure continued adherence to the coding manual. 20% of the videotaped sessions were randomly selected to be double-coded for inter-rater reliability. Intraclass correlations were calculated between the coders across all dimensions; average ICCs were high at .827.

Group Satisfaction Questionnaire

This questionnaire asked parents/guardians about their acceptability of, and satisfaction with, the AP group intervention. There were seven questions adapted from the Treatment Evaluation Inventory Short Form (TEI-SF; Kelley et al., 1989) about treatment acceptability (e.g., belief that intervention strategies are effective for improvements), and six questions regarding satisfaction of group format (e.g., balance of activity and discussion). Items were rated on a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). Ratings were averaged and higher scores represented greater acceptance and satisfaction of the AP.

Children were also asked three group satisfaction questions, using a 5-point Likert scale that ranged from “1” (A little) to “5” (A lot), regarding how much they learned, how much fun they had, and how much they will try to use the tools at home. Ratings were averaged and higher scores represented greater child satisfaction of the AP.

Treatment Engagement

To assess treatment engagement, group facilitators recorded weekly attendance, and made weekly ratings of the level of child participation and parent/guardian participation (0: not engaged to 4: actively engaged 100% of the time), as well as the amount of weekly homework completion (0: none, 1: some, 2: all).

Procedure

This research was reviewed and approved by the UBC C&W research ethics board. Interested and eligible parents and children were provided with consent and assent forms to review and sign prior to enrollment.

Baseline measures were completed 1 month before the first AP session (see Table 2). Also at this time, the primary group facilitator met with each family individually to discuss the child and treatment expectations. Then, 1 week before the first AP session (pre-AP), parents participated in an introductory session about the AP and completed outcome measures, while children concurrently participated in a computerized attention task in a group setting (see Attention Network Task below). Then, families participated in the 8-week AP intervention (see Alert Program below). One week after the final AP session (post-AP), parents participated in a group debriefing session and completed outcome measures, while children once again concurrently participated in the attention task in a group setting.

Table 2.

Study Timeline.

Timepoint	Baseline (1-month before AP)	Pre-AP (1-week before AP)	AP (8-week intervention)	Post-AP (1-week after AP)
Measures	Demographics, SSP-2, ADHD-5 (parent, teacher)	SMSQ, ADHD-5 (parent, teacher), ANT-C behaviour coding	Treatment engagement	SMSQ, ADHD-5 (parent, teacher), group satisfactionANT-C behaviour coding
Activity	Meet and greet	Parent introduction	8 week AP group	Parent debrief

The Alert Program

The AP (Williams & Shellenberger, 1996) was designed to teach children, parents, and teachers how to recognize arousal states and help children recognize and expand their repertoire of self-regulation strategies. In this study, the AP ran once a week, for 90-minutes each session, for eight consecutive weeks. Each group consisted of three to six parent-child pairs. An occupational therapist trained on the AP was the primary facilitator of all the sessions, and was supported by a secondary clinician (i.e., nurse clinician or psychologist). Each session consisted of didactic education presented on structured PowerPoint presentations and handouts about sensorimotor strategies for self-regulation, as well as hands-on activities to practice applying the strategies (see Table 3 for session topics). To promote parental knowledge and trouble-shooting skills, parent-only psychoeducation sessions occurred at pre- and post-AP. Clinicians met after each session to debrief and check the intervention manual for fidelity. Information or activities missed due to time constraints were included in the following session.

Table 3.

Alert Program (AP) Group Sessions.

AP Session	Topic
Pre-AP parent session	Introduction to AP: Parent role, sensory processing, parent sensorimotor preferences
Session 1	Intro to engine speeds: AP orientation and terminology
Session 2	Sorting engine speeds: Sensory preferences, speedometers
Session 3	Changing engine by mouth: Breathing, chewing, tasting games
Session 4	Changing engine by move: 6 ways to move activities
Session 5	Changing engine by touch: Fidgets and tools
Session 6	Changing engine by look and listen: Visual and auditory stations
Session 7	Problem solving for home
Session 8	Problem solving for school and when tools are limited
Post-AP parent session	Debriefing: Generalization to home and school, use of incentives

Attention Network Task for Children

Child behaviours (i.e., off-task problem behaviours and use of sensorimotor strategies) were observed while children were engaged in the ANT-C, which includes child-friendly modifications based on the computerized, performance-based test used to assess the attentional networks of alerting, orienting, and executive function by Fan et al. (2002). Two modified versions were used in this study: 1) a visual alertness task in which a target image is shown above a grid of nine comparison images while a blinking border highlights each image in the grid sequentially, and the child presses a key when the highlighted image matches the target; and 2) an auditory Stroop task in which the child listens to a series of words (i.e., high, low, day, or tah) presented one at a time in either a high, low, or neutral pitch, and the child presses one of two keys to indicate whether the pitch is high or low, but refrains from responding when the word “tah” is presented. The visual and auditory tasks were presented in a counter-balanced order for each group of participants across pre-AP and post-AP time points.

To simulate independent work times requiring sustained mental effort in a classroom environment (which is often a challenging time for children with ADHD), each child completed the tasks individually on their own laptop but in a group setting, such that the other peers participating in their AP group were also present and arranged in a cluster seating arrangement (i.e., six desks in a rectangle facing each other). A research assistant remained in the corner of the room to monitor the group and be available to answer questions if needed. This took place in a room with a one-way glass mirror, and cameras on the ceiling were used to video record the sessions, which were later used for behavioural coding.

Data Analysis

All analyses were conducted using SPSS version 24. Available case analysis was used, such that participants without observed outcomes (i.e., those who dropped-out and did not complete the post-treatment data) were excluded. The Type-I error rate of 0.05 was used for all analyses. Normality of the data was assessed and no corrections were needed. Repeated measures Analysis of Variance (ANOVAs) were run to examine differences in parental and teacher ratings of ADHD symptoms across three timepoints: baseline, pre-AP, and post-AP. Paired sample t-tests were used to examine differences from pre-AP to post-AP in participants’ SMSQ scores, as well as in the coded observations of child problem behaviours and use of sensorimotor tools during the visual and auditory attention tasks. Finally, correlations were conducted to test the relationships among treatment engagement and baseline sensory processing and ADHD symptoms with child outcomes post-treatment.

Results

Feasibility

Recruitment and Retention

Of the 69 families referred to the study, two did not meet inclusion criteria, nine could not commit to the time and/or location, 11 did not respond to the invite, and five were not interested in participating. Of the 42 families recruited, four did not begin the program (e.g., schedule conflict), six were assessed at baseline or in the early group sessions to be not appropriate for the program (e.g., child aggression), two could not complete the program (e.g., family emergency), and three had missing data. Thus, the final sample size in our study was 27.

Treatment Engagement

All families attended at least six out of eight sessions (M = 7.22, SD = 0.58), with 63.00% of families attending seven sessions and 29.60% of families attending eight sessions. Children had an average participation score of 3.22 (SD = 0.58) out of 4, and parents had an average participation score of 3.43 (SD = 0.44), both reflecting more than 75% engagement in weekly sessions. The average homework completion score per week was 1.07 (SD = 0.42) out of 2, reflecting some (but not all) home practice activities were completed in-between sessions.

Acceptability and Satisfaction

Overall, parents found the AP group intervention to be acceptable (M = 3.89, SD = 1.13) and were highly satisfied (M = 4.29, SD = 0.88). Specifically, most parents found the AP strategies to be applicable to their child’s daily routine (83.3% agreed or strongly agreed), and were willing to use the strategies to help with difficult daily routines (83.4% agreed or strongly agreed). The majority of parents had a positive experience in the AP (83.4% agreed or strongly agreed), and would recommend the program to others (77.7% agreed or strongly agreed). Similar to their parents, children also reported high levels of satisfaction (M = 4.11, SD = 0.66), specifically indicating a high degree of learning (M = 4.27, SD = 0.84) and fun (M = 4.44, SD = 1.13), and moderate intentions to use strategies at home (M = 3.61, SD = 1.11).

Initial Efficacy

Descriptive statistics and effect sizes of outcomes are presented in Table 4. Parents reported significantly greater knowledge and use of sensorimotor strategies post-AP (50% or 3–4 times per week) compared to pre-AP (close to 0% or not at all). On average the most frequently used strategies were the Listening Tools for the Ears (M = 3.52, SD = 0.89) and the Engine Levels terminology (M = 3.47, SD = 0.72), while the least frequently used strategy was the Touch Tools for the Hands (M = 2.24, SD = 0.64).

Table 4.

Descriptive Statistics and Effect Sizes.

Measure	Baseline Mean (SD)	Pre-AP Mean (SD)	Post-AP Mean (SD)	Test Statistic	Effect Size
SMSQ	—	1.37 (0.46)	3.17 (0.56)	t (20) = −12.73***	d = 2.78
Parent report ADHD symptoms	31.82 (9.32)	30.35 (6.91)	27.12 (7.00)	F (2, 32) = 3.58*	η² = .18
Teacher report ADHD symptoms	32.38 (11.12)	30.75 (11.90)	32.13 (14.71)	F (2, 14) = 0.19	η² = .03
Behavioural problems
Visual task	—	48.60 (38.59)	77.30 (43.10)	t (19) = −3.18*	d = 0.71
Auditory task	—	14.17 (25.27)	8.57 (13.52)	t (22) = 1.25	d = 0.26
Tool use
Visual task	—	46.40 (48.23)	48.45 (35.82)	t (19) = −0.16	d = 0.04
Auditory task	—	32.52 (37.97)	41.83 (27.98)	t (22) = −1.05	d = 0.22

Note. *p < .05, ***p < .001.

Effect size was interpreted as follows: d: 0.2 is small, 0.5 is medium, and 0.8 is large; η²: 0.01 is small, 0.06 is medium, and 0.14 is large.

There was a significant difference across time on parental ratings of total child ADHD symptoms. Follow-up tests indicated no significant change between baseline and pre-AP, and a decrease in total ADHD symptoms from pre-AP to post-AP [F (1,16) = 3.65, p = .074, η² = .19]. Specifically, there was a significant difference across time on parental ratings of child symptoms of inattention [F (2, 32) = 4.85, p = .014, η² = .23], but not hyperactivity [F (2, 32) = 1.027, p = .369, η² = .06]. Follow-up tests of child inattentive symptoms also revealed no significant change between baseline and pre-AP, and a decrease from pre-AP to post-AP [F (1,16) = 3.70, p = .072, η² = .19].

Eight of 27 teachers completed the outcome measures, and their reports of child ADHD symptoms showed no significant change between the three time points.

Observed Child Behaviours

Contrary to expectations, child problem behaviours observed on the visual attention task significantly increased from pre-AP to post-AP. Specifically, the number of off-task behaviours observed significantly increased from pre-AP (M = 31.30, SD = 17.63) to post-AP (M = 46.15, SD = 20.389), [F (1, 19) = 19.86, p < .001, η² = .51], as well as the number of vocalizations from pre-AP (M = 12.90, SD = 18.538) to post-AP (M = 21.55, SD = 19.185), [F (1, 19) = 4.393, p = .050, η² = .188]. There were no significant changes in the amount of fidgeting, play, and out of seat behaviours observed. There were also no significant changes in the number of sensorimotor tools used during the visual attention task from pre-to post-AP. On average, the most frequently used sensorimotor strategy used at during the visual task post-AP was the Tools for the Mouth (M = 23.80, SD = 23.85).

During the auditory attention network task, there were small, but non-significant effects found in the number of problem behaviours demonstrated, and the number of tools used, from pre-AP to post-AP. Specifically, the largest effect was a trend towards decreased amount of play observed from pre-AP (M = 3.09, SD = 8.64) to post-AP (M = 0.22, SD = 0.52), [F (1, 22) = 2.521, p = .127, η² = .103]. Again, the Mouth strategies were the most common tool chosen by children to use at post-AP (M = 23.65, SD = 19.52).

Relationships Between Outcomes

Treatment Engagement and Post-AP Outcomes

Significant correlations were found between: a) child treatment engagement and observed use of tools during auditory ANT-C post-treatment, r (21) = .494, p = .016; and b) child engagement and observed problem behaviours during auditory ANT-C post-treatment, r (21) = −.672, p < .001. A trend was found in a moderate correlation between homework completion and observed problem behaviours during auditory ANT-C post-AP, r (21) = −.387, p = .068. No significant relationships among parent participation and attendance with child outcomes post-AP were found.

Baseline Child Sensory and Attention Profiles and Post-AP Outcomes

With regards to sensory processing, significant correlations were found between a) baseline sensory seeking and use of Touch tools post-AP, r (17) = .655, p = .002; b) baseline sensory sensitivity and use of Listen tools post-AP, r (17) = .460, p = .047; and c) baseline total sensory processing difficulties and the total number of tools used during visual ANT-C at post-AP, r (15) = −.55, p = .021. With regards to attention difficulties, significant correlations were found between a) baseline hyperactivity and use of Touch tools post-AP, r (18) = .697, p = .001; b) baseline ADHD and the number of child problem behaviours seen during the visual attention task at post-AP, r (15) = .52, p = .031, which in turn was significantly and negatively correlated with the number of tools used, r (18) = −.60, p = .005.

Discussion

The current study found support for the feasibility of a group AP treatment. Parents reported high treatment acceptability and, along with their children, were highly satisfied with the treatment. However, there were mixed findings regarding the efficacy of the AP treatment. As predicted, parents reported increased use and knowledge of sensory and motor strategies, and they reported less child ADHD difficulties (specifically inattentive symptoms) after treatment. In addition, the more engaged children were during treatment, the more they improved in observed behaviour and use of sensorimotor strategies during post-AP auditory attention tasks. Contrary to hypotheses, there were no significant changes in ADHD symptoms as reported by teachers, and no significant improvements were observed in child behaviours and use of sensorimotor tools during attention network tasks. Rather, there were significant increases in off-task and vocalizing behaviours on the visual attention task after group participation.

Our findings replicated those previously found by Mah and Doherty (2021) in which the AP group was enjoyed by participating parents and children, and led to parent-reported improvements in knowledge and use of sensorimotor strategies and child ADHD symptoms. However, we are disappointed by the lack of gains in child ADHD symptoms and behaviours reported by teachers and observers. We speculate three possible explanations: 1) self-reporting bias, 2) data and procedural limitations, and 3) insufficient treatment application across settings. First, it is possible that participating parents were expecting an improvement in symptoms and these expectations affected their judgment of child behaviour, whereas teacher and observer ratings were more objective.

Second, only eight of 27 teachers completed the outcome measures, so teacher-report data is limited in power to detect changes as well as representativeness of the sample. Moreover, we believe that the increased child problem behaviours observed during visual attention tasks at post-AP were indicative of increased child social engagement resulting from strong friendships built throughout the previous 8 weeks of AP sessions together. This is in contrast to the inhibited behaviour shown at pre-AP when the children had not yet met each other. In fact, children with greater baseline ADHD symptoms were those that showed greater number of problem behaviours post-AP, and children with greater sensory processing difficulties used fewer tools during the visual attention task at post-AP. This same problem did not exist for the auditory attention task where the children were wearing wired headphones, reducing the likelihood of them leaving their seats and getting distracted by each other. This is consistent with studies showing that headphones delivering white noise decreased off-task behaviour (Cook et al., 2014) and improved recall (Söderlund et al., 2007). During this auditory attention task, we found that those who were more engaged during AP treatment were the ones that showed greater improvements in observed use of sensorimotor tools and on-task behaviours. Thus, although we administered the attention network tasks in a group setting for a more ecologically valid context, this approach may have limited our ability to capture more nuanced individual changes.

Third, it is possible that the 8-week group AP treatment alone is simply not powerful enough to generalize across settings. Perhaps the children were better able to apply the skills they learned in treatment and have improved behaviour at home because they were well-supported by their parents who had received the AP treatment at the same time. Teachers were not trained in AP concepts and so could not be expected to support the children in the classroom setting in this way. In fact, Mac Cobb et al. (2014) recommended a whole-school approach to AP treatment in order to educate teachers on AP concepts and to have them incorporate the strategies into the classroom. In addition, children and parents at home are often in a high child-to-adult ratio of support, whereas at school and during the group-based attention network task observations, children were exposed to distracting peers with minimal adult support. We know that children with ADHD have a performance deficit rather than a knowledge deficit (Barkley, 1997); that is, they often know what they should do, but fail to do it in the moment due to competing distractions or impulses. This underlies why traditional social skills training programs for children with ADHD have also demonstrated similarly limited efficacy (Antshel & Barkley, 2008). Thus, treatment effects are best when children with ADHD have supporting adults providing reminders at the point of performance in the natural environment (Mikami et al., 2017). Therefore, we expect that children require consistent scaffolding of support from adults in their immediate context before they can successfully implement the self-regulation strategies independently in challenging settings. We believe all three factors (i.e., parent reporting bias, data and procedural limitations, and insufficient treatment application across settings) could be at play concurrently.

We are intrigued by the greater impact of the AP on parental reports of child inattentive symptoms compared to hyperactive-impulsive symptoms. This matches the parental reports of the most frequently used sensorimotor strategy as the Listening tools (e.g., headphones), which are often more applicable to helping children with concentration by removing auditory distractions. Likewise, parents reported using the Touch tools (e.g., hand fidgets) least frequently, which are often more relevant for decreasing motor hyperactivity. This is consistent with our explorations of which aspects of the AP worked well for which types of child attention and sensory profiles. Children with greater baseline hyperactivity tended to have greater use of Touch tools after participating in the AP. Children with greater sensory seeking needs tended to have greater use of Touch tools post-treatment, whereas children with greater sensory sensitivity tended to have greater use of Listen tools post-treatment.

Limitations and Future Directions

This study was limited by a small sample size of 27 families. Also, data were collected at only three timepoints: 1 month, 1 week before and 1 week after the AP treatment. Future directions include examining a larger sample size, and collecting data at multiple timepoints during the multi-week AP treatment to track weekly progress, as well as longer-term follow-up (e.g., 3-, 6-, and/or 12 months after treatment) to see if treatment gains are maintained over time.

Only a limited number of completed teacher data was successfully collected. We also experienced some technical difficulties with the ANT computerized tasks (e.g., repetitive key strikes resulted in freezing the computer), which distracted the children. Additional objective measurements could be used in future studies, such as reports from the non-participating parent or other caregivers, behavioural coding in functional contexts (e.g., classroom observations, parent-child interactions during homework), neurocognitive measures of executive functioning (e.g., Nash et al., 2015), and neuroimaging (e.g., Nash et al., 2018). Furthermore, training teachers concurrently in the AP treatment and supporting children to apply the sensorimotor strategies in socially distracting situations with booster sessions may help to solidify and generalize the skills towards greater independence of self-regulation with greater impact on attention and behaviour across settings.

Supplemental Material

Supplemental Material - Feasibility and Efficacy of the Alert Program® for Children with Attention-Deficit/Hyperactivity Disorder

Supplemental Material for Feasibility and Efficacy of the Alert Program® for Children with Attention-Deficit/Hyperactivity Disorder by Janet WT Mah, Harleen Gill, and Miranda Doherty in Clinical Child Psychology and Psychiatry

Footnotes

Acknowledgements

Thanks to Helen Kennett-Bacon, Ainsley Boudreau, and Nerissa Perucho for their clinical support during the groups, and research assistants, Dana Cochrane, Laurissa Wilson, Wendy Li, and Nicole Carbert, for data collection and behavioural coding. We dedicate this paper to the memory of Christine Tipper who developed the computerized attention tasks.

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 work was supported by the BC Children's Hospital.

ORCID iD

Janet WT Mah

Supplemental Material

Supplemental material for this article is available online.

Author biography

Dr. Janet Mah is a psychologist and investigator at BC Children's Hospital, and a clinical assistant professor at the University of British Columbia. Harleen Gill has a B.Sc. in Behavioural Neuroscience from the University of British Columbia. She worked on this project as part of a directed studies program. Miranda Doherty is an occupational therapist and clinic head of the Provincial ADHD Program at BC Children's Hospital.

References

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

Antshel

K. M.

Barkley

(2008). Psychosocial interventions in attention deficit hyperactivity disorder. Child and Adolescent Psychiatric Clinics of North America, 17(2), 421–437. https://doi.org/10.1016/j.chc.2007.11.005

Arnsten

A. F. T.

(2009). The emerging neurobiology of attention deficit hyperactivity disorder: The key role of the prefrontal association cortex. The Journal of Pediatrics, 154(5), S22–S31. https://doi.org/10.1016/j.jpeds.2009.01.018

Barkley

R. A.

(1997). Behavioral inhibition, sustained attention, and executive functions: Constructing a unifying theory of ADHD. Psychological Bulletin, 121(1), 65–94. https://doi.org/10.1037/0033-2909.121.1.65

Barkley

R. A.

(1990). Tests and observational scales. In Barkley

R. A.

(Ed), Attention-deficit hyperactivity disorder: A handbook for diagnosis and treatment (pp. 327–353). Guilford Press.

Barnes

K. J.

Vogel

K. A.

Beck

A. J.

Schoenfeld

H. B.

Owen

S. V.

(2008). Self- regulation strategies of children with emotional disturbance. Physical and Occupational Therapy in Pediatrics, 28(4), 369–387. https://doi.org/10.1080/01942630802307127

Cook

Bradley-Johnson

Johnson

C. M.

(2014). Effects of white noise on off-task behavior and academic responding for children with ADHD. Journal of Applied Behavior Analysis, 47(1), 160–164. https://doi.org/10.1002/jaba.79

Dunn

(2014). Sensory profile-2. Pearson Publishing.

DuPaul

G. J.

Power

T. J.

(2016). ADHD Rating Scale-5 for children and adolescents: Checklists, norms, and clinical interpretation. Guildford Press.

10.

Fan

McCandliss

B. D.

Sommer

Raz

Posner

M. I.

(2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 14(3), 340–347. https://doi.org/10.1162/089892902317361886

11.

Hoza

Smith

A. L.

Shoulberg

E. K.

Linnea

K. S.

Dorsch

T. E.

Blazo

J. A.

Alerding

C. M.

McCabe

G. P.

(2015). A randomized trial examining the effects of aerobic physical activity on attention-deficit/hyperactivity disorder symptoms in young children. Journal of Abnormal Child Psychology, 43(4), 655–667. https://doi.org/10.1007/s10802-014-9929-y

12.

Kelley

M. L.

Heffer

R. W.

Gresham

F. M.

Elliott

S. N.

(1989). Development of a modified treatment evaluation inventory. Journal of Psychopathology and Behavioral Assessment, 11(3), 235–247. https://doi.org/10.1007/bf00960495

13.

Kercood

Grskovic

J. A.

Lee

D. L.

Emmert

(2007). The effects of fine motor movement and tactile stimulation on the math problem solving of students with attention problems. Journal of Behavioral Education, 16(4), 303–310. https://doi.org/10.1007/s10864-007-9042-1

14.

Mac Cobb

Fitzgerald

Lanigan-O'Keeffe

Irwin

Mellerick

(2014). Students with social, emotional, and behavioral difficulties: The Alert Program trial in post-primary schools. Journal of Occupational Therapy, Schools, and Early Intervention, 7(2), 106–119. https://doi.org/10.1080/19411243.2014.930606

15.

Mah

J. W. T.

Doherty

(2021). Sensorimotor intervention group for children with ADHD and sensory processing difficulties: A feasibility study. Journal of Child and Family Studies, 30(2), 447–459. https://doi.org/10.1007/s10826-021-01900-y

16.

Mikami

A. Y.

Smit

Khalis

(2017). Social skills training and ADHD—what works? Current Psychiatry Reports, 19(12), 1–9.

17.

Nash

Stevens

Clairman

Rovet

(2017). Preliminary findings that a targeted intervention leads to altered brain function in children with fetal alcohol spectrum disorder. Brain Sciences, 8(1), 7. https://doi.org/10.3390/brainsci8010007.

18.

Nash

Stevens

Greenbaum

Weiner

Koren

Rovet

(2015). Improving executive functioning in children with fetal alcohol spectrum disorders. Child Neuropsychology: A Journal on Normal and Abnormal Development in Childhood and Adolescence, 21(2), 191–209. https://doi.org/10.1080/09297049.2014.889110

19.

Oliva

Malandrone

di Girolamo

Mirabella

Colombi

Carletto

Ostacoli

(2021). The efficacy of mindfulness-based interventions in attention-deficit/hyperactivity disorder beyond core symptoms: A systematic review, meta-analysis, and meta-regression. Journal of Affective Disorders, 292, 475–486. https://doi.org/10.1016/j.jad.2021.05.068

20.

Söderlund

Sikström

Smart

(2007). Listen to the noise: Noise is beneficial for cognitive performance in ADHD. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 48(8), 840–847. https://doi.org/10.1111/j.1469-7610.2007.01749.x

21.

Swaminathan

Nandgaonkar

H. P.

(2016). Effect of fostering self-regulation in children with attention deficit hyperactivity disorder. Indian Journal of Occupational Therapy, 48(3), 79–83. https://www.researchgate.net/publication/325153729_Effect_of_fostering_self-regulation_in_children_with_Attention_Deficit_Hyperactivity_Disorder

22.

Wells

A. M.

Chasnoff

I. J.

Schmidt

C. A.

Telford

Schwartz

L. D.

(2012, Neurocognitive habilitation therapy for children with fetal alcohol spectrum disorders: An adaptation of the Alert Program®. The American Journal of Occupational Therapy: Official Publication of the American Occupational Therapy Association, 66(1), 24–34. https://dx-doi-org.web.bisu.edu.cn/10.5014/ajot.2012.002691

23.

Williams

M. S.

Shellenberger

(1996). “How Does Your engine run?”® A leader’s guide to the Alert program for self-regulation. Albuquerque, NM: TherapyWorks, Inc.

24.

Wolraich

M. L.

Hagan

J. F.

Allan

Subcommittee on Children and Adolescents with Attention-Deficit/Hyperactive Disorder . (2019). Clinical practice guideline for the diagnosis, evaluation, and treatment of attention-deficit/hyperactivity disorder in children and adolescents. Pediatrics, 144(4), e20192528.

25.

Zentall

S. S.

Zentall

T. R.

(1983). Optimal stimulation: A model of disordered activity and performance in normal and deviant children. Psychological Bulletin, 94(3), 446–471. https://doi.org/10.1037/0033-2909.94.3.446

26.

Ziereis

Jansen

(2015). Effects of physical activity on executive function and motor performance in children with ADHD. Research in Developmental Disabilities, 38, 181–191. https://doi.org/10.1016/j.ridd.2014.12.005

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.33 MB