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Article

Promoting physical activity in people with intellectual and multiple disabilities through a basic technology-aided program

Giulio E Lancioni University of Bari, Italy

Nirbhay N Singh Augusta University, USA

Mark F O’Reilly University of Texas at Austin, USA

Jeff Sigafoos Victoria University of Wellington, New Zealand

Gloria Alberti Lega F. D’Oro Research Center, Italy

Viviana Perilli Lega F. D’Oro Research Center, Italy

Carmen Zimbaro Lega F. D’Oro Research Center, Italy

Adele Boccasini Lega F. D’Oro Research Center, Italy

Carlo Mazzola Lega F. D’Oro Research Center, Italy

Roberto Russo Lega F. D’Oro Research Center, Italy

Date accepted: 26 November 2016

Abstract This study assessed a technology-aided program (monitoring responding, and ensuring preferred stimulation and encouragements) for promoting physical activity with 11 participants with severe/ profound intellectual and multiple disabilities. Each participant was provided with an exercise device (e.g. a static bicycle and a stepper) and exposed to the program according to an ABAB design, in which A and B represented baseline and intervention phases, respectively. Data recording concerned (a) the participants’ responses with the exercise device (e.g. pedaling) during baseline and intervention phases and (b) their heart rates during the last intervention phase. The results showed that all participants had significant increases in responding with the exercise devices during the intervention phases. Heart-rate values during the intervention sessions indicated that the participants’ responding during those sessions mostly amounted to moderate-intensity physical activity, with potential benefits for their overall physical condition. Implications of the findings and questions for future research in the area were discussed.

Keywords intellectual disabilities, physical activity, multiple disabilities, technology-aided program, heart rates

Corresponding author: Giulio E Lancioni, Department of Neuroscience and Sense Organs, University of Bari, Corso Italia 23, 70121 Bari, Italy. Email: [email protected]

Journal of Intellectual Disabilities 2018, Vol. 22(2) 113–124

ª The Author(s) 2016 Reprints and permission:

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Introduction

There is a growing medical and social emphasis on the importance, for people in general, of increasing the level of physical activity and reducing sedentariness and passivity (Donnelly et al., 2016; Kohn et al., 2016; Zhang et al., 2016). This emphasis is directed at improving the chances of a healthy life and lowering the risks of, among others, cardiovascular diseases and diabetes (Merom et al., 2016; Mul et al., 2015). The activity guidelines provided for typical adults speak of a minimum of (a) 150 min per week of moderate-intensity physical activity (e.g. a brisk walk for 30 min a day and 5 days a week) or (b) 75 min per week of vigorous-intensity physical activity (Cavalieri et al., 2016; Warburton and Bredin, 2016). Moderate-intensity physical activity is defined as an activity engagement making the person’s heart rate (beats per minute) reach 50–70% of his or her maximum heart-rate level. Vigorous-intensity physical activity is defined as an activity engagement making the person’s heart rate reach 70–85% of his or her maximum heart- rate level (Gellish et al., 2007; Waninge et al., 2013). A commonly used formula for estimating a person’s maximum heart rate consists of subtracting the person’s age from a preset value of 220 (Waninge et al., 2013).

The importance of increasing physical activity can be considered even greater in the case of persons with intellectual and multiple disabilities, given that these persons engage in lower levels of physical activity than their typical counterparts and tend to have comparatively larger health con- cerns (Bartlo and Klein, 2011; Dixon-Ibarra et al., 2017; Queralt et al., 2016; Woodmansee et al., 2016). While the inclusion of persons with intellectual and multiple disabilities in intervention initiatives aimed at increasing physical activity is widely supported, the intervention conditions to apply with these persons are not necessarily obvious. Indeed, there is uncertainty with regard to the strategies to use for engaging these persons in activity, the types of activities to adopt for these persons, and the way to measure activity intensity and impact (Chen and Ringenbach, 2016; Hinckson and Curtis, 2013; Houwen et al., 2014; Lloyd, 2016; Waninge et al., 2013; Warms, 2006).

It is reasonable to assume that the activity guidelines mentioned earlier for typical individuals may also be applied to persons with mild intellectual disabilities. In fact, these persons may have daily routines resembling those of their typical counterparts, are likely to follow instructions about the activities to carry out, may be adequately informed about the reasons for those activities, and may be easily motivated to endure the effort required by the activities (Lloyd, 2016; Queralt et al., 2016). For persons with severe/profound intellectual and multiple disabilities, the situation could be quite different. These persons may require staff supervision (i.e. verbal and physical guidance) to engage in physical activity because they are unable or unwilling to be active independently (Gonzàlez-Agüero et al., 2012). The need for extensive supervision would raise questions as to whether an intervention in this area is feasible. The use of treadmills or electric, stationary bicycles that automatically produce a preset pedaling cadence (i.e. assisted cycling therapy; Ringenbach et al., 2016) may alleviate the need for direct staff supervision only if the persons comply with the devices’ activity requirements. It is worth noting here that the use of extensive supervision or combinations of supervision and the aforementioned devices (a) would be seen as compelling the persons to accept a physical activity condition without promoting (ensuring) their self- determination and independence and (b) could cause those persons considerable stress and anxi- ety (Hill et al., 2008; Hillier et al., 2011; Russell et al., 2014).

With regard to these issues, research has shown that increases in physical activity (i.e. in physical effort) without clear, personal motivation can bring about sharp increases in the levels of cortisol (i.e. a steroid hormone, which is produced in response to stress and low blood glucose

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concentration) (Hoppmann and Klumb, 2006; Qi et al., 2016; VanBruggen et al., 2011). High levels of cortisol could have a number of negative effects (e.g. in terms of body weight, blood pressure, and mood) that might largely eclipse the benefits expected from increases in physical activity and heart rates (Bloeming-Wolbrink et al., 2012; Lense et al., 2013; Lydon et al., 2015; Taverniers et al., 2010).

A plausible approach for helping persons with severe/profound intellectual and multiple dis- abilities may require the use of a technology-aided program monitoring the persons’ physical activity and ensuring automatic delivery of preferred stimulation contingent on such activity (Chang et al., 2016, 2014; Lancioni et al., 2003; Shih et al., 2013; Taylor et al., 2016). Within this approach, the participants would be (a) motivated by the automatic stimulation delivery to carry out the activity independently (i.e. provided the stimulation is adequate to compensate for the effort required by the activity) and thus (b) unlikely to experience remarkable or sustained increases in the levels of cortisol (Qi et al., 2016; Wrosch et al., 2009). The research assessing this approach has shown positive results as to the possibility of helping the participants increase their level of activity, but the data available need to be taken with caution. In fact, only 16 participants were included in the studies listed earlier. Moreover, the level of activity was documented in terms of behavioral responses (e.g. pedaling responses), but not in terms of physiological measures (e.g. heart rates).

The present study was aimed at extending the assessment of the last approach (and related technology-aided program) with 11 new participants with severe/profound intellectual and mul- tiple disabilities by monitoring the participants’ behavioral responses and heart rates (Kazdin, 2011). Proving the effectiveness of the approach in increasing and sustaining behavioral responding (i.e. with different participants and across different situations or exercise devices) would represent a systematic replication of previous research findings (Kazdin, 2011). Documenting the participants’ heart rates during such responding would provide an additional piece of information essential for (a) determining the possible impact of the approach on the participants’ health condition and (b) formulating hypotheses as to the way this approach (or revised forms thereof) could be used in daily contexts (Chang et al., 2016).

Method

Participants

Table 1 lists the 11 participants (i.e. participants 1 to 11) involved in the study, their sex, age, and sensory or sensory-motor disabilities and the exercise device available for them (i.e. static bicycle, hand-pedaling kit, or stepper). The participants, who represented a convenience sample (Pedhazur and Schmelkin, 1991), were exposed to the study according to a single-case ABAB design (Barlow et al., 2009; see below). They had intellectual and sensory or sensory-motor disabilities subsequent to congenital encephalopathy and attended rehabilitation and care centers for persons affected by such disabilities. Their intellectual disabilities were reported (i.e. by the psychological services of the centers they attended) to be in the severe/profound range, but no formal testing was possible due to their condition. As to the sensory-motor situation, five participants were diagnosed with blindness; five participants presented with blindness or low vision and spasticity, legs impairment, or poor body balance; and one participant was affected by blindness and mild hearing loss.

The participants were reported to be largely sedentary, although all of them except participant 4 were able to walk short distances (e.g. from one room to another either accompanied by staff or

Lancioni et al. 115

following sound cues) and engage in simple physical exercise with the use of exercise devices such as static bicycles or steppers. In practice, walking instances occurred just few times per day. The use of exercise devices was fairly irregular and participants tended to be only partially active with them (i.e. interspersing engagement with periods of passivity). The participants’ physiotherapists and regular staff (a) considered an improved use of those devices helpful for increasing the par- ticipants’ level of physical activity, (b) agreed with the view of providing positive stimulation contingent on the participants’ active engagement with the devices, and (c) deemed such stimu- lation potentially adequate to compensate for the participants’ physical effort and thus possibly effective in motivating their engagement (Catania, 2012; Chang et al., 2016; Lancioni et al., 2003; Shih et al., 2013). The participants could not be directly interviewed about their willingness to be involved in the study (given their disabilities), but their legal representatives provided informed consent for the study, which had been approved by the scientific and ethics committee of the Lega F. D’Oro, Osimo, Italy (P1221201510).

Setting, sessions, and research assistants

Baseline and intervention sessions were carried out in a quiet area of the rehabilitation and care centers that the participants attended. Sessions lasted 5 min (i.e. a time length considered suitable for the participants) and were generally implemented three times a day (i.e. during the morning or during the afternoon, with intervals between sessions of about or more than 10 min) or four times a day. In the latter case, two sessions would occur in the morning and two in the afternoon, with intervals between subsequent sessions (i.e. as mentioned earlier). Five research assistants experi- enced in the use of technology-aided programs with persons with multiple disabilities were in charge of the sessions (i.e. of the use of the exercise-related technology), of recording the participants’ heart rates, and of applying occasional instances of response guidance (i.e. of verbally and physically guiding the participant to perform two leg-pedaling responses, hand-pedaling responses, or foot/step responses) during the baseline and the introductory sessions preceding the intervention (see below).

Exercise devices, technology, responses, stimuli, and encouragements

The exercise devices included static bicycles, a hand-pedaling kit placed on the table in front of the participant, and steppers used in combination with an adapted support structure for the participants

Table 1. Participants’ sex, age, and sensory or sensory-motor disabilities, and exercise devices.

Participants Sex Age (years) Disabilities Exercise devices

1 Male 44 Blindness and mild spasticity Stepper 2 Male 50 Blindness Static bicycle 3 Female 25 Low vision and severe legs impairment Hand-pedaling kit 4 Male 35 Blindness Static bicycle 5 Male 37 Blindness Static bicycle 6 Male 18 Blindness Static bicycle 7 Female 38 Blindness and poor body balance Static bicycle 8 Female 44 Blindness and poor body balance Static bicycle 9 Male 42 Blindness and mild hearing loss Static bicycle 10 Male 26 Blindness and mild spasticity Stepper 11 Male 39 Blindness Stepper

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to hold on and keep balance while moving their feet and legs. Each of the devices was used in connection with two optic sensors that detected the participants’ responses (see below) and trig- gered a computer system set up to record those responses (throughout all sessions of the study) and deliver/activate various types of stimuli contingent on those responses as well as verbal encour- agements (during the intervention sessions of the study). The optic sensors used for the static bicycles and the hand-pedaling kit were on one side of each pedal or on the floor/table (i.e. under the pedals) and were activated by the left and the right pedal, respectively, as the pedal reached its closest proximity to the floor/table. The optic sensors used for the steppers were attached to the devices’ frames and activated by the right and the left foot, as the metal base supporting the foot neared the frame.

The responses consisted of (a) half pedaling cycles (each recorded automatically by the computer system, as a pedal reached its lowest position and activated an optic sensor) in relation to the bicycles and the hand-pedaling kit and (b) left or right foot-base downward movements (with the foot-base nearing the stepper’s frame). These responses/movements, like the half pedaling cycles, were recorded automatically by the computer system in connection with the activation of the optic sensors.

The stimuli that the participants received contingent on their responses during the intervention phases of the study (see below) could involve, among others, music and familiar voices, combi- nations of auditory and vibratory events, and/or light displays. Stimuli were rotated during the sessions to ensure variation in terms of stimulation inputs and possibly maintain high levels of motivation (Kazdin, 2001). The stimuli selected for each participant were deemed preferred for him or her based on staff’s reports and on direct screening. Screening involved 15 or more non- consecutive, 10-s presentations of each of several potentially attractive stimuli. A stimulus was selected/retained for use during the study only if the two research assistants conducting the screening agreed that it produced positive reactions (e.g. alerting, orienting, or smiling) in 60% or more of the presentations.

Procedural conditions and data analysis

Each participant was exposed to an ABAB design, in which A and B represented baseline and intervention phases, respectively (Barlow et al., 2009). The intervention phases (with the automatic, technology-regulated delivery of stimulation and verbal encouragements; see below) served to determine the effects of these variables used in combination with the exercise devices on the par- ticipants’ frequencies (increases) of behavioral responses (activity). The statistical significance of the response changes/increases from each baseline (A) to the subsequent intervention (B) phase of the single participants was assessed through the Kolmogorov–Smirnov test for two data sets (Siegel and Castellan, 1988), which was carried out via SPSS software (version 11 for Macintosh). To determine whether the participants’ response performance during the intervention sessions amounted to moderate-intensity physical activity (see Introduction), the following steps were taken. First, the participants’ heart rates were recorded during most sessions of the second intervention phase (i.e. when response engagement was consolidated). Second, the participants’ heart-rate means across those sessions were compared to the 50% levels of their estimated maximum heart rates. The means exceeding the 50% levels were considered representative of moderate-intensity physical activity (Gellish et al., 2007; Strath et al., 2013). Two formulas were used to estimate the maximum heart rates, that is, (a) the most common formula for typical individuals: ‘‘220 ! the individual’s age’’ and (b) the formula recommended for individuals with intellectual disabilities: ‘‘210 ! (0.56 " indi- vidual’s age) ! 15.5’’ (Fernhall et al., 2001; Fernhall and Pitetti, 2001; Waninge et al., 2013).

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Baseline I and II. At the start of each session of the baseline phases, the participant was accompanied to the exercise device selected for his or her physical activity (e.g. a static bicycle). The device, which was already familiar to him or her, was linked to the optic sensors and computer (so that responses were automatically recorded), but no stimulation for the responses and no automatic verbal encouragements were available. The research assistants applied response guidance (see setting, sessions, and research assistants) after 1 or 2 min of no responding.

Intervention I and II. Conditions were as in the baseline phases, with three exceptions, that is, (a) the participant’s responses (i.e. half pedaling cycles or foot-base downward movements) were fol- lowed by a brief period of preferred stimulation, (b) one to three words verbal encouragements (prompts) were presented by the computer after 10–15 s of no responding or at intervals of about 25 s, and (c) no response guidance was available from the research assistants except during two to four introductory sessions preceding the first intervention phase and serving to maximize the participants’ experience of the response–stimulation connection. The stimulation lasted 3 s during the first intervention phase. During the second intervention phase, the length of the stimulation was initially 3 s and then shortened to 2 s and occasionally to 1 s. Shortening the stimulation was thought to help increase (or maintain) the participants’ response frequencies in that any mini pause in response performance would lead to stimulation interruption (Kazdin, 2001; Pierce and Cheney, 2008).

Heart-rate measurements. Heart rates were recorded during most sessions of the second intervention phase. The recording was carried out using (a) a chest strap transmitter combined with a wrist receiver (Geonaute Onrhythm 310, with wireless chest strap, available from Decathlon, Italy) or (b) a running watch with built-in heart-rate monitor (Garmin Vivosmart HR, available from Garmin, Italy). Both devices automatically provided the mean heart-rate frequency per session.

Results

Table 2 reports the (a) participants’ numbers of sessions for the single baseline and intervention phases, with mean response frequencies per session and frequency ranges per phase, and (b) max- imum difference between cumulative distributions (D statistic and p values) for each baseline– intervention comparison. The first baseline phase included four to nine sessions. The mean response frequencies over that phase varied between 23 and 86 (see participants 4 and 5). The first intervention phase included 17 to 78 sessions (see participants 11 and 4). These differences were due to practical reasons more than to performance. The mean response frequencies over that phase varied between 124 and 285 (see participants 11 and 10). The frequency ranges for the single sessions of the phase varied from a minimum of 61 to a maximum of 408 (see participants 4 and 10).

The second baseline (5 to 14 sessions) showed frequency declines for all participants. The mean response frequencies over that phase varied between 37 and 116 (see participants 3 and 10). During the second intervention phase, the mean frequencies increased to levels that were generally higher than those achieved during the first intervention phase. Comparisons of each baseline with the subsequent intervention phase of the single participants through the Kolmogorov–Smirnov test yielded maximum differences between cumulative distributions (D values) of 1.0 except for the second baseline–intervention comparison of participant 1. For that comparison, a maximum dif- ference of 0.78 was found. The p values for those differences were always greater than 0.01.

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Table 3 reports (a) the participants’ heart-rate frequencies during the second intervention phase, that is, their overall mean frequencies across the 51 to 98 sessions during which measurements were taken and the range of mean values for the single sessions and (b) the 50% values of the participants’ maximum heart rates computed with the formulas: ‘‘220 ! the individual’s age’’ and ‘‘210 ! (0.56 " individual’s age) ! 15.5’’, respectively. Overall mean heart-rate frequencies exceeding the 50% level of the participants’ maximum rates were taken to indicate that their

Table 3. Heart-rate measurements (No) with overall mean heart-rate frequencies (M) and mean frequency ranges and estimated 50% levels of maximum heart rates.

Participants Measurements 50% levels 50% levels

No M Ranges (220 ! age) (210 ! [0.56 " age] ! 15.5)

1 89 92 81–105 88 85 2 86 96 81–108 85 83 3 98 78 67–94 98 90 4 51 94 72–119 93 87 5 79 85 72–103 92 87 6 96 95 83–115 101 92 7 93 98 80–128 91 87 8 87 96 84–125 88 85 9 84 87 77–104 89 85 10 90 124 104–140 97 90 11 86 97 87–117 91 86

Note: Frequency/level data points are rounded to the nearest full number values. The 50% levels exceeded by the overall mean heart-rate frequencies are in bold.

Table 2. Numbers of sessions (No) with mean response frequencies (M) per session, frequency ranges across baseline and intervention phases, and maximum difference between cumulative distributions (D statistic) for each baseline–intervention comparison.

Baseline I Intervention I D statistic (p values)

Baseline II Intervention II D statistic (p values)Participants No M Ranges No M Ranges No M Ranges No M Ranges

1 4 51 31–61 55 168 98–210 1.0 (**) 9 84 39–185 104 183 134–218 0.78 (**) 2 6 82 59–99 67 185 159–222 1.0 (**) 6 66 53–89 116 237 168–295 1.0 (**) 3 5 34 26–44 22 218 102–268 1.0 (**) 5 37 19–54 119 336 224–419 1.0 (**) 4 7 23 11–45 78 181 61–259 1.0 (**) 9 44 25–93 117 179 96–268 1.0 (**) 5 9 86 34–109 65 127 113–150 1.0 (**) 14 90 55–118 123 138 121–167 1.0 (**) 6 5 35 9–54 54 126 65–179 1.0 (**) 7 53 19–69 141 140 90–221 1.0 (**) 7 5 37 31–43 30 160 124–213 1.0 (**) 9 88 51–108 103 341 198–443 1.0 (**) 8 5 32 21–39 20 147 129–162 1.0 (**) 5 70 42–94 99 198 145–286 1.0 (**) 9 6 47 40–56 30 136 101–180 1.0 (**) 10 97 82–105 102 282 217–346 1.0 (**) 10 4 52 36–61 25 285 154–408 1.0 (**) 8 116 72–187 111 389 308–427 1.0 (**) 11 4 64 52–78 17 124 102–142 1.0 (**) 5 67 44–79 98 135 114–166 1.0 (**)

Note: Frequency data points are rounded to the nearest full number values. **p values smaller than 0.01.

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session responding amounted to moderate-intensity physical activity. As shown in the table, the participants’ overall mean heart-rate frequencies exceeded (a) the 50% level of their maximum heart-rate values computed with the first formula (i.e. 220 ! age) in seven cases and (b) the 50% level of their maximum heart-rate values computed with the second formula (i.e. 210 ! [0.56 " age] ! 15.5) in nine cases.

Discussion

The intervention data indicate that the approach used in this study (technology with stimulation and encouragements) was effective in increasing and sustaining behavioral responding across different participants and situations, thus providing a systematic replication of previous evidence in the area (Kazdin, 2011). The recording of the participants’ heart rates during such responding constituted a warranted extension of previous research in this area. The findings showed that (a) those rates exceeded the 50% level of the participants’ maximum heart rates in 9 of the 11 cases included in the study (i.e. using the formula recommended for individuals with intellectual dis- abilities) and hence (b) the participants’ session responding mostly amounted to moderate-intensity physical activity, with likely benefits for their physical condition (Aune et al., 2015; Cavalieri et al., 2016; Warburton and Bredin, 2016). In light of the above, a number of considerations might be in order.

First, the fact that all participants managed to engage in physical activity on the basis of their self-determination (supported through automatically delivered, contingent stimulation and encouragements) may be considered practically relevant. One could reasonably argue that the participants’ active role in shaping and maintaining their engagement was motivated by the fact that the stimulation they obtained for the activity largely compensated them for their efforts (Catania, 2012; Chang et al., 2016; Lancioni et al., 2003). The verbal encouragements available during the sessions may have alerted the participants about the activity and refocused them on the relationship between responses and stimulation (Catania, 2012; Kazdin, 2001; Pierce and Cheney, 2008). Participants who commit themselves to the activity independently can hardly be in a condition of stress and anxiety and may possibly experience a state of positive mood (Brown et al., 2013; Hoppmann and Klumb, 2006; Wrosch et al., 2009). Moreover, participants who show ini- tiative (self-determination) in engaging in the activity available provide a positive social image, which contrasts with the image emitted by participants who are guided/compelled into the same activity (Bartlo and Klein, 2011; Chang et al., 2014; Lancioni et al., 2003).

Second, it might be argued that an approach based on the participants’ self-determination and initiative cannot possibly lead the participants to produce very large efforts as required for vigorous activity. In fact, the effort required by such activity would be quite taxing compared to the positive stimulation available, with predictably negative implications for the participants’ motivation to be active. Moreover, given the gravity of the participants’ situation, one could not introduce other types of motivation elements (e.g. a description of the social and physical benefits linked to the activities) (Srinivasan et al., 2014). In other words, participants with severe/profound intellectual and multiple disabilities cannot be expected to appreciate the potential benefits of their activity engagement and use those benefits as motivating agents (Lloyd, 2016).

Third, an approach that appears quite successful in helping participants to independently engage in mild/moderate activity can be viewed as a practical resource. Obviously, clarifications are needed about (a) potential benefits of mild/moderate physical activity for the participants’ con- dition, (b) the amount of physical activity required, and (c) whether such activity needs to be

120 Journal of Intellectual Disabilities 22(2)

carried out within protracted sessions or can be divided into short sessions as it was done in this study. Regarding the first two aspects, research literature (a) confirms the positive effects of moderate and vigorous activity, and also suggests positive effects for mild physical activity, and (b) indicates that even small amounts of mild or moderate activity (e.g. 15–20 min a day) can have a favorable impact (Aune et al., 2015; Elosua et al., 2013; Hill et al., 2015; Janssen and Leblanc, 2010; Nigam and Juneau, 2011; Wen et al., 2011). Regarding the third aspect, no definite evidence is available (Barr-Anderson et al., 2011; Hill et al., 2015). One may argue that dividing the activity into short sessions is convenient when working with participants with severe/profound intellectual and multiple disabilities (i.e. it is likely to prevent or reduce participants’ tiredness). Those sessions could be distributed across the day and involve different exercise devices or specific tasks with contingent stimulation to maintain participants’ motivation (Catania, 2012; Pierce and Cheney, 2008; Waninge et al., 2013).

Fourth, some limitations of the study need to be mentioned here. For example, the relatively small number of participants and the absence of heart-rate measures during resting periods may be considered two research limitations that recommend caution in drawing general conclusions about the results. Two other limitations are the lack of cortisol measurements during the intervention/ activity sessions and the absence of strategies (protocols) for identifying and weighing potential benefits of moderate and mild physical activity in these types of participants. With regard to cortisol, the assumption was that it would not increase in any excessive manner due to the fact that the participants were independently engaged in the activity and thus did not experience any par- ticular pressure, distress or excessive exertion, and probably enjoyed the experience due to the stimulation available (Pascoe and Bauer, 2015; Qi et al., 2016; Webb et al., 2011). While these lines of reasoning are consistent with the results of previous research, direct evidence on this issue is needed, and it should be a target of new studies in the area. With regard to protocols, one could select a number of parameters to monitor (e.g. muscle tone, body fluids regulation, mood, and sleep patterns). These parameters would allow a wider evaluation of the potential benefits of mild to moderate activity, implemented as in this study as well as in extended doses, that is, over longer sessions (Aune et al., 2015; Hill et al., 2015).

In conclusion, the study has shown that (a) the approach employed was effective in increasing and sustaining behavioral responding across different participants and situations and (b) such responding amounted to moderate-intensity physical activity for most participants. New research would need to deal with the limitations of this study and, in particular, clarify the questions on cortisol and investigate the potential benefits of mild to moderate physical activity arranged in different weekly doses. Other points of interest could involve (a) technology upgrading and (b) social validation assessments of the approach compared to strategies in which the participants are exposed to more vigorous activity through supervision and/or active devices (Callahan et al., 2008; Lancioni et al., 2006, 2013).

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.

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References

Aune D, Norat T, Leitzmann M, et al. (2015) Physical activity and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis. European Journal of Epidemiology 30(7): 529–542.

Barlow DH, Nock M, and Hersen M (2009) Single-Case Experimental Designs. 3rd ed. New York: Allyn & Bacon.

Barr-Anderson DJ, AuYoung M, Whitt-Glover MC, et al. (2011) Integration of short bouts of physical activity into organizational routine. American Journal of Preventive Medicine 40(1): 76–93.

Bartlo P and Klein PJ (2011) Physical activity benefits and needs in adults with intellectual disabilities: systematic review of the literature. American Journal on Intellectual and Developmental Disabilities 116(3): 220–232.

Bloeming-Wolbrink KA, Janssen MJ, De Weerth C, et al. (2012) Stress in adults with congenital deaf- blindness and an intellectual disability: information from their cortisol curves. British Journal of Visual Impairment 30(3): 149–159.

Brown I, Hatton C, and Emerson E (2013) Quality of life indicators for individuals with intellectual dis- abilities: extending current practice. Intellectual and Developmental Disabilities 51(5): 316–332.

Callahan K, Henson R, and Cowan AK (2008) Social validation of evidence-based practices in autism by parents, teachers, and administrators. Journal of Autism and Developmental Disorders 38(4): 678–692.

Catania AC (2012) Learning. 5th ed. New York: Sloan. Cavalieri V, Straker L, Gucciardi DF, et al. (2016) Changing physical activity and sedentary behaviour in

people with COPD. Respirology 21(3): 419–426. Chang CJ, Chang ML, and Shih CH (2016) Encouraging overweight students with intellectual disability to

actively perform walking activity using an air mouse combined with preferred stimulation. Research in Developmental Disabilities 55: 37–43.

Chang ML, Shih CH, and Lin YC (2014) Encouraging obese students with intellectual disabilities to engage in pedaling an exercise bike by using an air mouse combined with preferred environmental stimulation. Research in Developmental Disabilities 35(12): 3292–3298.

Chen CC and Ringebach SDR (2016) Dose-response relationship between intensity of exercise and cognitive performance in individuals with down syndrome: a preliminary study. Journal of Intellectual Disability Research 60(6): 606–614.

Dixon-Ibarra A, Driver S, Vanderbom K, et al. (2017) Understanding physical activity in the group home setting: a qualitative inquiry. Disability and Rehabilitation 39(7): 653–662.

Donnelly JE, Hillman CH, Castelli D, et al. (2016) Physical activity, fitness, cognitive function, and academic achievement in children: a systematic review. Medicine and Science in Sports and Exercise 48(6): 1197–1222.

Elosua R, Redondo A, Segura A, et al. (2013) Dose-response association of physical activity with acute myocardial infarction: do amount and intensity matter? Preventive Medicine 57(5): 567–572.

Fernhall B, McCubbib JA, Pitetti KH, et al. (2001) Prediction of maximal heart rate in individuals with mental retardation. Medicine and Science in Sports and Exercise 33(10): 1655–1660.

Fernhall B and Pitetti KH (2001) Limitations to physical work capacity in individuals with mental retardation. Clinical Exercise Physiology 3(2): 176–185.

Gellish RL, Goslin BR, Olson RE, et al. (2007) Longitudinal modeling of the relationship between age and maximal heart rate. Medicine and Science in Sports and Exercise 39(5): 822–829.

Gonzàlez-Agüero A, Vicente-Rodrı́guez G, Gómez-Cabello A, et al. (2012) A 21-week bone deposition promoting exercise programme increases bone mass in young people with down syndrome. Develop- mental Medicine and Child Neurology 54(6): 552–556.

Hill EE, Zack E, Battaglini C, et al. (2008) Exercise and circulating cortisol levels: the intensity threshold effect. Journal of Endocrinological Investigation 31(7): 587–591.

Hill K, Gardiner PA, Cavalheri V, et al. (2015) Physical activity and sedentary behaviour: applying lessons to chronic obstructive pulmonary disease. Internal Medicine Journal 45(5): 474–482.

122 Journal of Intellectual Disabilities 22(2)

Hillier A, Murphy D, and Ferrara C (2011) A pilot study: short-term reduction in salivary cortisol following low level physical exercise and relaxation among adolescents and young adults on the autism spectrum. Stress and Health 27(5): 395–402.

Hinckson EA and Curtis A (2013) Measuring physical activity in children and youth living with intellectual disabilities: a systematic review. Research in Developmental Disabilities 34(1): 72–86.

Hoppmann CA and Klumb PL (2006) Daily goal pursuits predict cortisol secretion and mood states in employed parents with preschool children. Psychosomatic Medicine 68(6): 887–894.

Houwen S, Van der Putten A, and Vlaskamp C (2014) A systematic review of the effects of motor inter- ventions to improve motor, cognitive, and/or social functioning in people with severe or profound intellectual disabilities. Research in Developmental Disabilities 35(9): 2093–2116.

Janssen I and Leblanc AG (2010) Systematic review of the health benefits of physical activity and fitness in school-aged children and youth. International Journal of Behavioral Nutrition and Physical Activity 11(7): 40. DOI: 10.1186/1479-5868-7-40.

Kazdin AE (2001) Behavior Modification in Applied Settings. 6th ed. New York: Wadsworth. Kazdin AE (2011) Single-Case Research Designs: Methods for cLINical and Applied Settings. 2nd ed. New

York: Oxford University Press. Kohn M, Belza B, Petrescu-Prahova M, et al. (2016) Beyond strength: participant perspectives on the benefits

of an older adult exercise program. Health Education & Behavior 43(3): 305–312. Lancioni GE, O’Reilly MF, Singh NN, et al. (2006) A social validation assessment of microswitch-based

programs for persons with multiple disabilities employing teacher trainees and parents as raters. Journal of Developmental and Physical Disabilities 18(4): 383–391.

Lancioni GE, Sigafoos J, O’Reilly MF, et al. (2013) Assistive Technology: Interventions for Individuals with Severe/Profound and Multiple Disabilities. New York: Springer.

Lancioni GE, Singh NN, O’Reilly MF, et al. (2003) Assessing the effects of automatically delivered sti- mulation on the use of simple exercise tools by students with multiple disabilities. Research in Devel- opmental Disabilities 24(6): 475–483.

Lense MD, Tomarken AJ and Dykens EM (2013) Diurnal cortisol profile in Williams syndrome in novel and familiar settings. American Journal on Intellectual and Developmental Disabilities 118(3): 201–210.

Lloyd M (2016) Physical activity of individuals with intellectual disabilities: challenges and future directions. Current Developmental Disorders Reports 3(2): 91–93.

Lydon S, Healy O, Roche M, et al. (2015) Salivary cortisol levels and challenging behavior in children with autism spectrum disorder. Research in Autism Spectrum Disorders 10: 78–92.

Merom D, Ding D, and Stamatakis E (2016) Dancing participation and cardiovascular disease mortality: a pooled analysis of 11 population-based British cohorts. American Journal of Preventive Medicine 50(6): 756–760.

Mul JD, Stanford KI, Hirshman MF, et al. (2015) Exercise and regulation of carbohydrate metabolism. Progress in Molecular Biology and Translational Science 135: 17–37.

Nigam A and Juneau M (2011) Survival benefit associated with low-level physical activity. The Lancet 378: 1202–1203.

Pascoe MC and Bauer IE (2015) A systematic review of randomised control trials on the effects of yoga on stress measures and mood. Journal of Psychiatric Research 68: 270–282.

Pedhazur E and Schmelkin L (1991) Measurement, Design, and Analysis: An Integrated Approach. New York: Psychology Press.

Pierce WD and Cheney CD (2008) Behavior Analysis and Learning. 4th ed. New York: Psychology Press.

Qi M, Gao H, Guan L, et al. (2016) Subjective stress, salivary cortisol, and electrophysiological responses to psychological stress. Frontiers in Psychology 7: 229. DOI: 10.3389/fpsyg.2016.00229.

Queralt A, Vicente-Ortiz A, and Molina-Garcia J (2016) The physical activity patterns of adolescents with intellectual disabilities: a descriptive study. Disability and Health Journal 9(2): 341–345.

Lancioni et al. 123

Ringenbach SD, Holzapfel SD, Mulvey GM, et al. (2016) The effects of assisted cycling therapy (ACT) and voluntary cycling on reaction time and measures of executive function in adolescents with down syn- drome. Journal of Intellectual Disability Research. 60(11):1073–1085.

Russell VA, Zigmond MJ, Dimatelis JJ, et al. (2014) The interaction between stress and exercise, and its impact on brain function. Metabolic Brain Disease 29(2): 255–260.

Shih CT, Shih CH, and Luo CH (2013) Assisting people with disabilities in actively performing physical activities by controlling the preferred environmental stimulation with a gyration air mouse. Research in Developmental Disabilities 34(12): 4328–4333.

Siegel S and Castellan NJ (1988) Nonparametric Statistics for the Behavioral Sciences. 2nd ed. New York: McGraw-Hill.

Srinivasan SM, Pescatello LS, and Bhat AN (2014) Current perspectives on physical activity and exercise recommendations for children and adolescents with autism spectrum disorders. Physical Therapy 94(6): 875–889.

Strath SJ, Kaminsky LA, Ainsworth BE, et al. (2013) Guide to the assessment of physical activity: clinical and research applications. Circulation 128(20): 2259–2279.

Taverniers J, Van Ruysseveldt J, Smeets T, et al. (2010) High-intensity stress elicits robust cortisol increases, and impairs working memory and visuo-spatial declarative memory in Special Forces candidates: a field experiment. Stress 13(4): 323–333.

Taylor MJ, Taylor D, Gamboa P, et al. (2016) Using motion-sensor games to encourage physical activity for adults with intellectual disability. Studies in Health Technology and Informatics 220: 417–423.

VanBruggen MD, Hackney AC, McMurray RG, et al. (2011) The relationship between serum and salivary cortisol levels in response to different intensities of exercise. International Journal of Sports Physiology and Performance 6(3): 396–407.

Waninge A, Van der Putten AAJ, Stewart RE, et al. (2013) Heart rate and physical activity patterns in persons with profound intellectual and multiple disabilities. Journal of Strength and Conditioning Research 27(11): 3150–3158.

Warburton DE and Bredin SS (2016) Reflections on physical activity and health: what should we recom- mend? The Canadian Journal of Cardiology 32(4): 495–504.

Warms C (2006) Physical activity measurement in persons with chronic and disabling conditions: methods, strategies, and issues. Family and Community Health 29 (Suppl 1): 78S–88S.

Webb HE, Fabianke-Kadue EC, Kraemer RR, et al. (2011) Stress reactivity to repeated low-level challenges: a pilot study. Applied Psychophysiology and Biofeedback 36(4): 243–250.

Wen CP, Wai JPM, Tsai MK, et al. (2011) Minimum amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study. The Lancet 378: 1244–1253.

Woodmansee C, Hahne A, Imms C, et al. (2016) Comparing participation in physical recreation activities between children with disability and children with typical development: a secondary analysis of matched data. Research in Developmental Disabilities 49–50: 268–276.

Wrosch C, Miller GE and Schulz R (2009) Cortisol secretion and functional disabilities in old age: importance of using adaptive control strategies. Psychosomatic Medicine 71(9): 996–1003.

Zhang T, Xiang P, Gu X, et al. (2016) College students’ physical activity and health-related quality of life: an achievement goal perspective. Research Quarterly for Exercise and Sport 87(2): 182–190.

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