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Article

Using Qualitative Geospatial Methods to Explore Physical Activity in Children with Developmental Disabilities: A Feasibility Study

by
Cameron M. Gee
1,2,
Brianna T. Tsui
3,
Kathleen A. Martin Ginis
1,3,4,5,
Erica V. Bennett
6,
Kelly P. Arbour-Nicitopoulos
7 and
Christine Voss
3,8,*
1
International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC V5Z 1M9, Canada
2
Department of Orthopaedics, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
3
Centre for Chronic Disease Prevention and Management, University of British Columbia, Kelowna, BC V1V 1V7, Canada
4
Department of Medicine, Division of Physical Medicine & Rehabilitation, University of British Columbia, Vancouver, BC V5Z 2G9, Canada
5
School of Health and Exercise Sciences, University of British Columbia, Kelowna, BC V1V 1V7, Canada
6
School of Kinesiology, University of British Columbia, Vancouver, BC V6T 1Z1, Canada
7
Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON M5S 2W6, Canada
8
Department of Pediatrics, University of British Columbia, Vancouver, BC V6H 0B3, Canada
*
Author to whom correspondence should be addressed.
Disabilities 2024, 4(4), 856-871; https://doi.org/10.3390/disabilities4040053
Submission received: 24 July 2024 / Revised: 2 October 2024 / Accepted: 14 October 2024 / Published: 23 October 2024
Browse Figures
Versions Notes

Abstract

:
Children with developmental disabilities (DDs) experience barriers to physical activity (PA) participation. Greater contextual information regarding their PA behaviors is needed for effective PA promotion. We investigated the feasibility of using activity trackers and Global Positioning Systems (GPS) devices with follow-up interviews to explore PA behaviors in children with DDs. Fifteen children with DDs (aged 10 ± 2 years) wore an activity tracker and GPS device for 7 days. Data were time-aligned to measure PA and identify PA locations. Maps were created to guide follow-up semi-structured interviews with the children and their parents/guardians to understand PA contexts and perceptions of daily PA. The children took 8680 ± 4267 steps/day across 6 ± 1 days. The children provided preferences for PA locations and the parents/guardians gave context by expressing how DDs affect PA and identifying environmental factors in PA locations. The children with DDs who lived near parks, participated in PA that leveraged the strengths of their individual skillsets, and had parents/guardians who provided social support had more positive PA experiences. Combining activity tracking and GPS data with follow-up map-based interviews is feasible to explore PA behaviors and the experiences of children with DDs. This methodology may provide novel insight into daily PA in children with DDs, which can inform how future interventions can support them to be more active and have positive experiences while being active.

1. Introduction

Disability affects approximately 1 in 20 children in Canada between the ages of 5 and 14 years [1] and may be classified as developmental, mobility, chronic conditions, or emotional/psychological [2]. Developmental disabilities (DDs) are a group of conditions that are associated with an impairment in learning, language, and/or behavior [3]. Examples of DDs include intellectual disability, Down syndrome, cerebral palsy, attention deficit hyperactivity disorder, and autism spectrum disorder. Children with DDs experience delays that can impact their overall health and they are at a higher risk of developing obesity, type 2 diabetes, and other conditions [4,5,6]. Children with DDs are more than three times more likely to be overweight than children without disabilities [4], which may be in part due to lower physical activity (PA) levels [7].
Canadian PA guidelines recommend that children and youths aged 5–17 years accumulate at least 60 min of moderate-to-vigorous intensity PA each day and engage in strength-based activities on three days per week [8]. Children and youths who are more physically active gain a variety of health benefits including greater cardiorespiratory fitness and weight management, and reduced anxiety [9]; however, only around one in three Canadian children and youths meet the guidelines [10]. Notably, a large-scale study conducted in the United States found that only 19% of children and youths with DDs between the ages of 6 and 17 years achieved at least 60 minutes of moderate-to-vigorous PA each day [11].
According to the social ecological model, children’s PA is influenced at multiple levels, namely, the intrapersonal, interpersonal, organizational and community levels [12]. For example, within the social environment, parental support and positive interactions with peers are important facilitators in promoting PA participation among children with DDs; however, interactions may also be a barrier for some children with DDs who have limited friendships and experience difficulties with social skills [13]. At the institutional level, access to and participation in accessible community sport programs is a key facilitator in promoting daily PA in children with DDs [7,14]. An understanding of these factors and others may help determine what facilitators can be promoted and what barriers must be addressed to help children with DDs to be physically active.
There are important methodological factors to consider in measuring health behaviors, such as PA, accurately in children with DDs. Common quantitative methods used to measure PA in school-aged children include self-report measures (e.g., surveys and questionnaires) and/or direct observation [15]. While questionnaires are affordable and easy to distribute to a large number of participants, recall, cognitive capacity, and social desirability bias can limit their validity in accurately measuring PA [16]. Direct observation, whereby a trained individual observes and classifies behavior for a pre-determined length of time, can provide context to children’s PA behaviors in a variety of settings but can be time consuming, require intensive training for observation and data analysis, and has been reported to overestimate PA levels [17,18].
Alternatively, wearable devices (e.g., pedometers, accelerometers, and activity trackers) are compact, easy to wear, and provide time-stamped activity data that can mitigate the risk of recall bias [19]. For these reasons, wearable devices may be a useful tool for assessing daily PA behavior among children with DDs. Activity trackers are wearable devices that are widely utilized in the research setting with children [20]. Obtaining PA data from activity trackers may help us to better understand and contextualize the daily PA behaviors of children with DDs because the movement data can be combined with information on where the activity occurred.
Combining movement with location data may help better describe daily PA behaviors in children with DDs. Location data (e.g., latitude, longitude, movement speed) can be collected via global positioning system (GPS) devices—which can offer similar benefits to wearable devices regarding their use among children with DDs—to determine where people are spending time or where they are traveling to and from. Combining accelerometry and GPS devices has previously been used to explore associations between the physical environment and children’s context-specific PA behaviors [21].
Further, qualitative participant interviews can provide additional context and may be a feasible method that researchers can use to describe daily PA experiences of children with DDs. Interviews allow people to share their perceptions of PA experiences and provide meaning and context for their engagement [22]. There have been several studies that explore PA participation in individuals with DDs, however most studies only include stories and perspectives from adults or parents of children and youth with DDs [23,24,25], thereby leaving the children’s voices relatively absent from the extant research.
The purpose of the present study was to determine the feasibility of a sequential mixed methods approach to describe the PA behaviors and experiences of children with DDs aged 7 to 12 years in terms of the following: (1) sample recruitment, (2) adherence to the data collection protocol, and (3) suitability of the study design and measures to provide useful insight into target outcomes (PA behaviors and experiences). Determining the feasibility of utilizing this type of mixed methodology will provide a foundation for future research to explore PA contexts in children with other types of disabilities.

2. Materials and Methods

2.1. Feasibility

Feasibility was assessed in terms of (1) recruitment success, (2) adherence to the data collection protocol, and (3) suitability of the study design and measures to provide useful insight into PA behaviors. Specific feasibility criteria were defined a priori as follows. ‘Recruitment success’ was defined as achieving a recruitment goal of 15 child–parent dyads. ‘Adherence to the data collection protocol’ was defined as all child–parent dyads completing all of the following study components: (i) completed parent questionnaires, (ii) achieving minimum device wear time (see ‘Commercial Activity Tracker’), and (iii) participation in qualitative interviews. ‘Suitability of the study design and measures to provide useful insight into PA behaviors’ was explored by providing relevant descriptive statistics derived from chosen quantitative study measures, as well as conducting an in-depth thematic analysis of the qualitative interview data.

2.2. Study Design

A mixed methods sequential explanatory study design was chosen, where quantitative data were collected in the first phase and qualitative data in the second [26]. In phase one, the parents completed an online questionnaire to capture demographic, parent social support, and child PA data. The participants were then mailed a commercial activity tracker and GPS device. The child participants wore the devices simultaneously for seven consecutive days. Following completion of the data monitoring period, the parents mailed the GPS device to the researchers, and the participants were allowed to keep the commercial activity tracker. Data from the devices were time-aligned via an in-house custom algorithm and used to create individualized maps of the child participant PA locations for use in phase two.
During phase two, qualitative data were collected through semi-structured interviews (conducted via videoconferencing), with the children and parents interviewed separately. Individualized maps of the PA locations were used as prompts during follow-up interviews to guide the interviews and contextualize the child PA experiences.

2.3. Study Sample

Child–parent dyads were recruited through local community organizations that serve children with disabilities and that promoted the study to the target population through social media, newsletter, posters, and websites. The dyads had to live in the same household in British Columbia, Canada. Child participants were included if they were (1) living with a DD (according to parent self-report), (2) 7–12 years of age, and (3) able to communicate verbally. Sibling pairs were eligible to participate so long as all the other inclusion criteria were met. Convenience sampling was used to recruit from the target population (an often-used strategy in equity-deserving populations [27]), with a target sample size of 15 child–parent dyads required to consider our methodology feasible. The parents provided informed written consent and the children provided written assent electronically via Institutional Qualtrics (Provo, UT, USA). The study was approved by the Institutional Behavioural Research Ethics Board.

2.4. Quantitative Measures

2.4.1. Parent Questionnaire

The parents completed an online questionnaire via Institutional Qualtrics (Provo, UT, USA) to capture the child and parent demographics. The parents answered questions on the types of PA that their child participated in and whether their child participated in physical education at school, general PA at school outside of physical education, PA outside of school, and the frequency of all these activities. To delineate PA performed during and outside of physical education classes, parents were specifically asked whether their child participated “in any other sports or PA other than physical education at school.” Questions were yes/no, categorical, or asked parents to use text responses.
To understand parental support regarding their child’s PA, two questions from the validated PA Parenting Practices survey were used [28]. These questions captured the parents’ level of agreement with providing PA/sports equipment for their child (using a 5-point Likert scale, ranging from strongly disagree to strongly agree), and the frequency with which they had been active with their child during the past month (using a 5-point Likert scale, ranging from ‘never’ to ‘4 or more times per week’) [28].

2.4.2. Measurement Devices

The participants were mailed a commercial activity tracker (Fitbit Charge 4, Fitbit™, San Francisco, CA, USA) and a GPS device (QStarz BT-Q1000XT, QStarz International Co. Ltd., Taipei, Taiwan). The devices were set up by the researchers before being mailed to the participants. Given the potential challenges of wearing two devices and that it could limit data collection, the parents were sent an instruction manual on how to use the device, including figures that illustrated how to wear each device and contact information for troubleshooting. The parents were instructed to document any challenges with wearing the devices on a wear time log.

2.4.3. Commercial Activity Tracker

The Fitbit Charge 4 contains a 3-axis accelerometer to detect motion patterns, a built-in GPS receiver, an optical heart rate tracker, and a Bluetooth radio transceiver. The Fitbits were worn on the wrist and, for the purpose of this study, were used only to measure PA (steps/day) and heart rate (to estimate wear time). A unique de-identified Fitbit account was setup for each child using Institutional email addresses. Minute-by-minute step and heart rate data were extracted via a custom application program interface to a browser-based research database accessible to the research team (REDCap, Vanderbilt University, Nashville, TN, USA).
The minute-by-minute Fitbit data were processed and summarized in R Studio (v.1.1.456, Posit, Boston, MA, USA). Computation of the aggregate data for each participant required at least three valid days of Fitbit data, defined as ≥600 min of valid daily wear time (determined based on the presence of heart rate data for ≥600 min between the hours of 5 am and 11 pm). These definitions are broadly in line with commonly used conventional daily wear time criteria for accelerometers [29], which we applied in the absence of any consensus on data processing steps for commercial activity trackers. Overall, weekday, and weekend steps/day were recorded.

2.4.4. GPS Devices

The GPS function of the Fitbit was not used in this study due to the impacts on battery life and the inability to extract detailed time-stamped GPS coordinates from Fitbit servers. Therefore, a separate GPS data logger was used (QStarz BT-Q1000XT, QStarz International Co. Ltd., Taipei, Taiwan). The GPS devices were attached to a belt and worn on the right hip during waking hours. The GPS devices were configured to measure universal time, latitude and longitude, speed, and elevation at 15-s intervals. The data were downloaded directly from the device after the measurement period (QStarz Data Viewer Software V3.00.000, QStarz International Co. Ltd., Taipei, Taiwan).

2.4.5. Combining and Processing Activity Tracker and GPS Data

The minute-by-minute Fitbit and GPS data were combined by an in-house custom algorithm using Python programming language (versions 2.7 and 3.8). The algorithm removed unusable or poor data (e.g., when a poor GPS satellite connection resulted in scattered GPS tracks) and interpolated missing data points. The algorithm interfaced with geographic information system (GIS) software (ArcGIS ® version 10.7, Esri, Redlands, CA, USA) to link participants’ GPS tracks to land parcel data from CanMap Streetfiles (v2014.3, New York, NY, USA). To identify data points that occurred at home, each participant’s full residential address was geocoded into latitude and longitude coordinates using the ‘BC Address Geocoder’ [30] and a 125 m buffer was created around each home location. Algorithm output files included summary data for each child and provided segments with type of locations (e.g., home, school, or park), time spent at locations, and the volume of PA at that location (i.e., step count). The algorithm was developed with and verified against detailed travel logs and manually coded GPS tracks.

2.4.6. Map Creation

The combined activity tracker and GPS data were imported into GIS software (ArcGIS ® version 10.7, Esri, Redlands, CA, USA) for data visualization and customized maps were created for each child. Street-based maps were used to help visualize the data, which included clearly defined and labeled landmarks (e.g., street names and parks). Figure 1 illustrates an example customized map.

2.5. Qualitative Methods

Virtual Interviews

The children and their parents participated in separate semi-structured virtual interviews (Zoom Video Communications, San Jose, CA, USA) to contextualize the quantitative PA data [31]. Using the social ecological model as a framework, an interview guide was developed that aimed to explore the following potential levels of influence: the intrapersonal (e.g., the child’s perceptions of the environment), interpersonal (e.g., who the child was with at these locations and parent social support), organizational (e.g., the child’s experiences with physical activity at school) and community levels (e.g., proximity to parks) [12]. For sibling participants, each sibling was interviewed separately.
During the interviews, the children were shown maps of their combined Fitbit and GPS data that illustrated where and when they were physically active and were asked up to six questions (with follow-up prompts as required) about their activity based on the map (e.g., “Tell me about your day from looking at this map”, “Can you tell me about the activities that you did at these locations?”, “What did you like most (and least) about visiting these locations?”, “Was there anything you wanted to do at these locations, but couldn’t do?”, “How did you get to and from these locations”). The parents were present to provide support during their child’s interview given the unfamiliar situation, but were instructed to let the children answer on their own. The child was then asked to leave for the parent interview.
The parents were shown the same maps as their child as prompts and asked up to nine questions to provide more context to their child’s PA locations (e.g., “Tell me about your child’s day based on this map”) as well as more general questions regarding their child’s PA (e.g., “Tell me about locations that meet (and do not meet) your child’s physical activity needs”, “What are your perceptions about your child’s physical activity during school/outside of school?”, “What concerns do you have about your child’s physical activity?”, “How does your child’s disability impact their physical activity, if at all?”, “Describe your involvement in your child’s physical activity”). The combined time for the child and parent virtual interviews was capped at 60 min.

2.6. Data Analyses

2.6.1. Statistical Analyses

Descriptive statistics for the participant demographics and children’s PA were calculated. All the data were assessed for normality by Shapiro–Wilk tests and passed (all p < 0.05). Independent sample t-tests compared steps/day (overall, on weekdays, and on weekends) between younger (aged 7–9 years) and older children (aged 10–12 years). Chi-square tests compared the number of younger and older children who engaged in PA at distinct locations (i.e., home and park). The analyses were conducted in R studio (v.1.1.456, Posit, Boston, MA, USA) and GraphPad Prism (v.9.4.1, GraphPad Software, Inc., LaJolla, CA, USA). Significance was set at p < 0.05.

2.6.2. Thematic Analysis

Thematic analysis of the participant interviews was conducted taking a post-positivist philosophical position to explore patterns of meaning within the data pertaining to parent perceptions of, and experiences with, the environments in which their children were active [32]. A codebook was developed based on the interview guide and participant responses during the interviews. Similar concepts from transcripts were grouped and a reflexive journal was kept during the analysis to help formulate appropriate sub-themes. Once the codebook was completed, the main themes and sub-themes were generated by interpreting commonalities between the codes.

3. Results

3.1. Recruitment

Sixteen interested families provided consent but one family dropped out for reasons unrelated to the study. Fifteen child–parent dyads were successfully recruited, including 3 sibling pairs. Therefore, our feasibility recruitment goal was achieved.

3.2. Adherence to Data Collection Protocol

All the child–parent dyads completed the entire study protocol, including the parent questionnaire, device wear time protocol, and follow-up semi-structured interviews. All children met the minimum device wear time criteria of ≥600 min wear time/day on at least three days. The mean valid days per child for Fitbit wear time was 6 ± 1 days. All the child participants were able to engage with the interview process, though levels of engagement varied between children, as was to be expected. The parents did not report any significant logistical issues with the children wearing the devices, the setup of the Fitbit app, or the charging devices. Therefore, our feasibility goal in terms of adherence to the data collection protocol was achieved.

3.3. Participant Demographics and Physical Activity Characteristics

Fifteen children (100% boys, including three sets of brothers) with DDs aged 7 to 12 years and 12 parents (10 mothers, 1 father, 1 grandfather) participated in this study. The relevant child and parent demographics are presented in Table 1 and Table 2, respectively.
The PA participation data, reported from the online parent questionnaire, are presented in Table 3. The parents reported that 9/15 children participated in PA outside of school including soccer, swimming (both n = 5), track, baseball (both n = 2), hockey, gymnastics, cricket, archery, skiing, biking, and hiking (all n = 1). All the parents indicated that they had participated in PA with their child at least 1–2 times during the past month, with more than half (53%) having done so at least 2–3 times per week during the past month. The parents were neutral (7%), agreed (47%), or strongly agreed (47%) that they provided PA/sport equipment for their child.
The overall, weekday, and weekend wear time for the Fitbit device was not different between the younger and older children. The weekday and weekend steps/day were not different among all children, older children, or younger children (ps ≥ 0.189). The younger children took more steps/day than the older children across all valid days (10,121 ± 4238 vs. 7906 ± 4114 steps/day, p = 0.023) (Figure 2A). The younger children also took more steps/day on weekdays (10,585 ± 4244 vs. 7404 ± 3587 steps/day, p = 0.003) (Figure 2B) compared to the older children, but not on weekends (8663 ± 4185 vs. 8998 ± 5028 steps/day, p = 0.878) (Figure 2C). Transportation to and from the locations where the children were physically active was categorized as either walking trips or car trips. Walking trips between locations were only seen in older children with a mean step count of 959 (steps/day) across 7 days.

3.4. Virtual Interviews

When analyzing the transcripts, it was observed that the child participant answers varied, depending on their ability to comprehend and respond to questions. For example, Kevin had difficulty articulating realistic numbers, as seen in the following exchange:
Interviewer: And how, how often do you play in your pool?
Kevin: um… 1000 times a year.
We found here, as previously, that the parent participants were able to elaborate and provide context when asked similar questions during their part of the interview [33].
Four main themes were identified from the interviews conducted with the children and their parents, as follows: (1) perceptions of PA locations; (2) children’s social connections; (3) perceptions of organized sport and PA; and (4) navigating disability and PA. Pseudonyms are used to anonymize the participants.

3.4.1. Theme 1—Perceptions of Physical Activity Locations

The combined Fitbit and GPS data captured the children’s PA locations. The children and their parents provided context to this data by sharing their perspectives on the locations during the map-based interviews. The geospatial data demonstrated that the children spent on average 450 min/day (~7.5 h/day) at home. The younger children had significantly higher mean daily step counts at home compared to the older children (2795 ± 3271 vs. 1671 ± 1958 steps/day, p < 0.05). A common area in the home where the children were active was the backyard and the parents recounted how their child often played outside by themselves or with friends, parents, and/or siblings. Leila described her son’s experiences playing in their backyard and how equipment facilitates her child’s PA:
Yeah, they go on the trampoline. He likes to do back flips and front flips. And we also have, like, a pull up bar that my husband made in the tree that he likes to use.
The older children were more likely to visit the park than the younger children (χ2 = (1, 15), 5.625, p = 0.02). However, the younger children tended to spend more time, and took more steps, in the park (both p > 0.05). Playgrounds at parks were a major facilitator to encourage PA among the children, who shared what activities they liked to do at the park. Phillip described his favorite activities:
Interviewer: What do you do there usually?
Phillip: Play tag. Play hide and seek, use the obstacle course, play on the swings, and sometimes even bike there, play, hide and seek. I found a really good spot in the corner.
The parents shared their perspectives on their child’s PA at school. Most parents expressed their concerns over their child’s sedentary behavior at school and how they would like to see more opportunities for unstructured PA during the school day. Mary shared how she would like to see more opportunities for her son to participate in unstructured PA during the school day:
I think it’d be nice if there was more time for them to you know move their body, even if it’s not necessarily like free time but just being outside maybe going for like nature walks or whatever you know spending some time, being a little bit more, not just sitting in the desk.

3.4.2. Theme 2—Children’s Social Connections

The children’s social connections during PA were provided by both the parents and peers. The parents encouraged their child to be active, participated in PA with their child, and reported providing PA/sport equipment for their child (e.g., bicycles, trampolines, basketball hoops). During the interviews, the parents shared their experiences about providing social support to encourage their child to be active. Abbey described her involvement with her son’s PA, which included driving him and his siblings to various PA programs:
Well, I drive them to most of it. Yeah. So I think if it’s structured, usually I drive them. And then I’m there for a drop, pick up and sometimes stay in between…
Kojel spoke of how she encourages her son to be active:
We do a lot of things together as a family, too. So you know, we are always trying to think of something new like we’ll go for a hike, or we’ll go paddle boarding or go skiing, or something like that. So we have sort of things that we do as a family, and it’s expected that he goes, but he enjoys it.
The children recounted social interactions that they had with others, often speaking of these interactions when describing their experiences at the park and/or when they participated in organized sports. Michael described his experiences of playing soccer and other sports at parks with his dad:
Usually just like on basically any park that me and Dad are thinking to go to like usually we’ll do soccer, baseball maybe a little bit of basketball there too so usually it’s like, I don’t even know the names of the parks because we probably have quite improper names for them.
The parents shared views on interactions that their child experienced with their peers during PA. They explained that children often play and socialize with their friends in their neighborhood, which contributes to their daily PA. The children highlighted that they develop social connections with both their peers and parents at the park in their neighborhood. Some parents also emphasized the challenges of children with DDs in socializing with peers. Norman spoke of a time when his child had a hard time interacting and connecting with peers:
I think that it might just be because of the social aspects of it. He has a hard time making friends and like actually playing with some other kids sometimes. He also has like explosive kind of behavioral outbursts and the other kids will see that. And they’ll kind of stay away from him.

3.4.3. Theme 3—Perceptions of Organized Sports and Physical Activities

During the interviews, the parents provided context on their child’s experiences in organized sport and PA. The parents expressed how their children experienced finding their role and fitting into a team setting. They explained how individual skillsets could either hinder or encourage children to participate in team sport. Felisha spoke of a time when her child was at a lower skill level compared to his peers, which negatively impacted his experience:
Practices were fine because you know, obviously they’d like say “have a partner” and they’d be practicing skills or whatever, but during the actual game like you know, he would never get the ball and stuff but again that’s also due to his skill level… he definitely didn’t want to play more after.
The parents also shared that they typically chose specific programs due to their child’s interest and enjoyment. These programs also provided the children with opportunities to gain new experiences, meet new people, and learn new skills. Kia shared that her son’s passion for hockey was part of the reason why she enrolled him in the program:
Hockey has been a major, major interest of his since he was about two. He’s been very passionate and so it was like a no brainer. He started ice skating lessons at I think maybe two and a half. Because he wanted to learn how to ice skate so that he could play hockey and then yeah it just developed from there, and so we joined [minor hockey] as soon as he could when he was five…

3.4.4. Theme 4—Navigating Disability and Physical Activity

Forty-seven percent of the parents reported they had concerns about their child’s PA and provided further context through interviews. The parents expressed how cognitive concerns such as difficulties with focus and concentration, children having difficulties in transitioning to different activities, and difficulties with interacting with their peers impacted their child’s PA behaviors. Some parents shared how their children experienced developmental delays such as slow reaction time, secondary conditions, and motor concerns that influenced PA. Grace described her concerns about how developmental delays impact her son’s PA:
Luke has his own limitations, and he did require therapy. He still does. He has a hard time squatting for instance, he still does. Early on he couldn’t transition between different surfaces without falling.
The parents shared their perceptions about PA and supervising their child. Some parents shared that they let their child play in the neighborhood with limited supervision. Others shared stories about their concerns with supervising their child due to road safety concerns. More specifically, the parents were concerned about how their child’s DD impacted their awareness and ability to safely cross streets. Mimi described her thoughts and concerns on supervising her son when he plays outside the house and in the neighborhood at nearby parks:
He’s fully supervised. Part of the reason of going around the neighborhood like this is also learning how to cross the street and looking properly in different scenarios and not just familiar ones.
The level of supervision provided appeared related to the degree of a child’s impairment/s.

4. Discussion

Investigating the context of where children are physically active is important to understanding their daily PA behaviors and to improve both participation quality and quantity. This study demonstrates that a sequential mixed methods design using an activity tracker and GPS device with follow-up map-based interviews is a feasible way of examining the context of PA behaviors and experiences among children with DDs. Our findings demonstrate that key PA locations for children with DDs include the park and home. Parents are integral in providing PA support for their children through encouragement, providing sports/PA equipment, and being active with their child.

4.1. A Mixed Methods Study Design Is Feasible to Study Physical Activity in Children with Developmental Disabilities

That we were able to recruit 15 child–parent dyads reinforces the feasibility of our mixed methods study design. Recruitment was made more feasible by the fact that this study was accessible to participants who did not reside near our research center and through the assistance of community organizations.
In further support of a mixed methods study design, utilizing devices to measure daily PA in children with DDs was feasible over a 7-day period. All the children had at least three days of valid data and wear time that was comparable to previous research on the feasibility of using Fitbits to measure PA in children with disabilities [20]. Additionally, parents did not report any major sensitivity issues or concerns with wearing the Fitbit and GPS devices simultaneously.
Follow-up semi-structured map-based interviews were feasible to conduct virtually. As has previously been shown [34,35], offering online interviews was convenient and accessible as the participants did not report any challenges or barriers to completing the interviews—with some parents commenting that had the study not utilized remote/virtual data collection they would not have been able to participate. The maps generated using the GIS software proved feasible in the interviews as they elicited responses from most children about their perceptions and experiences of PA locations. It was our experience that having the customized maps as a visual aid was critical to keeping the children engaged during the interviews.

4.2. Physical Activity Levels in Children with Developmental Disabilities

The PA participation among the children with DDs was comparable to that reported in studies of children with a broader range of developmental and physical disabilities [20] but less than that in children without disabilities [36]. The parent responses from the interviews supported previous research suggesting lower levels of PA participation by children with DDs is due to a variety of barriers including limited social skills, motor impairments [37], not having friends to be active with, and their own fear of children getting injured during sports/PA [38].
The younger children were generally more active than the older children in this study. This finding aligns with previous evidence that PA levels in children with autism decline with age [39]. This may in part be due to increased sedentary behavior and screen time as children grow older or that sports become more competitive as children age and those with lower skill levels are unable to fully participate [40], the latter being consistent with the findings of the present study.

4.3. Understanding Where Children with Developmental Disabilities Are Active and the Role of Parents

The home was a location where the children with DDs received parent social support to be physically active. This is in agreement with combined accelerometry and GPS data from similarly aged children without disabilities, which found most of their PA was done at home [41].
The parents and children described outdoor play at home as a frequent PA location. Parent preferences for their children to play in the backyard at home is likely due to providing a safe space for children to play [42]. The parents mentioned how they provide equipment to facilitate their child’s PA outside at home such as access to bicycles, trampolines, basketball hoops, and other sports equipment.
The home provided the children with DDs opportunities to participate in a variety of activities that they enjoyed. Although the quantitative methodology used in this study did not allow for a distinction between time spent or exact step count for indoors versus outdoors in the home environment, the children provided more context about these spaces during the interviews. For instance, the children shared what they enjoyed doing in the backyard (e.g., gardening, biking) and who they were with (e.g., siblings, parents).
The park was another common PA location for the children identified through both the geospatial tracking and interviews. Previous research has demonstrated that proximity to parks is a facilitator of PA in children both with autism and with other types of disabilities [43,44]. However, as they relied only on device-based measures, these studies described only the amount and not the type of PA children with DDs engaged in. By utilizing qualitative approaches through follow-up semi-structured interviews, this study provides greater context to these PA experiences as the children with DDs described activities such as playing tag, hide and seek, ball games, and playing on the playground.
Whereas others have found that neighborhood social support does not predict PA in children with autism [45], we found that the children’s neighborhood play was facilitated by opportunities for unstructured PA with peers and siblings, which allowed several children to play freely in a nearby park or within the neighborhood. Most children in the current study who required supervision were supervised by friend’s parents when playing at their friend’s house or outside in the neighborhood.

4.4. Navigating Disability and Physical Activity

We explored the parents’ perspectives on the interaction between their child’s DDs and PA experiences. The parents elaborated on how their children’s developmental delays in motor skills impacted their ability to participate in daily PA and described how their children’s skillset either hindered or encouraged them to participate in organized sports. Inclusive out-of-school PA programs may help to navigate these barriers by enhancing skill development and physical literacy [46]. PA and sport environments that foster mastery and a sense of accomplishment have also proven beneficial for children with autism [47].
Enjoyment promotes PA participation in children with intellectual disabilities [7], who prefer PA that includes a social component [48]. Accordingly, the parents recounted choosing specific PA programs based on their children’s preferences and enjoyment and highlighted the importance of providing opportunities for their child to socialize and interact with peers.
It is noteworthy that the parents expressed concerns with their child’s ability to navigate neighborhoods. For instance, some parents did not feel comfortable letting their child play outside due to safety concerns, particularly with road safety, and this likely influences PA behavior outside of the home.

4.5. Methodological Considerations

Children with all forms of DDs were eligible to participate in the present study. However, only the parents of children diagnosed with autism, attention deficit hyperactivity disorder, or both expressed interest in participating. Children with other DDs, such as those with Down syndrome, were not included. Additionally, we did not collect data on children’s daily autonomy or associated co-morbidities that may have influenced our results. The voices of children with all forms of DDs and insights into their PA experiences remain to be elucidated.
Three sibling pairs participated in this study and were presented the same maps in their interviews since they visited the same locations together and it was challenging to separate the siblings into two distinct participants based on the device data. However, the interviews were conducted separately and each sibling was able to share their perspectives on their experiences with PA at each location.
Only boys with DDs were included in this study and this should be considered in the feasibility of our sequential mixed methods approach to describing PA behavior and the experiences of children with DDs. While this may in part be due to the higher prevalence of boys diagnosed with autism compared to girls [49], why no parents of girls showed an interest in this research study is unknown. Future research studies should partner with the parents of girls with DDs to help develop recruitment materials and design future studies.
We used commercial activity trackers to measure PA in the form of steps/day. A limitation of these devices is that they favor step-based activities, meaning that some activities that the children engaged in during the study may not have been adequately captured (e.g., swimming, cycling) [50]. Such activities were documented in the survey and during the interviews with the participants. Further, the trackers used in the present study are not specifically designed for children and values may differ from those collected via accelerometry [51]. Therefore, through the mixed methods study design, a wider context for daily PA in children with DDs was captured.
Researchers are encouraged to find ways to better understand the experiences and perceptions of PA among children with DDs. Novel methods that investigate PA experiences in children with DDs will help parents, researchers, and community organizations improve current, and develop new, strategies to enhance PA experiences for children with DDs.

5. Conclusions

This study demonstrated that combining data from activity trackers and GPS devices with follow-up map-based interviews was feasible to better understand the context of PA behaviors and experiences in children with DDs. We found that children with DDs who live in communities with nearby parks, who participate in PA that leverages the strengths of their individual skillsets, and who have parents who provide social support have positive PA experiences. Further, follow-up map-based interviews were found to be a useful and feasible tool for parents and children to provide more context to children’s PA behavior and experiences. Based on the usefulness of the qualitative data obtained in this study, it is strongly encouraged that children with DDs are provided with more opportunities to share their perceptions of their PA experiences. Understanding these experiences is important to address the low daily PA participation of children with DDs.
Finally, as researchers who do not identify as individuals with, or parents of children with, DDs, we acknowledge that we do not have the same lived experiences as children with DDs nor the parents of children with DDs. Our intention has been to understand the experiences of children with DDs with transparency and we have endeavored to limit implicit biases throughout our interactions with the child and parent participants. We hope to have conducted this study with respect and openness to understand the experiences of children with DDs.

Author Contributions

Conceptualization, B.T.T., K.A.M.G., E.V.B., K.P.A.-N. and C.V.; Methodology, B.T.T. and C.V.; Formal analysis, C.M.G. and C.V.; Investigation, B.T.T. and C.V.; Data curation, C.M.G., B.T.T. and C.V.; Writing—original draft, C.M.G. and C.V.; Writing—review & editing, C.M.G., K.A.M.G., E.V.B. and K.P.A.-N.; Supervision, K.A.M.G., E.V.B., K.P.A.-N. and C.V.; Project administration, C.V.; Funding acquisition, C.V. All authors have read and agreed to the published version of the manuscript.

Funding

The study was partly funded by a seed grant from the BC Children’s Hospital Research Institute. C.V. was funded by a Michael Smith Health Research BC Scholar Award (SCH-2021-1574).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki. The University of British Columbia Okanagan Behavioural Research Ethics Board gave approval for this research (H22-00842, 6 May 2022).

Informed Consent Statement

Legal guardians provided written informed consent and child participants provided written assent.

Data Availability Statement

Some of the data presented in this study may be available on request from the corresponding author, but privacy and ethical considerations apply.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Example of a customized map of a walking trip used during virtual interviews. Note: Illustrated GPS tracks do not resemble real participant data.
Figure 1. Example of a customized map of a walking trip used during virtual interviews. Note: Illustrated GPS tracks do not resemble real participant data.
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Figure 2. Steps/day (A) over entire monitoring period, (B) on weekdays, and (C) on weekend by age group. * indicates p < 0.03; † indicates p < 0.01. Data are presented as mean ± SD. Individual data points represent each child’s mean daily step count. Only 4/6 younger children wore the activity tracker on a weekend day.
Figure 2. Steps/day (A) over entire monitoring period, (B) on weekdays, and (C) on weekend by age group. * indicates p < 0.03; † indicates p < 0.01. Data are presented as mean ± SD. Individual data points represent each child’s mean daily step count. Only 4/6 younger children wore the activity tracker on a weekend day.
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Table 1. Child participant demographics.
Table 1. Child participant demographics.
AllBy Age Group
(n = 15)7–9 Years
(n = 6)		10–12 Years
(n = 9)
Age (years)10.0 (8.5–11.0)8.0 (7.3–8.8)11.0 (10.0–11.0)
Disability Type
Autism6 (40%)2 (33%)4 (44%)
Attention deficit hyperactivity disorder3 (20%)N/A3 (33%)
Autism and attention deficit hyperactivity disorder6 (40%)4 (67%)2 (22%)
Data are presented as n (%) or median (IQR); IQR—Interquartile range (25th–75th percentile). Note that all child participants were boys and all three sibling pairs included one younger and one older child.
Table 2. Parent participant demographics.
Table 2. Parent participant demographics.
AllBy Parent Type
(n = 12)Mother
(n = 10)		Father/Grandfather
(n = 2)
Employment
   Full Time 1 (8%)1 (10%)0 (0%)
   Part Time 3 (25%)3 (30%)0 (0%)
   Unemployed4 (33%)3 (30%)1 (50%)
   Self-Employed1 (8%)1 (10%)0 (0%)
   Student2 (17%)2 (20%)0 (0%)
   Retired1 (8%)N/A1 (50%)
Median Annual Household Income
  < $59,000 2 (17%)1 (10%)1 (50%)
  $60,000–75,0004 (33%)3 (30%)1 (50%)
  >$75,0006 (50%)6 (60%)0 (0%)
Data are presented as n (%).
Table 3. Child physical activity participation.
Table 3. Child physical activity participation.
AllAge Group
(n = 15)7–9 Years
(n = 6)		10–12 Years
(n = 9)
School Type
   Regular School14 (93%)5 (83%)9 (100%)
   Special Education Class in Regular School1 (7%)1 (17%)0 (0%)
Physical Education Participation
   Yes14 (93%)6 (100%)8 (89%)
   No 1 (7%)0 (0%)1 (100%)
If yes, Frequency of Physical Education
   1–2 times per week 7 (50%)3 (50%)4 (50%)
   3–4 times per week6 (43%)3 (50%)3 (38%)
   5 times per week1 (7%)0 (0%)1 (13%)
Physical Activity at School
   Yes9 (60%)4 (67%)5 (56%)
   No 6 (40%)2 (33%)4 (44%)
If yes, Frequency of Physical Activity at School
   Once per week1 (11%)1 (25%)0 (0%)
   2–3 times per week7 (78%)3 (75%)4 (80%)
   4–5 times per week1 (11%)0 (0%)1 (2%)
Physical Activity Outside of School
   Yes9 (60%)4 (67%)5 (56%)
   No 6 (40%)2 (33%)4 (44%)
If yes, Frequency of Physical Activity Outside of School
   Once per week2 (22%)1 (25%)1 (20%)
   2–3 times per week6 (67%)3 (75%)3 (60%)
   4–5 times per week1 (11%)0 (0%)1 (20%)
Data are presented as n (%).
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MDPI and ACS Style

Gee, C.M.; Tsui, B.T.; Martin Ginis, K.A.; Bennett, E.V.; Arbour-Nicitopoulos, K.P.; Voss, C. Using Qualitative Geospatial Methods to Explore Physical Activity in Children with Developmental Disabilities: A Feasibility Study. Disabilities 2024, 4, 856-871. https://doi.org/10.3390/disabilities4040053

AMA Style

Gee CM, Tsui BT, Martin Ginis KA, Bennett EV, Arbour-Nicitopoulos KP, Voss C. Using Qualitative Geospatial Methods to Explore Physical Activity in Children with Developmental Disabilities: A Feasibility Study. Disabilities. 2024; 4(4):856-871. https://doi.org/10.3390/disabilities4040053

Chicago/Turabian Style

Gee, Cameron M., Brianna T. Tsui, Kathleen A. Martin Ginis, Erica V. Bennett, Kelly P. Arbour-Nicitopoulos, and Christine Voss. 2024. "Using Qualitative Geospatial Methods to Explore Physical Activity in Children with Developmental Disabilities: A Feasibility Study" Disabilities 4, no. 4: 856-871. https://doi.org/10.3390/disabilities4040053

APA Style

Gee, C. M., Tsui, B. T., Martin Ginis, K. A., Bennett, E. V., Arbour-Nicitopoulos, K. P., & Voss, C. (2024). Using Qualitative Geospatial Methods to Explore Physical Activity in Children with Developmental Disabilities: A Feasibility Study. Disabilities, 4(4), 856-871. https://doi.org/10.3390/disabilities4040053

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