Development, usability, and preliminary efficacy of a virtual reality experience to promote healthy lifestyle behaviors in children: pilot randomized controlled trial

Introduction

Childhood is a critical period of development where lifelong behavioral patterns are established and where intervention has the potential for helping to solidify healthful habits. In particular, dietary and physical activity patterns established during childhood and adolescence can persist into adulthood, conferring a cascade of long-term positive impacts on physical health, mental health, and even socioeconomic and interpersonal outcomes (1). Eating and activity behaviors also have immediate impacts on children’s cognitive functioning, energy levels, and risk of chronic diseases (2), yet over half of U.S. children have low-quality diets and less than 1% of children have ideal quality diets (3). Efforts aimed at helping children develop and foster a healthy, positive relationship with eating and activity behaviors are crucial to improve their health and quality of life. Moreover, improving population diet quality is and continues to be a public health priority (4).

Although numerous effective interventions to promote healthy lifestyle behaviors among children exist, such as Family-based Behavioral Treatment (FBT) (5,6), they are not widely or equitably distributed (7-9), are often costly or not reimbursed (10), and can be burdensome, limiting reach, scalability, and adoption (11-16). There is an urgent need for translation of key tenets of established, behavioral interventions for promoting healthy eating and activity behaviors into novel digital tools to drastically increase scalability of interventions and promote healthy habit development.

Digital solutions: virtual reality (VR)

VR is a burgeoning digital medium and has been shown to be a promising tool for augmenting treatment approaches (17), including for behavior change and eating disorders (18,19). Embodiment experiences in immersive virtual environments, which allow individuals to see, hear, and feel digital stimuli as if they were in the physical world, have been shown to impact adults’ prosocial behavior, vaccination intentions, and social anxiety (20,21). Some preliminary work shows VR as effective for delivering behavioral interventions in children (22,23). Research also demonstrates use of VR with children for the treatment of attention deficit hyperactivity disorder (ADHD), autism spectrum disorder, anxiety, pain management, and rehabilitation (23-25). Research with children undergoing physical rehabilitation suggests VR increases children’s self-efficacy and adherence to their therapy exercises by having their virtual bodies appear to move more fluidly than their real bodies (26). A fundamental characteristic of VR is that it provides users with a sense of “being there” (i.e., psychological presence), which results in VR environments producing emotional, behavioral, and physiological responses similar to those in real life, particularly in children (27-29). Embodiment in VR may be particularly compelling compared to less immersive mediums, because it seems more realistic; children can control their avatar with their own body movements (26). Thus, embodiment in VR may be particularly promising for health interventions, and especially so for children, who may more easily identify with immersive fictional environments that mimic imaginary play (28,30).

Despite burgeoning research on VR for health promotion (31), and that VR has shown promise for addressing eating disorders (32), and other psychological concerns in adults (33-37), there is a dearth of research that leverages a VR experience as an intervention tool for child healthy lifestyle behavior (34).

Evidence-based framework

One key tenet of evidence-based behavioral interventions promoting healthy behavior change (5,38) involves consideration of future consequences (i.e., episodic future thinking). This principle is ripe for translation to VR, where embodiment can help immerse one in a virtual “future”. Specifically, VR could allow a child to experience what it might be like to live in various bodies in the future and experience the long-term effects of dietary and activity behaviors. VR allows for the creation of avatars whose movements can differ from the participants’ own, increasing the potential impact of consideration of the “future self” on motivation and behavior (39,40). Much work demonstrates the impact of consideration of one’s future or “possible” self on motivation and behavior across domains (41,42), including health behavior in early adolescents (43). VR has been used to connect individuals with a future self to promote behavior change (40); however, this has not been applied to health behaviors in children. Additionally, evidence-based behavioral health interventions often involve psychoeducation and behavior modification strategies to help promote optimal nutrition intake for cardiometabolic health (6). These frequently draw on nutritional frameworks that generally recommend consuming a wide variety of foods, with greater emphasis on consuming more nutrient-dense foods such as fruits and vegetables (44). Therefore, we also incorporated these aspects into the VR experience.

The present study

The overarching goals of this study were to (I) develop a prototype VR experience to promote healthy eating behaviors among children, (II) refine the experience using user-centered design and usability testing, and (III) evaluate the acceptability and preliminary efficacy of the experience in changing cognitions and behavior in a pilot randomized controlled trial (RCT) among children aged 6–12 years and their caregivers. User-centered design approaches can result in more acceptable and effective interventions (45) and increase the successful implementation of evidence-based interventions when translated to “real-world” settings (46). User-centered design can be particularly important for the translation of psychosocial intervention components to digital platforms (47). Given that children may be particularly impacted by VR environments (30), the focus is on children ages 6–12 years, prior to adolescence. This article is presented in accordance with the CONSORT reporting checklist (available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-24-24/rc).

Methods

Study design overview

This project involved two studies. Study 1 utilized a user-centered design approach to create a prototype VR experience and conduct usability testing with 5 children with higher body mass index (BMI) and one of their caregivers to inform refinements. Study 2 involved a parallel, two-group pilot RCT whereby 27 children with higher BMIs and one of their caregivers with higher BMI were randomized with a 1:1 ratio to the VR experience or to view an educational video and play a mobile game that also encouraged healthy eating as well as consideration of future consequences (i.e., control condition), to determine whether VR can magnify the effect of psychoeducation on cognitions and behavior. Caregivers are included in the intervention because caregivers typically arrange family eating/exercise environments, model behaviors, and reinforce healthy or unhealthy behavioral patterns (48,49).

VR experience

The VR experience involves driving a go-kart by moving your arms up and down to go forward down a city road that is filled with healthful foods (e.g., fruits, vegetables) and less healthy foods (e.g., candy, donuts). The go-kart is meant to harness the virtual embodiment experience. The user is first given instructions for operating the game (i.e., move your hands up and down to move forward) and some psychoeducational content in child-friendly language to inform the child/user that the go-kart will mimic how your body feels and moves when you consume different foods. The psychoeducational content was based on content delivered in FBT related to the concepts of “food as fuel” and the traffic light nutrition classification system (50). Additionally, the concept of “episodic future thinking” informs the second part of the VR experience, whereby participants experience what it would feel like to move in the future if they make healthy vs. less healthy choices in the present (i.e., the go-kart would move more quickly and be more agile when “fueling” with more healthy foods or go more slowly when “fueled” with less healthy foods) (51). This is reinforced in the voiceover psychoeducational content [e.g., “Food is fuel for our bodies (just like gas is fuel for cars), and we want to put really good fuel into our bodies to make them work well. If you fuel your body with lots of good nutrients, like vitamins and minerals, your body feels better now, and it will also feel better in the future!”].

RealizedCare (formerly BehaVR) developed and hosted the VR experience. See Appendices 1,2 for the entire VR game script and screenshots of the VR experience. To engage with the VR experience, participants used the Oculus Quest device, which participants wear over their eyes. To move the go-kart forward in the game, the user has to move their hands up and down like pistons while holding the VR handles, and swivel their torso and arms to steer the go-kart on the road (like a steering wheel) in the virtual environment.

Study 1: usability testing

Participants, recruitment, and procedure

Participants for study 1 included five English-speaking children ages 6–12 years with BMI above the 85^th percentile for age and sex (52) who did not screen positive for bingeing or purging behavior and one of their caregivers. A sample size of ten participants for the usability study was based on prior work demonstrating that ten people identify 95% of usability problems (53). Participants were recruited from the community using methods such as social media and flyers. Children provided assent and caregivers provided written informed consent. Children and their caregivers used the VR experience to test functionality and provided feedback. Children were debriefed post-VR experience given their increased vulnerability to believing virtual experiences as real. Specifically, children were asked after the VR experience whether they found anything about the experience confusing, and follow up questions were asked to ensure children understood the idea of a virtual or artificial environment.

Measures

Usability was assessed through caregiver-proxy report by revising items to have caregivers report on their child’s experience of usability. Measures included: (I) the System Usability Scale (SUS), a 10-item measure of usability (54); (II) the Usefulness, Satisfaction, and Ease of Use (USE) questionnaire (55), a 30-item measure assessing usefulness, ease of use, ease of learning, and satisfaction; and (III) the Presence Questionnaire (PQ) (56), a 24-item measure of the degree to which an individual feels immersed in a virtual environment; one item related to sense of touch was not applicable and removed from the scale before administration. Total scores on the SUS, USE, and PQ are created by reverse coding negative items and summing item responses. In addition to reverse coding, item scores on the SUS are transformed linearly to create possible total scores from 0 to 100.

During usability testing cycles, participants were observed while being asked to use the “think aloud” strategy, verbalizing their thoughts as they use the VR experience, including reactions and identification of glitches, while a trained research assistant took notes (57). Children also completed a brief, semi-structured interview to assess acceptability, satisfaction, and overall impressions of the VR experience. Children were asked to indicate their subjective experience of “presence”, i.e., their impression of how much they felt to be in the virtual environment rather than merely observing it, as well as how much they enjoyed the experience, how willing they would be to use the experience again, and how willing they are to eat healthier, on a 5-point analogue Likert scale with faces. Greater scores on the scale indicate greater immersion, satisfaction, and acceptability. Participants were compensated $25 each for their participation (i.e., $50 total for each child-caregiver dyad).

Data analysis

Descriptive statistics for the SUS, USE, and PQ were calculated. Audio recordings were transcribed verbatim using Amazon Transcribe, and were cross-checked for accuracy by research staff and examined for major themes. These data were used to inform refinements to the VR experience examined in study 2.

Results of study 1

Children (n=5, 3 girls) had a mean age of 11.0 (SD =2.24) years. As seen in Table 1, caregivers (n=5, 5 women) reported good usability (mean SUS =82.5 out of maximum score of 100, mean USE =97.6) and excellent immersion in the virtual environment (mean PQ =128.0 out of maximum score of 161). Children reported high immersion (mean =4.4 of 5), and willingness to try to eat healthier after playing the game (mean =4.8 of 5). All children reported high satisfaction with the game, and that they would want to use the game again. Qualitative feedback from children and caregivers informed refinements, which included technical (e.g., controllability of the go-kart and display functions) and content refinements (e.g., voiceover changes for clarity of psychoeducational content), presented in Table 1.

Study 2: pilot RCT

Study 2 used a pilot randomized trial design to compare the VR experience to an active comparison condition with a focus on evaluating the acceptability and preliminary efficacy of the intervention (58). The control intervention involved a video (developed for the study) and mobile game (BAM Dining Decisions developed by the Centers for Disease Control and Prevention) that provides child-friendly education on what types of foods are most nutritious and which are less healthy, and how the food they eat now affects their health. The video was approximately 4 minutes long, with PBS FitKids Eat (59) short videos (e.g., “Eat a Rainbow”) combined with additional video content with a voiceover that included the same language used in the VR experience. Children played the mobile game for approximately 6 additional minutes, such that both conditions had a gaming aspect, included similar psychoeducational content, and were similar in length (approximately 10 minutes).

Participants & recruitment

Participants were eligible for enrollment if they were children between 6 and 12 years of age, comfortable speaking English, had a parent or legal guardian who could provide informed consent/assent, and had a BMI ≥85^th percentile for age and sex. Caregivers were eligible if they had an eligible child and a BMI ≥25 kg/m². Children were excluded if they were participating in behavioral weight management, screened positive for disordered eating behaviors (purging or bingeing), or did not meet inclusion criteria. Participants were recruited from the community using methods such as social media and flyers. Additionally, participants were contacted and recruited through medical chart review of patients meeting eligibility criteria and volunteering to be contacted for research studies within a midwestern medical system. The sample size was determined a priori to be 25–30 dyads, with the goal to examine acceptability and preliminary efficacy on behavioral cognitions. Data were collected from April 2021 until March 2022 (ClinicalTrials.gov Identifier: NCT04845568). Recruitment ended after reaching the a priori target sample size along with funding limitations.

Procedure & randomization

All procedures took place in a clinical laboratory within a medical school in the midwestern U.S. Dyads were randomly assigned to the experimental or control condition as they were recruited using a random number generator in Excel generated by a blinded assessor prior to the laboratory visit by participants. After children provided assent and caregivers provided written informed consent, children and caregivers completed baseline measures, including having height and weight taken. Participants were told which condition they were receiving after the baseline assessments. In the VR condition, both caregivers and children used the VR experience, to allow the caregivers to report on their experience of immersion (i.e., presence) in the VR environment. Caregivers also watched their children play the VR experience on a 2-dimensional monitor, where the VR environment that the child was seeing was telecasted onto a screen for viewing. In the control condition, caregivers watched the video with the child and then watched the child play the smartphone game. Immediately after experiencing either the experimental or control task, participants completed post assessments. Children were debriefed post-VR experience as in study 1. Two weeks later, participants were emailed follow-up measures and asked to complete them within 48 hours. Participants received $25 each for their participation in the in-person session (i.e., $50 total for each child-caregiver dyad). For completion of the 2-week follow-up, participants received $25 each (i.e., $50 total for each child-caregiver dyad), for a total of up to $100 compensation for each child-caregiver dyad, as well as a chance to win one of two $250 gift cards via a raffle.

Four caregiver-child dyads were recruited from the same household/family (i.e., two dyads from 2 different households), with different caregivers and children (e.g., mother and son, father and daughter) in each dyad. Dyads from the same household were assigned to the same condition.

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the institutional ethics board of Washington University School of Medicine (No. 201912002 for study 1; No. 202004074 for study 2). Informed consent was obtained from the parents/guardians and informed assent was obtained from all children.

Assessments

Caregivers provided demographic information on their child and self at baseline.

Acceptability was assessed with the same caregiver-proxy and child report measures used in study 1.

Motivation to change behavior was measured by self-efficacy (60) and readiness to change behavior (61). Children reported self-efficacy for behavior change at baseline and post-intervention using the 16-item Self-Efficacy for Healthy Eating and Physical Activity measure (62). Caregivers reported their readiness to help their child change their eating and activity behaviors using the 6-item Readiness to Change Diet and Physical Activity Scale at baseline and two-week follow-up; caregivers were classified into their stage of change (i.e., precontemplation/contemplation, preparation, or action/maintenance) based on recommended criteria (63). Body esteem was self-reported by children at baseline and post-intervention using 3 items from the body esteem scale for children (64).

Behavioral attitudes and intentions toward eating fruits and vegetables and engaging in physical activity were assessed among children and caregivers at baseline and post-intervention with items adapted from previous literature based on the Theory of Planned Behavior (65,66). Scores were summed for behavioral cognitions, reported by children and caregivers pre- and post-intervention, with greater scores indicating more positive behavioral cognitions. For children, six items measured intentions to eat more fruits and vegetables or eat less junk food (defined as sugar-sweetened beverages such as soda, salty snacks such as chips, fast food, and sweet snacks or desserts such as cookies or candy) over the next 2 weeks, six items measured perceived behavioral control, and eight items measured attitudes towards eating more fruits and vegetables or less junk food. Items were adapted to measure caregiver intentions (4 items), perceived behavioral control (4 items), self-efficacy (3 items) and attitudes (7 items) toward helping their child engage in healthier eating behaviors. Where needed, language was adapted to lower the reading level for child participants.

Children self-reported and caregivers reported on child behavior at baseline and 2-week follow-up, assessed with items adapted from the Health Behavior in School-aged Children survey (67). Outcomes included number of meals away from home, fast food meals, days with at least 60 minutes of activity over the past 7 days, and frequency of fruit and vegetable consumption over the past 2 weeks. Caregivers reported on the child’s behaviors in the prior 2 weeks including frequency of consumption of breakfast, servings of fruit and vegetables, fast foods, family dinners, and the number of hours per day on a typical weekday that the child engaged in sedentary screen time and physical activity.

The 10-item Positive and Negative Affect Schedule for Child and Parent (68) was administered pre- and post-intervention for children to examine effects on mood. Current hunger was measured with a single item on a 10-point scale by children pre-intervention.

Data analysis

Descriptive statistics of primary (acceptability, child behavioral cognitions and behavior) and secondary outcomes (body esteem, caregiver behavioral cognitions and readiness to change) were examined. Independent samples t-tests evaluated the difference in acceptability measures between conditions. Self-reported child hunger did not differ between conditions and was unrelated to any outcomes at the bivariate level.

Tests of normality were conducted on dependent variables across and within conditions using histograms, normality plots, skewness, and kurtosis metrics. Due to non-normality and small group sizes, nonparametric tests were employed. Wilcoxon signed rank tests examined within group changes from baseline to post-intervention (cognitive outcomes) or 2-week follow-up (behavioral outcomes). Mann-Whitney U tests examined differences in change scores across experimental conditions. All analyses were completed in R Version 4.3.3 with use of the statsExpressions package (69).

Results

Study 2 results

Fifty-three caregiver-child dyads were assessed for eligibility and 32 dyads met eligibility criteria. Five caregiver-child dyads declined to enroll or were lost to follow-up. Fourteen dyads were randomized to the VR condition and 13 dyads were randomized to the control condition (Figure 1). Participants were 10.35 years old on average (SD =1.87), and caregivers (who were primarily the parents of the children with one grandparent participating) were an average of 44.48 (SD =7.21) years old. Children were 51.9% girls, 59.3% White, 25.9% Black, and 92.6% Non-Hispanic. Other baseline characteristics of the sample are presented in Table 2. Of the 14 dyads in the VR condition, only one owned a VR gaming system, four children reported using VR at least once or twice prior to the study, and seven stated they had never used VR. No child or caregiver reported (at the 2-week follow-up) that they played the publicly available dining decisions game after being in the lab. No adverse events were reported by study participants.

Figure 1 Study 2 CONSORT diagram. BMI, body mass index.

Table 3 presents the means and test statistics for the acceptability and usability measures. Acceptability, as measured by the SUS and the USE among caregivers, was above average (i.e., >68) (70) in both conditions. SUS and USE scores did not differ across conditions (Table 3). Presence in the virtual environment, reported by children and caregivers in the VR condition only, was high. Children in the VR condition reported significantly greater acceptability (mean =4.31, SD =0.48) compared to children in the control (mean =3.54, SD =0.84).

For all children, self-efficacy for healthy eating, self-efficacy for physical activity, attitudes toward healthy eating, and behavioral intentions for healthy eating increased from pre- to post-test. From baseline to 2-week follow-up, children reported more weekly vegetable servings (U=46, P=0.047), and number of active days (i.e., days with at least 60 minutes of activity; U=42.5, P=0.006) in the past week. Caregivers reported an average decrease in child screen time hours per day from baseline to 2-week follow-up (U=205, P<0.001. Across both conditions, positive affect increased significantly from pre-test to post-test (U=60.5, P=0.03), while negative affect did not change. Change scores in positive and negative affect did not differ across conditions. See Tables 4,5 for means and test statistics.

Change scores from pre- to post-test (cognitive outcomes) or pre- to two-week follow-up (behavioral outcomes) were significantly different for only one outcome: child attitudes towards healthy eating [rank biserial correlation (r); 95% confidence interval (CI): 0.44; 0.03, 0.72]. Children in the VR condition had greater change in attitudes towards healthy eating from pre- to post-test compared to children in the control condition. This is further reflected in the significant paired test for within condition change, where there was an increase in eating attitudes among children in the VR condition [r (95% CI)=−0.96 (−0.99, −0.88), P=0.004] but not in the control condition (P=0.10). Paired tests for within condition change also showed self-efficacy for physical activity significantly increased for children in the VR condition (U=20.5, P=0.047) and self-efficacy for healthy eating increased in the control condition (U=6, P=0.03). Behavioral intentions for healthy eating also increased from baseline to post-test among children in the control condition (U=10, P=0.045).

At baseline, caregivers were all in the preparation (63%) or action/maintenance (37%) stage of change, which did not differ across condition [χ²(1)=0.02, P=0.88]. At follow-up, caregivers were in the preparation (44.4%) or action/maintenance (55.6%) stage of change, which did not differ across conditions [χ²(1)=0.36, P=0.55]. Caregivers overall had greater attitudes, perceived behavioral control and self-efficacy toward helping their child improve their health from pre- to post-intervention. In paired within-group tests, only attitudes and self-efficacy increased among caregivers in the VR condition. Readiness to help child change significantly increased for caregivers in the VR condition from pre- to two-week follow-up (U=4.5, P=0.041), and did not differ for caregivers in the control condition (P=0.59).

Discussion

This project developed and tested a 10-minute, VR experience for children with higher BMIs and their caregivers, informed by evidence-based psychoeducational and behavioral change frameworks, to promote healthy eating behavior among families in a format that would be scalable and engaging for children. The VR intervention was found to have high acceptability and feasibility among both children and their caregivers. Moreover, usability scores on two different scales did not differ between the VR and control condition, which is noteworthy given that most children and adults are highly familiar with videos and mobile games and would likely rate usability and acceptability of these technologies as high. Similar usability scores reported by caregivers in both the video/mobile game and the VR conditions further emphasizes the high usability and acceptability of this digital medium, as this was most participants’ first time engaging with VR. It is also promising that children were highly interested in engaging with the experience, especially in the context of well-documented engagement issues in digital health, and that engagement is frequently associated with behavior change (71).

Children in both conditions increased their vegetable intake from pre-intervention to 2-week follow-up, which is consistent with brief digital psychoeducational, gamified interventions for promoting healthy nutrition intake among children (72). Self-efficacy for healthy eating and physical activity similarly increased in both conditions. Attitudes toward fruits and vegetables, an important antecedent for habit formation (73), also increased among all children, but children in the VR condition had significantly greater increases in positive attitudes from pre- to post-intervention compared to children in the control condition. This finding is promising and suggests the potential for VR to magnify the effects of evidence-based psychoeducational and behavioral intervention through an engaging medium. Attitudes are a significant, proximal determinant and predictor of behavior, and therefore a critical intervention target for sustaining behavior change. Longer or repeated engagement with digital programs and interventions is associated with greater cognitive and behavioral changes, therefore it will be important for future work to examine the effects of repeated exposure to the intervention as compared to the control condition to determine whether differences across conditions would be sustained, heightened, or diminished. Additionally, when considering real-world dissemination of the intervention, where engagement cannot be highly controlled as in a clinical trial, it is even more important to have high acceptability of an intervention. Children in the VR experience rated the intervention highly acceptable, and expressed interest in using the experience repeatedly, suggesting that motivation to engage with this medium and intervention could have significant implications for real-world engagement with this type of digital health programming.

Caregiver readiness to help their child change eating habits was high among both conditions, reflected in the fact that all caregivers were categorized in the preparation or action/maintenance stage of change, suggesting they were already involved in supporting healthy habits among their children. High motivation is a common demand characteristic among participants who enroll in behavioral interventions; future research could aim to enroll participants with more varied motivation levels. Interestingly, caregiver readiness to change increased at 2-week follow-up among caregivers randomized to the VR condition, while caregivers in the control condition did not report any change from baseline to 2-week follow-up in readiness to support child behavior change. Given the critical role caregivers play in supporting and encouraging healthy lifestyle behaviors among children (48), this finding suggests that there may be benefits to including caregivers in this intervention, although further research will need to investigate whether these effects would translate to positive, supportive behavioral changes among caregivers. The majority of VR studies that target children and adolescents have not included parents in the intervention, though they may benefit from doing so. Although the caregivers and children interacted with one another during their use of the VR experience, future research could consider developing and testing specific VR programming targeted at caregivers that could more fully integrate caregivers in the intervention, including multiplayer games to involve the caregiver and child together.

VR research with children in this context is still nascent, although VR research with adults supports the ecological validity of virtual eating environments (74), and the utility of VR for replicating real-world eating contexts (75,76). Future iterations of this experience could include more simulated eating behavior to support children in trying new or unfamiliar foods, as VR environments are particularly helpful for promoting self-efficacy (22,77), as was reflected in this pilot. Motivational interviewing could also be included in future iterations of the experience, which has shown promise for promoting healthy habits among children (78). Despite the present trial being a small, underpowered pilot RCT, this work suggests that VR should be considered in intervention design, where children may find the VR environment more engaging and interactive when compared with similar content in a video format including a mobile gaming element. This has important implications for community-based interventions such as school-based nutrition education interventions, where children could engage with school-owned VR headsets to supplement and reinforce health or nutrition concepts in a compelling, immersive environment. The ubiquity of smartphones coupled with the proliferation of inexpensive VR headsets (e.g., Google Cardboard, which turns a smartphone into a VR device, costs $5), makes the adaptability of the VR platform to these highly portable and prevalent devices a unique opportunity for disseminating evidence-based treatment. That said, this work should continue to be developed in parallel with efforts focused on understanding and addressing social, economic, and contextual factors related to eating behavior and nutritional health promotion. Promoting health equity in this work will need to not only demonstrate the efficacy of the VR intervention, but simultaneously promote equitable access to the intervention and to affordable healthy food through partnerships and collaborations.

Strengths and limitations

This study had several strengths, including using user-centered design principles and usability testing prior to piloting the experience in a RCT. Rigorously designing the VR experience from a user-centered design perspective facilitates engagement and ultimate scale up, and this was reflected in the high acceptability and usability reported by the participants. The psychoeducational content was developed from tenets of evidence-based behavioral health treatment that have been previously shown to improve eating and activity behaviors among children and their caregivers in rigorous clinical trials (6). Finally, the study utilized a rigorous comparison condition which included similar psychoeducational content delivered through a kid-friendly video, including exact quotes from the VR experience, combined with a smartphone game that reinforced healthy eating choices. Therefore, our preliminary findings highlight the unique properties of VR that show potential for engaging children in healthy habit formation through enjoyable games.

This study is not without limitations, including the use of a convenience sample, and the small sample size inherent to pilot studies. The study also included self-reported behaviors which can be subject to recall bias, and did not have long-term follow-up. The VR experience took a high-level approach to nutrition education, and the brevity of the intervention (10 minutes) limited the ability to explore more nuanced concepts within nutrition, where all foods have functions and purpose (e.g., protein can sustain us longer), and nourishment in any form is preferable if choices are limited (by food insecurity, for example). Given that the intervention involved only one 10-minute experience, it is noteworthy that the VR intervention showed significant improvements in eating-related cognitions compared to a robust, active control condition. Future work should examine the impact of repeated exposure to the experience over time, and examine long-term effects and other important mediators and moderators of intervention efficacy such as internalization of shame involved with eating. Finally, this study limited participants to children and caregivers with higher BMIs according to BMI growth charts and CDC classifications of overweight and obesity. If this study were to be conducted again, the weight-related inclusion/exclusion criteria would be removed, as the VR experience could be beneficial and health promoting to children and caregivers regardless of body size.

Conclusions

Childhood is a critical time for development of health behaviors that persist into adulthood making this time in a child’s life optimal for instilling healthy eating habits. Harnessing novel technologies such as the immersive properties of VR to engage children in theory-informed brief psychoeducational gaming experiences shows promise for improving child and caregiver eating-related cognitions. Given the increasing accessibility of virtual and augmented reality environments, VR interventions have the potential for providing highly scalable behavioral interventions to children and families.

Acknowledgments

The authors wish to thank the families who participated in this study, and Ms. Yilin Wang who assisted in the literature searches. We also wish to acknowledge and thank our industry partners, RealizedCare.

Funding: This study was supported by NIDDK P30 DK092950 Washington University Center for Diabetes Translation Research (to L.A.F., D.E.W., and E.F.C.). Additional support was provided by National Institutes of Health (No. K01 MD017630 to L.A.F., No. K08 MH120341 to E.F.C., and No. R01 MH115128-02S1 to M.M.V.). The National Institutes of Health had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.

Footnote

Reporting Checklist: The authors have completed the CONSORT reporting checklist. Available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-24-24/rc

Trial Protocol: Available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-24-24/tp

Data Sharing Statement: Available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-24-24/dss

Peer Review File: Available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-24-24/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-24-24/coif). L.A.F. reports support from NIDDK P30 DK092950 Washington University Center for Diabetes Translation Research, and funding from the National Institutes of Health (NIH) (No. K01 MD017630). M.M.V. reports the funding from NIH (No. R01 MH115128-02S1). E.F.C. reports support from NIDDK P30 DK092950 Washington University Center for Diabetes Translation Research, and funding from NIH (K08 MH120341). E.F.C. also serves on the Clinical Advisory Board for Beanbag Health, receives royalties from UpToDate, and is a consultant for Kooth. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the institutional ethics board of Washington University School of Medicine (No. 201912002 for Study 1; No. 202004074 for Study 2). Informed consent was obtained from the parents/guardians and informed assent was obtained from all children.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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