Abstract
PURPOSE:
The majority of behavioral intervention technologies (BITs) have been designed and targeted towards the general population (i.e., typically-developing individuals); thus, little is known about the use of BITs to aid those with special needs, such as youth with disabilities. The current study assessed adolescents and young adults with spina bifida (AYA-SB) for: 1) their technology usage, and 2) anticipated barriers to using technology to help manage their health.
METHODS:
AYA-SB completed a survey of their media and technology usage. A card sorting task that ranked and grouped anticipated barriers to using a mobile app to manage health was also completed. Ranked means, standard deviations, and the number of times a barrier was discarded were used to interpret sample rankings.
RESULTS:
AYA-SB reported less frequent technology and media use than the general population. However, differences emerged by age, with young adults endorsing higher usage than their younger counterparts. Top concerns focused on usability, accessibility, safety, personal barriers due to lack of engagement, technological functioning, privacy, and efficacy.
CONCLUSIONS:
AYA-SB appear to be selective users of technology. It is therefore critical that the design of BITs address their concerns, specifically aiming to have high usability, accessibility, and engagement.
Keywords
Introduction
Behavioral Intervention Technologies (BIT) is a term used to describe the use of technology (e.g., mobile apps, web pages, sensors [e.g., FitBit]) to deliver behavioral change interventions aimed at improving mental and/or physical health and achieving wellness targets [1]. “MyFitnessPal,” a web platform and mobile app that aims to help people lose weight through tracking their caloric intake and physical activity, is one of many examples of BITs currently available for public use [1, 2]. BITs were originally introduced as a means to access those who might not otherwise receive care. However, with the now ubiquitous nature of technology in daily life [3] and the growing fields of electronic and mobile health (eHealth/mHealth), BITs are being designed, evaluated, and deployed to reach large varieties of populations [4]. Despite the growth of BITs, the majority of products have been designed and targeted towards the general population (i.e., typically-developing individuals). Therefore, little is known about the use of BITs to aid those with special needs, such as youth with disabilities.
Individuals with spina bifida (SB) are a uniquely situated patient population for which to design BITs. SB is the most common congenital birth defect affecting the central nervous system and requires self-management of a complex medical regimen [5]. Nicknamed a “snowflake condition,” because no two individuals are impacted in the exact same way, SB overlaps with symptom profiles and the management needs of chronic health conditions, physical disabilities, and intellectual disabilities [6]. BITs therefore offer the potential to deliver flexible monitoring and intervention tools that can address the variability of self-management needs in SB, while also overcoming barriers (e.g., mobility) that may interfere with traditionally-delivered interventions [7]. Further, given the overlap of SB with the symptom profile of many other conditions, BIT tools designed for youth with SB may generalize well to other pediatric populations.
Previous BIT development for SB has centered around self-management in people with disabilities. Indeed, the iMHere platform (originally designed for people with SB, cerebral palsy, and spinal cord injuries) includes an app with many self-management modules (e.g., medication management, skin integrity, bowel/bladder programs, mental health) and the potential to use a communication portal to connect patients with their clinicians and caregivers [8]. Unfortunately, a randomized controlled trial of the first version of the platform indicated that benefits were only observed with high users of the system [9]. Improvements to the system since the trial have focused on increasing accessibility of the platform, particularly for those with dexterity impairments [10, 11, 12]. While iMHere is a comprehensive system, one that is being further refined through usability testing and focus groups [13], it has been evaluated primarily with young adults with SB.
Youth with SB likely have unique needs as users of technology [6]. This includes adolescents and young adults (AYA) with SB (hereafter referred to as AYA-SB), who must navigate the complex developmental period from childhood to adulthood. During this time, AYA-SB gain increasing responsibility and autonomy over their demanding medical regimen, and are also at increased risk for a decline in medical adherence [14, 15]. Non-adherence increases the likelihood of experiencing preventable complications (e.g., urinary tract infections) that can be life-threatening for AYA-SB [16, 17]. Given the high stakes of adherence, youth with SB require BITs that reach them effectively and consistently.
To ensure that BITs reach youth with SB appropriately, this population’s use and approach to such technology needs to be better understood. While most AYA-SB endorse internet use [18] but relatively low screen time [19], little is known about their overall technology usage. Additionally, in using BITs to overcome barriers in monitoring and interventions delivered through traditional means (e.g., clinic), it is likely that the use of this technology (e.g., a mobile app platform to deliver self-management like the iMHere system) has barriers of its own from the perspective of youth with SB. Further, these barriers might affect individuals differently across a given sample due to the variable symptom profile of SB. This emphasizes the need to also assess individual barriers. If technology consumption and anticipated obstacles to using BITs for self-management can be determined early in the app development process, design decisions can be better informed to meet the diverse needs of youth with SB. Therefore, the purpose of the current study was to address these gaps in knowledge. Specifically, AYA-SB were assessed for: 1) their technology usage, and 2) anticipated barriers to using technology to help manage their health.
Methods
Participants
Participants were recruited from the YMCA- sponsored Camp Independence during the 2018 summer sessions. Camp Independence is located in Illinois and is a sleep away camp designed for AYA-SB. Programming included: 1) a one week stay with similarly aged campers; 2) typical camp-based activities (e.g., swimming) with accommodations for camper needs; and 3) camp-based interventions to promote medical and social independence. This study contained two separate procedures: 1) the completion of a self-report technology usage assessment; and 2) a technology barriers assessment completed using a card sorting task. All campers who participated in an ongoing, camp-based independence study were invited to complete the questionnaire assessing technology usage [20, 21, 22]. Participants were eligible for study inclusion for the card sorting task assessing barriers to using technology if they: 1) had SB; 2) were between 13 and 30 years of age; 3) attended Camp Independence during the summer of 2018; 4) had previously used a mobile app independently; and 5) could read and write in English.
Procedure
This study was approved by the Loyola University Chicago Institutional Review Board (IRB). Participants 18 years of age and older provided informed consent. Participants under 18 years of age provided informed assent, and their parents provided consent.
Technology usage
All campers participating in an ongoing independence study were invited to complete a questionnaire assessing their use of technology as part of their baseline camp assessment [20, 21, 22]. Please see the Measures section for information about this questionnaire.
Barriers
Replicating previous work which identified barriers to the use of apps for condition-specific interventions [23], this study adopted an open card sorting task to identify barriers to the use of BITs for AYA-SB [24]. Participants completed this task one-on-one with a moderator. To complete the card sorting task, participants were handed a stack of 20 cards, each with anticipated barriers to general BIT use that were based on findings from the literature [13] and informal polls of experts (i.e., clinicians and researchers with expertise in SB). Participants were instructed to: 1) sort the cards from the greatest to the smallest barriers, 2) discard any cards that were not relevant to them, 3) add any cards they thought were missing (i.e., they were provided blank cards onto which they could add their own barrier ideas), and 4) ultimately, group any barriers that they thought belonged together. Specifically, the moderator read the following script to each participant:
I’m providing you with a stack of cards that have reasons that people might not want to or be able to use technology to help with their physical or mental health, like a healthy eating app on a phone. I would like you to go through the cards and choose the ones you think are barriers to this way of using technology. Once you choose them, please decide which ones are the biggest barriers. You can lay the cards down on the table so that you can put ideas down from biggest barriers to smallest. You also might notice that some could be placed into groups in your mind; feel free to put them into groups. If there are cards you think do not apply, feel free to put them over here to be discarded. If there are cards with barriers we didn’t think of, we can add more [indicate blank cards and marker]. Please feel free to think aloud as you go through the cards.
The task was timed as a measure of feasibility to ensure that the task was not overly burdensome for this population (i.e., taking an especially long time to complete). The finished groupings of cards were photographed to ensure data accuracy. Participants were also provided time to share their rationale regarding their card sort via qualitative feedback. Finally, the cards were shuffled between participants to reduce possible bias.
Measures
Demographics
Participants were asked to report the following information: age, sex, race/ethnicity, and SB characteristics such as type, shunt status, and lesion level. If participants were unsure of any of their demographic information (e.g., type of SB), they were provided the option to answer “not sure.” Full Scale Intelligence Quotient (FSIQ) was measured and collected for AYA-SB who: 1) also participated in another camp-based study [20, 21, 22]; and 2) completed the barriers assessment through the card sorting task.
Technology usage
The Media and Technology Usage and Attitudes Scale (MTUAS) is a self-report measure assessing media and technology use [25]. Participants were offered a choice in completing the MTUAS in a paper or online format. For the purposes of the current study, the usage subscales were administered, which are comprised of 44 items, with 11 subscales: smartphone usage, general social media usage, internet searching, emailing, media sharing, text messaging, video gaming, online friendships, Facebook/social media friendships, phone calling, and TV viewing. Respondents were asked to provide frequencies to their technology usage behaviors based on a 10-item frequency response scale, including: never, once a month, several times a month, once a week, several times a week, once a day, several times a day, once an hour, several times an hour, and all the time. For the Facebook/social media friendships section, participants were queried if they had a Facebook or similar type of social media account (e.g., Instagram); if not, they were instructed to skip the Facebook/social media friendships section. Frequencies related to Facebook/social media friends were based on a nine-item frequency scale, including: 0, 1–50, 51–100, 101–175, 176–250, 251–375, 376–500, 501–750, and 751 or more. The reliability of the subscales range from acceptable to high in the general population (
Demographic and spina bifida characteristics,
(%)
Demographic and spina bifida characteristics,
Note. M
Descriptive analyses were used to explore the technology usage reported on the MTUAS. To explore differences in technology usage by age group, standardized mean differences were calculated between youth under 18 years of age and adults 18 years of age and older [26].
For the card sorting task, each card was assigned a number to enable the mean rank for each card to be determined for each participant. Mean rankings of cards varied by participant. For example, one participant may have placed several cards into three different “groupings” (which would then have equal rankings with their other group members) and not used four cards (as the participant did not find the barriers noted on those cards to be personally relevant; therefore, these cards would not have a mean ranking for this participant). Conversely, another participant may have listed all cards in order from greatest to lowest barriers without creating groupings nor discarding any cards.
Results
Sample characteristics
All campers participating in an ongoing, camp-based independence study were invited to complete the questionnaire [20, 21, 22]. However, as some elected not to participate in the barriers assessment and/or did not meet inclusion criteria, the samples differed in size. Ninety-one campers completed the MTUAS and 29 campers completed the card sorting task. Those completing the MTUAS were between the ages of seven and 37 (
Media and technology usage,
(SD;
frequency response anchor)
Media and technology usage,
Note. Frequency scales range from 1–10, with higher scores indicating more frequent use. For the Online and Facebook Friendship subscales, frequency scales range from 1–9, with higher scores indicating more friendships. The frequency anchor associated with the means for the subscales are provided in the table. M
AYA-SB reported average frequency anchors that would suggest less frequent technology and media use on the MTUAS than the average frequency anchors endorsed by adults in the general population [25] (see Table 2). The only exception to this was TV watching, with respondents with SB reporting that they watch shows, movies, etc., on a television set several times a day (as opposed to the average of once a day reported by the general population [25]). Of note, 25 participants (27.5%) reported not having a Facebook or similar social media account.
The adult participants with SB (18–37 years old) endorsed higher usage than youth with SB (7–17 years old) in multiple categories. Specifically, in examining standardized mean differences between the two age groups, a medium difference was detected for social media usage (0.70), media sharing (0.60), number of Facebook friendships (0.68), and phone calling (0.60). A large standardized mean difference was detected for emailing (0.98).
Barriers
The average time required to complete the card sorting task was around five minutes (
Barriers to using a mobile app to manage health
Barriers to using a mobile app to manage health
Note. Lower ranked means indicate higher ratings as a barrier. SD
Qualitative feedback following the card sorting task most frequently addressed worries about an app being too difficult to use (
The current study aimed to assess technology usage in AYA-SB and their anticipated barriers to utilizing BITs to help manage health. AYA-SB reported less media and technology use than norms established with typically-developing adults [24], with the exception of TV watching. The lessened frequency overall may have been driven by the child and adolescent reporters, who endorsed significantly lower frequencies than adults with SB in general social media usage, emailing, media sharing, text messaging, Facebook friendships (more friendships), and phone calling. For anticipated barriers to using an app to manage their health, AYA-SB most frequently endorsed concerns around usability, accessibility, safety, personal barriers due to lack of engagement, technological functioning, privacy, and efficacy.
Recent reports indicate that 45% of adolescents describe their internet usage as nearly-constant [27] and that adults spend about half of the day engaging with media [28]. This stands in contrast to the overall reported frequencies of media and technology use in the current study. Yet, the frequencies reported by the current sample may be accurate for AYA-SB, given a recent survey indicating daily screen time is around two hours for this population (ages 15–24) [19]. These frequencies may also be reflected by about 40% of the sample selecting that it “Takes too long to use” as a top barrier to using an app. However, this limited usage is not necessarily an indicator that we should avoid developing BITs for AYA-SB. Rather, it likely raises the bar for the design of BITs to fit the unique needs of AYA-SB as selective technology users.
The anticipated barriers to BIT use identified in the current study further implicate the importance of design in the selective technology usage of AYA-SB. Indeed, the top barriers reflect the need for BITs targeted at AYA-SB to have high usability, accessibility, and engagement. In terms of usability, top barriers reflected the attributes of: 1) learnability, or how easily a user can complete a task during the first encounter (e.g., “too hard to use”), 2) efficiency, or how well and fully tasks are completed in a given amount of time (e.g., “too many steps,” “takes too long to use”), and 3) satisfaction (e.g., “not helpful”) [29]. Usability has been implicated in poor engagement with BITs for other populations [30, 31]. These findings in and of themselves are therefore not novel. It is likely that if AYA-SB anticipate poor usability, or experience it during initial use, they are likely to abandon the BIT. While the identified usability issues highlight the frequently touted importance of user-centered design to not only best serve likely end users of a BIT, they also emphasize the need to overcome anticipated barriers to use. BITs for AYA-SB must not only be highly usable for the population, but also must be marketed to this population to effectively relay that these BITs are designed and/or adapted for their specific needs [32]. Therefore, formative (conducted throughout the development process) and summative (conducted at the end of the development process) usability testing is critical for future BITs designed for AYA-SB [6]. Feedback on how to market such BITs should be directly elicited from AYA-SB and their caregivers.
Related to effective communication with AYA-SB about the usability of specific BITs, safety measures must also be transparent. Experiences with bullying for youth with SB are unfortunately well-documented [33, 34] and the current sample’s reported concerns were consistent with the literature. Indeed, two-thirds of the sample included “Don’t want to be bullied” in their card sorts and when generally queried about perceived barriers to using a health app, several participants described strong concerns about bullying in an online space. This response was elicited without any suggestion of peer or interactive components involved in a health app. While clear and effective privacy settings frequently have been noted as a critical design feature in the BIT and larger digital health literature, the current findings highlight that these privacy and safety mechanisms must be made explicit for AYA-SB. Without making such features explicit, AYA-SB are less likely to engage with BITs for fear of safety.
SB is associated with variable levels of impairment in motor dexterity, coordination, hearing, vision, and visuo-spatial processing [35]. These impairments were also implicated in barriers, highlighting accessibility problems with technology (e.g., “not personalized for spina bifida,” “too hard to use,” “no hands-free options,” “font and buttons too small”). This finding may speak to two issues. First, it may stand as a possible explanation for the low technology usage rates compared to the general population [19, 27, 28]. Second, it highlights that BIT designs must thoroughly address barriers due to accessibility (for such an example, see the work to improve the iMHere platform for motor dexterity impairments) [10, 11, 12]. This latter point further underscores the need for formative usability testing of BITs for AYA-SB, while also emphasizing the need to ensure as much simplicity and accessibility as possible [36], starting with the very first design iteration [37].
The included barriers also implicate the need for engagement (e.g., “I forget to use it”). Indeed, as it is likely that AYA-SB are selective technology users, a BIT to support their self-management must compete with screen time already dedicated to popular sites, such as YouTube, Instagram, Snapchat, and Facebook (e.g., “Rather use social media”) [27]. While it is expected that AYA are generally interested in social media, AYA-SB may be particularly reliant on such platforms to facilitate social interactions that they may not have through in-person experiences [38, 39]. The use of technology to facilitate social interactions may also serve as a possible explanation for the higher media and technology usage reported by the adults of this sample, as they may be less likely to: 1) have structured social interactions in daily life (e.g., no longer being in school), and 2) have parental monitoring of their screen time (e.g., the Centers for Disease Control and Prevention recommend two hours or less per day for children under 18) [40]. The need for BITs targeted to AYA-SB to be engaging further speaks to the need for acceptable usability [29], and also implicates the incorporation of social networking and/or peer interactions in design [6].
The current study had multiple strengths, including being the first evaluation of barriers to using an app for self-management in AYA-SB through the use of a card sorting task [24]. While there was a highly variable amount of time for participants to complete the card sorting task (Range: 0:57–34:32), this study demonstrated that this methodology is feasible for use with AYA-SB. However, the findings should also be considered in light of several limitations. First, some medium to large differences in technology and media usage emerged between the youth (17 years of age and under) and adults (18 years of age and older) in the sample. For this reason, it is likely these two groups anticipate and face different barriers to BIT use. However, the sample size limited our ability to analyze the card sorting data separately for these two groups (e.g., a sample size of 15 per “group” is recommended in analyzing differences in card sorting data) [41]. Also of note, the MTUAS was normed with individuals 18 years of age and older. While the items appeared to be easily understood by the pediatric participants in this study, face and construct validity testing with pediatric participants was not conducted. Future research should be powered to detect and explore age-driven differences within a sample of AYA-SB, allowing for specific age groups to be explored (e.g., early teens [12, 13, 14] vs. late teens [15, 16, 17] vs. young adults [18, 19, 20, 21, 22, 23, 24, 25]). Future research should also explore whether parental factors (e.g., monitoring and/or limiting screen time) drive such differences in use by age. Second, the sample was recruited from the YMCA-sponsored Camp Independence [20, 21, 22]. Beyond the sample lacking a great deal of ethnic and racial diversity (i.e., the majority was non-Hispanic Caucasian), it was also comprised of AYA-SB who have the support and ability to attend a sleep-away summer camp session. Future research involving BITs with users with SB should include more diverse populations (including those who are bilingual and/or do not use English as a primary language within the home) within their “real world” environments. Third, as has been previously noted in other card sorting studies [23], participants may have inferred different meanings than intended from the barriers listed on the cards. However, following the task, qualitative feedback was utilized to ensure appropriate meanings were inferred.
In conclusion, AYA-SB may be selective users of technology. Further, this selectivity may be dependent upon age, such that young adults with SB engage with technology more frequently than their younger counterparts. Based upon barriers in the current study, BITs likely need to have high usability, accessibility, and engagement to best reach and serve AYA-SB in promoting their self-management. Future research should continue to involve AYA-SB directly in the design, evaluation, and implementation of BITs for their self-management.
Footnotes
Acknowledgments
This research was supported in part by a Research Support Grant from Loyola University Chicago and grants from the Kiwanis Neuroscience Research Foundation: Illinois-Eastern Iowa District of Kiwanis International, National Institute of Nursing Research and the Office of Behavioral and Social Sciences Research (R01 NR016235), National Institute of Child Health and Human Development (R01 HD048629), and the March of Dimes Birth Defects Foundation (12-FY13-271). Dr. Stiles-Shields is also supported by a fellowship from the Cohn Family Foundation. The authors thank the YMCA-Sponsored Camp Independence and the CHATS Research Team, without whom this research would not have been possible.
Conflict of interest
The authors do not have any conflicts to report.