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While technology use in pediatric therapies is increasing, there is so far no research available focusing on how pediatric speech-language pathologists (SLPs) in the United States use technology.
This paper sought to determine if, and to what extent, pediatric SLPs are using mobile apps, to determine what purpose they are using them for, and to identify gaps in available technology to provide guidance for future technological development.
Pediatric SLPs completed an online survey containing five sections: demographics, overall use, use in assessment, use in intervention, barriers, and future directions.
Mobile app use by 485 pediatric SLPs in the clinical setting was analyzed. Most (364/438; 83.1%) pediatric SLPs reported using technology ≤50% of the time in their clinical work, with no differences evident by age group (<35 years and ≥35 years;
A majority of pediatric SLPs are using mobile apps less than 50% of the time in a pediatric setting and they use them more during intervention compared to assessment. While pediatric SLPs are hesitant to add to their client’s screen time, they would like more apps to be developed that are supported by research and are less expensive. Implications for future research and app development are also discussed.
Mobile health (mHealth) is health information or medical services that are delivered or enhanced through mobile communication and information technology [
Technology use is rapidly increasing, and not just for adults. Children are interacting with technology at home: more than half of parents have downloaded apps specifically for their children [
Despite the obvious growth of mHealth in home, medical, and educational settings, research supporting the outcomes of mHealth in speech-language pathology is just emerging, and research in the United States has been limited. There is a body of research that has examined the use of game-based applications for speech and language disorder intervention [
However, despite the American-Speech-Language-Hearing Association (ASHA) member newsletter having published numerous articles about mHealth in clinical practice, ranging from promoting specific apps [
It is clear that mHealth is a growing trend, with children using mobile and tablet devices at home and school. Furthermore, there is emerging evidence that suggests that how adults interact with children during tablet use plays a strong role in their effectiveness [ (1) Do pediatric SLPs use technology in clinical practice and what are the barriers to use;
and
(2) Do pediatric SLPs want more technology available and in which areas?
To answer the above research questions
The final survey questions were not randomized, due to adaptive questioning. Adaptive questioning was used to reduce the number of questions asked when they were not applicable. Due to adaptive questioning, participants saw as few as two screens (if they did not meet the first inclusion criteria) or as many as 11 screens based on their responses (including informed consent). Each screen contained a range of one to six questions per page. Only inclusion criteria questions had to be answered before moving on or completing the survey. Participants were able to revise answers using a back button on the survey. See
Survey flow diagram.
Participants were recruited using convenience sampling through advertisements on social media and direct emails to pediatric practices from all fifty states. See
Investigators posted to pediatric SLP–focused Facebook groups on topics such as pediatric speech therapy, preschool SLPs, early intervention SLPs, and school-based SLPs. The announcement was also posted in research-based groups, such as “SLPs for Evidence Based Practice”. SLPs visit these groups to ask clinical questions, inquire about issues in the field, provide ideas and resources to others, ask questions, present recent research, and occasionally post job openings. Thus, most survey participants were engaged in social media and continuing education in the field. Additionally, private practices were randomly selected using Google searches for “pediatric speech therapy + state name” for all 50 states. The first three listings were emailed the email script (see
Participants reported demographic and practice information (see
Participant demographics (n=485).
Variable | Value, n | |
|
|
|
|
Female | 467 |
|
Male | 18 |
|
|
|
|
18-24 | 14 |
|
25-34 | 252 |
|
35-44 | 128 |
|
45-54 | 59 |
|
55-64 | 22 |
|
65-74 | 1 |
|
|
|
|
White | 434 |
|
Black | 8 |
|
American Indian or Alaska Native | 1 |
|
Asian | 17 |
|
Native Hawaiian or Pacific Islander | 0 |
|
Other | 15 |
|
|
|
|
0-3 | 120 |
|
4-7 | 118 |
|
8-11 | 81 |
|
12+ | 154 |
|
|
|
|
Hospital-NICUa | 5 |
|
Hospital-other inpatient | 5 |
|
Hospital-outpatient | 40 |
|
Private practice | 83 |
|
School | 227 |
|
Early intervention | 74 |
|
Other | 41 |
|
|
|
|
Birth to age 3 | 195 |
|
Preschool (age 3-4) | 308 |
|
Early school (age 5-7) | 297 |
|
Late elementary (age 8-10) | 234 |
|
Middle school (11-13) | 134 |
|
High school (14-18) | 85 |
aNICU: neonatal intensive care unit.
All entries were analyzed, including incomplete questionnaires. Questionnaires were not monitored for multiple entries or atypical time stamps before analysis. The survey sample was judged to be representative, as it closely aligns with ASHA membership demographics in terms of gender, ethnicity, and work site, so weighting was not utilized. One notable difference is age, which was specifically analyzed using chi square analyses. Age was divided into two categories of near equal population size: age 18-34 years (n=254) and 35 years and older (n=201). The average time participants spent on the survey was 22 minutes. The average progress (how much of the survey they completed) was 88.2%. Of the 624 surveys opened, 482 were completed, resulting in a completion rate of 77.2%. View and participation rates could not be calculated.
For questions with discrete answers, percentages for each question were calculated automatically using Qualtrics’ analysis of responses. The survey also included open-ended questions about the participants’ barriers to use and desires for future use. Coding and analysis of these responses followed an inductive, iterative process inspired by grounded theory analysis, where responses were analyzed for codes and these codes were then iteratively clustered into higher-level themes [
The first aim of the study was to understand if pediatric SLPs are using technology in clinical practice. A total of 367/457 respondents (80.3%) indicated they use technology all or some of the time. Only 73/457 (16.0%) of the pediatric SLPs reported rarely using technology, and 17/457 (3.7%) reported never using technology. There was not a significant difference between age groups in the use of technology (X21=0.221;
Of those who did use technology, 223/438 respondents (50.9%) used it during 0-25% of their clinical practice time, and a total of 364/438 respondents used technology during 50% or less of their clinical practice time. There was not a significant difference in percentage of time used between age groups (X21=1.024;
SLPs who reported using technology were asked how often they used it for assessment and intervention specifically. For assessment, 265/309 (86.0%) used it 0-25% of the time, with no difference by age group again (X21=1.676;
Pediatric SLPs were also asked about what purposes they felt technology was most useful for in a select all that apply type of question. Intervention was most frequently cited (39.0%; 362/929 responses), followed by parent education (17.7%; 164/929), looking up clinical information (ie, developmental norms, treatment techniques) (17.3%;161/929), assessment (11.6%; 108/929), and client education (11.3%; 105/929). Of those who selected other (3.1%; 29/929), a keyword analysis revealed most pediatric SLPs found technology useful for motivation (6/929), augmentative and alternative communication (5/929), and home practice (3/929). Pediatric SLPs were also asked what they are currently using technology for in a select all that apply type of question. Results from a total of 1105 selections were like their ratings for usefulness, and are listed in order of prevalence: intervention (36.1%; 399/1105), clinical information (21.8%; 241/1105), parent education (13.7%; 151/1105), assessment (12.0%; 132/1105), client education (9.8%; 108/1105), and other (5.0%; 55/1105). It is interesting to note that SLPs are currently using apps for what they feel they are most useful for (see
Barriers to technology use was addressed by two questions. The first was a check all that apply type of question, with cost (34.0%; 46/135 responses) and lack of an evidence base (26.7%; 36/135) most frequently reported. Technology not being relevant to their population (13.3%; 18/135) or clinical area (9.6%; 13/135), and not being broad enough to use with a variety of clients (3.7%; 5/135) were not major barriers. Interestingly, 17 pediatric SLPs reported no barriers to using technology (see
Speech-language pathologists’ ratings of the most useful (dark gray), most used (medium gray) and areas where more technology is desired (light gray) across intervention, parent education, clinical information, assessment, client education and other.
An open-ended question about barriers was also presented to discover additional obstacles. Based on a keyword/theme analysis of text responses, 34/131 responses included concerns about not wanting to add to the screen time kids are already getting. Additionally, 11 responses reported anecdotal evidence of children having a tough time transitioning away from screens and 17 responses conveyed feelings that speech and language therapy should be focused on face to face interactions. Other frequently cited concerns included: recommendations for no screen time in early intervention (14/131), not having access to technology (13/131), cost (10/131), focusing on play (10/131), and lack of awareness about which apps to use (6/131).
The last section of the survey examined gaps in the availability of technology and future directions. Most pediatric SLPs, 268/380 respondents (70.5%), indicated they wished that there was more technology available “all or some of the time”. This was not affected by age (X21=0.974;
In a select all that apply type of question with 925 total responses, pediatric SLPs desired additional or better technology for: assessment (214/925), parent education (205/925), data recording or viewing (194/925), intervention (180/925), clinical information (120/925), and other (12/925). Pediatric SLPs were also given the opportunity to expand through an open-ended question. Key words and themes extracted from text analysis indicated a strong interest in apps for data collection (11/925), less expensive apps (7/925), evidence-based apps (7/925), language apps (6/925), and customizable apps (4/925). Finally, in a select all that apply type of question, pediatric SLPs indicated they would be more likely to use apps if they were: evidence-based (51/202 responses; 25.3%), cheaper (28/202; 13.9%), targeted a specific skill (27/202; 13.4%), or were endorsed by ASHA (25/202; 12.4%). Less than 10% were interested in apps that were: customizable, broadly applicable, visually enhanced, easier to use, or games that kids were interested in.
The purpose of this study was to elucidate the practice patterns of pediatric SLPs in the United States, using mobile technology, to frame the development of future technology for this field. Specifically, we were interested in barriers and desires for future technology. We found that pediatric SLPs were using technology in practice less than half of the time and most frequently for intervention. Pediatric SLPs wanted more evidence for technology use, as they had concerns about screen time and how this may impact development, and they felt that children needed more face to face interactions. They were also concerned about cost. Pediatric SLPs were interested in more technology that focuses on aiding the clinician rather than the child, such as apps for data collection, assessment protocols, and parent education. There was no difference in technology use or desire for future technology based on age group, which is somewhat surprising as research shows younger people are more likely to use mobile technology in general [
The recurrent theme across responses was a concern about screen time and the lack of an evidence base for using technology with children. Pediatric SLPs responding to the survey cited concerns about kids getting too much screen time or pointed to the fact that some populations they work with have difficulty transitioning from tablets back to nontablet-based activities, which can hinder the therapy session. Often pediatric SLPs cited the American Academy of Pediatrics’ (AAP) recommendations that screen time should be limited for infants and toddlers, as well as feelings that speech-language pathology treatment should focus on play and face-to-face interactions. While the AAP recommends no screen time for children less than 18 months and limited screen time (1 hour/day), with a focus on educational programming and coviewing for children 18 months to 5 years, the National Association for the Education of Young Children supports the developmentally appropriate and intentional use of technology in early childhood education [
Overall, data shows that how teachers and parents integrate technology with children [
There are a few simple steps that should be taken to increase technology use with SLPs working in a pediatric setting. One is creating and disseminating speech-language therapy specific evidence to support or refute the appropriateness of using technology in speech language pathology assessment and intervention. This will require research into a variety of types of apps and populations, which could take a great deal of time, with limited generalizability for those in the clinical field. This is a broad area that needs to be addressed for a variety of applications, populations, age groups, and settings. Treatment applications that are specifically for use by parents as home carryover and have similarly established efficacy need to be developed.
Applications that offer easy to follow instructions and targets or prompts that the SLP can modify for the family to fit the child’s needs would be beneficial. Another barrier to address is cost; reducing the cost or offering free trials of apps could encourage pediatric SLPs to try apps with their clients, as the majority of pediatric SLPs reported that they are not provided a budget for materials from their place of employment.
Finally, there is an opportunity for development of apps that are adult-facing rather than child-facing, such as apps for data collection, assessment, and parent education. Pediatric SLPs are in a critical position to use technology to enhance a child’s learning and generalization and to educate parents about how to best choose and use apps for their children, as it is evident children are using technology at home regardless of evidence base [
There are some limitations to this survey that should be acknowledged. The survey was distributed through email lists and Facebook groups, so participants were already engaged with technology. We were not able to reach pediatric SLPs from all 50 states, and although 45 states were represented, the number of respondents for each state were not proportional to the population. Our participant demographics closely matched those reported by ASHA in terms of gender, ethnicity, and work site, but one notable difference was our participants were younger than most ASHA members [
A majority of pediatric SLPs reported using mobile apps less than 50% of the time in a pediatric setting and used them more during intervention compared to assessment. More research is needed to elucidate the effectiveness of mobile apps for speech and language therapy, to reduce costs, and to develop apps for data collection and parent education to address the barriers to technology adoption in this population.
Social media announcement and email script for study recruitment.
Participant demographics.
Technology use by age group.
American Academy of Pediatrics
American-Speech-Language-Hearing Association
mobile Health
speech-language pathologist
We would like to thank the pediatric SLPs who participated in this survey.
None declared.