Rapid technological advancements have opened new frontiers in healthcare, offering innovative avenues to support the physical, behavioral, and mental health of pediatric patients and their families. Digital health approaches, ranging from mobile apps to enhancements to the electronic health record, have the potential to transform pediatric health care by making supportive services more accessible, personalized, and engaging (Lattie et al., 2022). However, the successful implementation of digital health interventions in real-world settings remains a significant challenge (Psihogios et al., 2022, 2024). This special issue of the Journal of Pediatric Psychology (JPP) explores the current landscape of implementing digital health/mental health interventions with pediatric populations. It highlights both the promise and the complexities involved in integrating these tools into routine care or community settings to reach and engage young people. While there have been two prior JPP special issues focused on digital health (2009, 2019), these special issues were predominantly focused on pilot trials describing digital health intervention acceptability, feasibility, and early efficacy (Cushing et al., 2019; Ritterband & Palermo, 2009). As noted by Cushing et al. (2019), “there continues to be an untapped power in eHealth/mHealth approaches that is easy to articulate but often elusive to implement.” (Cushing et al., 2019). In the same year, this call was made, the Society of Pediatric Psychology Digital Health Special Interest Group was formed, providing a forum for our field to share and discuss digital health opportunities and common challenges (Psihogios et al., 2024). This special issue builds on pediatric psychology’s rich legacy in digital health research, while expanding its scope to highlight human-centered design and implementation science methods for enhancing the real-world impact of these technologies. Importantly, this special issue also represents the first collection of articles in JPP that address implementation science. Implementation science is a broad field focused on promoting the uptake, fidelity, reach, and sustainment of evidence-based practices (i.e., the “things” that clinicians, clinics, and health systems do to promote health; Bauer & Kirchner, 2020). Traditional intervention design and evaluation can span a decade or more to move from feasibility to implementation trials (Rubin, 2023). Designing for implementation can help expedite the process by considering, from the outset, how an eventual evidence-based intervention could be successfully implemented in the setting that it is intended. Implementation science contains a multitude of frameworks, including ones specifically intended for the development, optimization, implementation, and sustainment of digital tools and technology-enabled services (e.g., the Accelerated Creation-to-Sustainment Model; Mohr et al., 2017). These frameworks help to guide the design of digital tools in tandem with planning for integration in clinical and community spaces, whether in early stages (preimplementation) or late (sustainment; Aarons et al., 2011). Contributions to this special issue examine a wide array of topics, ranging from early-stage studies co-designing new digital interventions with youth to maximize future adoption, to the evaluation and testing of digital strategies aimed at improving the implementation of patient screening within electronic health records. In some cases, the digital intervention itself was the “thing” being implemented, while in other studies, digital tools were used as implementation strategies. Lane-Fall et al. (2019) developed a heuristic tool to help investigators determine where their research questions fall in the translational research continuum. They use a “subway model” to illustrate a journey to implementation research with stops along the way at efficacy and effectiveness research (Lane-Fall et al., 2019). To visualize the state of the literature on implementing digital health tools in pediatric populations, we adapted this model (see Figure 1) and described the “subway stops” represented by articles within this special issue. This model also helps us identify gaps and next steps for driving this work forward. That is, where is pediatric psychology on the “subway” line of translational digital research? How can we push promising digital strategies through the pipeline more efficiently so that we can test them in the contexts in which they are meant to be delivered? Adapted subway scheme for implementation of digital tools and interventions. Adapted model from Lane-Fall, Curran, & Beidas (2019), Creative Commons Attribution 4.0 International License, (http://creativecommons.org/licenses/by/4.0/). Most articles (n = 9) within this special issue reflect the “first subway” stop: incorporating implementation science into the design of a new digital health tool that has not yet shown efficacy. This falls within the scope of “preimplementation” (Aarons et al., 2011; Chamberlain et al., 2011). Aligned with the accelerated creation-to-sustainment framework, articles showcase how human-centered design principles can be employed with youth, caregivers, and clinicians to enhance the likelihood of later implementation success for digital tools and interventions (Mohr et al., 2017). Human-centered design is a methodology that embraces implementation challenges by iteratively designing technologies with a target population to ensure that it fits their needs, preferences, behaviors, and constraints. Similar to broader changes within Pediatric Psychology, applications of human-centered design increasingly emphasize the need to ensure that such methods involve inclusive and equitable approaches and methodologies (Stiles-Shields et al., 2022). For example, prioritizing co-design with diverse samples and those who have the most systemically imposed barriers to care throughout the digital health development process. Multiple applications of human-centered design methodologies in the current issue highlight the relevance of this methodology for preimplementation. Carrera Diaz et al. (2024) provide a methodological blueprint for applying human-centered design to create a mobile health intervention aimed at promoting transition readiness among early adolescents with various chronic conditions. Chen et al. (2024) followed four sequential phases of human-centered design methods to co-design and pilot Aid For Fertility-Related Medical Decisions—an interactive website for transgender and nonbinary youth/young adults and their parents to facilitate shared decision-making about fertility preservation interventions. Kaur et al. (2024) situated their work within the Reach stage of the Reach, Efficacy, Adoption, Implementation, and Maintenance implementation framework (Glasgow et al., 1999), harnessing human-centered design and community partnered participatory research methods to develop KeepCalm, a digital mental health app that incorporates biosensing wearables to address challenging behaviors and emotional dysregulation for children on the autism spectrum. Their preimplementation research laid groundwork for progressing through the RE-AIM framework for this digital tool. Petruccelli et al. (2024) demonstrated how iterative design methods can be applied not only to patient-facing digital interventions, but researcher-facing technologies to facilitate remote data collection. To collect observational, social communication data with pediatric populations in geographically diverse home environments, they customized a technology toolkit (including cameras, wireless 5G modem, etc) with consideration of relevant implementation outcomes including feasibility, usability, portability, and cost. The Consolidated Framework for Implementation Research (CFIR) was used to proactively understand the multilevel factors (i.e., intervention, organization, clinic, individual) that could later impact successful implementation of a digital tool (Damschroder et al., 2009, 2022). Colton et al. (2024) applied CFIR to optimize the web-based intervention, “Fertility edUcaTion to Understand ReproductivE health in Sickle cell disease”, for clinic integration. This paper illustrates the practical application of CFIR to forecast implementation barriers and facilitators at the preimplementation phase. These insights can guide the development of proactive, tailored strategies to overcome anticipated challenges during formal implementation evaluation (Waltz et al., 2019). In a similar vein, Stiles-Shields et al. (2024) applied CFIR to identify potential barriers and facilitators of implementing a digital mental health intervention into urban pediatric primary care–both in terms of a specific digital mental health tool (the TeACH System), and broader integration practices for such tools. Prior to launching into implementing a digital intervention and/or service, preliminary investigations of feasibility and/or efficacy are also important in the preimplementation stage. In an initial feasibility study of a virtual reality enhanced outpatient physical therapy program for youth with musculoskeletal pain, Jehl et al. (2024) conducted interviews with key players (youth, caregivers, clinicians) to define determinants of engagement with the intervention. Prior to launching a larger, randomized trial design, Nelson et al. (2024) conducted a proof-of-concept study with caregivers in Peru to assess the Universal Baby video innovation program to assess and ensure feasibility and acceptability. In tandem with an ongoing preliminary trial of efficacy and prior to implementation, Mirzadegan et al. (2024) used a convergent mixed-methods design (Creswell & Plano Clark, 2017) to assess perceived acceptability and appropriateness of “Making Mistakes,” a digital mental health program targeting anxiety risk in children. Participants were recruited across various phases of intervention completion to have a better understanding of preimplementation outcomes across interviews and questionnaires (e.g., The Acceptability of Intervention Measure, Intervention Appropriateness Measure; Weiner et al., 2017). Finally, in a commentary, Hamiliton and Kidwell (2024) highlight the important gap this digital intervention fills for preventing childhood anxiety difficulties, while also discussing the need to understand fit and possible interventions adaptions for diverse pediatric populations. Three articles within this special issue focused on implementing evidence-based practices/policies into regular use. Till et al. (2024) focused on optimizing the electronic health record to facilitate uptake of the American Academy of Pediatrics Bright Futures Guidelines for Health Supervision of Infants, Children, and Adolescents in three diverse primary care settings. The Bright Futures Guidelines include age-specific recommendations for well-child visits, including routing developmental and social-emotional screening (Hagan et al., 2017). Here, they describe the following implementation gap: despite general interest among pediatricians to implement these evidence-based pediatric care guidelines, electronic health records have not been optimized to facilitate adoption. In this study, enhancing electronic health record (EHR) functionality—such as adding standardized fields for documenting screening results, referrals, and follow-ups—improved data accuracy and facilitated better use of data for quality improvement. While these enhancements supported high-quality care delivery and aligned with Bright Futures Guidelines, they required considerable time and resource investment to overcome identified implementation barriers (e.g., limited capacity of site Information Technology teams). A second implementation study (Achieving Routine Screening for Emotional Health [ARISE]) focused on the implementation challenge of increasing the uptake of patient-reported outcome measures in pediatric care delivery (Zahidy et al., 2024). ARISE, developed with human-centered design methods with patients, families, and clinicians, is a digital system to capture patient-reported outcomes and feedback results to healthcare teams. It was implemented in three subspeciality clinics, resulting in nearly 80% of eligible children and their families completing patient-reported outcome measures. A third article also evaluated the implementation outcome of adoption, but in a broader context than health systems (Zhao et al., 2023). Utilizing data from thousands of adolescents (ages 13–17) who completed the California Health Interview Survey (2019–2021), Zhao et al. found that real-world adoption of any digital mental health intervention was low among adolescents (<10%), despite approximately 50% of teens reporting psychological distress. Interestingly, among teens experiencing high distress, the most highly-endorsed reason for not adopting an online mental health tool was a lack of perceived need. The National Institutes of Health defines dissemination research as “the scientific study of targeted distribution of information and intervention materials to a specific public health or clinical practice audience. The intent is to understand how best to communicate and integrate knowledge and the associated evidence-based interventions” (TIDIRC Facilitated Course, n.d.). That is, dissemination focuses on the strategic spread of knowledge through communication channels, whereas implementation science is more behaviorally oriented (e.g., changing clinical care practices). Dissemination and implementation science are complementary but conceptually distinct. Some have argued that dissemination has been understudied (Purtle et al., 2020), as evidenced by the absence of dissemination within widely used frameworks (Powell et al., 2015; Proctor et al., 2011), including no stop for “dissemination” on the original subway line schematic of translational research. In our adaption of this model for this special issue, we added a stop for dissemination which reflects one article in our special issue (Figure 1). Social media platforms, such as TikTok, are dissemination channels where young people already seek and share information about health. Lau et al. (2024) explored the current landscape of popular TikTok mental health content to inform opportunities for effective dissemination of evidence-based mental health information (e.g., aligning mental health communication efforts with the qualities of the most engaged with TikTok content). Specifically, this study analyzed the “top 100” videos on TikTok with the hashtag “teenmentalhealth.” These popular videos were created by both teens and mental health professionals, and the most prevalent type of content was personal narratives about mental health experiences (Lau et al., 2024). This article highlights how social media can offer an avenue for enhancing the availability, reach, and engagement of supportive information, such as partnering with popular content creators (“influencers”) to propagate credible social media content about mental (Motta et al., 2024) and behavioral health (Psihogios et al., 2024). The current issue highlights exciting and innovative digital health research being conducted within the field of pediatric psychology to improve the quality and accessibility of care for youth and their families. However, it also highlights the early-stage nature of where our field stands with applying implementation science to digital health. Indeed, most studies were situated in the preimplementation phase of research. While it is exciting to anticipate the continued work and eventual sustainment and dissemination of the works presented here, our field must broadly and strategically adopt implementation science to maximize impact. Whether focused on digital approaches or other intervention modalities, collaborating with implementation scientists (or seeking opportunities to advance personal expertise in these methods, frameworks, and applications) is critical for promoting systematic uptake of evidence-based pediatric psychology practices. A phase-based approach to behavioral intervention testing (e.g., ORBIT Model, which was modeled after drug development; Czajkowski et al., 2015) provides one rigorous pathway to fully seeing an intervention through the pipeline, from design to implementation. However, this pathway is inefficient, taking decades or more for patients to receive the evidence-based care they need. Further, the individuals who are included in efficacy trials may not be representative of the community that these interventions most need to serve. For example, excluding individuals with co-morbidities or who cannot access a trial delivered in the “ideal” setting by the “ideal” therapists (Schleider, 2023). As such, some leaders in implementation science have called for a more efficient pathway—skipping efficacy trials in favor of effectiveness trials when the behavioral intervention is low-risk. They argue that we may test and deliver such low-risk interventions in the setting that they are intended to better assess real-world impact and accelerate the process of delivering them to people who need them (Beidas et al., 2023). We are excited to acknowledge that some articles in this issue explored areas that extend beyond pediatric medical settings, including environments like social media and schools, as well as a broader emphasis on mental health outcomes. These articles reflect the evolving landscape of pediatric psychology, which is increasingly moving beyond traditional medical clinics. The contributions presented here showcase our capacity to adopt innovative methods to support pediatric patients and their families in diverse, real-world contexts, aided by advances in digital health technologies. In sum, as pediatric psychology embraces implementation science, we must consider how to harness these methods to accelerate (not further delay) how we move promising digital interventions through the translational “subway”. Rather than solely focusing on the “what?” (the intervention), we can move towards answering two questions in tandem: “what?” (the intervention) and “how?” (the implementation strategies). Doing so requires (1) intentional collaboration with people with lived experience and implementation scientists; (2) practicality, such as leveraging the digital platforms that young people already use; and (3) agility to respond to iterative feedback from key players: patients, caregivers, and clinicians/staff, throughout the design and implementation process. Alexandra Psihogios, Ph.D. was supported by the National Cancer Institute (K08CA241335). Colleen Stiles-Shields, Ph.D. was supported by a the National Institute of Mental Health (K08MH125069). Conflicts of interest: None declared.
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