The protocol for this study was registered on the Open Science Framework [29], and the literature search was conducted on August 31, 2026. This scoping review was conducted in accordance with the 5-stage methodological framework proposed by Arksey and O’Malley [30], with the aim of systematically mapping the research landscape of digital health interventions for cognitive management among children with cancer. We specifically included studies that used digital health interventions for cognitive management among children with cancer and examined intervention characteristics, including delivery modalities, functional components, implementation features, and reported outcomes. The reporting of this review was guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews; Checklist 1) to ensure methodological rigor and transparency [31].

We used the population-concept-context (PCC) framework instead of the population intervention comparison outcome framework because our research question does not aim to assess a specific outcome or comparison intervention. For this purpose, the PCC framework is recommended by the JBI Manual for Evidence Synthesis [32]. In this review, the population comprised children with cancer, and the concept was the use of digital health interventions for cognitive management. Digital health refers to the use of digital technologies to support health care delivery, disease management, health promotion, and health-related outcomes, including mobile health, web-based platforms, computer-assisted programs, and other digital devices. The context was pediatric oncology care and was not operationalized as a separate search category because it was inherently encompassed by the population with childhood cancer.

Included studies were required to fulfill the following criteria.

Eligible study designs were required to include quantitative research. Studies were excluded if they were published study protocols, reviews, editorials, conference proceedings, books, or non-English publications. Studies in which mobile technology was used solely for outcome data collection without providing tailored feedback or counseling based on the collected data were excluded. For interventions involving digital components accessible through apps as well as computers or other devices, studies were included only when participants’ use of digital devices was explicitly reported; otherwise, they were excluded. Studies without accessible full texts were also excluded.

A systematic search was conducted across multiple electronic databases, including PubMed, Embase (Ovid), CINAHL, PsycINFO, Web of Science, and Cochrane Library, to identify studies published between January 2010 and August 2026. The reference lists of all eligible studies were examined to identify any potentially relevant studies.

We developed and refined the search strategy iteratively, adapting it as necessary for different databases (see Multimedia Appendix 1 for the full strategy). The PCC framework and corresponding search components used in this study are presented in Table 1.

Study selection was independently conducted by 2 reviewers (TL and MT), who screened titles, abstracts, and full texts according to the predefined eligibility criteria. Disagreements were resolved through discussion, and a third reviewer (LM) was consulted when consensus could not be reached.

Data were extracted and charted using Microsoft Excel. Extracted data included publication year, study design, participant characteristics, cancer types, digital health modalities, intervention characteristics, and reported outcomes. Data related to intervention functions, cognitive management strategies, and implementation features were also extracted.

Data synthesis was conducted through an iterative process of summarization, coding, and comparison. Descriptive analysis was used to summarize the characteristics of included studies. A thematic content analysis approach was applied to synthesize the functional components and key characteristics of digital health cognitive management interventions [33]. Following established principles of qualitative content analysis [34], extracted data related to intervention functions, cognitive management strategies, and implementation features were systematically coded and categorized. Similar codes were grouped into broader categories, and key themes were generated through iterative comparison across studies.

The methodological quality of the included studies was assessed using the 2018 version of the Mixed Methods Appraisal Tool by the same 2 reviewers (TL and MT). Any disagreements during the appraisal process were resolved through discussion until consensus was achieved.

A total of 5371 records were identified through database searches. After removing duplicates and other ineligible sources, 2495 titles and abstracts were screened for eligibility, and 279 full-text articles were subsequently assessed. Ultimately, 19 publications [24,35-52] representing 14 independent study samples were included in this review (Figure 1). No additional eligible studies were identified through backward citation searching. No new studies were identified from the updated search.

Several included publications represented multiple reports from the same underlying studies. Specifically, 5 publications [24,35-38] originated from the same randomized controlled trial (RCT) involving 68 survivors of childhood cancer but reported different aspects of the intervention, including efficacy, feasibility, coaching conditions, transfer effects, and caregiver perspectives. Additionally, 2 publications [39,40] were derived from the same Nintendo Wii intervention study involving 13 participants but focused on different outcomes. These publications were retained as separate reports because they addressed distinct research questions; however, they were considered as a single independent sample when summarizing study characteristics and calculating the overall sample size. The sample size reported by Scott et al [38] was not counted separately because this study focused on caregiver perspectives rather than providing an independent patient sample. After accounting for overlapping samples, the 19 publications represented 14 independent study samples involving 566 children with cancer.

Among the 19 included publications, RCTs were the predominant study design (n=14), including one randomized crossover controlled trial. Two studies used quasi-experimental designs, while one study adopted a quantitative descriptive design, one used a pilot before-and-after design, and one applied a mixed methods design.

From a temporal perspective, the included studies were primarily published between 2010 and 2022 (Figure 2). In terms of geographical distribution, the included studies were predominantly conducted in North America and Europe. The majority originated from the United States (13/19) [24, 35-38, 42-44, 46-49, 52], followed by Sweden (2/19) [39, 40], with one study each from Canada [45], the Netherlands [50], Switzerland [41], and Estonia [51]. Overall, the evidence base is concentrated in North America and Europe, with limited representation from other world regions.

In terms of delivery modes, digital health interventions were predominantly implemented through computer-based cognitive training programs, with other approaches including internet-based physical activity, mobile apps, and electroencephalography (EEG)-based neurofeedback. Among these, computerized cognitive training systems (eg, Cogmed, provided by Pearson) represented the most commonly used intervention, accounting for a substantial proportion of the included studies (11/19) [24,35-38,41-46]. These interventions were typically delivered via computers or tablets, often combined with remote guidance or home-based training. In addition to Cogmed, other software-based interventions were also identified, including programs such as Fast ForWord (Scientific Learning Corporation) [47], Captain’s Log (BrainTrain, Inc) [48], and Lumosity (Lumos Labs, Inc) [49], which similarly rely on computers or mobile devices to deliver cognitive training content. Moreover, one study [50] used neurofeedback interventions, which use computer interfaces to provide real-time feedback on brain activity to facilitate cognitive regulation.

A subset of studies has begun to explore game-based and gamified intervention approaches, such as Nintendo Wii/Wii-Fit exergaming [39,40] and newly developed digital health gaming applications (eg, Triumf) [51]. These approaches integrate physical activity or entertainment elements into the intervention to enhance engagement and adherence among children. Additionally, one study [52] used web-based platforms or interactive websites to deliver interventions, thereby expanding the application scenarios of digital health.

Regarding implementation-related outcomes, most studies focused on cognitive-related outcomes, including working memory, attention, executive function, processing speed, and intelligence. Some studies additionally examined academic achievement [36,42,45,47] and serum brain-derived neurotrophic factor (BDNF) levels [49]. In addition, most studies evaluated the feasibility of the interventions [35,42-49,51], acceptability [35,36,42,44,48,51], and adherence [35,36,43,45], while only a limited number of studies assessed adverse events as an outcome measure [43,46]. Economic outcomes were not reported in the included studies.

The results of the quality assessment showed that most studies were of good quality. Specific details of the quality assessment can be found in Multimedia Appendix 2. Table 2 provides an overview of the key characteristics of the included studies.

Most included studies (14/19) used computer-based digital health interventions for cognitive management among children with cancer, with Cogmed being the most frequently used platform (11/19). Other delivery modalities included internet-based physical activity interventions, mobile app-based interventions, and EEG-based neurofeedback training. Regarding target cognitive domains, existing interventions predominantly focused on specific cognitive functions, with working memory and attention being the most frequently targeted domains. All digital health intervention models included cognitive training components aimed at improving cognitive function, whereas only a limited number of studies integrated additional supportive functions, such as coaching support, activity monitoring, educational materials, and screening functions. The details can be found in Table 3. Figure 3 presents the evidence gap map of cognitive management across different digital health intervention modalities among children with cancer.

This review synthesized evidence from 19 publications representing 14 independent study samples published between 2011 and 2022 and characterized the intervention modalities, functional components, implementation features, and research gaps of digital health interventions for cognitive management in populations with pediatric cancer [24,34-52]. Our findings highlight substantial heterogeneity in intervention design, participant characteristics, and outcome measures across studies examining digital health interventions for cognitive management among children with cancer. The findings indicate that most of the included studies (11/19) reported implementation-related outcomes [35,36,42-49,51], such as feasibility, acceptability, and adherence, providing preliminary evidence regarding the implementation potential of digital health interventions for cognitive management among children with cancer. However, the evidence base remains limited and requires further development.

In recent years, digital health technologies have rapidly advanced in the field of cognitive management, particularly among populations such as older adults with mild cognitive impairment, where diverse application models have been developed. Previous studies have demonstrated that digital health interventions have expanded beyond traditional computerized cognitive training to encompass a variety of approaches, including computerized cognitive training, physical activity-based interventions, serious games, and remote monitoring technologies, reflecting increasing diversity in intervention design [53,54]. In contrast, the application of digital health interventions for cognitive management among children with cancer remains at an early stage of development. The findings of this review indicate that digital health interventions in this population remain relatively limited, with most studies focusing on computer-based cognitive training and remotely delivered intervention models. Among these, programs for adaptive working memory training, such as Cogmed, were the most frequently adopted intervention approaches. This finding is consistent with previous literature, indicating that digital cognitive interventions for children with cancer have predominantly focused on single-domain computerized or application-based cognitive training approaches [28,43]. Furthermore, evidence from both the included studies and previous research suggests that outcome assessments in digital health-based cognitive interventions remain relatively narrow [28,46], primarily focusing on changes in specific cognitive domains, particularly working memory. The observed intervention benefits have mainly been limited to near-transfer effects, referring to improvements in trained tasks or closely related cognitive abilities, whereas evidence regarding far-transfer effects, such as improvements in academic performance and daily functioning, remains inconsistent [55,56]. Several factors may contribute to these limitations. First, cognitive impairment in children with cancer is multidimensional, involving multiple cognitive domains, including executive function, memory, attention, and processing speed. Therefore, interventions targeting a single cognitive domain may improve specific cognitive skills but may be insufficient to address broader cognitive and functional difficulties [17,57]. Second, children with cancer represent a heterogeneous population, with variations in developmental stage, cognitive abilities, cancer type, and treatment history. Such heterogeneity may contribute to differences in cognitive impairment patterns and intervention responses, thereby increasing the complexity of evaluating intervention effects [15]. In addition, limited far-transfer effects may be related to the mismatch between current digital health intervention targets and the broader functional needs of children with cancer. Most existing interventions primarily focus on improving specific cognitive abilities, such as working memory; however, whether cognitive improvements achieved through training can translate into benefits in broader functional domains, including academic performance, daily functioning, and social adaptation, remains influenced by multiple factors [17,58].

This review further explored the functional characteristics of digital health interventions for cognitive management among children with cancer. The findings indicated that existing interventions remain primarily focused on cognitive training, whereas the integration of additional functions, including educational support, behavioral management, psychosocial support, and family engagement, remains limited. In contrast, digital health applications in chronic disease management and mental health fields have increasingly adopted multifunctional intervention models by integrating components such as health education, symptom monitoring, behavioral interventions, emotional support, and family involvement to establish more comprehensive support systems [59,60]. Such integrated designs have demonstrated potential for enhancing user engagement and promoting long-term adherence [61,62]. The limited functional integration observed in pediatric cancer cognitive management may reflect the early developmental stage of this field. Most existing interventions have been adapted from established cognitive training platforms, and their functional scope therefore remains largely restricted to cognitive improvement. However, children with cancer often have broader supportive needs related to disease knowledge, emotional adjustment, social adaptation, and self-management [63,64]. Therefore, relying solely on isolated cognitive training may not adequately address their comprehensive needs [65,66].

Future digital health interventions for cognitive management among children with cancer should move beyond single-domain cognitive training toward integrated, multidimensional intervention strategies. From a functional design perspective, future systems should incorporate multiple cognitive domains, including attention, working memory, executive function, and processing speed, while integrating additional components such as health education, behavioral support, psychosocial interventions, and symptom management to address the multidimensional needs associated with cancer-related cognitive impairment and disease management [65,66]. Considering variations in children’s age, cognitive development, and disease status, modular and adaptive designs may be adopted to dynamically tailor intervention content and difficulty according to individual characteristics [15]. For younger children, greater emphasis may be placed on gamified designs and caregiver-assisted functions, whereas older children and adolescents may benefit from enhanced disease education, self-management support, and psychosocial functions. In addition, greater involvement of caregivers and health care professionals through training assistance, symptom feedback, professional guidance, and remote monitoring may improve intervention acceptability and long-term adherence [65,67]. Furthermore, digital health interventions should be integrated into pediatric oncology care pathways, allowing initiation during hospitalization and continued implementation in home settings. Future studies should use large-scale, multicenter RCTs with age-stratified designs and long-term follow-up to further evaluate the effects of multidomain digital health interventions on core cognitive outcomes as well as far-transfer outcomes, including academic performance, daily functioning, and quality of life, thereby facilitating clinical translation [65,68].

Among the included studies, only a few reported adverse events as safety outcomes [43,46], suggesting that safety monitoring of digital health interventions for cognitive management among children with cancer remains insufficient. Therefore, future research should incorporate safety assessment as a core outcome measure and establish standardized reporting guidelines for adverse events to improve the quality of evidence and support clinical translation. Beyond safety considerations, broader implementation-related evidence, including economic feasibility, is also essential for translating digital health interventions into routine clinical practice [68]. However, no studies included in this review evaluated the economic aspects of digital health-based cognitive management among children with cancer. Future research should incorporate health economic evaluations to assess the feasibility, sustainability, and scalability of these interventions, thereby informing policy development and clinical decision-making. Finally, most of the included studies were RCTs focusing primarily on intervention efficacy, whereas qualitative studies and process evaluations were relatively limited. This restricts a deeper understanding of adherence, user experience, and implementation barriers. Previous research has also suggested that the long-term effects of cognitive training may be influenced by adherence and contextual factors. Therefore, in addition to conducting high-quality RCTs, future studies should incorporate qualitative or mixed methods designs and strengthen evaluations of acceptability, feasibility, and implementation processes to optimize intervention design and facilitate clinical translation.

This study has several strengths. First, it specifically focused on the population with pediatric cancer and synthesized evidence from diverse study designs, providing a comprehensive overview of digital health interventions for cognitive management in children with cancer. The findings characterize intervention modalities, delivery approaches, and functional components of existing digital health interventions and provide valuable insights for future intervention development. This review also highlights current evidence gaps and emerging research priorities, including the need for optimized functional module design, improved user experience, and integration of clinically relevant outcomes and assessment tools. These findings may support researchers and clinicians in advancing the development and implementation of digital health interventions in pediatric oncology.

There are also some limitations. First, the broad scope and complexity of the search strategy may have led to the omission of relevant studies, despite adherence to the PRISMA-ScR guidelines to enhance rigor and transparency. Second, the heterogeneity of cognitive outcome measures, including the combination of subjective and objective assessments, limited data synthesis and reduced comparability across studies. Third, the heterogeneity in participant age ranges across the included studies is another limitation. Some studies included participants older than 18 years, while age-disaggregated data were not consistently available. Therefore, findings from mixed-age samples should be interpreted cautiously when applied specifically to children and adolescents. Fourth, only English-language publications were included, and most studies were conducted in North America and Europe, which may limit the generalizability of the findings to other regions. Therefore, future research should expand search strategies and database coverage, include studies published in other languages, and incorporate more diverse populations across different continents to improve the comprehensiveness and global applicability of the evidence base.

This scoping review synthesized the existing evidence on digital health interventions for cognitive management among children with cancer. The findings indicate that this field remains in an early stage of development, with current interventions primarily focusing on cognitive training delivered through computer-based programs and other digital platforms. Although these interventions show potential for supporting cognitive function, most approaches remain centered on single-domain training, with limited integration of supportive components and relatively narrow outcome assessments. Future research should prioritize the development of multidimensional, personalized, and integrated digital health interventions that incorporate cognitive training, supportive functions, and clinically relevant outcomes. High-quality multicenter RCTs, together with safety monitoring, health economic evaluations, and qualitative or mixed-methods studies, are needed to strengthen the evidence base and facilitate clinical implementation.