This scoping review was conducted between April and September 2024. The review followed the Joanna Briggs Institute (JBI) methodology for scoping reviews [21,22] and was reported in accordance with PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews; Multimedia Appendix 1) guidelines [23]. The 6-stage framework proposed by Arksey and O’Malley [24] was applied. The protocol was registered with the Center for Open Science [25], and the review was conducted without deviations from the registered protocol.

Individual studies published between 2000 and March 2024 were included. The starting year of 2000 was selected to capture research conducted during the period when digital technologies began to be systematically introduced into health care and rehabilitation, marking the global transition toward digital health strategies and culminating in the WHO’s Global Strategy on Digital Health 2020-2025 [27]. The selection of records for this review was guided by predefined inclusion and exclusion criteria to ensure a comprehensive and relevant assessment of digital technologies for monitoring PA in patients with pediatric cancer. Inclusion and exclusion criteria were defined according to the Population, Concept, and Context framework (Textbox 1).

A comprehensive search was conducted in ProQuest, Web of Science, EBSCO Complete, Google Scholar, ScienceDirect, Scopus, MEDLINE (PubMed), and Cochrane on April 18-19, 2024. The search strategy (Multimedia Appendix 2) combined keywords and controlled vocabulary (eg, MeSH [Medical Subject Headings] terms) related to pediatric cancer, digital technologies, PA, and outcome measurement, using Boolean operators. The final search strategy was adapted for each database. Only articles published in English were included, and gray literature was excluded. Following the database searches, all records were imported into the Rayyan AI-assisted review tool, after which the study selection process was conducted in 3 phases. First, titles and abstracts were screened, followed by full-text review to identify articles relevant to the research questions of this scoping review. In the final phase, a data extraction template was created within the Rayyan AI-assisted review tool to facilitate the systematic collection of key information from the selected articles. Given the anticipated volume of articles, all 11 coauthors participated in the selection process at each stage, with each article independently reviewed by 2 team members (AK and DB). If the Rayyan AI-assisted review tool identified a conflict regarding inclusion or exclusion, a third reviewer (GS) resolved it. Data extraction was performed independently and cross-checked to enhance accuracy. In addition, the team met regularly online to address any issues arising during the article selection phases.

Extracted data from the reviewed articles were categorized and analyzed using a structured set of variables. Key elements of the analysis included the paper ID, first author (name and surname), journal name, and article title, providing a bibliographic foundation for the review. To contextualize the research geographically and demographically, the country of the study, study aim, and participant information (number, sex, age, diagnosis, comorbidities, treatment status, and setting) were documented. In addition, details regarding participants’ diagnosis and treatment were recorded to further clarify the clinical context. The methodology of each study was assessed, including study type (eg, cross-sectional, longitudinal), applied methods (PA monitoring instruments, questionnaires, proxy reports, digital technologies), specific tools used for monitoring, and study outcomes (objectives, data type, inclusion or empowerment, intervention effectiveness, and potential effects of monitoring methods on activity levels). In this review, the treatment period was defined as the active treatment phase, extending up to 2 years posttreatment.

Following the final stages of the 6-stage framework for scoping reviews proposed by Arksey and O’Malley [24], data synthesis was conducted after identifying, selecting, and charting the relevant studies. Extracted information was first organized in a structured Excel (Microsoft Corporation) matrix, enabling systematic comparison across studies. The synthesis process involved 2 main phases:

This structure enabled the systematic identification of recurring patterns, differences, and knowledge gaps across studies. Results were synthesized narratively and organized in tables to highlight key themes, relationships, and interconnections among the examined variables.

Our search identified a total of 7876 records across 8 electronic databases. Of these, 2069 duplicates were removed, leaving 5807 records eligible for screening, which indicates the feasibility of our search strategy. Following the initial screening based on eligibility criteria, 5772 records were excluded, and 35 were sought for retrieval. Of these 35 records, 23 were excluded because they did not include a measure of PA, the research was conducted more than 2 years after treatment, the sample included adults, or the records were research protocols, reviews, theses, or conference papers. A total of 12 publications met all eligibility criteria and were included in this scoping review. The source and selection of evidence are presented in the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram (Figure 1).

The characteristics of the 12 selected studies included in this review are summarized in Table 1. The studies encompassed various research designs, including 4 (33%) randomized controlled trials [28-31], 1 (8%) quasi-randomized trial [32], 4 (33%) cross-sectional studies [33-36], 1 (8%) multicenter cohort study [37], 1 (8%) pilot study [15], and 1 (8%) prospective observational study [38]. The included studies investigated PA levels, motor performance, and quality of life among children and adolescents diagnosed with cancer, both during and after treatment. Studies were conducted in Germany [16,27,33,37], the Netherlands [15,29,30,33], the United States [37,38], Hong Kong [36], and South Korea [32]. The interventions employed objective PA monitoring tools, such as accelerometers (Actical, Move 3, Step Watch 3, Garmin vívofit 3) and subjective self-report measures, including the Activities Scale for Kids (ASK), Pediatric Quality of Life Inventory (PedsQL)-Multidimensional Fatigue Scale, and other health-related quality-of-life instruments. Across the 12 studies, a total of 1083 participants (ages 3-20 years) were assessed, with sample sizes ranging from 25 to 482. Most participants had leukemia (acute lymphoblastic leukemia or acute myeloid leukemia) or lymphoma (non-Hodgkin lymphoma or Hodgkin), while others had solid tumors (eg, bone tumors, brain tumors, neuro-oncology cases). Some studies included mixed cancer diagnoses without specific classification. Two studies examined participants posttreatment [32,35], whereas the remaining 10 focused on patients undergoing active treatment or within the first year after completion. For example, Kang et al [32] investigated a mobile game–based healthy lifestyle program for childhood cancer survivors in South Korea, while Stössel et al [35] compared PA behaviors before, during, and after cancer treatment in Germany.

Both objective and self-reported methods were used to assess PA levels, motor performance, and fatigue in children and adolescents with cancer. Across the included studies, these 2 approaches complemented each other, providing quantitative and subjective perspectives on PA behavior and its relationship to treatment-related fatigue and recovery. Objective PA monitoring was employed in 5 studies [28,30,33,34,38], using accelerometers such as Actical, Move 3, Step Watch 3, and Garmin vívofit 3. van Dijk-Lokkart et al [30] used Actical accelerometers with a required wear time of at least 500 minutes/day to measure PA levels in children undergoing or recently completing cancer treatment. Similarly, Gaser et al [28] utilized the Move 3 accelerometer alongside motor performance tests to examine PA in patients with leukemia and lymphoma. Withycombe et al [38] used the Garmin vívofit 3 over a 4-day period to track step counts and correlate them with symptom reports. This illustrates that objective PA monitoring focused primarily on step counts and time spent in different intensity zones (light, moderate, and vigorous), reflecting a general shift toward using wearable accelerometers as a feasible and noninvasive method for tracking daily movement patterns during and after cancer treatment. In addition, subjective self-reported PA assessment methods were applied in 7 studies [28,30,33-37]. For example, the ASK, which includes 30 items across 7 subdomains (personal care, dressing, other skills, locomotion, play, standing up, and movement), and the PedsQL-Multidimensional Fatigue Scale were used. Gaser et al [28] combined ASK with motor performance testing to evaluate functional abilities such as mobility and locomotion, balance and coordination, strength and endurance, as well as fatigue and energy levels. Mack et al [37] employed caregiver-reported measures to assess mobility, pain interference, and fatigue, incorporating surveys that evaluated children’s ability to perform daily tasks, their experience of pain, and levels of physical exhaustion. Götte et al [34] assessed fatigue using the PedsQL-Multidimensional Fatigue Scale, which captures general, sleep-related, and cognitive fatigue. Additional self-report instruments, such as the Child Health Utility 9D used by Stössel et al [35], were applied to assess health-related quality of life, while structured questionnaires like the Pediatric Outcomes Data Collection Instrument, used by Braam et al [33], provided insights into mobility and participation in PAs. These self-reported instruments captured complementary domains—mobility, participation, fatigue, and quality of life—allowing researchers to contextualize accelerometer-derived data with patient-perceived outcomes and daily functional capacity. The integration of objective and self-reported measures provided a comprehensive understanding of patients’ functional status across different stages of cancer care. For comparison, while some studies focused on the active treatment phase, others, such as Kang et al [32] and Stössel et al [35], specifically examined PA behaviors in posttreatment survivors. Kang et al [32] investigated the effects of a mobile game–based healthy lifestyle program on PA levels, sedentary behavior, and overall quality of life in childhood cancer survivors in South Korea. Stössel et al [35] analyzed PA behaviors before, during, and after cancer treatment, focusing on changes in daily activity levels, mobility patterns, and engagement in sports or recreational activities. Both studies provided valuable insights into long-term functional outcomes, highlighting the impact of cancer treatment on sustained PA and overall well-being in survivors. This comparison between active treatment and posttreatment groups revealed common patterns: patients typically exhibited reduced PA levels during therapy, with gradual improvement during recovery, although many survivors continued to experience limitations in endurance and persistent fatigue. In the included studies, PA monitoring primarily focused on assessing overall activity levels using accelerometers to calculate step counts and estimate time spent in light, moderate, and vigorous activity. None of the studies conducted detailed activity recognition beyond basic actions such as walking, running, or sitting, nor did they employ multisensor systems for body motion analysis or fatigue detection. More sophisticated approaches—such as recognizing complex daily activities, detecting nuanced movement patterns, or assessing early signs of fatigue—were absent, highlighting an important gap for future research.

Overall, the studies included in this review demonstrated that PA monitoring instruments were feasible for use with patients with pediatric cancer. Feasibility was largely determined by patient adherence and device usability, both of which were reported as satisfactory in most studies. Withycombe et al [38] utilized the Garmin vívofit 3, worn on the wrist for 4 consecutive days, to measure step counts and activity patterns, observing that wearable technology effectively tracked PA, although results varied according to treatment stage and location (eg, fewer steps during hospitalization). van Dijk-Lokkart et al [30] reported good compliance with accelerometer-based PA monitoring using Actical accelerometers worn on the hip for at least 500 minutes/day over a 1-week period. Gaser et al [28] employed the Move 3 accelerometer, also positioned on the hip, with a minimum required wear time of 5 days. Some studies imposed restrictions on PA measurement, such as excluding nonambulatory patients or requiring a minimum number of valid wear days for data inclusion [34,37]. While feasibility and compliance rates were generally acceptable, the studies also highlighted important contextual and individual barriers affecting the accuracy and consistency of PA monitoring in this population. Mack et al [37] found that fatigue, treatment side effects, and hospitalization influenced step counts and overall compliance. Braam et al [29] identified psychological factors, including lack of motivation and fear of overexertion, as key barriers to PA engagement. Lam et al [36] cited time constraints and limited access to PA resources as additional challenges for participants. Despite these barriers, authors suggested that self-monitoring through wearable devices served as a motivational tool, encouraging participants to maintain PA levels. These findings suggest that while device-based PA monitoring is technically and behaviorally feasible, its effectiveness depends on addressing both physical and psychosocial barriers that influence patient participation during cancer treatment and recovery.

PA interventions varied across the 12 selected studies, incorporating individualized exercise programs, supervised training, and digital health tools to enhance and monitor PA levels. Intervention durations ranged from 4 weeks to 12 months, depending on study design and patient condition. Most studies reported retention rates above 80% and adherence rates ranging from 70% to 95%, indicating strong engagement with the interventions [28-30,32]. For example, Braam et al [29] reported a 92% adherence rate to supervised PA sessions, which included aerobic training, resistance exercises, and motor performance activities 2-3 times/week at moderate-to-high intensity. Similarly, Kang et al [32] reported a 90% program completion rate and high user engagement metrics (eg, daily log-ins and activity tracking) with a mobile game–based lifestyle program for childhood cancer survivors, encouraging daily movement. van Dijk-Lokkart et al [30] implemented individually tailored programs with varying intensity and duration based on the child’s physical condition, reporting over 85% adherence in most participants. Gaser et al [28] also employed individualized exercise protocols for patients with leukemia and lymphoma, focusing on moderate-intensity exercises, and reported a 100% retention rate and 88% session completion. Across these interventions, personalization of exercise type, frequency, and duration emerged as a key determinant of both adherence and safety, reinforcing the importance of individualized approaches in pediatric oncology rehabilitation.

Table 2 (also see Multimedia Appendix 3) summarizes the PA monitoring methods, variables, applicability, and interventions across the studies in pediatric oncology, providing detailed information on the tools and strategies used to assess and promote PA in this population. A summary addressing each research question, accompanied by easily interpretable tables, is presented in Multimedia Appendix 4, offering an overview of how the selected studies address the research questions.

In addition to traditional exercise and supervised rehabilitation programs, several studies integrated digital components to enhance monitoring capabilities and sustain motivation beyond clinical settings. Digital health interventions, such as Kang et al’s [32] mobile game–based program, wearable step-count monitoring [15,38], and other digital tracking tools, were used across multiple studies to assess PA levels and support motivation in patients with pediatric cancer. These programs were implemented in diverse settings, including hospitals [29,38], physical therapy centers [29,30], and home-based contexts [15,32], with supervision provided by physiotherapists, pediatric oncology specialists, or through digital applications. The inclusion of gamified and interactive elements was particularly effective in maintaining engagement among children and adolescents, consistent with evidence that motivation and enjoyment play critical roles in sustaining PA behavior during and after cancer treatment. Despite challenges such as fatigue and other treatment-related side effects, studies consistently reported that structured PA programs—including those incorporating digital elements—were associated with improved adherence and participation [30,32,38]. These digital and traditional interventions targeted a range of physical and psychosocial outcomes, with variations in duration and intensity influencing their overall effectiveness. PA intervention durations varied across studies examining effects on physical functioning [29,30,38], fitness [29,31], fatigue [30,37], quality of life [32,36], and psychological well-being [29,37]. For example, Kang et al [32] evaluated a mobile game–based intervention, which increased daily activity, improved health behaviors, and enhanced self-reported well-being. van Dijk-Lokkart et al [30] implemented a structured PA program that reduced fatigue and improved functional capacity over time. Rehorst-Kleinlugtenbelt et al [15] examined a structured physical exercise intervention delivered in both hospital and home settings, which led to increased PA levels and better adherence to exercise programs over time. By contrast, Braam et al [29] examined a structured exercise intervention delivered in a hospital and at a local physical therapy practice, which showed no significant beneficial effects on physical outcomes.

This scoping review identified various PA assessment instruments, including digital solutions, used to monitor PA in patients with pediatric cancer. Self-reported questionnaires remain the most frequently used instruments due to their accessibility and cost-effectiveness [28-30,32-39]. While these instruments provide valuable insights from the patient’s perspective, their reliability is limited by recall bias and motivational factors, making them inherently subjective. Although widely utilized, self-reported questionnaires have been increasingly complemented by accelerometry, which provides empirical, quantifiable measurements of PA [38,39]. Self-reported surveys are often favored because they are inexpensive, easy to administer, and adaptable to different age groups, making them feasible even in larger study settings. Self-reported questionnaires also provide important patient-centered insights by capturing subjective experiences such as fatigue, pain interference, and broader quality-of-life outcomes (eg, Götte et al [34], Mack et al [37], Stössel et al [35], Braam et al [33]). However, their accuracy is limited by recall bias, motivational influences, and social desirability, which may distort reported activity levels. While self-reported surveys offer valuable perspectives on how children and adolescents perceive their PA and related symptoms, they are less reliable for accurately quantifying activity levels. This underscores the importance of complementing self-reported surveys with objective monitoring tools to achieve a more comprehensive assessment of PA in pediatric cancer. Self-reported questionnaires remain widely used due to their low cost, ease of administration, and ability to capture subjective patient experiences that objective measures may not assess. These instruments are also feasible for large-scale studies and adaptable to different age groups. However, subjective methods are prone to bias, social desirability, and motivational influences, which can affect the accuracy of data outcomes. In summary, self-reported questionnaires demonstrate lower reliability in quantifying PA levels compared with objective instruments such as accelerometers.

Accelerometer-based approaches provided objective data such as step counts, wear-time compliance, and time spent at different activity intensity levels (eg, Actical in van Dijk-Lokkart et al [30], Garmin vívofit 3 in Withycombe et al [38], Move 3 in Gaser et al [28]). In some studies, accelerometry was combined with motor performance testing to assess balance, coordination, strength, and endurance [28]. Other studies extended the focus to participation in recreational or social activities, linking activity patterns to broader dimensions of daily life [33,34]. Overall, accelerometers appear to be practical and feasible tools for objectively monitoring PA in patients with pediatric cancer. Accelerometers provide reliable, quantifiable data and are generally well-tolerated by participants; however, their usefulness is limited by the need for compliance, inability to capture complex or context-specific activities, and the lack of standardized protocols across studies. When used alongside complementary instruments, accelerometers can be a valuable component of PA monitoring in both research and clinical practice. Despite growing interest in interventions using digital tools, this review found that only 1 study employed a mobile game–based approach for PA tracking in patients with pediatric cancer [32], which also functioned as a mobile engagement tool. In this study, children participated in a serious game requiring completion of 26 quests, including 7 subelements (nutrition, exercise, hygiene, interpersonal relationships, stress management, meaning of life, and health responsibility), to promote a healthy lifestyle [32]. This review demonstrated the potential of digital solutions to integrate PA monitoring with the promotion of healthy lifestyle habits during cancer treatment in clinical settings. The selected studies also highlighted the limited research outcomes available to date. While digital tools may be feasible and applicable, their broader implementation in pediatric oncology remains largely unexplored.

The integration of PA monitoring with patient engagement strategies for behavior change, such as gamification and AR, holds promise for enhancing both data accuracy and patient motivation [18,32]. This highlights a research gap where interactive digital solutions could play a pivotal role in optimizing PA interventions for patients with pediatric cancer. While prior studies have extensively examined the effectiveness of digital technology in promoting PA [15,31,32,38], only a few have explored how PA monitoring itself can facilitate PA participation and adherence [30,32,38]. Although most studies relied on accelerometers and questionnaires, a gap remains regarding the use of AR and gamification specifically for PA monitoring in pediatric oncology. Studies employed a variety of methods to promote PA in children and adolescents with cancer, including self-reported questionnaires, wearable accelerometers, and digital game–based tools. Self-reported questionnaires, such as the ASK used by Gaser et al [28] and the PedsQL-Multidimensional Fatigue Scale applied by Götte et al [34], Mack et al [37], and others [33,36], captured subjective experiences of mobility, fatigue, pain, and quality of life, providing valuable patient-centered insights, though they are limited by recall bias and motivational factors. Wearable devices, including Actical accelerometers in van Dijk-Lokkart et al [30], Move 3 in Gaser et al [28], and Garmin vívofit 3 in Withycombe et al [38], offered objective, continuous measures of step counts, activity intensity, and motor performance, enhancing accuracy and enabling longitudinal monitoring, but they may fail to capture complex or context-specific activities and depend on participant compliance. Digital interventions, such as Kang et al’s [32] mobile game–based program, combined PA tracking with engagement and health education, supporting adherence and motivation; however, evidence remains limited, and these tools are largely unvalidated. Hybrid approaches integrating subjective and objective measures, as applied in several studies [32,38], show promise for providing a multidimensional understanding of PA and potentially improving adherence, though they require greater resources and supervision. Overall, these findings highlight the need to further explore innovative interventions that implement digital tools designed to be both engaging and user-friendly for patients with pediatric cancer. For instance, AR-based interactive games have been proposed as a promising approach, as they may enable real-time monitoring and provide personalized support for daily PA. Such technologies have the potential to offer health care professionals accurate information about a patient’s daily activity level and enhance motivation to remain active during different treatment stages. Further research is required to evaluate the impact of digital tools on physical and mental health outcomes in patients with pediatric cancer, while also addressing the limitations of current methods highlighted in this review.

This review underscores the need for a standardized approach to PA monitoring in patients with pediatric cancer, as current practices are heterogeneous and often lack consistency. While innovative digital solutions, such as AR and gamification, may offer promising approaches to enhance motivation and adherence to PA interventions, their applicability and effectiveness in pediatric oncology remain largely unexplored and require further investigation.

Additionally, this review highlighted the need for a standardized approach to PA monitoring in patients with pediatric cancer. The diversity of accelerometers [28-34,38] and self-report questionnaires [28-38] underscores the necessity for unified guidelines to ensure consistency in data collection and interpretation. Developing standardized guidelines for PA assessment would enhance comparability across studies and support the integration of digital monitoring solutions into clinical practice.

This review has several limitations. It included only articles published in English, which may have resulted in the exclusion of relevant research published in other languages. Additionally, the focus on children and adolescents aged 7-19 years who were undergoing treatment or within 2 years posttreatment may have limited insights into long-term PA outcomes beyond this period. Furthermore, heterogeneity in study designs, PA measurement tools, and intervention methodologies posed challenges for direct comparisons. The aim of this review was not to evaluate the validity or reliability of the selected instruments but to map the available measurement methods and digital solutions used to monitor PA in patients with pediatric cancer. The limited adoption of interactive digital solutions highlights a critical research gap, underscoring the need for further studies to evaluate their feasibility, appropriateness, and long-term impact on PA engagement in this population.

Our findings indicate that future research should focus on exploring how PA monitoring can actively facilitate PA participation in patients with pediatric cancer. While numerous studies have examined PA monitoring tools, only a few have assessed their impact on promoting PA. Further investigation is also needed into the use of AR-based interventions and gamification for PA monitoring in pediatric cancer. Among the 12 included studies, none involved an AR-based intervention, and the only digital engagement tool identified was a gamified mobile game by Kang et al [32]. AR represents an unexplored but promising area for future research in pediatric oncology rehabilitation. Interactive digital interventions have the potential to both measure and enhance PA engagement by providing real-time feedback and motivation [18]. Evaluating patient acceptance, clinical integration, and long-term adherence to such technologies will be crucial to optimizing their effectiveness. Furthermore, the absence of standardized PA monitoring protocols highlights the need for unified guidelines for digital monitoring solutions tailored to patients with pediatric cancer. Establishing consistent assessment criteria would improve comparability across studies and facilitate the integration of digital monitoring solutions into routine clinical practice.

Despite the growing need to monitor and promote PA in patients with pediatric cancer, opportunities for interactive and engaging PA monitoring remain limited. The findings of this scoping review indicate an emerging body of literature on digital health technologies, including wearable sensors such as accelerometers, mHealth apps, and gamification, which are being explored for PA assessment and engagement. Future research should further investigate the purpose, scope, and integration of digital health technologies to facilitate interactive and personalized approaches for effectively monitoring and enhancing PA in both clinical and home-based settings for patients with pediatric cancer.