Design and implementation of mHealth applications for older people with cancer: A scoping review.

Introduction

GLOBOCAN 2020 reported 19.29 million new cancer cases worldwide, with 12.35 million (64%) occurring in individuals over 60. 1 With the growing aging population, the incidence of cancer in older people has shown a significant upward trend, reaching an estimated 28.4 million new cases by 2040. 2 Cancer in older adults is an increasing public health concern. Compared to younger individuals, older people are more likely to experience comorbidities and frailty, 3 which increase the risks of adverse treatment outcomes such as prolonged hospitalizations, readmissions, and reduced quality of life. 4

Given these challenges, digital health solutions such as mHealth apps have emerged to support cancer management in older adults. It provides medical information and services to people through smart mobile devices, with smartphone apps being the most popular and widespread. 5 Smartphones are portable, and mHealth apps allows users to monitor their physical conditions and help people get immediate feedback from specialized persons anytime and anywhere as well as retrieve information to improve their medical knowledge and consult medical staff to reduce unnecessary hospital visits. 6 mHealth apps not only address patients' health needs but also optimize medical resource allocation. 7 Previous quantitative studies have shown that mHealth apps play an important role in improving the quality of life and overall health outcomes of people with cancer. 8 , 9 , 10

However, research suggests that older adults may be hesitant to adopt new technologies due to privacy concerns, past negative experiences, and limited digital literacy. 11 Cognitive decline and physical limitations can also hinder engagement with new tools. 12 Moreover, few studies have examined mHealth use among older people with cancer, indicating a significant gap in understanding their unique needs and preferences. 13

Despite challenges in adopting new technology, the COVID-19 pandemic accelerated the use of mHealth solutions among older adults. 14 As the adoption of mobile health applications among older cancer survivors continues to rise, together with the increasing number of elderly cancer patients and the escalating burden of health management, the widespread implementation of mobile health interventions targeting this population is anticipated. 15 Accordingly, related research efforts have been expanding, highlighting the need for a comprehensive synthesis of existing evidence.

Several recent studies have reviewed mHealth literacy, barriers to apps’ use, and personalized measures for mHealth apps use among older people with cancer. 16 , 17 However, to the best of our knowledge, little is known about the functions, design, implementation, and evaluation of mHealth apps for older people with cancer. A comprehensive review of existing evidence is necessary to guide the development of user-friendly and effective mHealth apps tailored to older adults with cancer. Therefore, this scoping review aims to systematically synthesize the existing evidence on the functions, design features, implementation strategies, and evaluation practices of mHealth applications developed for older adults with cancer, to identify existing gaps and inform future development and research in this field.

Methods

This scoping review followed Arksey and O'Malley's methodological framework, which includes five stages: (1) defining the research question, (2) identifying relevant studies, (3) selecting relevant studies, (4) data extraction, and (5) collating and reporting results. 18 This review adhered to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews) guidelines. 19

Defining research questions

The aim of this review was to systematically explore existing studies on mHealth apps for older people with cancer, with the goal of informing future app development and implementation.

Specifically, this review addressed the following research questions.

What are the main functions of mHealth apps for older people with cancer?

What strategies are used in the design and implementation of these apps?

How are these apps evaluated, and what evaluation methods and indicators are commonly used?

Identification of relevant studies

An initial exploratory search was conducted in PubMed and the Cochrane Library Databases to identify key terms and keywords. Based on these findings, a comprehensive search strategy was developed to capture relevant literature on mHealth interventions for older people with cancer. The strategy was then adapted to suit the syntax and indexing terms of each database. The search strategy was constructed using three key concept sets: older adults, cancer, and mHealth. The full search strategy is detailed in Supplementary Table S1 . Five databases were searched: Medline (OVID), Web of Science, CINAHL (EBSCO), Embase, and the Cochrane Library. Two reviewers independently conducted the literature search, screened titles and abstracts, and assessed eligibility for inclusion.

Study selection

All retrieved references were imported into EndNote X9 for deduplication. Title and abstract screening were then conducted independently by two reviewers based on predefined inclusion and exclusion criteria. Subsequently, two reviewers independently conducted full-text screening to further assess eligibility. Any disagreements were resolved through discussion, and if consensus could not be reached, a third reviewer was consulted. The screening process was conducted manually without the use of automation tools. The inclusion criteria were: (1) articles published in English from January 1, 2008 to February 28, 2025, considering the launch of the first mobile app store in 2008; 20 (2) studies targeting individuals aged 60 years or older diagnosed with cancer; (3) research focusing on health management using mHealth applications for older adults with cancer; and (4) articles reporting qualitative, quantitative, mixed-methods, or development studies related to the functions, design and implementation strategies, or evaluation of mHealth apps. The exclusion criteria were: (1) studies lacking a detailed description of mHealth apps; (2) studies where the target population was under 60 years of age or not diagnosed with cancer; and (3) full texts unavailable for review.

Data extraction

Key data relevant to the research questions were extracted using a standardized charting form. The charting form included the author, year of publication, country, study design, sample size, target population, and mHealth app characteristics (name, target group, domain, features, functional elements, design, use, and evaluation). Two reviewers independently extracted the data, and discrepancies were resolved through discussion or consultation with a third reviewer.

Collating and reporting results

A narrative synthesis was used to summarize the findings. Frequency analysis of study characteristics and thematic analysis of app functions, design features, implementation strategies, and evaluation methods were conducted to reveal the complexity of mHealth interventions targeting older adults with cancer.

Results

Retrieval and filtering of results and study characteristics

A total of 5689 articles were initially retrieved. After removing duplicates using EndNote X9, 3721 unique records remained. Titles and abstracts were independently screened by two reviewers, resulting in the exclusion of 3468 articles. Subsequently, full-text screening of 253 potentially eligible articles was conducted based on predefined inclusion and exclusion criteria, leading to the exclusion of 186 articles. Ultimately, 30 articles met the inclusion criteria and were included in this review, covering 19 different mHealth apps. The reasons for exclusion are detailed in the PRISMA flow sheet ( Fig. 1 ).

The publication years of the included studies ranged from 2013 to 2025. Regarding geographical distribution, five applications were developed in the United States, three in Sweden, two each in the Netherlands, France, and Germany, and one each in the United Kingdom, Greece, Spain, Canada, and China. All articles were published in academic journals.

The study designs included development studies ( n = 1), qualitative studies ( n ​= ​3), quantitative studies ( n ​= ​11: observational ​= ​4, interventional ​= ​7), and mixed methods studies ( n ​= ​15). Among the mixed-methods studies, three were research protocols that described fully developed mobile health applications undergoing planned intervention testing but without reporting outcome data. These protocols were retained because they provided detailed descriptions of theoretical frameworks, design strategies, and user adoption methods applied during app development.

In terms of cancer focus, 10 mHealth apps targeted older adults with a specific type of cancer, including myeloma ( n ​= ​2), prostate cancer ( n ​= ​4), lung cancer ( n ​= ​1), ovarian cancer ( n ​= ​1), bladder cancer ( n ​= ​1), and hematologic malignancies ( n ​= ​1). Nine applications did not specify the type of cancer targeted and were intended for broader cancer populations.

Regarding the applications' specific purposes, five apps were focused on postoperative period, four were designed for individuals undergoing chemotherapy, immunotherapy, or other targeted therapies, two were for patients undergoing radiation therapy, and eight were intended for cancer survivors. Sample sizes in these studies varied from 9 to 170 participants.

Among the 19 mHealth apps, nine were developed for remote home monitoring, six for self-management, three for guiding rehabilitation exercises, and one for providing information support. A summary of these studies is presented in Table 1 .

App functions

The apps examined in the reviewed studies had the following functions: (1) monitoring and alerting, which allows users to upload vital signs, symptom information, and other data, with the algorithm intelligently generating health risk warnings; 23 , 24 , 25 , 26 , 27 , 31 , 32 , 34 , 35 , 38 , 39 , 40 (2) health education, which provides health outcome educational content, elucidates the advantages of self-monitoring for risk control and comprehension of medication along, and describes the potential side effects of self-monitoring, thereby addressing users’ informational requirements; 21 , 31 , 34 , 38 , 39 , 44 , 45 , 47 , 48 , 49 , 50 (3) intelligent reminders, which provide prompts and guidance for completing daily tasks, including physical activities, appointment arrangements, medication situations, and nutrition and fluid intake; 24 , 26 , 27 , 31 , 34 , 35 , 38 , 40 , 45 , 47 , 48 , 49 , 50 (4) consultation with medical staff, which allows structured face-to-face, telephone, and virtual communication, thereby promoting education and self-management; 27 , 31 , 34 , 37 , 38 , 39 , 46 , 47 , 50 (5) personalized interventions to motivate participation in health promotion programs, such as videos, pictures, and text on health education, including physical activity and sole training, and establish personalized goals for treatment or behavior change; 26 , 27 , 33 , 34 , 35 , 44 , 45 , 48 , 50 (6) personal information and medical records, including examination results, revisit information, and relevant advice; 31 , 34 , 36 , 39 , 45 , 47 , 48 , 49 , 50 (7) social support, including information on family or peer support and provision of emotional and psychological peer support through online forums and other platforms 27 , 33 , 36 , 44 , 49 ; and (8) additional resources, such as links to high-quality websites with abundant and beneficial medical and health information. 26 , 31 , 33 , 38 , 39 , 40 , 44 , 48 Among these applications, those targeting specific cancer types (e.g., prostate cancer, myeloma) primarily emphasized symptom monitoring and management of treatment-related side effects. In contrast, applications developed for broader cancer populations incorporated a wider range of functions, including health education, personalized interventions, and social support features.

App design

The apps examined in the reviewed studies had several designs. (1) Theoretical guidance frameworks: developed based on established theoretical models to guide their design and content development. Theories applied included: self-determination theory, 37 , 41 person-centered care models, 38 fogg behavior model, 47 health belief model, 47 and self-management theory. 49 However, the systematic integration of theoretical frameworks across all applications remained limited. (2) Human-centered interface design: (a) age-appropriate interface design ( Fig. 2 ), 24 , 26 , 27 , 31 , 32 , 34 , 47 , 48 , 49 , 50 (b) acoustic navigation considering the toxicity of cancer treatment for people was prone to polyneuropathy, 24 , 39 , 50 and (c) visualization to present vital signs, symptoms, and other data in a form conducive to understanding. 21 , 24 , 27 , 32 , 34 , 39 , 40 , 41 , 45 , 46 , 49 (3) Human-centered functional design: (a) customization, such as selecting male or female voices according to user preferences, which was found likely to arouse user interest, 24 , 26 , 27 , 32 , 34 , 37 , 47 , 50 (b) timely communication, such as feedback communication channels, ability to send and receive messages, and phone or video communication with doctors and nursing staff to report symptoms, 26 , 27 , 31 , 34 , 37 , 38 , 47 , 50 (c) privacy protection, such as encrypting or anonymizing survey data, conducting confidentiality and privacy training for researchers and implementing access, and signing confidentiality agreements, 24 , 26 , 34 , 45 , 46 , 47 , 48 , 50 and (d) encouragement, such as providing motivational messages after tasks are completed. 41 , 50 (4) Digital literacy and accessibility support: (a) using Bluetooth instead of Wi-Fi to solve the delay in data transmission; 21 and (b) other auxiliary equipment, such screen touch pens, wearable activity monitors, and speakers to assist older people and reduce their burden. 21 , 26 , 27 , 34 , 41 , 45 , 46

Strategies to promote implementation

The reviewed studies employed several strategies to promote the adoption and sustained use of mHealth applications among older adults with cancer. These strategies were categorized into five main areas: (1) Training and instruction: Studies suggested improving the abilities of older people with cancer through (a) training and demonstration before using apps, 21 , 25 , 26 , 27 , 34 , 37 , 45 , 46 , 47 , 50 and (b) use of instruction manuals, as older people are often forgetful. 21 , 26 , 27 , 37 , 38 , 45 (2) Simplification of operational processes: To reduce cognitive and technical barriers, applications were designed with simplifying the operation and helping users install apps and create usernames and passwords for long-term use. 21 , 25 , 26 , 27 , 32 , 34 , 47 , 48 , 50 (3) Professional support: (a) multidisciplinary cooperation between patients, caregivers, information design teams, and hospital remote health management teams, 26 , 27 , 34 , 40 , 50 and (b) professional technical support by telephone or email available at any time, 21 , 26 , 37 , 38 , 39 , 45 , 46 , 47 (4) Family and peer support: Some applications integrated family members or peer networks to assist users in navigating the apps and maintaining engagement to enhance motivation and reduce technological anxiety. 26 , 27 , 34 , 37 , 47 , 50 (5) Incentive mechanisms: Several studies employed strategies such as (a) home follow-ups, which can reduce drop-out rates, especially for older people with mobility difficulties, 21 , 49 , 50 (b) provision of equipment for using mHealth apps, as some older people do not possess the required technology 21 , 25 , 26 , 27 , 38 , 41 , 48 and (c) empowerment to promote autonomy and compliance. 24 , 37

Assessment of feasibility and usability

Among the 19 identified mHealth apps, 18 were evaluated, with the primary evaluation criteria focusing on their feasibility and usability for older people with cancer, 21 , 24 , 25 , 26 , 28 , 31 , 32 , 34 , 37 , 38 , 39 , 40 , 44 , 45 , 46 , 47 , 49 , 50 Among them, the feasibility of 15 apps was evaluated, 21 , 24 , 25 , 26 , 28 , 34 , 37 , 38 , 40 , 44 , 45 , 46 , 47 with evaluation methods including: app use data, 21 , 25 , 26 , 28 , 40 , 44 , 45 , 46 , 47 , 49 , 50 compliance, 21 , 25 , 26 , 40 , 44 , 46 , 50 and questionnaires or scales (four articles using self-designed feasibility questionnaires, 24 , 47 acceptability questionnaires 21 , 34 and System Usability Scale 21 ), and interviews. 26 , 28 , 34 , 37 , 38 , 44 Some studies combined multiple methods to triangulate findings. 12 apps were evaluated with the usability for older people with cancer, 21 , 26 , 28 , 31 , 32 , 37 , 39 , 44 , 45 , 46 , 47 , 49 including System Usability Scales, 21 , 26 , 28 , 39 interviews, 26 , 37 , 39 , 44 , 45 , 46 , 49 beta tests, 31 , 32 and think aloud technique. 36 , 47 Overall, most applications demonstrated good feasibility and usability among older adults with cancer. However, considerable variability existed in the evaluation methods and indicators used across studies, and no unified standard was observed. Moreover, few studies incorporated systematic, in-depth feedback from older users and caregivers beyond general satisfaction ratings, highlighting a gap in user-centered evaluation practices.

Discussion

To the best of our knowledge, this is the first comprehensive review of the functions, design, usage, and evaluation of mHealth apps for older people with cancer. This review synthesizes evidence from 30 studies that assessed 19 different mHealth apps developed for older cancer patients, reflecting, to varying degrees, their health management needs. However, the studies included in this review have several limitations. Most of the research was conducted in Western countries, while the cancer burden among older adults remains significantly high in many Asian countries. 51 Additionally, the studies varied greatly in sample size, ranging from small pilot trials to large-scale studies, which may affect the generalizability of the findings. The majority of the studies were observational or mixed-methods, with limited user feedback, providing only superficial insights into older cancer patients’ perceptions of the applications. 52 Another notable limitation is that the needs of older adults with cancer across different cancer types and treatment stages have received minimal attention, with only one study specifically focusing on the needs of older cancer patients with comorbidities. This lack of targeted focus may limit the effectiveness of these applications for patients at specific cancer stages or those with multiple health conditions. Future research should focus on developing mHealth applications that address the diverse needs of older cancer patients, considering different cancer types and treatment stages. Research should also prioritize non-Western settings, particularly in Asia, where the cancer burden is high but research remains limited. Larger studies with diverse sample sizes are needed to enhance the generalizability of findings. Additionally, more in-depth user feedback, especially from older adults with comorbidities, should be incorporated to ensure that mHealth applications are both effective and user-friendly. 53

We summarized the core features of mHealth apps for older people with cancer aimed at assisting individuals in monitoring, managing, and coping with their health conditions. However, the effectiveness of these features varies, and several issues were identified. For example, the monitoring and alerting functions may lead to unnecessary anxiety due to excessive symptom monitoring. 54 With technological advancements, these monitoring and alerting features can be enhanced through machine learning and other methods to improve the accuracy of algorithms and provide personalized settings to reduce unnecessary alerts and reminders. 55 Additionally, the customization features need refinement to consider the diverse needs of different individuals and offer targeted services. 56 Social support is crucial in the health management of older adults; 57 however, the incorporation of social support features in apps is limited. Promotion and guidance should be enhanced to improve users’ social engagement and interactions. In addition to health management functionalities, aspects such as reminder services, entertainment, and feedback mechanisms need further enhancement to improve the effectiveness and usability of the apps and to meet the diverse health management needs of older adults. 58

Design plays a crucial role in the development of mHealth apps for older people with cancer, as it can significantly enhance app efficacy and user satisfaction, thereby driving the digitization of health management. 59 However, many studies indicate a lack of consistent application of theoretical frameworks, which are essential for improving the effectiveness of these apps. While some mHealth apps utilize guiding frameworks, few fully integrate them into their design process. For example, Social Cognitive Theory, which emphasizes the interactions between individuals, their environments, and behaviors, has been applied to in certain apps to influence health behaviors. 37 Additionally, LifeChamps incorporates Self-Determination Theory and Patient and Public Involvement Theory to better support older people with cancer, improve their quality of life, and enhance their autonomy in health management. 41 These theoretical frameworks guide the development of user-friendly features tailored to the unique needs of older patients, addressing challenges such as cognitive decline and other age-related factors.

As discussed earlier, the lack of systematic application of theoretical frameworks in the design of mHealth applications for older cancer patients highlights a significant gap. In contrast, a user-centered interface and feature design for older cancer patients can significantly enhance user adherence and engagement. 60 Age-appropriate design and personalized customization contribute to an improved user experience, making the applications more accessible and effective for this population. 61 Additionally, privacy protection and other important considerations help to build trust, enhancing the credibility and sustainability of the applications. Furthermore, addressing aspects related to older adults' digital cognition and capabilities, such as using Bluetooth instead of Wi-Fi and configuring auxiliary devices, can improve the usability of the apps. 62 However, challenges persist, including overly generalized designs, risks of privacy data breaches, and the increased complexity in learning and operation due to technological advancements. 63 Therefore, future app design should be grounded in theoretical frameworks, which provide a scientific basis for systematic design, ensuring greater effectiveness and user satisfaction. 64 Additionally, multi-disciplinary methods, such as design thinking, 65 user journey, 66 and user portrait, 67 should be considered to involve target users in the development process, ultimately improving usability.

The strategies to promote the use of mHealth applications among older cancer patients emphasize training, simplified operations, professional support, family and peer support, and incentive mechanisms. Consistent with previous studies, these strategies—especially training and guidance—can significantly improve the acceptance and effectiveness of these applications. 68 , 69 , 70 One of the most important approaches remains the smartphone training courses for older adults, offered by universities and community organizations, to enhance their digital literacy. 71 However, these courses mainly improve general information literacy rather than health information literacy. 72 mHealth training programs, typically led by study sponsors, should ensure the quality and long-term impact of these courses. While several studies highlight the importance of family and peer support, they do not address how to guide supporters and overcome communication barriers. Additionally, incentive mechanisms, such as rewards and emotional support, are underrepresented. 73 Future research should focus on developing more specific and targeted incentive measures to effectively engage users and refine these strategies to improve their implementation efficiency and sustainability.

Feasibility and usability assessments of mHealth applications for older cancer patients involve various methods, including app usage data, self-designed feasibility questionnaires, acceptability surveys, usability scales, and interviews. However, using usability questionnaires to assess feasibility may not be appropriate, as they represent different concepts. Feasibility refers to the practicality and applicability of implementing a policy or program in a specific environment, while usability refers to the ease and effectiveness of using a product or system. 74 Enhancing the usability of mHealth apps is crucial to help older individuals overcome the digital divide. 75 Among the included literature, usability was evaluated using the System Usability Scales, 76 interviews, beta testing, 77 and think-aloud methods. However, the System Usability Scale fails to account for the unique needs of older adults. 78 Previous research has shown that older cancer patients have significantly lower mHealth literacy compared to younger populations, suggesting that the needs and abilities of older cancer patients should be considered when designing and implementing mHealth applications. 11 Most current usability assessments are designed for the general user population, neglecting the specific characteristics and requirements of older adults. Therefore, there is a need to develop usability assessment tools tailored to older adults. However, most current usability evaluation methods are designed for general user groups, and the characteristics and needs of older people have been overlooked. Therefore, usability evaluation tools for older adults should be developed. Additionally, it is worth noting that none of the included studies explicitly reported the use of heuristic evaluation. As a practical, expert-driven method, heuristic evaluation can proactively identify usability issues early in the app development process, significantly improving age-appropriate usability. The absence of heuristic evaluation in the current literature indicates a potential underuse or underreporting. Therefore, future research should prioritize integrating heuristic evaluation methods during app development to enhance interface design and usability tailored specifically to older adults.

Future research should prioritize the development of mHealth applications grounded in robust theoretical frameworks and adapted to the specific needs of older adults with cancer. While user-centered principles are widely adopted, many apps lack systematic integration of behavior change theories and cancer-specific considerations. Incorporating methods such as user journey mapping and persona profiling may enhance patient engagement and ensure that app features are both contextually relevant and personalized for aging users.

Implications for nursing practice and research

In addition, standardized evaluation tools tailored to older populations are needed to improve the consistency and rigor of usability and feasibility assessments. Heuristic evaluation should be introduced early in the development process to proactively identify age-related design barriers. Future studies should also expand research beyond Western contexts, especially in East Asia, to improve the cultural applicability of findings. Mixed-methods designs that combine quantitative outcomes with qualitative user experiences are recommended to capture the real-world impact and acceptability of mHealth interventions.

Limitations

This study had several limitations. First, mHealth is a rapidly evolving field, and the applicability of the reported findings may require reassessment due to the constantly changing innovation landscapes. Second, gray literature was not included; the sources for this review were limited to articles published in peer-reviewed journals. Unpublished but pertinent information relevant to the latest trends in the field may have been overlooked. Finally, apps in the app store were not included, as details regarding their development process were not available.

Conclusions

Recent research has focused on developing effective mHealth apps to maximize the health management of older people with cancer. Despite the potential benefits of mHealth apps, research on these technologies is limited. Interdisciplinary mHealth app development teams must consider specific factors when designing, implementing, and evaluating technologies to create apps appropriate for the unique context of older people with cancer and their care providers. The questions and selection criteria of this review allow the consideration of a wide range of mHealth apps applicable to older people with cancer. This study introduces some common points between different contexts. Development of suitable mHealth apps for older people with cancer should consider older people with cancer as the center, combine relevant theories, select functions based on population preferences, and consider population characteristics in app implementation. The inclusion of older people with cancer in clinical cancer trials and eHealth studies designed for this population, which has complex health care needs, offers potential for improving the health of this population. Future research should pay greater attention to developing applications specifically designed for older people with cancer based on theoretical guidance frameworks, and efforts should be made to standardize usability and feasibility evaluations, thereby improving the reliability and applicability of mHealth solutions in geriatric oncology practice.

CRediT authorship contribution statement

Qi Sun : Conceptualization, Methodology, Software, Data Curation, Writing – Original Draft, Visualization; Danyu Li : Data Curation, Writing – Review & Editing; Tingting Cai : Investigation, Writing Review & Editing; Jing Luo : Writing – Review & Editing; Qing Jia : Writing – Review & Editing; Xiaoyan Yu : Supervision, Writing – Review & Editing; Fulei Wu : Supervision, Writing – Review & Editing; Changrong Yuan : Conceptualization, Supervision, Data Curation, Writing – Review & Editing, Visualization. All authors have read and approved the final manuscript.

Ethics statement

Not required.

Data availability statement

Data availability is not applicable to this article as no new data were created or analyzed in this study.

Declaration of generative AI and AI-assisted technologies in the writing process

No AI tools/services were used during the preparation of this work.

Funding

This review was supported by the National Natural Science Foundation of China Youth Project (Grant No. 72104055) and the Ministry of Education of Humanities and Social Science Project (Grant No. 23YJC630002). The funding agencies had no role in the design of the study, or collection, analysis, and interpretation of the data.

Declaration of competing interest

The authors have no conflicts of interest that need to be disclosed. The third author, Dr. Tingting Cai, is an editorial board member of Asia–Pacific Journal of Oncology Nursing . The article was subject to the journal's standard procedures, with peer review handled independently of Dr. Cai and their research groups.

Acknowledgments

The authors thank librarian Jibin Xing for her help with the database search and for specific advice that made this work easier and more enjoyable.

Footnotes

Supplementary data to this article can be found online at https://doi.org/10.1016/j.apjon.2025.100726 .

Contributor Information

Fulei Wu, Email: wufulei@fudan.edu.cn.

Changrong Yuan, Email: yuancr@fudan.edu.cn.

Supplementary data

The following is the Supplementary data to this article.

Multimedia component 1

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Data Availability Statement

Data availability is not applicable to this article as no new data were created or analyzed in this study.