Study On The Core Symptoms Trajectories In Children With Acute Lymphoblastic Leukemia During Chemotherapy Based On Dynamic Symptom Model

Objective:Based on the dynamic symptom model,this study aims to develop and apply a smartphone-based ecological momentary assessment(EMA)symptom assessment platform to longitudinally track the core symptoms trajectories of children with acute lymphoblastic leukemia(ALL)during chemotherapy in real time from their perspective and to analyze influencing factors of different types of trajectories,which is conducted to gain insight into the dynamic characteristics of core symptoms of children with ALL during chemotherapy,and to provide a reference basis for formulating precise and personalized symptom management strategies in the future.Methods:This study consists of three parts:1.Construction,usability,and user experience of a smartphone-based EMA symptom assessment platform(1)Construction of the "EMA symptom assessment" WeChat appletThe research team used the literature review and brainstorming method to develop the platform construction scheme.Two rounds of expert working group meetings were used to revise and improve the platform construction framework and functional modules,finally determined the platform construction scheme.(2)Usability and user experience of the "EMA symptom assessment"WeChat appletA mixed research design was used to evaluate usability and user experience in children with ALL chemotherapy based on practical application scenarios.Quantitative usability and user experience evaluation was performed by the system usability scale and user experience questionnaire.At the end of the 2-week test,qualitative usability and user experience evaluation was conducted through semistructured interview.2.Longitudinal study of core symptoms trajectories in children with ALL during chemotherapyWith convenience sampling,newly diagnosed children with ALL who planned to receive chemotherapy using the CCCG-ALL-2020 scheme in the Department of Hematology,a university affiliated with Children’s Hospital from November 2021 to February 2023 were selected.The " EMA symptom assessment" WeChat applet was used for real-time repeated measures of core symptoms in children with ALL,who were asked to report their prior night’s sleep quality in the morning time window,and their severity of fatigue,pain,and depression in the morning and afternoon time Windows for a total of 49 days(including 35 days of induction remission and 14 days of consolidation chemotherapy).The piecewise growth mixture model(PGMM)approach was used to identify the latent classes of the core symptom trajectories.3.Analysis of influencing factors of latent classes of core symptoms trajectories in children with ALL during chemotherapyThe demographic and disease-related information of children with ALL were investigated at baseline.Univariate analysis and binomial Logistic regression analysis were used to explore the influence of the different latent classes of core symptoms trajectories in children with ALL.Results:1.Construction,usability,and user experience of a smartphone-based EMA symptom assessment platform(1)Construction of the "EMA symptom assessment" WeChat appletThe "EMA symptom assessment" WeChat applet takes symptom assessment as the main module,which combines two sampling schemes of EMA’s event-based and time-based.This platform includes a user side and a backend administration side,where the user side includes click login,personal information,symptom assessment,assessment feedback,reminder service,and my score module,and the backend administration side has the functions of user management,user EMA assessment data management and data export.(2)Evaluation of usability and user experience of "EMA Symptom Assessment" WeChat appletIn this study,a total of 34 children with ALL chemotherapy were investigated,and the mean EMA assessment completion rate was 82.8%.The system usability scale of the "EMA symptom assessment" WeChat applet scored 82.65±16.85.The results of the WeChat applet user experience questionnaire in each dimension:attractiveness,clarity,and efficiency were in the "good" category,with scores of 1.61(CI=1.2951.921),1.83(CI=1.528-2.134),and 1.62(CI=1.312-1.923)respectively;novelty,stimulation,and reliability were in the "above average" category with scores of 0.90(CI=0.534-1.274),1.07(CI=0.699-1.433),and 1.43(CI=1.107-1.746),respectively.Three themes emerged from the semi-structured interviews including an overall evaluation of the "EMA Symptom Assessment" WeChat applet,barriers to the use of the "EMA Symptom Assessment" WeChat applet,and suggestions for improvement of the "EMA Symptom Assessment" WeChat applet.2.Longitudinal study of core symptoms trajectories in children with ALL during chemotherapyIn this study,a total of 83 newly diagnosed children with ALL were investigated,and the mean EMA assessment completion rate was 80.6%.(1)Latent classes of fatigue trajectories in children with ALL during chemotherapyBy PGMM analysis,the fatigue trajectories of children with ALL during the induction remission and the consolidation chemotherapy phase were divided into two latent classes:fatigue remission class(72.2%),and persistent fatigue class(28.2%).(2)Latent classes of pain trajectories in children with ALL during chemotherapyBy PGMM analysis,the pain trajectories of children with ALL during the induction remission and the consolidation chemotherapy phase were divided into two latent classes:moderate pain class(23.5%),and mild pain class(76.5%).(3)Latent classes of depression trajectories in children with ALL during chemotherapyBy PGMM analysis,the depression trajectories of children with ALL during the induction remission and the consolidation chemotherapy phase were divided into two latent classes:depression remission class(75.2%),and persistent depression class(24.8%).(4)Latent classes of sleep disturbance trajectories in children with ALL during chemotherapyBy PGMM analysis,the sleep disturbance trajectories of children with ALL during the induction remission and the consolidation chemotherapy phase were divided into two latent classes:mild sleep disturbance class(63.9%),and moderate to severe sleep disturbance class(34.1%).3.Analysis of influencing factors of latent classes of core symptoms trajectories in children with ALL during chemotherapy(1)Influencing factors of latent classes of fatigue trajectories in children with ALL during chemotherapyUnivariate analysis showed that the difference in monthly per capita household income in the latent classes of fatigue trajectories was statistically significant(p=0.015).Binomial Logistic regression analysis showed that the monthly per capita household income of less than 1000 RMB was the only factor influencing the development of children with ALL into the persistent fatigue class(OR=13.800,p=0.006).(2)Influencing factors of latent classes of pain trajectories in children with ALL during chemotherapyUnivariate analysis showed no significant differences in demographic and disease-related factors among different latent classes of pain trajectories(p>0.05).(3)Influencing factors of latent classes of depression trajectories in children with ALL during chemotherapyUnivariate analysis showed that the difference in age and education level in the latent classes of depression trajectories were statistically significant(p=0.018,p=0.020).Binomial Logistic regression analysis showed that compared to the persistent depression class,being 8～9 years old(OR=0.295,p=0.022)and in primary school(OR=0.255,p=0.026)were influential factors in the development of the depression remission class in children with ALL.(4)Influencing factors of latent classes of sleep disturbance trajectories in children with ALL during chemotherapyUnivariate analysis showed no significant differences in demographic and disease-related factors among different latent classes of sleep disturbance trajectories(p>0.05).[Conclusion]1.The construction process of the smartphone-based EMA symptom assessment platform is scientific and reasonable.Through its initial application in practical scenarios,it was found that the completion rate of EMA assessment of children with ALL was high,and it has good usability and user experience evaluation,which achieved real-time monitoring of symptoms of children with ALL to a certain extent.2.The heterogeneous and stage-specific trajectories of core symptoms in children with ALL during chemotherapy,with two different latent trajectory classes for fatigue,pain,depression,and sleep disturbance,which are associated with different demographic and disease-related factors,provide a reference basis and empirical support for the future prediction and management of children with ALL with high symptom burden.