Authors: Cui Cui, Shuangzi Li, Qing Xia, Wenjing Chen, Xianlan Zheng
Categories: Research, Epilepsy, Children and adolescents, Self-management, Transition readiness, Evidence-based nursing practice
Source: BMC Nursing
Authors: Cui Cui, Shuangzi Li, Qing Xia, Wenjing Chen, Xianlan Zheng
Self-management interventions are crucial for adolescents with epilepsy (AWEs) to control seizures during their transition to adulthood. However, many AWEs face challenges in sustaining effective self-management, and evidence-based practices tailored to this population remain underexplored. This study developed and evaluated a self-management intervention plan to enhance transition readiness for AWEs.
The setting is the neurological center of a Grade-III children’s hospital in Southwest China. From March 2023 to February 2024, 92 AWEs and their families participated, along with 31 hospital staff members. A historical comparison design evaluated the intervention’s effects on AWEs, while a self-controlled design assessed impacts on healthcare providers and the system environment. The intervention was developed using the Knowledge-To-Action framework and intervention mapping theory, guided by a logical model and a matrix of change goals. Through expert consensus, 53 strategies were formed using evidence-based behavior change methods. Key outcomes included behavior and physical health of AWEs, compliance among healthcare providers, and system-level improvements.
Post-intervention, significant improvements were observed across all assessed areas, including self-management, transition readiness, and electroencephalogram results, except for number of seizures and doctor-patient communication. Compliance with self-management behaviors among AWEs and family caregivers increased by 21.43%, healthcare providers’ practice compliance improved by 34.08%, and clinical audit results at the system level rose by 58.83%. Notable system-level changes included improved resource allocation and care standardization.
This intervention is a promising approach to improving health outcomes in AWEs and fostering self-management behaviors among patients and caregivers, while enhancing healthcare providers’ practice and service capacity. The framework offers valuable guidance for integrating self-management support into transition ecosystems, with implications for both clinical practice and nursing education.
The online version contains supplementary material available at 10.1186/s12912-025-03876-2.
According to the UN Global Strategy for the Health of Women, Children and Adolescents (2016–2030), adolescents are core to the global health strategy [1]. According to a survey of 1.8 billion adolescents in 195 countries, chronic diseases account for over half of their disease burden and are the main cause of their deteriorating health status [2]. It is difficult to establish continuous and whole-cycle health services for children and adolescents with chronic diseases [3]. The American Academy of Adolescent Medicine defines transition as the purposeful and planned transfer of adolescents with chronic conditions from a child-centered to an adult-centered health care system [4]. Transition readiness (TR) is how able adolescents with chronic diseases and their support systems (family, medical and social) are to prepare, start, continue and complete healthcare transfer [5]. Transition readiness is a key predictor of self-management ability and quality of life of adolescents with chronic diseases [6]. Adequate TR improves adverse medical outcomes and treatment compliance, and reduces the number of emergency visits and the risk of morbidity and mortality [7, 8]. However, most adolescents with chronic diseases have insufficient TR [9].
Epilepsy is one of the most common chronic neurological disorders, affecting people of all ages. More than 50 million people worldwide live with epilepsy, nearly 80% of whom live in low- and middle-income countries [10]. Epilepsy has an incidence rate of approximately five to seven cases per 10,000 children, and about 50% of children with epilepsy continue both seizures and treatment into adulthood [11]. The prevalence in children is higher than in other age groups, and about 54% of children with epilepsy will have seizures until adulthood [12]. Given the complexity, stage-specific challenges, family dependence, and long-term nature of epilepsy in adolescents, enhancing self-management ability is essential to achieving successful healthcare transition [13]. Lack of self-management may lead to poor epilepsy control, affecting patients’ self-identity, self-efficacy, treatment compliance, and family relationships and function [14, 15]. Self-management behavior is key to controlling seizures, and compliance with the treatment plan is vital in reducing convulsive recurrence and comorbidities [16].
There is limited consensus on the definition of self-management in AWEs [17]. Wagner et al. defined this as the ability of this group and their families to jointly manage epilepsy, and establish a dynamic self-regulation process through core skills, aiming to improve the onset of epilepsy, patient well-being and quality of life [18]. While the concept of self-management during transition from pediatric to adult careis established [6, 19], there is a relative scarcity of research specifically integrating the characteristics of TR behavior, the nuanced needs of all stakeholders, and the translation of these elements into robust evidence-based practices for self-management support. Existing studies [20, 21] indicate that children, adolescents, and families affected by epilepsy exhibit multidirectional, social, and dynamic characteristics in their transitional readiness intentions and behaviors. A more inclusive theoretical framework is needed to address personal, familial, and social interconnections. Therefore, this study applies the Social-ecological model of adolescents and young adults readiness for transition (SMART) model to identify core elements and key links in transitional readiness practices for Chinese AWEs, offering a solid theoretical framework for developing evidence-based self-management interventions. From the perspective of the SMART model, social cognitive theory is taken as the explanatory theory of health behavior; we have conducted current state analysis studies and summarized the evidence on self-management for AWEs [22–25]. The evidence summary included 45 pieces of evidence in 10 categories from four aspects, namely intervention principles, environmental intervention, behavioral intervention, and cognitive intervention. Focusing on AWEs and their families, this study uses the knowledge-to-action (KTA) framework and intervention mapping (IM) as evidence-based practice methodology. The aim is to provide a reference for self-management practice during transition.
The KTA framework is a widely used evidence-based model in nursing practice that outlines the dynamic process of knowledge generation and application [26]. While it provides clear steps for knowledge implementation, it offers limited guidance on the actual application process. In contrast, IM - introduced by Bartholomew in 1998 [27] - emphasizes a social ecological approach to health intervention design, grounded in theory and evidence. Kok et al. [28] further developed IM into a structured tool for health promotion programs, comprising six iterative steps; the sequence is detailed in Appendix Fig. 1(1–1) [29, 30]. IM is characterized by its theoretical foundation, participatory planning, ecological perspective, integration of implementation planning, and iterative process [30]. Although IM has been applied in chronic disease management, its use in child and adolescent health remains underexplored [30, 31].
Based on the fundamental principles, procedures, and objectives of the KTA Framework and IM, this study identified the commonalities and complementary strengths between the two as the core methodological integration point. The KTA Framework was used to facilitate the effective application of research-generated knowledge into clinical practice, allowing for a more comprehensive consideration of tailoring scientific evidence, addressing the practical needs of stakeholders, and selecting intervention strategies during the intervention design process. Meanwhile, IM was employed to achieve evidence-based design of intervention strategies and pathways; it was used to employ change objectives to concretize and visualize intervention steps, thereby addressing the limitations of the KTA Framework in developing context-specific interventions in real-world settings.The study flow is illustrated in Appendix Fig. 1(1–2).
A historical control design was used to evaluate the effects of the intervention programs on AWEs’ behavioral health and objective physical health outcomes. A self-controlled design was used to evaluate the effects on health care workers’ practice compliance and the system environment.
Study The main site in this study was the neurological center of a children’s hospital in China. It was composed of a neurological ward,* a specialized outpatient clinic*,* a pediatric epilepsy diagnosis and treatment center*,* a clinical nerve electrophysiology room*,* and a neurology laboratory.*
Between March 2023 and February 2024, we employed a convenience sampling method to consecutively recruit AWEs and their families who met the study criteria from a Grade-III children’s hospital in Chongqing. Eligible participants were adolescents aged 12 to 18 years diagnosed with epilepsy according to established diagnostic criteria [32]. Exclusion criteria encompassed individuals in a critical stage of illness, those with comorbid intellectual disability, mental health disorders, or severely impaired brain function. These criteria align with those applied in our preceding evidence synthesis and current state analysis studies. The required sample size was determined based on the number of seizures as the primary outcome measure, using the mean difference between two independent samples. Sample size significance level (α) was assumed to be 0.05 and 1-β was set to be 80%. A family-centered intervention group for children with epilepsy had 10.29 ± 0.31 seizures within a fixed time and the control group had 13.78 ± 2.15 [33]. The calculated effect size (Cohen’s d) was 2.25, indicating a large intervention effect. Then the following calculation was tα/2 = 1.98, tβ = 0.84, σ2 = 7.121, µ1-µ2 = 4.36, and n = 42. Considering 10% loss to follow-up, it was calculated that at least 46 samples were required in each group, for a total of at least 92 samples. Grouping subjects eligible for enrollment from March-August 2023 were included in the control group, and those eligible from September 2023 to February 2024 were included in the intervention group.
In evidence-based practice transformation research, the sample size in the clinical review phase typically does not rely on statistical calculations but is based on the “complete practice team” as the object. The inclusion of health care workers follows the principle of “full coverage of stakeholders” [26]. Health care workers who met the inclusion/exclusion criteria were recruited at the evidence conversion site between March 2023 and February 2024. The 31 staff members three nursing managers, one medical manager, 20 clinical nurses, and seven clinicians. Inclusion ≥2 years relevant experience and voluntary participation. Exclusion not on duty due to leave; trainees of health care personnel; no medical practice certificate; refusal to participate in the study.
Study contents: Control AWEs and their family were given routine nursing guidance. After discharge, telephone follow-up was performed every month, an EEG review was performed at 3 and 6 months, and patients were given routine self-management education. A specialized internet service platform facilitated consultation and guidance services for patients and family caregivers. During this period, medical staff received routine professional training, including monthly in-department learning and difficult case discussion, and weekly nursing rounds.
Intervention the protocol for TR of AWEs in this study is shown in Appendix 1. The intervention group received a comprehensive, multi-level self-management intervention program. The control group received routine care, which typically includes basic health education and routine follow-up, but were not provided with the systematic, multi-dimensional intervention components given to the experimental group.
This study was approved by the ethics committee of the Children’s Hospital of Chongqing Medical University. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from parents of all patients.
Evidence-based practice groups were established, consisting of 13 two head nurses, two nursing specialists, two pediatric and adolescent epilepsy medical specialists, one pediatric chronic disease management expert, one pediatric and adolescent psychological counseling and treatment expert, one evidence-based medicine expert, three neurology nurses and one clinician. See Appendix Table 1(1–1).
Table 1Comparison of baseline data in included AWEs n (%)ItemsCategoriesSubjectsn = 96Intervention groupn = 47Controlgroupn = 49х^2^ P AgeAges 10 to 1215 (15.63)7 (14.89)8 (16.33)0.2310.782Ages 13 to 1547 (48.96)22 (46.81)25 (51.02)Ages 15 to 1834 (35.42)18 (38.30)16 (32.65)GenderMale51 (53.13)27 (57.45)24 (48.98)0.8330.531Female45 (46.88)20 (42.55)25 (51.02)Level of educationPrimary school18 (18.75)8 (17.02)10 (20.41)2.4320.761Junior high46 (47.92)24 (51.06)22 (44.90)High school32 (33.33)15 (31.91)17 (34.69)Comorbidities1 type52 (54.17)27 (57.45)25 (51.02)1.816^^1.2172 to 341 (42.70)18 (38.30)23 (46.94)> three3 (3.13)2 (4.26)1 (2.04)Duration of illness< 6 months3 (3.13)1 (2.13)2 (4.08)0.763^^0.1026 to 12 months8 (8.33)5 (10.64)3 (6.12)13 to 23 months39 (40.63)18 (38.30)21 (42.86)2 to 5 years34 (25.00)18 (38.30)16(32.65)> 5 years12 (12.50)5 (10.64)7 (14.29)Epilepsy typePartial epilepsy61 (63.53)32(68.09)29 (59.18)1.2110.531Comprehensive epilepsy18 (18.75)7 (14.89)11 (22.45)Epilepsy unclassified17 (17.71)8 (17.02)9 (18.37)Antiepileptic drugsMonotherapy46 (47.92)21 (44.68)25 (51.02)2.4380.120Multi-drug treatment50 (52.08)26 (55.32)24 (48.98)Note. AWEs: adolescents with epilepsy; *: using Fisher’s exact test
A requirements assessment was conducted to create a logical model of the problem. Self-management behavioral problems and support needs of AWEs were explored, the theoretical framework of TR was optimized for self-management intervention, and the logical model of the problem was determined [24, 25].
A PIPOST model [34] was used to construct evidence-based questions, and computer retrieval was conducted according to the “6S” evidence model and top-down principle [35]. The strategies for computer retrieval or Internet search are presented in Appendix 2. After evaluation of methodology quality, the evidence was extracted and summarized according to the judgment of evidence-based practice groups. According to the inclusion criteria, five guidelines, six systematic reviews, seven expert consensus documents, and one recommended practice were screened in Appendix 3. From the four aspects of intervention principles, environmental intervention, behavioral intervention, and cognitive intervention, 45 pieces of evidence were summarized in 10 categories [23].
Evaluate the clinical applicability of the evidence using mixed evaluation. In the quantitative evaluation method, a FAME strategy (Feasibility-Appropriateness-Meaningfulness-Effectiveness) was adopted to evaluate the clinical applicability of the internal and external authenticity of evidence from four aspects [26], and a Likert 5-point scale was adopted. The participants were nine experts from the evidence-based practice groups. In the qualitative evaluation method, evidence which was below the threshold or disputed was discussed by the practice group.Develop and revise clinical review indicators. Members of the practice group combined evidence with clinical situations and professional judgment to formulate review indicators and methods under the principles of effectiveness, credibility and measurability. These indicators were established after three rounds of discussion. Clinical nurses, clinicians and patients or caregivers were included in the process.Create change goals. Based on the results of the clinical indicators review, intervention targets for health care workers were determined from the organizational, team and individual levels of AWE self-management support interventions. The intervention direction was based on the evidence review indicators, and Performance Objectives were identified through practice group discussions. These combined barriers, facilitators, and health promotion behavior recommendations.Build a logical model for changing goals. Based on intervention goals, performance goals and the hypothesized causal path of changing goals [30, 36], a logical model of self-management intervention for changing goals in AWEs was constructed. See Appendix Fig. 1(1–3).Construct a matrix of change goals. Intervention mapping helps to apply determinants from social cognitive theory to the process of changing behavior [27, 37]. According to the logical model, a matrix was established as above, and the specific contents of changing goals were defined to provide a basis to formulate intervention strategies. See Appendix Table 1(1–2 and 1–3).
This step involves theoretical or practical techniques [29, 37, 38]. Based on the logical matrix, the construction, composition and description of social cognitive theory [39, 40], and the recommendations of clinical review indicators, intervention strategies were determined through group discussion, as shown in Appendix Table 1(1–4).
A pre-strategy was developed based on evidence and theory, combined with findings from the pilot site and medical staff. From this, the draft self-management Intervention Plan for AWEs during TR was formed and discussed during an Expert Meeting (see Appendix 1).
Assessment of readiness for evidence-based practice in pilot sites. An interpretative sequence mixed method was adopted to study the barriers and facilitators to evidence-based practice from the perspective of pediatric nursing staff, to optimize preparation [25]. Clinical implementation of intervention program.
According to the KTA framework, evaluation was carried out at three patient, nursing staff and organization.
(1) Evaluation indicators and methods at patient level
Objective physical health EEG results and the number of seizures in the last three months were used. Fewer seizures and an EEG close to normal suggest better physical health of AWEs. Among them, EEG manifestations were divided into six levels according to the Young grading standard [41]: a lower grading indicating a less severe brain injury.
Behavioral health status self-management ability. The Chinese Epilepsy Self-Management Scale was adopted [42]. This includes management of drugs, information, safety, seizure, and lifestyle across five dimensions, a total of 20 items. Each item was scored on a Likert 5-level scale, from “never” to “often”, with some items reverse scored. The higher the score, the better the self-management behavior. The Cronbach’s α coefficient of this scale was 0.829 and the retest reliability coefficient was 0.743 [42].
TR: the Epilepsy Transition Readiness Assessment Questionnaire (EpiTRAQ), translated into Chinese for this study [22], includes 35 projects across six dimensions. The total Cronbach’s α coefficient of the Chinese version was 0.919, and the retest reliability was 0.923 [22].
Self-management behavior a review table was used to evaluate self-management behavior compliance of patients and family caregivers. There were 19 items in total, which could each be answered yes or no. Compliance for each entry = number of patients or family caregivers for the entry/total number of patients for the entry × 100%.
(2) Evaluation indicators and methods at medical staff level
Compliance with evidence-based practice. A review table was used to assess implementation of practice behavior. There were 17 items, each having a yes/no answer. The calculation was performed as above.
(3) Evaluation index and evaluation method at system level
The 17 items could be answered yes or no, and the average completion rate of system improvement = the number of projects completed in this stage/17 × 100%.
There are 19 review items at the patient and family caregiver levels, 17 at the medical staff level and 17 at the system level, totaling 53 review items. To assess content validity, we conducted a two-stage process. First, there was an expert authority the familiarity coefficient (Ca = 0.91), judgment coefficient (Cs = 0.83), and authority coefficient (Cr = 0.87) all exceeded the threshold of 0.7, confirming the credibility of expert input. Secondly, there was a quantitative validity based on expert ratings, we calculated an Item-level Content Validity Index (I-CVI) ranging from 0.81 to 1.00 for all 53 items. Scale-level Content Validity Index (S-CVI/Ave = 0.96).
(4) Data collection method
Data collection was carried out jointly by the researchers and members of the practice team. Data collection was divided into two time before the application of the plan, data for the control group were collected (March 2023 to August 2023); and during the application period (September 2023 to February 2024) data for the intervention group were collected. The specific methods of data collection are shown in Appendix Table 2.
Table 2Comparison of baseline data in included primary caregivers of AWEs n (%)ItemCategoriesSubjectsn = 96Intervention groupn = 47Controlgroupn = 49х^2^ P Relationship to patientFather33 (34.38)15 (31.91)18 (36.73)1.2390.523Mother48 (50.00)23 (48.94)25 (51.02)Other15 (15.63)9 (19.15)6 (12.24)Age30–4011 (11.46)4 (8.51)7 (14.29)0.180^*****^0.83241–5067 (69.79)31 (65.96)36 (73.47)51–6018 (18.75)12 (25.53)6 (12.24)Level of educationJunior high school and below45 (46.88)21 (44.68)24 (48.98)2.0120.878High school or secondary school27 (28.13)12 (25.53)15 (30.61)University or above24 (25.00)14 (29.79)10 (20.41)Family structureNuclear family38 (39.58)17(36.17)21 (42.86)0.8550.352Trunk family36 (37.50)20 (42.55)16 (32.65)Mobile home22 (22.92)10 (21.28)12 (24.49)Locationrural53 (55.21)29 (61.70)24 (48.98)0.4260.129Towns and cities43 (44.79)18 (38.30)25 (51.02)Medical payment methodsOut-of-pocket payment69 (71.88)35 (74.47)34 (69.39)1.8211.326Health insurance27 (28.13)12 (25.53)15 (30.61)Note. AWEs: Adolescents with Epilepsy; *: using Fisher’s exact testNuclear parents and children; backbone outside/grandparents, parents and children; floating a family in which one of the couple or a grandparent provides long-term care
Statistical analysis was performed using the Windows version of SPSS 26.0 (IBM Corp., Armonk, New York, USA) and the Windows version of Stata 3.0 (Stata Corp., College Station, Texas, USA). Data entry was checked by two researchers. Count data were described by frequency and component ratio. Measurement data were described as mean ± standard deviation. All continuous variables were tested for normality (required skewness < 3.0, kurtosis < 8.0) before statistical analysis. Independent sample t, paired t and Chi-square tests were used for inter-group comparison.
The 31 participants were 30 women and 1 man, the average age was 34.61 ± 6.20 years, and the mean experience of epilepsy care was 9.32 ± 6.26 years (Appendix Table 3).
Table 3Comparison of baseline survey outcomes between patients before interventionFeaturesGroupingIntervention groupn = 47Control groupn = 49t/х^2^ P Self management(ESMS)Information management16.45 ± 2.2117.78 ± 2.550.495^^0.093Security management10.68 ± 1.8711.89 ± 2.010.003^^0.972Lifestyle management14.33 ± 2.3113.36 ± 2.56-1.256^^0.426Medication management13.19 ± 1.3415.02 ± 1.100.802^^0.789Management of seizures12.06 ± 2.1211.23 ± 2.030.255^^0.513Transition readiness(EpiTRAQ)To make an appointment20.60 ± 3.4122.03 ± 2.150.654^^0.241Doctor-patient communication5.23 ± 1.105.01 ± 1.221.584^^0.752Daily activity management25.23 ± 3.0325.56 ± 2.89-0.301^^0.427Health problem tracking19.10 ± 4.3019.25 ± 4.38-0.813^^0.233Medication management13.42 ± 2.8812.87 ± 3.250.503^^0.621Number ofseizures in recent3 months (times)1–325 (53.19)28 (57.14)1.6790.2104–1014 (29.79)13 (26.53)> 108 (17.02)8 (16.33)EEG resultsNormal5 (10.64)7 (14.29)2.0010.481Level 121 (44.68)26 (53.06)Level 216 (34.04)13 (26.53)Level 35 (10.64)3 (6.12)Note. *: t test
In the control group, 55 AWEs and their families were included. Due to patient relocation in four cases and change of medical care location in two cases, six patients were lost to follow-up, giving a final total of 49 patients (loss rate 10.91%). Mean age in this group was 14.78 ± 2.15 years. In the intervention group, 51 patients and their families remained. Four patients (7.84%) were lost to follow-up due to relocating (n = 2), aggravation of the disease (n = 1), and change of hospital (n = 1). The average age of family caregivers was 45.87 ± 3.56 years. There were no significant differences in age, gender, education level, number of comorbidities, course of disease, type of epilepsy, or antiepileptic drugs before and after the program (P > 0.05; Table 1). There was no significant difference in the relationship between caregiver and patient, caregiver’s age, education level, family structure, or place of residence (P > 0.05; Table 2).
Comparison of Baseline Survey Outcomes Between Patients Before Intervention. There was no significant difference in the number of seizures or EEG data (P > 0.05; Table 3).
Comparison of Outcomes in the Control Group Before and After Intervention. There was a significant difference in the number of seizures, drug management in both self-management and TR; but no significant differences in the other parameters (P > 0.05; Table 4).
Table 4Comparison of outcomes in the control group before and after interventionCharacteristicsGroupingBeforeAftert/х^2^ P Self-management(ESMS)Information management17.78 ± 2.5516.23 ± 3.02-1.217 *0.230Security management11.89 ± 2.0112.18 ± 1.270.521 *0.675Lifestyle management13.36 ± 2.5614.13 ± 2.660.682 *0.493Administration of medications15.02 ± 1.1021.89 ± 1.520.142 *0.028Seizure management11.23 ± 2.0312.36 ± 2.55-1.016 *0.155Transition readiness(EpiTRAQ)make an appointment22.03 ± 2.1523.16 ± 2.310.305 *0.761Doctor-patient communication5.01 ± 1.225.25 ± 1.400.421 *0.323Daily activity management25.56 ± 2.8925.12 ± 2.290.393 *0.590Health problem tracking19.25 ± 4.3820.12 ± 3.651.637 *0.121Medication management12.87 ± 3.2516.24 ± 2.260.801 *0.017Number ofseizures in recent3 months (times)1–328 (57.14)30(61.22)3.0210.0234–1013 (26.53)15 (30.61)> 108 (16.33)4 (8.16)EEG resultsNormal7 (14.29)6 (12.24)2.3730.541Level 126 (53.06)30 (61.22)Level 213 (26.53)11 (22.45)Level 33 (6.12)2 (4.08)Note. *: t test; Data collected are seizure frequencies over the past three months
Comparison of Outcomes in the Intervention Group Before and After Intervention. All parameters were significantly different except doctor-patient communication in TR (P > 0.05; Table 5).
Table 5Comparison of outcomes in the intervention group before and after interventionFeaturesGroupingBeforeAftert/х^2^ P Self-management(ESMS)Information management16.45 ± 2.2121.68 ± 2.713.511^^0.003Security management10.68 ± 1.8716.33 ± 2.285.421^^0.000Lifestyle management14.33 ± 2.3125.49 ± 2.466.788^^0.015Medication management13.19 ± 1.3423.01 ± 1.78-2.430^^0.010Seizure management12.06 ± 2.1219.06 ± 3.322.355^^0.006Transition readiness(EpiTRAQ)Appointment20.60 ± 3.4125.89 ± 2.894.511^^0.028Doctor-patient communication5.23 ± 1.106.23 ± 2.015.327^^0.723daily activity management25.23 ± 3.0331.47 ± 2.63-3.030^^0.001Health problem tracking19.10 ± 4.3025.77 ± 3.522.861^^0.006Medication management13.42 ± 2.8820.31 ± 2.692.237^^0.026Number ofseizures in the past 3 months00 (0.00)2 (4.26)3.0210.0101–325 (53.19)28 (59.57)4–1014 (29.79)12 (25.53)> 108 (17.02)5 (10.64)EEG resultsNormal5 (10.64)5 (10.64)2.3730.014Level 121 (44.68)27 (57.45)Level 216 (34.04)13 (27.66)Level 35 (10.64)2 (4.26)Note. * t test
Comparison of Outcomes Between the Two Groups After Intervention. At 6 months after discharge, there was a significant difference in all parameters except the number of seizures and doctor-patient communication (P > 0.05; Table 6).
Table 6Comparison of outcomes between the two groups after interventionCharacteristicGroupingIntervention groupn = 47Control groupn = 49t/х^2^ P Self-management(ESMS)Information management21.68 ± 2.7116.23 ± 3.022.0410.011Safety management16.33 ± 2.2812.18 ± 1.273.1210.008Lifestyle management25.49 ± 2.4614.13 ± 2.66-2.4530.000Pharmaceutical administration23.01 ± 1.7821.89 ± 1.52-3.4320.000Seizure management19.06 ± 3.3212.36 ± 2.552.0510.023Transition readiness (EpiTRAQ)Reservation25.89 ± 2.8923.16 ± 2.313.0050.001Doctor-patient communication6.23 ± 2.015.25 ± 1.406.1170.389Daily activity management31.47 ± 2.6325.12 ± 2.29-2.2310.001Health problem tracking25.77 ± 3.5220.12 ± 3.652.8100.023Medication management20.31 ± 2.6916.24 ± 2.262.5210.007Number of seizures in the last three months02(4.26)0(0.00)2.6720.3231–328(59.57)30(61.22)4–1012(25.53)15(30.61)>105(10.64)4 (8.16)Electroencephalogram resultNormal5(10.64)6(12.24)-3.4120.023First level27(57.45)30(61.22)Second level13(27.66)11(22.45)Third level2(4.26)2(4.08)Note. *: t-test
Comparison of Patient and Caregiver Compliance Before and After the Program. A second review of self-management behavior compliance was conducted for 47 patients and family caregivers in the intervention group six months after discharge. Across 19 items, the compliance rate increased from 53.37 to 74.80% (Table 7). The results of the six review criteria are shown in Appendix Fig. 1 (1–4).
Table 7Comparison of patient and caregiver compliance before and after the programReview criteriaBefore applicationAfter applicationTotal timesN1R1Total timesN1R115.1Caregivers can participate in training, guidance, and supervision of self-management of AWEs865159.30%473574.47%15.2Caregivers were aware of their role change requirements864248.84%473165.96%15.3Caregivers correctly reported the academic progress and cognitive function of AWEs to medical staff861719.77%473063.83%16.1Know the management of missing AED866170.93%474289.36%16.2Use and adjust AED according to the doctor’s advice, and do not stop, reduce or change AED at will868295.35%474595.74%16.3Use tools or methods that improve medication adherence866575.58%473676.60%16.4Aware of measures to observe and manage seizures during sleep in AWEs865159.30%474187.23%17.1Physical exercise was encouraged, and caregivers could accompany patients to avoid overexertion867789.53%474391.49%17.2If the epilepsy is not well controlled, know to carry out physical exercise under the guidance of a doctor; and limit diving, skydiving, and altitude sports867283.72%474289.36%17.3People with a history of febrile seizures should avoid excessive exercise, hot water baths, and outdoor activities when the ambient temperature is too high **867890.70%474391.49%18.1AWEs /caregiver families have a checklist of ASAP and know how to use it8600472348.94%18.2Caregivers will properly use video to document out-of-hospital seizures in AWEs patients866676.74%474187.23%18.3Benzodiazepines were readily available at home861112.79%471838.30%18.4AWEs/caregivers should visit the hospital as soon as possible within 2 weeks of a recurrence of epilepsy during remission867486.05%473880.85%19.1AWEs/caregivers were aware of self-health monitoring content and comorbid symptoms of epilepsy863237.21%473472.34%19.2AWEs were aware of the consultation procedures and the names of key care-team members863034.88%473063.83%19.3AWEs/caregivers were aware of illness stigma coping and future career development861213.95%471940.43%19.4AWEs/caregivers were aware of the access to major medical resources861922.09%473778.72%20Caregivers were aware of their own health behaviors as role models for their patients863237.21%474187.23%Average adherence rate53.37%74.80%Note. N: number of compliance cases; R: execution rate; AWEs: adolescents with epilepsy; ASAP:acute seizure action plans; AED: anti epileptic drug
Compliance of Health Care Workers With Evidence-Based Practice. In January-February 2024, a second review of health care staff was conducted, including 23 nurses and eight doctors at the pilot site as baseline review subjects. Across 17 items, the compliance rate increased from 43.19 to 77.27% (Table 8). The results of the eight review criteria are shown in Appendix Fig. 1 (1–5).
Table 8Comparison of clinical audit before and after implementation of the program for medical staffReview criteriaTotal timesBefore applicationAfter applicationN1R1N2R27When a doctor orders an AED, the drug name is consistent8787.50%8100.00%8AWEs were assessed for sleep status by health care providers312580.65%2890.32%9.1Monitoring and management of body temperature after vaccination2328.70%1878.26%9.2Delay vaccinations23521.74%2295.65%9.3Specific visual stimuli or flashes of light can trigger seizures231565.22%1878.26%10Nurses provide information about ketogenic diet readiness, how to consume it, observation and prevention of adverse effects, and precautions for eating out and withdrawing from the ketogenic diet232086.96%23100.00%11Nurses explained the concept and risks of comorbidities according to the specific needs and disease characteristics of AWE patients/caregivers23313.04%1773.91%12Medical staff organized and guided families to carry out “seizure exercise”31001548.39%13.1Within three days of diagnosis, education and skills on measures to improve medication adherence, avoid inducing seizures, and reduce the risk of seizures were provided231773.91%2086.96%13.2Health education for AWE patients/caregivers was completed at different times23521.74%1773.91%13.3The presentation of health information is easy to understand231460.87%1982.61%13.4Provide educational information in many forms and formats231252.17%1878.26%13.5Correct the misunderstanding of AWE patients/caregivers about health information in a timely manner231460.87%1878.26%13.6Provide both written and oral education on AEDs to AWE patients/caregivers231252.17%2086.96%14.1Mental health education for AWE/caregivers was carried out23626.09%1252.17%14.2Medical staff can timely refer AWEs for neuropsychological evaluation31516.13%2167.74%14.3Cognitive behavioral therapy and mindfulness training were provided to patients with AWEs according to need and assessment3126.45%1341.94%Average execution rate43.19%77.27%Note. N: number of executions; R: execution rate; AWEs: adolescents with epilepsy; ASAP:acute seizure action plans; AED: anti epileptic drug
Comparison of Review Indicators at the System Level Before and After Program Application. During January-February 2024, a second review was conducted in the outpatient and ward areas of the pilot sites against six standards and 17 items. The system improvement rate increased from 29.41 to 88.24%. The results are shown in Table 9.
Table 9Comparison of clinical audit before and after implementation of the program at system levelReview standardBefore applicationPost-application1There are patient self-management intervention internal quality control mechanisms1.1There are requirements and norms for self-management interventionsNOYES1.2There are comprehensive guidelines and illustrative examples provided for personalized self-management interventionsNOYES1.3Establish patient and family involvement in the implementation, feedback and evaluation of self-managementNOYES2Ensure AWE caregiver self-management information platform2.1AWEs self-management support information systemYESYES2.2Platform development and application include AWE patient/caregiver feedback collection, feedback and improvementNOYES2.3The self-management information platform is designed with gamification technologyNONO3A multidisciplinary TR self-management intervention team was formed3.1The panel included members of the pediatric and adult medical care team, pharmacists, nutritionists, psychologists, staff from the Department of Social Work, administrators from the Medical Administration Department of the Health and Health Commission, and staff from the Education CommissionYESYES3.2There are multi-disciplinary communication mechanismsYESYES3.3Nurses have clear responsibilities and are responsible for group project organization, promotion, supervision and effect evaluationNOYES3.4There is a record of improving public knowledge of epilepsy diseases in primary and secondary schoolsYESYES3.5Demonstration of convulsive management techniques for primary and secondary school publicNONO4Provide social events and community platforms for AWEsYESYES5Establish a transition readiness list5.1The list has AWE/caregiver self-management goalsNOYES5.2The list is presented in no Pass/Fail scoring formNOYES5.3The list includes potential emergencies during the transition period and recommendations for handling themNOYES5.4The list includes the type of seizures, number of seizures, characteristics of seizures, treatment measures and effects, adverse drug events and comorbidities evaluation and management recommendationsNOYES6Improve and promote ASAP applicationsNOYESAverage completion rate (completed items/total items)29.41%88.24%Note. TR: transition readiness; AWEs: adolescents with epilepsy; ASAP: acute seizure action plans
Improvement of Relevant Processes and Working Mechanisms. The following improvements were developing operational requirements for the multidisciplinary support group including revising the workflow; an improved training program for nursing staff in the pilot sites and ketogenic diet demonstration classroom; producing a health education document for AWEs; revised mechanisms of sleep clinical evaluation for AWEs; and improved referral of AWEs to a psychology clinic, as cognitive psychological problems are common comorbidities in AWEs.
Support Work and Information Platform Development. The following developments were a chronic disease youth transitional service information platform (Growth Bridge) and a training manual on self-management interventions during TR for both health care workers and AWEs.
In constructing an intervention plan, it is helpful to identify and classify the key elements of the theoretical framework, by constructing a logical model and matrix of the change goal. The results of the program implementation and evaluation support the relationship between the theoretical framework and conclusion. The theoretical framework of this study has been optimized and developed to improve self-management intervention for TR of AWEs, as shown in Appendix Fig. 1(1–6). This theoretical framework is not a simple repetition of existing theories or concepts. Based on the existing research achievements of the team, combined with literature review and theoretical analysis, the social ecological model and social cognitive theory of transitional readiness for adolescents and young adults were integrated to form the preliminary theoretical framework of this study, namely the 1.0 version of the theoretical framework for self-management intervention of transitional readiness for adolescent epilepsy patients. Through the current situation research, construction and empirical research of the intervention plan, the theoretical framework is further optimized and developed to form a theoretical framework for self-management intervention during the transitional period of adolescent epilepsy patients.
Evidence-based practice emphasizes combining the best available evidence with clinical experience and patient values to make decisions that make practical sense. In this process, attention to stakeholder needs is key to ensure that patient and other stakeholder values are fully considered [26]. Under the framework of KTA [26], researchers carry out knowledge application, including evidence applicability evaluation. All stakeholders were included in baseline measurement. Under IM theory [29], the logical model and matrix of the change goal are created; and the intervention, performance goals and change goals are presented based on stakeholders’ positions. This comprehensive approach makes the intervention more practical and sustainable. Moreover, the scope, components, time/frequency, and method were clarified to improve clinical acceptance, and the intervention strategy was combined into a systematic and reasonable program through expert meetings. Combining the KTA Framework and IM theory leverages the complementary strengths of these two evidence-based methodologies [26, 29]. This integrated approach allows for more systematic tailoring of scientific evidence to the actual needs of stakeholders, facilitates the clear definition of intervention objectives, and supports the informed selection of strategies during the intervention design process. As a result, it enhances the operability, sustainability, and contextual relevance of the intervention, thereby better addressing the practical requirements of real-world evidence implementation.
As an initial exploration of this combined methodological pathway, this study demonstrates how the integration of KTA and IM can contribute to a more robust and stakeholder-responsive intervention design. The approach not only improves intervention feasibility and effectiveness but also offers novel insights for advancing the field of implementation mapping research.
There were significant differences in the intervention group before and after intervention except for doctor-patient communication in TR. This indicates that the interventions can improve patients’ physical health, including the number of seizures and EEG results, within 3 months. The lack of improvement in doctor-patient communication may reflect its complex requirements, and may be related to development of patients’ communication and social skills, medical staff’s concern and action for shared decision-making, and the family still playing a major role in adolescence. These factors have no obvious effect on practice change in a relatively short period of time. Therefore, to improve doctor-patient communication, pediatric medical staff need to establish trust and close relationship with patients, improve their communication skills, encourage patients to express preferences and needs, provide more understandable medical information, strengthen mental health support and other comprehensive methods. This will enable greater participation of adolescents in their treatment decisions and management.
There were significant differences between the two groups after intervention except for number of seizures and doctor-patient communication. This intervention program is comprehensive and actionable, including changes at the system, health care worker, and the patient/family caregiver levels. Effective cooperation between researchers and practitioners is key to promoting and applying the program. Researchers not only provide content, but also participate in implementing and monitoring changes; they can adjust intervention strategies during implementation and provide feedback on the effects. The lack of difference in the doctor-patient communication again suggests the challenges faced by AWEs in developing communication skills in the medical environment, and more active coping strategies are needed. The proportion of the group without seizures was higher than the control group, but there was no significant difference between the two similar to previous results [39]. This study did not demonstrate significant reduction in seizure frequency, a finding consistent with epilepsy’s inherent neurobiological variability. However, this outcome does not diminish the intervention’s value [43]. Effective seizure control requires individualized, long-term management strategies extending beyond the current study duration [44]. Critically, successful self-management should prioritize core behavioral improvements (e.g., medication adherence, symptom recognition), which our intervention demonstrably achieved. This study introduces an innovative, evidence-based self-management intervention program designed to enhance transition readiness among AWEs. For the first time, the scope and strategies of self-management interventions for this population have been clearly defined within the context of transition preparation. The development of this intervention actively involved multiple stakeholders, including AWEs, family caregivers, and specialists in pediatric chronic disease.
This approach aligns with existing literature emphasizing the importance of behavioral interventions in epilepsy self-management [45]. However, our study advances the field by integrating behavioral techniques into a comprehensive, multi-stakeholder-informed program. This represents a significant departure from previous studies, which have often focused on isolated intervention aspects rather than a holistic approach.
Comparing the control group before and after the intervention, there were significant differences in number of seizures as well as drug management in self-management and TR. The former may be related to the updated treatment plan and medication adjustment. The latter might be related to the importance of family management of antiepileptic drugs, including guidance and health education. To fully understand these differences, researchers need to explore more effective intervention strategies based on the advantages of pilot sites. Increasing the sample size may improve statistical power, making potential effects easier to observe.
Implementation rate of review items by patients and family caregivers was 74.80% after the application of the program, which was 21.44% higher than before application. After application, implementation rate of three indicators was < 60%. The results showed this program could promote compliance of AWEs and family caregivers in self-management behavior, including improving caregivers’ participation in patient self-management guidance and supervision. In the observation and reporting behavior of patients with comorbidity, the improvement was more obvious. The item “caregivers correctly reported patients’ academic progress and cognitive function to medical staff” increased by 44.06%; and the item “Patients/caregivers know the content of self-health monitoring and symptoms of epilepsy comorbidity” increased by 35.13%, indicating that management of comorbidity has received attention by patients’ families. In addition, access to medical resources has also the item “patients/caregivers know the access to major medical resources” increased by 56.63%. Improving AWEs’ awareness of medical resources is key to increasing their access, screening and use of medical information, and is vital for smooth transition to adult medical treatment.
In contrast to the single-session approach described in some previous studies [8, 33]. our program employed a multi-session structure that allowed for more in-depth skill development and reinforcement. This design difference may account for the improvements observed in our trial, particularly in areas such as both patient and family caregiver reporting and comorbidity management. These clinical outcomes are particularly relevant, as they address well-recognized challenges in epilepsy care, including the need for improved caregiver–provider communication and more effective management of epilepsy-related comorbidities.
Notably, the item assessing “caregivers’ awareness of serving as role models through their daily health behaviors” showed a striking increase of 50.02%, underscoring the critical role of familial influence in promoting cooperative and empathetic dynamics within the household and reduced the likelihood of adolescents adopting unhealthy behaviors. Post-intervention, significant improvements were observed across six key indicators among AWEs and their family caregivers. Specifically, gains exceeding 30% were recorded for both “patients’ knowledge of transitional readiness” and “caregivers’ awareness of their role as behavioral models”, demonstrating the program’s efficacy in improving TR knowledge and consciously reinforcing caregiver modeling. These findings highlight the innovative dimension of our by systematically integrating role-modeling awareness and transition readiness into a structured program, we targeted fundamental family-centered mechanisms that are frequently overlooked in conventional epilepsy care.
Among all the items reviewed in this part, 18 improved, except for “patients/caregivers know the recurrence of epilepsy in remission and seek medical treatment as soon as possible within 2 weeks”, which decreased by 6.00%. This may be because the study period was from September to February of the following year, and the school holidays affected timely medical treatment behavior. Internet hospital platforms should be developed to provide safe and convenient online diagnosis and treatment services for adolescents with chronic diseases.
After the application of the program, the implementation rate of medical staff review items was 77.27%, which was 24.08% higher than that before the application, and the implementation rate of three indicators was < 60%. This program can improve the quality of health education by providing staff with correct medical advice, routine patient sleep assessment, guidance on reducing epileptic-inducing factors, management of a ketogenic diet, and management of comorbid symptoms and psychological support. For the three review items with implementation rate < 60%, although there is a great improvement compared with before application, all of them are greater than 30%. Due to the short duration of the program, the popularization of seizure drills and staff professional improvement was insufficient. This suggests that the scope and frequency of activities should be expanded through the hospital’s Social Work Department to organize families to carry out seizure drills. To provide mental health education and intervention for psychosocial problems, it is also necessary to strengthen cooperation with professional child and adolescent psychological treatment personnel when advocating neurospecialists to strengthen psychological training.
Eight indicators at the patient and family caregiver level improved after the program. For four indicators, the increase rate was > 30%, suggesting that self-management intervention programs based on evidence-based practice are effective. It is advantageous for medical staff in the direction of health education guidance, to carry out family-centered out-of-hospital emergency treatment of epilepsy and mental health support.
The completion rate of system level items after the program was 88.24%, which is 58.83% higher than at the start. However, “gamification technology design for self-management information platform” was not achieved. This is because design of gamification technology requires a professional game engine or application program, which involves complex technology development. It failed to advance as planned due to lack of technical support. In conjunction with health needs, open-source gamification or modular development techniques should be leveraged in response to recommendations for gamified health management platforms. In addition, “Providing demonstration of convulsive management technology for primary and secondary school public” was not achieved, probably because it is difficult to change school administrators’ understanding of the importance of epilepsy and related management technology in a short period of time. The school’s demand and acceptance of demonstration of out-of-hospital convulsive management is not high, suggesting that improvements require comprehensive social cooperation.
The theoretical framework of TR self-management intervention for AWEs reflects SMART theory on the control of potential intervention factors and the advantages of a social ecosystem, as well as the interaction of cognition, behavior and environment with the triadic determinism of social cognition theory in improving patients’ and families’ self-management behavior. The elements within the theoretical framework reflect different intervention categories and support levels, which can define the scope and focus of TR services for AWEs, and avoid deviations of the research process and clinical practice from the theme. In addition, further revision and improvement of the theoretical framework through evidence-based methodology can help researchers to systematically consider the relationship between the research purpose, intervention variables and results, and clarify the theoretical hypothesis and logical structure of the research. The interplay among stakeholders (patients, family caregivers, and healthcare professionals) across organizational levels underscores a core rationale for combining the KTA Framework with IM the centrality of addressing stakeholder needs in evidence-based practice.Incorporating stakeholder’s feedback into constructing and improving the theoretical framework enriched its practical orientation and applicability. Therefore, construction and continuous improvement of the theoretical framework is key to optimizing self-management intervention programs. In addition to expanding the boundaries of self-management knowledge, the existing theoretical system of TR for chronic adolescents should be improved.
This study proposed a theoretical framework of self-management of TR for AWEs. The formation of the framework begins with a scope review and theoretical study. Mixed results were optimized for behavioral distress and intervention needs of the target population. KTA frameworks and IM methodologies were developed in a logical model and validated in evidence-based practice. In addition, this study combines the KTA framework and IM theory into the practice of evidence transformation, and explores the cross-application of the two methodologies, providing ideas to expand the mapping research field. Finally, this study constructs a self-management intervention plan for TR of AWEs based on evidence-based practice, providing a reference for practicing localized transitional services for adolescents with chronic diseases.
Due to the limitation of research time, a large-scale, multi-center and periodic intervention could not be carried out. The sample of this study came from a grade-III children’s hospital, therefore promoting the research results and verifying the theoretical framework were limited. The intervention time was short, and the short-term intervention effect could only be reflected. There was no long-term follow-up or health economics evaluation. This study only assessed evidence-based practice readiness of the pilot pre-experiment of the intervention program could not be evaluated due to time limitations. In addition, due to ethical limitations and the requirements of patients’ rights and interests, this study’s intervention study for clinical translation of evidence was designed as a Quasi-experimental study, which weakened the strength of the study’s argument. Moreover, this study used historical controls rather than randomized controls, which may introduce confounding bias. Future studies should consider using more rigorous research designs, such as randomized controlled trials, to minimize potential biases and enhance the robustness of the findings.
Clinical transformation of evidence is a systematic process of change with certain risks, and ensuring its validity and safety is the primary consideration of evidence-based practitioners [26]. Prior to application of the intervention program, this study adopted an interpretative sequence mixed method to understand the readiness of the program from the perspective of pediatric nurses, who are the main practitioners of TR services, to optimize preparation. In the clinical application of the program, a historical comparison design was used to evaluate the impact of the program on the health status of AWEs. A self-controlled design was used to evaluate the impact of evidence-based practice on the compliance of medical staff and the system environment. The results suggest that the intervention is feasible and effective. Process monitoring at the pilot site suggests that dynamic assessment of obstacles to implementation and consequent adjustment is key, along with the reserve of knowledge and skills for practitioners to prepare for the transition period.
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Supplementary Material 1
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Supplementary Material 7