Development and evaluation of an eHealth self-management intervention for chronic kidney disease patients in China: protocol for a mixed-method hybrid type 2 trial

Development and evaluation of an eHealth self-management intervention for chronic kidney disease patients in China: protocol for a mixed-method hybrid type 2 trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Study protocol Development and evaluation of an eHealth self-management intervention for chronic kidney disease patients in China: protocol for a mixed-method hybrid type 2 trial Hongxia Shen, Rianne van der Kleij, Paul JM van der Boog, Xiaoyue Song, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.2.22736/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Chronic kidney disease (CKD) is a significant public health concern. In CKD patients, interventions that support disease self-management have shown to improve health status and quality of life. At the moment, the use of electronic health (eHealth) technology in self-management interventions is becoming more and more popular. Evidence suggests that eHealth-based self-management interventions can improve CKD patients’ health-related outcomes. However, knowledge of the implementation and effectiveness of such interventions in general, and in China in specific, is still limited. This study protocol aims to develop and tailor the evidence-based Dutch ‘Medical Dashboard’ eHealth self-management intervention for patients suffering from CKD in China and evaluate its implementation process and effectiveness. Methods To develop and tailor a Medical Dashboard intervention for the Chinese context, we will use an Intervention Mapping (IM) approach. A literature review and mixed-method study will first be conducted to examine the needs, beliefs, perceptions of CKD patients and care providers towards disease (self-management) and eHealth (self-management) interventions (IM step 1). Based on the results of step 1, we will specify outcomes, performance objectives, and determinants, select theory-based methods and practical strategies. Knowledge obtained from prior results and insights from stakeholders will be combined to tailor the core interventions components of the ‘Medical Dashboard’ self-management intervention to the Chinese context (IM step 2-5). Then, an intervention and implementation plan will be developed. Finally, a 9-month hybrid type 2 trial design (N=60) will be employed to investigate the effectiveness of the intervention using a pilot randomized controlled trial with two parallel arms, and the implementation integrity (fidelity) and determinants of implementation (IM step 6). Discussion Our study will result in the delivery of a culturally tailored, standardized eHealth self-management intervention for CKD patients in China, which has the potential to optimize patients' self-management skills and improve health status and quality of life. Moreover, it will inform future research on the tailoring and translation of evidence-based eHealth self-management interventions in various contexts. Internal Medicine Nursing eHealth Self-management Chronic kidney disease China Hybrid design Implementation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Contributions To The Literature Knowledge of the use of eHealth-based self-management interventions in China is still lacking. Our study will result in the delivery of a culturally tailored, standardized eHealth self-management intervention for CKD patients in China, which has the potential to optimize patients’ self-management skills and improve health status and quality of life. This study will inform future research on the tailoring and translation of evidence-based eHealth self-management interventions in various contexts. This study can serve as proof of concept for the use of Intervention Mapping and a hybrid type 2 trial design to evaluate the implementation and effectiveness of eHealth self-management interventions. Background Prevalence and burden of chronic kidney disease Chronic kidney disease (CKD) poses a significant threat to public health [1-3]. Globally, more than 70 million individuals are affected by CKD [4]. In China, an estimated 10.8% (119.5 million) of adults suffer from CKD [5]. CKD is defined as abnormalities of kidney structure or function, present for more than three months, with severe implications for health [6]. CKD is chronic and follows five stages of functional decline based on the estimated glomerular filtration rate (eGFR) [6]. Numerous detrimental health outcomes are linked to CKD [7]. Also, CKD increases mortality risk and hospitalization rates, and negatively impacts the quality of life [7-9]. Additionally, health-related and societal costs of CKD are considerable and constitute a substantial economic burden [10-12]. Self-Management and eHealth interventions for CKD Interventions that support disease self-management (further referred to as ‘self-management interventions’) can have a significant impact on the health and quality of life of patients suffering from chronic conditions in general [13], and CKD patients in specific [14-16]. Self-management support is often defined as “ [……] improving chronic illness outcomes consisting of patient-centered attributes (involving patients as partners; [……]), provider attributes (possessing adequate knowledge, skills, attitudes in providing care), and organizational attributes (putting an organized system of care in place, having multidisciplinary team approach, using tangible and social support) ” [17]. In the last decade, the use of electronic health (eHealth) technology in self-management interventions has become more and more popular. EHealth technology can facilitate remote patient-provider communication and exchange of (health) data and has the potential to increase healthcare accessibility and efficiency [18]. EHealth-based self-management interventions have been shown to improve health-related outcomes, such as blood pressure (BP) control and medication adherence [19, 20], and found to be feasible and acceptable for CKD patients and care professionals [19]. Hence, the use of eHealth self-management interventions for CKD patients has become increasingly popular. Knowledge of the implementation and effectivity of such interventions in China and other developing countries is, however, still lacking [21]. Medical dashboard Researchers from the Leiden University Medical Center (LUMC) developed ‘Medical Dashboard’, an eHealth intervention to help support and involve CKD patients in their disease self-management. This platform is used in the Outpatient Clinic Kidney Transplant of the LUMC since February 2016. Via Medical Dashboard, patients can monitor their health from home (e.g., BP, weight), and can exchange health data with their care professionals. Moreover, during consultations in the outpatient clinic, care professionals and patients can also use Medical Dashboard to set personal health goals such as BP control and nutrition management (e.g., energy). In a randomized controlled trial (RCT), the use of “Medical Dashboard” has been shown to improve patients’ adherence to sodium restriction intake and BP control [14]. Also, patients reported being highly satisfied with the online disease management system used in the platform [22]. All core intervention components of ‘Medical dashboard’ and their supporting evidence base are presented in Additional file 1. Opportunities for eHealth interventions in China There is significant support and momentum for the implementation of eHealth based self-management interventions in China. China had 731 million internet users (penetration rate 53%) and 1.3 billion mobile phone users (penetration rate of 90%) in 2016, and this number is still growing [23-26]. Furthermore, policymakers and care experts in China have recently launched the national health strategy ‘Healthy China 2030’. This strategy describes eHealth technology as an essential pillar to improve disease self-management as well as the accessibility and cost-effectiveness of care in rural areas. Moreover, it views eHealth technology as the preferred medium to reach one of the main goals: ‘ enable everyone to be involved in health, share health, and be responsible for health ’ [27, 28]. Also, the prevalence rate and severe adverse health outcomes of CKD have put it high on the public health agenda in China. Study aims and research methods In conclusion, eHealth self-management interventions have the potential to fundamentally improve the quality of life and health outcomes of patients suffering from CKD in China. Therefore, we aim to tailor the evidence-based Dutch intervention ‘Medical Dashboard’ to the Chinese context and evaluate its implementation process and effectiveness. To this end, we will use an intervention mapping (IM) approach comprising six steps: (1) a needs assessment, (2) preparation of change objectives matrices, (3) selection of theory-informed intervention methods and strategies, (4) development of a tailored ‘Medical Dashboard’ based intervention plan, (5) development of an implementation - and (6) evaluation plan. In correspondence with the steps of IM [29], we aim to: Phase 1: Needs, beliefs and perceptions (Step 1 of IM) Examine the needs, beliefs, perceptions of CKD patients and care providers towards disease self-management and eHealth interventions; Phase 2: Intervention and implementation development & planning (Step 2-5 of IM) Tailor the core components of the ‘Medical Dashboard’ self-management intervention for CKD patients to the Chinese context; Phase 3: Intervention evaluation (Step 6 of IM) Employ a hybrid type 2 trial to: Evaluate the effectiveness of the intervention using a pilot RCT with two parallel arms; Evaluate implementation integrity (fidelity) and determinants of implementation. Methods The study has been approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University (reference number 2019-KY-52). Study setting All study phases are (to be) conducted in the First Affiliated Hospital of Zhengzhou University in the Henan province in China. Henan is one of the biggest provinces of China, and it accounts for 9% of the rural Chinese population. An estimated 16.4% (12 million) of adults suffer from CKD in rural areas in Henan [30]. The Department of Nephrology of the First Affiliated Hospital of Zhengzhou University has five sub-units with approximately 276 beds; more than 60,000 CKD patients visit the Outpatient Clinic of Department of Nephrology each year. Overview of Study Design An overview of the study flow following the six steps of IM is displayed in Table 1. Phase 1 Aim Preliminary evidence suggests that both patients’ and care providers’ needs, beliefs (i.e., an idea or principle judged to be true) and perceptions (i.e., the organized cognitive representations that individuals have about a subject) of disease (self-management) can influence their display of health behaviors and uptake of (self-management) interventions [31-34]. Therefore, following step 1 of IM, we will first conduct a needs assessment and examine the needs, beliefs, perceptions of CKD patients and care providers towards disease (self-management) and the use of eHealth interventions. Design Intervention monitoring group First, a multi-disciplinary intervention monitoring group including both Dutch and Chinese experts will be established. This group will consist of five members: two researchers, one nephrologist, and two experts in chronic disease care. This expert group has ample experience with CKD care and the implementation of (eHealth) self-management interventions. The intervention monitoring group will meet monthly throughout all IM steps to discuss progress and the execution of major deliverables such as the needs assessment (e.g. program goals), intervention development (e.g. intervention content, delivery strategies), and evaluation planning (e.g. inclusion, outcome choice, analysis). Literature review A scoping literature review will be conducted to identify relevant evidence on CKD patients’ and care providers’ needs toward disease management. The search strategy is already developed in collaboration with a certified librarian (see Additional file 2). Mixed-method study We will conduct a mixed-method study to gain insight into the needs, beliefs, perceptions of CKD patients, and care providers towards disease (self-management) and the use of eHealth (self-management) interventions. This study will include face to face interviews, focus group discussions, observations, and survey research. Methods will build on an adapted version of the theoretical framework on beliefs and perceptions towards chronic lung disease used in FRESH AIR (Brakema et al., submitted). This adapted framework combines the Health Belief Model [35] and the Theory of Planned Behavior [36] and focuses on individuals’ beliefs and perceptions as well as the sociocultural context in which the individual resides (see Fig. 1). We will explore CKD patients’ and care providers’: (1) beliefs and perceptions towards CKD and disease self-management, (2) needs towards CKD self-management, and (3) needs, beliefs, perceptions towards the use of eHealth interventions in disease self-management. The survey will consist of three validated measures: (1) ‘The Brief Illness Perception Questionnaire’ (BIPQ) [37], (2) ‘Chronic Kidney Disease Self-management instrument’ (CKD-SM) [38], and (3) ‘Chinese eHealth Literacy Scale’ (C-eHEALS) [39]. For the qualitative part, following principles of “purposive and convenience sampling” [40], the inclusion of participants will be based on opportunity, willingness to participate, and creation of diversity (e.g., age, gender) in our sample. We will also use snowball sampling [41], in which participants will be asked if they know any other individuals who could participate in the study. As there are no defined rules for calculating sample size in qualitative studies, data collection will continue until no new themes are identified from the data. For the quantitative part, as a rule of thumb, the sample size should be 5-10 times the number of items in the questionnaires [42]. Therefore, our aim is to recruit at least 230 patients. Eligibility criteria are detailed in Table 2. The methods to be used differ between care providers and patients following the relevant group- and context characteristics (see details in Table 3). For instance, focus groups cannot be held with care providers as they (1) cannot be of duty all at the same time, and (2) work with a tight schedule, and finding a time slot that suits all care providers is very difficult. Moreover, we feel that CKD patients would be comfortable discussing their needs towards eHealth self-management interventions in a focus group setting, but not their needs and beliefs towards their disease in general. Hence, we will plan to discuss this topic in face-to-face interviews. More details on the methods use and relevant research materials used are presented in Additional file 3. Phase 2 Aim Following step 2-5 of IM, we aim to tailor the core interventions components of the ‘Medical Dashboard’ self-management intervention to the Chinese context following the results of the needs assessment performed in Phase I. Design All the IM concepts used in the steps below are operationalized and further detailed in Table 4 and Figure 2. Step 2: Preparing matrices of change objectives First, we will formulate program outcomes [29] on all levels as defined in the socio-ecological model [43]. This model will help us to understand the complex interplay between individual, interpersonal, community, and societal outcomes. Second, we will subdivide program outcomes into performance objectives [29]. Third, as each performance objective can only be reached if matching behavioral determinants are addressed, we will break each performance objective down into key underlying determinants [29]. We will use the Theoretical Domains Framework (TDF) to support the identification and selection of relevant determinants of behavior [44]. Two researchers will independently identify the determinants, and discrepancies will be resolved through discussions. Also, the intervention monitoring group will evaluate the determinants selected based on relevance and changeability, using the four possible consensus-based recommendation levels proposed by Michie et al.[44]. Finally, based on the determinants identified, we will specify change objectives [29]. Step 3: Selecting theory-informed intervention methods and practical strategies We will first review the literature and identify relevant theoretical methods that can potentially induce a change in the determinants identified in step 2 [29]. Second, we will match the selected methods with specific change objectives. Third, the selected methods will be translated into practical strategies to target each determinant. Finally, the intervention monitoring group will rank the practical strategies per method [44] and ensure that these methods and practical strategies match with the program goals. Step 4: Develop a tailored ‘Medical Dashboard’ based intervention (plan) First, we will review the results of the needs assessment, the initial program’s logic model of change, and discuss intervention objectives, theoretical methods, and practical strategies for each level (e.g., individual, organization) specified in step 1-3. Second, the intervention monitoring group will have a meeting to amend, and if necessary, reconstruct the core components of Medical Dashboard to tailor the intervention. Also, the intervention monitoring group will create a plan for developing and testing the new version of the Medical Dashboard. Third, we will recruit five care providers and five patients to discuss the acceptability and feasibility of the intervention plan (member-check). To this end, we will use the ‘think aloud’ method [45], in which care providers and patients can speak aloud any words in their mind as they read through parts of the intervention plan. The think-aloud research method has been demonstrated to provide valid data on participant thinking and was successfully used in other intervention development studies [46, 47]. Based on the results obtained, further modifications will be made, resulting in a pre-tested version of the intervention plan ready for implementation in practice. The description of the intervention plan will follow the Template for Intervention Description and Replication [48]. Step 5: Develop an adoption and implementation plan The goal of this step is to write a detailed adoption and implementation plan, containing relevant strategies to optimize intervention delivery and implementation (fidelity). First, we will discuss results obtained from step 1-4 and inventory local resources (e.g., connections with primary care clinics) that may facilitate intervention implementation. Second, based on all results obtained from previous steps and our previous systematic review [21], the intervention monitoring group will have a meeting to pragmatically identify potential adopters and implementers. Also, this group will demonstrate program use outcomes, performance objectives and related determinants of implementation. Third, the intervention monitoring group will design the implementation plan following Figure 3 [49] based on Expert Recommendations for Implementing Change list of strategies [50]. Then, we will use the ‘think aloud’ method to obtain feedback from CKD patients and care providers on the implementation plan. Finally, the adoption and implementation plan will be finalized with further modifications. Phase 3 Aim Following step 6 of IM, we will establish an intervention evaluation plan. Our evaluation will follow a hybrid type 2 trial design, comprising of (1) a pilot RCT with two parallel arms to study effectiveness, and (2) a process evaluation to evaluate implementation integrity (fidelity) and determinants of implementation. Design This study will be a 9-month, two-arm, hybrid type 2 trial [51]. The trial design and corresponding study elements are detailed in Figure 4. The Standard Protocol Items: Recommendations for Interventional Trials 2013 Statement is used to report the pilot RCT protocol [52] (see Additional file 4), and the Standards for Reporting Implementation Studies will be followed for reporting the implementation study [53]. Intervention CKD patients in the comparison group will receive usual care consisting of personalized in- and outpatient treatment based on symptoms experienced and disease severity, as outlined in the Kidney Disease Improving Global Outcomes [6]. CKD patients in the intervention group will receive the usual care plus the culturally tailored ‘Medical Dashboard’ based self-management intervention for nine months. Before the start of the intervention, CKD patients and care providers will receive a face-to-face training session on the use of Medical Dashboard. To avoid contamination, Medical Dashboard will only be made accessible for participants in the intervention group via a secure password-protected registration process. Study population, recruitment & randomization Effectiveness; Pilot RCT CKD patients will be recruited from the First Affiliated Hospital of Zhengzhou University. Recruitment strategies, inclusion, and exclusion criteria are identical to those in phase 1 (see Table 2 and Additional file 3). In pilot studies, Sim and Lewis [54] recommend 55 or more patients in total. Thus, we aim to recruit 60 patients in total for randomization in our study. We summarize the participant flow through the study in Figure 5. The outcomes for effectiveness are presented in Table 5. A biostatistician blind to the study conditions will complete the random allocation sequence using a computer random number generator, allocating equal numbers of patients in the intervention (group 1) and comparison group (group 2). The care providers delivering the intervention cannot be blind to the intervention, but will not collect data or analyze outcomes. Research assistants blind to group membership will perform all face to face assessments and will not be involved in intervention delivery. Those conducting statistical analyses will be blind to group allocation until the evaluation is completed. Implementation study CKD patients, as well as care providers in the intervention group, will participate in the process evaluation to evaluate implementation integrity (fidelity) and determinants of implementation. Implementation outcomes on the patient level as well as care provider level will be evaluated, see the further paragraph about details of outcomes of implementation. All CKD patients in the intervention group will be invited to complete the survey. Also, following principles of “purposive and convenience sampling”, CKD patients and care providers in the intervention group will be invited and interviewed either face to face or by telephone for the process evaluation. A research assistant who will not involve in the pilot RCT study will collect data within process evaluation. Outcomes measures & data collection Outcomes for the pilot RCT evaluating the effectiveness We plan to evaluate: patients’ physical outcomes including biomedical measures, patients’ lifestyle and psychosocial functioning including self-efficacy, perceptions about CKD, quality of life, anxiety and depression status, hospital admission, health care utilization, and cost-benefit A trained research assistant will conduct data collection, and the intervention monitoring group will supervise the data collection process. We will invite participants in both the intervention and comparison group to visit the Department of Nephrology at the First Affiliated Hospital of Zhengzhou University for data collection at baseline (T0), three months (T1), six months (T2) and nine months (T3) post-randomization. At baseline, we will collect demographic data, including age, race, income, education, marital status, work type of participants. To avoid dropping out of participants, if participants cannot come to the hospital, data will then be collected via telephone interview. Table 5 provides details on the proposed outcome measures and timing of the measures. The operationalization of outcomes and descriptions of the measurement tools used are detailed in Additional file 5. Outcomes for implementation integrity (fidelity), and determinants of implementation The process evaluation will be based on the RE-AIM framework [55]. The RE-AIM model is used to comprehensively measure the public health impact of research conducted in real-world settings [56]. Four dimensions (with the Effectiveness domain being applicable above)—Reach (refers to the proportion of CKD patients reached by our program) , Adoption (refers to the proportion of participants who use our intervention) , Implementation (refer to completion as well as fidelity to the protocol) , and Maintenance will be used to evaluate the implementation only in the intervention group. We will collect the implementation outcome measurements throughout the 9-month trial. The outcome measures for each dimension of the RE-AIM model are as described in Table 6. We will use the Measurement Instrument for Determinants of Innovations questionnaire [57, 58] to evaluate the determinants of implementation. Also, individual interviews with stakeholders (e.g. patients, care providers) will be conducted to learn more about the usability and feasibility of Medical Dashboard, its potential for wide-scale implementation, and barriers and facilitators to implementation. We will categorize the determinants identified from this mixed-method study according to Fleuren Framework [59]. Data Analysis Qualitative data analysis A Framework Method [69] will be used to guide our qualitative analysis. We will structure the qualitative data in a matrix output formed by rows (cases), columns (codes), and ‘cells’ (summarized data). We will follow the consolidated criteria for reporting qualitative research to ensure quality and validity. Stage A: Transcribing : All audio-taped interviews will be anonymized and transcribed verbatim in Chinese. Long pauses and interruptions (relevant to the study subject) will be noted within the text. Additionally, all participants’ names will be replaced by an ID number. Any names mentioned during the interview will not be transcribed. One researcher will perform transcription, and another will check them to ensure content accuracy. Stage B: Familiarization : Two researchers will independently read all transcriptions and make contextual/reflective notes to become familiar with the whole data set. Stage C: development of an analytical framework& coding : Atlas.ti for Windows version 7.5.18 (Scientific Software development, Berlin) will be used to analyze our data. Our study includes four qualitative research parts. These are research into the (1) needs, beliefs, perceptions toward CKD and self-management (phase 1); (2) needs, beliefs, perceptions toward eHealth self-management interventions in CKD (phase 1); (3) the acceptability and usability of intervention components (phase 3); (4) determinants of implementation of eHealth self-management interventions (phase 3). Therefore, based on prior literature in which specific theoretical frameworks were used for similar research questions [70-74], we will develop four distinct initial coding trees. For the first and second research questions, we will develop two coding trees based on the adapted version of the theoretical framework of Brakema et al., (submitted) and the TDF [75]. The Technology Acceptance Model [76] will be used to develop the coding tree for evaluating the acceptability and usability of intervention components. Also, the Fleuren framework [59] will be used to develop the coding tree for determinants of implementation of eHealth self-management interventions. The second researcher and third researcher will check the coding tree developed and make amendments if necessary. One researcher will then independently code two or three transcripts using the coding tree, and add new codes if the textual abstracts identified do not fit with the existing set of codes. Then, this researcher will meet with the second researcher and discuss the newly added codes. New codes will be added into the coding tree, and if needed, related codes will be grouped into categories. Thus, the process will be repeated until no new codes arise. The final coding tree will be checked and approved by the second researcher and the third researcher. This coding tree will include codes and categories; all codes and categories will be operationalized, and relevant examples will be provided. The finalized coding tree will then be applied to each transcript. One researcher will go through each transcript, highlight the meaningful textual abstracts, and assign the appropriate code from the final coding tree. Then, all codes assigned will be verified by the second researcher. All coding differences will be discussed until consensus is reached. Stage D: Charting data into the framework matrix : Data will be charted into matrices per research question identified by two researchers using Microsoft Excel 2010. The matrix will comprise of one row per participant and one column per code. Interesting or illustrative quotations will be added to the matrices. Stage E: Interpreting the data : Overarching themes will be generated from codes derived from the data set by reviewing the matrix and making connections within and between participants and codes. Relations, connections, and causality will be further explored and interpreted, and conclusions will be drawn. As for data derived from observations, all checklists will be digitalized and transported to Microsoft Excel 2010. Also, all written filed notes will be digitalized and will be taken into account to triangulate data collected from other methods. For instance, observation data obtained in phase 3 will support the analysis of implementation integrity (fidelity). Quantitative data analysis All quantitative analyses will be performed using SPSS version 23 (IBM, Armonk, NY, USA). We will enter the quantitative data into Microsoft Excel 2010 and calculate descriptive statistics such as the mean, standard deviation, median, and range of linear variables, and frequencies and percentages of categorical variables. To gain insight into the needs, beliefs, perceptions of CKD patients towards disease (self-management) and the use of eHealth interventions in phase 1, we will use the descriptive statistics to describe CKD patients’ demographic characteristics, BIPQ scores, CKD-SM score, and C-eHEALS scores. Also, we will conduct secondary analysis using (1) independent t -tests for normally distributed continuous variables, (2) Mann–Whitney U-tests for nonnormally distributed variables and (3) Chi-squared or Fisher’s exact tests for categorical variables to compare the difference between certain types of different groups of CKD patients (e.g., age, gender, disease stage) and BIPQ scores, CKD SM score and C-eHEALS scores. P -values <0.05 and odds ratios with a 95% confidence interval excluding one will be considered statistically significant. In phase 3, one of the primary hypothesis is that the intervention group, when compared to the comparison group, will demonstrate (statistically) significant improvement in self-management behavior at 3, 6 and 9 months post-randomization. Secondary hypotheses are that the intervention group when compared to patients in the comparison group, will demonstrate (statistically) significant improvement in biomedical status, self-efficacy, illness perception, mental health, quality of life, hospital admission, healthcare utilization and cost-benefit analysis at the timing of measurement. All primary statistical analyses will be conducted using intent-to-treat methods. The primary goal of statistical analyses is to examine and compare trends over time in the primary outcome. We will replicate this analytic approach for other secondary outcomes; secondary analyses will examine trends over time for biomedical status, self-efficacy, illness perception, mental health, quality of life, hospital admission, healthcare utilization, and cost-benefit analysis. We will use longitudinal, mixed-model analyses to test the hypotheses. Exploratory analyses will assess the impact of the intervention on primary and secondary outcomes for patients. Mixed analysis of qualitative and quantitative data by triangulation We will conduct a combined analysis by merging the quantitative and qualitative results after separate analyses have been carried out [77]. In phase 1, the quantitative results will triangulate the qualitative results of the perception of disease, self-management behavior, and eHealth literacy. To this end, we will develop a thematic matrix [78] that includes participants’ characteristics and data derived from surveys and emerging themes from our qualitative results to summarize CKD patients’ illness perception, self-management behavior, and eHealth literacy. In phase 3, we will use the results collected from the qualitative interviews to help interpret the quantitative results from the pilot trial. Qualitative results will, therefore, be used to expand upon the results of this trial to understand the implementation process as experienced by participants. For instance, the questionnaire of determinants of implementation will be matched with the qualitative research on determinants of implementation. Discussion Some research has shown that eHealth based self-management interventions in CKD can help to improve health-related outcomes. However, evidence on the effectiveness of CKD eHealth based self-management interventions is still inconclusive [ 21 ]. Thus, our study will gain insights into the development of theoretically based, and target population tailored implementation of eHealth based self-management interventions to improve CKD care. Our study will add knowledge on the implementation research of eHealth self-management interventions in CKD care, with fitting with the needs and priorities expressed by health care professionals and patients. Also, this study will add evidence of the effectiveness of eHealth based self-management interventions on CKD health outcomes. There are some strengths to our research. First, we will use an innovative hybrid design to concurrently study the effectiveness and implementation of the tailored ‘Medical Dashboard’ self-management intervention in CKD care. The hybrid designs can test the implementation process by looking inside the so-called “black box” to see what happens in the intervention implementation and how that could affect intervention outcomes [ 79 , 80 ]. Therefore, hybrid designs can provide the potential to speed the translation of intervention findings into routine practice by optimizing the implementation process [ 51 ]. In addition, the triangulation of both quantitative and qualitative results allows researchers to understand the implementation process and intervention effectiveness from multiple perspectives, different types of causal pathways, and multiple types of outcome, thereby strengthening the validity of intervention effects [ 77 , 79 , 81 ]. Second, the robust theory will be used to guide the process of intervention development. The IM method ensures a theory-based approach from the recognition of a need or problem to the identification of a solution and intervention testing. To translate interventions into different contexts (e.g., health care system, population), it is essential to optimize the intervention fit with the needs and priorities expressed by the target population. IM was successfully applied in the development of self-management interventions for osteoarthritis and chronic low back pain [ 72 ], and children with CKD [ 82 , 83 ]. Also, the RE-AIM framework as utilized in this study provides systematic guidance on how to evaluate the intervention effect on the process and outcome level. A major limitation of this study is that we only perform the study within one hospital in China. Hence, findings may not be immediately generalizable to other health system contexts in China where the access to eHealth technology is (more) limited. Also, the transferability of developed Medical Dashboard self-management intervention to routine clinical practice in primary care may be limited and needs further exploration. In conclusion, our study will result in the delivery of a culturally tailored, standardized eHealth self-management intervention for CKD patients in China, which has the potential to optimize patients’ self-management skills and improve health status and quality of life. Also, this study can serve as proof of concept for the use of IM and a hybrid type 2 trial design to evaluate the implementation and effectiveness of eHealth self-management interventions. Moreover, it will inform future research on the tailoring and translation of evidence-based eHealth self-management interventions in various contexts. Abbreviations CKD: chronic kidney disease; eGFR: estimated glomerular filtration rate; eHealth: electronic health; BP: blood pressure; LUMC: Leiden University Medical Center; RCT: randomized controlled trial; IM: Intervention Mapping; BIPQ: Brief Illness Perception Questionnaire; CKD-SM: Chronic Kidney Disease Self-management instrument; C-eHEALS: Chinese eHealth Literacy Scale; TDF: Theoretical Domains Framework; CKD-SE: Chronic Kidney Disease Self-efficacy; KDQOL-36: The Kidney Disease Quality of Life 36-item short-form survey; HADS: Hospital Anxiety and Depression Scale Declarations Ethics approval and consent to participate The study has been approved by the Institutional Review Boards of the First Affiliated Hospital of Zhengzhou University, reference number (2019-KY-52). Consent for publication Not applicable. Availability of data and materials Not applicable. Competing interests The authors declare that they have no competing interests. Funding This study is funded by the China Scholarship Council. Authors’ contributions HS led the conception and design of this study and is the main contributor in writing this manuscript. RK, PB, XS, WW, TZ, ZL, XL and NC contributed to the conception and design of the study and editing of this manuscript. All authors read and approved the final manuscript. Acknowledgements Not applicable. Authors’ information 1 Department of Public Health and Primary Care, Leiden University Medical Centre, Leiden, Netherlands. 2 Department of Nursing, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China. 3 Department of Obstetrics and Gynaecology, Erasmus Medical Center, Rotterdam, Netherlands. 4 Department of Nephrology, Leiden University Medical Centre, Leiden, Netherlands. 5 School of Nursing and Health, Zhengzhou University, Zhengzhou, China. 6 Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China. References Jha V, Modi GK. Getting to know the enemy better-the global burden of chronic kidney disease. Kidney Int. 2018;94:462-4. Hill NR, Fatoba ST, Oke JL, Hirst JA, O'Callaghan CA, Lasserson DS, et al. Global Prevalence of Chronic Kidney Disease - A Systematic Review and Meta-Analysis. Plos One. 2016; doi: 10.1371/journal.pone.0158765. Nugent RA, Fathima SF, Feigl AB, Chyung D. 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(DOCX 22KB) Tables Table 1 Overview of study phases Phase IM steps Activities I Step 1 Conduct needs assessment · Establish an intervention monitoring group · Perform a systematic literature review · Conduct a mixed-methods study into needs, beliefs & perceptions of chronic kidney disease patients and care providers toward chronic kidney disease (self-management) and the use of eHealth (self-management) interventions II Step 2 Identify outcomes, performance objectives, and determinants · Formulate program outcomes · Specify performance objectives · Specify determinants of change · Map the performance objectives to the determinants and create a matrix of change objectives Step 3 Select theory-based methods and practical strategies · Review potentially relevant theoretical methods · Match each determinant to the relevant method(s) · Translate methods into practical strategies to target each determinant · Monitoring group reaches consensus on methods and practical strategies Step 4 Develop a tailored ‘Medical Dashboard’ based intervention (plan) · Develop an intervention plan by tailoring the core components of the Dutch Medical Dashboard to the Chinese context · Member check with the target population Step 5 Develop an adoption- and implementation plan · Identify potential adopters and implementers · Specify program use outcomes and performance objectives · Specify determinants of change · Map the performance objectives to the determinants and create a matrix of change objectives · Design a plan for adoption and implementation · Member check with the target population III Step 6 Develop an intervention evaluation plan · Specify the two-arm, hybrid 2 trial design and: -Develop the effectiveness evaluation plan -Develop the implementation evaluation plan Table 2 Eligibility criteria for chronic kidney disease patients and care providers Category Participant eligibility criteria Inclusion criteria Patients: (1) aged over 18 years old; (2) diagnosis of chronic kidney disease; (3) Chinese speaking. · Health care providers who work in the Department of Nephrology Exclusion criteria · Individuals unable to participate due to physical or mental disabilities. · Individuals unable to write or read. Table 3 Field methods used for topics Method Care providers Patients Sampling Beliefs, perceptions, toward chronic kidney disease and self-management Needs toward chronic kidney disease self-management Needs, beliefs, perceptions toward eHealth self-management interventions Beliefs, perceptions toward chronic kidney disease and self-management Needs toward chronic kidney disease self-management Needs, beliefs, perceptions toward eHealth self-management interventions Face to face interview X X X X X X Purposive, Convenience Focus group discussion X Purposive, Convenience Observation X X X X X X Purposive, Convenience Survey X X X Randomly Table 4 The concepts from Intervention Mapping step 2-5 Concept of Intervention Mapping Definition in Bartholomew LK et al. [29] Step 2 Program outcome Desired changes in the behavior and the environmental conditions Performance objective The required actions to accomplish the change in the behavioral and environmental outcomes Determinant Factors that are associated with the performance of behavior Change objective Specific goals stating what should change at the determinants for program outcomes in different level Step 3 Theoretical method General technique or process for influencing changes in the determinants of behaviors and environmental conditions Practical strategy A specific technique for the practical use of theoretical methods in ways that fit with the target group and the context in which the intervention will be conducted Step 4 Intervention plan A plan detailing intervention scope and sequence including delivery channels, themes, and list of the intervention materials needed Step 5 Implementation plan A plan detailing how intervention adoption and implementation can be supported and maintained over time. Table 5 Effectiveness outcomes and timing of measurements Outcome Outcome Indicators Measures Tools Sources Timing of measures T0 a T1 b T2 c T3 d Primary Outcome Self-management behavior Survey Chronic Kidney Disease Self-Management instrument [60, 61] Patient X X X X Secondary outcome Biomedical status Clinical records Blood pressure, Bodyweight, Glomerular filtration rate, Serum albumin, Length, Serum calcium, Serum phosphate, Serum hemoglobin, Sodium and protein in 24h urine, albumin/creatinine ratio, Cholesterol, High-density lipoprotein, Low-density lipoprotein, Triglycerides, Hemoglobin A1C, Complications Patient X X X X Self-efficacy Survey Chronic Kidney Disease Self-efficacy scale [61, 62] Patient X X X X Illness perception Survey Brief Illness Perception Questionnaire [63, 64] Patient X X Quality of life Survey The Kidney Disease Quality of Life 36-item short-form survey [65-67] Patient X X Mental health Survey Hospital Anxiety and Depression Scale [68] Patient X X X Hospital admission Survey The time to first acute hospital admission with an exacerbation of CKD or death due to CKD within nine months after randomization Patient X Healthcare utilization Survey Number of hospitalizations and emergency room visits of patients, primary and secondary care visits Patient X X Cost-benefit analysis Records All costs delivering the interventions (e.g., materials used in the interventions) Program, intervention group X X Records Medical cost (e.g., cost of treatment, hospitalization rates minored as monetary terms) Patient X X a At baseline b Three months post-randomization c Six months post-randomization d Nine months post-randomization Table 6 Implementation outcomes (intervention group only) Outcome Outcome Indicators Measures Tools Sources Reach Number of patients (eligible, excluded, enrolled) Records The proportion of patients eligible to use our intervention program, excluded, invited, and enrolled Patient Number of health care providers (eligible, excluded, enrolled) Records The proportion of care professionals eligible to use our intervention program, excluded, invited, and enrolled Care provider Characteristics of participating patients Records Comparing participating patients to the target population on key clinical characteristics (e.g., disease stage) Patient Qualitative assessment-reach Interview The barriers/facilitators to study participation Patient Adoption Characteristics of participating care providers Records Comparing participating care providers to the target population on key characteristics (e.g., work type) Care provider Use of program Records Frequency of materials or medical dashboard used Patient, care provider Qualitative assessment-adoption Interview The appropriateness, comfort, relative advantage, and credibility of the intervention Patient, care provider Implementation Implementation completion Interview, observation The implementation completion tasks will be made as a checklist, and the completion of the task and the length of time to finish will be checked. Patient, care provider Acceptability and feasibility of the intervention Interview Experiences and perceptions of the intervention Patients, care provider, research assistant Maintenance Follow up on the use of medical dashboard Records The use of intervention to assess long-term maintenance Records Qualitative assessment-maintenance Interview Perceptions of the integration of intervention in health facilities Patient, care provider Supplementary Files Additionalfile5.docx Additionalfile1.docx Additionalfile2.docx Additionalfile4.docx Additionalfile3.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-13310","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Study protocol","associatedPublications":[],"authors":[{"id":331982,"identity":"30217ecf-998d-4d87-bbee-8305f891d0bc","order_by":1,"name":"Hongxia Shen","email":"","orcid":"","institution":"Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, Netherlands; Department of Nursing, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China","correspondingAuthor":false,"prefix":"","firstName":"Hongxia","middleName":"","lastName":"Shen","suffix":""},{"id":331983,"identity":"e7939a4c-3fa5-48bc-a6c5-03e328246ba7","order_by":2,"name":"Rianne van der Kleij","email":"","orcid":"","institution":"Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, Netherlands; Department of Obstetrics and Gynaecology, Erasmus Medical Center, Rotterdam, Netherlands","correspondingAuthor":false,"prefix":"","firstName":"Rianne","middleName":"van der","lastName":"Kleij","suffix":""},{"id":331984,"identity":"8b133b34-e35c-469d-92dd-a6b66caf4c7e","order_by":3,"name":"Paul JM van der Boog","email":"","orcid":"","institution":"Department of Nephrology, Leiden University Medical Center, Leiden, Netherlands","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"JM van der","lastName":"Boog","suffix":""},{"id":331985,"identity":"859c56e3-fec6-4986-b4d4-6357e16f45e0","order_by":4,"name":"Xiaoyue Song","email":"","orcid":"","institution":"Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, Netherlands; School of Nursing and Health, Zhengzhou University, Zhengzhou, China","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyue","middleName":"","lastName":"Song","suffix":""},{"id":331986,"identity":"d462add5-8050-4eec-ac0f-f90cf7dc2423","order_by":5,"name":"Wenjiao Wang","email":"","orcid":"","institution":"Department of Nursing, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China","correspondingAuthor":false,"prefix":"","firstName":"Wenjiao","middleName":"","lastName":"Wang","suffix":""},{"id":331987,"identity":"e160044a-01d0-4e8e-b4aa-5a3085e5da8b","order_by":6,"name":"Tongtong Zhang","email":"","orcid":"","institution":"Department of Nursing, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China","correspondingAuthor":false,"prefix":"","firstName":"Tongtong","middleName":"","lastName":"Zhang","suffix":""},{"id":331988,"identity":"f2b743ed-a37e-4a36-8dc4-46373558755f","order_by":7,"name":"Zhengyan Li","email":"","orcid":"","institution":"Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China","correspondingAuthor":false,"prefix":"","firstName":"Zhengyan","middleName":"","lastName":"Li","suffix":""},{"id":331989,"identity":"14aaef71-0011-4ddb-b3e4-0d498eaa834e","order_by":8,"name":"Xiaoping Lou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYBACPhCRAMRsDAyMDz42gLiMjQfwaWFD0sJsOLOBQQKopYGwFhhbmBeshYEBvxb2HjOJBzU2eXzS7deYbXfY1Om2HwbaUmMTjVMLzxljg4RjacVsMmfKHueeSZMwO5MI1HIsLbcBlxaJHMMHCWyHE9skctKNc9sOS5gdAGphbDiMT4vBgYR/YC1p0pYgLecfEtRi+CCxDaQl/Zg0I0jLDUK28BwrNkjsA/pFIofZsLctTXLbDaAtCXj8ws/evE3yxzebPPkZ6Q8f/Gyz4Tc7D2R8qLHBqQUGEhgYeAxQuAQBUA37AyLUjYJRMApGwUgEAHfEXpYuzUqWAAAAAElFTkSuQmCC","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Xiaoping","middleName":"","lastName":"Lou","suffix":""},{"id":331990,"identity":"ccdd521a-8aae-4480-a36d-2e771c03ff87","order_by":9,"name":"Niels Chavannes","email":"","orcid":"","institution":"Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, Netherlands","correspondingAuthor":false,"prefix":"","firstName":"Niels","middleName":"","lastName":"Chavannes","suffix":""}],"badges":[],"createdAt":"2020-02-04 16:20:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.2.22736/v1","doiUrl":"https://doi.org/10.21203/rs.2.22736/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":458792,"identity":"f3d615dc-1db1-4b7d-9100-e300552387aa","added_by":"auto","created_at":"2020-02-06 17:36:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":79904,"visible":true,"origin":"","legend":"Adapted version of the theoretical framework of Brakema et al (submitted). A combination of concepts of the Health Beliefs Model (green) and the Theory of Planned Behavior (blue).","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/5eb3759a-cfc1-44b9-8c6e-d6dab14c3f9d/v1/Figure 1.png"},{"id":458793,"identity":"9a062de1-b880-450b-ba7b-69635f9548c6","added_by":"auto","created_at":"2020-02-06 17:36:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":124974,"visible":true,"origin":"","legend":"Methods and examples of the possible output of Intervention Mapping step 2-5. Step 2 (blue) , step 3(red), step 4(green), step 5(purple).","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/5eb3759a-cfc1-44b9-8c6e-d6dab14c3f9d/v1/Figure 2.png"},{"id":458796,"identity":"e3ba3b90-a264-4f02-823b-efd3c06e9c39","added_by":"auto","created_at":"2020-02-06 17:36:24","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":148663,"visible":true,"origin":"","legend":"Guidance for specifying implementation strategies of Proctor EK et al. [49].","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/5eb3759a-cfc1-44b9-8c6e-d6dab14c3f9d/v1/Figure 3.jpg"},{"id":458797,"identity":"ca0ba347-2c58-44a5-986e-56dda781765c","added_by":"auto","created_at":"2020-02-06 17:36:24","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":47188,"visible":true,"origin":"","legend":"Study schema","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/5eb3759a-cfc1-44b9-8c6e-d6dab14c3f9d/v1/Figure 4.png"},{"id":458799,"identity":"afe16047-1b31-4da0-90a8-c532a5b4e84e","added_by":"auto","created_at":"2020-02-06 17:36:24","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":59436,"visible":true,"origin":"","legend":"CONSORT flow diagram for our trial","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/5eb3759a-cfc1-44b9-8c6e-d6dab14c3f9d/v1/Figure 5.png"},{"id":13489103,"identity":"3da6ec99-3b1c-420d-8c5d-7e40a07ea9c8","added_by":"auto","created_at":"2021-09-16 22:17:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1165015,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-13310/v1/7920662b-9c87-4407-8dae-c2a9805cd27a.pdf"},{"id":458798,"identity":"e0b5d5a5-2c89-486b-8a3c-85a5d4229165","added_by":"auto","created_at":"2020-02-06 17:36:24","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":21956,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile5.docx","url":"https://assets-eu.researchsquare.com/files/5eb3759a-cfc1-44b9-8c6e-d6dab14c3f9d/v1/Additional file 5.docx"},{"id":458791,"identity":"802721fa-5537-45da-a373-9115b44e65f6","added_by":"auto","created_at":"2020-02-06 17:36:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":23261,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/5eb3759a-cfc1-44b9-8c6e-d6dab14c3f9d/v1/Additional file 1.docx"},{"id":458790,"identity":"2f469bac-afa0-45b5-befa-cb93c879c7a7","added_by":"auto","created_at":"2020-02-06 17:36:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":25184,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile2.docx","url":"https://assets-eu.researchsquare.com/files/5eb3759a-cfc1-44b9-8c6e-d6dab14c3f9d/v1/Additional file 2.docx"},{"id":458794,"identity":"2ffc59aa-c6da-4be6-be4b-9b9efe686ddf","added_by":"auto","created_at":"2020-02-06 17:36:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":47215,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile4.docx","url":"https://assets-eu.researchsquare.com/files/5eb3759a-cfc1-44b9-8c6e-d6dab14c3f9d/v1/Additional file 4.docx"},{"id":458795,"identity":"27f22c14-9476-4adc-b31f-d1a69b6a3f73","added_by":"auto","created_at":"2020-02-06 17:36:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":55639,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile3.docx","url":"https://assets-eu.researchsquare.com/files/5eb3759a-cfc1-44b9-8c6e-d6dab14c3f9d/v1/Additional file 3.docx"}],"financialInterests":"","formattedTitle":"Development and evaluation of an eHealth self-management intervention for chronic kidney disease patients in China: protocol for a mixed-method hybrid type 2 trial","fulltext":[{"header":"Contributions To The Literature","content":"\u003cul\u003e\n\u003cli\u003eKnowledge of the use of eHealth-based self-management interventions in China is still lacking. Our study will result in the delivery of a culturally tailored, standardized eHealth self-management intervention for CKD patients in China, which has the potential to optimize patients\u0026rsquo; self-management skills and improve health status and quality of life.\u003c/li\u003e\n\u003cli\u003eThis study will inform future research on the tailoring and translation of evidence-based eHealth self-management interventions in various contexts.\u003c/li\u003e\n\u003cli\u003eThis study can serve as proof of concept for the use of Intervention Mapping and a hybrid type 2 trial design to evaluate the implementation and effectiveness of eHealth self-management interventions.\u003c/li\u003e\n\u003c/ul\u003e\n"},{"header":"Background","content":"\u003cp\u003e\u003cem\u003ePrevalence and burden of chronic kidney disease \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Chronic kidney disease (CKD) poses a significant threat to public health [1-3]. Globally, more than 70 million individuals are affected by CKD [4]. In China, an estimated 10.8% (119.5\u0026thinsp;million) of adults suffer from CKD [5]. CKD is defined as abnormalities of kidney structure or function, present for more than three months, with severe implications for health [6]. CKD is chronic and follows five stages of functional decline based on the estimated glomerular filtration rate (eGFR) [6]. Numerous detrimental health outcomes are linked to CKD [7]. Also, CKD increases mortality risk and hospitalization rates, and negatively impacts the quality of life [7-9]. Additionally, health-related and societal costs of CKD are considerable and constitute a substantial economic burden [10-12].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSelf-Management and eHealth interventions for CKD\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Interventions that support disease self-management (further referred to as \u0026lsquo;self-management interventions\u0026rsquo;) can have a significant impact on the health and quality of life of patients suffering from chronic conditions in general [13], and CKD patients in specific [14-16]. Self-management support is often defined as \u0026ldquo;\u003cem\u003e[\u0026hellip;\u0026hellip;]\u003c/em\u003e\u003cem\u003e improving chronic illness outcomes consisting of patient-centered attributes (involving patients as partners; [\u0026hellip;\u0026hellip;]), provider attributes (possessing adequate knowledge, skills, attitudes in providing care), and organizational attributes (putting an organized system of care in place, having multidisciplinary team approach, using tangible and social support)\u003c/em\u003e\u0026rdquo; [17].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; In the last decade, the use of electronic health (eHealth) technology in self-management interventions has become more and more popular. EHealth technology can facilitate remote patient-provider communication and exchange of (health) data and has the potential to increase healthcare accessibility and efficiency [18]. EHealth-based self-management interventions have been shown to improve health-related outcomes, such as blood pressure (BP) control and medication adherence [19, 20], and found to be feasible and acceptable for CKD patients and care professionals [19]. Hence, the use of eHealth self-management interventions for CKD patients has become increasingly popular.\u0026nbsp; Knowledge of the implementation and effectivity of such interventions in China and other developing countries is, however, still lacking [21].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMedical dashboard\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Researchers from the Leiden University Medical Center (LUMC) developed \u0026lsquo;Medical Dashboard\u0026rsquo;, an eHealth intervention to help support and involve CKD patients in their disease self-management. This platform is used in the Outpatient Clinic Kidney Transplant of the LUMC since February 2016. Via Medical Dashboard, patients can monitor their health from home (e.g., BP, weight), and can exchange health data with their care professionals. Moreover, during consultations in the outpatient clinic, care professionals and patients can also use Medical Dashboard to set personal health goals such as BP control and nutrition management (e.g., energy). In a randomized controlled trial (RCT), the use of \u0026ldquo;Medical Dashboard\u0026rdquo; has been shown to improve patients\u0026rsquo; adherence to sodium restriction intake and BP control [14]. Also, patients reported being highly satisfied with the online disease management system used in the platform [22]. All core intervention components of \u0026lsquo;Medical dashboard\u0026rsquo; and their supporting evidence base are presented in Additional file 1.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOpportunities for eHealth interventions in China\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; There is significant support and momentum for the implementation of eHealth based self-management interventions in China. China had 731 million internet users (penetration rate 53%) and 1.3 billion mobile phone users (penetration rate of 90%) in 2016, and this number is still growing [23-26]. Furthermore, policymakers and care experts in China have recently launched the national health strategy \u0026lsquo;Healthy China 2030\u0026rsquo;. This strategy describes eHealth technology as an essential pillar to improve disease self-management as well as the accessibility and cost-effectiveness of care in rural areas. Moreover, it views eHealth technology as the preferred medium to reach one of the main goals: \u0026lsquo;\u003cem\u003eenable everyone to be involved in health, share health, and be responsible for health\u003c/em\u003e\u0026rsquo; [27, 28]. Also, the prevalence rate and severe adverse health outcomes of CKD have put it high on the public health agenda in China.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStudy aims and research methods\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; In conclusion, eHealth self-management interventions have the potential to fundamentally improve the quality of life and health outcomes of patients suffering from CKD in China. Therefore, we aim to tailor the evidence-based Dutch intervention \u0026lsquo;Medical Dashboard\u0026rsquo; to the Chinese context and evaluate its implementation process and effectiveness. To this end, we will use an intervention mapping (IM) approach comprising six steps: (1) a needs assessment, (2) preparation of change objectives matrices, (3) selection of theory-informed intervention methods and strategies, (4) development of a tailored \u0026lsquo;Medical Dashboard\u0026rsquo; based intervention plan, (5) development of an implementation - and (6) evaluation plan.\u003c/p\u003e\n\u003cp\u003eIn correspondence with the steps of IM [29], we aim to:\u0026nbsp;\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003e\u003cem\u003ePhase 1:\u003c/em\u003e\u003c/strong\u003e \u003cstrong\u003e\u003cem\u003eNeeds, beliefs and perceptions (Step 1 of IM)\u003c/em\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eExamine the needs, beliefs, perceptions of CKD patients and care providers towards disease self-management and eHealth interventions;\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003e\u003cem\u003ePhase 2: Intervention and implementation development \u0026amp; planning (Step 2-5 of IM)\u003c/em\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eTailor the core components of the \u0026lsquo;Medical Dashboard\u0026rsquo; self-management intervention for CKD patients to the Chinese context;\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003e\u003cem\u003ePhase 3: Intervention evaluation (Step 6 of IM) \u003c/em\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eEmploy a hybrid type 2 trial to:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eEvaluate the effectiveness of the intervention using a pilot RCT with two parallel arms;\u003c/li\u003e\n\u003cli\u003eEvaluate implementation integrity (fidelity) and determinants of implementation.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Methods","content":"\u003cp\u003eThe study has been approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University (reference number 2019-KY-52).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy setting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll study phases are (to be) conducted in the First Affiliated Hospital of Zhengzhou University in the Henan province in China. Henan is one of the biggest provinces of China, and it accounts for 9% of the rural Chinese population. An estimated 16.4% (12 million) of adults suffer from CKD in rural areas in Henan [30]. The Department of Nephrology of the First Affiliated Hospital of Zhengzhou University has five sub-units with approximately 276 beds; more than 60,000 CKD patients visit the Outpatient Clinic of Department of Nephrology each year.\u003c/p\u003e"},{"header":"Overview of Study Design","content":"\u003cp\u003eAn overview of the study flow following the six steps of IM is displayed in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhase 1 \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAim \u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePreliminary evidence suggests that both patients\u0026rsquo; and care providers\u0026rsquo; needs, beliefs (i.e., an idea or principle judged to be true) and perceptions (i.e., the organized cognitive representations that individuals have about a subject) of disease (self-management) can influence their display of health behaviors and uptake of (self-management) interventions [31-34]. Therefore, following step 1 of IM, we will first conduct a needs assessment and examine the needs, beliefs, perceptions of CKD patients and care providers towards disease (self-management) and the use of eHealth interventions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eDesign \u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntervention monitoring group \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, a multi-disciplinary intervention monitoring group including both Dutch and Chinese experts will be established. This group will consist of five members: two researchers, one nephrologist, and two experts in chronic disease care. This expert group has ample experience with CKD care and the implementation of (eHealth) self-management interventions. The intervention monitoring group will meet monthly throughout all IM steps to discuss progress and the execution of major deliverables such as the needs assessment (e.g. program goals), intervention development (e.g. intervention content, delivery strategies), and evaluation planning (e.g. inclusion, outcome choice, analysis).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLiterature review\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA scoping literature review will be conducted to identify relevant evidence on CKD patients\u0026rsquo; and care providers\u0026rsquo; needs toward disease management. The search strategy is already developed in collaboration with a certified librarian (see Additional file 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMixed-method study \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe will conduct a mixed-method study to gain insight into the needs, beliefs, perceptions of CKD patients, and care providers towards disease (self-management) and the use of eHealth (self-management) interventions. This study will include face to face interviews, focus group discussions, observations, and survey research. Methods will build on an adapted version of the theoretical framework on beliefs and perceptions towards chronic lung disease used in FRESH AIR (Brakema et al., submitted). This adapted framework combines the Health Belief Model [35] and the Theory of Planned Behavior [36] and focuses on individuals\u0026rsquo; beliefs and perceptions as well as the sociocultural context in which the individual resides (see Fig. 1).\u003c/p\u003e\n\u003cp\u003eWe will explore CKD patients\u0026rsquo; and care providers\u0026rsquo;: (1) beliefs and perceptions towards CKD and disease self-management, (2) needs towards CKD self-management, and (3) needs, beliefs, perceptions towards the use of eHealth interventions in disease self-management. The survey will consist of three validated measures: (1) \u0026lsquo;The Brief Illness Perception Questionnaire\u0026rsquo; (BIPQ) [37], (2) \u0026lsquo;Chronic Kidney Disease Self-management instrument\u0026rsquo; (CKD-SM) [38], and (3) \u0026lsquo;Chinese eHealth Literacy Scale\u0026rsquo; (C-eHEALS) [39].\u0026nbsp; For the qualitative part, following principles of \u0026ldquo;purposive and convenience sampling\u0026rdquo; [40], the inclusion of participants will be based on opportunity, willingness to participate, and creation of diversity (e.g., age, gender) in our sample. We will also use snowball sampling [41], in which participants will be asked if they know any other individuals who could participate in the study. As there are no defined rules for calculating sample size in qualitative studies, data collection will continue until no new themes are identified from the data. For the quantitative part, as a rule of thumb, the sample size should be 5-10 times the number of items in the questionnaires [42]. Therefore, our aim is to recruit at least 230 patients. Eligibility criteria are detailed in Table 2.\u003c/p\u003e\n\u003cp\u003eThe methods to be used differ between care providers and patients following the relevant group- and context characteristics (see details in Table 3). For instance, focus groups cannot be held with care providers as they (1) cannot be of duty all at the same time, and (2) work with a tight schedule, and finding a time slot that suits all care providers is very difficult. Moreover, we feel that CKD patients would be comfortable discussing their needs towards eHealth self-management interventions in a focus group setting, but not their needs and beliefs towards their disease in general. Hence, we will plan to discuss this topic in face-to-face interviews. More details on the methods use and relevant research materials used are presented in Additional file 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhase 2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAim\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing step 2-5 of IM, we aim to tailor the core interventions components of the \u0026lsquo;Medical Dashboard\u0026rsquo; self-management intervention to the Chinese context following the results of the needs assessment performed in Phase I.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eDesign\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the IM concepts used in the steps below are operationalized and further detailed in Table 4 and Figure 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 2: Preparing matrices of change objectives \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, we will formulate \u003cem\u003eprogram outcomes \u003c/em\u003e[29] on all levels as defined in the socio-ecological model [43]. This model will help us to understand the complex interplay between individual, interpersonal, community, and societal outcomes. Second, we will subdivide program outcomes into \u003cem\u003eperformance objectives \u003c/em\u003e[29]. Third, as each performance objective can only be reached if matching behavioral determinants are addressed, we will break each performance objective down into \u003cem\u003ekey underlying determinants\u003c/em\u003e [29]. We will use the Theoretical Domains Framework (TDF) to support the identification and selection of relevant determinants of behavior [44]. Two researchers will independently identify the determinants, and discrepancies will be resolved through discussions. Also, the intervention monitoring group will evaluate the determinants selected based on relevance and changeability, using the four possible consensus-based recommendation levels proposed by Michie et al.[44]. Finally, based on the determinants identified, we will specify \u003cem\u003echange objectives\u003c/em\u003e [29].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 3: Selecting theory-informed intervention methods and practical strategies \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe will first review the literature and identify relevant \u003cem\u003etheoretical methods\u003c/em\u003e that can potentially induce a change in the determinants identified in step 2 [29]. Second, we will match the selected methods with specific change objectives. Third, the selected methods will be translated into practical strategies to target each determinant. Finally, the intervention monitoring group will rank the practical strategies per method [44] and ensure that these methods and practical strategies match with the program goals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 4: Develop a tailored \u0026lsquo;Medical Dashboard\u0026rsquo; based intervention (plan)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, we will review the results of the needs assessment, the initial program\u0026rsquo;s logic model of change, and discuss intervention objectives, theoretical methods, and practical strategies for each level (e.g., individual, organization) specified in step 1-3. Second, the intervention monitoring group will have a meeting to amend, and if necessary, reconstruct the core components of Medical Dashboard to tailor the intervention. Also, the intervention monitoring group will create a plan for developing and testing the new version of the Medical Dashboard. Third, we will recruit five care providers and five patients to discuss the acceptability and feasibility of the intervention plan (member-check). To this end, we will use the \u0026lsquo;think aloud\u0026rsquo; method [45], in which care providers and patients can speak aloud any words in their mind as they read through parts of the intervention plan. The think-aloud research method has been demonstrated to provide valid data on participant thinking and was successfully used in other intervention development studies [46, 47]. Based on the results obtained, further modifications will be made, resulting in a pre-tested version of the intervention plan ready for implementation in practice. The description of the intervention plan will follow the Template for Intervention Description and Replication [48].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 5: Develop an adoption and implementation plan \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe goal of this step is to write a detailed adoption and implementation plan, containing relevant strategies to optimize intervention delivery and implementation (fidelity). First, we will discuss results obtained from step 1-4 and inventory local resources (e.g., connections with primary care clinics) that may facilitate intervention implementation. Second, based on all results obtained from previous steps and our previous systematic review [21], the intervention monitoring group will have a meeting to pragmatically identify potential adopters and implementers. Also, this group will demonstrate program use outcomes, performance objectives and related determinants of implementation. Third, the intervention monitoring group will design the implementation plan following Figure 3 [49] based on Expert Recommendations for Implementing Change list of strategies [50]. Then, we will use the \u0026lsquo;think aloud\u0026rsquo; method to obtain feedback from CKD patients and care providers on the implementation plan. Finally, the adoption and implementation plan will be finalized with further modifications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhase 3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAim \u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing step 6 of IM, we will establish an intervention evaluation plan. Our evaluation will follow a hybrid type 2 trial design, comprising of (1) a pilot RCT with two parallel arms to study effectiveness, and (2) a process evaluation to evaluate implementation integrity (fidelity) and determinants of implementation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eDesign\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study will be a 9-month, two-arm, hybrid type 2 trial [51]. The trial design and corresponding study elements are detailed in Figure 4. The Standard Protocol Items: Recommendations for Interventional Trials 2013 Statement is used to report the pilot RCT protocol [52] (see Additional file 4), and the Standards for Reporting Implementation Studies will be followed for reporting the implementation study [53].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eIntervention\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCKD patients in the comparison group will receive usual care consisting of personalized in- and outpatient treatment based on symptoms experienced and disease severity, as outlined in the \u003ca href=\"https://www.theisn.org/kidney-disease-improving-global-outcomes-kdigo\"\u003eKidney Disease Improving Global Outcomes \u003c/a\u003e[6]. CKD patients in the intervention group will receive the usual care plus the culturally tailored \u0026lsquo;Medical Dashboard\u0026rsquo; based self-management intervention for nine months. Before the start of the intervention, CKD patients and care providers will receive a face-to-face training session on the use of Medical Dashboard. To avoid contamination, Medical Dashboard will only be made accessible for participants in the intervention group via a secure password-protected registration process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eStudy population, recruitment \u0026amp; randomization\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEffectiveness; Pilot RCT\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCKD patients will be recruited from the First Affiliated Hospital of Zhengzhou University. Recruitment strategies, inclusion, and exclusion criteria are identical to those in phase 1 (see Table 2 and Additional file 3). In pilot studies, Sim and Lewis [54] recommend 55 or more patients in total. Thus, we aim to recruit 60 patients in total for randomization in our study. We summarize the participant flow through the study in Figure 5. The outcomes for effectiveness are presented in Table 5.\u003c/p\u003e\n\u003cp\u003eA biostatistician blind to the study conditions will complete the random allocation sequence using a computer random number generator, allocating equal numbers of patients in the intervention (group 1) and comparison group (group 2). The care providers delivering the intervention cannot be blind to the intervention, but will not collect data or analyze outcomes. Research assistants blind to group membership will perform all face to face assessments and will not be involved in intervention delivery. Those conducting statistical analyses will be blind to group allocation until the evaluation is completed.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eImplementation study\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCKD patients, as well as care providers in the intervention group, will participate in the process evaluation to evaluate implementation integrity (fidelity) and determinants of implementation.\u003c/p\u003e\n\u003cp\u003eImplementation outcomes on the patient level as well as care provider level will be evaluated, see the further paragraph about details of outcomes of implementation. All CKD patients in the intervention group will be invited to complete the survey. Also, following principles of \u0026ldquo;purposive and convenience sampling\u0026rdquo;, CKD patients and care providers in the intervention group will be invited and interviewed either face to face or by telephone for the process evaluation. A research assistant who will not involve in the pilot RCT study will collect data within process evaluation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eOutcomes measures \u0026amp; data collection\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcomes for the pilot RCT evaluating the effectiveness\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe plan to evaluate:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003epatients\u0026rsquo; physical outcomes including biomedical measures,\u003c/li\u003e\n\u003cli\u003epatients\u0026rsquo; lifestyle and psychosocial functioning including self-efficacy, perceptions about CKD, quality of life, anxiety and depression status,\u003c/li\u003e\n\u003cli\u003ehospital admission, health care utilization, and cost-benefit\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eA trained research assistant will conduct data collection, and the intervention monitoring group will supervise the data collection process. We will invite participants in both the intervention and comparison group to visit the Department of Nephrology at the First Affiliated Hospital of Zhengzhou University for data collection at baseline (T0), three months (T1), six months (T2) and nine months (T3) post-randomization. At baseline, we will collect demographic data, including age, race, income, education, marital status, work type of participants. To avoid dropping out of participants, if participants cannot come to the hospital, data will then be collected via telephone interview. Table 5 provides details on the proposed outcome measures and timing of the measures. The operationalization of outcomes and descriptions of the measurement tools used are detailed in Additional file 5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcomes for implementation integrity (fidelity), and determinants of implementation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe process evaluation will be based on the RE-AIM framework [55]. The RE-AIM model is used to comprehensively measure the public health impact of research conducted in real-world settings [56]. Four dimensions (with the \u003cem\u003eEffectiveness\u003c/em\u003e domain being applicable above)\u0026mdash;Reach \u003cem\u003e(refers to the proportion of CKD patients reached by our program)\u003c/em\u003e, Adoption \u003cem\u003e(refers to the proportion of participants who use our intervention)\u003c/em\u003e, Implementation \u003cem\u003e(refer to completion as well as fidelity to the protocol)\u003c/em\u003e, and Maintenance will be used to evaluate the implementation only in the intervention group. We will collect the implementation outcome measurements throughout the 9-month trial. The outcome measures for each dimension of the RE-AIM model are as described in Table 6.\u003c/p\u003e\n\u003cp\u003eWe will use the Measurement Instrument for Determinants of Innovations questionnaire [57, 58] to evaluate the determinants of implementation. Also, individual interviews with stakeholders (e.g. patients, care providers) will be conducted to learn more about the usability and feasibility of Medical Dashboard, its potential for wide-scale implementation, and barriers and facilitators to implementation. We will categorize the determinants identified from this mixed-method study according to Fleuren Framework [59].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eQualitative data analysis\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA Framework Method [69] will be used to guide our qualitative analysis. We will structure the qualitative data in a matrix output formed by rows (cases), columns (codes), and \u0026lsquo;cells\u0026rsquo; (summarized data). We will follow the consolidated criteria for reporting qualitative research to ensure quality and validity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStage A: Transcribing\u003c/em\u003e\u003c/strong\u003e: All audio-taped interviews will be anonymized and transcribed verbatim in Chinese. Long pauses and interruptions (relevant to the study subject) will be noted within the text. Additionally, all participants\u0026rsquo; names will be replaced by an ID number. Any names mentioned during the interview will not be transcribed. One researcher will perform transcription, and another will check them to ensure content accuracy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStage B: Familiarization\u003c/em\u003e\u003c/strong\u003e: Two researchers will independently read all transcriptions and make contextual/reflective notes to become familiar with the whole data set.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStage C: development of an analytical framework\u0026amp; coding\u003c/em\u003e\u003c/strong\u003e: Atlas.ti for Windows version 7.5.18 (Scientific Software development, Berlin) will be used to analyze our data. Our study includes four qualitative research parts. These are research into the (1) needs, beliefs, perceptions toward CKD and self-management (phase 1); (2) needs, beliefs, perceptions toward eHealth self-management interventions in CKD (phase 1); (3) the acceptability and usability of intervention components (phase 3); (4) determinants of implementation of eHealth self-management interventions (phase 3). Therefore, based on prior literature in which specific theoretical frameworks were used for similar research questions [70-74], we will develop four distinct initial coding trees. For the first and second research questions, we will develop two coding trees based on the adapted version of the theoretical framework of Brakema et al., (submitted) and the TDF [75]. The Technology Acceptance Model [76] will be used to develop the coding tree for evaluating the acceptability and usability of intervention components. Also, the Fleuren framework [59] will be used to develop the coding tree for determinants of implementation of eHealth self-management interventions. The second researcher and third researcher will check the coding tree developed and make amendments if necessary. One researcher will then independently code two or three transcripts using the coding tree, and add new codes if the textual abstracts identified do not fit with the existing set of codes. Then, this researcher will meet with the second researcher and discuss the newly added codes. New codes will be added into the coding tree, and if needed, related codes will be grouped into categories. Thus, the process will be repeated until no new codes arise.\u003c/p\u003e\n\u003cp\u003eThe final coding tree will be checked and approved by the second researcher and the third researcher. This coding tree will include codes and categories; all codes and categories will be operationalized, and relevant examples will be provided.\u003c/p\u003e\n\u003cp\u003eThe finalized coding tree will then be applied to each transcript. One researcher will go through each transcript, highlight the meaningful textual abstracts, and assign the appropriate code from the final coding tree. Then, all codes assigned will be verified by the second researcher. All coding differences will be discussed until consensus is reached.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStage D: Charting data into the framework matrix\u003c/em\u003e\u003c/strong\u003e: Data will be charted into matrices per research question identified by two researchers using Microsoft Excel 2010. The matrix will comprise of one row per participant and one column per code. Interesting or illustrative quotations will be added to the matrices.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStage E: Interpreting the data\u003c/em\u003e\u003c/strong\u003e: Overarching themes will be generated from codes derived from the data set by reviewing the matrix and making connections within and between participants and codes. Relations, connections, and causality will be further explored and interpreted, and conclusions will be drawn.\u003c/p\u003e\n\u003cp\u003eAs for data derived from observations, all checklists will be digitalized and transported to Microsoft Excel 2010. Also, all written filed notes will be digitalized and will be taken into account to triangulate data collected from other methods. For instance, observation data obtained in phase 3 will support the analysis of implementation integrity (fidelity).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eQuantitative data analysis\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; All quantitative analyses will be performed using SPSS version 23 (IBM, Armonk, NY, USA). We will enter the quantitative data into Microsoft Excel 2010 and calculate descriptive statistics such as the mean, standard deviation, median, and range of linear variables, and frequencies and percentages of categorical variables.\u003c/p\u003e\n\u003cp\u003eTo gain insight into the needs, beliefs, perceptions of CKD patients towards disease (self-management) and the use of eHealth interventions in phase 1, we will use the descriptive statistics to describe CKD patients\u0026rsquo; demographic characteristics, BIPQ scores, CKD-SM score, and C-eHEALS scores. Also, we will conduct secondary analysis using (1) independent \u003cem\u003et\u003c/em\u003e-tests for normally distributed continuous variables, (2) Mann\u0026ndash;Whitney U-tests for nonnormally distributed variables and (3) Chi-squared or Fisher\u0026rsquo;s exact tests for categorical variables to compare the difference between certain types of different groups of CKD patients (e.g., age, gender, disease stage) and BIPQ scores, CKD SM score and C-eHEALS scores. \u003cem\u003eP\u003c/em\u003e-values \u0026lt;0.05 and odds ratios with a 95% confidence interval excluding one will be considered statistically significant.\u003c/p\u003e\n\u003cp\u003eIn phase 3, one of the primary hypothesis is that the intervention group, when compared to the comparison group, will demonstrate (statistically) significant improvement in self-management behavior at 3, 6 and 9 months post-randomization. Secondary hypotheses are that the intervention group when compared to patients in the comparison group, will demonstrate (statistically) significant improvement in biomedical status, self-efficacy, illness perception, mental health, quality of life, hospital admission, healthcare utilization and cost-benefit analysis at the timing of measurement. All primary statistical analyses will be conducted using intent-to-treat methods. The primary goal of statistical analyses is to examine and compare trends over time in the primary outcome. We will replicate this analytic approach for other secondary outcomes; secondary analyses will examine trends over time for biomedical status, self-efficacy, illness perception, mental health, quality of life, hospital admission, healthcare utilization, and cost-benefit analysis. We will use longitudinal, mixed-model analyses to test the hypotheses. Exploratory analyses will assess the impact of the intervention on primary and secondary outcomes for patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eMixed analysis of qualitative and quantitative data by triangulation\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe will conduct a combined analysis by merging the quantitative and qualitative results after separate analyses have been carried out [77]. In phase 1, the quantitative results will triangulate the qualitative results of the perception of disease, self-management behavior, and eHealth literacy. To this end, we will develop a thematic matrix [78] that includes participants\u0026rsquo; characteristics and data derived from surveys and emerging themes from our qualitative results to summarize CKD patients\u0026rsquo; illness perception, self-management behavior, and eHealth literacy. In phase 3, we will use the results collected from the qualitative interviews to help interpret the quantitative results from the pilot trial. Qualitative results will, therefore, be used to expand upon the results of this trial to understand the implementation process as experienced by participants. For instance, the questionnaire of determinants of implementation will be matched with the qualitative research on determinants of implementation.\u003c/p\u003e"},{"header":"Discussion","content":" \u003cp\u003eSome research has shown that eHealth based self-management interventions in CKD can help to improve health-related outcomes. However, evidence on the effectiveness of CKD eHealth based self-management interventions is still inconclusive [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Thus, our study will gain insights into the development of theoretically based, and target population tailored implementation of eHealth based self-management interventions to improve CKD care. Our study will add knowledge on the implementation research of eHealth self-management interventions in CKD care, with fitting with the needs and priorities expressed by health care professionals and patients. Also, this study will add evidence of the effectiveness of eHealth based self-management interventions on CKD health outcomes.\u003c/p\u003e \u003cp\u003eThere are some strengths to our research. First, we will use an innovative hybrid design to concurrently study the effectiveness and implementation of the tailored \u0026lsquo;Medical Dashboard\u0026rsquo; self-management intervention in CKD care. The hybrid designs can test the implementation process by looking inside the so-called \u0026ldquo;black box\u0026rdquo; to see what happens in the intervention implementation and how that could affect intervention outcomes [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Therefore, hybrid designs can provide the potential to speed the translation of intervention findings into routine practice by optimizing the implementation process [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. In addition, the triangulation of both quantitative and qualitative results allows researchers to understand the implementation process and intervention effectiveness from multiple perspectives, different types of causal pathways, and multiple types of outcome, thereby strengthening the validity of intervention effects [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Second, the robust theory will be used to guide the process of intervention development. The IM method ensures a theory-based approach from the recognition of a need or problem to the identification of a solution and intervention testing. To translate interventions into different contexts (e.g., health care system, population), it is essential to optimize the intervention fit with the needs and priorities expressed by the target population. IM was successfully applied in the development of self-management interventions for osteoarthritis and chronic low back pain [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e], and children with CKD [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. Also, the RE-AIM framework as utilized in this study provides systematic guidance on how to evaluate the intervention effect on the process and outcome level. A major limitation of this study is that we only perform the study within one hospital in China. Hence, findings may not be immediately generalizable to other health system contexts in China where the access to eHealth technology is (more) limited. Also, the transferability of developed Medical Dashboard self-management intervention to routine clinical practice in primary care may be limited and needs further exploration.\u003c/p\u003e \u003cp\u003eIn conclusion, our study will result in the delivery of a culturally tailored, standardized eHealth self-management intervention for CKD patients in China, which has the potential to optimize patients\u0026rsquo; self-management skills and improve health status and quality of life. Also, this study can serve as proof of concept for the use of IM and a hybrid type 2 trial design to evaluate the implementation and effectiveness of eHealth self-management interventions. Moreover, it will inform future research on the tailoring and translation of evidence-based eHealth self-management interventions in various contexts.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eCKD: chronic kidney disease; eGFR: estimated glomerular filtration rate; eHealth: electronic health; BP: blood pressure; LUMC: Leiden University Medical Center; RCT: randomized controlled trial; IM: Intervention Mapping; BIPQ: Brief Illness Perception Questionnaire; CKD-SM: Chronic Kidney Disease Self-management instrument; C-eHEALS: Chinese eHealth Literacy Scale; TDF: Theoretical Domains Framework; CKD-SE: Chronic Kidney Disease Self-efficacy; KDQOL-36: The Kidney Disease Quality of Life 36-item short-form survey; HADS: Hospital Anxiety and Depression Scale\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study has been approved by the Institutional Review Boards of the First Affiliated Hospital of Zhengzhou University, reference number (2019-KY-52).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is funded by the China Scholarship Council.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHS led the conception and design of this study and is the main contributor in writing this manuscript. RK, PB, XS, WW, TZ, ZL, XL and NC contributed to the conception and design of the study and editing of this manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Public Health and Primary Care, Leiden University Medical Centre,\u0026nbsp; Leiden, Netherlands. \u003csup\u003e2\u003c/sup\u003eDepartment of Nursing, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China. \u003csup\u003e3\u003c/sup\u003eDepartment of Obstetrics and Gynaecology, Erasmus Medical Center, Rotterdam, Netherlands. \u003csup\u003e4\u003c/sup\u003eDepartment of Nephrology, Leiden University Medical Centre, Leiden, Netherlands.\u003csup\u003e \u0026nbsp;5\u003c/sup\u003eSchool of Nursing and Health, Zhengzhou University, Zhengzhou, China. \u003csup\u003e6\u003c/sup\u003eDepartment of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJha V, Modi GK. 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Brit J Psychol. 1991;82:237-8.\u003c/li\u003e\n\u003cli\u003eGeense WW, van Gaal BGI, Knoll JL, Maas NM, Kok G, Cornelissen EAM, et al. Effect and Process Evaluation of e-Powered Parents, a Web-Based Support Program for Parents of Children With a Chronic Kidney Disease: Feasibility Randomized Controlled Trial. J Med Internet Res. 2018;20: e245.\u003c/li\u003e\n\u003cli\u003eGarba RM, Gadanya MA. The role of intervention mapping in designing disease prevention interventions: A systematic review of the literature. Plos One. 2017; doi: 10.1371/journal.pone.0174438.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Additional file","content":"\u003cp\u003eAdditional file 1: Core intervention components of Medical dashboard and evidence base. (DOCX 23KB)\u003c/p\u003e\n\u003cp\u003eAdditional file 2: Search strategy. (DOCX 25KB)\u003c/p\u003e\n\u003cp\u003eAdditional file 3: Detailed methods and relevant materials of the mixed-method study. (DOCX 55KB)\u003c/p\u003e\n\u003cp\u003eAdditional file 4: SPIRIT 2013 Statement: Defining standard protocol items for clinical trials. (DOCX 46KB)\u003c/p\u003e\n\u003cp\u003eAdditional file 5: The operationalization of outcomes and descriptions of the measurement tools used in pilot RCT. (DOCX 22KB)\u003c/p\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Overview of study phases\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"7.973421926910299%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhase\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.574750830564785%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIM steps\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"64.45182724252491%\"\u003e\n \u003cp\u003e\u003cstrong\u003eActivities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"7.973421926910299%\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.574750830564785%\"\u003e\n \u003cp\u003eStep 1\u003c/p\u003e\n \u003cp\u003eConduct needs assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"64.45182724252491%\"\u003e\n \u003cul\u003e\n \u003cli\u003e· \u0026nbsp;Establish an intervention monitoring group\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Perform a systematic literature review\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Conduct a mixed-methods study into needs, beliefs \u0026amp; perceptions of chronic kidney disease patients and care providers toward chronic kidney disease (self-management) and the use of eHealth (self-management) interventions\u0026nbsp;\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"7.973421926910299%\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.574750830564785%\"\u003e\n \u003cp\u003eStep 2\u003c/p\u003e\n \u003cp\u003eIdentify outcomes, performance objectives, and determinants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"64.45182724252491%\"\u003e\n \u003cul\u003e\n \u003cli\u003e· \u0026nbsp;Formulate program outcomes\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Specify performance objectives \u0026nbsp;\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Specify determinants of change\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Map the performance objectives to the determinants and create a matrix of change objectives\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"7.973421926910299%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.574750830564785%\"\u003e\n \u003cp\u003eStep 3\u003c/p\u003e\n \u003cp\u003eSelect theory-based methods and practical strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"64.45182724252491%\"\u003e\n \u003cul\u003e\n \u003cli\u003e· \u0026nbsp;Review potentially relevant theoretical methods\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Match each determinant to the relevant method(s)\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Translate methods into practical strategies to target each determinant\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Monitoring group reaches consensus on methods and practical strategies\u0026nbsp;\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"7.973421926910299%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.574750830564785%\"\u003e\n \u003cp\u003eStep 4\u003c/p\u003e\n \u003cp\u003eDevelop a tailored ‘Medical Dashboard’ based intervention (plan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"64.45182724252491%\"\u003e\n \u003cul\u003e\n \u003cli\u003e· \u0026nbsp;Develop an intervention plan by tailoring the core components of the Dutch Medical Dashboard to the Chinese context\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Member check with the target population\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"7.973421926910299%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.574750830564785%\"\u003e\n \u003cp\u003eStep 5\u003c/p\u003e\n \u003cp\u003eDevelop an adoption- and implementation plan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"64.45182724252491%\"\u003e\n \u003cul\u003e\n \u003cli\u003e· \u0026nbsp;Identify potential adopters and implementers\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Specify program use outcomes and performance objectives\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Specify determinants of change\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Map the performance objectives to the determinants and create a matrix of change objectives\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Design a plan for adoption and implementation\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp;Member check with the target population\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"7.973421926910299%\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.574750830564785%\"\u003e\n \u003cp\u003eStep 6\u003c/p\u003e\n \u003cp\u003eDevelop an intervention evaluation plan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"64.45182724252491%\"\u003e\n \u003cul\u003e\n \u003cli\u003e· \u0026nbsp;Specify the two-arm, hybrid 2 trial design and:\u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003e-Develop the effectiveness evaluation plan\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-Develop the implementation evaluation plan\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Eligibility criteria for chronic kidney disease patients and care providers\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.450915141430947%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"70.54908485856905%\"\u003e\n \u003cp\u003e\u003cstrong\u003eParticipant eligibility criteria\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.450915141430947%\"\u003e\n \u003cp\u003eInclusion criteria\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"70.54908485856905%\"\u003e\n \u003cul\u003e\n \u003cli\u003ePatients: (1) aged over 18 years old; (2) diagnosis of chronic kidney disease; (3) Chinese speaking.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Health care providers who work in the Department of Nephrology\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.450915141430947%\"\u003e\n \u003cp\u003eExclusion criteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"70.54908485856905%\"\u003e\n \u003cul\u003e\n \u003cli\u003e· \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Individuals unable to participate due to physical or mental disabilities.\u003c/li\u003e\n \u003cli\u003e· \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Individuals unable to write or read.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong style=\"text-align: inherit;\"\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 \u0026nbsp;Field methods used for topics\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"36.42857142857143%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCare providers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"2.7142857142857144%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"36.57142857142857%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSampling\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"16.037735849056602%\"\u003e\n \u003cp\u003eBeliefs, perceptions, \u0026nbsp;toward chronic kidney disease and self-management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.037735849056602%\"\u003e\n \u003cp\u003eNeeds toward\u0026nbsp;chronic kidney disease\u0026nbsp;self-management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.037735849056602%\"\u003e\n \u003cp\u003eNeeds, beliefs, perceptions toward eHealth \u0026nbsp;self-management interventions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.5849056603773586%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.037735849056602%\"\u003e\n \u003cp\u003eBeliefs, \u0026nbsp; \u0026nbsp; perceptions toward chronic kidney disease and self-management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.037735849056602%\"\u003e\n \u003cp\u003eNeeds toward chronic kidney disease self-management\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.22641509433962%\"\u003e\n \u003cp\u003eNeeds, beliefs, perceptions toward eHealth self-management interventions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eFace to face interview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"2.7142857142857144%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.285714285714286%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003ePurposive,\u003c/p\u003e\n \u003cp\u003eConvenience\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eFocus group discussion\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"2.7142857142857144%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.285714285714286%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003ePurposive, Convenience\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eObservation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"2.7142857142857144%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.285714285714286%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003ePurposive, Convenience\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eSurvey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"2.7142857142857144%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.285714285714286%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.142857142857142%\"\u003e\n \u003cp\u003eRandomly\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\n \u003cbr\u003e\n\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 The concepts from Intervention Mapping step 2-5\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003e\u003cstrong\u003eConcept of Intervention Mapping\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDefinition in Bartholomew LK et al. [29]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStep 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003eProgram outcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003eDesired changes in the behavior and the environmental conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003ePerformance objective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003eThe required actions to accomplish the change in the behavioral and environmental outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003eDeterminant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003eFactors that are associated with the performance of behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003eChange objective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003eSpecific goals stating what should change at the determinants for program outcomes in different level\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStep 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003eTheoretical method\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003eGeneral technique or process for influencing changes in the determinants of behaviors and environmental conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003ePractical strategy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003eA specific technique for the practical use of theoretical methods in ways that fit with the target group and the context in which the intervention will be conducted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStep 4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003eIntervention plan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003eA plan detailing intervention scope and sequence including delivery channels, themes, and list of the intervention materials needed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStep 5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.3801652892562%\"\u003e\n \u003cp\u003eImplementation plan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.6198347107438%\"\u003e\n \u003cp\u003eA plan detailing how intervention adoption and implementation can be supported and maintained over time.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5 Effectiveness outcomes and timing of measurements\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"12.879581151832461%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"16.858638743455497%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome Indicators\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"7.958115183246074%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"33.61256544502618%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Tools\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"12.879581151832461%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Sources\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"15.811518324607329%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTiming of measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eT0\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eT1\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eT2\u003csup\u003ec\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eT3\u003csup\u003ed\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003ePrimary Outcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.84100418410042%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949790794979079%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.57740585774059%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.84100418410042%\"\u003e\n \u003cp\u003eSelf-management behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949790794979079%\"\u003e\n \u003cp\u003eSurvey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.57740585774059%\"\u003e\n \u003cp\u003eChronic Kidney Disease Self-Management\u0026nbsp;instrument [60, 61]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003eSecondary outcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.84100418410042%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949790794979079%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.57740585774059%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.84100418410042%\"\u003e\n \u003cp\u003eBiomedical status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949790794979079%\"\u003e\n \u003cp\u003eClinical records\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.57740585774059%\"\u003e\n \u003cp\u003eBlood pressure, Bodyweight, Glomerular filtration rate, Serum albumin, Length, Serum calcium, Serum phosphate, Serum hemoglobin, Sodium and protein in 24h urine, albumin/creatinine ratio, Cholesterol, High-density lipoprotein, Low-density lipoprotein, Triglycerides, Hemoglobin A1C, Complications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.84100418410042%\"\u003e\n \u003cp\u003eSelf-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949790794979079%\"\u003e\n \u003cp\u003eSurvey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.57740585774059%\"\u003e\n \u003cp\u003eChronic Kidney Disease Self-efficacy scale [61, 62]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.84100418410042%\"\u003e\n \u003cp\u003eIllness perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949790794979079%\"\u003e\n \u003cp\u003eSurvey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.57740585774059%\"\u003e\n \u003cp\u003eBrief Illness Perception Questionnaire [63, 64]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.84100418410042%\"\u003e\n \u003cp\u003eQuality of life\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949790794979079%\"\u003e\n \u003cp\u003eSurvey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.57740585774059%\"\u003e\n \u003cp\u003eThe Kidney Disease Quality of Life 36-item short-form survey\u0026nbsp;[65-67]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.84100418410042%\"\u003e\n \u003cp\u003eMental health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949790794979079%\"\u003e\n \u003cp\u003eSurvey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.57740585774059%\"\u003e\n \u003cp\u003eHospital Anxiety and Depression Scale [68]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.84100418410042%\"\u003e\n \u003cp\u003eHospital admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949790794979079%\"\u003e\n \u003cp\u003eSurvey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.57740585774059%\"\u003e\n \u003cp\u003eThe time to first acute hospital admission with an exacerbation of CKD or death due to CKD within nine months after randomization\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.84100418410042%\"\u003e\n \u003cp\u003eHealthcare utilization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949790794979079%\"\u003e\n \u003cp\u003eSurvey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.57740585774059%\"\u003e\n \u003cp\u003eNumber of hospitalizations and emergency room visits of patients, primary and secondary care visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.84100418410042%\"\u003e\n \u003cp\u003eCost-benefit analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949790794979079%\"\u003e\n \u003cp\u003eRecords\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.57740585774059%\"\u003e\n \u003cp\u003eAll costs delivering the interventions (e.g., materials used in the interventions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003eProgram, intervention group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.84100418410042%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.949790794979079%\"\u003e\n \u003cp\u003eRecords\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.57740585774059%\"\u003e\n \u003cp\u003eMedical cost (e.g., cost of treatment, hospitalization rates minored as monetary terms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.866108786610878%\"\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.9748953974895396%\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eAt baseline\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eThree months post-randomization\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003eSix months post-randomization\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ed\u003c/sup\u003eNine months post-randomization\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\n \u003cbr\u003e\n\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6 Implementation outcomes (intervention group only)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"22.5%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome Indicators\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Tools\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Sources\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd height=\"31\" width=\"NaN%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003eReach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"23\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003eNumber of patients (eligible, excluded, enrolled)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003eRecords\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003eThe proportion of patients eligible to use our intervention program, excluded, invited, and enrolled\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"47\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003eNumber of health care providers (eligible, excluded, enrolled)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003eRecords\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003eThe proportion of care professionals eligible to use our intervention program, excluded, invited, and enrolled\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003eCare provider\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"47\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003eCharacteristics of participating patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003eRecords\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003eComparing participating patients to the target population on key clinical characteristics (e.g., disease stage)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"47\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003eQualitative assessment-reach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003eInterview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003eThe barriers/facilitators to study participation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"37\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003eAdoption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"7\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003eCharacteristics of participating care providers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003eRecords\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003eComparing participating care providers to the target population on key characteristics (e.g., work type)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003eCare provider\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"7\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003eUse of program\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003eRecords\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003eFrequency of materials or medical dashboard used\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003ePatient, care provider\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"7\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003eQualitative assessment-adoption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003eInterview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003eThe appropriateness, comfort, relative advantage, and credibility of the intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003ePatient, care provider\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"7\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003eImplementation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"23\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003eImplementation completion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003eInterview, observation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003eThe implementation completion tasks will be made as a checklist, and the completion of the task and the length of time to finish will be checked.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003ePatient, care provider\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"23\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003eAcceptability and feasibility of the intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003eInterview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003eExperiences and perceptions of the intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003ePatients, care provider, research assistant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"91\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003eMaintenance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"23\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003eFollow up on the use of medical dashboard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003eRecords\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003eThe use of intervention to assess long-term maintenance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003eRecords\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"23\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.452380952380953%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003eQualitative assessment-maintenance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.119047619047619%\"\u003e\n \u003cp\u003eInterview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.214285714285715%\"\u003e\n \u003cp\u003ePerceptions of the integration of intervention in health facilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.714285714285714%\"\u003e\n \u003cp\u003ePatient, care provider\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"23\" width=\"0%\"\u003e\n \u003cbr\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"eHealth, Self-management, Chronic kidney disease, China, Hybrid design, Implementation ","lastPublishedDoi":"10.21203/rs.2.22736/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.2.22736/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground \u003c/p\u003e\u003cp\u003eChronic kidney disease (CKD) is a significant public health concern. In CKD patients, interventions that support disease self-management have shown to improve health status and quality of life. At the moment, the use of electronic health (eHealth) technology in self-management interventions is becoming more and more popular. Evidence suggests that eHealth-based self-management interventions can improve CKD patients’ health-related outcomes. However, knowledge of the implementation and effectiveness of such interventions in general, and in China in specific, is still limited. This study protocol aims to develop and tailor the evidence-based Dutch ‘Medical Dashboard’ eHealth self-management intervention for patients suffering from CKD in China and evaluate its implementation process and effectiveness. \u003c/p\u003e\u003cp\u003eMethods\u0026nbsp;\u003c/p\u003e\u003cp\u003eTo develop and tailor a Medical Dashboard intervention for the Chinese context, we will use an Intervention Mapping (IM) approach. A literature review and mixed-method study will first be conducted to examine the needs, beliefs, perceptions of CKD patients and care providers towards disease (self-management) and eHealth (self-management) interventions (IM step 1). Based on the results of step 1, we will specify outcomes, performance objectives, and determinants, select theory-based methods and practical strategies. Knowledge obtained from prior results and insights from stakeholders will be combined to tailor the core interventions components of the ‘Medical Dashboard’ self-management intervention to the Chinese context (IM step 2-5). Then, an intervention and implementation plan will be developed. Finally, a 9-month hybrid type 2 trial design (N=60) will be employed to investigate the effectiveness of the intervention using a pilot randomized controlled trial with two parallel arms, and the implementation integrity (fidelity) and determinants of implementation (IM step 6). \u003c/p\u003e\u003cp\u003eDiscussion \u003c/p\u003e\u003cp\u003eOur study will result in the delivery of a culturally tailored, standardized eHealth self-management intervention for CKD patients in China, which has the potential to optimize patients' self-management skills and improve health status and quality of life. Moreover, it will inform future research on the tailoring and translation of evidence-based eHealth self-management interventions in various contexts.\u003c/p\u003e","manuscriptTitle":"Development and evaluation of an eHealth self-management intervention for chronic kidney disease patients in China: protocol for a mixed-method hybrid type 2 trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-02-06 17:36:22","doi":"10.21203/rs.2.22736/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"efbe259d-fc47-4ae6-bb25-ca690e0900e8","owner":[],"postedDate":"February 6th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56241,"name":"Internal Medicine"},{"id":56242,"name":"Nursing"}],"tags":[],"updatedAt":"","versionOfRecord":[],"versionCreatedAt":"2020-02-06 17:36:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-13310","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"identity":"rs-13310","version":["v1"]},"buildId":"J0_U0BvcaRcwD8yVFaRlm","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}