The normal value for eGFR is 90 ml/min/1.73 m2 and it is considered the best test to measure kidney function and determine the stage of kidney disease (NKF, 2019). The level of eGFR and its magnitude of change over time is vital to the detection of kidney disease, understanding its severity, making decisions about diagnosis, prognosis, and treatment, and screening of CKD progression. One year is a proper period to measure an eGFR decline rate, and it is a good predictor of CKD prognosis (Nojima et al., 2017). However, an eGFR is a standard outcome to measure the progression of CKD. Thus, it is necessary to measure eGFR between the
experimental and control groups after receiving an intervention in the current study.
A Self-and family management support combined with the mHealth
2. Delivery characteristics
Most of the studies had more than one delivery element that utilized face-to- face delivery and integrated IT tools, such as VDO media (Lin et al., 2013), telephone support and consultation (Havas et al., 2018; Seephom et al., 2014), interactive websites (Blakeman et al., 2014), mobile applications (Chen et al., 2018; Doyle et al., 2019), and the nutrition data system for research software (Timmerman et al., 2017).
All studies had members of the multidisciplinary team facilitating the delivery of self-management support interventions. A diversity of providers included nurses, nephrologists, dietitians, social workers, general practitioners, and lay health workers, among whom nurses are the most common health professional group.
3. Duration of intervention delivery
The study duration varied and ranged from three weeks to three years, with at least four weeks required to achieve clinically meaningful outcomes and a three-month follow-up effect (He et al., 2017; Jeddi et al., 2017; Lee et al., 2016; Zimbudzi et al., 2018). Also, the duration of the face-to-face session was between 20 minutes and 2 hours, and the telephone phone session lasted 5–60 minutes (Havas et al., 2018;
Timmerman et al., 2017).
From the above literature review, there is still a gap in research, which is a lack of systematic involvement of the family in self-management programs. The family has a crucial person for chronic disease management. The majority of the management of chronic conditions takes place in the everyday home setting, and family can be highly influential on individual behavior (Ory et al., 2013). Proper family functioning can lead to improved self-care confidence and autonomous motivation for medication and diet adherence (Stamp et al., 2016). Also, families were essential in constructing an environment that was conducive to family
engagement and support. Adaptation within the family included maintaining cohesion between family members, normalization, and contextualization of the chronic
condition (Whitehead et al., 2017).
Also, there is a limit to the interactive IT tools that have an interactive function to transfer knowledge, communication, and trigger patients to have effective and sustainable self-management behaviors. The IT tools that are integrated into the self-management support program consists of telephones, mobile applications,
telemedicine, video conferencing, computerized systems (websites), and the internet.
The mobile application was often used to transfer data or knowledge and to communicate with healthcare providers or researchers (Blakeman et al., 2014)
because it was easier to use and access than computerized systems (Jeddi et al., 2017).
Moreover, 49.6 million Thai people (79.3%) use a mobile phone (National Statistical Office, 2015). Thus, integrating mHealth into the self-management program for Thai people is suitable.
CKD stage 3 is considered a critical problem because it has the highest number of all stages of CKD which further develop into a massive number of ESRD if they live without effective self-management programs. Therefore, the researcher conducted an RCT study that aimed to develop and examine the effectiveness of self- and family management support combined with the mHealth application program among persons with CKD stage 3. This program was created from the synthesis of evidence-based practice and is supported by the IFSMT of Ryan and Sawin (2009).
Family members were invited to participate in program activities to help patients using the mHealth application and support self-management in daily life.
The program implementation consisted of four sessions over four weeks.
The delivery intervention comprised: (1) identifying and measuring risks and protective factors, (2) providing knowledge and caring beliefs, (3) developing self-regulation skills and providing support from family and mHealth applications, and (4) developing abilities in self-evaluation and management of responses associated with health behavior change. The outcomes were measured three times:
pre-intervention (week 1), post-intervention (week 4), and follow-up (week 16).
The mHealth application was designed by researchers and created by experts who developed the mHealth application. It was used for Android operating systems and working online. This application consisted of six functionalities that were proper for self-management among patients with CKD stage 3, as follows: (1) personal
information; (2) eGFR calculation; (3) laboratory result record and BP monitoring;
(4) trend graph; (5) CKD management; and (6) communication with the healthcare provider. We expected that the program might show good outcomes for patients with CKD stage 3, were able to improve self-management behaviors, control BP, and prevent the decline of eGFR.
The objective of this study was to examine the effectiveness of self-and family management support combined with the mHealth application program on self-management behaviors, BP, and eGFR among persons with CKD stage 3. This chapter describes the research design, population and sample, research setting, instrumentation, protection of human subjects, data collection procedures, and data analysis.