Effectiveness of mHealth Education on Health Outcomes Among Pregnant Women

Overview

Gestational weight gain (GWG), weight gain of a mother during pregnancy, is an important determinant that influence the health outcomes of mothers and fetus. There is an increasing trend of pregnant women using mobile health (mHealth) to assess for pregnancy-related health information. While evidence on the effectiveness of mHealth education on improving pregnancy outcomes among pregnant women is growing, the findings had been inconclusive with scarcity of such data in Malaysia. The objective of the study is to determine the effectiveness of a 9-month mHealth intervention on GWG and other outcomes (prenatal knowledge, physical activity, psychosocial well-being, nutritional status, quality of life and sleep quality) among pregnant women.

This study will evaluate the usability, feasibility and practicality of a previously developed smartphone application with complete alpha and beta testing on pregnancy outcomes in a cluster randomised control trial (RCT). The study will be completed by involving the nutrition intervention using either mHealth interventions or conventional methods that will be carried out among pregnancy women. Subjects will be allocated into groups according to respective health clinics, namely, two interventions group which are: Group 1: mHealth intervention group Group 2: mHealth intervention group + dietitian consultation Group 3: control group which total of 294 eligible subjects will be recruited, with 98 subjects are needed in respective groups. This is a cluster-randomised controlled trial. For Malaysia consist of two regions which are East Malaysia and West (or peninsular) Malaysia and they are actually about 400 miles (640 km) apart. At East Malaysia, we targeted on the area with higher density of population which are Klang Valley (Kuala Lumpur, Selangor and Putrajaya). As shown in Figure 1, for three states under Klang Valley, we obtained ethics approval from the Jabatan Kesihatan Negeri Selangor for Selangor state and Jabatan Kesihatan Wilayah Persekutuan Kuala Lumpur dan Putrajaya for Putrajaya state. In order to prevent cross contamination between the states, we use simple random sampling which Selangor been allocated into control group and Putrajaya as intervention group. As under Putrajaya states only two clinics granted approval for data collection which are Presint 9 Health Clinic and Presint 18 Health Clinic. By using cluster sampling method, Presint 9 Health Clinic was randomised into intervention group 1 which whole cluster participant will be receiving mHealth intervention alone and Presint 18 Health Clinic into intervention group 2 which whole cluster participants will receive mHealth intervention group in addition with personal dietitian consultation. There are nine districts in Selangor: Gombak, Hulu Langat, Hulu Selangor, Klang, Kuala Langat, Kuala Selangor, Petaling, Sabak Bernam and Sepang which consist of total of 81 health clinics, we stratified the number of health clinics within the 25 km radius from the Faculty of Medicine and Health Sciences, Universiti Putra Malaysia due to the geographical proximity and financial constraints (limited budget). There were total of 15 health clinics after stratification and simple random sampling was done which Seri Kembangan health clinics in Petaling District had been chosen as control group. As this is an intervention study, thus blinding is not applicable for data collection personnel and participants. The health clinics that involved in this study will be maternal and child health clinics. This study will use a set of questionnaires to obtain information on personal information, anthropometry data, prenatal knowledge, physical activity, psychosocial well-being, dietary intake, quality of life, sleep quality and gestational weight gain of the subjects, based on appropriate instruments. Re-assessment will be performed at month-6 and month-9 (delivery) after baseline measurements. During the re-assessment, the data will be collected again on dietary intake, physical activity, psychosocial well-being, sleep quality and quality of life. All subjects will be followed up prospectively until delivery. The follow up data collection will be matched with the prenatal visit of the pregnant mother to the clinic.