JMIR Publications

ABSTRACT

Background:

Mobile health (mHealth) applications are increasingly used for health promotion, particularly for managing noncommunicable diseases (NCDs) through behavior modification. Understanding the factors associated with successful weight loss in such interventions can improve program effectiveness.

Objective:

This study aimed to determine the factors associated with weight change rates and to examine the relationship between weight recording frequency and the volume of chat communication with healthcare professionals on weight loss outcomes in patients with obesity and NCDs.

Methods:

The participants had obesity (BMI ≥ 25 kg/m²) and were diagnosed with noncommunicable diseases (e.g., hypertension, diabetes, dyslipidemia). The program included 12 telephone consultations with healthcare professionals. Only participants who completed the full six-month program, including all 12 telephone consultations and provided an end-of-study weight, were included in the analysis. The primary outcome was the rate of weight change, defined as the percentage change in weight from the initial period (first 14 days) to the final period (two weeks before the last consultation), relative to the initial weight. The key independent variables were weight input frequency (proportion of days with weight recording) and chat communication volume (total messages exchanged). An interaction term between these variables was included to assess moderation effects in the regression analysis. The volume of communication was measured as the total number of messages exchanged, with each message, regardless of who sent it, being counted as one interaction. Healthcare providers were instructed to send one scheduled chat message per week following each biweekly phone consultation. These scheduled messages primarily included personalized feedback, reminders, and motivational support. Additionally, providers responded to participant-initiated messages at any time during the program. One professional responded to each participant. Hierarchical multiple regression and simple slope analyses were conducted to identify relationships and interactions among these variables.

Results:

Therefore, the final analysis of this study included 2,423 participants. Significant negative associations were found between the rate of weight change and baseline body mass index (BMI) (β = −0.097, p < 0.01), weight input rate (β = −0.017, p < 0.01), and communication volume (β = −0.193, p < 0.01). The interaction between weight input rate and chat frequency also showed a significantly negative effect on weight change (β = −0.006, p < 0.01). Simple slope analysis showed that when the weight input rate was +1 SD above the mean, frequent chats were associated with greater weight reduction (slope = −0.6, P<.001), whereas no significant effect was observed at −1 SD (slope = −0.01, P=.94)

Conclusions:

The findings suggest that both proportion of days with weight recording and communication volume independently and interactively influence weight change in patients with obesity and NCDs.