Association of Generation and Group Size With the Usage of a Mobile Health App in Thailand: Secondary Analysis of the ThaiSook Cohort Study (Preprint)

Author:

Inchusri TharojORCID,Surangsrirat DechoORCID,Kwanmuang PapichayaORCID,Poomivanichakij PrapasiriORCID,Apiwatgaroon PonnapatORCID,Ongprakobkul SurathepORCID,Kongchu ApissaraORCID,Klinpikul AndaORCID,Taneeheng AmmarinORCID,Pruphetkaew NannapatORCID,Thongseiratch TherdpongORCID,Ngamchaliew PitchayanontORCID,Vichitkunakorn PolathepORCID

Abstract

BACKGROUND

In Thailand, The National Science and Technology Development Agency developed ThaiSook, a behavior-tracking app, to promote healthy lifestyles. The Faculty of Medicine, Prince of Songkla University (MED PSU)×ThaiSook Healthier Challenge encouraged employees to use the app over a 28-day period (from July 11 to August 7, 2022). Until recently, no previous studies have examined the association of generations and group sizes with mobile health (mHealth) app use. Understanding these relationships can inform the design of effective mHealth interventions and facilitate targeted interventions.

OBJECTIVE

This study aimed to (1) compare the overall app usage and logging function across different generations and group sizes and (2) describe the demographic characteristics of the participants of the MED PSU×ThaiSook Healthier Challenge.

METHODS

We conducted a secondary data analysis of the data from the ThaiSook prospective cohort study. Data were collected through the app and comprised demographic characteristics (ie, age, sex, weight, height, and group size) and behaviors (ie, water consumption, fruit and vegetable consumption, sleep hours, and exercise). The outcomes consisted of users who used the app for at least 80% of the participation period (≥23 days). Bivariate tests (Pearson chi-square test for categorical variables and Mann-Whitney <i>U</i> and Kruskal-Wallis tests for continuous variables) were conducted over sex, generations, initial BMI, and group size. Finally, multiple logistic regression models were used to examine the relationship between the independent variables used by the ThaiSook app and consistent users who had used the app for at least 80% of the participation period.

RESULTS

Of the 827 participants, most were female (734/827, 88.8%), belonged to a medium-sized group of 6-10 members (479/827, 57.9%), and belonged to generation Y (377/761, 49.5%). Multivariate analysis revealed that the overall app usage was 2.09 times higher in women than in men (adjusted odds ratio [AOR] 2.09, 95% CI 1.27-3.44). The older generations used all logging functions more frequently than did generation Y (baby boomers AOR 2.54, 95% CI 1.31-4.92; generation X AOR 1.96, 95% CI 1.42-2.72). The use of all logging functions was higher among participants belonging to larger groups than among those belonging to smaller groups (large groups AOR 2.85, 95% CI 1.58-5.16; medium groups AOR 2.06, 95% CI 1.47-2.88). Water logging was most used (806/827, 97.5% participants), followed by food, sleep, and workout logging.

CONCLUSIONS

The MED PSU×ThaiSook Healthier Challenge participants were mostly females from generation Y and medium-sized groups. Water logging was most frequently used, followed by fruit and vegetable logging. The results indicate that generation and group size were significantly associated with consistent and daily usage (<i>P</i>&lt;.05). Older generations and larger groups engaged with the app more consistently than younger generations and smaller groups and individuals.

CLINICALTRIAL

Publisher

JMIR Publications Inc.

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