Home Men Health How self-monitoring and motivation fuel online weight reduction success

How self-monitoring and motivation fuel online weight reduction success

How self-monitoring and motivation fuel online weight reduction success

A recent BMC Public Health study analyzes self-monitoring data from Chinese adults who participated in a gaggle weight reduction intervention using a mixed-methods approach.

Study: Why more successful? An evaluation of participants’ self-monitoring data in a web-based weight reduction intervention. Image Credit: Ground Picture / Shutterstock.com


In response to the World Health Organization (WHO), over 1.9 billion adults were chubby in 2016. This global public health problem has reached alarming proportions in China, which significantly increases the risks of several diseases, including cancer, diabetes, and cardiovascular diseases. 

Self-monitoring, which reinforces self-awareness, promotes desired behaviors, and reduces unwarranted behaviors, could be achieved through setting specific targets and logging progress. Changes in body weight, exercise, and dietary intake are often monitored by participants of weight reduction interventions. In truth, obese individuals who periodically monitor their food plan and body weight have experienced more helpful responses to interventions.

Researchers have each quantitatively and qualitatively analyzed the self-monitoring behaviors of dieters; nevertheless, few have utilized a mixed-methods approach for this purpose. Notable benefits of the mixed-methods approach include its ability to elucidate the association between weight reduction and different self-monitoring indicators and reduce bias to ultimately develop reliable insights into self-monitoring.

In regards to the study

Self-monitoring data from 61 Chinese adults who participated in a five-week online weight reduction intervention group were analyzed in the present study. Along with providing information on their weight reduction motivation and body mass index (BMI) values, the study participants also engaged in day by day quantitative monitoring, which included parameters like caloric intake and sedentary behavior, in addition to qualitative self-monitoring, which involved a day by day log of weight reduction progress. 

A scoring rule assessed the timeliness of the information. A one-way repeated measurement ANOVA was used to investigate the dynamics of self-monitoring indicators.

Regression and correlation analyses were performed to explore the connection between weight change, self-monitoring indicators, and baseline data. Participants were grouped into three categories based on their weight reduction outcomes, and their qualitative data was assessed using content evaluation. 

Key findings

Some fluctuation in self-monitoring data was observed throughout the intervention. Moreover, some baseline characteristics of participants and self-monitoring behaviors were positively related to their final weight reduction outcomes. Across the burden loss categories, heterogeneity in qualitative self-monitoring data was observed. 

Through the weight reduction process, a gradual decrease in caloric intake was observed, thus suggesting the educational behavior amongst participants. Through the last week, participants exhibited some variation in commitment levels, which led to concerns a couple of rebound in caloric intake.

Weight reduction satisfaction was highest in the primary week and steadily declined. This decline in satisfaction was consistent with their weight reduction, highlighting the link between effort and end result. 

Weight reduction motivation, baseline BMI, and timeliness of day by day self-monitoring data completion predicted final weight reduction. The connection between weight reduction, day by day physical activity expenditure, and day by day caloric intake was insignificant. Moreover, no significant relationship was observed between weight reduction and day by day mood. 

The qualitative evaluation of participants’ day by day logs revealed 4 categories: eating behavior, weight reduction awareness, physical activity, and perception of change, the latter of which was most often mentioned. This was followed by the mention of weight reduction awareness, eating behavior, and physical activity.

Inconsistencies were noted within the probability distribution of participants’ day by day log frequencies. Poor and moderate weight reduction groups reported lower observed frequencies across all 4 categories than the superb group. The superb group reported a better frequency of adjustments in eating habits, self-awareness, disadvantages, and demonstrating greater patience.


An inconsistent pattern within the self-monitoring behavior amongst individuals undergoing a gaggle weight reduction intervention was observed. More specifically, a better level of self-monitoring was identified through the initial weeks of weight reduction, followed by a slow decline.

More significant weight reduction was attained by individuals with higher levels of motivation, higher baseline BMI, and people who often self-monitored. Moreover, more detailed and frequent content was reported within the texts submitted by successful participants.

These findings imply that weight reduction motivation and adherence to self-monitoring must be emphasized. The usage of digital technologies might be helpful, as they may facilitate greater weight reduction awareness and promote healthy dietary habits.

In the long run, more studies with larger sample sizes and precise measurement tools are needed to judge day by day calorie expenditure and intake. 


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