According to new research, persons who used analytical language saw greater weight reduction and a lower dropout rate.
Millions of people throughout the globe struggle with obesity, which is linked to a significantly elevated risk for metabolic and cardiovascular diseases. According to a study by Annabell Ho at Noom, Inc. in New York, USA, recently published in the journal PLOS Digital Health, using analytical language while defining a weight-loss goal was linked to better weight loss success and a reduced risk of dropout.
Results of behavioral interventions used to treat obesity vary greatly, and some patients quit the program before receiving the whole intervention. However, little is known about the causes leading to attrition or weight loss. Researchers performed a retrospective analysis of 1,350 Noom Weight users who paid to engage in a 16-week program in order to better understand how language may impact weight loss and program attrition.
Each participant established a starting goal and spoke with a coach to discuss their specific weight loss objectives in further depth. The researchers then used an automated text analysis algorithm to analyze the language, and they used program activity data to determine weight loss as well as weight loss and the dropout rate.
The authors discovered that in goal-striving dialogues, such as discussing attempts to achieve a goal with a coach, using analytical as opposed to present-focused language was associated with more weight loss and a lower likelihood of dropout.
Despite the potential usefulness of these results, the research did not look at other pertinent factors, such as the influence of education level or English language ability on goal-setting language. To determine precisely why analytical language is beneficial, future research should concentrate on the variables that mediate the relationship between language and outcomes.
According to the authors, “Our results are among the first to identify individuals’ language, which has not been studied much previously, as relevant and informative for understanding weight loss and dropout. This raises directions for future research to improve intervention development and ascertain whether language is informative in other lifestyle behavior change interventions.”
Ho adds, “Using analytical language, for example analyzing what’s important and why predicts more weight loss and less program attrition on a digital weight loss program. On the other hand, using words that are more self-focused or present-focused like ‘I’ and ‘me’ predict less weight loss and more attrition.”
Reference: “Goal language is associated with attrition and weight loss on a digital program: Observational study” by Annabell Suh Ho, Heather Behr, E. Siobhan Mitchell, Qiuchen Yang, Jihye Lee, Christine N. May and Andreas Michaelides, 16 June 2022, PLOS Digital Health.