Abstract

BackgroundChronic conditions in the United States are among the most costly and preventable of all health problems. Research suggests health coaching is an effective strategy for reducing health risks including decreases in weight, blood pressure, lipids, and blood glucose. Much less is known about how and when coaching works.ObjectiveThe aim of this study was to conduct an analysis of intrapersonal variations in participants’ progression in health coaching, examining gender and age-related differences.MethodsThis was a cross-sectional, retrospective analysis of 35,333 health coaching participants between 2012 and 2016. Differences in number of goals and activities set and completed, and number of interactions were assessed using negative binomial models. Differences in goal type were assessed using logistic regression for gender and using the Welch test for age to account for unequal variances.ResultsParticipants choosing online coaching were more likely to be younger and female (P<.001). Gender and age differences were found for the types of goals set by participants. Regarding program activity, women set and completed 12% more action steps than men (P<.001), averaging 21% more interactions than men (P<.001); no gender differences were found in number of goals completed (P=.12), although the percentage of males and females completing goals was significantly different at 60 and 120 days postenrollment (P<.001). Results indicated significant age-related differences in all aspects of program activity: number of interactions, goals set and completed, action steps set and completed (all P values <.01), as well as significant differences in percentage of individuals completing initial goals within 30 days, with older individuals completing more than younger individuals did (all P values <.001).ConclusionsThis study found significant intrapersonal variation in how people participate in and progress through a coaching program. Age-related variations were found in all aspects of coaching activity, from modality preference and initial choice of goal type (eg, weight management, tobacco cessation) to goal completion, whereas gender-related differences were demonstrated for all program activities except number of goals set and completed. These findings indicate that to maximize behavior change, coaches need to personalize the coaching experience to the individual.

Highlights

  • The authors’ rationales for selecting this topic are the costly and preventable chronic health problems that plague the United States including obesity

  • Dr Wallace and her colleagues (2017) have provided appropriate direction and support in their efforts to develop the understanding of how successful administration of a health coaching initiative among a diverse population must be adaptable to gender and age variables and personal preference

  • This study revealed that women were more likely than men to choose online interactions and engage in face-toface Tele-Health Coaching sessions, whereas men were more likely to choose telephone and texting Tele-Health Coaching

Read more

Summary

Introduction

The authors’ rationales for selecting this topic are the costly and preventable chronic health problems that plague the United States including obesity. The authors build a strong case for personalizing the online e-health and mobile health coaching experience to each individual for optimal health outcomes and cost savings. “Health information technologies are a critical component of our healthcare system, and often relevant to value-based care” The key findings in this study support online health coaching, m-Health Smartphone apps for behavior change, activity trackers and wearable as a significantly effective strategy to achieving value and cost savings in healthcare. The evidence from this research supports the use of Tele-Health Coaching for improved nutrition and fitness, tobacco cessation, weight loss and weight management, and for reducing health risks including but not limited to decreases in blood pressure, lipids, blood glucose, weight, body mass index (BMI), cholesterol, and or diabetes

Objectives
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.