scholarly journals Smartphone-based health coaching and behavior change for pregnant patients

2022 ◽  
Vol 226 (1) ◽  
pp. S494
Author(s):  
Shannon Malloy ◽  
Danielle Bradley
2019 ◽  
pp. 299-310
Author(s):  
Karen L. Lawson ◽  
Margaret Moore ◽  
Matthew M. Clark ◽  
Sara Link ◽  
Ruth Wolever

10.2196/14458 ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. e14458 ◽  
Author(s):  
Victor Cueto ◽  
C Jason Wang ◽  
Lee Michael Sanders

Background Effective treatment of obesity in children and adolescents traditionally requires frequent in-person contact, and it is often limited by low participant engagement. Mobile health tools may offer alternative models that enhance participant engagement. Objective The aim of this study was to assess child engagement over time, with a mobile app–based health coaching and behavior change program for weight management, and to examine the association between engagement and change in weight status. Methods This was a retrospective cohort study of user data from Kurbo, a commercial program that provides weekly individual coaching via video chat and supports self-monitoring of health behaviors through a mobile app. Study participants included users of Kurbo between March 2015 and March 2017, who were 5 to 18 years old and who were overweight or obese (body mass index; BMI ≥ 85th percentile or ≥ 95th percentile) at baseline. The primary outcome, engagement, was defined as the total number of health coaching sessions received. The secondary outcome was change in weight status, defined as the change in BMI as a percentage of the 95th percentile (%BMIp95). Analyses of outcome measures were compared across three initial commitment period groups: 4 weeks, 12 to 16 weeks, or 24 weeks. Multivariable linear regression models were constructed to adjust outcomes for the independent variables of sex, age group (5-11 years, 12-14 years, and 15-18 years), and commitment period. A sensitivity analysis was conducted, excluding a subset of participants involuntarily assigned to the 12- to 16-week commitment period by an employer or health plan. Results A total of 1120 participants were included in analyses. At baseline, participants had a mean age of 12 years (SD 2.5), mean BMI percentile of 96.6 (SD 3.1), mean %BMIp95 of 114.5 (SD 16.5), and they were predominantly female 68.04% (762/1120). Participant distribution across commitment periods was 26.07% (292/1120) for 4 weeks, 61.61% (690/1120) for 12-16 weeks, and 12.32% (138/1120) for 24 weeks. The median coaching sessions (interquartile range) received were 8 (3-16) for the 4-week group, 9 (5-12) for the 12- to 16-week group, and 19 (11-25) for the 24-week group (P<.001). Adjusted for sex and age group, participants in the 4- and 12-week groups participated in –8.03 (95% CI –10.19 to –5.87) and –9.34 (95% CI –11.31 to –7.39) fewer coaching sessions, compared with those in the 24-week group (P<.001). Adjusted for commitment period, sex, and age group, the overall mean change in %BMIp95 was –0.21 (95% CI –0.25 to –0.17) per additional coaching session (P<.001). Conclusions Among overweight and obese children using a mobile app–based health coaching and behavior change program, increased engagement was associated with longer voluntary commitment periods, and increased number of coaching sessions was associated with decreased weight status.


2019 ◽  
Author(s):  
Victor Cueto ◽  
C Jason Wang ◽  
Lee Michael Sanders

BACKGROUND Effective treatment of obesity in children and adolescents traditionally requires frequent in-person contact, and it is often limited by low participant engagement. Mobile health tools may offer alternative models that enhance participant engagement. OBJECTIVE The aim of this study was to assess child engagement over time, with a mobile app–based health coaching and behavior change program for weight management, and to examine the association between engagement and change in weight status. METHODS This was a retrospective cohort study of user data from <italic>Kurbo</italic>, a commercial program that provides weekly individual coaching via video chat and supports self-monitoring of health behaviors through a mobile app. Study participants included users of <italic>Kurbo</italic> between March 2015 and March 2017, who were 5 to 18 years old and who were overweight or obese (body mass index; BMI ≥ 85th percentile or ≥ 95th percentile) at baseline. The primary outcome, engagement, was defined as the total number of health coaching sessions received. The secondary outcome was change in weight status, defined as the change in BMI as a percentage of the 95th percentile (%BMIp95). Analyses of outcome measures were compared across three initial commitment period groups: 4 weeks, 12 to 16 weeks, or 24 weeks. Multivariable linear regression models were constructed to adjust outcomes for the independent variables of sex, age group (5-11 years, 12-14 years, and 15-18 years), and commitment period. A sensitivity analysis was conducted, excluding a subset of participants involuntarily assigned to the 12- to 16-week commitment period by an employer or health plan. RESULTS A total of 1120 participants were included in analyses. At baseline, participants had a mean age of 12 years (SD 2.5), mean BMI percentile of 96.6 (SD 3.1), mean %BMIp95 of 114.5 (SD 16.5), and they were predominantly female 68.04% (762/1120). Participant distribution across commitment periods was 26.07% (292/1120) for 4 weeks, 61.61% (690/1120) for 12-16 weeks, and 12.32% (138/1120) for 24 weeks. The median coaching sessions (interquartile range) received were 8 (3-16) for the 4-week group, 9 (5-12) for the 12- to 16-week group, and 19 (11-25) for the 24-week group (<italic>P</italic>&lt;.001). Adjusted for sex and age group, participants in the 4- and 12-week groups participated in –8.03 (95% CI –10.19 to –5.87) and –9.34 (95% CI –11.31 to –7.39) fewer coaching sessions, compared with those in the 24-week group (<italic>P</italic>&lt;.001). Adjusted for commitment period, sex, and age group, the overall mean change in %BMIp95 was –0.21 (95% CI –0.25 to –0.17) per additional coaching session (<italic>P</italic>&lt;.001). CONCLUSIONS Among overweight and obese children using a mobile app–based health coaching and behavior change program, increased engagement was associated with longer voluntary commitment periods, and increased number of coaching sessions was associated with decreased weight status.


2021 ◽  
pp. 167-183
Author(s):  
Mark D. Faries ◽  
Alyssa Abreu ◽  
Sarah-Ann Keyes ◽  
Tasnim El Mezain ◽  
Jessica A. Matthews

1974 ◽  
Vol 19 (4) ◽  
pp. 334-334
Author(s):  
ROBERT C. CARSON
Keyword(s):  

2013 ◽  
Author(s):  
Melanie D. Hingle ◽  
Aimee Snyder ◽  
Naja McKenzie ◽  
Cynthia Thomson ◽  
Robert A. Logan ◽  
...  

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Evans K. Lodge ◽  
Annakate M. Schatz ◽  
John M. Drake

Abstract Background During outbreaks of emerging and re-emerging infections, the lack of effective drugs and vaccines increases reliance on non-pharmacologic public health interventions and behavior change to limit human-to-human transmission. Interventions that increase the speed with which infected individuals remove themselves from the susceptible population are paramount, particularly isolation and hospitalization. Ebola virus disease (EVD), Severe Acute Respiratory Syndrome (SARS), and Middle East Respiratory Syndrome (MERS) are zoonotic viruses that have caused significant recent outbreaks with sustained human-to-human transmission. Methods This investigation quantified changing mean removal rates (MRR) and days from symptom onset to hospitalization (DSOH) of infected individuals from the population in seven different outbreaks of EVD, SARS, and MERS, to test for statistically significant differences in these metrics between outbreaks. Results We found that epidemic week and viral serial interval were correlated with the speed with which populations developed and maintained health behaviors in each outbreak. Conclusions These findings highlight intrinsic population-level changes in isolation rates in multiple epidemics of three zoonotic infections with established human-to-human transmission and significant morbidity and mortality. These data are particularly useful for disease modelers seeking to forecast the spread of emerging pathogens.


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