Dialing In: Effect of Telephonic Wellness Coaching on Weight Loss | Page 2
Published Online: February 25, 2014
Min Tao, PhD; Krishna Rangarajan, MS; Michael L. Paustian, PhD, MS; Elizabeth A. Wasilevich, PhD, MPH; and Darline K. El Reda, DrPH, MPH
Differences in the distribution of demographic characteristics, self-reported chronic disease status, smoking status, and motivation to lose weight at baseline among the study groups were tested using c2 test, while differences in baseline BMI among the groups were tested using ANOVA. Paired t-tests were used to detect whether significant weight changes were reported for each group between baseline and follow-up.
To illustrate the impact of outliers, we reported the 1-year weight change for each group after removing outliers in 2 ways: a) statistically, by calculating upper and lower fences based on mean and standard deviation of the weight changes between T1 and T2 using “outer fence” formula (mean + 4.72* standard deviation),30 and b) by removing 4% of the study population that had more than an 18-kg (40-lb) difference (increase or decrease) in self-reported weight based on health coach suggestions of what constituted a substantial weight change.
The association between self-reported weight change and the wellness coaching program was determined using multivariable linear regression, adjusted for sex, race, education, motivation to lose weight, and comorbidities. P values less than .05 were considered statistically significant. Analyses were performed in SAS 9.2.31
In addition to our primary analyses among targeted members, we also conducted stratified analysis among wellness coaching program participants. We examined the average weight change stratified by: a) wellness coaching objective; b) the number of phone calls with the wellness coach; and c) the initial stage of change. Since wellness coaching participants could establish multiple goals upon program initiation, we applied a hierarchy to make these categories mutually exclusive. The hierarchy was: weight loss > physical activity > nutrition > smoking > others. Due to sample size concerns, the intensity of intervention (ie, number of phone calls the participant received) was dichotomized into 1 to 3 calls and 4 or more calls. Although the program is designed to consist of 4 calls, on rare occasions participants (<1%) may have had more than 4 calls with a health coach if additional coaching was requested by the participant. Participants who received 4 or more phone calls with health coaches were considered program completers. We used a paired t-test to determine whether weight changes were significant for each group between baseline and follow-up, with 95% confidence intervals (CIs) for weight changes were reported.
Demographic Characteristics for Study Population
Table 1 shows the characteristics of the study population. This population was well educated, with 70% of them having had at least some college education. The majority of the population was Caucasian; 55% of the population was male. The distributions of gender, race/ethnicity, and education were not different among the groups. More than 70% of respondents reported having motivation to lose weight in all study groups.
The average age was 45 years or above for all 3 groups, with the group targeted for other WCM programs having the highest average age (50 years). The groups were significantly different in their smoking and chronic disease status. Respondents targeted for other WCM programs had consistently higher rates of diabetes (40%) and asthma (27%) compared with respondents targeted for wellness coaching (12% and 9%, respectively). The group targeted for wellness coaching program had the highest prevalence of ever smoking (smoking sometime during their lifetime, may or may not smoke currently). As expected, the group not targeted for any programs had the fewest risk factors. Overall, the group targeted for wellness coaching was more similar to the group not targeted for any program than to the group targeted for other WCM programs.
Average Weight Change for Intervention and Control Groups
Table 2 provides the changes in self-reported weight between baseline and follow-up at 1 year by group, removing outliers using the 2 methodologies. After excluding 4% of individuals who reported a more than 18-kg (40-lb) weight change between baseline and follow-up, the average weight change was –0.44 kg (95% CI, –0.76 to –0.16) among respondents targeted for wellness coaching and –0.74 kg (95% CI, –1.06 to –0.15) specifically among wellness coaching participants. There was no statistically significant weight loss reported by either comparison group.
Table 3 shows the comparison of weight changes among the groups from the multivariable model. After excluding 4% of respondents who reported more than 18 kg (40 lb) weight changes, respondents targeted for wellness coaching reported –0.59 kg (95% CI, –0.88 to –0.30) more weight loss than respondents not targeted for any program. The unadjusted model and the full model adjusting for age, gender, education, and self-reported comorbidities yielded similar coefficient estimates for being targeted for wellness coaching. The respondents targeted for wellness coaching reported a 0.28-kg greater weight loss than the respondents targeted for other wellness programs, but the difference was not statistically significant.
Stratified Analysis Among Wellness Coaching Program Participants
Table 4 shows the results of average weight change stratified by participants’ goals, number of phone calls between the health coach and the participants, and the participants’ initial stage of changes. Based on the results of the paired t-test, individuals who set goals of weight loss and physical activity benefited most by losing 1.51 kg (P = .001) and 0.99 kg (P = .01), respectively with no significant weight change reported for participants that set other goals. Participants who started in the preparation stage report an average weight change of –1.43 kg (95% CI, –2.17 to –0.68) if they completed the 4 phone calls.
Overweight or obese health assessment respondents targeted for wellness coaching reported an average of .44 kg weight loss, .59 kg more weight loss than health assessment respondents not targeted for any wellness care management programs. Among wellness coaching participants, we observed that individuals who set goals of weight loss and physical activity reported significant weight loss while individuals who chose other health goals did not. Participants who started wellness coaching in the preparation stage and completed the 4-call program reported the most weight loss (–1.43 kg).
The strengths of this study are the large sample size and collection of program participation information among program participants that allowed stratified analysis using factors such as initial stage of change, wellness goals set, and program completion. It is interesting that among participants who began the program in the preparation stage, those who completed all 4 calls reported the most weight loss while those who did not complete the 4 calls reported no significant weight loss. Meanwhile, the weight loss reported by participants who started in the action stage did not differ by whether they completed the 4-call intervention or not. This suggests that if health coaches are able to increase the motivation preparation stage, and provide them necessary tools to act on, these individuals may benefit from the program while participants in other stages may realize little benefit from the program as it is currently designed. Interventions may need greater customization according to the participants’ initial stage of change to maximize program benefits for all participants.
These results should be interpreted conservatively, since this is a retrospective study with limited information collected for the study population. There are many additional unobserved factors could have had an impact on weight loss among program participants. For example, motivated participants might enroll in wellness or weight loss programs in addition to the employer-sponsored and health plan-administered wellness coaching programs. It is unclear whether these unobserved factors were distributed differentially among the groups and whether this impacts the comparison among the 3 groups. Despite the large sample size, another limitation of this study is the generalizability of the findings. Our study population includes commercially insured individuals with education levels higher than those of the general population. The findings may not be generalizable to minority, younger, or less educated populations. Using selfreported weight is another limitation of this study.
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