Did Anyone Lose Weight With a Life Coach Reviews
J Med Internet Res. 2018 Mar; 20(iii): e92.
Expert Coaching in Weight Loss: Retrospective Analysis
Monitoring Editor: Gunther Eysenbach
Stefanie Lynn Painter, RD, DHEd, 
# 1 Rezwan Ahmed, PhD,# ane Robert F Kushner, MD,1 James O Hill, PhD,1 Richard Lindquist, Physician,i Scott Brunning, MS,1 and Amy Margulies, RD1
1 Retrofit, Inc, Chicago, IL, The states,
Stefanie Lynn Painter, Retrofit, Inc, 123 North. Wacker Drive, Suite 1250, Chicago, IL, 60606, United States, Phone: i 18007745962, Electronic mail: moc.emtiforter@einafets.
Stefanie Lynn Painter
1 Retrofit, Inc, Chicago, IL, United states of america,
Rezwan Ahmed
1 Retrofit, Inc, Chicago, IL, Us,
Robert F Kushner
1 Retrofit, Inc, Chicago, IL, Us,
James O Hill
i Retrofit, Inc, Chicago, IL, Us,
Richard Lindquist
1 Retrofit, Inc, Chicago, IL, United states of america,
Scott Brunning
1 Retrofit, Inc, Chicago, IL, United States,
Amy Margulies
1 Retrofit, Inc, Chicago, IL, United States,
Received 2017 Dec 27; Revisions requested 2018 Jan 17; Revised 2018 Jan 29; Accustomed 2018 Jan 30.
- Supplementary Materials
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Multimedia Appendix 1.
Retrofit logo.
GUID: 5C411667-851A-4C2D-AA55-5501150886FF
Multimedia Appendix 2.
Features of the Retrofit Weight Loss plan.
GUID: 86AD3A22-7379-4CE7-BBEA-3EC1EA131C33
Abstract
Background
Providing coaches as role of a weight management programme is a common practice to increase participant appointment and weight loss success. Understanding coach and participant interactions and how these interactions impact weight loss success needs to be further explored for coaching best practices.
Objective
The purpose of this study was to analyze the coach and participant interaction in a 6-month weight loss intervention administered by Retrofit, a personalized weight direction and Spider web-based disease prevention solution. The written report specifically examined the association betwixt different methods of coach-participant interaction and weight loss and tried to understand the level of coaching impact on weight loss outcome.
Methods
A retrospective analysis was performed using 1432 participants enrolled from 2011 to 2016 in the Retrofit weight loss program. Participants were males and females aged 18 years or older with a baseline body mass index of ≥25 kg/m², who also provided at least 1 weight measurement beyond baseline. First, a detailed analysis of unlike coach-participant interaction was performed using both intent-to-treat and completer populations. Side by side, a multiple regression analysis was performed using all measures associated with coach-participant interactions involving proficient coaching sessions, alive weekly expert-led Web-based classes, and electronic messaging and feedback. Finally, 3 significant predictors (P<.001) were analyzed in depth to reveal the affect on weight loss upshot.
Results
Participants in the Retrofit weight loss program lost a mean v.14% (SE 0.fourteen) of their baseline weight, with 44% (SE 0.01) of participants losing at least 5% of their baseline weight. Multiple regression model (R 2=.158, P<.001) identified the following superlative 3 measures as significant predictors of weight loss at 6 months: expert coaching session attendance (P<.001), live weekly Web-based class attendance (P<.001), and food log feedback days per calendar week (P<.001). Attending 80% of expert coaching sessions, attending 60% of live weekly Web-based classes, and receiving a minimum of 1 food log feedback day per calendar week were associated with clinically significant weight loss.
Conclusions
Participant's one-on-ane proficient coaching session attendance, live weekly expert-led interactive Web-based class omnipresence, and the number of food log feedback days per week from expert jitney were meaning predictors of weight loss in a 6-month intervention.
Keywords: body mass index, coaching, feedback, obesity, overweight, weight loss, weight reduction programme
Introduction
Worldwide, 1.ix billion adults are classified as being overweight or obese with the United states leading the globe [1,2]. This preventable affliction is considered the commuter of rising wellness care costs, and the almanac directly and indirect health care costs have risen to $ane.42 trillion [2].
In 2014, the direct medical costs of health conditions caused by overweight and obesity amounted to US $427.8 billion [2]. Indirect costs, such as absenteeism or loss of productivity due to disease, totaled US $988.8 billion [2]. With 70.7% of US adults being overweight or obese, employers spend an additional U.s.a. $4000 more than per yr on an employee with obesity than on a healthy weight employee through costs related to health intendance, productivity, and job absence [3-5]. According to the 2017 Employer Health Benefits Survey, 85% of employers provide health and wellness programs to forbid and manage chronic diseases [vi]. Employer-sponsored weight management programs come in a multifariousness of packages, including self-guided, group coaching, and individualized coaching related to activity, nutrition, and behavior alter [7-11].
Weight management programs offering coaches to support participants accept been shown to be more effective in participant engagement and weight loss success [7-nine]. Females are more than successful with weight loss programs that include directly and protocol-driven coaching effectually diet, physical action, and engagement, whereas males tend to underuse coaches [12,13]. However, both males and females do benefit from coaches to increase engagement and weight loss success [ix,12,thirteen].
Offering education around behavior change and accountability for adherence of implementing data learned is 1 do good of providing coaches with weight management programs. Face-to-confront coaching sessions with weekly email contact from a coach was successful in helping participants lose at least 10% of initial trunk weight [14]. Alternatively, offering weekly e-mail behavior coaching and monthly individualized coaching telephone calls has also shown to improve adherence to wellness-related strategies, decrease health gamble factors, and improve weight loss [15-17]. In addition to individualized coaching, weekly behavioral change lessons, weekly individualized self-monitoring feedback, and an Web-based community group accept likewise been shown to increase likelihood of achieving 5% weight loss in 6 months, 10% weight loss in 12 months, and maintenance of weight loss over two years [xi,18,19].
Self-monitoring is important in achieving greater weight loss [20]. Coach-provided individualized feedback around self-monitoring increases consistency in both men and women [twenty]. Personalization proves to be more effective than automated emails providing general wellness information or tips specifically around diet and beliefs [21-24].
The purpose of this study was to analyze the participant and coach interaction in a 6-calendar month weight loss intervention administered by Retrofit (see Multimedia Appendix ane), a personalized weight management and Web-based illness prevention solution. The interactions were evaluated for their association with weight loss to determine the level of impact on predicting weight loss outcomes. Additionally, each type of interaction was evaluated independently to assess the association betwixt the interaction and weight loss to decide best practices for expert coaches.
Methods
Study Blueprint
A retrospective assay was performed to assess the impact of expert coaching during a 6-month weight loss intervention using deidentified data from the Retrofit weight loss programme. Various measures were designed to quantify coach-participant interactions involving i-on-one expert coaching sessions, live weekly expert-led interactive Web-based classes, nutrient and practise log feedback, and electronic messages. All measures were included in a multiple regression assay to predict weight loss during the intervention. Finally, three statistically pregnant (P<.001) expert coaching measures were analyzed in depth to understand the affect on weight loss upshot at 6 months. Western Institutional Review Board granted exemption to the study every bit it is a retrospective assay with no identifiable protected wellness data.
Participants
Participants included paying customers of the Retrofit program who enrolled through an employer-sponsored plan. Employers of participants had selected Retrofit as a subsidized weight management program for employees as part of their employer health benefits package. Customers were considered as eligible participants if they were at least 18 years of age; had a starting trunk mass index (BMI) of ≥ 25 kg/m2; had signed up for the program between September 27, 2011, and December 31, 2016; and had provided at to the lowest degree 1 weight measurement beyond baseline measurement. A participant was considered to have completed the plan if he or she provided a weight measurement at the 6th month of his or her program. A total 1432 customers satisfied all inclusion criteria to be report participants, and 1045 of the participants completed the program. No customer was removed or eliminated from the population due to a lack of weight loss in the plan.
Programme
The Retrofit weight loss program was designed with a 6-calendar month weight loss phase with the option to continue into a maintenance plan called Retrofit Next. The plan (Multimedia Appendix 2) includes one-on-one expert coaching, unlimited passenger vehicle interactions through electronic messaging, lifestyle patterns assessment, and personalized coaching content and program. Expert coaches perform weekly reviews of participants' program and self-monitoring data to provide personalized feedback. Participants have access to an practiced-moderated Spider web-based customs and are encouraged to attend live weekly good-led interactive Spider web-based classes regarding topics of exercise, nutrition, and heed-set. Digital tools, including a mobile app, Web-based dashboard, action tracker, and Wi-Fi calibration, are provided for tracking behaviors related to weight, food, mood, steps, and exercise.
As part of the Retrofit weight loss protocol, all participants are offered 7 ane-on-ane expert coaching sessions, including an initial 60-min session and 30-min follow-upwardly sessions. Coaching sessions were conducted via Web-based video telephone call or mobile phone. All coaching sessions include education effectually the Retrofit philosophy and weight loss guiding principles associated with nutrition, mind-fix, practice, and daily activities. In addition, each coaching session was used for coach-participant collaboration on current and desired health-related behaviors, goal setting to create individualized plans and strategies, and to come to an agreement on how the adept motorbus will hold the participant accountable to agreed-upon plans and strategies.
Participants were encouraged to weigh in, clothing their activity tracker, log all food and beverages consumed, and communicate daily with their practiced coach and in the Spider web-based customs. Retrofit protocol required good coaches to review a participant's nutrient and practice logs, step data, weight data, and progress toward plan goals a minimum of 1 fourth dimension per week to provide personalized feedback. If a participant initiated a coaching conversation, the expert coach was required to reply within 24 hours.
Retrofit adept coaches were employed professionals with a master's or doctorate-level pedagogy in dietetics or nutritional sciences, practise physiology, nursing, health educational activity, counseling, or psychology. Expert coaches were certified in Retrofit'south weight loss protocol and have completed yearly recertification, if applicable.
Measures
Weight
Participants were provided a Wi-Fi-enabled calibration that deeply transmitted weight data over the Net to a Retrofit fundamental data server. Participants' weight data were collected through the use of the provided wireless calibration (92% of recorded weights) or self-reported entry (8%). Self-reported entry was permissible if a participant had difficulty setting upward his or her Wi-Fi calibration. Baseline weight was considered as the first weight measurement received from the participant, which was designated as the recording for week 1. Per centum of baseline weight lost at half dozen months was calculated and used as the master outcome.
Expert Coaching Sessions
Participants were provided 7 one-on-one adept coaching sessions over the half-dozen-month weight loss plan. Percentage of coaching sessions attended at 6 months was calculated to quantify participant's appointment with their coach and used as one of the primary metrics to indicate coaching bear upon on participant consequence. A secondary metric was calculated to measure the total time a participant spent in coaching sessions.
Live Weekly Adept-Led Interactive Web-Based Classes
Participants were provided 26 weekly Web-based classes (1 class per week) where an expert autobus conducted a alive Web-based class on a predetermined topic. Percentage of classes attended at 6 months was calculated to quantify participants' interest in gaining in-depth knowledge on a salubrious lifestyle and weight direction practices. A secondary metric was calculated to capture the total time a participant spent in weekly Web-based classes.
Coach-Participant Conversations
The total number of coach-participant conversations was calculated by counting all electronic letters including coach-initiated conversations, coach responses to participant-initiated conversations, and double-decker feedback on food or practice logs. The total number of coach-participant chat days was calculated by including all days when an practiced bus sent at least one electronic message. The average conversation length per calendar week was calculated by counting the average of total length of all electronic letters (in characters) sent in a week.
To evaluate the bear on of food log feedback on weight loss outcome, we calculated several measures to capture coach-initiated electronic feedback messages that include evaluation and guidance in response to participants' food logs. Total number of nutrient log feedback counts all food log feedback provided by double-decker, which are defined as an adept coach comment written directly on a participant's private food log or weekly diary of food log entries entered through digital tools provided. The full number of food log feedback days was calculated past counting all days with at least ane food log–related feedback from the expert motorbus. The average food log feedback length per week was measured past averaging the total length of all feedback messages (in characters) provided in a calendar week. Like to food log feedback, 3 measures for exercise log feedback were also calculated.
Finally, iii measures were divers to measure out participant engagement with coach. Similar to expert autobus–initiated electronic message measures, the total number of participant-initiated electronic letters, the full number of participant-initiated electronic message days, and the average participant-initiated electronic message lengths per week were calculated.
Statistical Assay
All measures associated with double-decker-participant interactions involving good coaching sessions, weekly Web-based classes, and electronic messaging and feedback were included in a multiple regression analysis to predict weight loss during the six-month intervention. The least informative covariates were successively removed from the model in a stepwise elimination procedure based on the Akaike information criterion [25]. The regression model included only the main furnishings; interactions were across the scope of this assay. In improver, this study focused on analyzing 3 statistically pregnant (P<.001) coaching interactions that were determined to exist significant predictors in a weight loss model.
Information analyses were performed using R version three.ii.3 [26], which included dplyr 0.4.3, ggplot2 2.one.0, data.table 1.9.6, and leaps 2.9 packages. We also conducted t tests of equal variance on continuous variables at baseline and subsequent time points for 2 grouping comparisons. 1-way analysis of variance (ANOVA) was utilized to determine mean differences for greater than 2 group comparisons. Subsequent Tukey tests were conducted to make up one's mind mean differences. Chi-square analyses were performed to determine differences among categorical variables when appropriate. For intent-to-treat (ITT) analyses, we used a last observation carried frontwards imputation approach. Blastoff was set at .05 for all statistical tests to determine statistical significance.
Results
The reported results are based on the retrospective assay evaluating the effect of diverse coach-participant interactions during the Retrofit vi-month weight loss intervention using both the ITT (N=1432) and the completer (n=1045 participants) populations. First, a detailed analysis on different coach-participant interaction measures is provided to sympathise both coach and participant behavior over a half dozen-month weight loss intervention. 2nd, a multiple regression model is presented to capture interaction measures that significantly bear on participant outcome at 6 months, and finally, an in-depth analysis is provided for the top 3 meaning measures.
Baseline Characteristics
Table 1 shows the demographic details at baseline for both ITT and completer populations. Although not clinically meaningful, the completers had higher average age compared with the overall population (45.73 vs 44.39, P=.001). Although at that place are differences in starting weight betwixt completer and noncompleter groups, there are no differences in BMI at baseline between both populations. Furthermore, there are no differences in the male and female distribution among the ITT and completer groups (females: 61% vs 63%, P=.33).
Tabular array 1
Baseline demographics and consequence at six months.
| Baseline demographics | Intent to treat (Due north=1432a), mean (SD) | Completers (northward=1045b), mean (SD) | Noncompleters (n=387c), mean (SD) | P valued |
| Age, years | 44.39 (10.31) | 45.73 (10.10) | 40.79 (10.00) | <.001 |
| Starting weight, kg | 104.76 (22.46) | 103.95 (22.03) | 106.94 (23.45) | .03 |
| Starting body mass alphabetize, kg/k2 | 35.88 (6.56) | 35.82 (6.46) | 36.03 (6.81) | .62 |
Weight Change at half-dozen Months
For ITT population, the average weight loss at 6 months was 5.fourteen% (SE 0.12), and 44% of the participants lost v% or more than of their baseline weight (see Tabular array two). For completers, the average weight loss at half-dozen months was 6.fifteen% (SE 0.17), and 54% of the participants lost five% or more than of their baseline weight. For both ITT and completers, there were no meaning differences between males and females in terms of weight loss percentage or the pct losing 5% or more weight at half dozen months.
Table 2
Weight loss outcomes at 6 months.
| Population | Intent to treat | Completers | |||||
| | north (%) | Weight loss percent, hateful (SE) | Lost 5% or more than of baseline weight, mean (SE) | n (%) | Weight loss percentage, hateful (SE) | Lost 5% or more of baseline weight, mean (SE) | |
| Overall | 1432 (100.00) | five.14 (0.fourteen) | 44 (0.01) | 1045 (100.00) | half-dozen.15 (0.17) | 54 (0.02) | |
| Gender | | | | | | | |
| | Female | 869 (sixty.68) | 5.19a (0.14) | 44b (0.02) | 655 (62.68) | half dozen.00c (0.17) | 52d (0.02) |
| | Male person | 563 (39.32) | 5.06a (0.14) | 43b (0.01) | 390 (37.32) | 6.40c (0.eighteen) | 55d (0.03) |
Agreement Coach-Participant Interaction
The detailed quantitative assay of the interaction between expert coach and participant is presented in Table 3. In general, completers had more than interaction with coaches than the ITT population. The higher percentage of attendance or higher amount of interaction of the completers could be due to length of time actively participating in the weight loss program. Note that the average time in program for the noncompleters was about 3 months (hateful 92.45 days, SE ii.xx). In our assay of the participant behavior below, we will focus on the ITT population.
Table 3
Motorcoach-participant interaction measures at 6 months.
| Interactions | Intent to treat (N=1432), mean (SE) | Completers (due north=1045), mean (SE) | |
| Proficient coaching sessions | | | |
| | Percentage of coaching sessions attended | 75.36 (0.72) | 85.99 (0.61) |
| | Total time spent in coaching sessions, min | 188.34 (1.61) | 211.32 (one.41) |
| Alive weekly expert-led interactive Web-based classes | | | |
| | Percentage of class attended | twoscore.74 (0.83) | 52.92 (0.92) |
| | Total fourth dimension spent in form, min | 546.70 (10.52) | 663.31 (11.81) |
| Passenger vehicle-participant conversations | | | |
| | Number of charabanc messages | 158.91 (ii.36) | 180.00 (2.82) |
| | Number of coach message days | 75.xvi (0.65) | 82.36 (0.65) |
| | Coach message length/week, characters | 1458.34 (13.79) | 1434.34 (xx.94) |
| | Number of nutrient log feedback | 74.91 (1.82) | 89.27 (2.26) |
| | Number of food log feedback days | 31.89 (0.fifty) | 37.01 (0.56) |
| | Food log feedback length/calendar week | 409.29 (half-dozen.69) | 410.05 (7.56) |
| | Number of exercise log feedback | 16.69 (0.32) | 19.21 (0.38) |
| | Number of exercise log feedback days | 12.89 (0.23) | fourteen.6 (0.26) |
| | Exercise log feedback length/week | 187.56 (3.89) | 180.42 (4.22) |
| | Number of participant messages | 48.89 (i.27) | 58.54 (i.60) |
| | Number of participant bulletin days | 29.02 (0.64) | 34.67 (0.77) |
| | Participant bulletin length/week, characters | 399.29 (9.71) | 433.12 (12.37) |
Participants attended 75% of the one-on-one adept coaching sessions. Females attended college percentage of coaching sessions than males (78.37% vs 70.72%, P<.001). Participants attended near 41% of the weekly Web-based classes. There is a gender deviation observed in weekly Spider web-based grade attendance equally females attended significantly higher percentage of classes than males (51% vs 32%, P<.001). Consequently, females spent significantly higher amount of total time (638 min vs 405 min, P<.001) in classes learning about exercise, nutrition, and heed-set behaviors.
Furthermore, coach-participant conversations were reviewed to assess the amount of interactions over the 6-month program. On an average, an expert motorbus reached out to his or her participant with responses, food/exercise log feedback, or general weight management guidelines approximately 75 days within the 6-month plan (about 3 times a week). In general, participants who were more engaged in the programme by initiating more conversations or logged more food/practise logs received college corporeality of communication from coaches. In improver, females received college number of coach messages than males (170.24 vs 141.42, P<.001).
As reported in Table iii, near half of the coach conversations were nutrient log feedback (74.91 out of 158.91 messages). Females received significantly higher number of nutrient log feedback than males (81.96 vs 64.04, P<.001). As females logged a higher number of nutrient logs capturing their daily food intakes, coaches provided a higher corporeality of feedback. Participants either initiated chat or responded to coach messages at to the lowest degree in one case a week (33.28 days) on average. Females sent higher number of letters than males (56.41 vs 37.28, P<.001 ).
Multiple Regression Model for Autobus-Participant Interactions
A multiple regression model was built to predict weight change at 6 months by including all interaction measures related to coaching sessions, weekly Spider web-based classes, and charabanc-participant conversations. In the backward stepwise elimination multiple regression analysis, the final model (R 2=.158, P<.001) included 7 coach-participant interaction measures, in which 6 of the measures were identified every bit statistically significant predictors: percentage of coaching sessions completed (β=−1.05, SE 0.21, P<.001), percentage of grade attended (β=−.76, SE 0.21, P<.001), number of nutrient log feedback days (β=−.92, SE 0.26, P<.001), total number of coach message days (β=.89, SE 0.31, P=.005), coach message length per week (β=.54, SE 0.17, P=.002), and number of participant bulletin days (β=−1.56, SE 0.60, P=.01). The all-time regression model containing vii coach-participant interaction measures is reported in Table 4.
Table 4
Multiple regression models identifying predictors of weight loss at 6 months. Multiple regression model summary: R2=.158; adjusted R2=.152, P<.001.
| Models | Coefficients | ||
| | β ( SE) | t (degrees of freedom=997) | P value |
| Percentage of coaching sessions attendance | −1.05 (0.21) | −4.90 | <.001 |
| Percent of weekly grade attendance | −.76 (0.21) | −iii.66 | <.001 |
| Number of food log feedback days | −.92 (0.26) | −3.50 | <.001 |
| Total number of double-decker message days | .89 (0.31) | two.83 | .005 |
| Coach bulletin length per week | .54 (0.17) | 3.fourteen | .002 |
| Number of participant messages | .95 (0.56) | 1.68 | .09 |
| Number of participant message days | −1.56 (0.60) | −two.59 | .01 |
Significant Weight Loss Predictors: In-Depth Analysis
This department focuses on analyzing iii of the predictors from the terminal regression model in Table iv, which have P<.001: percent of coaching sessions completed, percent of weekly classes completed, and number of nutrient log feedback days. These analyses focus on quantifying different levels of coaching interaction and corresponding weight loss at 6 months to characterize the association with outcome. In addition, average coaching interactions were calculated for participants with different levels of weight loss at half dozen months: lost ≥10% (264/1432, eighteen.44%), lost 5% to 10% (366/1432, 25.56%), and lost <five% (802/1432, 56.01%).
Adept Coaching Sessions
On the ground of the per centum of coaching session attendance data from the 6-month program, a higher percentage of coaching session attendance is significantly associated with a college level of weight loss at six months. Every bit shown in Effigy 1, clinically significant weight loss (5%) was associated with at to the lowest degree lxxx% of coaching session attendance. The results of ane-way ANOVA showed a significant difference of mean weight loss between dissimilar counterbalance-in levels (P<.001). A subsequent Tukey exam confirmed the significant differences among the 80% to 90% and ≥90% attendance levels with the lower 2 levels (P<.001). Similar ANOVA tests were performed on male and female participants separately, and a significant difference in mean weight loss between dissimilar attendance levels was plant (male: P<.001; female person: P<.001).
Weight loss outcomes for different levels of coach-participant interaction.
Further analysis of coaching session attendance of participants with dissimilar levels of weight loss showed that a college coaching session attendance was significantly associated with groups with higher levels of weight loss. Figure two shows a articulate difference in coaching session attendance between loss <5% group and other two groups (P<.001). Both male person and female person participants separately showed a similar significant difference in coaching session attendance.
Interaction levels of participants with different levels of outcome.
Live Weekly Adept-Led Interactive Spider web-Based Classes
As reported in Figure 1, the clan between the percentage of weekly Spider web-based class attendance and weight loss at 6 months is linear where college level of weight loss is significantly associated with higher per centum of class omnipresence. Clinically significant weight loss is associated with at to the lowest degree threescore% of course attendance for overall and both male person and females separately. One way ANOVA and a subsequent Tukey exam confirmed significant mean differences in weight loss among 60% to 80% and ≥80% groups with the remaining levels of class omnipresence (P<.001). The analysis of percentage of class omnipresence of participants with different levels of weight loss showed that a higher grade attendance was significantly associated with groups with higher levels of weight loss. Male and female participants separately showed like significant differences in mean per centum of form attendance between different outcome levels (male: P<.001; female: P<.001).
Food Log Feedback Days
A higher number of food log feedback days per week is significantly associated with higher level of weight loss at vi months. I mode ANOVA test showed a significant hateful difference in weight loss between deviation in food log feedback levels (P<.001). A subsequent Tukey test confirmed significant mean differences between all levels of food log feedback days. Further analysis of food log feedback days of participants with different levels of weight loss showed that higher counts of food log feedback days were significantly associated with groups with higher levels of weight loss (P<.001).
Word
Master Findings
The results provide strong support for expert coaches in weight direction programs. Participants had greater weight loss with a higher attendance of expert coaching sessions and alive weekly expert-led interactive Web-based classes, as well as higher engagement with an practiced autobus through food log feedback. Completers as well had greater interaction and omnipresence than ITT. In a multiple regression analysis, half dozen of the vii interaction measures were identified equally statistically significant predictors of weight loss. In add-on, an in-depth analysis of the meridian iii significant predictors quantified the impact of coaching sessions completed, weekly Spider web-based class omnipresence, and days of receiving nutrient log feedback on varying levels of weight loss. Overall, expert coaches were found to have a high impact on weight direction.
Expert coaches provide guidance and accountability to increase participant engagement and weight loss success, which is supported by previous studies, including website, electronic mail, and/or mobile phone apps, besides equally interventions using but phone calls for coaching [7-9,27]. Still, the participant must exist actively engaged in the programme to receive benefit of the interactions. Quantifying the minimum and maximum level of date for meaning weight loss can bulldoze best practices for weight management expert coaches.
Although consequent self-monitoring is shown to accept a predictive value for weight loss, the challenge is maintaining consistency among participants [20]. Findings support previous studies that personalized feedback and communication from expert coaches tin produce greater appointment in self-monitoring activities when compared with tech-based interventions for self-monitoring without skillful feedback [23,28,29]. We found that expert coaching sessions, alive weekly expert-led classes, and nutrient log feedback specifically increased interaction and accept predictive weight loss values. On the basis of these results, information technology may be important to promote these coach-participant interactions together in an intervention or weight loss programme.
Pregnant Predictors of Weight Loss
Expert Coaching Session Attendance
The percentage of coaching sessions completed was identified as a significant predictor of weight loss (P<.001). Attending fourscore% of the offered coaching sessions is associated with clinically meaning weight loss of 5% or more. Others have shown that weekly to monthly coaching sessions are linked with v% to x% weight loss, improved adherence to health strategies, and decreased chance factors over a six- to 12-month intervention [14-17]. Overall, female participants attended more coaching sessions than male person participants, nonetheless no significant difference was establish in weight loss outcomes. Similar observations were reported in prior studies where male participants did not utilize expert coaches as frequently as female person participants [12,xiii,15].
Live Weekly Adept-Led Interactive Web-based Classes
The percentage of weekly Web-based classes completed was identified as a significant predictor of weight loss (P<.001). Clinically significant weight loss of 5% is associated with at least 60% class omnipresence overall and betwixt male person and females separately. However, form attendance to a higher place threescore% was associated with greater weight loss among all groups. Higher class omnipresence was linked to participants achieving five% to 10% and >ten% weight loss, withal male and female differed in class per centum attendance associated with levels of issue. Males had a significantly lower attendance rate than females, which is historically common in weight loss interventions [12,13,xv].
Nutrient Log Feedback Days
The number of food log feedback days per week was identified every bit a meaning predictor of weight loss (P<.001). Participants receiving food log feedback ane to 2 days per calendar week and ≥2 days per week were associated with clinically significant weight loss of five% or greater. Additionally, participants in the v% to 10% and >10% weight loss levels received more nutrient log feedback days than those in the <5% weight loss level regardless of group. Food log feedback is directly dependent upon the participant's engagement in providing nutrient logs for an good coach to review. Females received a greater corporeality of feedback due to logging a college number of food logs than males, which has been reported in before studies [20]. All the same, this finding is linked to the understanding that personalized feedback increases engagement and weight loss outcomes [22-24].
Strengths and Limitations
This study has several strengths, including the reporting of real-world weight loss outcomes and a focused analysis into adept coaches' role in a weight management program to determine which coach-participant interactions have a significant bear upon on participant success. Participants were existing participants of Retrofit and not recruited or incentivized to participate in the study. All participants who met the starting BMI, age, and weight criteria and provided at least 1 weight measurement beyond baseline were included every bit participants. No participant was removed from the population considering of lack of success on the program, which is an uncommon enquiry do in the weight management field [30]. This report provides further insight on best practices of expert coaches in weight direction interventions and programs. In addition, with the high population of male participants, gender comparisons were reported to create a greater agreement of interaction between male participants and coaches.
The study has limitations, which include the retrospective analysis study design that does not provide whatsoever causal inferences based on the disquisitional observations. Coach-participant interaction was measured from a quantitative signal of view. Also, the use of a existent-earth population does not reveal whether a participant was actively using any other weight direction programme outside of the Retrofit plan components.
Hereafter Inquiry
Retrofit encourages all commercial weight loss programs to publish existent-globe research to enhance the understanding of bus-participant interactions in weight loss programs. Reporting existent-world data in relation to expert coaches allows commercial weight loss program to structure protocols for participant engagement and adherence to weight loss strategies. Past fine-tuning interactions and by understanding how skillful coaches are most effective, commercial weight loss programs will increase capability in overcoming the obesity crisis.
Recommended future enquiry includes an analysis of specific strategies used by expert coaches and their impact on weight loss outcomes, also as a qualitative analysis of the interactions betwixt a autobus and a participant, which may provide more insight into an expert coach's touch on participants. With the connected observation in this study and previous studies that male person participants are less engaged than females, an assay of strategies to increase male date and to understand whether increased engagement improves male weight loss outcomes is recommended. Additionally, further enquiry is needed to analyze coaching bear on on participants' self-monitoring behaviors to decide association between coach-participant interaction and the level of self-monitoring behaviors. Finally, expert coaches' impact beyond an initial 6-calendar month intervention and the impact of each predictor of weight loss on weight maintenance would be a valuable future inquiry report.
Conclusions
In conclusion, participants on the Retrofit weight loss program lost on boilerplate five.xiv% (SE 0.14), and participants who completed the programme lost on average 6.15% (SE 0.17) in 6 months. Over one-half of completers (54%) and 44% of all participants lost 5% or more than of their baseline weight. Coach-participant interactions that include one-on-i expert coaching session attendance, alive weekly expert-led interactive Spider web-based class omnipresence, and food log feedback days per week were shown to exist significant predictors of weight alter at half-dozen months. Specifically, attending 80% or more of offered skilful coaching sessions, attending sixty% or more of offered weekly Web-based classes, and receiving nutrient log feedback one or more than days per week from an expert coach increased participants' weight loss success.
Acknowledgments
Members of the Retrofit Informational Board provided comments and professional insight around the data and results.
Abbreviations
| ANOVA | assay of variance |
| BMI | body mass alphabetize |
| ITT | intent to treat |
Multimedia Appendix 1
Retrofit logo.
Multimedia Appendix two
Features of the Retrofit Weight Loss program.
Footnotes
Conflicts of Interest: SP, RA, SB, and AM are employees of Retrofit, Inc, with equity in the visitor. JH, RK, and RL are agile members of the Retrofit, Inc Advisory Board, with equity in the company.
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Articles from Periodical of Medical Internet Research are provided hither courtesy of Gunther Eysenbach
Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5871741/
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