Weight Loss and Engagement in a Tirzepatide-Supported Digital Obesity Program: A Four-Arm Patient-Blinded Retrospective Cohort Study

Abstract

Background:

Obesity is arguably the greatest public health concern in the present day. Digital weight-loss services (DWLSs) that utilize modern medications have demonstrated potential in increasing access to effective obesity treatment. However, the world’s major health institutions emphasize that pharmacotherapy should only ever be used as an adjunct to lifestyle coaching. While recent research has found that patients tend to prefer DWLS lifestyle coaching that is personalized and proactive, the extent to which these preferences impact weight and engagement outcomes is unknown. In addition, previous DWLS studies have only observed interventions supported by Liraglutide and Semaglutide, rather than the most efficacious weight-loss medication, Tirzepatide.

Methods:

This study retrospectively compared 16-week program engagement and weight-loss outcomes in a cohort of 522 patients from the Juniper UK DWLS who received four variants of Tirzepatide-supported lifestyle coaching.

Results:

Over the 16-week study period, the entire cohort averaged 12.91 (±21.99) messages to their health coach. Statistical analyses revealed that the proactive coaching group sent a statistically higher number of messages (M = 19.95) to their health coach than patients from the reactive text (M = 9.8), reactive premium (M = 11.2), and control groups (M = 6.09). Mean weight loss for the entire cohort was 13.8% (±5.04%), with an analysis of variance revealing no significant difference between the four coaching groups. Further analyses revealed that the cohort spent a mean of 55.2 (±22.67) days on the Juniper app and 41.7 (±22.56) days viewing their progress tracker, again without a statistical difference between groups. However, cohort-wide weight loss and health coach engagement were significantly associated with body mass index.

Discussion:

These findings add an important layer to the emerging literature on medication-supported DWLSs. They suggest that app design may be more important than proactive messaging in such services and that Tirzepatide is a more effective supplement to lifestyle coaching than other weight-loss medications in real-world settings.

Introduction

The global obesity rate has more than tripled since the mid-1970s, with approximately 3 billion people currently living with overweight or obesity.¹ Most experts attribute this trend to the disease’s complexity, acknowledging its association with various economic, environmental, social, and neurological factors,^2–4 rather than simplifying it as a question of self-control, as was common in bygone eras.⁵ As a result of this complexity, weight-loss interventions have historically struggled to deliver meaningful and sustainable outcomes to the majority of users.⁶ The difficulty of accessing and adhering to effective weight-loss programs is arguably an underestimated determinant of the world’s rising obesity levels.⁷

Over the past decade, glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have emerged as a promising class of weight-loss medications. Multiple randomized clinical trials have demonstrated their unprecedented efficacy in both diabetic and nondiabetic populations.^8–10 In some of these trials, mean weight loss has been above 20% of baseline weight in under 18 months.^11,12 The most common explanation for this discovery is that GLP-1 RAs address the neurological component of obesity by regulating the neural pathways involved in satiety and the food-reward feedback loop.^13,14 However, many influential commentators are concerned that these medications are being viewed as a panacea to excess weight, rather than as a tool to support lifestyle modifications.^15–16 Indeed, the world’s leading health institutions, such as the World Health Organization (WHO) and the National Institute for Health and Care Excellence (NICE), stress that in the treatment of obesity, GLP-1 RAs should only ever be used as an adjunct to lifestyle therapy.^17,18 These institutions also emphasize that obesity programs should be continuous and guided by a coordinated multidisciplinary team (MDT).

Although this treatment protocol should not be questioned, the challenges of accessing and adhering to ongoing lifestyle therapy in traditional care settings are considerable. First, people with significant work or family commitments typically struggle to coordinate and travel to regular and ad hoc consults with their MDTs—a barrier that has arguably been exacerbated by increasing general practice wait times in the United Kingdom in recent years.^7,19 Second, many people with overweight or obesity (PWOO) perceive their condition to be stigmatized and feel less comfortable discussing it in face-to-face (F2F) settings.^7,20 Furthermore, some PWOO have reported that their general practitioners have been unable to provide comprehensive lifestyle therapy or refer them to a clinician who can.⁷ And finally, many PWOO live too far away from allied health clinicians to be able to reasonably access quality obesity care.^21,22

In recent years, many digital weight-loss services (DWLSs) have emerged as a solution to these common obesity care access issues. DWLSs can mitigate the psychological and geographical barriers to obesity care by removing the need for F2F contact. The temporal barrier to obesity care is also overcome by the digital mode of delivery and is typically furthered by the common DWLS option of asynchronous consults, that is, consults that do not occur in real time. However, the quality spectrum of DWLSs is broad. While some DWLSs comply with WHO and NICE recommendations by delivering comprehensive lifestyle coaching through MDTs, others provide little more than access to GLP-1 RA scripts without any follow-up consults and thus confirm the concern among various health stakeholders about pharmacotherapy’s promotion as a panacea to weight management.²³ This concern is arguably compounded by the scarcity of research on unsubsidized GLP-1 RA-supported DWLSs. At the time of writing, only a handful of quantitative studies have been published on services of this description, including discrete effectiveness and adherence studies on Australian and British cohorts whose lifestyle coaching was supplemented with Liraglutide and Semaglutide, respectively.^23–26 Although these studies made some promising discoveries, multiple questions need to be addressed before GLP-1 RA-supported DWLSs are globally embraced. Among these questions are whether Tirzepatide (a dual glucose-dependent insulinotropic polypeptide/GLP-1 RA) is a more effective supplement to lifestyle coaching than Liraglutide and Semaglutide in real-world digital settings, as it has proven to be in subsidized clinical trials. Another important question is the extent to which lifestyle coaching design has an impact on unsubsidized medication-supported DWLSs. A previous mixed-methods study found that patients of these services tend to prefer a coaching style that is relatively personalized and proactive.²⁷

This study aims to assess the extent to which various lifestyle coaching methods impact the effectiveness of and engagement levels with a nonsubsidized Tirzepatide-supported DWLS in the United Kingdom, Juniper. By generating foundational findings on both lifestyle coaching method and the most advanced weight-loss medication, it is believed that the study will contribute vital knowledge to the fledgling literature on real-world DWLSs.

Methods

Study design

A four-arm patient-blinded retrospective design was used to achieve the aims of the investigation. Each phase of the study followed the Strengthening the Reporting of Observational Studies in Epidemiology guidelines. The study’s ethics were approved by the Bellberry Limited Human Ethics Committee on November 22, 2023 (No. 2023-05-563-A-1).

Program overview

The Juniper UK DWLS has been delivered exclusively through an app-based platform since its launch in 2021. Prospective patients complete an online preconsultation questionnaire, containing over 100 questions about their health background. A pharmacist reviews responses and typically requests further information such as test results, photos, and medical imagery to determine program eligibility. Decisions follow Medicines and Healthcare products Regulatory Agency (MHRA) guidelines for Mounjaro (Tirzepatide) and consider body mass index (BMI) ranges, contraindications such as medullary thyroid carcinoma, and drug interactions such as concomitant use with insulin.^28,29 Eligible patients who pay their first monthly subscription fee of 209 GBP (rising to 249 GBP when patients reach the higher Tirzepatide doses of 12.5 and 15 mg) are allocated an MDT consisting of a pharmacist, a university-qualified dietitian or nutritionist, and a nurse. Every communication between patients and their MDTs is automatically stored in an encrypted central data repository on Metabase to maximize care continuity. Access to the repository is limited to MDTs and the Juniper UK data analytics team. Patients are required to read an information sheet on GLP-1 RA side effects before they consent to the program and are instructed to report any adverse events to their MDT as soon as they arise. All patients are sent a standardized set of Bluetooth digital scales to track their weight, which the company manufactures itself through a partner in Hong Kong.

Under the standard Juniper UK DWLS, health coaches forward patients a lifestyle plan based on their health profile and responses to a short lifestyle quiz. The lifestyle quiz assesses patient competency with resistance training, aerobic exercise, and nutrition knowledge. Upon receiving their lifestyle plan, patients are also sent an automated message that explains how they can engage with the Juniper app and optimize program outcomes. Patients can request amendments to their lifestyle plan at any stage of their care journey; however, they are not prompted to consider any changes until their first compulsory follow-up consult at 6 months (clinicians can request earlier consults at their discretion). Similarly, patients can ask their health coach questions at any time during their subscription but are never prompted to seek advice or update progress through the app’s “Action” or weight trackers. “Actions” are micro diet and exercise goals organized into challenge pillars that are supported by various forms of educational material. Patients are organized into different levels of the challenge pillars based on their baseline exercise competency as presented in the lifestyle quiz. The only ‘prompt’ standard Juniper patients receive is an app notification to complete a fortnightly check-in questionnaire that solicits their satisfaction with the program and progress and offers them another opportunity to report adverse events. However, patients do not need to complete check-in questionnaires as a requirement of their program, and no reminder messages are sent beyond the initial prompt. Lifestyle coaching under the standard Juniper DWLS is therefore “reactive.”

In February 2024, the Juniper UK DWLS decided to test the potential program engagement benefits of slight variations to the service’s lifestyle coaching model. This test was motivated by the finding from an internal analysis that many patients were not tracking their weight and Actions frequently and, therefore, arguably not engaging with the program enough to maximize its potential. Accordingly, Juniper UK health coaches devised three alternative coaching models to compare with the standard one, which was used as the control group. The first of these alternatives (reactive text group) received the standard coaching model plus a message from their health coach after one week on the program, which encouraged patients to track Actions through the app and comment on their early experience. The second intervention group (reactive premium group) received the standard lifestyle coaching model and a video message from their health coach after one week on the program, delivering the exact same content as the text-based message, along with a link to a lifestyle plus quiz, which coaches used to develop lifestyle plans with a higher level of personalization. And the final intervention group received proactive lifestyle coaching with several distinctive features. These features included an introductory video and link to the lifestyle plus quiz (same as the Reactive premium group) and message prompts every 3 days to set or update Actions (accountability dates for each action) and complete fortnightly check-in questionnaires. Patients in all four groups had their lifestyle coaching supplemented with Tirzepatide (Mounjaro). Titration schedules followed MHRA guidelines as follows: 2.5 mg once weekly for weeks 1–4; 5 mg once weekly for weeks 5–9; 7.5 mg for weeks 10–14; and 10 mg thereafter. Patients were not informed that they were taking part in the internal experiment, because Juniper UK program designers reasonably deduced that the three coaching models they were testing would not generate inferior outcomes to the standard (control) model. Accordingly, all patients were blinded to their group allocation.

Participants

The first 852 patients who subscribed to the Juniper UK service in February 2024 were allocated on a 1-1-1-1 basis to one of four lifestyle coaching arms. This number was determined by the number of patients (213) that the Juniper UK coaching team could reasonably manage under the proactive protocol. Patients in any arm who failed to submit 16-week follow-up weight data between 100 and 120 days after program commencement were excluded from the analysis.

Measures

The study’s primary end-points included mean weight-loss percentage from baseline to 16-week follow-up and the mean number of patient messages to their MDT. Secondary end-points included the proportion of patients who reached 5%, 10%, and 15% weight-loss milestones and the mean number of days over the study period when patients opened the program app, opened the goal tracker feature, played a minimum of 80% of an educational video, and submitted weight data. For both the opening of program app and goal tracker features, data were only captured if patients had the respective pages open for a minimum of 5 sec.

Statistical analyses

The only primary end-point that was categorical was the proportion of patients who achieved the 5%, 10%, and 15% milestones. A chi-square test was used to test this end-point’s difference across the four groups. All other primary end-points were continuous, and thus, an analysis of variance (ANOVA) was used to determine their association with health coaching style. Various statistical analyses were conducted to test for correlation between all the engagement measures and weight-loss percentage, along with the association between demographic data (age, BMI, gender, and ethnicity) and the three primary end-points. Pearson tests were used when examining the relationship between continuous exploratory and dependent variables, such as age and weight-loss percentage. Two-sample t-tests were conducted to assess the correlation between two-level categorical exploratory variables and continuous dependent variables, such as gender and the number of sent messages. ANOVA was used to observe potential links between continuous dependent variables and categorical exploratory variables with three or more levels, such as BMI categories. In cases where dependent data were non-normally distributed, ANOVA, Pearson correlation tests, and two-sample t-tests were replaced by their nonparametric equivalents as follows: Kruskal–Wallis tests, Spearman correlation tests, and Mann–Whitney U tests, respectively. All statistical analyses and visualizations were performed on RStudio (version 2023.06.1 + 524).

Results

Of the 852 patients who were assigned to one of the four groups in the internal experiment, 248 discontinued the program before the week-16 follow-up consultation, and 82 failed to submit data within the specified 100- to 120-day window. Specifically, 60 patients from the control group discontinued the program before their week-16 consultation, 59 from the reactive text group, 73 from the reactive premium group, and 56 from the proactive coaching group. Thirty-one patients from the control group failed to submit data within the specified period,18 from the reactive text group, 19 from the reactive premium group, and 14 from the proactive group. Subsequently, a total of 522 patients were included in the final analysis, of whom 91.57% were female and 89.27% were of Caucasian ethnicity (Table 1). Mean cohort age was 44.94 (±10.44) years, and mean initial BMI was 35.7 (±6.81) km/m². Follow-up weight data were submitted at a mean of 111.78 (±5.11) days after program initiation.

Table 1.

Baseline Characteristics

Demographic Information	Mean (SD)
Age	44.94 (±10.44) years
Gender	Number (%)
Female	478 (91.57)
Male	44 (8.43)
Ethnicity	Number (%)
Caucasian	466 (89.27)
Asian, including subcontinent	32 (6.13)
Black African of African Caribbean	19 (3.64)
Latino/Hispanic	9 (1.72)
Rather not say	7 (1.34)
Middle Eastern	4 (0.76)
Clinical information	Mean (SD)
BMI	35.7 (±6.81) kg/m²
Weight	99.49 (±19.81) kg

BMI, body mass index; SD, standard deviation.

Mean 16-week weight loss for the entire cohort was 13.79% (±5.04) with an ANOVA revealing that the differences between each coaching group (Control = 13.8%; Reactive text = 14.1%; Reactive premium = 13.9%; and Proactive = 13.4%) were not statistically significant (F[3,518] = 0.47, p = 0.71). In terms of weight-loss milestones, 97.13% of the cohort achieved meaningful (≥5%) weight loss, and a chi-square test showed no significant differences between any of the coaching groups, X²(3, n = 522 = 0.32, p = 0.96). Following this trend, 75.67% and 40.04% of the full cohort lost at least 10% and 15% of baseline weight, respectively, with no statistically significant between-group differences observed (≥10%: X²[3, n = 522 = 0.48, p = 0.92]) (≥15%: X²[3, n = 522 = 1.18, p = 0.76]) (Fig. 1).

FIG. 1.

Proportion of patients who achieved weight-loss percentage milestones by health coaching group.

Over the 16-week study period, patients sent their health coach a mean of 12.91 (±21.99) messages, with a Kruskal–Wallis test detecting a statistically significant difference between the four groups, (X²[3, n = 522 = 73.12, p < 0.001]). A pairwise post hoc Dunn’s test revealed that differences existed between all groups except between the two reactive coaching groups. Median group scores were as follows: Proactive = 13.5; Reactive premium = 8; Reactive text = 5; and Control = 3 (Table 2) (Fig. 2).

FIG. 2.

Number of patient messages sent to their health coach by coaching group.

Table 2.

Post Hoc Dunn Test Results—Message Frequency by Coaching Group

Levels	Z-score	p
Control—Proactive	−8.45	<0.001^***
Control—Reactive text	−2.82	<0.01^**
Proactive—Reactive text	5.45	<0.001^***
Control—Reactive prem	−3.65	<0.001^***
Proactive—Reactive prem	3.97	<0.001^***
Reactive text—Reactive prem	−1.04	0.3

p < 0.01.

***

p < 0.001.

Across the full cohort, patients opened the app 55.2 (±22.67) days and the goal tracker 41.7 (±22.56) days; played educational videos 5.09 (±3.94) days; and submitted weight data on 36.94 (±23.04) days, on average, during the 16-week period. ANOVA tests found no statistically significant difference between groups in any of these markers (app: F[3,518] = 1.47, p = 0.22); goal tracker: (F[3,518) = 1.36, p = 0.25]); videos: (F[3,518] = 2.45, p = 0.06); and weight data: (F[3,518] = 1.23, p = 0.3).

Two-sample t-tests revealed that weight-loss percentage was not significantly impacted by gender (t[54.59] = 0.95, p = 0.35) or the binary ethnicity variable ([t56] = 1.97, p = 0.05), which was created due to the low representation of non-Caucasian patients. Pearson correlation tests found that weight-loss percentage was significantly associated with BMI (r[520]= −0.21, p < 0.001), but not with age (r[520] = −0.01, p = 0.33). To gain a more meaningful understanding of the relationship between BMI and weight loss, 4 BMI categories were created, and ANOVA (F[3,518] = 11.08, p < 0.001) and post hoc Tukey tests were conducted (Table 3). The latter revealed that patients with a BMI of 40 (Mean = 11.81) or more lost significantly less weight than patients from all other categories (BMI 35–39.99 kg/m²: mean weight = 13.42; BMI 30–34.99 kg/m²: mean weight = 14.96; BMI 27.5–29.99 kg/m²: mean weight = 14.36) (Fig. 3).

FIG. 3.

Sixteen-week weight-loss percentage by BMI category. BMI, body mass index.

Table 3.

Post Hoc Tukey Test Results—Weight Loss Frequency by BMI Category

Levels	Mean difference	p
30–34.99:27.5–29.99	0.6	0.77
35–39.99:27.5–29.99	−0.94	0.50
40 and over:27.5–29.99	−2.67	<0.001^***
35–39.99:30–34.99	−1.53	0.03
40 and over:30–34.99	−3.27	<0.001^***
40 and over:35–39.99	−1.72	0.03^*

p < 0.05.

***

p < 0.001.

In regard to the effect of program engagement on weight loss, three moderate and statistically significant associations were found. Pearson correlation tests revealed that weight loss was significantly impacted by the total number of days patients opened the Juniper app (r[520] = 0.3, p < 0.001) and the Action progress tracker (r[520] = 0.35, p = <0.001) and by the total number of days in which they uploaded weight data (r[520] = 0.3, p < 0.001). After inserting these three engagement markers and the weight loss variable in a regression model, a Durbin–Watson test was conducted to assess autocorrelation. The result of 0.85 indicated that errors from the three engagement markers were not independent of one another.

Mann–Whitney U tests found that the number of messages patients sent to their health coach did not correlate with gender (W = 694, p = 0.47) or the binary ethnicity variable (W = 10,358, p = 0.28). A Spearman correlation test revealed that the number of messages patients sent to their health coach was not associated with their age (r[520] = 0.04, p = 0.3). Similarly, a Kruskal–Wallis test revealed that a patient’s BMI category did not influence their message rate (X²[3, n = 522 = 4.58, p = 0.21]).

A total of 376 (72.03%) patients reported at least one side effect, with 65.24% of all reported events being of mild severity, 27.4% of moderate severity, and 7.36% considered severe (Table 4). An ANOVA found that between-group differences in side effect incidence were not statistically significant, F(3,518) = 0.83, p = 0.48. Across the entire cohort, gastrointestinal issues were the most commonly reported side effect (63.8%) followed by headaches (15.13%) and bouts of fatigue or dizziness (13.9%).

Table 4.

Side Effects

	Number (% of cohort)
Gastrointestinal issues	312 (63.8)
Headaches	74 (15.13)
Fatigue or dizziness	68 (13.9)
Other	35 (7.16)
Total patients with at least one side effect	376 (72.03)
	Number (% of total reported side effects)
Mild side effects	319 (65.24)
Moderate side effects	134 (27.4)
Severe side effects	36 (7.36)

Side effect type by severity level—number (% of total number of side effect type)	Mild	Moderate	Severe
Gastrointestinal issues	203 (65.06)	89 (28.53)	20 (6.41)
Headaches	35 (47.3)	31 (41.89)	8 (10.81)
Fatigue or dizziness	53 (77.94)	11 (16.18)	4 (5.88)
Other	28 (80)	3 (8.57)	4 (11.43)

Discussion

This study aimed to assess the extent to which various lifestyle coaching methods impacted effectiveness and app engagement levels with the Juniper UK DWLS. Previous research had demonstrated that GLP-1 RA-supported DWLSs such as Juniper have the potential to significantly improve care access and outcomes to PWOO relative to traditional weight-loss services.^7,23,25,30 It had also discovered that patients of such services tend to prefer proactive and highly personalized lifestyle coaching rather than the more reactive and standardized models that are becoming an industry norm.²⁷ No study had hitherto investigated whether these preferences translate into meaningful differences in weight loss or program engagement outcomes. Moreover, no previous study had assessed any outcomes from a DWLS that supplemented lifestyle coaching with the most efficacious weight-loss medication observed in clinical trials, Tirzepatide.

The analysis found no significant difference between the four study groups in any of the weight-loss end-points (mean score and milestone distributions). From an engagement perspective, patients from the proactive coaching group sent, on average, significantly more messages to their health coach than patients from all other groups. The mean total message figure of the proactive group (19.95) more than doubled that of patients from the control (6.09) and reactive text groups (9.8). Although the analysis did not detect a correlation between mean total messages and weight-loss percentage, this may have been due to the study’s relatively short duration. Future research should attempt to run comparable experiments for longer periods.

The finding that total patient messages did not correlate with weight-loss percentage could also be interpreted in several other ways. First, it may reflect the fact that patients from the reactive and control groups were satisfied with the information they received from their initial program and the limited number of questions they may have posed in response to that information. Second, as the results from other correlation tests (app use, goal tracker use, and weight data submission) suggest, it may be an indication that certain DWLS engagement tools are more important than messaging frequency after a certain number of communications. And finally, the finding might simply reflect the diversity of personality types among PWOO, with some people preferring more frequent MDT contact than others. Nevertheless, it can be loosely concluded that proactive coaching through the Juniper UK DWLS elicits higher patient-coach engagement, which, in turn, does not appear to have any impact on weight-loss outcomes.

Arguably the most significant findings generated from the study are those pertaining to cohort-wide engagement. Over the 16-week study period, patients averaged 55.2 (±22.67) days of Juniper app engagement, 41.7 (±22.56) days of goal tracker engagement, and 36.94 (± 23.04) days of weight data submissions. These figures translate to app usage more than every other day and tracker usage and weight data submissions more than every third day. In terms of patient messages to their health coach, the cohort mean of 12.91(±21.99) messages over 16 weeks (111.78 days) converts to one message every 8.66 days. However, while the proactive group figure converts to one message every 5.6 days, the control group mean 6.09 (±8.42) days translates to one message every 18.35 days. WHO and NICE stress the importance of continuous MDT care in obesity programs.^17,18 Although neither institution proffers a benchmark for obesity care continuity, it is hard to imagine a F2F obesity service providing a comparable level of engagement. These findings add to those generated in a previous study of the Juniper UK DWLS and the foundational literature on care continuity in digital chronic care services.²⁵

Mean cohort-wide weight loss of 13.79% (±5.04) after 16 weeks is also a significant figure. Perhaps even more notable was that 97.13% of the cohort achieved meaningful (>=5%) weight loss. Nonmedicated DWLSs have historically struggled to deliver such outcomes to significant proportions of their user base. Although DWLSs that supplement lifestyle coaching with GLP-1 RAs such as Liraglutide and Semaglutide have reported meaningful weight loss for over 75% of their study cohorts,^23,25,30 the figure in this study (which ran for a shorter period than those referenced) is considerably higher. Given that side effect incidence was comparable to Liraglutide- and Semaglutide-supported cohorts,^23,25 this study’s weight-loss findings suggest that Tirzepatide may have an important role to play in DWLS design and the global struggle against obesity in general.

The final full-cohort discovery of significance was that mean weight loss for patients from the highest BMI category (BMI ≥ 40 kg/m²: mean weight loss = 11.81) was roughly 3 percentage points lower than patients from the lowest two BMI categories (BMI 30–34.99 kg/m²: mean weight loss = 14.96; BMI 27.5–29.99 kg/m²: mean weight loss = 14.36) and significantly lower than the other BMI category (BMI 35–39.99 kg/m²: mean weight = 13.42). This finding is relatively consistent with that of a recent study of a Semaglutide-supported Juniper Germany DWLS cohort.³⁰ Future research should seek to assess whether this trend persists across other DWLSs and consider a qualitative study of patients from higher BMI groups to explore the possibility of unique barriers to DWLS effectiveness.

The study had several limitations. First, the sample was predominantly Caucasian and female and thus unrepresentative of the United Kingdom’s diverse population. Second, the study’s outcomes may have been different if it had run for longer than 16 weeks. Third, as the experiment was designed to replicate the Juniper UK experience as accurately as possible and, thus, enforce no extra data entry requirements for program continuation other than those for 6-month follow-up consultations, no data were available for the 248 (29.11%) of the 852 patients who discontinued the program before the 16-week mark. In addition to this limitation, no discontinuation reason data were collected. Previous dedicated adherence studies of the Juniper DWLS have found that extrinsic factors such as GLP-1 RA supply, program cost, and or personal weight-loss expectations (met or unmet) have been the most common discontinuation reasons.^24,26 However, it is possible that the main discontinuation factors for this cohort were very different. Future research should compare the discontinuation intervals and reasons for Tirzepatide-supported DWLSs with services supplemented with other GLP-1 RAs. Furthermore, although patients were all sent the same set of Bluetooth scales, weight data were patient-reported and may have been impacted by various biases and/or weighing strategies. And finally, the design of the two reactive coaching models was arguably too similar to generate meaningful disparities between those groups’ outcomes, differing only in the delivery medium of introductory material. This arguably missed an opportunity to test whether the removal of different app features, such as the Action tracker, had a significant effect on outcomes.

Conclusions

Previous research had suggested that the early potential displayed by medication-supported DWLSs could be maximized by increasing the level of personalization and ‘proactivity’ in the service’s lifestyle coaching component and using the most efficacious weight-loss medication, Tirzepatide. This study found that proactive coaching group patients engaged much more frequently with their health coach than patients from the control and reactive coaching groups, but no significant between-group difference in weight-loss outcomes. Mean 16-week weight loss for the entire cohort was 13.79% (±5.04) with 97.13% of the cohort losing a meaningful (≥5%) amount of weight. However, cohort-wide weight loss was significantly associated with BMI and days spent on the app, tracking goal progress, and uploading weight data. These findings suggest that Tirzepatide is a more effective supplement to lifestyle coaching than other weight-loss medications in real-world settings and that app design may be more important than proactive messaging in DWLSs. Future research should further explore the link between BMI and effectiveness in GLP-1 RA-supported programs and compare Tirzepatide-only interventions with Tirzepatide-supported DWLSs.

Footnotes

Acknowledgments

The authors thank all patients, clinicians, and auditors involved in the Juniper weight-loss program over the study period.

Authors’ Contributions

Conceptualization: L.T., T.G., and M.V. Methodology: L.T., T.G., M.V., and C.B. Validation: L.T., T.G., and M.V. Formal analysis: L.T. and T.G. Investigation: L.T. Resources: T.G. and C.B. Data curation: L.T., T.G., and C.B. Writing—original draft preparation: L.T. Writing—review and editing: L.T., M.V., and C.B. Supervision: L.T. and C.B. Project administration: L.T., T.G., and C.B. Visualization: L.T. Software: L.T. All authors have read and agreed to the published version of the article.

Author Disclosure Statement

L.T., M.V., C.B., and T.G. are paid a salary by Eucalyptus (Juniper parent company).

Funding Information

This research received no external funding.

Supplementary Material

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