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Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/105583, first published .
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Peer Referral Pathways and 6-Month Outcomes in a Tirzepatide-Supported Digital Weight Loss Service: Retrospective Cohort Study

Peer Referral Pathways and 6-Month Outcomes in a Tirzepatide-Supported Digital Weight Loss Service: Retrospective Cohort Study

1Department of Clinical Research, Eucalyptus Health, Level 3, 155 Clarence Street, Sydney, New South Wales, Australia

2Department of Medicine, Stanford University Medical Centre, Stanford, CA, United States

Corresponding Author:

Louis Talay, PhD


In a retrospective analysis of 34,449 adults using an unsubsidized, tirzepatide-supported digital weight loss service (DWLS) in Australia, patients entering via peer referral showed higher 6-month program adherence and greater percentage weight loss than propensity score–matched nonreferred patients, suggesting that peer referral pathways may support retention and effectiveness in medicated obesity care.

J Med Internet Res 2026;28:e105583

doi:10.2196/105583

Keywords



The real-world effectiveness of modern weight loss medications, such as tirzepatide and semaglutide, depends heavily on medication adherence and sustained behavioral modification [1]. Recent studies have demonstrated that 6- and 12-month adherence rates in real-world tirzepatide-supported obesity programs are generally low [2,3]. While digital weight-loss services (DWLSs) deploy algorithmic nudges and multidisciplinary coaching to drive retention, external sociopsychological factors, such as preexisting peer support networks, are frequently overlooked [4]. Behavioral medicine frameworks suggest that patients entering interventions via social referrals benefit from built-in accountability and shared social proof, which can mitigate the attrition commonly observed in remote care [5,6]. However, the specific impact of peer-to-peer referral pathways on adherence and objective weight loss metrics within a medication-supported DWLS remains unquantified. This study evaluated the programmatic persistence and 6-month percentage weight loss of referred vs nonreferred patients receiving tirzepatide treatment via an Australian DWLS.


Background

This retrospective cohort study examined deidentified data from the Juniper (Eucalyptus Health) DWLS data repository on Google BigQuery. Patients were included if they initiated a tirzepatide treatment pathway between May 20 and December 2, 2025. Juniper patient eligibility is determined by doctors and nurse practitioners in accordance with Therapeutic Goods Administration guidelines for obesity treatment. Once accepted, patients communicate with prescribing clinicians, health coaches, and medical support staff via the Juniper app. All patient data are stored in the Juniper data repository, including weight data, which are submitted by patients via Bluetooth smart scales or manual input on the Juniper app.

The study cohort was stratified into referred patients and nonreferred patients. Referral was implemented as a tracked marketing mechanism using invitation links that existing patients could share with others. When a new patient enrolled via this link, the referrer and referee received a discount of AUD $75 (AUD $1=US $0.65 as of December 1, 2025) on 2 of their upcoming tirzepatide orders. The referral program did not include an in-app chat function or a peer-support group. Order costs ranged from AUD $449 to $855 (depending on tirzepatide dose) over the study period.

Adherence Criteria

Program adherence at 6 months was operationalized using 2 measures:

  • Medication adherence: fulfillment of 5 or more orders within 183 days of program initiation.
  • Per-protocol persistence: submission of at least 1 verified body weight entry within a strict window of day 173 to day 193 postinitiation.

Covariates

To isolate the independent effect of peer referral on mean 6-month percentage weight loss, propensity score matching (PSM) was implemented. Referred patients with a minimum 6-month program tenure were matched 1:1 with nonreferred controls using a nearest-neighbor algorithm based on age, sex at birth, ethnicity, baseline BMI, comorbidity count, previous tirzepatide/semaglutide use, and first order price. Differences in adherence rates were evaluated using Pearson χ2 tests, and matched weight loss outcomes were compared via independent t tests. For differences in ordinal variables such as comorbidity count, we used a Wilcoxon rank sum test. To account for multiple statistical testing across baseline characteristics and outcome metrics, P values were adjusted using the Benjamini-Hochberg false discovery rate procedure. Statistical analyses were performed in RStudio (version 2023.06.1; Posit PBC), with significance set at P=.05.

Ethical Considerations

The Stanford University Institutional Review Board determined that this study did not constitute human subjects research (protocol 82970, October 22, 2025).


The full cohort comprised 2576 referred and 31,873 nonreferred patients. Age, BMI, and ethnicity distributions were similar between groups (Table 1). However, the referred cohort organically exhibited a significantly higher concentration of male patients (592/2576, 23%) than the nonreferred cohort (2486/31,873, 7.8%) (P<.001) and a lower prevalence of prior tirzepatide/semaglutide use (438/3576, 17%) than the nonreferred cohort (7331/31,873, 23%) (P<.001).

Table 1. Baseline characteristics of adults enrolled in an Australian tirzepatide-supported digital weight loss service by referral status (referred vs nonreferred), May-December 2025.
VariableReferred cohort (N=2576)Nonreferred cohort (N=31,873)Adjusted P
(FDR)a
Sex at birth, n (%)<.001
Female1984 (77)29,387 (92.2)
Male592 (23)2486 (7.8)
Ethnicity binary, n (%).17
White2128 (82.6)26,040 (81.7)
Non-White448 (17.4)5833 (18.3)
Initial BMI, mean (SD)33.5 (5.27)33.3 (5.49).16
Age category, n (%).20
Under 30 years314 (12.2)4474 (14)
30‐44 years1249 (48.5)14,907 (46.8)
45‐59 years848 (32.9)11,072 (34.7)
60+ years165 (6.4)1420 (4.5)
Total comorbidities, n (%).05
0 complications1571 (61)18,486 (58)
1 complication799 (31)10,200 (32)
2 complications154 (6)2550 (8)
3+ complications52 (2)637 (2)
Prior tirzepatide/semaglutide use, n (%)<.001
Yes, prior history438 (17)7331 (23.0)
Subscription plan, n (%).14
Standard monthly1958 (76)25,179 (79)
Bundled package618 (24)6694 (21)
Month 1 weight track count, n (%).16
Baseline only108 (4.2)1787 (5.6)
2‐5 entries693 (26.9)7885 (24.7)
6‐10 entries446 (17.3)6271 (19.7)
11‐15 entries513 (19.9)5688 (17.8)
16‐25 entries374 (14.5)5302 (16.6)
>25 entries442 (17.2)4940 (15.5)
Financial markers (median).30
First-order price ($ AUDb)385390

aFDR: false discovery rate.

bAUD $1=US $0.65 as of December 1, 2025.

A total of 9508 (27.6%) patients met the study’s 6-month adherence criteria (Table 2). Of the remaining 24,941 patients, 10,318 (30%) failed to receive at least 5 tirzepatide orders, while 14,623 (42.4%) met this criterion but failed to submit data within the specified window. Referred patients achieved significantly higher 6-month medication adherence (≥5 orders) than nonreferred patients (1236/2576 [48%] vs 13,387/31,873 [42%]; P<.01). This adherence disparity was maintained under the per-protocol persistence criteria, with 35% of referred patients sustaining medication compliance and submitting data within the 6-month weight window versus 27% of the nonreferred cohort (P<.01). Following 1:1 PSM to control for baseline imbalances (n=804 matched pairs), all mean SDs had values <0.10, indicating good covariate balance. Referred patients achieved a mean weight loss of 16.2% (SD 6.2%) compared to 14.1% (SD 6.5%) in the matched nonreferred control group (P<.001).

Table 2. Six-month medication adherence and clinical weight loss outcomes among adults in the Juniper Australia tirzepatide-supported digital weight loss service in the nonreferred (propensity score–matched) cohort, May-December 2025.
Evaluation metricReferred cohortNonreferred cohortEffect size (95% CI)Adjusted P value
(FDRa)
Per protocol adherence matrixn=902n=8606ORb=0.99 (0.91‐1.07).78
6-month matched weight loss (PSMc)n=804n=804—d—
 Mean percentage weight loss, % (SD)16.2% (6.2%)14.1% (6.5%)Difference=2.10 (1.56‐2.64)<.001
 Achieved ≥5% total weight loss, n (%)756 (94%)724 (90%)OR=1.74 (1.20‐2.52).01
 Achieved ≥10% total weight loss, n (%)675(84%)535 (66.5%)OR=2.63 (2.07‐3.34)<.001
 Achieved ≥15% total weight loss, n (%)498 (62%)386 (48%)OR=1.76 (1.45‐2.15)<.001

aFDR: false discovery rate.

bOR: odds ratio.

cPSM: propensity score matching.

dNot applicable.


In this retrospective analysis of a tirzepatide-supported DWLS, patients entering via peer referral were more likely to remain engaged in the program and, in PSM analyses, had higher observed 6-month percentage weight loss than nonreferred patients (16.2% vs 14.1%). These findings are preliminary but suggest that peer referral networks may have an important role in supporting retention and effectiveness in unsubsidized, medication-supported DWLSs.

Notably, the referral pathway was associated with a shift in participant demographics, particularly in the higher male representation (23% vs 7.8%). As men are traditionally underrepresented in weight management services [7], peer referral mechanisms may offer a promising approach to engage this group. However, further work is needed to understand underlying motivations and barriers.

This work has several limitations. Its retrospective, observational design limits causal inference, and although PSM was used to reduce demographic variability, residual confounding by unmeasured variables (eg, intrinsic motivation, socioeconomic status, or social network structure) is likely [8,9]. The analysis of weight outcomes in a per-protocol framework introduced survivorship bias and may overestimate effects relative to a broader DWLS population. Additionally, all weight data were self-reported and were therefore susceptible to error and social desirability bias. Finally, this study reflects a single commercial, unsubsidized Australian DWLS, which may limit generalizability to other health systems or populations. The observed associations cannot disentangle tirzepatide’s direct pharmacological effects from digital support components or social factors related to referral.

Despite these constraints, the data suggest that peer referral pathways may improve program persistence and weight loss within a medicated DWLS. Prospective studies are needed to clarify mechanisms, confirm reproducibility, and determine how best to operationalize peer networks to enhance retention and outcomes in obesity care.

Acknowledgments

Generative AI was not used in any portion of the manuscript generation.

Funding

The authors declared no financial support was received for this work.

Data Availability

The datasets generated or analyzed during this study are not publicly available due to privacy or ethical restrictions but are available from the corresponding author on reasonable request.

Authors' Contributions

Conceptualization: LT, JH, NA

Data curation: LT, LS, JH, MT

Formal analysis: LT, LS, JH, MT

Funding acquisition: NA

Investigation: LT, LS, JH, MT

Methodology: LT, LS, JH

Project administration: LT, LS

Supervision: LT, LS

Validation: JH, MT

Visualization: LT, LS, JH

Writing – original draft: LT, LS, JH

Writing – review & editing: LT, JH, MT

Conflicts of Interest

LT and LS are paid employees at Eucalyptus Health (Juniper's parent company), while NA is a paid advisor at the company. JH and MT declare no conflicts of interest.

  1. Aronne LJ, Sattar N, Horn DB, et al. Continued treatment with tirzepatide for maintenance of weight reduction in adults with obesity: the SURMOUNT-4 randomized clinical trial. JAMA. 2024;331(1):38-48. [CrossRef]
  2. Hankosky ER, Chinthammit C, Meeks A, et al. Real-world use and effectiveness of tirzepatide among individuals without type 2 diabetes: results from the Optum Market Clarity database. Diabetes Obes Metab. May 2025;27(5):2810-2821. [CrossRef] [Medline]
  3. Talay L, Hom J, Scott T, Ahuja N. Effectiveness and adherence in a tirzepatide-supported digital weight-loss programme in Australia: a real-world observational study. Diabetes Obes Metab. Apr 2026;28(4):2835-2848. [CrossRef] [Medline]
  4. Johnson H, Huang D, Liu V, Ammouri MA, Jacobs C, El-Osta A. Impact of digital engagement on weight loss outcomes in obesity management among individuals using GLP-1 and dual GLP-1/GIP receptor agonist therapy: retrospective cohort service evaluation study. J Med Internet Res. Mar 31, 2025;27:e69466. [CrossRef] [Medline]
  5. Wing RR, Phelan S. Long-term weight loss maintenance. Am J Clin Nutr. Jul 2005;82(1 Suppl):222S-225S. [CrossRef] [Medline]
  6. Gerhardt U, Kreuzenbeck C. Strategies to improve treatment adherence of digital health applications—rapid review and mixed-method analysis. AI Soc. 2026. [CrossRef]
  7. Regan CP, Morgan PJ, Hardacre SL, et al. Men’s representation in behavioral weight loss trials: a systematic review. Obes Rev. May 31, 2026:e70170. [CrossRef] [Medline]
  8. Patrick H, Williams GC. Self-determination theory: its application to health behavior and complementarity with motivational interviewing. Int J Behav Nutr Phys Act. Mar 2, 2012;9(18). [CrossRef] [Medline]
  9. Greaves CJ, Sheppard KE, Abraham C, et al. Systematic review of reviews of intervention components associated with increased effectiveness in dietary and physical activity interventions. BMC Public Health. Feb 18, 2011;11(119). [CrossRef] [Medline]


‎
DWLS: digital weight loss service
PSM: propensity score matching


Edited by Amaryllis Mavragani; submitted 25.Jun.2026; peer-reviewed by Peng Liu, Zhao Liu; final revised version received 09.Sep.2026; accepted 09.Sep.2026; published 28.Sep.2026.

Copyright

© Louis Talay, Laura Swinckels, Jason Hom, Marilyn Tan, Neera Ahuja. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 28.Sep.2026.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.