---
type: source
title: "Noom GLP-1 Engagement Report: 2.2x Longer Persistence for High-Engagement Users (January 2026 Analysis)"
author: "Noom (internal engagement report, published February 4, 2026)"
url: https://www.noom.com
date: 2026-02-04
domain: health
secondary_domains: []
format: report
status: null-result
priority: medium
tags: [glp1, adherence, behavioral-wraparound, digital-health, noom, engagement, persistence]
extraction_model: "anthropic/claude-sonnet-4.5"
---

## Content

Noom Engagement Report (January 2026 analysis, published February 4, 2026):

**Sample:** 30,239 members for persistence analysis; 14,203 for weight loss metrics. Cohort: started GLP-1 programs December 2024–February 2025.

**Methodology:** Members stratified into engagement quartiles by app opens (capped at 20/day).
- Bottom quartile (Q1): 244.7 app opens
- Top quartile (Q4): 2,162.2 app opens
- Statistical significance confirmed (p < 0.001)

**Persistence outcomes:**
- Top engagement quartile persisted on GLP-1 medication 2.2x longer than bottom quartile within first 12 months
- Q1 (lowest engagement): 2.8 months median persistence
- Q4 (highest engagement): 6.2 months median persistence

**Weight loss outcomes:**
- Top quartile lost 25.2% more weight at week 40 vs. bottom quartile
- Absolute difference: approximately 8.3 additional pounds

**Retention signal:**
- Day-30 engagement: 40% of December cohort returned on day 30 (claimed 10x higher than digital health app average)

**Noom GLP-1 product suite:**
1. GLP-1 Companion: behavioral support layer for people already prescribed GLP-1s elsewhere
2. GLP-1Rx (Microdose program): Noom prescribes medication + behavioral program, starting at $119/month
3. Components: AI food logging, medication tracking, side effect support, body composition scanning, glucose forecasting, muscle preservation ("Muscle Defense"), gamification

**PDURS positioning:** Noom updated GLP-1 Companion to prepare for FDA's expected Prescription Drug Use-Related Software (PDURS) framework — attempting to position as regulated software companion to GLP-1 prescriptions.

**Explicit limitation noted by Noom itself:**
"These findings reflect observational analyses and report associations/correlations, not proof that engagement causes improved outcomes." Reverse causality acknowledged: people doing well on medication may engage more with app.

## Agent Notes
**Why this matters:** The 2.2x persistence improvement for high-engagement vs. low-engagement users is the clearest engagement dose-response signal in the behavioral wraparound literature. Noom is unusual in explicitly noting the reverse causality caveat in their own report.

**What surprised me:** That Noom acknowledged reverse causality in their own internal analysis. Most company reports present favorable data without explicitly flagging the confound. This is either genuine methodological integrity or savvy pre-emption of criticism.

**What I expected but didn't find:** Any randomized comparison of high vs. low engagement (randomizing app access to test causal effect). This doesn't exist from Noom. Also no post-discontinuation data — Noom only reports persistence ON medication, not maintenance after stopping.

**KB connections:**
- Behavioral adherence thread (this session)
- GLP-1 persistence data (14.3% two-year adherence baseline from Sessions 20-22)
- Digital health intervention effectiveness claims

**Extraction hints:**
- The 2.2x persistence finding is extractable as an observational signal, but confidence should explicitly acknowledge the reverse causality problem
- More useful as a data point in a broader behavioral wraparound claim than as a standalone
- The PDURS positioning is separately interesting for the regulatory/atoms-to-bits boundary claims — Noom is explicitly trying to convert a behavioral app into regulated prescription software

**Context:** Noom is a commercial digital health company with significant GLP-1 market aspirations. The $119/month price for their microdose program is substantially cheaper than branded GLP-1s alone. They have financial incentives to show engagement drives outcomes.

## Curator Notes (structured handoff for extractor)
PRIMARY CONNECTION: Behavioral wraparound for GLP-1 adherence; digital health intervention effectiveness
WHY ARCHIVED: Provides engagement dose-response data for the behavioral wraparound claim; the reverse causality acknowledgment is noteworthy as methodological transparency
EXTRACTION HINT: Use as one of 4-5 behavioral wraparound data points, noting the reverse causality caveat. The PDURS positioning detail is separately interesting for regulatory/digital health extractor.
