Is Loam meditation app free?

Yes. Loam is free to download and free to start. Core tools like breathing exercises, journaling, daily check-ins, and streak tracking are always available at no cost. Premium unlocks the full guided session library, unlimited custom Moments, and advanced features.

What makes Loam different from Calm or Headspace?

Loam composes every session around how you feel right now — the voice, the pace, and the therapeutic approach all adapt in real time. Instead of a catalog of pre-recorded tracks, Loam generates a new meditation tailored to your current emotional state, calibrated to your experience level, and grounded in peer-reviewed research. It also ships with Sage, a wellness coach trained in Motivational Interviewing, and 15 breathing exercises with haptic-synced animations.

Is Loam safe to use alongside therapy or medication?

Yes. Loam is designed with clear clinical guardrails. Sessions never claim to diagnose or treat mental illness, never tell you to stop therapy or medication, and always defer to professional care for symptoms that warrant it. Content is constrained to evidence-based techniques (ACT, self-compassion, MBSR, somatic experiencing, CBT-I) and a carefully reviewed voice and pacing library. Meditation is a complement to care, not a replacement. If you're in crisis, please contact a local crisis line or your care provider.

What research is Loam based on?

Every therapeutic technique in Loam cites primary peer-reviewed research. Loam's breathing library is grounded in work by Balban et al. (Stanford, 2023), Zaccaro et al. (2018), and Lehrer & Gevirtz (2014). The Moment's therapeutic architecture draws on polyvagal theory (Porges), ACT (Hayes), self-compassion (Neff), MBSR (Kabat-Zinn), and somatic experiencing (Levine). A full citation library is available at /research.

Who are the voices in Loam?

Loam uses 13 research-selected voices. Each voice is chosen for the emotional state it handles best, based on polyvagal theory, ASMR research, and voice psychology — low resonant voices for grounding, warm bright voices for light moods, measured voices for heavy ones. Loam automatically picks the voice the research says will work for your current state, or you can override manually.

Does Loam work offline?

Core tools work offline, including downloaded meditations, breathing exercises, and the journal. The Moment — Loam's custom meditation composer — requires an internet connection at the moment of generation, because the session is composed on the fly. Once generated, every Moment is saved to your library and can be replayed offline without using any credits.

Does Loam have sleep stories?

Yes. Loam includes narrated sleep stories, sleep soundscapes, and wind-down rituals. The sleep content uses anti-storytelling techniques — structured to prevent the mind from latching on to narrative — based on CBT-I stimulus control research (Bootzin & Epstein, 2011).

What breathing exercises does Loam offer?

Loam offers 15 breathing techniques across beginner, intermediate, and advanced tiers, including Box Breathing (4-4-4-4), 4-7-8 Relaxation, the Physiological Sigh, Coherent (Resonance) Breathing at 5.5-5.5, Alternate Nostril, Ujjayi, Kapalbhati, and the Wim Hof method. Every technique links to the peer-reviewed research that validates it, so you can read the study if you want to.

Will I lose my streak if I miss a day?

No. Loam's streak system is explicitly wellness-first: streaks pause, they don't break. You get two streak freezes, you can mark rest days, and the app never shames you for missing a session. Anxious users are especially vulnerable to streak mechanics turning self-care into another source of pressure — Loam is designed to avoid that failure mode.

DATA

Every claim cited · Every technique peer-reviewed

Meditation app adherence, by the numbers.

Name: Loam
Availability: InStock
Author: Loam

This is a synthesis of the published research on who actually keeps using meditation apps — and who drops off. We did not run the studies; we read them, compared the numbers, and wrote down what seems to hold up across the literature.

Updated April 2026·9 min read

By Loam EditorialUpdated April 2026

The meditation-app category has a visible retention problem. App store ratings are high; long-term use is low. That gap is well-documented in the research, but the specific numbers are scattered across dozens of small trials and a few larger meta-analyses. This page compiles what we think is the most reliable public picture as of 2026 — including the parts that are inconvenient for us as an app-maker.

The short version

Across peer-reviewed trials, typical eight-week meditation-app interventions show session-completion rates well below 100% — roughly half of assigned content is a common finding, with wide variance by study design and population.
Dropout is heaviest in the first two weeks and flattens after that. People who reach a regular rhythm in weeks 3–4 tend to keep using the app.
Studies that paid participants or embedded apps in clinical contexts report higher adherence than naturalistic in-the-wild use.
Meaningful mental-health effects in the published meta-analyses are small-to-moderate and tend to correlate with amount of practice completed, not with assignment to an app.

A note on our claims

Loam's content is grounded in peer-reviewed research where it exists, and clearly flagged when it doesn't. We're a wellness app, not a clinic — for diagnosed conditions, please work with a qualified clinician. Read our editorial methodology for how we decide what to publish.

Where these numbers come from

The two most-cited pieces of evidence on digital mindfulness interventions are Goldberg et al.'s 2022 meta-analysis of mindfulness-based app interventions, and the broader meta-analytic work on mHealth mental-health interventions by Firth et al. (2017) and successors. These papers collate effect sizes and, where reported, adherence. Individual randomized trials — e.g. Flett et al. on university students and Huberty et al. on Calm — are where the more granular usage data lives.

The picture that emerges from these sources is less flattering than the app-marketing picture, but more useful. The effects are real; they're also conditional on actually using the app.

What the adherence numbers look like

Across published RCTs of meditation apps, the proportion of assigned sessions that participants actually complete varies substantially. A reasonable summary of the pattern we observed reading the literature:

Clinical samples, supervised delivery (e.g. cancer survivors with staff check-ins): adherence often reaches 70–80% of assigned content.
Unsupervised adult users in an 8-week RCT: completion of around half of assigned sessions is typical.
University-student samples (often the most-studied population): highly variable, with some studies reporting median completion in the low single digits of sessions.
Real-world app usage outside a trial: published analyses of anonymized app telemetry — when companies share it — suggest steeper fall-off than any trial population, with a large share of downloads never translating into a second session.

These are ranges rather than exact percentages because each study's operational definition differs. “Completion” means different things in different trials — starting a session vs. finishing a session vs. hitting a 90% playback threshold. We are skeptical of any single headline retention number that doesn't specify which of those is being measured.

The first-two-weeks pattern

The most consistent adherence signal across trials is the shape of the curve. Dropout is concentrated in the first 14 days. People who reach a regular rhythm in weeks 3–4 are substantially more likely to still be using the app at week 8.

Mechanistically this is what you'd expect from habit-formation research more broadly. Early practice competes with existing routines; once the practice is connected to an existing anchor — getting into bed, commute start, post-coffee pause — it stops competing and starts riding on existing cues. We designed The Moment and the guided programs around that model rather than around a 30-day streak ladder.

Effects scale with practice, not assignment

The published effect sizes on anxiety and stress from meditation-app RCTs cluster in the small-to-moderate range — typically somewhere around Cohen's d = 0.3 for stress, smaller for anxiety. But within-study analyses consistently find that the effect is concentrated among participants who actually practiced. Low-adherence participants often show effect sizes indistinguishable from control.

That's the honest interpretation of the research for users choosing an app: the category works, but only if you use it. Most of the variation in outcome across people comes from variation in practice completion, not from which app they downloaded. This is why our comparisons pages (/compare) push so hard on “pick the one you'll actually open on a Wednesday night.”

Why marketed retention numbers are hard to trust

App companies occasionally publish retention or “active user” numbers in press releases. These numbers are almost always selected from the tail of highly-engaged users and don't correspond to any standard published metric. Where a company reports peer-reviewed results, those are closer to the truth; marketing collateral is not.

We deliberately don't publish headline retention numbers for Loam. Our honest position: the research on our category says long-term use is hard, and there's no reason to believe any specific app has solved it. What we can commit to is that every technique in Loam ties back to a primary research source and is chosen because it has a fair evidence base — not because it has the best-looking chart.

Practical takeaways

If you're starting a meditation app, give yourself two weeks before judging whether it's working. The dropout cliff is real; plan for it.
Anchor practice to something you already do — waking up, lying down in bed, the end of lunch. Don't rely on motivation.
Pick an app whose default session length fits your actual schedule, not your ideal schedule. Short sessions completed beat long sessions skipped.
If you stop for a week, you haven't failed. Start again. The published effects accrue from cumulative practice, not from unbroken streaks.

Methodology & corrections

This page is a reading of the public literature as of April 2026. We did not run statistical analyses on raw trial data; we read the peer-reviewed papers and the most-cited meta-analyses and wrote down the patterns that held up across them. We'll revise this page when meaningful new meta-analyses or app-company peer-reviewed studies land.

If you spot an error or a study we've missed — particularly newer work we should incorporate — our methodology page describes how to flag it.