Evidence map›Paper›PMID 42607057›Full record

ArticlePLOS digital health2026

DOSE: An open-source, iOS watch-based tool for experience sampling.

Ian Kim, Sahiti Kunchay, Saeed Abdullah, David E Conroy

Abstract read
In one paragraph

Article in PLOS digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ian KimDepartment of Kinesiology, Penn State University, University Park, Pennsylvania, United States of America.ORCID https://orcid.org/0000-0003-0818-3692
Sahiti KunchayDepartment of Psychiatry, Yale University, New Haven, Connecticut, United States of America.
Saeed AbdullahCollege of Information Sciences and Technology, Penn State University, University Park, Pennsylvania, United States of America.
David E ConroyDepartment of Kinesiology, Penn State University, University Park, Pennsylvania, United States of America.

Funding

Penn State Clinical and Translational Science InstituteUL1TR002014 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI KRASCHNEWSKI, JENNIFER L. · 2016 to 2025
$33.7M
Roybal Center for Promoting Adherence to Behavior Change and Enhancing Cognitive FunctionP30AG086637 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DAVID E. CONROY · 2024 to 2026
$2.9M
NCATS NIH HHS UL1 TR002014NIA NIH HHS P30 AG086637
6 · The paper itself

Abstract

Smartwatches facilitate low-burden rapid-access micro-interactions, making them ideal for Experience Sampling Methods (ESMs). Despite the Apple Watch being the most popular smartwatch in the U.S., its broad use in ESM studies has been limited by a lack of accessible frameworks that enable deployment without technical expertise. We developed DOSE, an open-source ESM framework tailored for the Apple Watch. It includes tools and documentation that allow researchers to configure surveys, build custom apps, deploy studies, and stream data to servers with minimal familiarity with Xcode and iOS development workflows. We evaluated the framework's feasibility in a 28-day field study with 18 participants (mean age = 55.3 ± 9.2). Results showed reliable prompt delivery; middle-aged and older adults achieved median survey completion rates of 69% and 88% during watch wear periods, median device access times of 9 and 9.5 seconds, and median total response times of 22 and 29 seconds, respectively. Participants generally demonstrated increasing efficiency in responses over time. These findings establish the DOSE framework as a practical, feasible solution for Apple Watch-based ESMs and a foundation for future smartwatch research.

Identifiers

PMID42607057
PMCPMC13480617

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.