Evidence map›Paper›PMID 38839708›Full record

ArticleJournal of general internal medicine2025

User-Centered Design of a Preference-Driven Patient Activation Tool for Optimizing Depression Treatment in Integrated Primary Care Settings (The Transform DepCare Study).

Katherine L Dauber-Decker, Maria A Serafini, Rachel Monane, Lisa Grossman Liu, Alyssa Sales, Jennifer Mizhquiri Barbecho, Meredith E Diamond, Sera Levy, D 'Arcy King, Thomas McGinn and 2 more

Abstract read
In one paragraph

Article in Journal of general internal medicine, 2025. 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

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Katherine L Dauber-DeckerNorthwell, New Hyde Park, NY, USA.
Maria A SerafiniCenter for Behavioral Cardiovascular Health, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.
Rachel MonaneHealth Design Lab, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA, USA.
Lisa Grossman LiuDepartment of Pediatrics, University of California San Francisco, San Francisco, CA, USA.
Alyssa SalesDepartment of Medicine, University of California San Francisco, San Francisco, CA, USA.
Jennifer Mizhquiri BarbechoCenter for Behavioral Cardiovascular Health, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.
Meredith E DiamondCenter for Behavioral Cardiovascular Health, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.
Sera LevyDepartment of Psychology, State University of New York at Buffalo, Buffalo, NY, USA.
D 'Arcy KingDepartment of Clinical Psychology, Fielding Graduate University, Santa Barbara, CA, USA.
Thomas McGinnMedicine Department, Baylor College of Medicine, Houston, TX, USA.
Suzanne BakkenColumbia University School of Nursing, Columbia University Irving Medical Center, New York, NY, USA.
Nathalie MoiseCenter for Behavioral Cardiovascular Health, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA. Nm2562@cumc.columbia.edu.ORCID 0000-0002-5660-5573

Funding

AHRQ HHS R01 HS025198AHRQ HHS R01HS025198
6 · The paper itself

Abstract

backgroundFew patient engagement tools incorporate the complex patient experiences, contexts, and workflows that limit depression treatment implementation.

objectiveDescribe a user-centered design (UCD) process for operationalizing a preference-driven patient activation tool.

designInformed by UCD and behavior change/implementation science principles, we designed a preference-driven patient activation prototype for engaging patients in depression treatment. We conducted three usability cycles using different recruitment/implementation approaches: near live/live testing in primary care waiting rooms (V1-2) and lab-based think aloud testing (V3) oversampling older, low-literacy, and Spanish-speaking patients in the community and via EHR algorithms. We elicited clinician and "heuristic" expert input. MAIN MEASURES: We administered the system usability scale (SUS) all three cycles and pre-post V3, the patient activation measure, decisional conflict scale, and depression treatment barriers. We employed descriptive statistics and thematically analyzed observer notes and transcripts for usability constructs.

resultsOverall, 43 patients, 3 clinicians, and 5 heuristic (a usability engineering method for identifying usability problems) experts participated. Among patients, 41.9% were ≥ 65 years old, 79.1% female, 23.3% Black, 62.8% Hispanic, and 55.8% Spanish-speaking and 46.5% had ≤ high school education. We described V1-3 usability (67.2, 77.3, 81.8), treatment seeking (92.3%, 87.5%, 92.9%), likelihood/comfort discussing with clinician (76.9%, 87.5%, 100.0%), and pre vs. post decisional conflict (23.7 vs. 15.2), treatment awareness (71.4% vs. 92.9%), interest in antidepressants (7.1% vs. 14.3%), and patient activation (66.8 vs. 70.9), with fewer barriers pertaining to cost/insurance, access/coordination, and self-efficacy/stigma/treatment efficacy. Key themes included digital literacy, understandability, high acceptability for aesthetics, high usefulness of patient/clinician videos, and workflow limitations. We adapted manual entry/visibility/content; added patient activation and a personalized algorithm; and proposed flexible, care manager delivery leveraging clinic screening protocols. DISCUSSION: We provide an example of leveraging UCD to design/adapt a real-world, patient experience and workflow-aligned patient activation tool in diverse populations.

Indexed as

DepressionPatient ParticipationPatient PreferenceUser-Centered DesignAdultAgedDelivery of Health Care, IntegratedFemaleHumansMaleMiddle AgedPrimary Health Carebehavioral cardiologydepressionimplementation scienceintervention

Identifiers

PMID38839708
PMCPMC11861791

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.