Evidence map›Paper›PMID 41050829›Full record

ArticleExploration of medicine2025

Adherence timescale impacts completion rates of high-frequency mobile cognitive assessments among older adults.

Kieffer Christianson, Meha Prabhu, Zachary T Popp, Md Salman Rahman, James Drane, Marissa Lee, Corinna Lathan, Honghuang Lin, Rhoda Au, Preeti Sunderaraman and 1 more

Abstract read
In one paragraph

Article in Exploration of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Observational
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Kieffer ChristiansonDepartment of Psychology, University of Nevada, Reno, NV 89557, USA.ORCID 0009-0001-5587-7673
Meha PrabhuDepartment of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA.ORCID 0009-0008-3147-4088
Zachary T PoppDepartment of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA.ORCID 0009-0001-7935-5300
Md Salman RahmanDepartment of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA.ORCID 0009-0009-5225-3150
James DraneAnthroTronix, Silver Spring, MD 20910, USA.
Marissa LeeAnthroTronix, Silver Spring, MD 20910, USA.
Corinna LathanAnthroTronix, Silver Spring, MD 20910, USA.
Honghuang LinDepartment of Medicine, UMass Chan Medical School, Worcester, MA 01655, USA.ORCID 0000-0003-3043-3942
Rhoda AuDepartment of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA.ORCID 0000-0001-7742-4491
Preeti SunderaramanDepartment of Psychiatry and Human Behavior, Brown University, Providence, RI 02912, USA.ORCID 0000-0001-6011-8412
Phillip H HwangDepartment of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA.ORCID 0000-0001-6780-6808

Funding

Neuropathology CoreP30AG013846 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI KOWALL, NEIL W. · 1996 to 2020
$29.1M
DANA; A Tool to Detect Cognitive Changes in Pre-clinical and MCI Patients (Admin Supplement)R44AG063635 · NIA · ANTHROTRONIX, INC. · PI LATHAN, CORINNA E · 2019 to 2020
$2.6M
NIA NIH HHS P30 AG013846NIA NIH HHS R44 AG063635
6 · The paper itself

Abstract

Aim: Mobile technology enables frequent, remote cognitive assessments, introducing new methodological opportunities and challenges. The study evaluated the feasibility of a high-frequency cognitive assessment schedule among older adults, in terms of total assessments and adherence to a prescribed schedule. Methods: Thirty-three older adults were recruited from the Boston University Alzheimer's Disease Research Center (mean age = 73.5 years; 27.3% cognitively impaired; 57.6% female; 81.8% White, 18.2% Black). Participants downloaded the DANA Brain Vital mobile application on their own mobile devices during a remote study visit, and were provided a schedule with seventeen assessments to complete over one year at varying frequencies. The first segment contained three subsegments to be completed within one week, the second segment consisted of weekly subsegments spanning three weeks, and the third and fourth segments consisted of monthly subsegments spanning five and six months, respectively. Three adherence types were defined to reflect incrementally broader adherence timescales: subsegment adherence (strict adherence to each prescribed assessment period), segment adherence (completing the required number of assessments within each broader segment), and cumulative adherence (completing the total number of assessments irrespective of timing). Results: Completion rates differed depending on the adherence timescale and corresponding adherence type. Using the strictest adherence definition (subsegment adherence), completion rates declined (from 93.9% to 72.7%, Conclusions: Older adults, including those with cognitive impairment, are able to complete remote cognitive assessments at a high-frequency, but may not necessarily adhere to prescribed schedules. Future high-frequency studies should consider adherence as a potential behavioral variable to complement cognitive test data, while recognizing the potential influence of adherence timescale on interpreting completion rates.

Indexed as

adherenceassessmentcognitivedigitalhigh-frequencylongitudinalremotetimescale

Identifiers

PMID41050829
PMCPMC12494297

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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.