Evidence map›Paper›PMID 39356682›Full record

ArticlePloS one2024

Predicting adherence to gamified cognitive training using early phase game performance data: Towards a just-in-time adherence promotion strategy.

Yuanying Pang, Ankita Singh, Shayok Chakraborty, Neil Charness, Walter R Boot, Zhe He

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

6 authors.

Yuanying PangSchool of Information, Florida State University, Tallahassee, Florida, United States of America.
Ankita SinghDepartment of Computer Science, Florida State University, Tallahassee, Florida, United States of America.
Shayok ChakrabortyDepartment of Computer Science, Florida State University, Tallahassee, Florida, United States of America.
Neil CharnessDepartment of Psychology, Florida State University, Tallahassee, Florida, United States of America.
Walter R BootDepartment of Psychology, Florida State University, Tallahassee, Florida, United States of America.
Zhe HeSchool of Information, Florida State University, Tallahassee, Florida, United States of America.ORCID 0000-0003-3608-0244

Funding

Using social networks to map and evaluate team science across CTSA hubsUL1TR001427 · NCATS · UNIVERSITY OF FLORIDA · PI MITCHELL, DUANE A. · 2015 to 2024
$37.2M
The Adherence Promotion with Person-centered Technology (APPT) Project: Promoting Adherence to Enhance the Early Detection and Treatment of Cognitive DeclineR01AG064529 · NIA · FLORIDA STATE UNIVERSITY · PI BOOT, WALTER RICHARD, CHAKRABORTY, SHAYOK · 2019 to 2023
$3.2M
NCATS NIH HHS UL1 TR001427NIA NIH HHS R01 AG064529
6 · The paper itself

Abstract

BACKGROUND AND

objectivesThis study aims to develop a machine learning-based approach to predict adherence to gamified cognitive training using a variety of baseline measures (demographic, attitudinal, and cognitive abilities) as well as game performance data. We aimed to: (1) identify the cognitive games with the strongest adherence prediction and their key performance indicators; (2) compare baseline characteristics and game performance indicators for adherence prediction, and (3) test ensemble models that use baseline characteristics and game performance data to predict adherence over ten weeks. RESEARCH DESIGN AND

methodUsing machine learning algorithms including logistic regression, ridge regression, support vector machines, classification trees, and random forests, we predicted adherence from weeks 3 to 12. Predictors included game performance metrics in the first two weeks and baseline measures. These models' robustness and generalizability were tested through five-fold cross-validation.

resultsThe findings indicated that game performance measures were superior to baseline characteristics in predicting adherence. Notably, the games "Supply Run," "Ante Up," and "Sentry Duty" emerged as significant adherence predictors. Key performance indicators included the highest level achieved, total game sessions played, and overall gameplay proportion. A notable finding was the negative correlation between initial high achievement levels and sustained adherence, suggesting that maintaining a balanced difficulty level is crucial for long-term engagement. Conversely, a positive correlation between the number of sessions played and adherence highlighted the importance of early active involvement. DISCUSSION AND IMPLICATIONS: The insights from this research inform just-in-time strategies to promote adherence to cognitive training programs, catering to the needs and abilities of the aging population. It also underscores the potential of tailored, gamified interventions to foster long-term adherence to cognitive training.

Indexed as

CognitionVideo GamesCognitive TrainingHumansMachine LearningPatient Compliance

Identifiers

PMID39356682
PMCPMC11446454

What OpenQuestion holds

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LicenceCC BY
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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.