Evidence map›Paper›PMID 42871603›Full record

ArticleMethodsX2026

DECIDE-CTA: A designer-empowered method for creating structured cognitive task analyses from product instructions.

Janell S Joyner, Monifa Vaughn-Cooke

Abstract read
In one paragraph

Article in MethodsX, 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

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

2 authors.

Janell S JoynerDepartment of Mechanical Engineering, James A. Clark School of Engineering, University of Maryland at College Park, College Park, 8228 Paint Branch Dr, MD, 20742, United States.
Monifa Vaughn-CookeDepartment of Health Systems and Implementation Science, VT Carilion School of Medicine, Virginia Tech, 2 Riverside Circle, Roanoke, VA, 24016, United States.

Funding

FDA HHS U01 FD004320
6 · The paper itself

Abstract

Designers are required to perform human factors testing to demonstrate that their product is safe to use before it reaches the market, which includes identification of potential use errors. While this evaluation often focuses on physical tasks, many errors are driven by cognition. Cognitive Task Analysis (CTA) offers a structured method to expose the cognitive processes that shape physical actions, enabling deeper identification of tasks to evaluate. However, existing CTA methods were developed for cognitively trained experts, making them difficult for most design teams to apply. To improve accessibility, the underlying structure of existing CTA methods was combined with (a) embedding of discrete cognitive tasks within psychomotor information-processing sequences, (b) human-machine interaction principles, and (c) syntactic task guidance. This new framework empowers designers to incorporate cognitive depth into their product development considerations and risk assessments. The method, DECIDE-CTA (Designer-Empowered Cognitive Integration for Decomposition and Evaluation), was created by following the steps outlined below:•Develop a cognitive-psychomotor unified model, accessible to designers for CTA generation (Phases 1 and 2).•Create Task Categories linking designer knowledge to the cognitive-psychomotor unified model (Phase 3).•Create rule-based cognitive sentence syntaxes and CTA templates for describing the tasks and ordering the information within a CTA (Phase 4).

Indexed as

Cognitive taxonomyFormative testingHuman factorsHuman-machine interactionInformation processing modelsPsychomotor taxonomyRisk mitigationSentence syntaxSummative testingUse error

Identifiers

PMID42871603
PMCPMC13659902

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.