Evidence map›Paper›PMID 39382561›Full record

ArticleJMIR human factors2024

User-Centered Design for Designing and Evaluating a Prototype of a Data Collection Tool to Submit Information About Incidents of Violence Against Sex Workers: Multiple Methods Approach.

Melissa H Ditmore, Jose Fernando Florez-Arango

Abstract read
In one paragraph

Article in JMIR human factors, 2024. 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

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

1 citing paper in PubMed.

  1. Article
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.

Melissa H DitmoreCUNY School of Public Health and Health Policy, 55 W 125th St, New York, NY, 10027, United States, 1 3475609159.ORCID 0000-0002-1579-5235
Jose Fernando Florez-ArangoCUNY School of Public Health and Health Policy, 55 W 125th St, New York, NY, 10027, United States, 1 3475609159.ORCID 0000-0001-9083-0195

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sex workers face an epidemic of violence in the United States. However, violence against sex workers in the United States is underreported. Sex workers hesitate to report it to the police because they are frequently punished themselves; therefore, an alternative for reporting is needed. Objective: We aim to apply human-centered design methods to create and evaluate the usability of the prototype interface for ReportVASW (violence against sex worker, VASW) and identify opportunities for improvement. Methods: This study explores ways to improve the prototype of ReportVASW, with particular attention to ways to improve the data collection tool. Evaluation methods included cognitive walkthrough, system usability scale, and heuristic evaluation. Results: End users were enthusiastic about the idea of a website to document violence against sex workers. ReportVASW scored 90 on the system usability scale. The tool scored neutral on consistency, and all other responses were positive toward the app, with most being strong. Conclusions: Many opportunities to improve the interface were identified. Multiple methods identified multiple issues to address. Most changes are not overly complex, and the majority were aesthetic or minor. Further development of the ReportVASW data collection tool is worth pursuing.

Indexed as

Data CollectionSex WorkersUser-Centered DesignViolenceFemaleHumansMaleMobile ApplicationsSex WorkUnited Statesabuseaggressionbarrierscognitive walkthroughdata collectiondigital healthenablersheuristic analysisheuristicshuman-centered designimplementationmobile healthoccupational healthprototypereportingsex workerunderreportingusabilityuser-centered design methods

Identifiers

PMID39382561
PMCPMC11481817

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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.