Evidence map›Paper›PMID 36506382›Full record

ArticleHeliyon2022

Designing pain visualisation for caregivers of people with special needs: A co-creation approach.

H Korving, P S Sterkenburg, E I Barakova, L M G Feijs

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 39% of its field
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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. 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

4 authors at 2 institutions in 1 country.

H KorvingDepartment of Behavioral and Movement Sciences, Clinical Child and Family Studies, Amsterdam Public Health, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT, Amsterdam, the Netherlands.
P S SterkenburgDepartment of Behavioral and Movement Sciences, Clinical Child and Family Studies, Amsterdam Public Health, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT, Amsterdam, the Netherlands.
E I BarakovaDepartment of Industrial Design, Future Everyday Group, Eindhoven University of Technology, Groene Loper 3, 5612 AE Eindhoven, the Netherlands.
L M G FeijsDepartment of Industrial Design, Future Everyday Group, Eindhoven University of Technology, Groene Loper 3, 5612 AE Eindhoven, the Netherlands.
Eindhoven University of Technology · NLBartiméus · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recognizing pain in people with communicative disabilities is challenging. A support system detecting pain signals provides caregivers with information to intervene adequately. This study aims to develop a design for a user interface visualizing pain experiences for a signalling system intended for caregivers. Caregivers receive alerts, indicating the presence or absence of pain experienced by a disabled individual. The design process included the use of value proposition, a brainstorm, a mood board with basic design elements, and multiple questionnaires and focus groups. During the multi-disciplinary design process end-users were extensively involved. The final design was deemed intuitive, clear and recognizable, and useable in daily caregiving. This article describes the creation process for a non-hedonistic visualization for this niche end-user group.

Indexed as

Collaborative designDaily caregiversInterface designPerceptionUser-centred design

Identifiers

PMID36506382
PMCPMC9730134
OpenAlexW4311290423

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.