Evidence map›Paper›PMID 36554822›Full record

ArticleInternational journal of environmental research and public health2022

Study of Ageing in Complex Interface Interaction Tasks: Based on Combined Eye-Movement and HRV Bioinformatic Feedback.

Ting Huang, Chengmin Zhou, Xin Luo, Jake Kaner

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. 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
0.6field-weighted citation impact, top 29% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  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

4 authors at 2 institutions in 2 countries.

Ting HuangCollege of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China.ORCID 0000-0001-9771-8147
Chengmin ZhouCollege of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China.ORCID 0000-0002-4988-5896
Xin LuoCollege of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China.
Jake KanerSchool of Art and Design, Nottingham Trent University, Nottingham NG1 4FQ, UK.ORCID 0000-0002-7946-7433
Nanjing Forestry University · CNNottingham Trent University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human-computer interaction tends to be intelligent and driven by technological innovation. However, there is a digital divide caused by usage barriers for older users when interacting with complex tasks. To better help elderly users efficiently complete complex interactions, a smart home's operating system's interface is used as an example to explore the usage characteristics of elderly users of different genders. This study uses multi-signal physiological acquisition as a criterion. The results of the study showed that: (1) Older users are more attracted to iconic information than textual information. (2) When searching for complex tasks, female users are more likely to browse the whole page before locating the job. (3) Female users are more likely to browse from top to bottom when searching for complex tasks. (4) Female users are more likely to concentrate when performing complex tasks than male users. (5) Males are more likely to be nervous than females when performing complex tasks.

Indexed as

AgingUser-Computer InterfaceAgedComputational BiologyFeedbackFemaleHeart RateHumansMaleage-friendly interfacecomplex interaction taskseye trackingmulti-physiological signals

Identifiers

PMID36554822
PMCPMC9779224
OpenAlexW4312196141

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.