Evidence map›Paper›PMID 35009623›Full record

SynthesisSensors (Basel, Switzerland)2021

A Review of Data Gathering Methods for Evaluating Socially Assistive Systems.

Shi Qiu, Pengcheng An, Kai Kang, Jun Hu, Ting Han, Matthias Rauterberg

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 20% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
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 at 4 institutions in 3 countries.

Shi QiuDepartment of Design, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0003-0764-9147
Pengcheng AnSchool of Design, Southern University of Science and Technology, Shenzhen 518055, China.
Kai KangDepartment of Industrial Design, Eindhoven University of Technology, 5600MB Eindhoven, The Netherlands.ORCID 0000-0002-4553-9996
Jun HuDepartment of Industrial Design, Eindhoven University of Technology, 5600MB Eindhoven, The Netherlands.ORCID 0000-0003-2714-6264
Ting HanDepartment of Design, Shanghai Jiao Tong University, Shanghai 200240, China.
Matthias RauterbergDepartment of Industrial Design, Eindhoven University of Technology, 5600MB Eindhoven, The Netherlands.ORCID 0000-0002-2596-395X
Eindhoven University of Technology · NLShanghai Jiao Tong University · CNNantong University · CNUniversity of Waterloo · CA

Funding

National Social Science Fund 18BRK009Shanghai Jiao Tong University WF220543011Shanghai Pujiang Program 2020PJC071
6 · The paper itself

Abstract

Social interactions significantly impact the quality of life for people with special needs (e.g., older adults with dementia and children with autism). They may suffer loneliness and social isolation more often than people without disabilities. There is a growing demand for technologies to satisfy the social needs of such user groups. However, evaluating these systems can be challenging due to the extra difficulty of gathering data from people with special needs (e.g., communication barriers involving older adults with dementia and children with autism). Thus, in this systematic review, we focus on studying data gathering methods for evaluating socially assistive systems (SAS). Six academic databases (i.e., Scopus, Web of Science, ACM, Science Direct, PubMed, and IEEE Xplore) were searched, covering articles published from January 2000 to July 2021. A total of 65 articles met the inclusion criteria for this systematic review. The results showed that existing SASs most often targeted people with visual impairments, older adults, and children with autism. For instance, a common type of SASs aimed to help blind people perceive social signals (e.g., facial expressions). SASs were most commonly assessed with interviews, questionnaires, and observation data. Around half of the interview studies only involved target users, while the other half also included secondary users or stakeholders. Questionnaires were mostly used with older adults and people with visual impairments to measure their social interaction, emotional state, and system usability. A great majority of observational studies were carried out with users in special age groups, especially older adults and children with autism. We thereby contribute an overview of how different data gathering methods were used with various target users of SASs. Relevant insights are extracted to inform future development and research.

Indexed as

Persons with DisabilitiesQuality of LifeAgedChildEmotionsHumansLonelinessSocial Isolationassistive technologydata gathering methodsolder adultspeople with disabilitiessocial interaction

Identifiers

PMID35009623
PMCPMC8747743
OpenAlexW4200332722

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.