Evidence map›Paper›PMID 39015130›Full record

ArticleProceedings of the SIGCHI conference on human factors in computing systems. CHI Conference2024

An Iterative Participatory Design Approach to Develop Collaborative Augmented Reality Activities for Older Adults in Long-Term Care Facilities.

Akshith Ullal, Mahrukh Tauseef, Alexandra Watkins, Lisa Juckett, Cathy Maxwell, Judith Tate, Lorraine C Mion, Nilanjan Sarkar

Abstract read
In one paragraph

Article in Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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  8. Article
  9. HCI and Older Adults: The Critical Turn and What Comes Next.Foundations and trends in human computer interaction · 2025
    Article
  10. 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

8 authors.

Akshith UllalVanderbilt University, Nashville, Tennessee, USA.
Mahrukh TauseefVanderbilt University, Nashville, Tennessee, USA.
Alexandra WatkinsVanderbilt University, Nashville, Tennessee, USA.
Lisa JuckettThe Ohio State University, Columbus, Ohio, USA.
Cathy MaxwellVanderbilt University, Nashville, Tennessee, USA.
Judith TateThe Ohio State University, Columbus, Ohio, USA.
Lorraine C MionThe Ohio State University, Columbus, Ohio, USA.
Nilanjan SarkarVanderbilt University, Nashville, Tennessee, USA.

Funding

Reducing Loneliness of Older Adults in Long Term Care Facilities through Collaborative Augmented RealityR21AG078480 · NIA · VANDERBILT UNIVERSITY · PI SARKAR, NILANJAN, TATE, JUDITH ANN · 2022 to 2023
$433k
NIA NIH HHS R21 AG078480
6 · The paper itself

Abstract

Over four million older adults living in long-term care (LTC) communities experience loneliness, adversely impacting their health. Increased contact with friends and family is an evidence-based intervention to reduce loneliness, but in-person visits are not always possible. Augmented Reality (AR)-based telepresence activities can offer viable alternatives with increased immersion and presence compared to video calls. However, its feasibility as an interaction technology for older adults is not known. In this paper, we detail the design of two dyadic collaborative AR activities that accommodate diminished physical and cognitive abilities of older adults. The findings include a general design framework based on an iterative participatory design focusing on preferred activities, modes of interaction, and overall AR experience of eight older adults, two family members, and five LTC staff. Results demonstrate the potential of collaborative AR as an effective means of interaction for older adults with their family, if designed to cater to their needs.

Indexed as

accessibilitycollaborative augmented realityiterative participatory designlong term care settingsolder adults

Identifiers

PMID39015130
PMCPMC11251005

What OpenQuestion holds

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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.