文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

五项基于开源应用程序的认知和感官任务在澳大利亚18至82岁成年人生命历程样本中的效标效度:无墙实验室。

Criterion validity of five open-source app-based cognitive and sensory tasks in an Australian adult life course sample aged 18 to 82: Labs without walls.

作者信息

Zhou Shally, Brady Brooke, Anstey Kaarin J

机构信息

School of Psychology, University of New South Wales, Sydney, Australia.

UNSW Ageing Futures Institute, Sydney, Australia.

出版信息

Behav Res Methods. 2025 Jan 22;57(2):69. doi: 10.3758/s13428-024-02583-1.


DOI:10.3758/s13428-024-02583-1
PMID:39843606
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11754352/
Abstract

With recent technical advances, many cognitive and sensory tasks have been adapted for smartphone testing. This study aimed to assess the criterion validity of a subset of self-administered, open-source app-based cognitive and sensory tasks by comparing test performance to lab-based alternatives. An in-person baseline was completed by 43 participants (aged 21 to 82) from the larger Labs without Walls project (Brady et al., 2023) to compare the self-administered, app-based tasks with researcher-administered equivalents. 4 preset tasks sourced from Apple's ResearchKit (Spatial Memory, Trail Making Test, Stroop Test, and dBHL Tone Audiometry) and 1 custom-built task (Ishihara Color Deficiency Test) were compared. All tasks except the Spatial Memory task demonstrated high comparability to the researcher-administered version. Specifically, the Trail Making Tests were strongly correlated (.77 and .78 for parts A and B, respectively), Stroop correlations ranged from .77 to .89 and the Ishihara tasks were moderately correlated (r = .69). ICCs for the Audiometry task ranged from .56 to .96 (Moderate to Excellent) with 83% sensitivity and 100% specificity. Bland-Altman plots revealed a mean bias between -5.35 to 9.67 dB for each ear and frequency with an overall bias of 3.02 and 1.98 for the left and right ears, respectively, within the minimum testing interval. Furthermore, all app-based tasks were significantly correlated with age. These results offer preliminary evidence of the validity of four open-source cognitive and sensory tasks with implications for effective remote testing in non-lab settings.

摘要

随着近期技术的进步,许多认知和感官任务已被改编用于智能手机测试。本研究旨在通过将测试表现与基于实验室的替代方法进行比较,评估一部分基于开源应用程序的自我管理认知和感官任务的标准效度。来自规模更大的“无墙实验室”项目(布雷迪等人,2023年)的43名参与者(年龄在21至82岁之间)完成了一次面对面基线测试,以比较基于应用程序的自我管理任务与研究人员管理的等效任务。比较了从苹果研究套件中获取的4个预设任务(空间记忆、连线测验、斯特鲁普测验和dBHL纯音听力测定)和1个定制任务(石原色盲测试)。除空间记忆任务外,所有任务与研究人员管理的版本都具有高度可比性。具体而言,连线测验的相关性很强(A部分和B部分分别为0.77和0.78),斯特鲁普测验的相关性在0.77至0.89之间,石原任务的相关性中等(r = 0.69)。听力测定任务的组内相关系数在0.56至0.96之间(中等至优秀),灵敏度为83%,特异性为100%。布兰德-奥特曼图显示,在最小测试间隔内,每只耳朵和每个频率的平均偏差在-5.35至9.67分贝之间,左耳和右耳的总体偏差分别为3.02和1.98。此外,所有基于应用程序的任务都与年龄显著相关。这些结果为四项开源认知和感官任务的效度提供了初步证据,对非实验室环境中的有效远程测试具有启示意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a53a/11754352/a485d8565599/13428_2024_2583_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a53a/11754352/a485d8565599/13428_2024_2583_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a53a/11754352/a485d8565599/13428_2024_2583_Fig1_HTML.jpg

相似文献

[1]
Criterion validity of five open-source app-based cognitive and sensory tasks in an Australian adult life course sample aged 18 to 82: Labs without walls.

Behav Res Methods. 2025-1-22

[2]
Characterizing Performance on a Suite of English-Language NeuroUX Mobile Cognitive Tests in a US Adult Sample: Ecological Momentary Cognitive Testing Study.

J Med Internet Res. 2024-11-25

[3]
Designing Survey-Based Mobile Interfaces for Rural Patients With Cancer Using Apple's ResearchKit and CareKit: Usability Study.

JMIR Form Res. 2024-9-26

[4]
Virtual Reality Gamification of Visual Search, Response Inhibition, and Visual Short-Term Memory Tasks for Cognitive Assessment: Experimental Study.

JMIR Form Res. 2025-7-29

[5]
Performance of Hearing Test Software Applications to Detect Hearing Loss.

JAMA Netw Open. 2025-3-3

[6]
Prescription of Controlled Substances: Benefits and Risks

2025-1

[7]
MyCog Mobile smartphone-based cognitive screening system: a cross-sectional construct validation in a general population sample at multiple research facilities in the USA.

BMJ Open. 2025-8-24

[8]
Validating Smartphone-Based and Web-Based Applications for Remote Hearing Assessment.

J Am Acad Audiol. 2025-3-31

[9]
Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19.

Cochrane Database Syst Rev. 2022-5-20

[10]
Measurement Properties of Smartphone Approaches to Assess Physical Activity in Healthy Young People: Systematic Review.

JMIR Mhealth Uhealth. 2022-10-21

引用本文的文献

[1]
Associations between objective hearing function and subjective views of aging.

Eur J Ageing. 2025-7-16

本文引用的文献

[1]
A Technology-Enriched Approach to Studying Microlongitudinal Aging Among Adults Aged 18 to 85 Years: Protocol for the Labs Without Walls Study.

JMIR Res Protoc. 2023-7-6

[2]
Hearing screening using the uHear™ smartphone-based app: reproducibility of results from two response modes.

Codas. 2023

[3]
To BYOD or not: Are device latencies important for bring-your-own-device (BYOD) smartphone cognitive testing?

Behav Res Methods. 2023-9

[4]
Analytical methods for evaluating reliability and validity of mobile audiometry tools.

J Acoust Soc Am. 2022-7

[5]
An Open-Source Cognitive Test Battery to Assess Human Attention and Memory.

Front Psychol. 2022-6-10

[6]
The Mobile Toolbox for monitoring cognitive function.

Lancet Neurol. 2022-7

[7]
Ecological Momentary Assessment: A Meta-Analysis on Designs, Samples, and Compliance Across Research Fields.

Assessment. 2023-4

[8]
Diagnostic performance of digital cognitive tests for the identification of MCI and dementia: A systematic review.

Ageing Res Rev. 2021-12

[9]
Mobile health and neurocognitive domains evaluation through smartphones: A meta-analysis.

Comput Methods Programs Biomed. 2021-11

[10]
Diagnostic Accuracy of Smartphone-Based Audiometry for Hearing Loss Detection: Meta-analysis.

JMIR Mhealth Uhealth. 2021-9-10

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索