Evidence map›Paper›PMID 35079606›Full record

ArticleInternational journal of nursing sciences2022

Demand analysis of an intelligent medication administration system for older adults with chronic diseases based on the Kano model.

Jiayi Mao, Liling Xie, Qinghua Zhao, Mingzhao Xiao, Shuting Tu, Wenjing Sun, Tingting Zhou

Abstract read
In one paragraph

Article in International journal of nursing sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

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

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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

7 authors.

Jiayi MaoDepartment of Nursing. the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Liling XieDepartment of Nursing. the First Branch of the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Qinghua ZhaoDepartment of Nursing. the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Mingzhao XiaoDepartment of Urology. the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Shuting TuDepartment of Nursing. the First Branch of the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Wenjing SunDepartment of Nursing. the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Tingting ZhouDepartment of Nursing. the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesGerontechnology has great potential in promoting older adults' well-being. With the accelerated aging process, gerontechnology has a promising market prospect. However, most technological developers and healthcare professionals attached importance to products' effectiveness, and ignored older adults' demands and user experience, which reduced older adults' adoption intention of gerontechnology use. The inclusion of older adults in the design process of technologies is essential to maximize the effect. This study explored older adults' demands for a self-developed intelligent medication administration system and proposed optimization schemes, thus providing reference to developing geriatric-friendly technologies and products.

methodsA cross-sectional survey was conducted to explore older adults' technological demands for the self-developed intelligent medication administration system, and data were analyzed based on the Kano model. A self-made questionnaire was administered from July 2020 to October 2020 after participants used this system for two weeks. The study was registered with the Chinese Clinical Trial Registry (ChiCTR2000040644).

resultsA total of 354 older adults participated in the survey. Four items, namely larger font size, simpler operation process, scheduled medication reminders and reliable hardware, were classified as must-be attributes; three items, namely searching drug instructions through WeChat, more sensitive system and longer battery life, as attractive attributes; one item, viewing disease-related information through WeChat, as the one-dimensional attribute; and the rest were indifferent attributes, including simple and beautiful displays, blocking advertisements automatically, providing user privacy protection protocol, viewing personal medical information only by logged-in users, recording all the medications, ordering medications through WeChat. The satisfaction values were between 0.24 and 0.69, and dissatisfaction values were between 0.06 and 0.94.

conclusionThis study suggested that older adults had personalized technology demands. Including their technological demands and desire may assist in decreasing the digital divide and promoting the satisfaction of e-health and/or m-health. Based on older adults' demands, our study proposed optimization schemes of the intelligent medication administration system, which may help developers design geriatric-friendly intelligent products and nurses to perform older adults-centered and efficient medication management.

Indexed as

AgedCommunicationData collectionElectronic medication deviceMedication therapy managementMobile applicationsNeeds assessmentPersonal satisfaction

Identifiers

PMID35079606
PMCPMC8766777

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.