Evidence map›Paper›PMID 35225818›Full record

ArticleJMIR aging2022

Older Adults' and Clinicians' Perspectives on a Smart Health Platform for the Aging Population: Design and Evaluation Study.

Alessia Cristiano, Stela Musteata, Sara De Silvestri, Valerio Bellandi, Paolo Ceravolo, Matteo Cesari, Domenico Azzolino, Alberto Sanna, Diana Trojaniello

Open access · goldAbstract read
In one paragraph

Article in JMIR aging, 2022. 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
6.4field-weighted citation impact, top 3% 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

10 citing papers in PubMed, 24 citations in OpenAlex.

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  9. A Regulatory Game Analysis of Smart Aging Platforms Considering Privacy Protection.International journal of environmental research and public health · 2022
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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

9 authors at 3 institutions in 1 country.

Alessia Cristiano *Center for Advanced Technology in Health and Wellbeing, Istituto di Ricovero e Cura a Carattere Scientifico Ospedale San Raffaele, Milan, Italy.ORCID https://orcid.org/0000-0002-7682-0270
Stela Musteata *Center for Advanced Technology in Health and Wellbeing, Istituto di Ricovero e Cura a Carattere Scientifico Ospedale San Raffaele, Milan, Italy.ORCID https://orcid.org/0000-0001-7717-7654
Sara De Silvestri *Center for Advanced Technology in Health and Wellbeing, Istituto di Ricovero e Cura a Carattere Scientifico Ospedale San Raffaele, Milan, Italy.ORCID https://orcid.org/0000-0002-4926-5259
Valerio Bellandi *Department of Computer Science, Università Degli Studi di Milano, Milan, Italy.ORCID https://orcid.org/0000-0003-4473-6258
Paolo Ceravolo *Department of Computer Science, Università Degli Studi di Milano, Milan, Italy.ORCID https://orcid.org/0000-0002-4519-0173
Matteo Cesari *Geriatric Unit, Istituto di Ricovero e Cura a Carattere Scientifico Istituti Clinici Scientifici Maugeri, Università Degli Studi di Milano, Milan, Italy.ORCID https://orcid.org/0000-0002-0348-3664
Domenico Azzolino *Geriatric Unit, Istituto di Ricovero e Cura a Carattere Scientifico Istituti Clinici Scientifici Maugeri, Università Degli Studi di Milano, Milan, Italy.ORCID https://orcid.org/0000-0002-4910-7373
Alberto Sanna *Center for Advanced Technology in Health and Wellbeing, Istituto di Ricovero e Cura a Carattere Scientifico Ospedale San Raffaele, Milan, Italy.ORCID https://orcid.org/0000-0002-0640-9021
Diana Trojaniello *Center for Advanced Technology in Health and Wellbeing, Istituto di Ricovero e Cura a Carattere Scientifico Ospedale San Raffaele, Milan, Italy.ORCID https://orcid.org/0000-0001-8935-5593
IRCCS Ospedale San Raffaele · ITIstituti Clinici Scientifici Maugeri · ITUniversity of Milan · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOver recent years, interest in the development of smart health technologies aimed at supporting independent living for older populations has increased. The integration of innovative technologies, such as the Internet of Things, wearable technologies, artificial intelligence, and ambient-assisted living applications, represents a valuable solution for this scope. Designing such an integrated system requires addressing several aspects (eg, equipment selection, data management, analytics, costs, and users' needs) and involving different areas of expertise (eg, medical science, service design, biomedical and computer engineering).

objectiveThe objective of this study is 2-fold; we aimed to design the functionalities of a smart health platform addressing 5 chronic conditions prevalent in the older population (ie, hearing loss, cardiovascular diseases, cognitive impairments, mental health problems, and balance disorders) by considering both older adults' and clinicians' perspectives and to evaluate the identified smart health platform functionalities with a small group of older adults.

methodsOverall, 24 older adults (aged >65 years) and 118 clinicians were interviewed through focus group activities and web-based questionnaires to elicit the smart health platform requirements. Considering the elicited requirements, the main functionalities of smart health platform were designed. Then, a focus group involving 6 older adults was conducted to evaluate the proposed solution in terms of usefulness, credibility, desirability, and learnability.

resultsEight main functionalities were identified and assessed-cognitive training and hearing training (usefulness: 6/6, 100%; credibility: 6/6, 100%; desirability: 6/6, 100%; learnability: 6/6, 100%), monitoring of physiological parameters (usefulness: 6/6, 100%; credibility: 6/6, 100%; desirability: 6/6, 100%; learnability: 5/6, 83%), physical training (usefulness: 6/6, 100%; credibility: 6/6, 100%; desirability: 5/6, 83%; learnability: 2/6, 33%), psychoeducational intervention (usefulness: 6/6, 100%; credibility: 6/6, 100%; desirability: 4/6, 67%; learnability: 2/6, 33%), mood monitoring (usefulness: 4/6, 67%; credibility: 4/6, 67%; desirability: 3/6, 50%; learnability: 5/6, 50%), diet plan (usefulness: 5/6, 83%; credibility: 4/6, 67%; desirability: 1/6, 17%; learnability: 2/6, 33%), and environment monitoring and adjustment (usefulness: 1/6, 17%; credibility: 1/6, 17%; desirability: 0/6, 0%; learnability: 0/6, 0%). Most of them were highly appreciated by older participants, with the only exception being environment monitoring and adjustment. The results showed that the proposed functionalities met the needs and expectations of users (eg, improved self-management of patients' disease and enhanced patient safety). However, some aspects need to be addressed (eg, technical and privacy issues).

conclusionsThe presented smart health platform functionalities seem to be able to meet older adults' needs and desires to enhance their self-awareness and self-management of their medical condition, encourage healthy and independent living, and provide evidence-based support for clinicians' decision-making. Further research with a larger and more heterogeneous pool of stakeholders in terms of demographics and clinical conditions is needed to assess system acceptability and overall user experience in free-living conditions.

Indexed as

age-related chronic conditionshealthy agingInternet of Thingsmobile phoneolder populationremote monitoringrequirement elicitationsmart health

Identifiers

PMID35225818
PMCPMC8922154
OpenAlexW3214067231

What OpenQuestion holds

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LicenceCC BY
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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.