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Articles

Determining the ambient influences and configuration of optimised environments for emotional wellbeing of older adults

ORCID Icon, &
Pages 1146-1159 | Received 14 Jan 2021, Accepted 24 Mar 2021, Published online: 16 Apr 2021
 

Abstract

It is now widely recognised that aspects such as tiredness or mood state can have an impact on an individual’s wellbeing. However, there also exist other less studied factors that might be influential, and whose analysis is important to maximise personal wellbeing. The aim of this study was to determine the influence of a set of 12 selected factors. Using the analysis of a 20-experiment case study by soft computing techniques the intention was to establish the most appropriate configuration for each factor to compose an optimal living environment to foster wellbeing. The analysis revealed that ambient lighting and stress level are the factors that most impact emotional wellbeing. To a lesser extent, being able to take a break, ambient temperature and ambient noise play a relatively determining role. The findings of this work can be used to establish a living environment for older persons that favours their emotional wellbeing.

Practitioner summary: This study analyses the level of influence of a set of ambient factors on the emotional wellbeing of older people, conducting, to this end, a series of controlled experiments, and concluding that ambient lighting and stress level are the factors most relevant to promote a better living environment.

    KEY POINTS

  • Older adults’ emotional interpretation of pictures depends on the environment and ambient factors.

  • Ambient factors, such as lighting and stress, have a significant, positive effect on visual interpretation of stimuli and greater wellbeing.

  • The use of soft computing techniques facilitates the quantification of the influence of factors affecting emotional wellbeing.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work has been partially supported by Spanish Ministerio de Ciencia, Innovación y Universidades, Agencia Estatal de Investigación (AEI)/European Regional Development Fund (FEDER, UE) under [EQC2019-006063-P, SBPLY/19/180501/000181 and PID2020-115220RB-C21 (AEI/FEDER, EU) grants], and by CIBERSAM of the Instituto de Salud Carlos III.

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