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Record W4393408153 · doi:10.1108/arch-11-2023-0304

An architectural insight into the role of personalisation of homes and its effects on residents’ psychological well-being

2024· article· en· W4393408153 on OpenAlexaff
Dalia Al-Tarazi, Rachel Sara, Paul Redford, Louis Rice, Colin A. Booth

Bibliographic record

VenueInternational Journal of Architectural Research Archnet-IJAR · 2024
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsWell-beingPsychologyPsychological well-beingPersonalizationSocial psychologyComputer sciencePsychotherapistWorld Wide Web

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to explore the importance of personalisation in the relationship between the architectural design of homes and inhabitants’ psychological well-being. Design/methodology/approach This interdisciplinary mixed-method study first investigates the existence of a link between personalisation and users’ association with home through a quantitative study (n = 101) and then explores the nature of this relationship through qualitative interviews (n = 13) in a sequential explanatory approach. Findings The main findings of the study highlight the significance of personalisation in relation to the way people perceive home. A direct link was established between participants’ involvement in the transformation of the home and their satisfaction with the residence, as well as satisfaction with life in general. Further thematic analysis of the qualitative study revealed further conceptualisations of personalisation, which together form an umbrella concept called transformability. Research limitations/implications The findings underscore the need for embedding flexibility as an architectural concept in the design of residential buildings for improving the well-being of occupants. Originality/value The design of homes has a great impact on inhabitants’ psychological well-being. This is becoming of greater importance in light of the global COVID-19 pandemic that has led to an increase in the amount of time spent in homes. This research contributes to this debate by proposing concepts for a deeper understanding of architectural influences on the psychology of the home.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score0.850

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.429
Teacher spread0.396 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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