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Record W4387325944 · doi:10.2196/45442

Understanding the Connection Among Ikigai, Well-Being, and Home Robot Acceptance in Japanese Older Adults: Mixed Methods Study

2023· article· en· W4387325944 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Aging · 2023
Typearticle
Languageen
FieldPsychology
TopicSocial Robot Interaction and HRI
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessHappinessPsychologyWell-beingLife satisfactionSocial supportMeaning (existential)PerceptionSocial isolationSuccessful agingGerontologySocial psychologyDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Ikigai (meaning or purpose in life) is a concept understood by most older adults in Japan. The term has also garnered international attention, with recent academic attempts to map it to concepts in the Western well-being literature. In addition, efforts to use social and home robots to increase well-being have grown; however, they have mostly focused on hedonic well-being (eg, increasing happiness and decreasing loneliness) rather than eudaimonic well-being (eg, fostering meaning or purpose in life). OBJECTIVE: First, we explored how Japanese older adults experience ikigai and relate these to concepts in the Western well-being literature. Second, we investigated how a home robot meant to promote ikigai is perceived by older adults. METHODS: We used a mixed methods research design-including 20 interviews with older adults, a survey of 50 older adults, and 10 interviews with family caregivers. For interviews, we asked questions about older adults' sources of ikigai, happiness, and social support, along with their perception of the robot (QT). For surveys, a number of well-being scales were used, including 2 ikigai scales-ikigai-9 and K-1-and 6 Patient-Reported Outcomes Measurement Information System scales, measuring meaning and purpose, positive affect, satisfaction with participation in social roles, satisfaction with participation in discretionary social activities, companionship, and emotional support. Questions related to the perception and desired adoption of the robot and older adults' health status were also included. RESULTS: Our results suggest that health is older adults' most common source of ikigai. Additionally, although self-rated health correlated moderately with ikigai and other well-being measures, reported physical limitation did not. As opposed to social roles (work and family), we found that ikigai is more strongly related to satisfaction with discretionary social activities (leisure, hobbies, and friends) for older adults. Moreover, we found that older adults' sources of ikigai included the eudaimonic aspects of vitality, positive relations with others, contribution, accomplishment, purpose, and personal growth, with the first 3 being most common, and the hedonic aspects of positive affect, life satisfaction, and lack of negative affect, with the first 2 being most common. However, the concept of ikigai was most related to eudaimonic well-being, specifically meaning in life, along the dimension of significance. Finally, we found that Japanese older adults have high expectations of a home robot for well-being, mentioning that it should support them in a multitude of ways before they would likely adopt it. However, we report that those with the highest levels of meaning, and satisfaction with their leisure life and friendships, may be most likely to adopt it. CONCLUSIONS: We outline several ways to improve the robot to increase its acceptance, such as improving its voice, adding functional features, and designing it to support multiple aspects of well-being.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.066
GPT teacher head0.423
Teacher spread0.357 · 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