The ethics of pet robots in dementia care settings: Care professionals’ and organisational leaders’ ethical intuitions
Bibliographic record
Abstract
Background: Pet robots are gaining momentum as a technology-based intervention to support the psychosocial wellbeing of people with dementia. Current research suggests that they can reduce agitation, improve mood and social engagement. The implementation of pet robots in care for persons with dementia raises several ethical debates. However, there is a paucity of empirical evidence to uncover care providers' ethical intuitions, defined as individuals' fundamental moral knowledge that are not underpinned by any specific propositions. Objectives: Explore care professionals' and organisational leaders' ethical intuitions before and when implementing pet robots in nursing homes for routine dementia care. Materials and methods: We undertook a secondary qualitative analysis of data generated from in-depth, semi-structured interviews with 22 care professionals and organisational leaders from eight nursing homes in Ireland. Data were analysed using reflexive thematic analysis. Ethical constructs derived from a comprehensive review of argument-based ethics literature were used to guide the deductive coding of concepts. An inductive approach was used to generate open codes not falling within the pre-existing concepts. Findings: Ethical intuitions for implementing pet robots manifested at three levels: an (1) individual-relational, (2) organisational and (3) societal level. At the individual-relational level, ethical intuitions involved supporting the autonomy of residents and care providers, using the robots to alleviate residents' social isolation, and the physical and psychosocial impacts associated with their use. Some care providers had differing sentiments about anthropomorphizing pet robots. At the organisational level, intuitions related to the use of pet robots to relieve care provision, changes to the organisational workflow, and varying extents of openness amongst care providers to use technological innovations. At the societal level, intuitions pertained conceptions of dementia care in nursing homes, and social justice relating to the affordability and availability of pet robots. Discrepancies between participants' ethical intuitions and existing philosophical arguments were uncovered. Conclusion: Care professionals and organisational leaders had different opinions on how pet robots are or should be implemented for residents with dementia. Future research should consider involving care practitioners, people with dementia, and their family members in the ethics dialogue to support the sustainable, ethical use of pet robots in practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.081 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.065 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".