Testing the Social Robot LOVOT´s Interaction With Adults With Autism and Mental Impairment: Preliminary Findings
Bibliographic record
Abstract
Background Persons with autism and mental impairment face communicative, social, and behavioral challenges, and there is a need to establish effective interventions to improve the quality of daily life. Social robots working with children with autism have successfully improved their communication and social behavior and reduced stereotypic behavior. However, there is only limited evidence regarding the effectiveness of social robots. Objective This study aimed to investigate the interactions, effects on well-being, experiences from health care professionals, and ethical aspects of deploying the LOVOT social robot as a tool for adults with autism and mental impairment. Methods Two social robots have been deployed in 3 residences. A total of 12 adults with autism and mental impairment were recruited. Individual planned sessions on interaction with the social robots are being carried out twice a week for 20-30 minutes over a period of 6 months. Participant observations are carried out every second week during the 6 months on themes such as well-being, interaction with the robot, the level of arousal, eye contact, and communication. Observations have been documented through standardized observation protocols and by video recording. Experiences from health care professionals and ethical aspects have been explored using semistructured interviews. Results Preliminary results indicate that LOVOT has improved the well-being of participants. Although the participants’ interest in LOVOT varies, the health care professionals report that some participants find great satisfaction interacting with LOVOT, describing LOVOT as a friend, and that LOVOT can provide comfort in stressed situations. Two LOVOTs were damaged by the participants during the study, indicating the importance of robust material in interventions with adults with autism and mental impairment. Conclusions Preliminary findings indicate that social robots can increase well-being among persons with autism and mental impairment. Future care of persons with autism and mental impairment might benefit from the use of social robots as part of their care and quality of life. Conflicts of Interest None declared.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".