Assessing virtual reality acceptance in long-term care facilities: a quantitative study with older adults
Bibliographic record
Abstract
PURPOSE: Our study aimed to investigate the factors associated with the acceptance of virtual reality (VR) games among older adults living in LTC, with a particular emphasis on identifying social and individual factors that have been overlooked in existing technology acceptance models. MATERIALS AND METHODS: We conducted VR gaming sessions, followed by a composite questionnaire to explore the factors associated with the acceptance of VR games among residents of LTC with a focus on technology acceptance models (TAM) and social factors derived from Selective Optimization with Compensation (SOC) theory and Socioemotional Selectivity Theory (SST). RESULTS: We studied 20 older adults aged 65 and older. Participants were moderately sedentary, with the majority of them having prior gaming experience. Participants with prior gaming experience had higher mean scores in most SOC theory and SST subscales, except for elective selection. Participants perceived the technology as useful and easy to use, with no heightened gaming-related anxiety. Significant correlations were found between perceived ease of use and selection strategies, and between attitudes towards gaming and elective selection strategies. No significant score differences were observed between male and female participants. CONCLUSIONS: The positive correlation between VR acceptance and using SOC strategies suggests a positive response to straightforward experiences. Our study highlights VR exergaming's potential benefits for encouraging LTC residents' engagement in valued activities and pursuing goals. Moreover, social theories of aging can inform technology acceptance and guide the design and marketing of VR exergames to better suit older adults' needs and preferences in LTC.IMPLICATIONS FOR REHABILITATIONThe findings of this study have important implications for rehabilitation programs aimed at enhancing physical activity (PA) and engagement among older adults living in long-term care (LTC) facilities. The use of virtual reality (VR) games can be an important tool to promote PA and improve the overall well-being of LTC residents. Based on the results, the following implications can be drawn:Integrating VR exergaming in rehabilitation:The positive perception of VR technology's usefulness and ease of use among older adults in LTC suggests that VR exergaming can be effectively integrated into rehabilitation programs. Healthcare professionals and rehabilitation specialists in LTC facilities can consider incorporating VR-based exercise routines and gaming sessions to motivate and engage residents in physical activities. By doing so, they can create enjoyable and interactive rehabilitation experiences that may lead to improved adherence to exercise regimens.Addressing social factors for VR acceptance:Our study highlights the significance of social factors derived from theories of aging, such as Selective Optimization with Compensation (SOC) and Socioemotional Selectivity Theory (SST), in influencing VR acceptance among LTC residents. Rehabilitation programs should take into account these social aspects and create a supportive and encouraging environment for older adults to engage with VR exergames. Encouraging social interactions and providing opportunities for residents to share their experiences with VR gaming may enhance acceptance and overall engagement.Tailoring VR exergames for older adults:The correlation between VR acceptance and the use of SOC strategies indicates that customized experiences may be well-received by LTC residents. Game developers and rehabilitation specialists should consider designing VR exergames that align with the specific preferences and needs of older adults. This could involve providing choices and options for users to optimize their gaming experiences based on their individual abilities and interests.Recognizing gaming experience:Our study highlights that prior gaming experience positively influenced participants' attitudes towards VR gaming. Rehabilitation professionals should acknowledge and leverage this prior experience when introducing VR exergaming to older adults in LTC. By incorporating elements familiar to older adults or providing guidance for those new to gaming, rehabilitation programs can foster a more seamless and enjoyable transition to VR exergames.Promoting goal pursuit and valued activities:Our study suggests that VR exergaming has the potential to encourage LTC residents' engagement in valued activities and goal pursuit. Rehabilitation programs can utilize VR exergaming as a means to help residents achieve specific rehabilitation goals and engage in activities that are meaningful to them. This approach can contribute to a sense of purpose and satisfaction in the rehabilitation process.Overall, the integration of VR exergaming in rehabilitation for older adults in LTC facilities has promising implications for improving physical activity levels, enhancing engagement, and addressing the holistic well-being of residents. By considering the social factors influencing VR acceptance and tailoring experiences to individual preferences, rehabilitation professionals can optimize the potential benefits of VR technology in LTC settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".