Tomoya Yokotani’s research while affiliated with Wakayama Medical University and other places

In spite of emphasis on patient-centered care and promotion of their quality, shortcomings have been seen in psychiatric care due to lack of compassion. To improve the quality of psychiatric caring in nursing, it is important to develop and implement in-service education based on Locsin’s Technological Competency as Caring in Nursing (TCCN) theory. Objectives to determine psychiatric nurse managers' perception and practice status as a preliminary survey to serve as a resource for in-service psychiatric nursing education. This survey was conducted in August 2022 using the Technological Competency as Caring in Nursing Instrument-Revised for Practice (TCCNI-Repract) scale at "A" psychiatric hospital. Descriptive statistics and Wilcoxon's signed-rank tests were used. Eleven head nurses and assistant head nurses participated in this study. Mean values for the perception dimension of each item of the TCCNI-RePract were high, whereas mean values for practice dimension were low. The results indicated that perception dimension was significantly higher than practice dimension in 21 of 26 items of the TCCNI-RePract. Nurse managers demonstrated a high level of perception of the TCCN theory; however, many practical items scored low. Nurse managers suggested developing a current educational program to inform practice based on the TCCN theory.

Background: Public Health Nurses (PHNs) collaborate with community volunteer welfare commissioners to support children with developmental disorders and their families lead a life without isolation. Objective: This study aims to clarify the roles and competencies that PHNs expect of welfare commissioners in supporting children with developmental disorders and their families. Methods: An online survey was administered through Survey Monkey© to 220 PHNs working in Japanese municipalities using an independently developed questionnaire regarding the roles and competencies of welfare commissioners supporting children with developmental disorders and their families expected by PHNs. Exploratory Factor Analysis (EFA) was performed to simplify the data structure and enhance understanding. The reliability of the scale was confirmed using Cronbach's α. Differences due to PHN attributes (e.g., experience collaborating with welfare commissioners) were analyzed using Welch's t-test. This study was conducted between April and September 2021. Results: The highest scoring items were, for the role, "a welfare commissioner's role is to pass on accurate information to their successor," and for competencies, "a necessary competency for a welfare commissioner is to protect the information about children with developmental disorders, and their families learned during one's work." The EFA results revealed a two-factor structure for role items: Factor 1, "Supporting children with developmental disorders and their families and preventing abuse," and Factor 2, "Connecting to social resources." Competency items were also found to have a two-factor structure: Factor 1, "Understanding the position of children with developmental disorders and their families and connecting with local residents," and Factor 2, "Understanding developmental disorders and supporting them based on assessment." A comparison of the attributes of PHNs showed no significant differences. Conclusion: PHNs feel welfare commissioners should pass on the information and protect confidentiality when supporting children with developmental disorders and their families. Furthermore, PHNs expect welfare commissioners to connect children with developmental disorders and their families to the community, prevent abuse, and provide support based on assessment. PHNs had the same expectations regarding the roles and competencies of welfare commissioners regardless of their own attributes.

Background: Expressing enjoyment when conversing with healthcare robots is an opportunity to enhance the value of human robots with interactive capabilities. In clinical practice, it is common to find verbal dysfunctions in patients with schizophrenia. Thus, interactive communication characteristics may vary between Pepper robot, persons with schizophrenia, and healthy persons. Objective: Two case studies aimed to describe the characteristics of interactive communications, 1) between Pepper as a healthcare robot and two patients with schizophrenia, and 2) between Pepper as a healthcare robot and two healthy persons. Case report: The "Intentional Observational Clinical Research Design" was used to collect data. Using audio-video technology, the conversational interactions between the four participants with the Pepper healthcare robot were recorded. Their interactions were observed, with significant events noted. After their interactions, the four participants were interviewed regarding their experience and impressions of interacting with the Pepper healthcare robot. Audio-video recordings were analyzed following the analysis and interpretation protocol, and the interview data were transcribed, analyzed, and interpreted. Discussion: There were similarities and differences in the interactive communication characteristics between the Pepper robot and the two participants with schizophrenia and between Pepper and the two healthy participants. The similarities were experiences of human enjoyment while interacting with the Pepper robot. This enjoyment was enhanced with the expectancy of the Pepper robot as able to entertain, and possessing interactive capabilities, indicating two-way conversational abilities. However, different communicating characteristics were found between the healthy participants' impressions of the Pepper robot and the participants with schizophrenia. Healthy participants understood Pepper to be an automaton, with responses to questions often constrained and, on many occasions, displaying inaccurate gaze. Conclusion: Pepper robot showed capabilities for effective communication pertaining to expressing enjoyment. The accuracy and appropriateness of gaze remained a critical characteristic regardless of the situation or occasion with interactions between persons with schizophrenia, and between healthy persons. It is important to consider that in the future, for effective use of healthcare robots with multiple users, improvements in the areas of the appropriateness of gaze, response time during the conversation, and entertaining functions are critically observed.

Background: The middle range theory Technological Competency as Caring in Nursing (TCCN) guides nursing practices. The TCCN Instrument (TCCNI) measures perception dimension of the theory and has been revised and translated into the Japanese language (TCCNI-R). Testing the translated version of the TCCNI-R to English language with the inclusion of a practice dimension is warranted. Purpose: This study aims to determine the psychometric properties of the TCCNI-Revised English version with Practice dimension (TCCNI-RePract). Methods: A web-based cross-sectional study was conducted with data from 202 valid questionnaire copies from professional nurses in selected hospitals and nurse educators in universities. Results: The suitability for factor analysis was determined using Kaiser-Meyer-Olkin index (0.93), Bartlett's sphericity test of 3256.93, p

Background: Nurses as primary healthcare providers demonstrate quality nursing care through competencies with healthcare technologies, while nurse managers assume the primacy of managing quality healthcare in their respective care settings. However, little is known about perceptions of the influence of care technologies on their nursing practice. Objective: This study aimed to determine managers' and staff nurses' perceptions regarding the Technological Competency as Caring in Nursing (TCCN) theory in general hospitals in Japan. Methods: This study employed a cross-sectional survey design, with 421 participants selected using a stratified sampling method. Technological Competency as Caring in Nursing Instrument-Revised (TCCNI-R) was used for online data collection using Survey Monkey©. Data were analyzed using Welch's t-test and ANOVA. Results: Nurses with years of experience within the range of 20 to less than 30 years showed the highest TCCNI-R scores among the two groups. Nurses who had received education on caring in nursing showed significant differences for Factor 2 (Technological Competency as Caring), that of expressing Technological Competency as Caring. Three other factors showed no significant difference, namely in Factor 1 (Nursing Expression as Caring), Factor 3 (Technology and Caring), and Factor 4 (Technological Knowing). However, the average scores of these factors were high, which reflect high professional ethics and occupational discipline and increased awareness of caring in nursing. It was also found that the nurse managers were more aware of the TCCN than were the staff nurses. The nurse managers were also more aware of providing care using technology, recognizing the need-to-know patient needs through technology and providing care to the ever-changing patient's condition. Conclusion: The study discovered that continuing education is needed regarding the practice of nursing based on theory, enabling appropriate and accurate understanding of practicing knowing persons as caring in nursing.

Frequent exposure to patient deaths prompts nurses to experience grief. Unresolved grief leads to harmful consequences of nurses’ mental health and quality of nursing care. A cross-sectional study using an online survey was conducted to determine the psychometric properties of the Grief traits and State Scale for Nurses. Exploratory factor analysis revealed two factors measuring the level of nurses’ grief traits (Cronbach’s alpha: 0.84) and two factors in grief state (Cronbach’s alpha: 0.86). Nurses’ feelings of unable to provide good care were associated with a higher risk of grief (odds ratio (OR): 4.30, 95% confidence interval (CI): 1.45–12.75), uncomfortable feeling toward deaths (OR: 11.29, 95%CI: 1.48–85.91), and emotional exhaustion (OR: 7.12, 95%CI: 1.63–30.99). Results indicated that the scale was reliable in determining the levels of their grief. Nurse managers can use the scale to identify their nurses’ levels of grief, creating opportunities to influence the resolution of the grief experiences.

Background: Caring expressions between humans and nonhuman intelligent machines are futuristic prototypes with healthcare robots as major advocates. Objective: To examine the experience of older persons with mental health conditions, particularly patients with schizophrenia and with dementia in the interaction with healthcare robots and intermediaries in a transactive relational engagement. Methods: Two qualitative case studies were conducted using sophisticated audio-video technologies to record the conversation and activities that were carefully documented. Following the procedure for qualitative descriptive analysis, a framework based on the Transactive Relationship Theory of Nursing was employed to analyze and interpret the data. Results: Three themes were revealed, including feelings for the other, inspiring meaningful responses, and demonstrating expressions of joy. The description of the experience of older persons involved in the conversation with humanoid robots was feeling for the other while inspiring meaningful responses in demonstrating expressions of joy. Conclusion: This study provided initial evidence that the transactive engagements of robots with older persons with schizophrenia and dementia and nurse intermediaries in psychiatric and mental health settings can result in occasions of 'joy' for the patients. These findings suggest that transactive engagements with robots facilitate expressions of joy among older persons with schizophrenia and dementia. However, these findings are not intended to prescribe nursing care actions but to describe the experience of older persons who are in transactive engagements with intelligent machines, indicating the importance and value of healthcare robots in nursing older persons with schizophrenia and with dementia.

This study aimed to develop the Grief State Scale for Nurses to measure the level of nurses' grief and to identify items influencing grief levels among Indonesian nurses. A total of 267 questionnaires were analyzed and interpreted. Statistical analyses were performed using descriptive statistics and exploratory factor analysis. Items influential in increasing nurses' grief were relating death with personal loss; patient's age/illness similar to nurse's family members; and having rapport with patients. Time and place to express grief, allocation of grieving time, and sharing collegial emotional expressions were items found to decrease levels of nurses' grief.

Although progress is being made in affective computing, issues remain in enabling the effective expression of compassionate communication by healthcare robots. Identifying, describing and reconciling these concerns are important in order to provide quality contemporary healthcare for older adults with dementia. The purpose of this case study was to explore the development issues of healthcare robots in expressing compassionate communication for older adults with dementia. An exploratory descriptive case study was conducted with the Pepper robot and older adults with dementia using high-tech digital cameras to document significant communication proceedings that occurred during the activities. Data were collected in December 2020. The application program for an intentional conversation using Pepper was jointly developed by Tanioka's team and the Xing Company, allowing Pepper's words and head movements to be remotely controlled. The analysis of the results revealed four development issues, namely, (1) accurate sensing behavior for "listening" to voices appropriately and accurately interacting with subjects; (2) inefficiency in "listening" and "gaze" activities; (3) fidelity of behavioral responses; and (4) deficiency in natural language processing AI development, i.e., the ability to respond actively to situations that were not pre-programmed by the developer. Conversational engagements between the Pepper robot and patients with dementia illustrated a practical usage of technologies with artificial intelligence and natural language processing. The development issues found in this study require reconciliation in order to enhance the potential for healthcare robot engagement in compassionate communication in the care of older adults with dementia.

Healthcare providers in advanced healthcare systems recognize the value of practices involving technological competencies in healthcare. Theory-based practice, grounded in Locsin's Technological Competency as Caring in nursing theory, warrants investments in quality nursing care. This study determined the effect of in-service educational programs for nurse managers regarding perceptions of the theory. Five, 1-hour lecture sessions weekly showed significant effects on understanding technological competency as expression of caring in nursing. Technological Competency as caring in nursing theory-based educational programs offer promising ways to ensure that understanding technological competency as caring assures quality healthcare.