Individual differences in touch attitudes shape acceptance of robotic touch in older adults: Evidence from a medical center setting

Individual differences in touch attitudes shape acceptance of robotic touch in older adults: Evidence from a medical center setting | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Individual differences in touch attitudes shape acceptance of robotic touch in older adults: Evidence from a medical center setting Monika Eckstein, Carlotta Julia Mayer, Melina Schmetterer, Leonie Leven, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9277646/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Interpersonal touch is a fundamental aspect of human social interaction and plays a crucial role in health and wellbeing. In geriatric healthcare, touch-capable social robots are increasingly discussed as a means of supporting older adults. Yet little is known about what shapes individual acceptance of robotic touch. Methods This study investigated the influence of individual differences in social touch attitudes on older adults' experiences with robot-assisted walking guidance including touching the robot. Twenty-four older adults participated in a within-subject design, completing four experimental conditions with varying physical contact types (no contact, hand-holding, arm-linking, and full forearm contact) using the TIAGo Pro robot. Results Participants with more positive attitudes toward social touch reported higher comfort and more favorable evaluations of the robotic interaction. Negative attitudes towards robots in general changed after the experiments in interaction with the prior preferences for social touch. Qualitative analysis revealed that while participants recognized the practical benefits of robots, they also emphasized ethical boundaries, stressing that robots cannot replace essential human qualities like empathy. Discussion The study highlights the importance of individual preferences in robot acceptance and underscores the need for context-specific implementation strategies, where person-centered approaches and transparency about robotic capabilities are crucial for future integration into geriatric healthcare. social touch geriatric healthcare human-robot interaction nursery affect Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Interpersonal touch is a fundamental aspect of human social interaction and plays a crucial role in physical and mental health across the lifespan. This includes geriatric care contexts, where physical contact is both clinically relevant and increasingly difficult to ensure given staff shortages and systemic pressures. Research has demonstrated that tactile contact can reduce stress and anxiety (Eckstein et al., 2020 ; Packheiser et al., 2024 ), and promote feelings of safety and social connection (Debrot et al., 2013 ; Jakubiak & Feeney, 2017 ). These beneficial effects are mediated through multiple neurobiological pathways, among them the release of oxytocin (Schneider et al., 2023 ), a neuropeptide associated with social attachment and stress reduction that inhibits the hypothalamic–pituitary–adrenal axis (HPA) axis and thereby contributes to decreased cortisol levels (Kidd et al., 2023 ). In medical and care settings, touch is frequently discussed as a component of nursing care. Systematic reviews reveal that touch in nursing practice is predominantly instrumental (task-oriented) rather than expressive or caring in nature (Gleeson & Timmins, 2004 ; Routasalo, 1999 ). Studies suggest potential benefits in specific contexts such as reduced anxiety in intensive care patients receiving touch (Henricson et al., 2008 ), decreased agitation following hand massage in some dementia patients (Hansen Edwards et al., 2024 ), as well as reduced anxiety and lower blood pressure in female surgical patients touched during preoperative teaching (Whitcher & Fisher, 1979 ). However, comprehensive systematic reviews emphasize that there is insufficient evidence to draw general conclusions about the efficacy of touch interventions (Packheiser et al., 2024 ). Research findings on the physiological and psychological effects of touch remain limited and contradictory (Routasalo, 1999 ). Recent reviews highlight that touch in healthcare cannot be reduced to a simple instrumental versus expressive dichotomy. Rather, touch in healthcare has complex communicative, social, and affective dimensions that depend on context, consent, and individual differences (Buono et al., 2025). These challenges and limitations in implementing human touch in care settings have contributed to growing interest in technological developments. Healthcare systems face increasing staff shortages and time constraints. At the same time, social robots have emerged as one possible way to provide tactile interaction to patients. The use of social robots in healthcare settings, particularly in geriatric care, has increased substantially in recent years (Abdi et al., 2018 ; Broekens et al., 2024 ). These robots range from companion robots designed primarily for social and emotional support to more complex assistive systems that can support activities of daily living (Abdi et al., 2018 ; Hermann, Oktay, et al., 2024). Proponents argue that robots could address critical challenges in elder care, including chronic staff shortages, the physical demands of caregiving, and the need for consistent patient monitoring (Papadopoulos, Koulouglioti, et al., 2020). Therefore robotic technology raises practical opportunities, but also fundamental questions about the nature of care and the role of technology in meeting basic human needs for physical contact. A key question concerns whether robotic touch might provide similar benefits to human touch. Recent meta-analytic evidence suggests that social robot interventions can produce significant positive effects on psychosocial outcomes. This meta-analysis of eight randomized controlled trials found large effect sizes for reductions in both depression and loneliness among older adults in long-term care facilities (Yen, Huang, et al., 2024 ). Individual studies have shown that companion robots incorporating tactile interaction, such as the seal-like PARO, can significantly reduce loneliness over extended periods (Robinson, MacDonald, et al., 2013 ). These benefits appear to also depend on implementation format, where group-based activities have stronger effects than individual sessions, and intervention duration, where longer interventions produce greater improvements (Yen, H.-Y., et al., 2024). Experience with social robots seems to shape attitudes towards them as shown in one study comparing negative attitudes towards robots (NARS scale by Nomura et al., 2006 ) before and after a physical interaction with the humanoid robot Pepper (Zhou et al., 2021 ): While attitudes did not change in general, ratings for specific items on social interactions with robots improved. Despite these promising findings, substantial barriers limit widespread implementation. These barriers include technical limitations and malfunctions, high costs, concerns about acceptance among caregivers, and the low to moderate methodological quality of many existing studies (Abdi et al., 2018 ; Papadopoulos, Koulouglioti, et al., 2020). Moreover, emerging evidence suggests that not all older adults respond similarly to social robots. For instance, cognitive benefits of robot interaction appear more pronounced in cognitively intact individuals, while effects vary based on factors such as previous technology experience and personal preferences (Hermann, Oktay, et al., 2024; Papadopoulos, Koulouglioti, et al., 2020; Yen, Huang, et al., 2024 ). However, little is known about whether individual differences in touch preferences, a key factor in human-to-human care interactions, similarly influence older adults' responses to physical touch from robots during hands-on assistance. Individuals differ considerably in how much they enjoy or avoid physical touch. While some individuals find touch comforting and seek it out, others experience touch as uncomfortable or intrusive and prefer to avoid it (Andersen & Leibowitz, 1978 ; Ozolins & Sandberg, 2009 ). These preferences appear to be relatively stable individual characteristics that influence how people respond to touch (Hielscher & Mahar, 2017 ; Jakubiak & Feeney, 2016 ; Krahe et al., 2018 ; Tanzer et al., 2025 ), but also how preferences of wanting touch in a particular situation play a role (Sailer et al., 2024 ). The role of individual differences in touch preferences for the acceptance of robotic touch during physical assistance has direct implications for person-centered implementation in geriatric care. Touch-capable robots are increasingly being introduced into geriatric care settings, but implementation strategies rarely account for the substantial individual variation in how older adults experience physical contact. While person-centered care is a well-established principle in geriatric medicine, extending this principle to robotic touch requires empirical evidence about which individual characteristics are important. It also remains an open question whether direct hands-on experience with a robot can override initial predispositions based on touch attitudes, a question with direct practical relevance for how robotic systems are introduced in care contexts. The present mixed-methods study aimed to investigate how older adults perceive and evaluate robotic touch after direct, hands-on experience with a haptically interactive social robot (TIAGo Pro). We examined how older adults evaluated a human-robot interaction by collecting ratings following touch interactions, including current subjective feelings. Participants' broader reflections on social robots in care were gathered through qualitative analysis of their open-ended comments about their experiences with TIAGo Pro. Self-reported quantitative ratings were then integrated with qualitative reflections to investigate whether individual differences in general attitudes toward touch are associated with responses to robotic touch. We hypothesized that perception and acceptance of robotic touch would be influenced by participants' attributes, with general attitudes toward touch being a key individual characteristic. Understanding whether individuals' general attitude to touch predicts their acceptance of robotic touch is critical for implementing such technologies in care settings. By combining direct experience with robotic touch and assessment of individual factors, this study provides empirically grounded insights directly from older adults as end-users. This approach illuminates factors shaping the acceptance of touch-capable robots in older adults in medical settings. Methods Study Design The mixed-methods study used a within-subject experimental design to examine the effects of different forms of physical contact during robot-assisted walking guidance. All participants completed all experimental conditions, with the order randomized between participants. This study was conducted from October to November 2025 in Heidelberg, Germany at a geriatric hospital (Agaplesion Bethanien Hospital Heidelberg). The larger overall project is preregistered ( https://osf.io/9dpxw ) and approved by the local ethics committee (S-290/2024). Other research questions with focus on robotic technology are prepared for publication elsewhere (Leven et al, in preparation, Mayer et al, submitted for publication). Participants Twenty-four older adults (age range: 68–88 years) participated in the study. Recruitment was conducted through the participant database of previous studies of the research department at the Agaplesion Bethanien Hospital Heidelberg which included individuals who had expressed interest in being contacted for future research. These individuals were contacted via telephone or email. Exclusion criteria included acute illness, severe cognitive impairment, or conditions preventing safe participation in guided walking. Participants were community-dwelling or living in assisted settings and were able to walk independently without walking aids. An a priori power analysis for condition comparisons (t-test for dependent means, one-tailed) was conducted using G*Power (Faul et al., 2009 ) based on previous similar research in healthy volunteers. Zhou et al ( 2021 ) reported that N = 21 persons showed a physiological response to actively touching a robot (effect size partial ƞ2 = 0.240, corresponds to approx. Cohen’s d = 1.12) and changes in some of their subjective attitude towards robots indicating more trust after the touch experience with the robot (d = 0.41). In order to detect similar medium to large effects with 80% power and 5% alpha error probability, we planned to include at least N = 25. For feasibility reasons, the study design was changed to a within subject design. A post hoc sensitivity analysis was also conducted to determine the smallest Pearson correlation and differences between two measures that could be reliably detected with the current sample size (n = 24), assuming a one-tailed α = 0.05 and 80% power. The analysis indicated that correlations of approximately |r| ≥ 0.34 could be detected (corresponding to a medium-to-large effect size according to Cohen, 1988); smaller correlations would likely go undetected due to limited statistical power. Likewise, differences between means with an effect size of d = 0.5 for the repeated measures are detectable. Robotic System The mobile robot TIAGo Pro (PAL Robotics, Barcelona, Spain https://pal-robotics.com/robot/tiago-pro/ ) was used as a walking guide. The robot is equipped with two 7-degree-of-freedom robotic arms, force-torque sensing, laser scanners, and an RGB-D camera. During the experiment, the robot guided participants along a predefined walking path at a constant. Find details at Leven et al (in preparation). The robot introduced itself and gave verbal instructions where to touch it as well as announcements when it starts and ends the walk. No other verbal interaction happened during the physical contact. Experimental Conditions Participants completed four walking conditions that differed in the type of physical contact with the robot: No Contact: Walking next to the robot without any physical contact. Holding Hands: The participant held the robot’s wrist. Linking Arms: The participant linked arms with the robot. Full Forearm Contact: The participant rested the entire forearm on the robot’s arm. Each condition involved walking a 10-meter straight path back and forth twice, and each participant completed all four conditions. The order of conditions was balanced across participants to reduce order effects. Procedure At the beginning of the session, participants completed baseline questionnaires and a short baseline recording of physiological signals while seated. Afterwards, participants performed an initial walking trial without robot contact to assess gait speed. For each experimental condition, participants walked the predefined path together with the robot. After each condition, participants completed condition-specific questionnaires and short interview questions assessing comfort, safety, trust, and emotional state. The entire session followed the same general sequence for all participants. See Fig. 1 . Questionnaires Participants answered baseline questions on demography upon arrival (see also Leven et al). The Social Touch Questionnaire (STQ, Lapp & Croy, 2021 ) assessed individual differences in attitudes toward social touch before start of the experiment: a 20-item measure assessing attitudes toward interpersonal touch on a 5-point Likert scale (1 = “strongly disagree”, 5 = “strongly agree”). STQ sum scores were built as suggested by Lapp & Croy ( 2021 ) by averaging items loading on the three empirically derived factors: (1) Liking of Informal Social Touch,(LiST) that assesses comfort with casual touch (example item: I greet my close friends with a kiss on the cheek.) LiST asks about attitudes toward touch in concrete, specific situations, particularly within familiar contexts. The items refer to tangible behaviors and experiences such as childhood cuddling with family members, greeting rituals with close friends, professional massages, and handshakes with strangers. This factor is characterized by its focus on particular situations rather than abstract attitudes. (2) Liking of General Social Touch (LgST) that assesses positive attitudes toward social touch across contexts (example item: I generally seek physical contact with others.). This factor captures an abstract, overarching attitude toward social touch and one's self-perception as a touch-oriented person. The items use general formulations ("I generally...", "I consider myself...") and assess a fundamental disposition toward physical contact and affection independent of specific contexts or relationships. This factor reflects a person's broad touch attitude across different situations. (3) Dislike of Social Touch (DST) for avoidance or discomfort (example item: I would rather avoid shaking hands with strangers.). Higher scores indicate stronger tendencies in each respective dimension. This factor captures discomfort and aversion toward social touch, particularly in situations involving non-self-initiated or unexpected physical contact. The items primarily describe scenarios where the respondent lacks control over being touched, such as unexpected touch, physical contact with strangers or acquaintances in public settings, and situations where touch might feel intrusive or boundary-violating. Negative attitudes toward robots were assessed before and after the experiment (see Fig. 1 ) using the Negative Attitudes toward Robots Scale (NARS; Nomura et al., 2006 ) as in Zhou et al. ( 2021 ). The NARS is a self-report questionnaire consisting of 14 items measuring negative evaluations of robots. Items are rated on a 5-point Likert scale, with higher scores indicating more negative attitudes. NARS comprises three subscales as mean values: (1) negative attitudes toward situations of interaction with robots (discomfort or anxiety in direct interaction), (2) negative attitudes toward the social influence of robots (concerns about societal impact), and (3) negative attitudes toward emotional interaction with robots (rejection of emotional or social relationships with robots). The present study focused on subscale 1. A short version of the Positive and Negative Affect Schedule (PANAS, Watson et al., 1988 ) Ref. Version by Mayer et al, submitted for publication) measured current positive and negative affect on a 5-point Likert scale (1 = “not at all,” 5 = “very much”). PANAS scales were built as mean positive (PA) and mean negative affect (NA). Additionally, four self-developed items evaluated participants’ subjective experience during walking in contact with the robot, rated on the same 5-point Likert scale: -”The physical contact with the robot was comfortable.” -”I felt comfortable with the physical contact”. -”The contact was natural”. and “Please evaluate the joint walk overall on a scale from 1 to 10?” After the last condition, participants could provide additional open-ended comments regarding the study, the robot, or other observations. These responses were used for exploratory qualitative analyses. Data Analyses Linear regression models were performed in RStudio (Version 2026.01.0 + 392) to test for the statistical influence of social touch attitudes (STQ scales) on (1) the evaluation of the interaction on the four self-report questions listed above, (2) negative attitudes towards robots (NARS) before and after and (3) the response valence towards the whole experiment. STQ scales were centered. Separate models for the subscales LiST and LgST were built to avoid homoscedasticity. All models tested one-sided for significance with p < .05 and controlled for age as covariate. Model assumptions were visually checked using residual plots. Open answers to the final evaluation at the end of the study procedures were analyzed with two approaches: Qualitative data were analyzed using deductive thematic analysis. A coding framework was developed based on established dimensions of human-robot interaction in healthcare contexts (Broadbent et al., 2009 ; Vandemeulebroucke et al., 2018 ) comprising seven main categories. Two researchers independently applied this framework to all responses (MS and DM). Inter-rater reliability was assessed using Cohen's Kappa (mean κ = 0.422, range: -0.088–0.701). Discrepancies were discussed in a consensus meeting where category definitions were refined, particularly to distinguish between negative affect (rejection/concerns) and positive affect (acceptance/openness), and to consolidate machine-human comparisons under ethical considerations. Following these refinements, all discrepancies were resolved through discussion until full consensus was reached. The final framework comprised the following seven categories: perceived usefulness, technical performance & design, embodied experience & physicality, rejection & negative affect, values, ethics & societal context, acceptance & positive affect, and situational & contextual factors. Responses within each category were further analyzed inductively to identify emergent sub-themes and patterns, and representative quotations were selected to illustrate key themes. Additionally, two independent raters blind to the study’s hypotheses rated the valence of the open answer on a 5-point scale from 1 (very negative) to 5 (very positive). Mean response valence scores (averaged across raters) were submitted to statistical analyses for associations with STQ scales as described above. Results Sample Description Table 1 Sample Description Age (years), mean (SD) 75.79 (5.22) Range 68–88 Female, n (%) 20 (83.3) Living alone, n (%) 10 (41.7) Living with partner, n (%) 12 (50.0) Chronic physical condition, n (%) 6 (26.1) Regular medication intake, n (%) 19 (79.2) Baseline gait speed, mean (SD) 3.59 (0.90) Note. Values are presented as mean (SD) or n (%). The sample consisted of 24 older adults (20 female, 4 male). Participants ranged in age from 68 to 88 years ( M = 75.79, SD = 5.22), see Table 1 . All participants were able to walk independently. Average gait speed during the baseline walking assessment was 3.59 m/s ( SD = 0.90). Six participants (26.1%) reported at least one chronic physical condition, and five participants (20.8%) were currently receiving medical treatment. The majority of participants (79.2%) reported regular medication intake. Table 2 shows descriptive statistics of the subjective preferences towards social touch prior to the experiment and self-reports of mean affect and evaluation after the three conditions with physical contact. Table 2 Descriptive Statistics Variable Mean SD Range Assessed prior to joint walks: STQ Liking of general Social Touch 2.48 0.63 1.2–3.8 STQ Liking of informal Social Touch 2.45 0.77 1.67–5 NARS Scale negative attitudes, discomfort or anxiety 1.98 0.67 1–3.33 Mean evaluation over conditions: Positive Affect (PANAS) 4.17 0.84 2.5–5 Negative Affect (PANAS) 1.03 0.09 1–1.33 Physical contact felt comfortable 4.19 0.63 2.67–5 I felt comfortable 4.40 0.70 3–5 Physical contact felt natural 3.14 1.34 1–5 Evaluation of the walk 8.35 1.55 4.5–10 Final evaluation: Response valence in final open comments 2.92 1.14 1.5–5 Associations between attitudes towards social touch and subjective reports after the interaction with the robot Analyzes of associations between the participants’ preferences toward touch as assessed by STQ scales and their mean self-report after the three conditions with physical contact resulted in significant or trend-level effects as summarized in the following. Self-reports after different conditions did not differ significantly and are reported at Leven et al). Social touch preference (STQ-LgST, centered) predicted mean physical comfort while controlling for age. The overall model was not statistically significant, F (2, 21) = 1.63, p = .22, explaining 13% of the variance in physical well-being ( R² = .13, adjusted R² = .05). STQ-LgST showed a positive effect toward predicting physical well-being ( b = 0.34, SE = 0.19, t = 1.80, p = .043) corresponding to a partial correlation of r = 0.35 (medium effect size; Cohen, 1988), explaining approximately 12% of the variance in physical well-being. See Fig. 2 . Associations between attitudes towards social touch and negative attitudes towards robots before and after the interaction Another linear regression was conducted to examine whether social touch preference predicted negative attitudes towards robots (NARS scale negative attitudes, discomfort or anxiety toward direct interaction with robots) before and after the interaction. The model included an interaction term between STQ-LgST and time (pre or post experiment). The overall model was not statistically significant but showed a trend, F (4, 43) = 1.70, p = .09, explaining approximately 14% of the variance in NARS scores ( R² = .14, adjusted R² = .06). The main effect of STQ-LgST was negative and statistically significant ( b = − 0.46, SE = 0.21, t = − 2.26, p = .015), indicating that higher STQ-LgST scores were associated with lower NARS scores at the first time point (T1). The main effect of time showed lower NARS scores after the experiment compared to before ( b = − 1.27, SE = 0.74, t = − 1.71, p = .047). The interaction between STQ-LgST and time reached significance ( b = 0.52, SE = 0.29, t = 1.82, p = .038, corresponding to a partial correlation of r ≈ 0.36), suggesting that the negative relationship between STQ-LgST and NARS scores may be slightly attenuated after participating in the experiment (see Fig. 3 ). Qualitative evaluation of the overall study procedure Participants mentioned all seven categories in their comments. Table 3 shows the frequency of the categories related by the total number of comments in %, following the theory-based framework. Table 3 Frequency of category brought up by participants Categories Category 1 perceived usefulness, Category 2 technical perform-ance & design, Category 3 embodied experience & physicality, Category 4 rejection & negative affect, Category 5 values, ethics & societal context, Category 6 acceptance & positive affect, Category 7 contextual factors % of comments 45 45 25 40 30 55 45 Note. Comments without any content, e.g. “as told to the experimenter”, were neglected for this analysis. Thematic analysis revealed that participants recognized practical benefits of robotic assistance across daily living and care contexts, but at the same time drew clear ethical boundaries. Despite expressing positive affect and constructive technical feedback, participants consistently emphasized the ontological limitations of machines and the irreplaceability of human qualities like empathy and emotional connection. Many participants stated that robot use would depend on the specific context, the individual's needs, and the type of support required. For a systematic overview of the answers, see Table 4 . Table 4 Themes, sub-themes, and representative quotes from qualitative analysis Category Sub-theme Description Representative Quote Perceived usefulness Support in daily living Assistance with mobility, walking, and everyday activities; becoming helpers in daily life "could be well used in the area of everyday assistance, e.g., walking" Healthcare and care settings Use in nursing/care contexts; support for patients; relief for caregiving staff "appropriate assistance for a patient would be very beneficial and at the same time a relief for the nursing staff" Specialized applications Medical diagnostics; learning and play "In medical diagnostics, AI is already very useful" Groups who could benefit For people who need help; older adults "especially in work with the elderly, is promising" Technical performance & design Movement Speed and gait quality "The robot should be able to walk properly, it is still too primitive" Physical design features Appearance suggestions (color, clothing); grip/hand design; padding/comfort features "Robot could be a bit more colorful (perhaps even with 'clothing')" Communication style Voice quality and intonation; command style "voice too monotonous, better with different intonation" Emotional expression Concerns about artificial emotional displays "Robots that express human emotions are extremely unpleasant" Embodied experience & physicality Thermal quality Warmth of robot arms as positive feature; comfort of physical contact "The physical contact went much better than I expected because its arms were warm" Contact preferences and comfort Preferences for walking with or without physical contact; physical experience of grip; desire for padding and softer materials "Without physical contact, walking was most comfortable for me” Rejection & negative affect Initial threat/discomfort Initial negative reactions "The robot's arms are 'threatening' at first sight" Design and maturity concerns Technology not yet mature enough; aversion to specific features "it is still too primitive” Contact aversion Preference for avoiding physical contact; feeling disturbed "Without physical contact, walking was most comfortable for me" Values, ethics & societal context Ontological limitations Fundamental nature as machines without soul; inherent limitations "Robots are human-programmed devices, machines, technical aids without their own 'will', soulless, emotionless, without life” Irreplaceability of human qualities Cannot replace human soul, empathy, or tasks requiring human feeling "It is questionable whether they can replace a human's soul when someone seeks empathy"; Societal risks & power dynamics Danger to humanity; concerns about dependency, domination, and loss of control "I see a huge danger to humanity if robots determine many areas of our lives" Safety, reliability and resource concerns Technical failure risks; environmental impact; need for regulations "Like all technology, they can also be defective or malfunction" Cognitive autonomy Concern that robots should not replace independent thinking "should not replace independent thinking" Acceptance & positive affect General positive evaluation Enjoyment, interest, and positive experience "was fun, is interesting" Future optimism Hope for development and implementation; following progress with interest "I hope that robots will develop quickly" Willingness to adapt Openness to befriending or getting used to robots; imagining future acceptance "I can already imagine that they will provide good service one day" Appreciation despite concerns Acknowledging research value or expressing gratitude even while noting limitations "However, I can still feel the joy of research" Situational & contextual factors Setting specificity Home environments; daily living contexts; care facilities "can be well used as an aid in the daily home environment” Target population specificity For people needing help; older adults "for people who need help, it will be very useful. I am glad that I can still manage without help" Task and domain specificity Appropriate for specific tasks (medical diagnostics, specific work areas) but not others "robots should not perform tasks that should be done by humans through feeling" Conditional implementation Situation-dependent appropriateness; need for proper regulations "depends on programming and uniform laws" Associations between attitudes towards social touch and response valence To additionally examine whether individual differences in touch attitudes relate to these evaluations, we analyzed associations between STQ scores and response valence. The overall linear regression model on social touch preference (STQ LiST) predicting response valence of overall evaluation, was marginally significant, F(2, 17) = 3.08, p = .072, and explained approximately 27% of the variance in response valence (R² = .27, adjusted R² = .18). STQ-LgST was a significant predictor (b = − 0.95, SE = 0.41, t(17) = − 2.29, p = .017), indicating that higher social touch preference was associated with more positive evaluations of the robot interaction (see Fig. 4 ). Regression models for other self-report items (e.g. after the conditions: “The physical contact with the robot was comfortable”, “The contact was natural”, “Please evaluate the joint walk overall”) did not result in any significant or trend-level effects. In none of the quantitative analyses, age as covariate reached significance. Discussion Summary of findings This mixed-methods study investigated whether individual differences in attitudes toward social touch influence older adults' responses to robotic touch assistance. General touch attitudes were associated with evaluations of robotic interaction. Participants with more positive attitudes toward social touch, particularly general social touch, reported higher comfort after physical contact with the robot and rated the walking experience more favourably. Similarly, participants with more positive attitudes to touch expressed more positive overall evaluations in their open-ended comments. Qualitative analysis provided deeper insight into how older adults evaluate robotic touch beyond these individual differences. Participants recognized practical benefits, but at the same time drew clear ethical boundaries. Despite expressing positive affect and constructive technical feedback, they consistently emphasized the inherent limitations of machines and the irreplaceability of human qualities like empathy. Participants made it also clear that their acceptance of this technology was highly dependent on specific contexts, individual needs, and task requirements. These findings have direct implications for the implementation of touch-capable robots in geriatric care settings. Individual Differences in Touch Attitudes and Robot Acceptance Our study showed that individuals with more positive touch attitudes reported higher comfort after walking with TIAGo Pro, evaluated the application as more positive and commented more positively on their general experience with the robot. These findings, interpreted with caution given the small effect sizes, support our hypothesis that touch attitudes modulate the acceptance of robotic devices. Thereby, touch attitudes add to the list of individual differences that influence technology acceptance, such as age, gender, education, personality type, resilience, experience and expectations (Gessl et al., 2019). Furthermore, literature on human care emphasizes that patients' individual characteristics and preferences regarding touch must be taken into account and respected by medical professionals (Davidhizar et al., 1997). The present findings suggest that such preferences are also important for the acceptance of robotic touch and should be further investigated in larger studies. Person-centered care is a cornerstone of geriatric medicine, and the present findings suggest this principle should extend to decisions about robotic touch. Before the robot interaction, participants with more positive attitudes toward general social touch held less/fewer negative attitudes toward robots (negative association between STQ-LgST and NARS). However, after hands-on experience, attitudes toward robots improved across all participants, and the association between touch attitudes and robot attitudes was attenuated. This suggests that direct positive experience with the robot reduced initial skepticism, particularly among those with less favorable touch attitudes. This finding highlights the importance of experiential learning in robot acceptance and suggests that concerns based on general attitudes may be mitigated through positive direct experience which is in line with similar research in different settings (Zhou et al, 2021 ). Understanding the mechanisms underlying this association is important for implementation. Positive attitudes toward touch might be related to more positive robot experiences for two possible reasons: individuals with positive touch attitudes may be generally more open to physical interaction, also with non-humans. This suggests that touch preferences reflect a broader openness to tactile contact rather than being specific to human touch. Alternatively, individuals with more positive touch attitudes might experience greater comfort with the specific tactile qualities of the robot (such as warmth and firmness). Future research should disentangle whether touch attitudes predict robot acceptance due to generalized tactile openness or specific design features. Practical benefits and ethical boundaries An interesting finding was that the participants acknowledged the practical utility of robots such as TIAGo Pro in healthcare, but also drew clear ethical boundaries. Despite reporting positive experiences during direct interaction with TIAGo Pro, including comfort and favourable evaluations of the walking experience, participants consistently emphasized in their open-ended reflections that robots remain fundamentally limited as machines and cannot replace essential human qualities such as empathy and emotional connection. This pattern mirrors findings from focus groups with older adults and carers across three European countries, where participants adamantly maintained that robots should not replace human contact, viewing persuasion and emotional understanding as distinctly human skills (Sorell & Draper, 2014 ). In geriatric healthcare specifically, where emotional connection and dignity are central to quality care, this distinction carries particular weight. This suggests that positive embodied experiences with robotic touch do not automatically translate into unreserved acceptance of care robots. Instead, they rather coexist with critical reflection about appropriate roles and limitations. A systematic review of empirical evidence on socially assistive devices highlighted this dual nature of interaction: users frequently attributed internal states to devices while simultaneously remaining aware of their mechanical nature (Haltaufderheide et al., 2023 ). In this study, TIAGo Pro was primarily tested in a physical interaction with the participants (joint walking), during which it did not interact verbally with participants. Future studies should also include verbal interaction to test whether concerns of non-emotionality in humanoid robots persist with this additional component of communication. Participants' acceptance was clearly context-dependent rather than general. They distinguished between tasks where robotic assistance seemed appropriate (e.g., mobility support, daily living activities, medical diagnostics) and domains where human presence was deemed irreplaceable (e.g., tasks requiring emotional understanding or "feeling"). (Sorell & Draper, 2014 ) similarly found that users assigned different roles to robots (servant, healthcare provider, companion) and used corresponding role norms to justify their ethical positions on robot behaviour. This nuanced perspective aligns with recent conceptualizations of touch in healthcare as having complex communicative, social, and affective dimensions that cannot be reduced to simple instrumental functions (Buono et al., 2025). Our findings suggest that older adults as end-users maintain a sophisticated understanding of both the potential and the limits of robotic care technology. Implications for Implementation The present findings have several practical implications for implementing touch-capable robots in care settings. First, person-centered approaches remain important. The role of touch attitudes appears to be time-dependent and outcome-specific. While general robot attitudes improved across all participants after hands-on experience, suggesting that direct exposure can overcome initial skepticism, touch attitudes continued to predict comfort during the interaction itself. This suggests that while acceptance may be achievable through positive experience regardless of touch preferences, the quality of the subjective experience may still vary based on individual differences. Thus, person-centered approaches are important not merely to ensure acceptance, but to optimize the individual experience and maximize well-being during robot-assisted care. Skeptical individuals may accept robotic assistance after exposure but experience it as less comfortable or pleasant depending on their a priori preferences, which could affect long-term adherence and satisfaction. Second, our findings underscore the importance of context-appropriate implementation. Participants' distinctions between appropriate and inappropriate robot applications align with emerging evidence that social robot effectiveness varies substantially by setting, format, and duration of intervention (Yen, H.-Y., et al., 2024). Meta-analytic evidence shows that group-based activities produce stronger effects than individual sessions, and longer interventions yield greater improvements (Yen, H.-Y., et al., 2024). Similarly, cognitive benefits appear more pronounced in cognitively intact individuals (Hermann, J., et al., 2024 ). Our qualitative findings extend this by showing that older adults themselves recognize such contextual dependencies and distinguish between tasks where robotic assistance seems beneficial versus domains requiring human presence. Third, the coexistence of positive direct experiences with critical ethical reflection suggests that acceptance of care robots is not a binary construct but involves a balance between practical benefits and value-based concerns. This has implications for how such technologies should be introduced: transparency about capabilities and limitations, respect for individual preferences, and acknowledgment of the irreplaceability of human care may be as important as technical performance. Limitations and Future Directions Several limitations should be considered when interpreting these findings. Our sample was relatively small (N = 24) and predominantly female, which may limit generalizability and means that effects of small magnitude may have gone undetected due to limited statistical power. The results should be replicated and expanded in additional samples. The participants were living independently or with a partner or family and able to walk independently, representing a relatively healthy subset of older adults. Responses among frailer individuals, those with cognitive impairments, or those in long-term care facilities, the very populations most likely to encounter care robots, may differ substantially. During recruitment, the interaction with a humanoid robot was explicitly announced. Consequently, the sample may be subject to selection bias, as participation was based on voluntary response to the study invitation. Furthermore, the study involved brief, controlled exposure to robotic touch in an experimental setting. Longer-term familiarity with robots might alter both immediate reactions and broader attitudes. Meta-analytic evidence suggests that intervention duration matters for effectiveness (Yen, H.-Y., et al., 2024), and longitudinal studies are needed to examine whether initial touch attitudes predict sustained acceptance over time or whether attitudes change with repeated exposure. Previous work suggests that individual difference factors like social role expectations strongly influence initial interactions but become less important with experience as users adapt to the robot's actual capabilities (Koay et al., 2014 ). Touch attitudes may follow a similar trajectory, exerting their strongest influence during first encounters. Additionally, while we assessed general touch attitudes as individual difference variables, we did not measure situational preferences for wanting touch in particular moments (Sailer et al., 2024 ). Future research should examine whether state-dependent touch preferences similarly moderate responses to robotic touch, and whether robots might be programmed to respond adaptively to such momentary preferences. Our study focused on users' perceptions and evaluations of robotic touch but did not systematically examine behavioural adaptation processes during interaction. Systematic reviews of socially assistive devices describe a "behavioural alignment" phenomenon, where users alter their behavior and habits to accommodate device limitations, for example, changing voice patterns to improve speech recognition or restricting themselves to simpler functions (Haltaufderheide et al., 2023 ). From an autonomy perspective, such adaptations represent a potential cost, where improvements in independence through robotic assistance may be offset by users conforming to technical constraints. Future research on touch-capable robots should investigate whether similar adaptation processes occur in physical interactions, for instance, whether users modify their movement patterns, touch preferences, or positioning to accommodate robotic limitations, and how such adaptations affect the autonomy-enhancing promise of assistive robotics. Finally, while our study focused on touch attitudes, other individual differences may also moderate acceptance of robotic care. Factors such as prior technology experience (Hermann, J., et al., 2024 ; Papadopoulos, I., et al., 2020 ), loneliness levels (given evidence that robots can reduce loneliness; (Robinson, H., et al., 2013 ), and general attitudes toward care robots should be examined alongside touch preferences in future work. Conclusion This study provides evidence that older adults' attitudes toward interpersonal touch shape their experiences with robotic assistance that involves touch. Those with more positive touch attitudes experienced greater comfort during physical contact with the robot and provided more positive evaluations. These quantitative patterns coexisted with nuanced qualitative reflections. While participants acknowledged practical utility and reported positive embodied experiences, they simultaneously articulated ethical concerns and underscored the irreplaceable nature of human connection in caregiving. This suggests that robot acceptance not only encompasses immediate tactile comfort but also deeper considerations about appropriate roles for technology in care contexts. As touch-capable robots advance, implementation strategies must account for this complexity. In geriatric healthcare, where person-centered care is a foundational principle, respecting individual variation in touch preferences, optimizing tactile design features, and maintaining transparency about what robotic systems can and cannot provide will be essential for ethical and effective integration. Declarations Author Contributions CREDIT Funding Acquisition: CJM, KM, ME Conceptualization: CJM, KM, ME, CW, MA Data Curation: LL, MS, TB Formal Analysis: ME, US, MS Writing Original Draft: ME, US Visualization: ME, US Project Administration: MS, CW Supervision: KM, ME, US Resources: KM, ME Writing Review & Editing: all authors Ethic Declaration Ethical approval was granted by the Ethics Committee of the Medical Faculty at Heidelberg University (S-290/2024). All participants provided informed consent in accordance with the Declaration of Helsinki. Clinical trial number: not applicable. Conflict of Interest The authors declare no conflict of interest. Funding Statement Funded by the Heidelberg Karlsruhe Research Partnership (HEiKA, Project PerRot-G) to ME and KM and the Dres. Majic/Majic-Schlez-Foundation at Medical Faculty Heidelberg to CJM. HEiKA funding is provided by Heidelberg University and the Karlsruhe Institute of Technology (KIT) as part of their Excellence University funding. Author Contribution Funding Acquisition: CJM, KM, MEConceptualization: CJM, KM, ME, CW, MAData Curation: LL, MS, TBFormal Analysis: ME, US, MSWriting Original Draft: ME, USVisualization: ME, USProject Administration: MS, CWSupervision: KM, ME, USResources: KM, MEWriting Review & Editing: all authors Acknowledgements We thank all participants for taking part in our study. We thank Dominik Misok (DM) for response valence ratings and preparation of data and Beate Ditzen and Charlotte Raithel for overall support of the project. Data Availability Fully anonymized data is available upon request by the authors. References Abdi J, Al-Hindawi A, Ng T, Vizcaychipi MP. (2018). Scoping review on the use of socially assistive robot technology in elderly care . https://doi.org/10.1136/bmjopen-2017-018815 Andersen PA, Leibowitz K. 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(2020). *Enablers and barriers to the implementation of socially assistive humanoid robots in health and social care: A systematic review* . https://doi.org/10.1136/bmjopen-2019-033096 Robinson H, MacDonald B, Kerse N, Broadbent E. The Psychosocial Effects of a Companion Robot: A Randomized Controlled Trial. J Am Med Dir Assoc. 2013;14(9):661–7. https://doi.org/10.1016/j.jamda.2013.02.007 . Routasalo P. Physical touch in nursing studies: A literature review. J Adv Nurs. 1999;30(4):843–50. https://doi.org/10.1046/j.1365-2648.1999.01156.x . Sailer U, Friedrich Y, Asgari F, Hassenzahl M, Croy I. Determinants for positive and negative experiences of interpersonal touch: Context matters. Cognition Emot. 2024;38(4):565–86. https://doi.org/10.1080/02699931.2024.2311800 . (WOS:001162915300001). Schneider E, Hopf D, Aguilar-Raab C, Scheele D, Neubauer AB, Sailer U, Hurlemann R, Eckstein M, Ditzen B. (2023). Affectionate touch and diurnal oxytocin levels: An ecological momentary assessment study. eLife , 12 . https://doi.org/10.7554/eLife.81241 Sorell T, Draper H. Robot carers, ethics, and older people. Ethics Inf Technol. 2014;16(3):183–95. https://doi.org/10.1007/s10676-014-9344-7 . Tanzer M, Koukoutsakis A, Galouzidi I, Jenkinson PM, Hammond C, Banissy MJ, Fotopoulou A. Touch in psychotherapy: Experiences, desires and attitudes in a large population survey. Psychother Research: J Soc Psychother Res. 2025;1–16. https://doi.org/10.1080/10503307.2025.2534971 . Vandemeulebroucke T, De Casterlé BD, Gastmans C. How do older adults experience and perceive socially assistive robots in aged care: A systematic review of qualitative evidence. Aging Ment Health. 2018;22(2):149–67. https://doi.org/10.1080/13607863.2017.1286455 . Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: The PANAS scales. J Personal Soc Psychol. 1988;54(6):1063–70. https://doi.org/10.1037/0022-3514.54.6.1063 . Whitcher SJ, Fisher JD. (1979). Multidimensional reaction to therapeutic touch in a hospital setting. J Pers Soc Psychol , 37 (1), Article 1. (458550). https://doi.org/10.1037//0022-3514.37.1.87 Yen H-Y, Huang CW, Chiu H-L. & J., & G. (2024). The Effect of Social Robots on Depression and Loneliness for Older Residents in Long-Term Care Facilities: A Meta-Analysis of Randomized Controlled Trials . https://doi.org/10.1016/j.jamda.2024.02.017 Yen H-Y, Huang CW, Chiu H-L, Jin G. The Effect of Social Robots on Depression and Loneliness for Older Residents in Long-Term Care Facilities: A Meta-Analysis of Randomized Controlled Trials. J Am Med Dir Assoc. 2024;25(6):104979. https://doi.org/10.1016/j.jamda.2024.02.017 . Zhou Y, Kornher T, Mohnke J, Fischer MH. Tactile Interaction with a Humanoid Robot: Effects on Physiology and Subjective Impressions. Int J Social Robot. 2021;13(7):1657–77. https://doi.org/10.1007/s12369-021-00749-x . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 20 Apr, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviewers invited by journal 17 Apr, 2026 Editor assigned by journal 17 Apr, 2026 Editor invited by journal 14 Apr, 2026 Submission checks completed at journal 14 Apr, 2026 First submitted to journal 14 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9277646","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":627746237,"identity":"a6cee60a-13f4-4ae2-a335-fd2432666ead","order_by":0,"name":"Monika 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(KIT)","correspondingAuthor":false,"prefix":"","firstName":"Katja","middleName":"","lastName":"Mombaur","suffix":""},{"id":627746245,"identity":"51c68562-1fe8-4dcf-a080-69ef2ccb7805","order_by":8,"name":"Uta Sailer","email":"","orcid":"","institution":"University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Uta","middleName":"","lastName":"Sailer","suffix":""}],"badges":[],"createdAt":"2026-03-31 09:25:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9277646/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9277646/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107838635,"identity":"976f5eae-160b-4c29-9745-c986ac22cd2d","added_by":"auto","created_at":"2026-04-26 17:12:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":88885,"visible":true,"origin":"","legend":"\u003cp\u003eTimeline of procedures relevant for the present data\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9277646/v1/512960c01db118527c45dc14.png"},{"id":107870189,"identity":"7c766602-e444-4938-9002-db3b819de697","added_by":"auto","created_at":"2026-04-27 07:39:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":93257,"visible":true,"origin":"","legend":"\u003cp\u003eMean physical comfort after the three conditions with the robot is associated with social touch preferences as assessed with STQ-LgST.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9277646/v1/1bdf14de0b3b2b869e03f135.png"},{"id":107838636,"identity":"65a2a72e-f9b4-4136-8eb8-4f1fa248a376","added_by":"auto","created_at":"2026-04-26 17:12:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":103821,"visible":true,"origin":"","legend":"\u003cp\u003eBefore interacting with the robot, positive attitudes towards social touch and negative towards robots are inversely associated. After the interaction, this association is dissolved.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9277646/v1/a1930648eda9729fa8aef676.png"},{"id":107838637,"identity":"7a9d3db5-bad7-4086-a9f5-fde0f470c0e8","added_by":"auto","created_at":"2026-04-26 17:12:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":97610,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between STQ and response valence (1 = very positive, 5 = very negative) in open evaluation\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9277646/v1/3b3b7ac887513101ee53647f.png"},{"id":108006894,"identity":"3d73f8c8-18a8-49cc-b4da-cf3b71f4abfc","added_by":"auto","created_at":"2026-04-28 12:57:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":801122,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9277646/v1/a2c13f49-517d-43fc-91c2-456f96ca6460.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Individual differences in touch attitudes shape acceptance of robotic touch in older adults: Evidence from a medical center setting","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInterpersonal touch is a fundamental aspect of human social interaction and plays a crucial role in physical and mental health across the lifespan. This includes geriatric care contexts, where physical contact is both clinically relevant and increasingly difficult to ensure given staff shortages and systemic pressures. Research has demonstrated that tactile contact can reduce stress and anxiety (Eckstein et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Packheiser et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and promote feelings of safety and social connection (Debrot et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Jakubiak \u0026amp; Feeney, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These beneficial effects are mediated through multiple neurobiological pathways, among them the release of oxytocin (Schneider et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), a neuropeptide associated with social attachment and stress reduction that inhibits the hypothalamic\u0026ndash;pituitary\u0026ndash;adrenal axis (HPA) axis and thereby contributes to decreased cortisol levels (Kidd et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn medical and care settings, touch is frequently discussed as a component of nursing care. Systematic reviews reveal that touch in nursing practice is predominantly instrumental (task-oriented) rather than expressive or caring in nature (Gleeson \u0026amp; Timmins, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Routasalo, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Studies suggest potential benefits in specific contexts such as reduced anxiety in intensive care patients receiving touch (Henricson et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), decreased agitation following hand massage in some dementia patients (Hansen Edwards et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), as well as reduced anxiety and lower blood pressure in female surgical patients touched during preoperative teaching (Whitcher \u0026amp; Fisher, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1979\u003c/span\u003e). However, comprehensive systematic reviews emphasize that there is insufficient evidence to draw general conclusions about the efficacy of touch interventions (Packheiser et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Research findings on the physiological and psychological effects of touch remain limited and contradictory (Routasalo, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Recent reviews highlight that touch in healthcare cannot be reduced to a simple instrumental versus expressive dichotomy. Rather, touch in healthcare has complex communicative, social, and affective dimensions that depend on context, consent, and individual differences (Buono et al., 2025).\u003c/p\u003e \u003cp\u003eThese challenges and limitations in implementing human touch in care settings have contributed to growing interest in technological developments. Healthcare systems face increasing staff shortages and time constraints. At the same time, social robots have emerged as one possible way to provide tactile interaction to patients. The use of social robots in healthcare settings, particularly in geriatric care, has increased substantially in recent years (Abdi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Broekens et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These robots range from companion robots designed primarily for social and emotional support to more complex assistive systems that can support activities of daily living (Abdi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Hermann, Oktay, et al., 2024). Proponents argue that robots could address critical challenges in elder care, including chronic staff shortages, the physical demands of caregiving, and the need for consistent patient monitoring (Papadopoulos, Koulouglioti, et al., 2020). Therefore robotic technology raises practical opportunities, but also fundamental questions about the nature of care and the role of technology in meeting basic human needs for physical contact.\u003c/p\u003e \u003cp\u003eA key question concerns whether robotic touch might provide similar benefits to human touch. Recent meta-analytic evidence suggests that social robot interventions can produce significant positive effects on psychosocial outcomes. This meta-analysis of eight randomized controlled trials found large effect sizes for reductions in both depression and loneliness among older adults in long-term care facilities (Yen, Huang, et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Individual studies have shown that companion robots incorporating tactile interaction, such as the seal-like PARO, can significantly reduce loneliness over extended periods (Robinson, MacDonald, et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These benefits appear to also depend on implementation format, where group-based activities have stronger effects than individual sessions, and intervention duration, where longer interventions produce greater improvements (Yen, H.-Y., et al., 2024). Experience with social robots seems to shape attitudes towards them as shown in one study comparing negative attitudes towards robots (NARS scale by Nomura et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) before and after a physical interaction with the humanoid robot Pepper (Zhou et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e): While attitudes did not change in general, ratings for specific items on social interactions with robots improved.\u003c/p\u003e \u003cp\u003eDespite these promising findings, substantial barriers limit widespread implementation. These barriers include technical limitations and malfunctions, high costs, concerns about acceptance among caregivers, and the low to moderate methodological quality of many existing studies (Abdi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Papadopoulos, Koulouglioti, et al., 2020). Moreover, emerging evidence suggests that not all older adults respond similarly to social robots. For instance, cognitive benefits of robot interaction appear more pronounced in cognitively intact individuals, while effects vary based on factors such as previous technology experience and personal preferences (Hermann, Oktay, et al., 2024; Papadopoulos, Koulouglioti, et al., 2020; Yen, Huang, et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, little is known about whether individual differences in touch preferences, a key factor in human-to-human care interactions, similarly influence older adults' responses to physical touch from robots during hands-on assistance.\u003c/p\u003e \u003cp\u003eIndividuals differ considerably in how much they enjoy or avoid physical touch. While some individuals find touch comforting and seek it out, others experience touch as uncomfortable or intrusive and prefer to avoid it (Andersen \u0026amp; Leibowitz, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1978\u003c/span\u003e; Ozolins \u0026amp; Sandberg, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). These preferences appear to be relatively stable individual characteristics that influence how people respond to touch (Hielscher \u0026amp; Mahar, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Jakubiak \u0026amp; Feeney, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Krahe et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Tanzer et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), but also how preferences of wanting touch in a particular situation play a role (Sailer et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe role of individual differences in touch preferences for the acceptance of robotic touch during physical assistance has direct implications for person-centered implementation in geriatric care. Touch-capable robots are increasingly being introduced into geriatric care settings, but implementation strategies rarely account for the substantial individual variation in how older adults experience physical contact. While person-centered care is a well-established principle in geriatric medicine, extending this principle to robotic touch requires empirical evidence about which individual characteristics are important. It also remains an open question whether direct hands-on experience with a robot can override initial predispositions based on touch attitudes, a question with direct practical relevance for how robotic systems are introduced in care contexts. The present mixed-methods study aimed to investigate how older adults perceive and evaluate robotic touch after direct, hands-on experience with a haptically interactive social robot (TIAGo Pro). We examined how older adults evaluated a human-robot interaction by collecting ratings following touch interactions, including current subjective feelings. Participants' broader reflections on social robots in care were gathered through qualitative analysis of their open-ended comments about their experiences with TIAGo Pro. Self-reported quantitative ratings were then integrated with qualitative reflections to investigate whether individual differences in general attitudes toward touch are associated with responses to robotic touch.\u003c/p\u003e \u003cp\u003eWe hypothesized that perception and acceptance of robotic touch would be influenced by participants' attributes, with general attitudes toward touch being a key individual characteristic. Understanding whether individuals' general attitude to touch predicts their acceptance of robotic touch is critical for implementing such technologies in care settings. By combining direct experience with robotic touch and assessment of individual factors, this study provides empirically grounded insights directly from older adults as end-users. This approach illuminates factors shaping the acceptance of touch-capable robots in older adults in medical settings.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThe mixed-methods study used a within-subject experimental design to examine the effects of different forms of physical contact during robot-assisted walking guidance. All participants completed all experimental conditions, with the order randomized between participants.\u003c/p\u003e \u003cp\u003eThis study was conducted from October to November 2025 in Heidelberg, Germany at a geriatric hospital (Agaplesion Bethanien Hospital Heidelberg). The larger overall project is preregistered (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://osf.io/9dpxw\u003c/span\u003e\u003cspan address=\"https://osf.io/9dpxw\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and approved by the local ethics committee (S-290/2024). Other research questions with focus on robotic technology are prepared for publication elsewhere (Leven et al, in preparation, Mayer et al, submitted for publication).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eTwenty-four older adults (age range: 68\u0026ndash;88 years) participated in the study. Recruitment was conducted through the participant database of previous studies of the research department at the Agaplesion Bethanien Hospital Heidelberg which included individuals who had expressed interest in being contacted for future research. These individuals were contacted via telephone or email. Exclusion criteria included acute illness, severe cognitive impairment, or conditions preventing safe participation in guided walking. Participants were community-dwelling or living in assisted settings and were able to walk independently without walking aids.\u003c/p\u003e \u003cp\u003eAn a priori power analysis for condition comparisons (t-test for dependent means, one-tailed) was conducted using G*Power (Faul et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) based on previous similar research in healthy volunteers. Zhou et al (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported that N\u0026thinsp;=\u0026thinsp;21 persons showed a physiological response to actively touching a robot (effect size partial ƞ2\u0026thinsp;=\u0026thinsp;0.240, corresponds to approx. Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;1.12) and changes in some of their subjective attitude towards robots indicating more trust after the touch experience with the robot (d\u0026thinsp;=\u0026thinsp;0.41). In order to detect similar medium to large effects with 80% power and 5% alpha error probability, we planned to include at least N\u0026thinsp;=\u0026thinsp;25. For feasibility reasons, the study design was changed to a within subject design. A post hoc sensitivity analysis was also conducted to determine the smallest Pearson correlation and differences between two measures that could be reliably detected with the current sample size (n\u0026thinsp;=\u0026thinsp;24), assuming a one-tailed α\u0026thinsp;=\u0026thinsp;0.05 and 80% power. The analysis indicated that correlations of approximately |r| \u0026ge; 0.34 could be detected (corresponding to a medium-to-large effect size according to Cohen, 1988); smaller correlations would likely go undetected due to limited statistical power. Likewise, differences between means with an effect size of d\u0026thinsp;=\u0026thinsp;0.5 for the repeated measures are detectable.\u003c/p\u003e\n\u003ch3\u003eRobotic System\u003c/h3\u003e\n\u003cp\u003eThe mobile robot TIAGo Pro (PAL Robotics, Barcelona, Spain \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pal-robotics.com/robot/tiago-pro/\u003c/span\u003e\u003cspan address=\"https://pal-robotics.com/robot/tiago-pro/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used as a walking guide. The robot is equipped with two 7-degree-of-freedom robotic arms, force-torque sensing, laser scanners, and an RGB-D camera. During the experiment, the robot guided participants along a predefined walking path at a constant. Find details at Leven et al (in preparation). The robot introduced itself and gave verbal instructions where to touch it as well as announcements when it starts and ends the walk. No other verbal interaction happened during the physical contact.\u003c/p\u003e\n\u003ch3\u003eExperimental Conditions\u003c/h3\u003e\n\u003cp\u003eParticipants completed four walking conditions that differed in the type of physical contact with the robot:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eNo Contact: Walking next to the robot without any physical contact.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHolding Hands: The participant held the robot\u0026rsquo;s wrist.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eLinking Arms: The participant linked arms with the robot.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eFull Forearm Contact: The participant rested the entire forearm on the robot\u0026rsquo;s arm.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eEach condition involved walking a 10-meter straight path back and forth twice, and each participant completed all four conditions. The order of conditions was balanced across participants to reduce order effects.\u003c/p\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003e At the beginning of the session, participants completed baseline questionnaires and a short baseline recording of physiological signals while seated. Afterwards, participants performed an initial walking trial without robot contact to assess gait speed.\u003c/p\u003e \u003cp\u003eFor each experimental condition, participants walked the predefined path together with the robot. After each condition, participants completed condition-specific questionnaires and short interview questions assessing comfort, safety, trust, and emotional state. The entire session followed the same general sequence for all participants. See Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eQuestionnaires\u003c/h2\u003e \u003cp\u003eParticipants answered baseline questions on demography upon arrival (see also Leven et al). The Social Touch Questionnaire (STQ, Lapp \u0026amp; Croy, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) assessed individual differences in attitudes toward social touch before start of the experiment: a 20-item measure assessing attitudes toward interpersonal touch on a 5-point Likert scale (1 = \u0026ldquo;strongly disagree\u0026rdquo;, 5 = \u0026ldquo;strongly agree\u0026rdquo;). STQ sum scores were built as suggested by Lapp \u0026amp; Croy (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) by averaging items loading on the three empirically derived factors: (1) Liking of Informal Social Touch,(LiST) that assesses comfort with casual touch (example item: I greet my close friends with a kiss on the cheek.) LiST asks about attitudes toward touch in concrete, specific situations, particularly within familiar contexts. The items refer to tangible behaviors and experiences such as childhood cuddling with family members, greeting rituals with close friends, professional massages, and handshakes with strangers. This factor is characterized by its focus on particular situations rather than abstract attitudes. (2) Liking of General Social Touch (LgST) that assesses positive attitudes toward social touch across contexts (example item: I generally seek physical contact with others.). This factor captures an abstract, overarching attitude toward social touch and one's self-perception as a touch-oriented person. The items use general formulations (\"I generally...\", \"I consider myself...\") and assess a fundamental disposition toward physical contact and affection independent of specific contexts or relationships. This factor reflects a person's broad touch attitude across different situations. (3) Dislike of Social Touch (DST) for avoidance or discomfort (example item: I would rather avoid shaking hands with strangers.). Higher scores indicate stronger tendencies in each respective dimension. This factor captures discomfort and aversion toward social touch, particularly in situations involving non-self-initiated or unexpected physical contact. The items primarily describe scenarios where the respondent lacks control over being touched, such as unexpected touch, physical contact with strangers or acquaintances in public settings, and situations where touch might feel intrusive or boundary-violating.\u003c/p\u003e \u003cp\u003eNegative attitudes toward robots were assessed before and after the experiment (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) using the Negative Attitudes toward Robots Scale (NARS; Nomura et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) as in Zhou et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The NARS is a self-report questionnaire consisting of 14 items measuring negative evaluations of robots. Items are rated on a 5-point Likert scale, with higher scores indicating more negative attitudes. NARS comprises three subscales as mean values: (1) negative attitudes toward situations of interaction with robots (discomfort or anxiety in direct interaction), (2) negative attitudes toward the social influence of robots (concerns about societal impact), and (3) negative attitudes toward emotional interaction with robots (rejection of emotional or social relationships with robots). The present study focused on subscale 1.\u003c/p\u003e \u003cp\u003eA short version of the Positive and Negative Affect Schedule (PANAS, Watson et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1988\u003c/span\u003e) Ref. Version by Mayer et al, submitted for publication) measured current positive and negative affect on a 5-point Likert scale (1 = \u0026ldquo;not at all,\u0026rdquo; 5 = \u0026ldquo;very much\u0026rdquo;). PANAS scales were built as mean positive (PA) and mean negative affect (NA).\u003c/p\u003e \u003cp\u003eAdditionally, four self-developed items evaluated participants\u0026rsquo; subjective experience during walking in contact with the robot, rated on the same 5-point Likert scale:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e-\u0026rdquo;The physical contact with the robot was comfortable.\u0026rdquo;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e-\u0026rdquo;I felt comfortable with the physical contact\u0026rdquo;.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e-\u0026rdquo;The contact was natural\u0026rdquo;.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eand \u0026ldquo;Please evaluate the joint walk overall on a scale from 1 to 10?\u0026rdquo;\u003c/p\u003e \u003cp\u003eAfter the last condition, participants could provide additional open-ended comments regarding the study, the robot, or other observations. These responses were used for exploratory qualitative analyses.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Analyses\u003c/h3\u003e\n\u003cp\u003eLinear regression models were performed in RStudio (Version 2026.01.0\u0026thinsp;+\u0026thinsp;392) to test for the statistical influence of social touch attitudes (STQ scales) on (1) the evaluation of the interaction on the four self-report questions listed above, (2) negative attitudes towards robots (NARS) before and after and (3) the response valence towards the whole experiment. STQ scales were centered. Separate models for the subscales LiST and LgST were built to avoid homoscedasticity. All models tested one-sided for significance with \u003cem\u003ep\u003c/em\u003e \u0026lt; .05 and controlled for age as covariate. Model assumptions were visually checked using residual plots.\u003c/p\u003e \u003cp\u003eOpen answers to the final evaluation at the end of the study procedures were analyzed with two approaches:\u003c/p\u003e \u003cp\u003eQualitative data were analyzed using deductive thematic analysis. A coding framework was developed based on established dimensions of human-robot interaction in healthcare contexts (Broadbent et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Vandemeulebroucke et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) comprising seven main categories. Two researchers independently applied this framework to all responses (MS and DM). Inter-rater reliability was assessed using Cohen's Kappa (mean κ\u0026thinsp;=\u0026thinsp;0.422, range: -0.088\u0026ndash;0.701). Discrepancies were discussed in a consensus meeting where category definitions were refined, particularly to distinguish between negative affect (rejection/concerns) and positive affect (acceptance/openness), and to consolidate machine-human comparisons under ethical considerations. Following these refinements, all discrepancies were resolved through discussion until full consensus was reached. The final framework comprised the following seven categories: perceived usefulness, technical performance \u0026amp; design, embodied experience \u0026amp; physicality, rejection \u0026amp; negative affect, values, ethics \u0026amp; societal context, acceptance \u0026amp; positive affect, and situational \u0026amp; contextual factors. Responses within each category were further analyzed inductively to identify emergent sub-themes and patterns, and representative quotations were selected to illustrate key themes.\u003c/p\u003e \u003cp\u003eAdditionally, two independent raters blind to the study\u0026rsquo;s hypotheses rated the valence of the open answer on a 5-point scale from 1 (very negative) to 5 (very positive). Mean response valence scores (averaged across raters) were submitted to statistical analyses for associations with STQ scales as described above.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSample Description\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSample Description\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years), mean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.79 (5.22) Range 68\u0026ndash;88\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (83.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving alone, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (41.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with partner, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (50.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic physical condition, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (26.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular medication intake, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (79.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline gait speed, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.59 (0.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cem\u003eNote.\u003c/em\u003e Values are presented as mean (SD) or n (%).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe sample consisted of 24 older adults (20 female, 4 male). Participants ranged in age from 68 to 88 years (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;75.79, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.22), see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. All participants were able to walk independently.\u003c/p\u003e \u003cp\u003eAverage gait speed during the baseline walking assessment was 3.59 m/s (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.90). Six participants (26.1%) reported at least one chronic physical condition, and five participants (20.8%) were currently receiving medical treatment. The majority of participants (79.2%) reported regular medication intake. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows descriptive statistics of the subjective preferences towards social touch prior to the experiment and self-reports of mean affect and evaluation after the three conditions with physical contact.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAssessed prior to joint walks:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTQ Liking of general Social Touch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2\u0026ndash;3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTQ Liking of informal Social Touch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.67\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNARS Scale negative attitudes, discomfort or anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u0026ndash;3.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eMean evaluation over conditions:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive Affect (PANAS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative Affect (PANAS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u0026ndash;1.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical contact felt comfortable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.67\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI felt comfortable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical contact felt natural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvaluation of the walk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eFinal evaluation:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponse valence in final open comments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssociations between attitudes towards social touch and subjective reports after the interaction with the robot\u003c/h2\u003e \u003cp\u003eAnalyzes of associations between the participants\u0026rsquo; preferences toward touch as assessed by STQ scales and their mean self-report after the three conditions with physical contact resulted in significant or trend-level effects as summarized in the following. Self-reports after different conditions did not differ significantly and are reported at Leven et al).\u003c/p\u003e \u003cp\u003eSocial touch preference (STQ-LgST, centered) predicted mean physical comfort while controlling for age. The overall model was not statistically significant, \u003cem\u003eF\u003c/em\u003e(2, 21)\u0026thinsp;=\u0026thinsp;1.63, \u003cem\u003ep\u003c/em\u003e = .22, explaining 13% of the variance in physical well-being (\u003cem\u003eR\u0026sup2;\u003c/em\u003e = .13, adjusted \u003cem\u003eR\u0026sup2;\u003c/em\u003e = .05). STQ-LgST showed a positive effect toward predicting physical well-being (\u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.34, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.19, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.80, \u003cem\u003ep\u003c/em\u003e = .043) corresponding to a partial correlation of \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.35 (medium effect size; Cohen, 1988), explaining approximately 12% of the variance in physical well-being. See Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAssociations between attitudes towards social touch and negative attitudes towards robots before and after the interaction\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAnother linear regression was conducted to examine whether social touch preference predicted negative attitudes towards robots (NARS scale negative attitudes, discomfort or anxiety toward direct interaction with robots) before and after the interaction. The model included an interaction term between STQ-LgST and time (pre or post experiment). The overall model was not statistically significant but showed a trend, \u003cem\u003eF\u003c/em\u003e(4, 43)\u0026thinsp;=\u0026thinsp;1.70, \u003cem\u003ep\u003c/em\u003e = .09, explaining approximately 14% of the variance in NARS scores (\u003cem\u003eR\u0026sup2;\u003c/em\u003e = .14, adjusted \u003cem\u003eR\u0026sup2;\u003c/em\u003e = .06). The main effect of STQ-LgST was negative and statistically significant (\u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.46, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.21, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;2.26, \u003cem\u003ep\u003c/em\u003e = .015), indicating that higher STQ-LgST scores were associated with lower NARS scores at the first time point (T1). The main effect of time showed lower NARS scores after the experiment compared to before (\u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;1.27, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.74, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;1.71, \u003cem\u003ep\u003c/em\u003e = .047). The interaction between STQ-LgST and time reached significance (\u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.52, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.29, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.82, \u003cem\u003ep\u003c/em\u003e = .038, corresponding to a partial correlation of \u003cem\u003er\u003c/em\u003e\u0026thinsp;\u0026asymp;\u0026thinsp;0.36), suggesting that the negative relationship between STQ-LgST and NARS scores may be slightly attenuated after participating in the experiment (see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eQualitative evaluation of the overall study procedure\u003c/h2\u003e \u003cp\u003eParticipants mentioned all seven categories in their comments. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the frequency of the categories related by the total number of comments in %, following the theory-based framework.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency of category brought up by participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory 1\u003c/p\u003e \u003cp\u003eperceived usefulness,\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCategory 2\u003c/p\u003e \u003cp\u003etechnical perform-ance \u0026amp; design,\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCategory 3\u003c/p\u003e \u003cp\u003eembodied experience \u0026amp; physicality,\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCategory 4 rejection \u0026amp; negative affect,\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCategory 5\u003c/p\u003e \u003cp\u003evalues, ethics \u0026amp; societal context,\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCategory 6\u003c/p\u003e \u003cp\u003eacceptance \u0026amp; positive affect,\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCategory 7 contextual factors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e% of comments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNote.\u003c/em\u003e Comments without any content, e.g. \u0026ldquo;as told to the experimenter\u0026rdquo;, were neglected for this analysis.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThematic analysis revealed that participants recognized practical benefits of robotic assistance across daily living and care contexts, but at the same time drew clear ethical boundaries. Despite expressing positive affect and constructive technical feedback, participants consistently emphasized the ontological limitations of machines and the irreplaceability of human qualities like empathy and emotional connection. Many participants stated that robot use would depend on the specific context, the individual's needs, and the type of support required. For a systematic overview of the answers, see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThemes, sub-themes, and representative quotes from qualitative analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSub-theme\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRepresentative Quote\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived usefulness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSupport in daily living\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAssistance with mobility, walking, and everyday activities; becoming helpers in daily life\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"could be well used in the area of everyday assistance, e.g., walking\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthcare and care settings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUse in nursing/care contexts; support for patients; relief for caregiving staff\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"appropriate assistance for a patient would be very beneficial and at the same time a relief for the nursing staff\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecialized applications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedical diagnostics; learning and play\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"In medical diagnostics, AI is already very useful\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroups who could benefit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFor people who need help; older adults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"especially in work with the elderly, is promising\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnical performance \u0026amp; design\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMovement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpeed and gait quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"The robot should be able to walk properly, it is still too primitive\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical design features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAppearance suggestions (color, clothing); grip/hand design; padding/comfort features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"Robot could be a bit more colorful (perhaps even with 'clothing')\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCommunication style\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVoice quality and intonation; command style\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"voice too monotonous, better with different intonation\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmotional expression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConcerns about artificial emotional displays\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"Robots that express human emotions are extremely unpleasant\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmbodied experience \u0026amp; physicality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThermal quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWarmth of robot arms as positive feature; comfort of physical contact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"The physical contact went much better than I expected because its arms were warm\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContact preferences and comfort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePreferences for walking with or without physical contact; physical experience of grip; desire for padding and softer materials\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"Without physical contact, walking was most comfortable for me\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRejection \u0026amp; negative affect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInitial threat/discomfort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInitial negative reactions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"The robot's arms are 'threatening' at first sight\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDesign and maturity concerns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTechnology not yet mature enough; aversion to specific features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"it is still too primitive\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContact aversion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePreference for avoiding physical contact; feeling disturbed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"Without physical contact, walking was most comfortable for me\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValues, ethics \u0026amp; societal context\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOntological limitations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFundamental nature as machines without soul; inherent limitations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"Robots are human-programmed devices, machines, technical aids without their own 'will', soulless, emotionless, without life\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIrreplaceability of human qualities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCannot replace human soul, empathy, or tasks requiring human feeling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"It is questionable whether they can replace a human's soul when someone seeks empathy\";\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSocietal risks \u0026amp; power dynamics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDanger to humanity; concerns about dependency, domination, and loss of control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"I see a huge danger to humanity if robots determine many areas of our lives\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSafety, reliability and resource concerns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTechnical failure risks; environmental impact; need for regulations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"Like all technology, they can also be defective or malfunction\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCognitive autonomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConcern that robots should not replace independent thinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"should not replace independent thinking\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcceptance \u0026amp; positive affect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral positive evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnjoyment, interest, and positive experience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"was fun, is interesting\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFuture optimism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHope for development and implementation; following progress with interest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"I hope that robots will develop quickly\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWillingness to adapt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOpenness to befriending or getting used to robots; imagining future acceptance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"I can already imagine that they will provide good service one day\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAppreciation despite concerns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAcknowledging research value or expressing gratitude even while noting limitations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"However, I can still feel the joy of research\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSituational \u0026amp; contextual factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSetting specificity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHome environments; daily living contexts; care facilities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"can be well used as an aid in the daily home environment\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTarget population specificity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFor people needing help; older adults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"for people who need help, it will be very useful. I am glad that I can still manage without help\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTask and domain specificity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAppropriate for specific tasks (medical diagnostics, specific work areas) but not others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"robots should not perform tasks that should be done by humans through feeling\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConditional implementation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSituation-dependent appropriateness; need for proper regulations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\"depends on programming and uniform laws\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAssociations between attitudes towards social touch and response valence\u003c/h2\u003e \u003cp\u003eTo additionally examine whether individual differences in touch attitudes relate to these evaluations, we analyzed associations between STQ scores and response valence. The overall linear regression model on social touch preference (STQ LiST) predicting response valence of overall evaluation, was marginally significant, F(2, 17)\u0026thinsp;=\u0026thinsp;3.08, p = .072, and explained approximately 27% of the variance in response valence (R\u0026sup2; = .27, adjusted R\u0026sup2; = .18). STQ-LgST was a significant predictor (b = \u0026minus;\u0026thinsp;0.95, SE\u0026thinsp;=\u0026thinsp;0.41, t(17) = \u0026minus;\u0026thinsp;2.29, p = .017), indicating that higher social touch preference was associated with more positive evaluations of the robot interaction (see Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegression models for other self-report items (e.g. after the conditions: \u0026ldquo;The physical contact with the robot was comfortable\u0026rdquo;, \u0026ldquo;The contact was natural\u0026rdquo;, \u0026ldquo;Please evaluate the joint walk overall\u0026rdquo;) did not result in any significant or trend-level effects. In none of the quantitative analyses, age as covariate reached significance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSummary of findings\u003c/h2\u003e \u003cp\u003eThis mixed-methods study investigated whether individual differences in attitudes toward social touch influence older adults' responses to robotic touch assistance. General touch attitudes were associated with evaluations of robotic interaction. Participants with more positive attitudes toward social touch, particularly general social touch, reported higher comfort after physical contact with the robot and rated the walking experience more favourably. Similarly, participants with more positive attitudes to touch expressed more positive overall evaluations in their open-ended comments.\u003c/p\u003e \u003cp\u003eQualitative analysis provided deeper insight into how older adults evaluate robotic touch beyond these individual differences. Participants recognized practical benefits, but at the same time drew clear ethical boundaries. Despite expressing positive affect and constructive technical feedback, they consistently emphasized the inherent limitations of machines and the irreplaceability of human qualities like empathy. Participants made it also clear that their acceptance of this technology was highly dependent on specific contexts, individual needs, and task requirements. These findings have direct implications for the implementation of touch-capable robots in geriatric care settings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eIndividual Differences in Touch Attitudes and Robot Acceptance\u003c/h2\u003e \u003cp\u003eOur study showed that individuals with more positive touch attitudes reported higher comfort after walking with TIAGo Pro, evaluated the application as more positive and commented more positively on their general experience with the robot.\u003c/p\u003e \u003cp\u003eThese findings, interpreted with caution given the small effect sizes, support our hypothesis that touch attitudes modulate the acceptance of robotic devices. Thereby, touch attitudes add to the list of individual differences that influence technology acceptance, such as age, gender, education, personality type, resilience, experience and expectations (Gessl et al., 2019). Furthermore, literature on human care emphasizes that patients' individual characteristics and preferences regarding touch must be taken into account and respected by medical professionals (Davidhizar et al., 1997). The present findings suggest that such preferences are also important for the acceptance of robotic touch and should be further investigated in larger studies. Person-centered care is a cornerstone of geriatric medicine, and the present findings suggest this principle should extend to decisions about robotic touch.\u003c/p\u003e \u003cp\u003eBefore the robot interaction, participants with more positive attitudes toward general social touch held less/fewer negative attitudes toward robots (negative association between STQ-LgST and NARS). However, after hands-on experience, attitudes toward robots improved across all participants, and the association between touch attitudes and robot attitudes was attenuated. This suggests that direct positive experience with the robot reduced initial skepticism, particularly among those with less favorable touch attitudes. This finding highlights the importance of experiential learning in robot acceptance and suggests that concerns based on general attitudes may be mitigated through positive direct experience which is in line with similar research in different settings (Zhou et al, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUnderstanding the mechanisms underlying this association is important for implementation. Positive attitudes toward touch might be related to more positive robot experiences for two possible reasons: individuals with positive touch attitudes may be generally more open to physical interaction, also with non-humans. This suggests that touch preferences reflect a broader openness to tactile contact rather than being specific to human touch. Alternatively, individuals with more positive touch attitudes might experience greater comfort with the specific tactile qualities of the robot (such as warmth and firmness). Future research should disentangle whether touch attitudes predict robot acceptance due to generalized tactile openness or specific design features.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePractical benefits and ethical boundaries\u003c/h2\u003e \u003cp\u003eAn interesting finding was that the participants acknowledged the practical utility of robots such as TIAGo Pro in healthcare, but also drew clear ethical boundaries. Despite reporting positive experiences during direct interaction with TIAGo Pro, including comfort and favourable evaluations of the walking experience, participants consistently emphasized in their open-ended reflections that robots remain fundamentally limited as machines and cannot replace essential human qualities such as empathy and emotional connection. This pattern mirrors findings from focus groups with older adults and carers across three European countries, where participants adamantly maintained that robots should not replace human contact, viewing persuasion and emotional understanding as distinctly human skills (Sorell \u0026amp; Draper, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In geriatric healthcare specifically, where emotional connection and dignity are central to quality care, this distinction carries particular weight. This suggests that positive embodied experiences with robotic touch do not automatically translate into unreserved acceptance of care robots. Instead, they rather coexist with critical reflection about appropriate roles and limitations. A systematic review of empirical evidence on socially assistive devices highlighted this dual nature of interaction: users frequently attributed internal states to devices while simultaneously remaining aware of their mechanical nature (Haltaufderheide et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this study, TIAGo Pro was primarily tested in a physical interaction with the participants (joint walking), during which it did not interact verbally with participants. Future studies should also include verbal interaction to test whether concerns of non-emotionality in humanoid robots persist with this additional component of communication.\u003c/p\u003e \u003cp\u003e Participants' acceptance was clearly context-dependent rather than general. They distinguished between tasks where robotic assistance seemed appropriate (e.g., mobility support, daily living activities, medical diagnostics) and domains where human presence was deemed irreplaceable (e.g., tasks requiring emotional understanding or \"feeling\"). (Sorell \u0026amp; Draper, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) similarly found that users assigned different roles to robots (servant, healthcare provider, companion) and used corresponding role norms to justify their ethical positions on robot behaviour. This nuanced perspective aligns with recent conceptualizations of touch in healthcare as having complex communicative, social, and affective dimensions that cannot be reduced to simple instrumental functions (Buono et al., 2025). Our findings suggest that older adults as end-users maintain a sophisticated understanding of both the potential and the limits of robotic care technology.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eImplications for Implementation\u003c/h2\u003e \u003cp\u003eThe present findings have several practical implications for implementing touch-capable robots in care settings. First, person-centered approaches remain important. The role of touch attitudes appears to be time-dependent and outcome-specific. While general robot attitudes improved across all participants after hands-on experience, suggesting that direct exposure can overcome initial skepticism, touch attitudes continued to predict comfort during the interaction itself. This suggests that while acceptance may be achievable through positive experience regardless of touch preferences, the quality of the subjective experience may still vary based on individual differences. Thus, person-centered approaches are important not merely to ensure acceptance, but to optimize the individual experience and maximize well-being during robot-assisted care. Skeptical individuals may accept robotic assistance after exposure but experience it as less comfortable or pleasant depending on their a priori preferences, which could affect long-term adherence and satisfaction.\u003c/p\u003e \u003cp\u003eSecond, our findings underscore the importance of context-appropriate implementation. Participants' distinctions between appropriate and inappropriate robot applications align with emerging evidence that social robot effectiveness varies substantially by setting, format, and duration of intervention (Yen, H.-Y., et al., 2024). Meta-analytic evidence shows that group-based activities produce stronger effects than individual sessions, and longer interventions yield greater improvements (Yen, H.-Y., et al., 2024). Similarly, cognitive benefits appear more pronounced in cognitively intact individuals (Hermann, J., et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Our qualitative findings extend this by showing that older adults themselves recognize such contextual dependencies and distinguish between tasks where robotic assistance seems beneficial versus domains requiring human presence.\u003c/p\u003e \u003cp\u003eThird, the coexistence of positive direct experiences with critical ethical reflection suggests that acceptance of care robots is not a binary construct but involves a balance between practical benefits and value-based concerns. This has implications for how such technologies should be introduced: transparency about capabilities and limitations, respect for individual preferences, and acknowledgment of the irreplaceability of human care may be as important as technical performance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and Future Directions\u003c/h2\u003e \u003cp\u003eSeveral limitations should be considered when interpreting these findings. Our sample was relatively small (N\u0026thinsp;=\u0026thinsp;24) and predominantly female, which may limit generalizability and means that effects of small magnitude may have gone undetected due to limited statistical power. The results should be replicated and expanded in additional samples. The participants were living independently or with a partner or family and able to walk independently, representing a relatively healthy subset of older adults. Responses among frailer individuals, those with cognitive impairments, or those in long-term care facilities, the very populations most likely to encounter care robots, may differ substantially. During recruitment, the interaction with a humanoid robot was explicitly announced. Consequently, the sample may be subject to selection bias, as participation was based on voluntary response to the study invitation.\u003c/p\u003e \u003cp\u003eFurthermore, the study involved brief, controlled exposure to robotic touch in an experimental setting. Longer-term familiarity with robots might alter both immediate reactions and broader attitudes. Meta-analytic evidence suggests that intervention duration matters for effectiveness (Yen, H.-Y., et al., 2024), and longitudinal studies are needed to examine whether initial touch attitudes predict sustained acceptance over time or whether attitudes change with repeated exposure. Previous work suggests that individual difference factors like social role expectations strongly influence initial interactions but become less important with experience as users adapt to the robot's actual capabilities (Koay et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Touch attitudes may follow a similar trajectory, exerting their strongest influence during first encounters.\u003c/p\u003e \u003cp\u003eAdditionally, while we assessed general touch attitudes as individual difference variables, we did not measure situational preferences for wanting touch in particular moments (Sailer et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Future research should examine whether state-dependent touch preferences similarly moderate responses to robotic touch, and whether robots might be programmed to respond adaptively to such momentary preferences.\u003c/p\u003e \u003cp\u003eOur study focused on users' perceptions and evaluations of robotic touch but did not systematically examine behavioural adaptation processes during interaction. Systematic reviews of socially assistive devices describe a \"behavioural alignment\" phenomenon, where users alter their behavior and habits to accommodate device limitations, for example, changing voice patterns to improve speech recognition or restricting themselves to simpler functions (Haltaufderheide et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). From an autonomy perspective, such adaptations represent a potential cost, where improvements in independence through robotic assistance may be offset by users conforming to technical constraints. Future research on touch-capable robots should investigate whether similar adaptation processes occur in physical interactions, for instance, whether users modify their movement patterns, touch preferences, or positioning to accommodate robotic limitations, and how such adaptations affect the autonomy-enhancing promise of assistive robotics.\u003c/p\u003e \u003cp\u003eFinally, while our study focused on touch attitudes, other individual differences may also moderate acceptance of robotic care. Factors such as prior technology experience (Hermann, J., et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Papadopoulos, I., et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), loneliness levels (given evidence that robots can reduce loneliness; (Robinson, H., et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and general attitudes toward care robots should be examined alongside touch preferences in future work.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides evidence that older adults' attitudes toward interpersonal touch shape their experiences with robotic assistance that involves touch. Those with more positive touch attitudes experienced greater comfort during physical contact with the robot and provided more positive evaluations.\u003c/p\u003e \u003cp\u003eThese quantitative patterns coexisted with nuanced qualitative reflections. While participants acknowledged practical utility and reported positive embodied experiences, they simultaneously articulated ethical concerns and underscored the irreplaceable nature of human connection in caregiving. This suggests that robot acceptance not only encompasses immediate tactile comfort but also deeper considerations about appropriate roles for technology in care contexts.\u003c/p\u003e \u003cp\u003eAs touch-capable robots advance, implementation strategies must account for this complexity. In geriatric healthcare, where person-centered care is a foundational principle, respecting individual variation in touch preferences, optimizing tactile design features, and maintaining transparency about what robotic systems can and cannot provide will be essential for ethical and effective integration.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eAuthor Contributions CREDIT\u003c/h2\u003e \u003cp\u003eFunding Acquisition: CJM, KM, ME\u003c/p\u003e \u003cp\u003eConceptualization: CJM, KM, ME, CW, MA\u003c/p\u003e \u003cp\u003eData Curation: LL, MS, TB\u003c/p\u003e \u003cp\u003eFormal Analysis: ME, US, MS\u003c/p\u003e \u003cp\u003eWriting Original Draft: ME, US\u003c/p\u003e \u003cp\u003eVisualization: ME, US\u003c/p\u003e \u003cp\u003eProject Administration: MS, CW\u003c/p\u003e \u003cp\u003eSupervision: KM, ME, US\u003c/p\u003e \u003cp\u003eResources: KM, ME\u003c/p\u003e \u003cp\u003eWriting Review \u0026amp; Editing: all authors\u003c/p\u003e \u003c/p\u003e\u003ch2\u003e \u003cb\u003eEthic Declaration\u003c/b\u003e \u003c/h2\u003e \u003cp\u003eEthical approval was granted by the Ethics Committee of the Medical Faculty at Heidelberg University (S-290/2024). All participants provided informed consent in accordance with the Declaration of Helsinki.\u003c/p\u003e\u003cp\u003e \u003ch2\u003eClinical trial number:\u003c/h2\u003e \u003cp\u003enot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConflict of Interest\u003c/h2\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding Statement\u003c/h2\u003e \u003cp\u003eFunded by the Heidelberg Karlsruhe Research Partnership (HEiKA, Project PerRot-G) to ME and KM and the Dres. Majic/Majic-Schlez-Foundation at Medical Faculty Heidelberg to CJM. HEiKA funding is provided by Heidelberg University and the Karlsruhe Institute of Technology (KIT) as part of their Excellence University funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eFunding Acquisition: CJM, KM, MEConceptualization: CJM, KM, ME, CW, MAData Curation: LL, MS, TBFormal Analysis: ME, US, MSWriting Original Draft: ME, USVisualization: ME, USProject Administration: MS, CWSupervision: KM, ME, USResources: KM, MEWriting Review \u0026amp; Editing: all authors\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe thank all participants for taking part in our study. We thank Dominik Misok (DM) for response valence ratings and preparation of data and Beate Ditzen and Charlotte Raithel for overall support of the project.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eFully anonymized data is available upon request by the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdi J, Al-Hindawi A, Ng T, Vizcaychipi MP. (2018). \u003cem\u003eScoping review on the use of socially assistive robot technology in elderly care\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmjopen-2017-018815\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2017-018815\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndersen PA, Leibowitz K. The development and nature of the construct touch avoidance. 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Int J Social Robot. 2021;13(7):1657\u0026ndash;77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12369-021-00749-x\u003c/span\u003e\u003cspan address=\"10.1007/s12369-021-00749-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"social touch, geriatric healthcare, human-robot interaction, nursery, affect","lastPublishedDoi":"10.21203/rs.3.rs-9277646/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9277646/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eInterpersonal touch is a fundamental aspect of human social interaction and plays a crucial role in health and wellbeing. In geriatric healthcare, touch-capable social robots are increasingly discussed as a means of supporting older adults. Yet little is known about what shapes individual acceptance of robotic touch.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study investigated the influence of individual differences in social touch attitudes on older adults' experiences with robot-assisted walking guidance including touching the robot. Twenty-four older adults participated in a within-subject design, completing four experimental conditions with varying physical contact types (no contact, hand-holding, arm-linking, and full forearm contact) using the TIAGo Pro robot.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eParticipants with more positive attitudes toward social touch reported higher comfort and more favorable evaluations of the robotic interaction. Negative attitudes towards robots in general changed after the experiments in interaction with the prior preferences for social touch. Qualitative analysis revealed that while participants recognized the practical benefits of robots, they also emphasized ethical boundaries, stressing that robots cannot replace essential human qualities like empathy.\u003c/p\u003e\u003ch2\u003eDiscussion\u003c/h2\u003e \u003cp\u003eThe study highlights the importance of individual preferences in robot acceptance and underscores the need for context-specific implementation strategies, where person-centered approaches and transparency about robotic capabilities are crucial for future integration into geriatric healthcare.\u003c/p\u003e","manuscriptTitle":"Individual differences in touch attitudes shape acceptance of robotic touch in older adults: Evidence from a medical center setting","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-26 17:11:50","doi":"10.21203/rs.3.rs-9277646/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"37692922567048943035240382298562423824","date":"2026-04-20T07:50:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"212147133060653875198042420630470261746","date":"2026-04-19T13:40:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-17T11:27:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-17T11:25:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-14T11:21:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-14T11:16:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2026-04-14T10:27:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6885c96c-a2e5-4155-8a99-253c97280fce","owner":[],"postedDate":"April 26th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-26T17:11:51+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-26 17:11:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9277646","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9277646","identity":"rs-9277646","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}