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New colleague or gimmick hurdle? A user-centric scoping review of the barriers and facilitators of robots in hospitals [1]
['Mathias Kofoed Rasmussen', 'Department Of Business', 'Management', 'University Of Southern Denmark', 'Anna Schneider-Kamp', 'Tobias Hyrup', 'Department Of Mathematics', 'Computer Science', 'Alessandro Godono', 'Department Of Public Health']
Date: 2024-12
Half of the included studies followed a qualitative methodological approach through either interviews, observations, or surveys (20/40). A few studies each applied a quantitative (4/40) and a mixed-methods (4/40) approach. The remaining studies were predominantly different types of reviews (9/40), position and survey papers (2/40), and a pilot study (1/40).
As indicated in Table 1, the countries of the studies were predominantly high-income countries, except for three upper-middle-income countries. All these countries exhibit high societal and technological readiness levels regarding integrating robots in hospital environments. The distribution of studies by country context is visualised in Fig 2, where the ‘Four Asian Tigers’ [41] include Singapore, South Korea, and Taiwan while the ‘Five Eyes’ [42] include Australia, the United Kingdom, and the United States. The remaining countries are either high-income countries from the ‘European Economic Area’ or the upper-middle-income countries China, Colombia, and Turkey grouped as ‘Other’.
Furthermore, in Table 1, we also indicate which type of professional end-users the included studies focused on. To visualise the results, in Fig 3 we group the professional roles into five categories, where ‘nursing’ covers nursing students, nurses, and nursing staff while ‘other’ covers cleaning, kitchen, service, and technical staff and ‘physicians’ also includes physical therapists. Most of the included studies focus on nurses (alone or in combination with physicians).
Table 2 illustrates the Grade-CERQual summary of qualitative findings (SoQF) table, presenting the barriers and facilitators of applying and integrating robots within a hospital environment, developed from the thematic synthesis of the included studies. The table offers an evaluation of the degree of confidence towards the identified evidence relating to the barriers, facilitators, and the findings associated with them.
The first column summarises the evidence of the studies indicated in the second column. The third and fourth columns provide the GRADE-CERQual assessment of the confidence in this evidence.
A total of 14 analytical themes emerged from the analysis and qualitative synthesis of the 40 included studies. Of these 14 themes, seven were identified as barriers and seven as facilitators. Table 3 visualises the distribution of barriers and facilitators among the 40 included studies. The following two subsections present first the barriers and then the facilitators. The third and fourth subsections structure the barriers and facilitators and analyse the anthropomorphisation of robots in hospital environments.
The hospital employee’s concerns about dependency, lack of involvement, and associated perceptions of unreliability were addressed by four out of the 40 included studies [ 44 , 45 , 52 , 66 ]. One study argued that the users among the pharmaceutical staff were frustrated with their lack of influence regarding the integration of robots and felt they were losing autonomy as routines were constantly rearranged to accommodate the robots’ limitations [ 52 ]. Furthermore, another study addressed that robots would be granted authority by subordinates and managers in the sense that they were given the ability to override hospital employees such as nurses in certain work processes [ 66 ].
Out of the 40 studies, seven addressed robots as an obstacle when implemented into routine- and workflow-related practices [ 1 , 12 , 47 , 52 , 59 , 66 , 68 ]. Several studies argued that the implementation of robots into workflows decreased the quality of care and disrupted the employees’ daily routines, which led to hospital employees feeling dissatisfied [ 12 , 59 , 66 , 68 ]. One study illustrated how nurses and physicians perceived the robots’ utility to be limited within their workflows, as their usefulness was only applicable in selective niche work processes and environments [ 1 ].
A few studies indicated that the introduction of robots led to modifications in the workplace dynamics perceived as dissatisfactory, as hospital employees filling various professional roles involuntarily were assigned to new roles and tasks [ 52 , 59 , 62 ]. This modification led to a hierarchy perceived as unpleasant as particularly nurses and service staff experienced being surveilled and expected to take on new less-favoured tasks [ 52 , 59 , 62 ]. One study highlighted how this hierarchy influenced some pharmaceutical staff members’ morale and perceived contribution: “Assistants became acutely aware that their primary work of stocking medicines was less valued than the work of the others. As they saw it, even the robot had downgraded their work” [ 52 ].
Robots’ impact on workplace dynamics has been addressed by six out of 40 studies, which found that robots complicated the distribution of responsibilities and roles when integrated into the hospital employees’ working environment [ 43 , 52 , 54 , 59 , 62 , 67 ]. Two studies illustrated several conflicting perspectives on the distribution of responsibility in instances of mistakes by robots. The perspectives varied from proposing that hospital employees such as nurses and physicians take responsibility, whereas other perspectives instead suggested that the robotic companies should be responsible and take accountability for errors [ 43 , 54 ].
Limitations to certain design features were further highlighted by several studies, such as ineffective interaction through touchscreens, lack of interactivity, elevated noise levels, excessive heat generation, too small or too bulky size, too short and direct phrases, ineffective interaction through touchscreens and verbal interfaces, and protruding attachments [ 12 , 45 , 47 , 49 , 64 , 65 ]. Moreover, a few studies argued that high volumes of noise and voice emerging from robots impacted privacy levels. Instances of the latter were particularly significant, as robots with verbal communicative features could lead to problems of confidentiality and privacy violations in the perception of healthcare professionals [ 44 , 49 , 64 ].
The adaptation to hospitals’ complex facilities and infrastructure was another challenge that hindered the integration and utilisation of robots [ 1 , 12 , 50 , 66 ]. One study found that the less-than-optimal integration into the hospital infrastructure led to annoyance and disruptions of the workflow, with one nurse relating her frustrations: “It overrides the elevator because the robot was using it, and I was let out into the basement of the hospital with a patient from recovery and had to get out of there. So, we stood there, and had to wait until the robot had finished” [ 66 ].
Out of the 40 studies, 10 addressed implications associated with the robots’ inadequate functionalities and design features [ 1 , 12 , 44 , 45 , 47 , 49 , 50 , 64 – 66 ]. Several studies highlighted how malfunctions and outages led to frustrations among hospital employees, as the robots interfered with task execution and even aggravated issues [ 12 , 45 , 50 ].
A multitude of studies highlighted that the implementation of robots led to an increase in workload and the frequency of errors [ 47 , 49 , 52 , 62 , 63 ]. Similarly, a perception of the robots being unreliable influenced how and to what degree hospital employees used them, as they were uncomfortable assigning tasks to the robots due to prior experiences of inconsistencies [ 59 , 62 ]. One particular study highlighted that the robots’ unreliability led to the employees performing the tasks themselves and subsequently refusing any further use of them: “Errors occur, and the robots do not as they are told, so we can’t rely on them to accomplish their missions. If I want something done, I will do it myself” [ 59 ].
A perception that the robots failed to have the expected impact was addressed in 10 out of the 40 studies, which raised concerns and dissatisfaction among hospital employees [ 1 , 12 , 45 , 47 , 49 , 52 , 59 , 61 – 63 ]. Several studies pointed out that the hospital employees as users did not recognise any noticeable improvements, as they perceived the utility of the robots to be limited [ 1 , 45 , 61 ].
A multitude of studies further argued for the necessity of providing extensive support to nurses, physicians, physical therapists, and service staff such that they gain an understanding of the robots they are supposed to work with [ 12 , 53 , 60 ]. Lack of scheduled time to gain experience and practice with robots was the most frequently mentioned concern, which subsequently was found to lead to both integration failure and a decrease in quality of care [ 12 , 53 ]. The studies further addressed the influence of both hesitant management and subordinates, which had a negative impact towards integrating the robots. Additionally, older hospital employees required more support as they perceived robots as more challenging to interact with compared to their younger colleagues [ 12 , 60 ].
Lack of awareness was identified as another concern, as some hospital employees from all groups barely acknowledged robots’ existence and subsequent utility, due to the lack of initiative and proper introduction [ 52 , 56 , 57 , 59 ]. One study highlighted that the lack of awareness led to unfamiliarity and inattentiveness, whereas some hospital employees only gained awareness by observing colleagues’ interactions with robots: “I didn’t pay much attention to the system. I didn’t have time to explore (…) I started using it only after seeing another nurse use it (…) it was then I realised how convenient and useful it is" [ 56 ].
Concerns regarding the sufficiency of hospital employees’ knowledge, awareness, and support were addressed by 14 out of the 40 studies [ 1 , 12 , 43 – 45 , 52 – 60 ]. The concern regarding insufficient knowledge was primarily illustrated through limited learning opportunities as well as a poor understanding of the robots’ functions, features, and utility [ 12 , 43 , 44 , 52 , 54 , 57 , 58 ]. A number of studies indicated that the lack of knowledge contributed to nurses, physical therapists, and pharmaceutical staff feeling nervous, underprepared, and doubtful of the robots’ utility [ 12 , 44 , 52 ].
Although fear of being replaced was the predominant argument, two studies further mentioned a decrease in the hospital nurses’ competences as a concern: “If robots help us to do the clinical tasks, we’ll reduce nurses’ clinical skills (…)” [ 49 ] and “(…) robots would take over nurses’ jobs and that using robots would reduce nurse skills” [ 43 ]. Furthermore, three studies addressed the practical implications associated with these attitudes, i.e., when nurses, physical therapists, and administrative staff reject any usage of robots [ 12 , 45 , 51 ].
Out of the 40 included studies, 11 addressed that the utilisation and acceptance of the robots were limited by the hospital employees’ animosity and scepticism towards robots [ 11 , 12 , 43 – 51 ]. This scepticism was prevalent in all groups of hospital employees, including nurses, physicians, physical therapists, and pharmaceutical and administrative staff. A major component that contributed to those attitudes was the fear of being replaced, as hospital employees across these groups were worried about their physical labour being delegated to and taken over by robots and consequently losing their jobs [ 12 , 43 , 45 , 46 , 49 ]. Similarly, one study highlighted that healthcare workers were impacted by an underlying fear, even when they recognised the robots’ utility and usefulness [ 46 ].
We identified seven of the analytical themes as barriers: (B1) user perceptions; (B2) insufficient knowledge, awareness, and support; (B3) inadequate impact on healthcare practices; (B4) limitations to functionalities and design; (B5) workplace dynamics; (B6) workflow implementation; and (B7) loss of control and authority.
3.2. Facilitators
Seven analytical themes emerged as facilitators: (F1) training and engagement; (F2) transparency; (F3) behavioural and cultural factors; (F4) intuitiveness; (F5) assistance and usefulness; (F6) familiarity; and (F7) enhancing healthcare practices.
F1: Training and engagement. Out of 40 included studies, 12 addressed the positive impact of extensive training and engagement on the robots’ perceived utility and overall satisfaction levels among hospital employees [11,12,43,44,46,50,54,55,60,65,68,69]. Multiple studies highlighted how hospital employees benefited from introductory and educational programs. The employees developed a greater understanding of the robots’ features and complexity, often by selecting certain employees as ‘key users’ or specialist supervisors, to ease the process for the remaining employees [12,44,46,50,54,60]. Several studies argued that hospitals must provide an adequate amount of support and resources throughout the training and educational procedures, complemented by freeing employees to develop and participate in public campaigns, consultations, implementation strategies, and active user involvement activities aimed at influencing the perception, intention, and usefulness of the robots [11,12,44,46,50,68,69].
F2: Transparency. A total of 10 out of 40 studies highlighted the importance of transparency regarding the robots’ utility, roles and responsibilities, and expectation management [11,12,43,44,48,50,52,54,66,68]. Several of the studies illustrated that the hospital employees appreciated clarity regarding the robots’ limitations and responsibilities, as well as a realistic insight into their potential impact on work processes and roles [11,12,43,44,48,50,54,68]. Three studies emphasised the importance of presenting robots as tools to assist hospital employees in avoiding doubt and uncertainty regarding replaceability, which contributed to increased acceptance among healthcare workers and cleaning staff [12,54,66].
F3: Behavioural and cultural factors. Hospital employees’ attitudes, perceptions, and values were addressed by 10 out of the 40 studies and were shown to have an enabling influence on the application and integration of robots within a hospital environment [11,12,44,45,49–51,63,66,68]. These behavioural and cultural factors were illustrated through the elements of motivation, enthusiasm, and a generally positive attitude towards technology, which facilitated the hospital employees to accept and engage with robots [12,44,49–51,68]. The impact of a positive attitude towards technology was especially highlighted in one study, where the nurses’ reflections indicated that robots were likely to be essential within future healthcare practices: “(…) constant learning and lifelong learning in improvements of technology is essential to respond to the alterations in pediatric nursing practice (…) nurses have to maintain current knowledge of highly skilled responses to meet the demands of complex health problems” [49]. Two studies illustrated that nurses and surgeons experienced an alignment between their personal values and norms with the acceptance and positive perceptions towards robots [51,68]. Other facilitating elements were the impact of the hospital employees’ fascination and curiosity regarding the robots’ designs and features, which contributed to a positive atmosphere and attitudes towards the robot [45,50,66].
F4: Intuitiveness. Out of the 40 studies, eight argued that robots’ intuitiveness and subsequent ease of use had a positive impact, as the robots would be easier to operate which had a facilitating influence on the integration process [44,45,53,56,57,60,61,63]. Several studies highlighted how user-friendliness and simplicity positively impacted the integration process, as the hospital employees could operate and implement the robots with less effort [45,56,61]. A few studies addressed intuitiveness in relation to certain elements of the robots’ designs and features such as touch screens, menu design, overall interface, and the ability to operate the robot through both verbal and non-verbal communication [45,53].
F5: Assistance and usefulness. Out of the 40 included studies, 19 highlighted how robots’ usefulness and ability to assist hospital employees in healthcare practices had a positive impact on attitude levels and perceived utility [1,11,12,43,45,46,48,49,56,57,61,62,64,67,69–73]. Multiple studies addressed the hospital employees’ appreciation for the robots’ utility, as it facilitated a reduction in their workload, enabling the employees to spend more time providing care [1,48,49,64,70–72]. One study, in particular, highlighted the robots’ usefulness in healthcare practices involving children, which nurses greatly appreciated due to the difficulties they often experienced with such patients: “The participants felt that care robots could enhance these patients’ cooperation by being friendly and engaging with them (…) All too often, it’s hard to get children to play along. So, I think [robots] could persuade children to cooperate while we do our jobs” [72]. Furthermore, several studies addressed the significance of robots being useful in healthcare practices as being the single most important component. Accordingly, the employees would be able to cope with the robots’ inconveniences in practice, if they instead experienced a utilitarian impact [11,46,62,67].
F6: Familiarity. Out of the 40 studies, 13 addressed the importance of familiarity built on experience and usage in practice as having a facilitating impact on the hospital employees’ perception of the robots’ utility [1,11,12,43,45,56,60,62,68,70,74–76]. Several studies addressed attitudes of both scepticism and neglect among hospital employees toward their relationships with robots. However, once the employees had become familiar with the robots, through engagement in practice and experiencing their utility, they acknowledged an increase in acceptance and satisfaction levels [1,11,56,60,62,68,74,75,77]. Similarly, two studies highlighted that knowledge, reliability, and satisfaction levels increased over a longer period, which indicates that both hospitals and employees such as nurses and service staff must be patient for robots to reach their full utilitarian potential [60,62]. Becoming familiar with the robots further ameliorated the fear of being replaced among some healthcare workers and administrative staff as they experienced the robots’ opportunities and limitations in real time, which contributed to a less unpleasant experience when using and cooperating with the robots [43,45]. One study also acknowledged the significance of integrating robots as early as possible into workflows and standardising subsequent workflow processes to avoid uncertainty among end-users such as nurses and physical therapists, as well as risks towards safety measures [12].
F7: Enhancing healthcare practices. Out of the 40 studies, 14 addressed how the implementation of robots had a positive impact on hospital employees, as they appreciated the robots’ capabilities and broader impact on hospitals [1,9,43,45,48,49,52,56,59,64,69,70,74,76]. Several studies highlighted that hospital employees were satisfied with the robots’ efficacy and efficiency, as they perceived them to provide a significant improvement in the quality of care [1,9,45,48,49,56,64,69,74,76,77]. Several studies acknowledged that robots could execute healthcare practices in an improved manner simply not possible for hospital employees due to restrictions in time and capabilities [9,45,49,56,59,64]. Multiple studies also indicated that the implementation of robots influenced unforeseen areas of the execution of healthcare practices, with a positive impact on overall satisfaction levels among hospital employees. These studies addressed the following four areas: bringing neutrality to challenge hierarchical culture and power dynamics, improving hospital employees’ well-being and reducing turnover intention, increasing legitimacy and professionalisation within the healthcare domain, and resolving long-term workforce problems by reducing workload for low-skilled jobs [1,9,52,74].
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