Significant challenges when introducing care robots in Swedish elder care

Figures & data

Table 1. Demographics.

Characteristics
Gender (N = 21)	14 Female and 7 Male
Age, Md (range)	49 (37–79)
Highest level of education
University, PhD	4
University	16
Secondary school	1
Occupations of the informants	Senior advisor/project leader (2), investigator (6), portfolio manager (1), communication manger (1), journalist (1), director (3), business developer (1), digitalisation strategist (1), principal (2), expert (1), and senior representative in retirement organisations (2)

Table 2. Example of the analysis process.

Data extracts	Codes	Theme	Grand challenge
“It is more positive if we don’t call them robots […] Assistive technology, yes, that is better […]” (IOO) “[…] I don’t like the word robots at all, it has a negative connotation” (RI)	The word “robot”	Attitudes	Individual and group challenges
“There is a fear that we will dismiss staff in favour of technical solutions. And it is certainly correct in its own way, whereas I think we, as management, have a broader perspective of what it will look like, and we will not get rid of a single person who wants to work in care, because we will need everyone one of them” (PSO) “[…] ignorance of how it works for e.g., in elder care, that people constantly think it is all about saving money and resources […]” (RI)	The incentives for introducing technology
“Everyone wants changes, but no one wants to change. People are afraid to let go of the old way […] Then you also need to focus on the obstacle “wrong”; the fear […] we are afraid of making mistakes and we believe that everything should work to 100%” (PDM) “The older you get, the more I feel that you have a built-in resistance to technological innovations” (IOO)	Fear of change and making mistakes
“If you talk to the municipalities, how much they want to invest in budget on technical solutions, then they say that they do not want to invest anything because they want to put the money on education of more nurses and more hands” (PSO) -“We see many quite experienced staff in the nursing programmes, they have been working for 20–30 years and they enter the education with a clear idea of how care is provided and should be provided” (EO)	Fixed beliefs about how care should be conducted

Table 3. Grand challenges: themes and codes displaying the challenges of introducing and embedding care robots in elder care, and the represented informant groups for the respective themes.

Grand challenges/Themes	Codes	Represented informants
Individual and group challenges
Belief in technology use	Expectations of robotics Expectations of economic benefits Trust in technology	FO, PSO, RC, RI
Attitudes	The word “robot” The incentives for introducing technology Fear of change and making mistakes Fixed beliefs about how care should be conducted	EO, FO, IOO, IOC, MO, PDM, PSO, RC, RI
Ethics	Let people speak/decide for themselves Technology is not for everyone Humans can’t be replaced by technology Nothing will benefit everyone Changing power relations between clients and care professionals	EO, FO, MO, IC, IOO, IOC, PDM, PSO, RC, RI
Knowledge and skills	Technical knowledge and developing the skills of care professionals New working methods based on digitalisation Technology in all healthcare education Skills of teachers in healthcare education Orientation to clients and their relatives	EO, FO, IOO, IOC, MO, PDM, PSO, RC, RI
Collaboration	Networking Accumulation of experiences and evaluations Dissemination of knowledge Decision-makers, non-profit organisations, research, and companies	FO, IOO, IOC, MO, PDM, PSO
Systemic and societal challenges
Infrastructure	Digital infrastructure Standards for communication between technical systems/devices Adapted home environments Adapted educational environments Logistics for services/goods supply	EO, IOO, IOC, MO, PDM, PSO
National governance	National coordination and strategy Autonomous municipalities Subjective- and interest-oriented prioritisation and development Focus is on healthcare; not municipal elder care Accountability: public, social service or healthcare?	FO, IOC, PDM, PSO, RC
Laws and regulations	Not up to date Conflicting laws A grey zone Time-consuming legal issues Legal liability when care robots replace human tasks	MO, IOC, PDM, PSO, RC, RI
Economy	Who is paying for expensive technology? The budget for procurement is not adapted for innovative technology No investment budget or strategy for technology in municipal care Internal organisations’ financial models Quick profits may attract the wrong actors Investment in educational environments	EO, FO, IC, MO, IOO, PDM, PSO, RC, RI
Procurement	Procurement routines – who and how? Competence to manage the procurement of technology Time-consuming procurement processes Maintenance, upgrades, and support	MO, IOO, IOC, PDM, PSO, RC, RI
Preconditional challenges
The utility of technology	Products that match users’ needs User involvement Fully-developed products (not prototypes) Requires a change of working routines/processes	EO, FO, IOO, IOC, MO, PDM, PSO, RC, RI
Implementation	When the project ends, it all ends Single products Unattainable market Access to capital and investors Complex implementation processes in the public sector It takes time to offer services in a new way The courage to try implementation	FO, MO, PDM, PSO, RC, RI
Evaluation	Models for evaluating the technology and its economic effects Follow-ups needed on how money is spent Profits needed within a foreseeable timescale; not far in the future Holistic approach: evaluate the cost-benefit ratio and users’ experiences New technology before the previous technology has been evaluated	FO, IOC, PSO
Safety, security, and integrity	Secure and safe technology Back-up plans in case technology fails Data security issues for clients and care professionals	EO, FO, MO, IOO, IOC, PDM, PSO, RI

Technology refers to welfare technology and care robots.

EO: educational organisations; FO: funding organisations; IC: insurance companies; IOC: interest organisations for care professionals; IOO: interest organisations for older persons; MO: media organisations; PDM: political decision makers; PSO: public sector organisations; RC: robot companies, and RIs: research institutes.