Digital technologies to promote social engagement of nursing home residents: A systematic review of existing literature

doi:10.21203/rs.3.rs-3786542/v1

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Digital technologies to promote social engagement of nursing home residents: A systematic review of existing literature

https://doi.org/10.21203/rs.3.rs-3786542/v1

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Background

Digital technologies are seen as helping to support and improve social interaction and participation of people in need of long-term care. This review aims to synthesize types of digital technologies used in nursing homes worldwide and their effects as reported by residents and staff members. In addition, inhibiting and facilitating factors in the use of these technologies are identified and potential for development is described.

Methods

A systematic literature review was conducted in April 2022 in the databases PubMed, CINAHL, IEEEXplore and ACM Digital Library from inception onwards for publications written in German or English language. Quantitative and qualitative studies were considered. The studies were selected by two independent reviewers according to predefined criteria. For critical appraisal, the RoB 2 tool was used for RCTs and a level of evidence rating for other studies.

Results

Of 6212 articles found, 24 studies were included. Different digital technologies were identified. The digital technologies most frequently examined in the included studies were mixed technologies, Information and communication technologies, Robotic pets and Virtual Reality. Two out of three included randomized controlled trails showed positive effects on the social participation of the residents, even if for one of them serious concerns on the risk of bias became visible. Thus, only for one technology, i.e. Paro, positive effects could be shown in an evaluation study with high level of evidence. Lack of infrastructure, high costs, ethical concerns, lack of training and user-unfriendly design were cited as inhibiting factors in the included studies.

Conclusion:

None of the included studies operationalized ‘social participation’ as a direct construct to measure effects. Instead, constructs of ‘loneliness’ or ‘social isolation’ are often used in the existing studies. Though respective technologies are attributed a high potential, there is no high-level evidence that digital technologies can promote social participation of nursing home residents (yet). Further research with high level of evidence is needed to access the constantly growing body of digital technologies and their impact on social participation. In the future, implementation and use of technologies, guidelines and policies for ethical use should be considered.

Social participation

Loneliness

Digital

Technology

Nursing home

Long-term care

systematic review

Moving into long-term-care (LTC) facilities is a significant disruption to the social life of an older person in need of care, limiting mobility and altering relationships with family, friends, and social networks. As a result, older adults living in nursing homes (NH) run the risk of social isolation and loneliness [1]. Residents of NH also typically have complex health limitations e.g., sensory, cognitive, or mobility impairments that can further affect their social participation [2–4].

Social isolation, as a result of reduced social participation and interaction, is defined as a lack of social relationships, sense of being part of something like a community or a group, and participation [5]. Loneliness, on the other hand, which can arise from social isolation, refers to a lack of meaningful interpersonal relationships that is felt subjectively and has negative emotional dimensions [5]. Missing social participation can exacerbate significant health problems in older people and those in need of care [6–10]. This affects not only mental health but also physical morbidity or even mortality [9, 11]. In turn, social participation and interaction enhances the quality of life of older adults [10], improves mental health [12], and reduces the likelihood of cognitive decline [13]. This is where digital technologies can address the challenges of social participation among residents and facilitating social interaction through virtual and location-independent activities, such as cooperative games, or electronic communications [14, 15]. Recent work has shown that the use of digital technologies in NH is increasingly being discussed as a way to enable residents to better interact socially both with each other and with distant relatives, this was particularly noticeable during the Covid-19 pandemic to counteract the negative effects previously mentioned [16]. Previously published reviews on this topic often focused on only one category of technology or only on residents with dementia [17, 18]. A comprehensive review of all known digital technology categories used in NH referring to social participation can provide a more comprehensive overview and help decision-makers in practice, such as facility managers and directors of nursing, to select appropriate technologies.

In this review, digital technologies to promote social engagement are defined as technologies that are linked by information technology and/or equipped with sensors/actuators that either represent a further development of an existing technology or appear in their form for the first time and intend to support social engagement, social contacts or social activities in persons in need of care. They can either be used alone or in a group setting and may target one or different means of participation, such as synchronized or asynchronized communication, body movement, physical activity and sports, everyday activities such as cooking, shopping or gardening or games. Their use may be guided by health professionals or be completely independent from any facilitator. They may have been specifically developed for the use within the LTC setting or can be adapted from other application contexts and user groups.

Objective and research question

This systematic review aims to give an overview on published research on digital technologies to promote social participation of LTC residents. The following review questions are addressed: (I) What types of digital technologies for the promotion of social participation of nursing home residents are being reported in the international literature? (II) What are the reported effects of these technologies for residents and nursing staff? (III) What are the reported user characteristics and are there gender, age and/or disability-related differences in reported effects and use-patterns? (IV) What needs for further development with regard to specific user-groups or application settings are reported? (V) What facilitating or inhibiting factors with regard to the use and further development of these technologies are reported?

Design

A systematic review was performed according to the protocol and extraction form in the Cochrane Handbook for Systematic Reviews of Interventions, version 6.4 [19]. A review protocol was registered in PROSPERO (ID: CRD42022321789) and the PRISMA statement [20] was followed to guide this review. This systematic review is part of a federal research project on technology use in German nursing homes.

Search strategy

We searched health and nursing science databases (Pubmed, CINAHL) and informatics databases (IEEE Xplore, ACM Digital Library) from inception onwards in April 2022. The literature search was conducted in German and English and the English search terms can be found in Table 1. The search strategy based on the block-building approach [21], combined terms for digital technologies, social integration, social participation and long-term care and their corresponding synonyms. Titles and abstracts were searched. First, single terms for each block were searched. Second, all terms of a single block were combined using the Boolean operator OR. Finally, the results from the second step were combined for the three blocks using the Boolean operator AND. The complete search strategy is shown in Additional File 1. Reference lists of publications were searched for potentially relevant articles. Grey literature and thesis were not included.

Table 1

English search terms of the systematic search
Term 1: Digital technologies Term 2: Social integration/ participation Term 3: Long-term care
"digital technology" Smart* technol* "assistive technology" "innovative technology" robot* intelligen* assistive "virtual reality" "mixed reality" “human computer interaction" "human machine interaction" gerontotechnology gerontechnology "augmented reality"		“social integration” “social interaction” “social isolation” “social activity” lonel* “social participation” “social engagement” “social involvement” “social activity”		“care home” “nursing home “ “retirement home” “long-term care” stationary inpatient elderly resident* facilit*

Inclusion and exclusion criteria

Scientific papers included in this review had to have been published in English or German. An abstract and full text had to be available. Quantitative and qualitative studies that assessed the use of any digital technology to enhance social interaction and participation in individual or group settings in nursing homes were included. Proof-of-concept studies, laboratory experiments, use case descriptions, conference posters, or study protocols were excluded. For quantitative studies, changes in social interaction and participation compared between baseline and a follow-up measurement assessed with standardized instruments or metrics had to be the primary outcome. For qualitative and quantitative studies, self-reported experiences with the use of digital technologies by care recipients, or the impact of digital technology use on care professionals were eligible as further outcomes or areas of interest. Table 2 lists all inclusion and exclusion criteria.

Table 2

Inclusion and exclusion criteria
	Inclusion criteria	Exclusion criteria
Population	Persons in need of long-term care > = 18 years in inpatient long-term care facilities	Persons in need of care in outpatient care, short-term care, day care, acute care
Intervention	Any digital technology used to enhance social interaction and participation in individual or group settings that is information-networked and/or contains sensors/actuators	Technologies that are not information-networked and/or do not contain sensors/actuators
Control	- usual care - alternative, non-digital interventions - no interventions	Studies without a control group
Study designs	- Meta-analyses - systematic reviews - randomized controlled trials - non-randomized controlled trials - controlled before-after studies - observational studies - Qualitative studies	- Proof-of-concept studies - Laboratory experiments - Use Case Descriptions - Conference posters/abstracts - study protocols
Setting	long-term care: nursing home	- outpatient care - day care - Short-term care - Outpatient and inpatient primary care
Outcome	- Primary outcome: changes in social interaction and participation compared between baseline and follow-up measurement captured with standardized instrument or metrics. - Secondary outcome: Self-reported experiences with the use of digital technologies by care recipients (qualitative data); impact on care professionals based on quantitative or qualitative data.	Social integration and participation addressed exclusively as secondary outcome
Estimated effects	Quantitative reported effect measures

Search outcomes

Database search hits were managed in an EndNote 20 database. Two reviewers (KD and JR) independently screened titles, abstracts, and full texts using the online resource https://www.rayyan.ai/ [22] and the criteria as shown in Table 2. The review process began after determining a Cohen's kappa of 0.82 for a random number generator-determined selection of a subsample of 166 titles and abstracts. A third person (KS) was consulted if there was uncertainty regarding study inclusion.

Data extraction

The data from the included studies was transferred into a Microsoft excel (version 16.0) table and extraction was conducted by a single reviewer (KD). The extraction form included the following items: authors, year, country, study design, aim of the study, population, intervention, digital technologies, definition and constructs of social participation, direction of effect, facilitating and inhibiting factors of technology use, and needs for further developments. In addition, categories for types of digital technologies were derived inductively from the studies either by labelling a technology as stated by the studies authors or labelling a technology in reference to the categories given in [23].

Quality appraisal and synthesis

To reflect the state of research in terms of reliability, external validity, and generalizability of results, each publication was assigned to a level of evidence (LOE) by KD and KS, as shown in Table 4. Based on proven evidence-based medicine and nursing hierarchies [24, 25], the included studies were ranked from Level I as highest evidence to Level VII as lowest evidence or to no applicable level. The characteristic "well-designed" is placed in brackets as a critical appraisal was only conducted for RCT. Pilot studies were included if they piloted one of the designs to be included.

Table 4

Level of Evidence
Level I • Evidence from a systematic review or meta-analysis of all relevant randomized controlled trials (RCTs) or evidence-based clinical practice guidelines, based on systematic reviews of RCTs, or of 3 or more RCTs of good quality that have similar results Level II • Evidence obtained from at least 1 well-designed RCT Level III • Evidence obtained from (well-designed) controlled trials without randomization (e.g., quasi-experimental) Level IV • Evidence from (well-designed) case-control or cohort studies Level V • Evidence from systematic reviews of descriptive and qualitative studies (metasynthesis) Level VI • Evidence from a single descriptive or qualitative study Level VII • Evidence from the opinion of authorities or reports of expert committees No applicable level • Concept only, Studies with methods that cannot be clearly defined

In addition, critical appraisal was performed by one reviewer (KD) for all randomized controlled trials using the Version 2 of the Cochrane risk-of-bias tool for randomized trials (RoB 2). RoB 2 is a further development of the world's most widely used tool for assessing risk of bias in randomized trials and captures risk of bias in five domains (randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, selection of the reported result) with an assessment of low risk, some concern or high risk [26]. The assessments within each domain lead to an overall assessment of risk of bias. Although the population and outcomes of the included studies were comparable in general, there was still too much heterogeneity left between the interventions and digital technologies used for meta-analysis. Therefore, results are presented in narrative form.

We identified 6,212 records across all included databases. After deduplication and title and abstract screening, 5,624 studies were excluded and full-text screening was performed for 318 studies. In the end, 24 articles were included in data extraction in this review. Figure a summarizes the process of literature screening and selection.

Fig. a PRISMA Flowchart diagram of the study selection

Characteristics of the studies

The 24 included studies (Table 5) were mainly carried out in Australia (n = 7) [31, 32, 41, 43, 45], followed by Canada (n = 5) [29, 37, 41, 42, 43] and the Netherlands (n = 3) [30, 36, 48]. Only three studies were RCTs [28, 36, 47], and three studies were controlled trials [39, 48, 49]. We further included five (non-systematic) reviews [31, 32, 41, 43, 45], five observational studies [29, 33, 34, 42, 46], three mixed-methods studies [35, 37, 44], one case study [30], and one case control study [40]. Studies were published between 2008 and 2022, mostly in 2020 (n=5) [36, 39, 45, 49, 50] and 2021 (n=5) [32, 35, 37, 41, 46]. All studies were published in English. For studies reporting nursing sample characteristics, ages ranged from 18 to 101 (n=20, mean age 76,29, SD 12,23) [27, 29-42, 44, 46-49]. In studies reporting gender distribution (n=18) [27, 29, 30, 33-37, 39, 40-50], more women than men were included in 14 of the studies [27, 29, 30, 33, 35, 36, 42, 43, 44, 46-50]. The smallest study included 8 participants in its sample and the largest sample entailed more than 847 participants. Seven studies included people with dementia [32, 34, 35, 36, 43, 44, 45]. Constructs of social participation used as outcome variable are ‘(social) engagement’, ‘social isolation’, ‘loneliness’, ‘social interaction’, ‘social connectedness’, ‘social communication’ or ‘social dimensions of quality of life’, with eight studies using an established definition of social participation or related constructs [28, 29, 30, 31, 32, 41, 44, 45].

Table 5 Included studies
Author, year, country code	Design	Aim or research question	Population and setting	Intervention technology	Duration	Instruments	Construct of social participation examined	Direction of outcome
[27] Badawy et al., 2022, NOR	Qualitative	To investigate the perspectives and practices of health care professionals who facilitate ad hoc and prompt use of a technology for social communication	N=22 STC^t LTC^u	KOMP	/	Focus groups, Individual interviews, Participant observations	Social communication, (Social) Engagement	Predominantly positive
[28] Banks et al., 2008, USA	RCT	Does Animal-assisted therapy with AIBO decrease loneliness and, if so, how does this compare with that of a living dog?	N=38 LTC	Robotic dog AIBO	30 minutes/ week for 8 weeks	UCLA loneliness scale (Version 3), MLAPS^a	Loneliness	Predominantly positive
[29] Barbosa Neves et al., 2019, CAN	Observational	To enhance social connectedness among frail older adults in a retirement home in North America	N=12 LTC	iPad-based communication app	3 months	Abbreviated Duke Social Support Index, Short Revised UCLA Loneliness Scale, Field observations, Semi-structured Interviews	Social connectedness	Predominantly positive
[30] Biemans & Dijk, 2009, NLD	Case Study	Does sharing of everyday things through photo frames have a positive effect on social connectedness between elderly people and their family.	N=8 LTC	Vodafone™ 520 photo frame with integrated SIM card	6 weeks	Structured Interviews, Quantitative analysis of the photos sent	Social connectedness	Predominantly positive
[31] Brimelow et al., 2017, AUS	Other Review	Current activities and interventions implemented across LTCFs	15 studies N=720 aged care, LTC	PARO and AIBO Nintendo Wii videoconferencing computer training AAT	/	Mix	Loneliness Social networks Social isolation	Heterogeneous

Table 5 continued
Author, year, country code	Design	Aim or research question	Population and setting	Intervention technology	Duration	Instruments	Construct of social participation examined	Direction of outcome
[32] Budak et al., 2021, DEU	Other Review	To provide an overview of studies that used Ambient Assisted Living technologies to impact loneliness for people with dementia (PwD) living in LTC	24 included studies N >=786 PwD^v RCF^w LTC	BANDIT AIBO PARO VENSTER CuDDler Giraff CIRCA JustoCat Sophie and Jack Soft Robotic cat and dog The Chitchatters (CC) Digital Life Storybooks CompanionAble robot Nintendo Wii	/	Mix	Loneliness, Social Isolation	Predominantly positive
[33] Cardoso et al., 2019, PRT	Observational	To assess the impact of a recently developed platform for senior exercise with augmented reality games (exergames) in the perception of quality of life and socialization of older adults institutionalized in nursing homes.	N=18 LTC	Exergames with the projection PEPE and the body motion capture sensor (Kinect V2)	90-120 minutes one session per week over 3 months	SSSS^b, WHOQOL-bref^c	Quality of Life social dimensions	Predominantly positive
[34] Chu et al. 2017, AUS	Observational	(1) How do social robots (Jack and Sophie) engage actively with PwD? (2) How do social robots improve the capacity of caregivers in residential care facilities?	N=167 (139 residents, 28 staff) PwD LTC	Sophie and Jack	4-6 hours/ two times	WIB^d, DCM^e, Observation	(Social) Engagement	Predominantly positive

Table 5 continued
Author, year, country code	Design	Aim or research question	Population and setting	Intervention technology	Duration	Instruments	Construct of social participation examined	Direction of outcome
[35] D'Cunha et al., 2021, AUS	Mixed Methods	To evaluate whether the Virtual cycling experience (VCE) was physically safe and feasible and if it provided benefits over usual exercise activities on mood, apathy and engagement. usual activities (daily exercises) in the RACF.	N=10 PwD LTC	Virtual cycling experience (VCE)	one time for 25 minutes	PEAR^f, EPWDS^g, Semi-structured interviews, Pre- and post-condition questions, Observations	(Social) Engagement	Heterogeneous
[36] Feng et al., 2020, NLD	RCT	To explore the effects of contextual interactions between PWD and an animal-like social robot embedded in the augmented responsive environment in an LTC facility	N=16 PwD LTC	LiveNature, robotic sheep, augmented responsive environment	once a week for four weeks/ between 10:00 to 12:30 a.m. and 2:00 to 5:00 p.m. with up to 10 sessions; planned each day and each session lasting up to 20 minutes	OME^h, EPWDS^g, OERSⁱ, PEAR–Apathy subscale^j	(Social) Engagement	Heterogeneous
[37] Fiocco et al., 2021, CAN	Mixed Methods	To examine the immediate and longer-term benefits associated with VR tourism among older adults living in residential care.	N=18 RCF	Samsung Gear VRheadset, with Samsung Galaxy Note7 mobile phones and Sony headphones	6-10 minutes/ three times per week over six weeks	OPQOL-35^k, SES^l, GDS^m	(Social) Engagement	Predominantly positive
[38] Juul et al., 2019, AUS	Qualitative	To investigate the role of ‘Touchscreen Technology’ (TT) in facilitating increased physical activity and stimulating social interaction in RACFs in order to decrease social and physical inactivity.	N=30 (15 residents, 10 family members, 5 staff) RCF	large 65” (165 cm) interactive portable touch screen, with Windows software installed + Sitdance	10 months/ once a week for aprox. 30 minutes	In-depth semi-structure Interviews, Observation, Video ethnography	Social Interaction	Predominantly positive
Table 5 continued
Author, year, country code	Design	Aim or research question	Population and setting	Intervention technology	Duration	Instruments	Construct of social participation examined	Direction of outcome
[39] Lin et al., 2020, TWN	Controlled Trial	To explore [this issue] by considering several health-related outcomes of residents of a long-term care facility.	N=106 LTC	3D virtual reality and hands-on horticultural therapy program	18 one-hour sessions for 9 consecutive weeks; twice a week	CHQ-12ⁿ, 12-item Chinese Health Scale, The meaning in life questionnaire, General Mattering Scale, ULS-6^o	Loneliness	Predominantly positive
[40] Loi et al., 2016, AUS	Case-Control	To investigated a structured training program on using the internet via TT to residents with psychiatric conditions living in residential care facility.	N=5 RCF	touchscreen technology (TT) with Apple iPads	six weeks/ twice weekly/ 45 minutes	Rosenberg self-esteem scale, Hawthorne Friendship scale, Internet/TT questionnaire	Social Isolation	No effects
[41] Macdonald et al., 2021, CAN	Other Review	What is the evidence related to the use of assistive technologies to support social interaction in older adults in LTC homes?	25 studies, N>=847 LTC	Videotapes, Telephone, Videophones, Nintendo Wii game, iPad/Android tablet games, Picture- and video-viewing tools: Collegamenti, Touch Screen Technology, Special instrument: CRDL	ranging from seven days of telephone to two years of computer kiosks; one to three times per week, irregular use or not reported	Mix	Social Interaction, Loneliness	Predominantly positive
[42] McColl & Nejat, 2013, CAN	Observational	To determine engagement and compliance of potential elderly users with Brian 2.1 during one-on-one meal-eating scenarios.	N=8 ECF	Brian 2.1.	1 week with 2 occasions	robot acceptance questionnaire, video	(Social) Engagement	Predominantly positive
[43] Mordoch et al., 2013, CAN	Other Review	To review literature on social commitment robots and determine their efficacy within elderly population living with dementia	21 studies N=283 PwD LTC RCF	Paro, AIBO, NeCoRo, Humanoid torso mounted on a mobile base, Simmy, YORISOIIfbot, Simmy, Biscuit	one time to 8 months	Mix	Social Interaction	Predominantly positive
Table 5 continued
Author, year, country code	Design	Aim	Population and setting	Intervention technology	Duration	Instruments	Construct of social participation examined	Direction of outcome
[44] Moyle et al. 2014, AUS	Mixed Methods	To explore the use of a Giraff tele-presence robot as a means of positively influencing communication and relationships between residents with dementia living in a long-term care facility and their family	N=18 PwD (5 residents, 6 family, 7 staff) LTC	Giraff telepresence robot	a six- to eight-week period with the aim of conducting six calls per dyad/ between 15–60 minutes	Observed Emotion Rating Scale’ visual alertness and verbal engagement, Interviews, video observation, reflection	(Social) Engagement	Predominantly positive
[45] Neal et al., 2020, AUS	Other Review	To identify and synthesize empirical, peer-reviewed studies focused on the use of technology to enhance meaningful engagement of people with dementia living in residential aged care.	20 studies N=4 to 415 PwD RCF	PARO, AIBO, CuDDler, JustoCat, Soft robotic cat and robotic dog, "Sophie”and“Jack”, Robotic dog, Giraff, CIRCA, VENSTER, Memory Box, The Chitchatters (CC), Digital life storybooks, Standard computer modified to include various games and activities		Mix	(Social) Engagement	Predominantly positive
[46] Obayashi et al.,2021, JPN	Observational	To report the development process and evaluation of this robot named Monchan (a monster-looking doll bringing harmonious communications among users)	N=34 (30 residents, 4 senior staff) LTC	Monchan (a monster-looking doll bringing harmonious communications among users)	4 weeks/ 3-min interactions	interRAI, VC-IOE^p	(Social) Engagement	Predominantly positive
[47] Robinson et al., 2013, NZL	RCT	To explore how the psychosocial effects of Paro could be compared with a control group.	N=34 LTC	PARO	2 weekday afternoons for 12 weeks	ULS^o (Version 3), GDS^m, QoLAD^q	Loneliness	Predominantly positive
[48] Sinnema et al., 2019, NLD	Control Trial	To measure a broader range of aspects that together form the complete attitude of two groups towards Nao robot as a social companion.	N=52 (24 residents, 28 students) LTC	NAO (called Charlie)	one occasion 10 minutes	Prior experience with technology, UTAUT^r + eight additional questions, video analysis	Social Interaction	Predominantly positive
Table 5 continued
Author, year, country code	Design	Aim	Population and Setting	Intervention technology	Duration	Instruments	Construct of social participation examined	Direction of outcome
[49] Tsai et al., 2020, TWN	Control Trial	To evaluate the effectiveness of a smartphone-based videoconference program on NH residents’ loneliness, depressive symptoms and QoL.	62 participants in nursing homes	LINE	6 months	ULS^o, GDS^m, Taiwanese version of SF-36^s	Loneliness	Predominantly positive
[50] Zamir et al., 2020, GBR	Qualitative	(1) to assess the feasibility and acceptability of using video calls to conduct an inter-care home quiz through Skype on Wheels (SoW) and/or Skype TV	30 participants (22 residents, 8 staff) in a care home	inter-care home quiz through Skype on Wheels (SoW) and/or Skype TV	8 sessions; 30 min quiz with 15–20 min Meet and Greet	Observation, interviews, feedback, memo writing	Loneliness, Socialisation	Predominantly positive
^a MLAPS: Modified Lexington Attachment to Pets Scale ^b SSSS: Satisfaction with Social Support Scale ^c WHOQOL-bref: World Health Organization Quality of Life ^d WIB: Well-being/Ill-being Scale ^e DCM: Dementia Care Mapping ^f PEAR: Apathy Rating scale ^g EPWDS: The Engagement of a Person with Dementia Scale ^h OME: Observational Measurement of Engagement ^I OERS: Observed Emotional Rating Scale ^j PEAR–Apathy subscale: People Environment Apathy Rating Scales–Apathy subscale (PEAR–Apathy subscale) ^k OPQOL-35: Older People’s Quality of Life Questionnaire ^l SES: Social Engagement Scale ^mGDS: Geriatric Depression Scale ⁿCHQ-12:12-item Chinese Health Questionnaire ^o ULS-(6): Loneliness Scale (Version 6) ^p VC-IOE: Video Coding Protocol-Incorporating Observed Emotion ^q QoLAD: Quality of Life for Alzheimer’s Disease ^r UTAUT: Unified Theory of Acceptance and Use of Technology ^s SF-36: Taiwanese version of the short-form health survey ^tSTC: short-term care ^uLTC: long-term care facility (nursing home) ^vPwD: People with dementia ^wRCF: residential care facility

Digital Technologies

Table 6 Technology categories
Studies	Used digital technology	Technology category
[27] Badawy et al., 2022	KOMP	ICT
[28] Banks et al., 2008	AIBO	Robot: Pet
[29] Barbosa Neves et al. 2019	iPad-based communication app	ICT
[30] Biemans & Dijk, 2009	Vodafone™ 520 photo frame with integrated SIM card	ICT
[31] Brimelow et al., 2017	PARO and AIBO, Nintendo Wii, videoconferencing, computer training, AAT	MIX
[32] Budak et al., 2021	BANDIT, AIBO, PARO, VENSTER, CuDDler, Giraff, CIRCA, JustoCat, Sophie and Jack, Soft Robotic cat and dog, The Chitchatters (CC), Digital Life Storybooks CompanionAble robot, Nintendo Wii	MIX
[33] Cardoso et al., 2019	Exergames with the projection PEPE + the body motion capture sensor (Kinect V2)	Exergaming
[34] Chu et al. 2017	Sophie and Jack	Robot: Social
[35] D'Cunha et al., 2021	Virtual cycling experience (VCE)	Virtual Reality
[36] Feng et al., 2020	LiveNature + robotic sheep + with an augmented responsive enviroment	MIX
[37] Fiocco et al., 2021	Samsung Gear VRheadset, with Samsung Galaxy Note7 mobile phones and Sony headphones	Virtual Reality
[38] Juul et al., 2019	large 65” (165 cm) interactive portable touch screen with Windows software installed + Sitdance	Exergaming
[39] Lin et al., 2020	3D virtual reality and hands-on horticultural therapy program	Virtual Reality
[40] Loi et al., 2016,	touchscreen technology (TT) with Apple iPads	ICT
[41] Macdonald et al., 2021	Videotapes, Telephone, Videophones, Games: Nintendo Wii game, iPad/Android tablet games, Picture- and video-viewing tools: Colle gamenti, Touch Screen Technology, Special instrument: CRDL	MIX
[42] McColl & Nejat, 2013	Brian 2.1	Robot: Assistive
[43] Mordoch et al., 2013	Paro, AIBO, NeCoRo, Humanoid torso mounted on a mobile base, YORISOIIfbot, Simmy, biscuit	Robot: Pet
[44] Moyle et al. 2014	Giraff telepresence robot	Robot: Social
[45] Neal et al., 2020	PARO, AIBO, CuDDler, JustoCat, Soft robotic cat and robotic dog, Sophie and Jack, Robotic dog, Giraff, CIRCA, VENSTER, Memory Box, The Chitchatters (CC), Digital life storybooks, Standard computer modified to include various games and activities	MIX
[46] Obayashi et al.,2021	Mon-chan	Robot: Social
[47] Robinson et al., 2013	PARO	Robot: Pet
[48] Sinnema et al., 2019	NAO, in this intervention called Charlie	Robot: Humanoid
[49] Tsai et al., 2020	LINE	ICT
[50] Zamir et al., 2020	Inter-care home quiz through Skype on Wheels (SoW) and/or Skype TV	MIX

Different technology types were used, with a mix of technologies being included in six studies. Information and communication technologies (ICT) were assessed in five studies and three studies each examined Virtual Reality, social robots and pet robots. Two studies dealt with Exergaming and one study assessed a Humanoid robot and one an assistive robot. The duration of the intervention use ranged from one time to once a week over 10 months. The different digital technologies are presented in Table 6.

Reported effects

With regard to the reported effects (Table 5) of technology use, the majority of studies report predominantly positive effects for residents, with 20 studies showing positive results in terms of fostering social participation (mentioned here as a superordinate construct that includes the constructs from the included studies) when using different types of technologies. Three studies [31, 35, 36] reported heterogeneous effects and only one study [40] reported no effect on social participation.

Level of Evidence

Table 7 Level of Evidence of the included studies
Level of Evidence	n	Studies
I	/	/
II	3	[28] Banks et al., 2008; [36] Feng et al., 2020; [47] Robinson et al., 2013
III	3	[39] Lin et al., 2020; [48] Sinnema et al., 2019; [49] Tsai et al., 2020
IV	/	/
V	5	[31] Brimelow et al., 2017; [32] Budak et al., 2021; [41] Macdonald et al., 2021;[43] Mordoch et al., 2013; [45] Neal et al., 2020
VI	10	[27] Badawy et al., 2022; [29] Barbosa Neves et al., 2019; [30] Biemans & Dijk, 2009; [33] Cardoso et al., 2019; [34] Chu et al., 2017;[38] Juul et al., 2019; [42] McColl & Nejat 2013; [44] Moyle et al., 2014; [46] Obayashi et al.,2021; [50] Zamir et al., 2020
VII	/	/
NA	3	[35] D'Cunha et al., 2021;[37] Fiocco et al., 2021; [40] Loi et al., 2016

Based on the proven evidence-based medicine and nursing hierarchies [24,25], the LOE assigned most frequently was level VI (n = 10) (evidence from a single descriptive or qualitative study). In second place the level V was assigned to five studies. Level V describes evidence from systematic reviews of descriptive and qualitative studies e.g., other reviews. Levels II and III were each assigned to three studies (evidence from RCTs or CTs). The highest level I (Evidence from a systematic review or meta-analysis of all relevant randomized controlled trials (RCTs)) and level IV (Evidence from (well-designed) case-control or cohort studies) was not assigned to any study and three studies could not be classified in any level of evidence due to missing information. Table 7 shows the studies assigned to each level of the evidence category.

Results of Risk of bias

Table 8 shows the results of the RoB2 Tool [26] for the three included RCTs. For each study, RoB 2 was applied to evaluate the risk of bias. All three studies were evaluated to have some concerns in the randomisation process. One study did not provide enough information. This leads to the overall assessment of “high risk of bias”. The overall result for the two remaining studies is “some concern”.

Facilitating factors

Different facilitating factors regarding the use of digital technologies in NH are reported. Most often, a user-friendly design of the technology is described as an important factor [27, 29, 32, 34, 35, 42, 44]. Together with the design the user acceptance is considered to foster implementation of digital technologies in LTC [28, 35]. Next to the acceptance of the users, a positive attitude and support of nursing staff is conducive for successful implementation [38-40]. Further, an absence of structural barriers like high acquisition costs or of cognitive impairments of users is beneficial for the use of digital technologies [31, 37]. It is even described that the use of digital technologies can save costs for the facility. [50]. The Covid-19-pandemic was mentioned as another promoting factor [32]. Due to the restrictions, managers had to consider alternative participatory activities for NH residents, with digital technologies, such as robotic pets, being classified as more hygienic and causing less allergic reactions than real animals [45].

Inhibiting factors

Many factors inhibit the use of digital technologies in LTC. Structural barriers such as high acquisition costs, lack of infrastructure, lack of staff or lack of time of often untrained staff are prominent factors [27, 32, 38, 41, 50]. A critical attitude towards the new technology on part of the users [28] as well as cognitive and physical limitations prevent residents from using a technology [27, 29, 40, 41]. In addition, negative effects on cognition or physique are reported in some cases [37]. Also, a user-unfriendly design, as well as hardware and software problems, often pose an obstacle to technology use [30, 35, 44, 41]. Accordingly, software updates for existing technologies are missing [23]. Ethical concerns when using, e.g., robotic pets, were also frequently described [32, 43, 45].

This systematic review investigates the potential impact of digital technologies on social participation in older adults in LTC. The focus of our review was on alleviating social participation. However, no paper out of 24 included papers was directly aimed to address the term ‘social participation’, revealing that the topic of social participation is approached using various constructs such as social isolation or engagement etc., and that neither a standard definition is applied nor a systematic operationalization was performed. In addition, no systematic reviews and meta-analyses on the topic were identified using this search strategy, which reinforces the innovation content of the topic and demonstrates the lack of high-evidence studies on it. Most studies used the term ‘(social) engagement’ or ‘loneliness’ to study the construct of social participation [27, 28, 31, 32, 34–37, 39, 41, 42, 44–47, 49, 50]. This might be due to the lack of an overall definition of social participation.

The identified technologies vary from different kind of robots to virtual reality or ICT. Due to the large number of (non-systematic) reviews included [31, 32, 45, 43], a mix of digital technologies has often been investigated in the studies. Besides the mix, ICT were the most frequently digital technology examined in the studies [27, 29, 30, 40, 49]. A limitation of the sample results from excluding studies that assessed a mix of outcomes and did not focus exclusively on social participation. For example, overarching systematic reviews such as Abbot et al. 2019 [51], were excluded even though they entail information on technology use in long-term care that might be of interest when choosing technologies to incorporate in everyday care and social activities. Though the majority of the included studies found positive effects on the social construct, the broad majority of them had a low level of evidence. Only three RCTs could be found and one of them found only heterogeneous results and for one serious risks of bias could be identified. Only one RCT found a predominantly positive effect and had an only moderate risk of bias. This one was on Paro. Thus, only for Paro a positive effect could be shown in a study with a high level of evidence. These results confirm a former review, which could also only found positive effects in high level studies for Paro [23]. This raises the question of the limitations of established study designs for mapping cause-and-effect relationships in connection with technology use in a setting known for difficult recruitment conditions and high drop-out rates which in turn influence sample sizes and observation periods [52]. In addition, the fast-moving nature of technical products also contributes to the fact that long-term studies using an unchanged technology hardly seem realistic. Nursing science is called upon to think about alternative or new ways of collecting and analysing data in long-term care settings that, for example, include a more thorough assessment of routine data or utilize technologies such as ambient or wearable sensors [53] to map interaction or communication patterns.

Less rapidly changing than the technologies, but persistent, is the problem of declining social participation as a result of moving into a care home. To establish the link between technology and participation, research also needs to further deepen the definition of the outcome of social participation and improve its operationalisation. The question would then be how to improve the social participation (as defined) of people living in LCTs and what role technology can play in promoting social participation.

The reported inhibiting and facilitating factors in the use of digital technologies relate to both the structural and the individual level. Most of the included studies describe the extra staff workload or a user-unfriendly design as main inhibiting factors [27, 32, 35, 44, 38, 50, 41, 30]. This is also described by Lemaire et al. 2023 [54] as a problem regarding the staff support to set up the technologies for the use and the staff support of using the technologies together with the residents. But also, negative attitude, lack of experience or ethical concerns are reported on the individual level [28, 32, 39, 43, 45]. In context of the ethical concerns Johansson-Pajala et al. 2020 [55] state that robots could also lead to a decrease in human-to-human contact, i.e., that the robot reduces human interaction [56, 57]. The barriers mentioned in the included studies are known factors in the use of digital technologies in nursing care and are already addressed in the framework for studying non-adoption and abandonment of technologies by individuals and the challenges to scale-up, spread and sustainability (NASSS) [58]. For example, the second domain of the NASSS framework mentions the usability of the technology used, which is also repeatedly referenced in the included studies. In the fifth domain, the NASSS framework also addresses the necessary conditions, such as financing processes, which are required for technology implementation in a healthcare institution [58]. Based on this, the factors identified in this review are predominantly factors that have already been reported in other studies for the use of digital technologies in care settings. In combination with the identified inhibiting and promoting factors, it can be assumed that these factors do not depend on the type of technology (i.e. technologies to foster social participation), but are rather setting-dependent.

Needs for further development

This review once again highlights the lack of evaluation studies with high levels of evidence. As public bodies in particular will be reluctant to invest massively in respective technologies if there is no convincing proof of effectiveness, the need for such research is adamant, and researchers and developers alike should engage in such endeavours.

The integration of digital technology to enhance social participation in LTC settings presents numerous other challenges as well. To address these, several critical factors for further development are evident. First, there should be no barriers in the infrastructure. This indicates that there should be an Internet Access and for example enough technologies like robots for everyone, who wants to interact with them [28, 44]. That goes along with enough financial support to purchase such technologies [38]. Furthermore, Mordoch et al. 2012 [43] and Neal et al. 2020 [45] recommend that guidelines and policies for the ethical use of technologies should be developed and implement in LTC facilities. In the technology design process, staff perceptions should be integrated to minimizing the burden on staff and preparation time for technology use. A training of the staff members can be considered as crucial for the implementation [35, 38, 50]. In addition, a digital intervention should have interactive features and there should be a promotion of an ongoing innovation and customized content to provide stimulation for residents and to take their individual preferences into account [36, 37, 41]. Mordoch et al. 2012 [43] suggest that robotic interventions should include family members in the application for a more comprehensive approach. However, nursing home managers and nursing staff should pay special attention to ensure that technology complements, rather than replaces human contact in LTC as described by Johansson-Pajala et al. 2020 [55].

The Covid-19 pandemic led to the expansion of the use of digital technologies in LTC to continue to promote contacts to the outside world [32, 59]. This might pose as a starting point to further advance the development and implementation of such technologies. This review is, to the best of our knowledge, the first to systematize digital technologies not only for elderly people in the general population or only for people with dementia, but to look specifically at all residents in LTC.

Limitations

In context of the literature search, additional databases could have been systematically searched to achieve more hits or more suitable studies. However, with such search strategy there is always a chance that something is remained undiscovered. There is also a limitation associated with a single researcher in the data extraction and critical appraisal process that may have affected the analysis process. Additionally, a meta-analysis was not applicable because the interventions were different and the outcome variables were not comparable. Further, deviating from the review protocol, a risk of bias was only performed for the included RCTs, but not for all other included study designs, due to the time elapsed in the project. The statements on possible effects are only possible to a limited extent, because only three RCTs could be identified with the help of the search strategy. Another limitation is the strict focus on the setting of LTC and the inclusion criteria for this. Thus, studies with mixed settings were excluded and relevant results might have been missed. Finally, only literature published in the English and German language was included, so language bias must be noted.

The current review shows that social participation is rarely studied as a primary outcome measure of digital technologies interventions for residents of LTC. Despite the limitations of this review, we conclude that digital technologies hold the potential to impact social participation in people in LTC. Digital technologies such as ICTs, different types of robots, virtual reality or exergaming are reported to have positive effects on the social participation of the residents and also the staff members in form of time savings. Unfortunately, however, these results come from studies with low levels of evidence, and – with the notable exemption of Paro – positive effects have not been proven in high level evaluation studies yet.

A lack of infrastructure, high costs, ethical concerns, training, and a user-unfriendly design are important starting points for improving the use and implementation of digital technologies in the setting. This study suggests a further research of the primary outcome "social participation" in future studies, as so far social participation is mainly researched under the outcomes ‘loneliness’ and ‘(social) engagement’. Additionally, more consistency in the measurement of social participation outcomes is needed.

LTC

Long-term (care facilities)

Nursing Home

ICT

Information and communications technology

LOE

Level of Evidence

Availability of data and materials

The datasets used and/or analyzed during the current study are included in this published article and the Additional files.

Acknowledgements

Not applicable

Funding

The study airses from the project „Digitale Technologien zur Verbesserung sozialer Interaktion und Teilhabe von Menschen mit Pflege- und Unterstützungsbedarf in der stationären Langzeitpflege” which was funded by the Federal State Bremen (Number 59000169)

Corresponding Author

*Corresponding E-Mail: [email protected]

Authors’ contributions

KD, JR, KS CS, HR, KWO, conceptualized and conducted the study. CS, HR, KWO: acquired the financial support for the project leading to this publication. CS, HR, KWO, KS advised on the review process. KD and JR handled the screening in all stages. KD, JR and KS conceptualised the data abstraction form. KD, JR, KS, CS, HR, KWO interpreted the results and KD wrote the first draft of the manuscript. All authors authorized the final version of the manuscript that was submitted.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

There are no competing interests to declare.

Additional files

Additional file 1: Search strategy

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No competing interests reported.

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Digital technologies to promote social engagement of nursing home residents: A systematic review of existing literature

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