In response to increased life expectancy and an increase of chronic diseases, the global need for primary health care is rising (World Health Organization, World Bank, 2011). Services in the community (i.e. outpatient, ambulatory and home-based settings) require participative, interprofessional interaction (Frenk et al., 2010). Interprofessional interaction is participative when service providers from different health and social care professions actively engage with patients, families and caregivers, whom we define as ‘service users’ (Ekman et al., 2011; World Health Organization, 2010). Service providers support users in their self-reflection of knowledge or performance and include them as equal contributors to solutions (Leino-Kilpi et al., 2005). They coordinate and network when users seek health services or proceed to further providers (Reeves et al., 2010).
Health service users and providers from different professions transfer and transform knowledge to assess, judge, and treat clinical data in a consensual approach (Edwards et al., 2004). This is defined as interprofessional collaborative reasoning (Blondon et al., 2017) and includes 1) assessment of expectations and functioning, as defined by the International Classification of Functioning, Disability and Health (ICF; Fifty-Fourth World Health Assembly, 2001); 2) interprofessional shared decision-making, as defined by Légaré et al. (2011), around a commitment point (Land et al., 2017); 3) procedural reasoning, e.g. care and action planning, implementing and progressing treatment (Edwards et al., 2004). Collaborating with health service users is relevant for considering their individual and contextual factors and key to their empowerment (Leino-Kilpi et al., 2005; World Health Organization, 2022).
Interprofessional collaborative reasoning is already used as a conceptual framework in learning (Gummesson et al., 2018). Thus, interprofessional collaborative learning occurs when health and social care professionals or students interact with each other to learn about and from their (future) service users’ clinical data in a consensual approach (Barr & Waterton, 1996; Edwards et al., 2004). The term ‘collaborative’ stands for collaboration between learning service providers from multiple professions and users. It refers to helping others to attain a goal (Castañer et al., 2020), by considering the service users’ and providers’ reasoning (Blondon et al., 2017). Collaborative teams or networks form, with more or less shared identity and responsibility, integration or independence, that solve tasks with varying clarity of roles and goals (Reeves et al., 2010).
Digital solutions can enhance health service interaction between learners by facilitating ways of communication (World Health Organization, 2020) regarding records of service users’ clinical data (Schouten et al., 2021), or remotely (Rosen & Leone, 2022). Digital technologies may, for example, include images, videos, speech and text systems such as collaborative documents or live online scenarios, messaging, applications or portable systems (Arntz et al., 2023). The COVID-19 pandemic increased the use of digital solutions in primary health care (Fahy et al., 2021; Kumpunen et al., 2022) as well as the transformation to digitally enhanced collaborative learning (Coleman et al., 2023; Gaebel et al., 2021). To extend this potential, quality improvement through training of service providers (Fahy et al., 2021), interdisciplinarity and civic engagement could be promoted (European University Association, 2021).
It remains unclear how digital solutions are currently used in interprofessional collaborative learning to facilitate service user participation. The transition of learners from knowing to performing collaborative interaction with the use of digital solutions affords bridging the gap of knowledge between undergraduate and continuous professional development (Connell et al., 2021; Lawn, 2016). Learning interactions in this process may vary in their technological, temporal, spatial or pedagogical planning, depending on the task, individuals and context (CAST, 2018; Joosten et al., 2021). When health service users and providers apply interprofessional collaborative learning, specific settings may influence their way of interaction (Reeves et al., 2010) and choice of digital solutions. Therefore, this research merges the existing knowledge on the use of digital solutions in collaborative learning between multiple professions and service users.
This systematic review aimed to identify which digital solutions can facilitate service users to participate in an interprofessional learning process of service providers, who reflect on the users’ health in a consensual approach. A systematic review was conducted to answer the following questions: (1) Which digital solutions can facilitate the participation of health service users in collaborative learning of interprofessional service providers? (2) How do service users participate in collaborative learning of interprofessional health teams or networks with the use of digital solutions?
In this systematic review, we followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework recommendations (Page et al., 2021).
Included studies met all of the following criteria: 1) English language, 2) original empirical work, 3) involving a service user and service providers from a minimum of two professions, 4) any health caring profession, including teachers and technicians involved in digital health services, 5) interprofessional collaborative learning in the range of team or network interaction, 6) identified or applied digital solutions used in a learning process.
We excluded studies that were: 1) proceedings, posters, books, protocols, frameworks, dissertations, reviews, editorials or comments, 2) focused on patient education or safety, inpatient, critical, veterinary or dental care, 3) without evaluation.
Reasons for these eligibility criteria were: 1) English being an international, scientific language, 2) to identify primary research with outcome measures and to exclude grey literature. 3) According to the aim and rationale of this review, the involvement of service users was mandatory, and for interprofessional interaction at least two professions are needed. 4) Any caring profession was included based on the definition of Ellis & Hogard (2021) to consider a broad range of stakeholders that contribute to delivering primary health care. 5) The concept of interprofessional collaborative learning and interaction by means of teams or networks applied as defined in the introduction (CAIPE, 1997; Edwards et al., 2004; Reeves et al., 2010). 6) To avoid a selection bias of research methods, not only the application, but also an identification of digital solutions were included. Finally, some exclusion criteria were used to support the focus on primary care of people’s overall health, while the exclusion of patient education was added as an amendment to the study protocol to clarify the focus on learning of service providers.
Search terms (displayed in Table 1) were synonymised within their PICO criteria (Centre for Evidence-Based Medicine, 2020) and evaluated in Medical Subject Headings (MeSH). Terms and synonyms were combined within their categories with OR and categories with each other using AND, as Table 1 describes. Some terms were excluded by being combined with NOT. Where possible, language (English), and species (humans) were applied, justified by the eligibility criteria. For the terms (communicat* OR collaborat* OR teamwork OR network OR coordinat*) the limitation [Title/Abstract/Keywords:] was used. The terms ‘function, functioning or ICF’ were used to emphasise publications with the International Classification of Functioning, Disability and Health (ICF) as a common framework and language (Leonardi et al., 2022), yet this was not included in the eligibility criteria.
Search Terms Clustered per PICO Criteria (Centre for Evidence-Based Medicine, 2020).
Population |
(profession OR profession* OR employee OR staff OR student OR provider) AND (interprofessional relations[MeSH Terms]) AND (health OR medic* OR care) AND (community OR client OR patient OR person OR family OR user) AND |
Intervention |
(communicat*[Title/Abstract] OR collaborat*[Title/Abstract] OR teamwork[Title/Abstract] OR network[Title/Abstract] OR coordinat*[Title/Abstract]) AND (educat* OR lecture OR course OR learn* OR train* OR teach OR taught) AND (ICF OR function OR functioning) AND (digital OR technology OR mail OR video OR speech OR text messaging OR app OR application OR platform OR wearables OR connected OR computer* OR interface OR ehealth OR e-health OR electronic) AND |
Outcome |
(expect* OR needs OR reason* OR deci* OR decision-making OR prevent* OR rehabilitat* OR therap* OR monitor*) AND (activ* OR interven* OR interact* OR exchange OR discuss* OR practice OR understand* OR behavi* OR support OR empower* OR participat* OR cent*) |
Limits | NOT veterinary NOT dental NOT dentist* NOT safety NOT critical NOT resuscitation |
Filters | Humans, English |
The databases CINAHL (via EBSCOhost), MEDLINE and PubMed Central (via PubMed), ScienceDirect (
The query was adapted to the respective structure of the search function in the relevant data resources. The ScienceDirect interface did not support wildcards and allowed a maximum of eight Boolean characters per field. Thus, search terms were limited to the MeSH term interprofessional relations and the terms health, medical or care, combined with educate, learn, train, or teach, function, functioning or ICF and digital or technology. In the field “title, abstract or author-specific keywords” the terms communication, collaboration, teamwork, network or coordination were used. At Cochrane library, a maximum of five fields were allowed. Thus, the terms interprofessional, health and function were combined with communicat*, collaborat*, teamwork, network or coordinat* as terms in title, abstract and keywords.
The PRISMA flow diagram (Figure 1, adapted from Page et al., 2009) shows the steps of selecting relevant publications. The results of database and register searches were imported into the literature management tool ‘Zotero version 6.0.19’. The first author removed duplicates as proposed by ‘Zotero’ and screened each record and full text report based on the eligibility criteria. First the exand then the inclusion criteria were applied, all criteria in their described hierarchical order. The last author dealt with arising conflicts (
The first author collected data from each report into the data management tool based on the following predefined domains (under consideration of Li et al., 2022): 1) year 2) country, 3) setting, 4) aim, 5) study design, 6) participants, 7) the use of digital solutions in interprofessional collaborative learning, 8) the participation of service users in the collaborative learning process. In line with the research questions, the last two domains were the most relevant, while other details from reported interventions or outcome measures were not considered in further detail.
Tabulation methods were used to present the results of individual studies and synthesis following the order of their publication. No statistical synthesis methods were used and therefore no effect measures were calculated. To be eligible for synthesis, data had to be reported in the respective domain. The first author synthesised data by clustering the described domains thematically. Countries were clustered per continent, study design was clustered in qualitative, quantitative and mixed methods. Settings were distinguished by whether participants accessed digital solutions from classrooms, from service provider facilities (outpatient or ambulatory care), or from the service users’ permanent living environment (home-based care). Furthermore, the number of service users and service providers involved and the participants’ professions were summarised.
To synthesise interventions and outcomes, the first author used the data management tool to identify the use of digital solutions and the participation of service users in interprofessional collaborative learning. The prepared synthesis was then reviewed by the co-authors. Due to the diversity of aims and methodology, tools to assess risk of bias could not have been evaluated in overall across findings. Thus, risk of bias in the included studies was not assessed by using any instrument or tool.
The database and register search led to a total of
Several studies appeared to meet the inclusion criteria but were excluded, for example because the help to attain a goal was only directed towards the service user (Castañer et al., 2020) and thus focusing on patient education, or because interprofessional collaborative learning was not given (Table 2).
Excluded Studies.
Focus on patient education |
Hjelle, K. M., Skutle, O., Førland, O., & Alvsvåg, H. (2016). The reablement team’s voice: A qualitative study of how an integrated multidisciplinary team experiences participation in reablement. Ho, P., Lambert-Kerzner, A., Carey, E., Fahdi, I., Bryson, C., Melnyk, S., Bosworth, H., Radcliff, T., Davis, R., Mun, H., & et al. (2014). Multifaceted intervention to improve medication adherence and secondary prevention measures after acute coronary syndrome hospital discharge: A randomized clinical trial. Knoop, J., de Joode, J. W., Brandt, H., Dekker, J., & Ostelo, R. W. J. G. (2022). Patients’ and clinicians’ experiences with stratified exercise therapy in knee osteoarthritis: A qualitative study. Noviani, L., Diantini, A., & Subarnas, A. (2020). Collaboration between interprofessional healthcare and patients to improve quality of life type 2 diabetes via smartphone application. Richards, D., Hill, J., Gask, L., Lovell, K., Chew-Graham, C., Bower, P., Cape, J., Pilling, S., Araya, R., Kessler, D., & et al. (2013). Clinical effectiveness of collaborative care for depression in UK primary care (CADET): Cluster randomised controlled trial. |
No learning interventions for service providers |
Blackstone, S. W., Wilkinson, K. M., Luo, F., Canchola, J., & Roman-Lantzy, C. (2021). Children with cortical visual impairment and complex communication needs: Identifying gaps between needs and current practice. Bradshaw, A. B., Bonnecaze, A. K., Burns, C. A., & Beardsley, J. R. (2021). Impact of an interprofessional collaborative quality improvement initiative to decrease inappropriate thyroid function testing. Heiden, S. M., Holden, R. J., Alder, C. A., Bodke, K., & Boustani, M. (2017). Human factors in mental healthcare: A work system analysis of a community-based program for older adults with depression and dementia. Pariser, P., Pham, T. N. T., Brown, J. B., Stewart, M., & Charles, J. (2019). Connecting people with multimorbidity to interprofessional teams using telemedicine. Van Dongen, J. J. J., Lenzen, S. A., Van Bokhoven, M. A., Daniëls, R., Van Der Weijden, T., & Beurskens, A. (2016). Interprofessional collaboration regarding patients’ care plans in primary care: A focus group study into influential factors. Wu, R., Appel, L., Morra, D., Lo, V., Kitto, S., & Quan, S. (2014). Short message service or disService: Issues with text messaging in a complex medical environment. |
Interaction with (simulated) service users was not part of the learning process |
Carroll, J. C., Talbot, Y., Permaul, J., Tobin, A., Moineddin, R., Blaine, S., Bloom, J., Butt, D., Kay, K., & Telner, D. (2016). Academic family health teams: Part 1: Patient perceptions of core primary care domains. MacNeill, H., Telner, D., Sparaggis-Agaliotis, A., & Hanna, E. (2014). All for one and one for all: understanding health professionals’ experience in individual versus collaborative online learning. Meystre, C., Bourquin, C., Despland, J.-N., Stiefel, F., & De Roten, Y. (2013). Working alliance in communication skills training for oncology clinicians: A controlled trial. Petersen, L., Birkelund, R., & Schiøttz-Christensen, B. (2020). Challenges to cross-sectoral care experienced by professionals working with patients living with low back pain: A qualitative interview study. Shoemaker, M., de Voest, M., Booth, A., Meny, L., & Victor, J. (2015). A virtual patient educational activity to improve interprofessional competencies: A randomized trial. Tempest, S., Harries, P., Kilbride, C., & De Souza, L. (2012). To adopt is to adapt: The process of implementing the ICF with an acute stroke multidisciplinary team in England. Walker, L. E., Cross, M., & Barnett, T. (2019). Students’ experiences and perceptions of interprofessional education during rural placement: A mixed methods study. |
Digital solutions did not support interprofessional collaborative learning |
Conti, G., Bowers, C., O’Connell, M. B., Bruer, S., Bugdalski-Stutrud, C., Smith, G., Bickes, J., & Mendez, J. (2016). Examining the effects of an experiential interprofessional education activity with older adults. Floren, L., Mandal, J., Dall’Era, M., Shin, J., Irby, D., Cate, O., & O’Brien, B. (2020). A Mobile Learning Module to Support Interprofessional Knowledge Construction in the Health Professions. O’Connell, M. B., Fava, J. P., Gilkey, S. J., Dereczyk, A. L., Higgins, R., Burke, C. A., Lucarotti, R. L., & Gaggin, P. E. (2021). Using community pharmacies and team observed structured clinical encounters (TOSCEs) for interprofessional education and training. Posenau, A., & Peters, T. (2016). Communicative positioning of one’s own profession in interprofessional settings. Thomson, K., Gripton, J., Lutchmiah, J., & Caan, W. (2007). Health facilitation in primary care seen from practice and education. Watt-Watson, J., McGillion, M., Lax, L., Oskarsson, J., Hunter, J., MacLennan, C., Knickle, K., & Victor, J. C. (2019). Evaluating an Innovative eLearning Pain Education Interprofessional Resource: A Pre-Post Study. |
Eligible studies were published between 2000 and 2022, although we did not restrict our search to these years. Seven studies were conducted in North America (Bluml et al., 2000; Byerly et al., 2021; Javadi et al., 2018; Lempicki & Holland, 2018; McGilton et al., 2011; Sabus et al., 2011; Shorten et al., 2015), six in Europe (Andersson et al., 2021; Korstjens et al., 2021; Metzelthin et al., 2013; Poss-Doering et al., 2020; Saia et al., 2020; Swallow et al., 2016), three in Asia (Liaw et al., 2020; Uslu-Sahan & Terzioglu, 2020; Yang et al., 2017) and two in Oceania (Darlow et al., 2015; Lucas et al., 2020). In Table 3, the origin countries of each study and the order of publication year are described.
Characteristics of Included Studies.
Authors, Year | Country | User | Provider | ||||
Bluml et al., 2000 | USA | Ambulatory care | Improve patients’ care | Qualitative | 397 | 26 | Point-of-care testing |
McGilton et al., 2011 | Canada | Continuing care facility | Assess implementation | Mixed methods | 9 | 18 | Videos before role play |
Sabus et al., 2011 | USA | University | Understand tool’s utility | Quantitative | 1 | 69 | Virtual reality, avatar |
Metzelthin et al., 2013 | Netherlands | Ambulatory practices | Examine implementation | Qualitative | 13 | 45 | Digital record forms |
Darlow et al., 2015 | New Zealand | University | Evaluate a programme | Quantitative | 1 | 83 | E-learning, videos |
Shorten et al., 2015 | USA | Urban outpatient clinics | Outline creation process | Qualitative | 9 | 21 | Interactive web site |
Swallow et al., 2016 | UK | Home-based care | Report users’ feasibility | Quantitative | 21 | 23 | Web application |
Yang et al., 2017 | Taiwan | Hospital simulation lab | Evaluate a programme | Quantitative | 1 | 88 | E-learning, videos, high-fidelity simulation |
Javadi et al., 2018 | Canada | Home settings | Test exercise feasibility | Mixed methods | 21 | 106 | Tablet, web application |
Lempicki & Holland, 2018 | USA | University | Evaluate feasibility | Quantitative | 2 | 6 | Video conferencing |
Liaw et al., 2020 | Singapore | University | Evaluate a programme | Quantitative | 1 | 120 | Virtual reality, avatar |
Lucas et al., 2020 | Australia | Hospital simulation lab | Explore perceptions | Mixed methods | 2 | 60 | Videos at a simulation |
Poss-Doering et al., 2020 | Germany | Primary care networks | Explore contributions to antibiotic prescribing | Mixed methods | 1 | 354 | E-learning, tablet, digital records |
Saia et al., 2020 | Estonia | Social rehabilitation | Investigate perceptions | Qualitative | 13 | 9 | Communication tools |
Uslu-Sahan & Terzioglu, 2020 | Turkey | University | Determine effectiveness of simulation methods | Quantitative | 2 | 84 | Power-point before a high-fidelity simulation |
Andersson et al., 2021 | Sweden | Primary care center | Explore partnership when using the system | Qualitative | 22 | 15 | Device, mobile phone, database, web portal |
Byerly et al., 2021 | USA | Nursing home | Explore role fluidity | Qualitative | 5 | 47 | Computer, records |
Korstjens et al., 2021 | Netherlands | Ambulatory practices and hospitals | Understand maternity care collaboration | Qualitative | 26 | 62 | Video-clips, pictures in |
In seven studies, participants accessed digital solutions from classrooms located either in higher education facilities (
The aims and study designs of the reports are displayed in Table 3. By using digital solutions, two reports aimed at understanding the collaboration between service users and providers (Andersson et al., 2021; Korstjens et al., 2021) and three studies explored how to improve patient’s care (Bluml et al., 2000; Poss-Doering et al., 2020; Saia et al., 2020). Five studies described the development and testing of the collaborative use of a digital solution (Sabus et al., 2011; Shorten et al., 2015; Swallow et al., 2016; Javadi et al., 2018; Lempicki & Holland, 2018). Eight studies evaluated a collaborative learning intervention that uses digital solutions (Byerly et al., 2021; McGilton et al., 2011; Metzelthin et al., 2013; Darlow et al., 2015; Liaw et al., 2020; Lucas et al., 2020; Uslu-Sahan & Terzioglu, 2020; Yang et al., 2017).
Seven studies applied qualitative methods, including observations (Bluml et al. 2000; Byerly et al., 2021), individual (Saia et al., 2020) and focus group interviews (Andersson et al., 2021), reflective ethnography (Korstjens et al., 2021), an iterative, participative design and development process (Shorten et al., 2015) and a process evaluation (Metzelthin et al., 2013). Four studies used mixed methods, specifically a development and feasibility study (Javadi et al., 2018), two pre-posttest designs, one supplemented with a focus group interview (McGilton et al., 2011), the other with a thematic analysis of reflective statements (Lucas et al., 2020). Poss-Doering et al. (2020) applied thematic analysis to interview data and a descriptive analysis to survey results. From the seven studies which applied quantitative methods, Sabus et al., (2011) also applied a descriptive analysis to survey results, Yang et al. (2017) a pre-post comparative cross-sectional study, Darlow et al. (2015) applied a controlled trial, and four studies used randomised controlled trials (Lempicki & Holland, 2018; Liaw et al., 2020; Swallow et al., 2016; Uslu-Sahan & Terzioglu, 2020).
The investigated studies reported on a total of 1,236 service providers (
In total 21 professions participated in the results (n = 18; MS = 3; 2–10). Table 4 displays the involved professions in the order of their frequency.
Frequency of Involved Professions.
Javadi et al. (2018) included other non-specified consulting specialists and non-paid volunteer pairs of undergraduate students and retired professionals or other experienced community members. Metzelthin et al. (2013) reported invitations to team meetings (providing a social worker, homecare provider or pharmacist as examples) and referrals to further disciplines (e. g. nutritionist, speech therapist) that were not interviewed and thus not counted as participants.
We provide a descriptive overview of the digital solutions used in the 18 included articles (Table 3). Digital solutions were used, on the one hand, to facilitate the interprofessional collaborative learning process, and on the other hand, to facilitate interactive communication between service users and interprofessional providers, which fostered learning about and from service users in a consensual approach. Several studies used more than one digital solution.
The following digital solutions facilitated interprofessional collaborative learning: Two studies applied avatars in a virtual reality environment, one was role-played by an instructor to teach interprofessional home assessment (Sabus et al., 2011), and the other was based on a prepared script and accompanied by a facilitator avatar located in a ward (Liaw et al., 2020). In one study, video recordings and pictures were used to engage reflection of communication in previous collaborative interaction (Korstjens et al., 2021), while four other studies used video demonstrations that were followed by live interaction, specifically a role-play on communication (McGilton et al., 2011), contact with a simulated service user (Lucas et al., 2020; Yang et al., 2017), or the visit of a person living in the community (Darlow et al., 2015). Two of these video demonstrations were part of a more extensive e-learning intervention (Darlow et al., 2015; Yang et al., 2017), while another e-learning intervention on communication did not report any video usage (Poss-Doering et al., 2020). One study reported the usage of a power-point-presentation to be followed by a simulation intervention (Uslu-Sahan & Terzioglu, 2020). In total, three studies applied high-fidelity simulation, yet only one, a SimMan® 3G simulator (Yang et al., 2017), could be identified as a mannequin that was equipped with digital technologies. The study of Uslu-Sahan & Terzioglu (2020) used a scenario template that described digital technologies, but did neither describe digital technologies in their simulation applications nor specify the terms high-fidelity and hybrid simulations any further. Lucas et al. (2020) used medium and high-fidelity simulators to apply nasogastric tube insertion, which was rated as mechanical simulation.
Interactive communication between service users and interprofessional providers formed the basis of learnings in studies that used the following digital solutions: Lempicki & Holland (2018) applied the web-based video conferencing service Zoom in comparison to a face-to-face encounter. Saia et al. (2020) identified the need to develop information and communications technology for information sharing, and to use the latest technology to communicate, e.g. by social media solutions, according to the service users’ preferences. In addition, clinical service user data was exchanged in a consensual approach in eight studies: Digital records were exchanged between service users and providers via web site (Shorten et al., 2015), web portal (Andersson et al., 2021) and web applications that were designed to be used on a mobile device in general (Swallow et al., 2016) or on a tablet (Javadi et al., 2018). Poss-Doering et al. (2020) used tablets for displaying digital material to service users and identified the use of shared digital records as supportive to continuity of primary care in networks. Two further studies recommended (Metzelthin et al., 2013) and applied (Bluml et al., 2000) documentation and exchange systems, without specifying them in any detail. Data of digital records was collected manually from digital devices that measured cholesterol (Bluml et al., 2000) and blood-pressure (Andersson et al., 2021). In the study of Byerly et al. (2021), live exchange between learning service providers on digital records in front of a local computer system was followed by a face-to-face encounter.
Digital solutions facilitated participation of service users in interprofessional learning via collaboration on their data (
In five studies, interprofessional learners interacted with played or digitally simulated service users (Lempicki & Holland, 2018; Liaw et al., 2020; Sabus et al., 2011; Uslu-Sahan & Terzioglu, 2020; Yang et al., 2017). In addition, four studies used videos as a solution to train learners on how to interact with service users (Darlow et al., 2015; Lucas et al., 2020; McGilton et al., 2011; Yang et al., 2017).
This systematic review aimed to identify digital solutions that can facilitate the participation of health service users in collaborative learning of interprofessional service providers who reflect on the users’ health in a consensual approach. It was further investigated how service users participate in collaborative learning of interprofessional health teams or networks with the use of digital solutions. This may support the technological, temporal, spatial or pedagogical planning (Joosten et al., 2021) in digitally enhanced interprofessional collaborative learning among health service providers. By using digital solutions to facilitate the participation of service users, the gap between theory and reality may be bridged and quality in primary health care could be improved (Connell et al., 2021; Fahy et al., 2021).
No study that was published before 2000 was eligible, which could be related to the inclusion of ‘patient-centredness’ as a health care quality goal (Committee on Quality of Health Care in America, 2001), the establishment of the ICF classification (Fifty-Fourth World Health Assembly, 2001), or to internet connectivity and digital transformation (Lin & Wu, 2022). The latter relates to the fact that none of the eligible studies were conducted in low- or middle-income countries.
Settings seemed to influence access to service users and professions: In educational settings, the digital solutions used focused on interprofessional learning and used simulated service users to facilitate collaborative reasoning (Blondon et al., 2017). This may have resulted from a lack of access to real service users, ethical considerations or served educational standardisation (Luck & Peabody, 2002). In primary care settings, interprofessional communication between providers with and about service users was identified or applied, which led to learning but might not have been planned as learning. Caring family or community members were considered in some studies, but could receive more attention in research methodologies and reporting (Arksey & Hirst, 2005).
Communication occurs in diverse settings and can be supported by various technologies (World Health Organization, 2020), which is also reflected in the findings. Digital solutions can facilitate the participation of health service users in collaborative learning of interprofessional service providers as a relevant factor in multiple ways (Van Dongen et al., 2016). For example, videos were either used to prepare for a service user encounter or to reflect on it. At four universities and in a hospital simulation lab, interaction with service users was played or digitally simulated. These studies were not excluded, because the actors or digital solutions were considered being service users. According to Towle et al. (2010), involvement of patients may range from focus of an electronic case and standardised patients to involving patients at the institutional level. Whether a technology enhances interprofessional communication between service users and providers depends on whether it is accessible to all parties and on how communication takes place. Holistic and flexible approaches will facilitate meeting communities’ diverse needs (European University Association, 2021).
How service users participate in collaborative learning of health teams or networks with the use of digital solutions differs between the level of the learners (students vs. professionals) and the settings (university or simulation lab vs. applied care). This may relate to a discrepancy of systems possibilities and desired functions or design ideas (Schouten et al., 2021). In several studies, the application or identification of digital solutions was not the aim. It could be that further studies had used digital solutions but did not explicitly report them. The focus on digital solutions may lead to underestimating the usage of analogue solutions or risk implying that digital solutions could be superior. Participation of service users in interprofessional collaborative learning may as well take place without any digital solution.
In all studies, the facilitation of interaction depended on a person engaging and/or leading interprofessional collaborative learning. Land et al. (2017) also point out the importance of engagement, focusing on a commitment point. As a possibly facilitating role, a decision coach is introduced by Légaré et al. (2011) in the model of interprofessional shared decision-making. As shown by Kienlin et al. (2022), collaborative interaction can be trained and assessed throughout collaborative reasoning. Thus, the use of a digital solution and not the technology itself influences, how service users participate. This is supported by the literature which indicates that digital skills influence the success of digital solutions’ use (Rosen & Leone, 2022).
A major limitation of this study lies in one cluster of the search terms: The terms ‘ICF’, ‘function’ or ‘functioning’ were used to emphasise studies with ICF as a common language and holistic view (Leonardi et al., 2022). Yet, to avoid selection bias, ICF was not defined among the eligibility criteria. As a coincidence, the term ‘function’ is related to design (Andersson et al., 2021; Shorten et al., 2015; Swallow et al., 2016) and further, a ‘function’ or ‘functioning’ of professionals, teams and organisations as service providers were described (Darlow et al., 2015; Lempicki & Holland, 2018; Lucas et al., 2020; Metzelthin et al., 2013; Poss-Doering et al., 2020; Yang et al., 2017). Thus, the included studies may have used the terms for various purposes, while other records which did not use one of these three terms were not identified. However, the term ‘functioning’ was used in relation to service users in five of the 18 eligible studies, even if the identified digital solutions did not explicitly refer to applying the ICF framework (Byerly et al., 2021; Javadi et al., 2018; McGilton et al., 2011; Sabus et al., 2011; Saia et al., 2020).
This review did neither assess the quality nor the risk of bias of the included studies. Only the synthesis was reviewed by more than one author. Imprecision of the included reports may have limited the quality of the synthesis. Specifically, Lempicki & Holland (2018) did not clearly describe the aim of their work, while Lucas et al. (2020) differed in their description between abstract and text. The number of participants was not clearly described in some studies (Darlow et al., 2015; Javadi et al., 2018; Yang et al., 2017). The authors were contacted via email, but did not respond. The included reports had different aims, study designs, interventions and outcomes. However, this review did not aim to identify the intended outcomes of the reports, but for identifying the use of digital solutions as part of their interventions or outcomes, as well as the participation of service users in these studies.
To conclude, the heterogeneity of the selected studies reflects lack of coherence in the use of digital solutions and clear conclusions cannot be drawn. Some of the identified digital solutions facilitate an active participation of service users in interprofessional collaborative learning, while some facilitate participation indirectly, with the service users being simulated or involved at a different moment. In educational settings, service users were simulated. The engagement of self-care groups in the education of service providers may be a relevant resource to interprofessional collaborative learning. Several types of digital solutions were identified that enabled students to engage in interprofessional collaborative learning, but neither digital assessments tools nor games were used. Findings from this review indicate that digital solutions are appropriate for being used and implemented in interprofessional collaborative learning, and future research could evaluate their usability. Further review of the literature may reveal recent developments and explore the influence of COVID-19 on the use of digital solutions, especially in educational settings. Directive roles may be needed that take the lead in facilitating the process of interprofessional collaborative learning. Lowor middle-income countries may need specific facilitation in using digital solutions.