Redefining Social Support: The Effect of Digital Technologies on the Social Support of Older Workers. A Scoping Review

Redefining Social Support: The Effect of Digital Technologies on the Social Support of Older Workers. 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A Scoping Review Cristina Maria Tofan, Anna Ševčíková, Nilufer Korkmaz Yaylagul, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5547499/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Jan, 2026 Read the published version in BMC Public Health → Version 1 posted 11 You are reading this latest preprint version Abstract Introduction: The rapid digitalisation of workplaces has created challenges and opportunities for older workers. This scoping review examines how digital technologies impact social support for older workers, focusing on emotional, informational, and instrumental support within professional environments. Social support is critical for enhancing well-being and sustaining productivity, especially in ageing workforces, yet the effects of digitalisation on social support dynamics remain underexplored. Methods This review follows Joanna Briggs Institute and PRISMA-ScR guidelines for a scoping review. A comprehensive search strategy was employed across databases like ERIH, Web of Science, Scopus, and PubMed from anytime to 2023 to identify peer-reviewed studies involving digital technologies used by older workers, generally considered as workers aged 50 years or older. Covidence software facilitated the screening of over 5000 scientific papers, study selection, and data extraction, and the Mixed Methods Appraisal Tool (MMAT) assessed quality. Data synthesis encompassed descriptive statistics and narrative analysis. Results Out of the 43 selected studies, findings indicate that digital technologies facilitate multiple types of social support. Remote work technology, messaging apps, and telemedicine enhance implicit and explicit social support, such as emotional connections and informational exchanges. However, digitalisation also introduces challenges, with some older workers experiencing isolation and technostress, highlighting the need for targeted digital literacy support. Discussion The findings of this scoping review highlight the dual impact of digital technologieson social support for older workers. While technologies like remote work platforms and messaging apps facilitate emotional connections and information sharing, they can also lead to technostress or even isolate older workers. Implementing tailored digital literacy programs and providing sustained managerial support are essential to help older employees effectively navigate these technologies, thereby enhancing their well-being and productivity in the workplace. digitalisation digital technologies social support older workers health Figures Figure 1 Figure 2 Background The world is witnessing multiple transitions. While the population and workforce are ageing rapidly, particularly in the Organization for Economic Cooperation and Development (OECD) countries [ 1 ], the accelerated integration rate of digital technologies into businesses is fundamentally transforming working life [ 2 ]. Extending working lives is increasingly being encouraged by national governments and European and international organizations such as the European Union (EU), OECD, the World Health Organization (WHO), and the United Nations (UN), not only for the sake of social security systems and working life but especially for healthy and active ageing [ 1 , 3 – 5 ]. This draws attention to the sustainability of working life, where social support is key in retaining older workers [ 6 , 7 ], specifically for their sustained health and well-being. In this study, older workers are defined as people over the age of 50 [ 8 ]due to age-related declines in physical functioning and longer recovery times [ 9 ]. Furthermore, people over 50 are likely to experience ageism at work, especially when trying to re-enter the labour market [6, 10Even so, we are aware that age cut-off points are a multi-perspective issue influenced by psychological perception, social norms, and economical reasoning [ 10 ]. argue that there is no universal accepted age that defines an "older worker". Reported cut-off points vary greatly depending on the type of occupation ranging between 28 (....) to 75 (....) years old, with an average of 52.4 years c Social support is commonly conceptualized in two forms: implicit and explicit. Implicit support refers to the reassurance derived from the mere presence or awareness of close others, without disclosing personal problems, whereas explicit support involves actively engaging one’s social network to share and discuss stressful experiences (- [ 7 , 11 ] ). Regardless of this distinction, previous research consistently identifies social support as a critical factor in sustaining a healthy working life across all age groups. [ 12 ]. However, as technological advancements reshape society, these changes also redefine the environment of work, opening new avenues for supporting an ageing workforce. In an increasingly digitised work environment, and with a growing ageing workforce, it is crucial to understand how digital technology (e.g., web-based platforms, smartphone, computers) impacts older workers’ general well-being and their ability to stay in the workforce. At the same time, the concept of social support itself is not straightforwardly defined, often used as an umbrella term referring to how relationships foster well-being, self-esteem, and other types of health indicators [ 13 ]. For example, Cobb’s [ 14 ] view is that social support provides information on how someone is cared for and acts as a defence mechanism against the impact of stress on health. He argues that social support is an important ally for health and reduces the time needed to manage stress. Lakey and Cohen [ 15 ] introduced three influential theoretical perspectives on social support: the stress and coping approach, the social constructionist approach, and the relationship approach. The stress and coping perspective suggest that social support enhances well-being by buffering individuals against the detrimental impacts of stress. In contrast, the social constructionist viewpoint argues that support enhances well-being by fostering self-esteem and self-regulation, irrespective of the presence of stress. The relational perspective proposes that the health outcomes of social support cannot be disentangled from the relational dynamics that often accompany support, including companionship, intimacy, and low social conflict. Finally, these perspectives highlight different mechanisms that can explain the connection between social support and health. According to LaMeres [ 16 ], digital technologies are used for data manipulation, storage, transmission, and processing in digital format, all aimed at enhancing quality of life (e.g., web-based platforms, smartphones, computers, digital cameras, digital videos/audios, etc.). These technologies are increasinly recognised as offering a new form of social support, although no clear definitions exist for this type due to the diversity of technologies involved. In this respect,, digital technologies have been examined as vehicles for providing new form of social support. (i.e., online social support), and evidence suggests that they influence health outcomes for older adults in similar ways to traditional forms of support [ 17 ] through companionship, coordination, maintaining ties, and casual conversations. However, digital technologies also present challenges. Both negative and positive effects are observed for older workers, and research does not always differentiate between effects for older adults and older workers. For example, Nimrod [ 18 ] describes technostress because of interactions with information and communication technology (ICT), which can threaten older adult’s well-being. Alcover et al.[ 19 ] argue that digitalisation (i.e., Artificial Intelligence (AI), robotics, automation) increases job insecurity or negatively affects older workers’ wellbeing, as they often lack ICT skills or need more time to solve tasks involving ICT compared to younger workers. Finally, other research results indicate that social support helps older adults learn to use digital technologies (i.e., tablet computers) [ 20 ]. Nick et al. [ 21 ] propose measuring online social support, categorising it based on its functional roles and purposes. They identify four types of online social support from previous theory and research: esteem/emotional support, social companionship, informational support, and instrumental support. Esteem/emotional support involves conveying acceptance, intimacy, care, liking, respect, and similar emotions through verbal and nonverbal cues. Social companionship support fosters a sense of belonging through actions that express inclusiveness or involve spending time together. Informational support encompasses sharing advice, feedback, knowledge, and resources. Instrumental support refers to the provision of practical assistance, including financial assistance, material help, task assistance, and taking on responsibilities. Current theoretical frameworks of online social support build on previous influential perspectives, as many digital technologies now provide social support. For example, AI-based applications (apps) can assist older adults in their daily lives, for instance, by tracking and monitoring health indicators and cognitive functioning [ 22 ]. Early research on social support in online environments reveals mixed effects [ 23 ]. Findings suggest that social support via email and online chat is critical for health indicators, but social conditions influence media choice, and individuals continually assess the appropriateness of the social context. Francis et al. [ 24 ] uncovered in their qualitative analysis that coping with technical issues from regular ICT use also provides opportunities for both online and traditional social support. Mendel et al.[ 25 ], through qualitative analysis, also highlight the mixed effects of the interaction between social support and digital technologies. While online social support related to fraud and phishing information may increase safety risks for older adults, mobile tools can also be used to raise awareness, encourage proactive behaviour, and foster learning to manage mobile safety challenges. Similarly, Marston and Musselwhite [ 26 ] advocate for the generally positive effects of technological tools in improving older people`s lives, while also identifying social barriers associated with learning to use such tools. Utz and Breuer [ 27 ] tested social network sites for providing social support and enhancing well-being. They found that those using social networks reported more online social support than those not using them, with users seeking more advice online. Likewise, Thompson and Atkins's [ 28 ] found that technological tools facilitate the sharing of ideas, the creation of meaningful relationships, and the instantaneous sharing of information. With respect to an ageing workforce, Thompson and Mayhorn [ 29 ] argue that digital technologies can serve as online support mechanisms for older workers by addressing physical demands, mobility concerns, visual acuity, workplace safety, memory limitations, new networking opportunities, and reducing age-related cues that prompt discrimination. Digital technologies are humanised, meaning they can become sources of social support or, conversely, a lack thereof (e.g. older workers may feel that computers restrict them), or alternatively, rely on them for assistance at work). For instance, researchers describe technological tools assisting older workers maintaining productivity, compensating for motor strength through using computer-aided manufacturing or using robotics to alleviate cognitive and physical stress by assisting with precise steps. Thus, the belief in digital social support could be seen as a type of social support shaped by digital technologies. Moreover, social support is reinforced by social identity theory [ 30 ], and empirical research [ 31 ] indicates that both online and offline social support depend on group membership, which is particularly relevant for groups in the workplace who rely on mutual support, such as informal caregivers, as they benefit from shared experiences, resources, and a sense of belonging within their peer groups. Previous research has often focused on the potential risks and vulnerabilities that digitalisation poses to ageing workers [ 18 ] or explored its positive impact on similar concepts to social support like social capital [ 32 ]. However, there has been little effort to identify types of social support provided through digital technologies specifically for older workers. This scoping review therefore aims to address this gap by exploring how digital technologies used in the work environment affect social support for older workers and identify the types of online social support that arise. Through a comprehensive review of existing research, this scoping review seeks to understand the role of digital technology in enhancing social support for older workers by addressing the following questions: Which digital technologies are most used by older workers and their colleagues to stay connected? How are these digital technologies being used by older workers? Do these digital technologies facilitate and mediate online social support? And how is the use of digital technologies for accessing social support is linked to the health of older workers? By synthesizing these findings, this study seeks to provide a comprehensive analysis of how digitalisation can be used to support and enhance the well-being of older workers. Methodology This scoping review follows standard and recognised methodology for systematic reviews reporting by the Joanna Briggs Institute (JBI) [ 33 ] along with recommendations from Scoping Reviews checklists and the PRISMA extension for scoping reviews (PRISMA-ScR) flow diagram for new systematic reviews, which includes searches of databases and registers only [ 34 ]. We used Covidence software as a tool for managing references to facilitate title and abstract screening, to conduct full-text reviews and to support data extraction. Search strategy A three-phase approach was implemented for the search strategy. First, we identified and defined the main concepts of digital technologies, online social support, and older workers. We followed the definitions of digital technologies provided by LaMeres [ 16 ]. Online social support refers to the use of digital technologies such as social media, online forums (i.e. professional groups/communities), and messaging platforms to manage difficulties, challenges, or serious problems. We considered three types of online social support: emotional support (key terms: empathy, encouragement, validation, concern, affection); informational support (key terms: advice, guidance); instrumental support (key terms: assistance with resources, financial assistance, online help, technical and organisational support). Additionally, we also paid attention to the availability of implicit social support, such as perception of workers of getting along with fellow workers. Social support through digital technology can take diverse forms, such as social media, online platforms, virtual communities, telemedicine platforms, online helpline services (e.g. psychological online services, professional IT or administrative online services, health apps, monitorization apps), facilitating easier connections and communication across distances. Older workers are defined as individuals aged 50 years and above who are employed. Secondly, following the JBI methodology for scoping reviews PCC (Participants, Concepts, Context) Framework was established. Accordingly, participants (P) are studies involving workers aged 50 and above. The concept (C) is studies on the use of digital technologiesin the work leading to social support. Context (C) is studies conducted in all workplace contexts. PCC informed our inclusion criteria. The search was limited to studies published in English and peer-reviewed scientific articles using quantitative, qualitative, or mixed methods, with no time constraints. The exclusion criteria were defined as studies not concerning working individuals or those not associated with work, studies using analogue technology (i.e., non-digital media such as analogue phone, analogue fax machine), non-English articles, theoretical papers, books, book chapters, reviews, systematic reviews, reports, protocols, and non-peer-reviewed studies (Table 1 ). Table 1 Inclusion and exclusion criteria PCC Framework Inclusion Exclusion Participants Studies involving workers aged 50 and above Non-working individuals or involving only individuals younger than 50 Concept Studies on the use of digital technologies in the workplace leading to social support Studies on analogue technology Context Studies conducted in all workplace contexts and in all countries English language articles Quantitative, qualitative, and mixed methods. Peer-reviewed scientific articles No time constraint regarding publication year Studies not associated with employment Non-English articles Other study types (theoretical papers, books, book chapters, reviews, systematic reviews, reports, protocols) Non-peer reviewed studies Finally, search terms were identified based on an initial literature review regarding our main concepts, namely digital technologies, online social support, and older workers. A single syntax search was designed for all databases. Terms were identified as “social support” OR ”social assistance” OR ”emotional support” OR ”social aid” OR ”social advice” OR ”social guidance” OR ”instrumental support” OR ”information support” OR ”social help” OR ”financial assistance” OR ”online*” OR ”technical support” OR ”organisational support” OR ”affect* support”) AND (”digital*” OR ”platform*” OR ”apps*” OR ”tech*” OR ”social media” OR ”chat” OR ”online*” OR ”telemedicine” OR ”cyber” OR ”virtual” OR ”computerized” OR ”computerised” OR ”electronic” OR ”ICT”) AND (”old* work*” OR ”old* employee*” OR ”old* profession*” OR ”elder work*” OR ”aging work*” OR ”ageing work*” OR ”old* workforce” OR ”aged work*” OR ”senior work*”. Searches were undertaken in the databases ERIH, Web of Science, Scopus, PubMed, PsycINFO, Proquest in 04 May 2023 by three reviewers CT, MAM, DG. The search results were uploaded into Covidence. Study selection and data extraction All studies identified through database searching were retrieved and then imported and stored in Covidence. Duplicates were automatically removed using Covidence’s build-in feature. The titles and abstracts of the identified studies were double screened by 12 reviewers to determine if they met the inclusion criteria. The full texts of eligible studies were then retrieved and assessed independently by two reviewers based on our main research questions and the inclusion and exclusion criteria. Any disagreements were resolved through discussion or with the intervention of a third reviewer. In the data extraction phase, 11 reviewers were involved. Two independent reviewers extracted the relevant information from the selected studies into the data extraction chart that we created in Covidence. Any disagreements between reviewers were resolved through discussion and validated by JS and CMT. The data chart included the following items: bibliographical reference, study location, data collection, information about invited and actual participants in the study, age used in the analysis or results of the study, information about whether the participants included both young and older people, and both older adults and workers, gender, population, social support, type of social support, the digital technologies used and type of digital technologies. Additionally, we extracted data about main theories and instruments used in the studies. Extracted data were exported to Microsoft Excel, analysed and presented using descriptive statistics, with a narrative summary presented below. Quality assessment All the included studies were critically appraised for their methodological quality using the Mixed Methods Appraisal Tool (MMAT) Version 2018, developed by Hong et al. [ 35 ]. The MMAT provides comprehensive guidelines for assessing quality across five categories of study designs, including qualitative studies, randomized controlled trials, nonrandomized studies, quantitative descriptive studies, and mixed methods studies). The tool consists of two parts: a checklist with two initial screening questions to confirm the paper is an empirical study (i.e., the clarity of research questions and feasibility of a study to answer them), followed by five criteria for each study design category. The second part provides detailed explanations for each criterion to guide the assessment process. Two reviewers independently appraised each study to minimize bias and ensure reliability. Discrepancies between reviewers were resolved through discussion to reach a consensus. For each study, the reviewers completed assessments that included two initial screening questions (“Yes” = 1 or “No” = 0) and then assessed a set of five criteria specific (“Yes”=1 or “No”=0) to the study design, as outlined by the MMAT. These criteria assess the appropriateness of the methodology, the adequacy of data collection methods, the relevance of the measurements to the research questions, and the coherence between data sources and analysis methods. Finally, for this review, we calculated the percentage of "Yes" responses for each study to provide an overview of the methodological quality. No studies were excluded based on this assessment. This quality percentage score was calculated by dividing the number of "Yes" answers by the number of applicable criteria and multiplying the result by 100. These quality percentage scores reflect the proportion of applicable MMAT criteria that each study met, indicating the level of methodological rigor according to the tool's framework. Next, the quality percentage scores were averaged for the two initial screening questions and then for each study design to obtain mean quality scores. Studies with scores below 50% were classified as low quality, those between 50% and 79% as moderate quality, and those at or above 80% as high quality. This quantitative measure of quality will help discuss the reliability and validity of the findings from these studies within the broader context of our review. Results Selected Studies The initial database search identified 5,213 studies. After removing duplicates, 4,730 were screened for eligibility, with 378 retrieved for full-text review. Of these, 43 met our pre-established inclusion and exclusion criteria and were selected for data extraction. Studies excluded during the process are detailed in the PRISMA flow-chart (Fig. 1 ). Qualitative assessment Overall, 81% of studies clearly stated research questions and collected appropriate data to answer them. The sample included 13 quantitative non-randomized studies of moderate quality (mean score: 66%), 9 quantitative descriptive studies of moderate quality (mean score: 50%), 2 randomized controlled trials bordering low to moderate quality (mean score: 40%), 9 qualitative studies of moderate quality (mean score: 78%), and 10 high quality mixed-method studies (mean quality: 80%). The lower quality of the quantitative descriptive studies was partly due to their frequent failure to report nonresponses or address the higher risk of nonresponse ( see Supplemental material_Quality assessment ). Characteristics of included studies Authors and publishing and collection of data years. Of the 43 selected studies, the earliest two were published in 1998 [ 36 ] and in 2000 [ 37 ]. All others were published between 2016 and 2023. Of these studies, three used data from the year 2000 or earlier, none had data collected between 2001 and 2014, 12 were based on data collected between 2015 and 2019, and 21 studies used data collected in 2020 or later (in three of these studies, data were collected twice, once in each of the latter two periods). In 11 studies, the data collection year was not stated (see Table 2 ). Participants . Regarding the number of participants invited, 19 papers did not report this information, while the remaining studies provided either precise or approximate numbers and described the invitation process. The number of participants ranged from 8 to over 14,000, depending on whether the study was qualitative, quantitative, or mixed methods. Finally, in terms of follow-up studies, only 8 studies included follow-up assessments, with participant numbers ranging from 12 to over 600, depending on the study design [ 36 , 38 – 44 ] see Table 2 ). Age categories used in the analysis or results of the study . Out of the 43 selected studies, 14 used age ranges (e.g., 19–63, 40–65), 13 used mean age (e.g., 42.1), and 18 used age categories (e.g., 18–25, 26–40) in the analysis. When assessing whether studies included both younger and older workers, our findings indicate that 34 studies included both, while 8 papers focussed exclusively on older workers. In one paper the age range was not stated [ 45 ] (see Table 2 ). Type of study. Regarding the type of study, 10 studies used mixed methods, 10 studies used qualitative methods, and 28 used quantitative methods (see Table 2 ). Type of population . Study populations include workers from various sectors such as public institutions, manufacturing, health care, academia, and other employment sectors. 17 studies included both older adults and older workers, while the remaining studies either included the general population or focussed on one specific group of workers (see Table 2 ). Gender. 21 studies analysed both men and women, two studies only women [ 36 , 40 ] and one also included a category for non-binary [ 46 ]. 4 studies did not report gender in their results [ 47 – 50 ] (see Table 2 ). Social support (SS). In 19 studies, SS is explicitly defined, while in the remaining 24 studies, it is implicit, i.e., SS could be inferred from one or more outcome variables. For instance, asking whether employees got on with fellow workers [ 51 ] or shared knowledge with people outside the company during the lockdown [ 52 ]. The source of support (e.g. from colleagues, supervisors, etc.) also varies across the studies (see Table 2 ). Digital technologies (DT). DT or technologies examined in the selected studies ranged from data entry work and teleworking to app-based interventions and ICT tools. In 20 studies, the DT is explicitly stated as part of the work or intervention, in 19 studies, its use is inferred, such as through remote work or hybrid working setups, while in the remaining 4 studies studied DT both explicitly and implicitly. For instance, Al Shamari [ 53 ] studied the experience with e-learning (an explicit DT) among Saudi Ministry of Health trainers and training coordinators who were forced to work from home (an implicit DT) during COVID-19 (see Table 2 ). Data collection method . All studies mention a method of data collection, which included questionnaires, surveys, interviews, focus groups, or combinations of these methods. The specific data collection method employed is described for each of the 43 studies (see Table 2 ). Countries. Across the 42 studies that disclosed location, 77 countries were represented [ 54 ]. The majority of research was conducted in European countries (68 instances), followed by countries in Asian/Oceania (8) and North America (1). No relevant studies were identified from South America or Africa. Italy had the highest representation, appearing in seven studies, followed by The Netherlands and Austria, with 5 each (see Fig. 2 and Supplemental material_Countries). Table 2 Selection and description of studies (N = 43) for the association between digital technologies and social support specific to older workers. Author(s) Year of data collection Data collection method N (invited / participants/follow-ups Age used in the analysis / results* both young & older workers both older adults & workers Gender** Population Social support (SS) Type of SS Digital technologies (DT) Type of DT Aborg et al. (1998) 1991, 1992 Online survey and in-depth interviews 153/22/17 AR: 19–63 Yes Yes F public institution workers SS from colleagues and supervisors Explicit Data entry type of work Explicit Carayon and Karsh (2000) 1994/1991-92. Survey, semi-structured interviews Agency A 149/47/NA Agency B 191/122/NA MAge = 42.1; SD = 10 Yes Yes T Workers in public institution SS from colleagues and supervisors Explicit Image and non-image users Implicit Meyers and Bagnall (2016) NS Semi-structured interview NS/10/NA AR: 45–55 No No F, M Older workers Cognitive support Implicit Online learning (e.g., the use of technology, hypermedia, independent learning) Explicit Mohadis et al. (2016) NS Interview NS/10/NA AR: 50–64 No No F, M Workers Social comparison and competition persuasive principles as SS Implicit FitSenior application Explicit Verbrugghe et al. (2016) 2015 Survey 22084/790/NA AC: Up to 54, 55+ Yes No NS Workers in the private sector SS for sustainable employability Implicit Development of Healthy Workplaces for all Ages e-guide Implicit Arvola (2017) 2016 Survey NS/107/NA AC: under 50, 50+ Yes No T Workers Getting on with fellow-workers and social networks implicit Teleworking and the extent that ICT devices and applications were used for work (PC, laptop, tablet PC, smart phone, MS Outlook, MS Office, social networks). Explicit Hauk et al. (2019) NS Online survey NS/1216/T2 = 840/T3 = 631 AR: 17–75 Yes Yes NS Workers Instrumental SS Explicit ICT tools Explicit Calderón-Gómez et al. (2020) 2016 Survey 3000/2800/NA AC: 16–34, 35–54, 55–64 Yes Yes F, M internet users Online communication with colleagues Implicit Online tools linked to the mobile phone and/or computer, including messaging services, social media, video conference apps, SMS, and email. Explicit Chandra et al. (2020) NS Online survey 700/163/NA MAge = 37.64, SD = 6.76. Yes No F, M service sector workers Technological spatial intrusion and usefulness of ICT for workers Explicit ICT use Implicit De Leeuw et al. (2020) 2017 Semi-structured interview NS/10/NA AR: 52–63 No No F, M Workers Health information implicit Health information technology; electronic health records and eHealth devices Explicit Handley and Outer (2020) NS Interview NS/24/NA AR: 48–58; MAge = 52.5 No Yes T Knowledge workers Lack of mentoring and acknowledgment at work through organisational decisions Implicit Workers from the IT software sector, film industry, and technology entrepreneurs. Implicit Middleton et al. (2020) 2019–2020 Text messages 464/291/NA AC: 17–30, 31–40, 41–50, 51–60, 61–70 Yes No F, M, T Workers Informational SS Implicit @Work (app intervention through text messages) Explicit Schmied et al. (2020) 2019 Semi-structured interview NS/17/12 (incl 2 new recruits) MAge Employed = 60; Just retired = 65 Yes Yes T Newly retired workers Emotional and social support through digital coach Implicit Possibility of working from home and the implementation of a virtual health care coach (Sanbot Elf robot and Sola avatar). Implicit Habánik et al. (2021) 2020–2021 Survey Survey 1:NS/302/NA. Survey 2:NS/284/NA AC: 18–25, 26–35, 36–45, 46–55, 56–65 Yes No T Workers Social contact with co-workers and instrumental SS for remote work Implicit Remote work, ICT use for work Both implicit and explicit Lai et al. (2021) 2017–2018 Survey 265/167/NA AC: 21–30, 31–40, 41–50 Yes No F, M Workers Employee agility and IT competency Implicit Enterprise Social Media, knowledge management systems, intranets, groupware, and bulletin board systems. Explicit Ma et al. (2021) 2018 Online survey 1500/1020/NA AC: 55–60, 61–65, 66–70, > 70 No No T Workers Information and emotional support through social media at work explicit Social media usage at work Explicit Molino et al. (2021) NS Focus-group and questionnaire Qual: NS/14/NA Quant: NS/263/NA Qual: NS. Quant: Mage = 41.44; SD = 12.01 Yes No T Manufacturing workers Supervisor SS Explicit Industry 4.0 Implicit Rantanen, et al. (2021) 2019 Online survey 1128/162/NA MAge = 43 Yes No T home care workers Informational and instrumental SS through care robots at work Explicit Care robots in-home care tasks Explicit Santini et al. (2021) 2019 / 2021 Focus-group, telephone interview NS/60/27 MAge: Austrian = 60.2; Italian = 60; Dutch = 65.5 Yes Yes F, M Workers and Retirees Social relationship improvement through digital technology Explicit Virtual coach Explicit Sederevičiūtė-Pačiauskienė et al. (2021) 2020 in-depth interviews NS/37/NA AR: 19–59 Yes No T Teachers Supportive collaboration implicit Online teaching Implicit Tonnessen et al. (2021) 2020 Survey 282/237/NA AC: 30–40, 40–50, 50–60 Yes No F, M Workers Digital knowledge sharing implicit Teleworking Implicit Wrede et al. (2021) NS Survey 1319/710/NA MAge = 44.57; SD = 12.69 Yes No F, M, non-binary Workers SS from colleagues Explicit E-governement services Implicit Bartkowiak et al. (2022) 2020 / 2021 in-depth interview NS/21/18 Wave 1 AR: 31–67 Mage = 52.04; Wave 2 AR: 35–67 MAge = 58.56 Yes No T Workers Socialization and social contact Implicit Teleworking Implicit Belostecinic et al. 2022 2021 Online survey 450/377/NA AC: 18–25, 26–40, 41–55, 55+ Yes Yes F, M Workers Employers' informational and instrumental SS Explicit Teleworking Implicit Busch et al. 2022 NS Survey 42/42/NS AR: 32–66; M = 52 Yes Yes T Small business workers SS from partners Explicit Blended coaching format (combined face-to-face with tele-sessions, an online diary, and online courses) Both implicit and explicit Danieli et al. (2022) 2021 Interview 60, remained 45. MAge = 55.58; SD = 5.08 AR / AC NS No T Workers MHealth AI conversational agent at work Explicit TEO, Therapy Empowerment Opportunity, a mobile personal health care agent with conversational AI, mHealth app. Explicit De Carlo et al. (2022) 2020–2021 Survey NS/295/185 MAge = 37.6; SD: 12.3 Yes No F, M Workers Colleagues and supervisor Interpersonal support Explicit Teleworking Implicit Kim et al. (2022) 2018–2019 Survey and app indicators 149/50/46 AR: 40–65 years, ET group (MAge = 47.79, SD = 7.01); ST group (MAge = 53,27, SD = 7.32) Yes No F migrant workers SS from team leader through digital technologies Implicit Mobile health app based on monitoring walking Participants used a Fitbit smart watch. Explicit Mazzuto et al. (2022) NS Not described NS/8/NA "younger" or "older" workers (born before 1980 or after) Yes Yes NS Academic workers Training nd work support implicit Digital technologieswere used at work, and the participants in the education learned how to handle new techonology and safety at work Explicit Memon et al. (2022) 2020 semi-structured interview 41/41/NA AC: 21–30, 31–40, 41+ Yes No F, M, Workers Lack of collaboration and coordination from the supervisor Implicit Teleworking Implicit Ober (2022) 2022 Survey 6000/402/NA AC: 18–24, 25–34, 35–44, 45–54, 55+. ANALYSIS: 18–24, 25–34, 35+ Yes No F, M, T Workers Motivation to use platforms, open innovation networks, reluctance to share knowledge, and insufficient support from top management Implicit Open innovation platforms networks Explicit Scheibe et al. (2022) 2021 Survey 6541/1715/NA AC: 18–25, 26–35, 36–45, 46–55, 56+ Yes No F, M Workers Social integration Implicit Teleworking Implicit Taboroši et al. (2022) NS Survey NS/313/NA AC: up to 35, 36+ Yes No F, M Workers Social networks for communication Implicit Social media usage in general Explicit Al Shamari (2022) 2021 Online survey 498/262/NA AR: 26–76 (Cohorts1946-64, 1965-80, 1981–1996) Yes Yes F, M, T Workers Lack of relational, emotional, informational, or instrumental SS within training setting at work Explicit E-learning experience, working from home Both implicit and explicit Martínez-Pérez et al. (2023) Quant: 2018 Qual: 2020 Survey and focus-group NS/504/NS AR: 21–64. Mage = 37.3 Yes No F, M, Workers Lack of SS from work and lack of instrumental SS Implicit General ICT Both implicit and explicit Ferreira and Gomes (2023) 2020 Survey 24144/14298/NA AC: 66 Yes No NS Remote workers Perceived organisational support Explicit Teleworking Implicit Lopes et al. (2023) 2020 Survey NS/573/NA MAge = 46.8, SD = 8.10 Yes No T Workers Perceived benefits of training (e.g. better relationship with citizens, peers, and chiefs) Implicit Participants in digital training field group Implicit Oksanen et al. (2023) 2020–2022 Survey 4069/1152/656 AR: 20–66 Yes No F, M Workers Supportive working environment and SS from colleagues and supervisors Explicit Teleworking Implicit Petcu et al. (2023) 2021 Survey NS/440/NA AC: up to 25, 26–35, 36–50, 50+ Yes No T Workers Relational communication through online tools between co-workers implicit Teleworking Implicit Raišienė et al. (2023) NS Online survey 202/202/NA AC: 18–24, 25–34, 35–48, 49–64 Yes No F, M, T Workers Management support Explicit Teleworking Implicit Santini et al. (2023) 2021 Survey and online focus-group 91/62/NA AR: 55+ No No T Workers before and after retirement Coach support through digital app Explicit Digital Coaching Explicit Schneider and Bousbiat (2023) 2020 Survey NS/34/NA AC: 55–58, 59–62, 63 − 6;. MAge = 61 No Yes T Workers who have retired or are about to retire Informational support Explicit Smartphone and tablet usage, and the use of a robot in their daily life Explicit Zin et al. 2023 2022 Survey 170/170/NA AC: 56–65, 66–75, 76–85, 86–95 No Yes F, M older adults Informational support Implicit smart health watch - wrist-worn wearable technologies Explicit Notes: NA = not applicable; NS = not stated; Quant = Quantitative; Qual = Qualitative; SS = social support; DT = digital technologies; ICT = Information and Communications Technology. *Age is reported: AC = age categories, AR = age ranges or Mage = mean age and SD = standard deviations; **We considered older workers from the age of 45 when ”older workers” was mentioned in the study's title (e.g. Meyers and Bagnall [ 55 ], Handley and Den Outer [ 56 ]; ***Gender is reported as categories used in the analysis or results: F = female, M = male, T = total F + M. Conceptual map of social support for older workers and impact on health Social support is a multifaceted concept encompassing various forms of assistance that individuals may receive from others, particularly within the workplace. It is often mediated through the use of digital technologies or provided in the context of remote work. Evidence from prior studies highlights diverse perspectives on how social support is facilitated and how it influences health outcomes [ 15 , 21 ]. The literature spans multiple health domains, including physical health (e.g., healthy ageing and healthy activities; [ 43 , 57 ], mental health (e.g., detachment; Busch et al, 2022; exhaustion; [ 41 , 58 ]), well-being [ 59 ]), social health (44, 60) and organizational outcomes (e.g., job satisfaction; 37) Furthermore, we have identified that different studies cover one or more of the four types of online support proposed by Nick et al[ 21 ], namely esteem/emotional support, social companionship, informational support, and instrumental support. For example, Schmied et al. [ 44 ] examined the esteem/emotional support type through the potential use of a digital coach for employees nearing retirement and retirees. Their findings indicate that individuals approaching retirement feared losing their workplace social network, and the coach provided a way to stay connected to alternative networks, thereby influencing health outcomes Similarly, Ma et al. [ 61 ] found that the direct use of social media at work enhanced both information and emotional support, as well as improved older employees’ self-efficacy at work. Several studies illustrate instrumental support, demonstrating how supervisors or chiefs use digital technologies to support older workers in tangible ways with practical aid such as task assistance and resource provision or how they obtain this support through training [ 48 , 49 , 53 , 54 , 62 , 63 , 64 , 65 ]. For example, Rantanenet al. [ 66 ] highlighted the role of care robots in assisting older home care workers. Employees age increases enthusiasm, but reduces self-efficacy. Lai et al. [ 67 ] highlighted employees’ agility in collaborative work is enhanced through IT competency development, enterprise social media, and knowledge management systems. Other resourceful instrumental support is health information [ 45 , 68 ] and support for sustainable employability [ 50 ]. Similarly, informational support encompasses sharing knowledge, advice, or guidance [ 40 , 69 , 70 , 71 ] with authors who discuss training and instructional content. Relational support seems to be highlighted directly through supervisor and colleagues support [ 39 , 40 , 51 , 72 , 58 ] and communication through digital technologies[ 73 , 59 ]. Another type, social companionship, reflects a sense of belonging and collaboration within the working setting [ 41 , 47 ]. For example, Scheibe et al. [ 60 ] and Calderón-Gómez et al. [ 74 ] examined teamwork and social relationships at work and other highlighting the relational nature of support [ 38 , 75 ] [ 37 , 42 ] [ 52 , 76 , 72 , 58 , 57 ]. Scheibe et al. [ 60 ] report more resilience through feeling more socially integrated in comparison to the younger employees, while Calderón-Gómez et al.report increased communicative activities although very few older workers. Santini et al. [ 43 ] emphasize relational support through social relationship improvement by using digital technologies and social contact with co-workers. The AgeWell digital coach was found to improve participants’ level of self-efficacy, mental well-being, and physical activity when supplemented with human coach support. However, once the human coach stopped their involvement, this positive effects on self-efficacy and mental well-being disappeared. However, insufficient social support may also lead to negative consequences, as attested by several studies [ 38 , 53 , 56 , 63 ]. For instance, Memon et al. [ 77 ] found that a lack of collaboration and social interaction in remote work environments led to isolation and detachment, adversely affecting older workers’ mental health and overall well-being. Finally, indirect measures of social support are found in Meyers and Bagnall [ 55 ] (e.g. cognitive support; 2017) and Mohadis et al. [ 78 ] (e.g., social comparison and competition persuasive principles as SS; 2016). Digital technologies enhancing social support for older workers Three types of digital technologies enhance social support for older workers. First of all, there are digital technologies that explicitly aim at enhancing communication, collaboration [ 36 , 37 , 50 , 73 ] and health management [ 48 ]. For example, messaging services, social media, and video conferencing tools are used to maintain communication and coordination among colleagues, enhancing both emotional and informational support [ 54 , 74 , 61 ]. Additionally, online learning platforms and applications like hypermedia-based training modules provide cognitive support for older workers by facilitating independent learning and skill development [ 49 , 55 ]. Other explicit digital technologies include ICT-driven health management systems, such as electronic health records and mobile health apps like the FitSenior application, which promote health-related social comparison and competition, offering persuasive encouragement through digital channels [ 45 , 78 , 68 ]. Secondly, teleworking setups, enabled by a range of ICT devices such as laptops, smartphones, and collaborative software [ 51 ], allow for continued collaboration and social interaction even when workers are remote [ 41 , 42 , 46 , 75 ]. Digital technologies like care robots used in healthcare settings also fall into this category, providing informational and instrumental support for older healthcare workers [ 66 ]. Teleworking is a common theme in the studies, with multiple reports indicating that remote work setups improve workers' social support networks through frequent interactions with colleagues over digital platforms [ 52 , 76 , 77 , 60 , 59 ]. Moreover, teleworking has been linked to increased employer-provided informational and instrumental support, enhancing older workers' sense of social connection and their ability to access resources [ 39 , 47 , 69 , 65 ]. Habanik et al, 2021; [ 40 , 67 , 72 ] or indicating less support for older workers [ 38 , 53 , 56 , 63 ]. Finally, blended formats that combine both face-to-face and digital interactions like coaching programs integrate digital platforms for mentoring, online diaries, and tele-sessions alongside traditional methods provide both emotional and instrumental support [ 44 , 64 ]. For example, blended coaching programs for small business workers have been shown to enhance partner support through tele-sessions and online diaries [ 58 ]. Additionally, mobile health apps, such as the AI-powered TEO mHealth app, offer continuous conversational support, further extending the range of digital technologies available to provide support through automation [ 43 , 45 , 70 , 71 ]. Another example is the use of digital coaching apps for retirees or workers transitioning out of the workforce, which provide emotional and informational support to facilitate smoother transitions [ 57 ]. Theories used in studies and shaping the association between digital technologies and social support In total, 20 studies used a theoretical foundation such as persuasive design [ 62 ], learning approaches [ 49 ], and systems approach frameworks [ 36 ]. Other studies used psychological theories with social capital [ 40 , 41 , 52 , 61 ] or social cognitive theory [ 40 , 51 , 53 ] or conservation of resources theory [ 39 , 58 ] or human capital theory [ 64 ] or stress theories and well-being [ 42 , 48 , 59 , 65 ], or the theory of planned behaviour [ 66 , 71 ] or behavioural change model (COM-B) [ 76 ]. Out of all, 8 studies combined theories and models, like the theory of acceptance and technology acceptance model [ 53 , 72 , 71 ], or applied models, such as Middleware’s model [ 54 ] or job-demands-resources (JD-R) model [ 41 , 47 , 72 , 59 ]. In 16 studies, the concepts used were resilience [ 60 , 59 ], self-efficacy and behavioural intention [ 51 , 66 ], spatial intrusion [ 54 ], narrative identities [ 56 ], open innovation [ 63 ], sustainable employability [ 50 ], information processing/communication [ 62 , 67 ], digital divide [ 74 ], work digitalisation [ 37 , 69 ] or social support [ 77 , 73 ]. Nine of the studies lacked a specific theoretical grounding [ 43 , 44 ] 573; [ 38 , 45 , 46 , 55 , 75 , 70 ]. Instruments used for measuring social support The results regarding social support for older employees' use of digital technology are measured with different types of instruments in the different studies, i.e. the design of the measuring instruments was different. Among the studies, 12 studies used interviews [ 38 , 42 – 45 , 55 , 68 , 56 , 72 , 75 , 77 , 57 ], and 30 studies used questions and questionnaires to measure social support for older workers' use of digital technology [ 36 – 41 , 45 – 54 , 74 , 62 , 67 , 61 , 66 , 69 , 63 , 73 , 64 , 59 , 65 , 57 , 70 , 71 ]. One study [ 60 ] measured frequent use of social support for digital technologies with the intention of measuring social support in older workers' use of digital technology. Instruments used for measuring the digital technologies The digital technology used by the older employees differed. However, not all studies measured the older employees' attitude, experience or frequency in using digital technology. In total, 20 studies used questions and questionnaires to measure the older employees' experiences and attitudes towards the digital technology [ 36 , 38 , 39 , 47 , 50 , 51 , 54 , 74 , 62 , 67 , 61 , 72 , 66 , 63 , 73 , 64 , 59 , 65 ,, 70 , 71 ]. There were six studies that conducted interviews with the older employees to investigate their experiences and attitudes towards the digital technology [ 37 , 38 , 42 – 44 , 77 ]. In six studies, measurements were made to investigate and estimate how often and for how long the older employees used the digital technology [ 37 , 40 , 52 , 55 , 77 , 75 ]. Discussion The scoping review analysed the role of digital technologies in providing social support to older workers, aiming to determine which technologies are most used and their impacts on social support and health and well-being. Notably, most of the studies we reviewed collected data in 2020 or later, coinciding with the COVID-19 pandemic and its aftermath. This timing likely influenced the findings: the pandemic’s rapid shift toward remote work and greater reliance on digital communication tools underscored the need for online forms of social support for employees. Our discussion reflects on the dual impacts of these digital technologies, both positive and negative, on older workers’ social support and health, and situates these findings within existing theoretical frameworks. Digital technologies shaping social support and health for older workers With the rise of digital technologies, the delivery of social support has evolved. Digital technologies like teleworking platforms, ICT systems, and mobile health apps, provide new avenues for offering social support. For instance, remote work technology facilitates relational support implicitly through digital knowledge-sharing, enabling workers to maintain professional relationships, exchange knowledge, and receive updates even when physically separated [ 52 ]. These digital technologies facilitate relational support, both formal and informal exchanges, addressing employees’ emotional and informational needs remotely [ 60 ]. Explicit forms of relational social support delivered via digital technologies include structured interventions like digital coaching or mobile health apps. Studies have shown that digital coaches, such as the AgeWell digital coach, can promote healthy ageing by enhancing physical activity, mental well-being, and socialization, providing direct support to participants [ 57 ]. Similarly, mobile health apps, like those studied by Kim et al. [ 40 ], deliver encouragement, motivation, and health advice through social-cognitive strategies, fostering a sense of community and promoting well-being. On the other hand, implicit digital technologies are equally significant. Scheibe et al. [ 60 ] examined how remote working environments can implicitly foster social integration and support through digital platforms. Workers used remote communication technologies to stay connected and share knowledge, even when such support was not explicitly structured as part of a digital intervention. Similarly, Martínez-Pérez et al. [ 38 ] studied the use of general ICT across various industries, highlighting how digital technologies—whether providing implicit and explicit instrumental support, or reflecting its absence—are integral to managing the social dynamics of remote and hybrid work settings, where workers may experience limited support from colleagues and supervisors. Middleton et al. [ 76 ] explored app-based interventions through the @Work program, where workers received informational support through text messages, illustrating how mobile technologies can offer targeted, real-time support. This study underscores the dual role of mobile-based tools in delivering both implicit support (through the tool itself) and explicit support (through messaging content). Other studies, such as Rantanen et al. [ 66 ], focus on more advanced digital technologies like care robots in home care tasks. These robots provide both informational and instrumental support, showing how technology is reshaping traditional forms of workplace support by integrating automation into day-to-day tasks. Similarly, Kim et al. [ 40 ] explored mobile health apps based on smart technology (e.g., Fitbits) for monitoring physical activity among migrant workers, where digital technologies provide both health-related and social support. Positive effects on social support Digital technologies have increasingly become essential in providing social support to older workers across different contexts and industries. The digital technologies used in these studies often range from basic communication platforms to more sophisticated technologies designed to offer esteem/emotional support, social companionship, informational support, and instrumental support [ 16 ], but can also provide a lack of social support. For instance, Aborg et al. [ 36 ] examined how workers in public institutions used digital technologies for data entry, where explicit social support came from colleagues and supervisors through the use of online surveys and in-depth interviews. This early study shows how even simple data entry work can be structured to foster support networks through digital means. Similarly, Carayon and Karsh [ 37 ] investigated image and non-image users in public institutions, where digital technologies facilitated explicit social support from colleagues and supervisors through both questionnaires and semi-structured interviews, reflecting how ICT tools could be used to support collaboration and communication. A more advanced example is Santini et al. [ 57 ], who explored the use of digital coaching apps to support workers both before and after retirement. This explicit form of social support, delivered via mobile apps, shows how digital interventions are tailored to meet the emotional and practical needs of workers transitioning out of the workforce. Likewise, Busch et al. [ 58 ] examined blended coaching formats (a mix of face-to-face and tele-sessions) for small business employees, where explicit social support from partners was enhanced through a combination of digital and traditional interactions. Acceptance of new technologies among older workers is closely linked to the social support they receive, both from colleagues and supervisors. Findings by Molino et al.[ 72 ] indicate that supervisor support and role clarity are critical in facilitating technology acceptance, which subsequently leads to higher work engagement. Conversely, a lack of organisational support structures limits the efficacy of teleworking for older employees, making it less sustainable for this group without targeted interventions [ 69 ]. Research also highlights the significant role of spousal and relational support outside of work, which is essential for maintaining work-life balance and mental health. Studies by Busch et al. [ 58 ] and Memon et al. [ 77 ] indicate that spousal support during periods of remote work enhances goal achievement and reduces stress, while social support from colleagues or family during digital interactions can help mitigate feelings of loneliness and detachment. Finally, digital technologies that encourage collaboration and communication, such as enterprise social media and knowledge management systems, are also widely used. Lai et al. [ 67 ] showed how these systems help workers enhance agility and IT competency, indirectly supporting social integration through increased collaboration. In summary, digital technologies in the workplace provide varying levels of social support, from explicit, well-structured interventions such as mobile apps and digital coaches to more implicit forms of support embedded in remote work and communication platforms. These digital technologies not only enhance social integration and informational support but also play a crucial role in emotional and instrumental support across different work environments [36,, 76 , 66 , 60 , 57 ]. Challenges and negative implications Despite these benefits, several studies reveal challenges. Older workers often face a digital divide, where their digital skill levels do not always align with job requirements, leading to feelings of isolation or exclusion. For instance, in teleworking environments, many older employees reported feelings of social deprivation and mental exhaustion, particularly when lacking peer or supervisory support [ 46 , 65 ]. Studies also noted that older employees working from home encountered reduced interaction with peers and supervisors, which can decrease job satisfaction and mental well-being [ 39 , 77 ]. Furthermore, teleworking and remote work setups can create a sense of isolation if not managed properly, with some workers reporting reduced collaboration and limited interaction with supervisors [ 77 ]. This detachment can lead to decreased social companionship, a critical component of social support, and can negatively impact employee morale and well-being. Nevertheless, the flexibility and connectivity afforded by digital technologies have the potential to greatly enhance support, particularly when combined with human interactions [ 44 , 58 ]. Many older workers express a need for additional training to navigate new digital platforms effectively. Findings by Mazzuto et al. [ 49 ] reveal a discrepancy in learning rates, indicating that older workers often require more times and support to adapt to evolving technological tools. This suggests that tailored training programs could play a crucial role in enhancing digital adaptability and sustaining employability among older workers. The literature also highlights divergent outcomes regarding the well-being of older workers. These outcomes appear to be shaped by several factors, such as presence or absence of organizational support (6, 47 Ferreira & Gomes (2023), the digital literacy level of older workers, the type of digital technologies employed (79) and the broader implementation. Accordingly, the impact of digital technologies on older workers is not unidimensional but multidimensional, encompassing social, organizational and individual layers. Limits of the Study Our study also has several limitations. First, the search was confined to English-language publications. This exclusion may limit the comprehensiveness and generalizability of our findings, as studies published in other languages could provide alternative perspectives or results. The exclusion of non-peer-reviewed sources represents an additional limitation, as grey literature may contain relevant data or studies with non-significant results that are not captured in the published record. Moreover, this review is predominantly based on research conducted in developed countries. The relationships identified may therefore be contingent upon specific contextual factors, e.g., cultural norms that differ in developing nations. Future research is thus needed to validate these findings across a broader range of geographical and economic settings. The studies included also reflect considerable variability in designs. However, the dominance of European contexts in the available literature may further limit the generalizability of the findings to other cultural and policy settings. In addition, some studies did not exclusively examine older workers but included broader working populations, which may have diluted age-specific insights. Finally, the absense of standardized instruments for measuring social support remains a significant gap, and addressing this issue should be considered priority for future research. Conclusion The article highlights the dualistic impact of digitalisation on social support for older workers, highliting both opportunities and challenges within modern workplaces. On the positive side, digital technologies enable older workers to receive various forms of social support (e.g., esteem/emotional support, social companionship, informational support, and instrumental support) through platforms that promote communication, such as teleworking, enterprise social media, and health-related apps. These technologies facilitate professional connections and provide mental health benefits, often fostering a sense of inclusion and continuous learning and are aligned with Nick and colleagues’ perspective [ 21 ] regarding types of online support. However, digitalisation also introduces challenges, especially for those with limited digital skills, potentially leading to social isolation, technostress, and a feeling of inadequacy in fast-paced digital environments. The reviewed studies highlight that, although digital technologies can bolster older workers' productivity and connectivity, the benefits are contingent on adequate training and organisational support. The research thus points to the need for targeted digital literacy programs and sustained managerial backing to mitigate negative impacts, ensuring that digitalisation enhances rather than hinders the well-being of older employees. Results also reflect the lens of Lakey and Cohen’s [ 15 ] three theoretical perspectives on social support. Regarding the stress and coping approach, results indicate that digital technologies such as teleworking platforms and communication apps provide implicit support, reducing the stress of isolation in remote work environments. However, older workers also report stress related to the use of technologies and a digital divide, implying that while these technologies can offer stress relief through connection, they can also introduce stress due to the necessity of digital skill adaptation. Tailored digital literacy programs could mitigate this stress, enabling these technologies to fulfil a more effective stress-buffering role. The constructionist approach aligns with the findings in the article that digital technologies provide emotional support and self-efficacy for older workers. For instance, apps that offer digital coaching or feedback boost a sense of autonomy and competence, enhancing well-being independent of stress levels. The development of skills and encouragement through technologies like mobile health apps also reinforces self-esteem, aiding workers in managing their roles effectively, even amid digital transitions. Finally, the relational approach is illustrated by the use of digital technologies such as enterprise social media, which foster relational support by promising communication and collaboration. Relationships formed or maintained through remote platforms enable emotional and informational exchanges that are essential for social companionship. However, insufficient interaction in remote settings can also leads to isolation, signalling the need to balance digital and in-person interactions to foster low-conflict, meaningful connections that enhance well-being. In conclusion, digital technologies are reshaping the landscape of social support by offering both implicit and explicit mechanisms for delivering emotional, informational, and instrumental support. When effectively integrated, these technologies enhance communication, collaboration, and social integration among older workers, thereby contributing to improved work experiences and overall well-being [ 36 , 61 , 60 ]. Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Competing interests The authors declare that the research was conducted without any commercial or financial relationships that could potentially create a conflict of interest. Acknowledgement of support The article was created as part of the CA21107 Work Inequalities in Later Life Redefined by Digitalisation (DIGI-net) project, which is supported by COST ACTION. Funding This work was partially supported through the actions within project CA 21107 Work Inequalities in Later Life Redefined by Digitalisation (DIGI-net) , supported by COST ACTION. Author Contribution Acknowledgment of author contribution: CMT and JS conceived and developed the protocol and concept for this review. DAG, AS, NKY, and MM provided feedback for the protocol. Writing the manuscript: CMT, AS, NKY, YG, HB, MM, GY, JS, KN, GK. Quality assessment: NKY, MM, CMT, JS, AS, YG, HB, GY, GK. CMT, AS, NKY, YG, HB, MM, GY, JS, KN, GK, DAG, and JRG undertook title and abstract screening, full-text screening, and full-text review. All authors extracted the data. CMT, JS, AS, NKY, YG, HB, MAM, GY, KN, and GK synthesized data. CMT led the drafting of the manuscript with input from JS, AS, NKY, YG, HB, MAM, GY, KN, JRG and GK. All authors edited and approved the final manuscript. Availability of data and materials Not applicable References OECD. 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19:08:28","extension":"html","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":270955,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-5547499/v1/fbc9c9d33a3326144595bdf6.html"},{"id":92542122,"identity":"5eba269b-109f-4516-af58-63fbd401a963","added_by":"auto","created_at":"2025-09-30 19:16:27","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":99079,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA flowchart for Digitalization and Social Support for Older Workers\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5547499/v1/98b61df2ef16eb9b504cd047.jpg"},{"id":92541924,"identity":"98a75970-fe72-45db-950c-45a900333803","added_by":"auto","created_at":"2025-09-30 19:08:28","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38337,"visible":true,"origin":"","legend":"\u003cp\u003eMap showing the countries where studies were conducted. The shading intensity corresponds to the frequency of studies in each country, ranging from 1 to 7, while the numbers in parentheses represents the range of appearances (e.g., only Italy appears in 7 studies).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5547499/v1/fc8c247c7d6478704450b5da.jpg"},{"id":100617519,"identity":"7990ef1c-6a2c-4927-890c-c5c32ec59058","added_by":"auto","created_at":"2026-01-19 17:54:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1770034,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5547499/v1/c65f1b07-ee56-4794-873a-8136b4a76b1c.pdf"},{"id":92541376,"identity":"b1aa2853-f2d3-4f0f-aa15-8fe134c46a61","added_by":"auto","created_at":"2025-09-30 19:00:27","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":128727,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalmaterialQualityassessment.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5547499/v1/050c0bdca73dd780020c74c8.xlsx"},{"id":92541374,"identity":"d78d1561-3849-43b6-b1c3-08bf542c7806","added_by":"auto","created_at":"2025-09-30 19:00:27","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16387,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalfileCountries.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5547499/v1/5a30f956fc273e6647590dc7.xlsx"},{"id":92541384,"identity":"b50dc1ee-ec2e-4c0e-b244-dca42b496a91","added_by":"auto","created_at":"2025-09-30 19:00:28","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":514195,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscripttrackchanges.docx","url":"https://assets-eu.researchsquare.com/files/rs-5547499/v1/da7fb5cc6120d4bc705a3fde.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Redefining Social Support: The Effect of Digital Technologies on the Social Support of Older Workers. A Scoping Review","fulltext":[{"header":"Background","content":"\u003cp\u003eThe world is witnessing multiple transitions. While the population and workforce are ageing rapidly, particularly in the Organization for Economic Cooperation and Development (OECD) countries [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], the accelerated integration rate of digital technologies into businesses is fundamentally transforming working life [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Extending working lives is increasingly being encouraged by national governments and European and international organizations such as the European Union (EU), OECD, the World Health Organization (WHO), and the United Nations (UN), not only for the sake of social security systems and working life but especially for healthy and active ageing [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This draws attention to the sustainability of working life, where social support is key in retaining older workers [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], specifically for their sustained health and well-being. In this study, older workers are defined as people over the age of 50 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]due to age-related declines in physical functioning and longer recovery times [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Furthermore, people over 50 are likely to experience ageism at work, especially when trying to re-enter the labour market [6, 10Even so, we are aware that age cut-off points are a multi-perspective issue influenced by psychological perception, social norms, and economical reasoning [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. argue that there is no universal accepted age that defines an \"older worker\". Reported cut-off points vary greatly depending on the type of occupation ranging between 28 (....) to 75 (....) years old, with an average of 52.4 years c\u003c/p\u003e\u003cp\u003eSocial support is commonly conceptualized in two forms: implicit and explicit. Implicit support refers to the reassurance derived from the mere presence or awareness of close others, without disclosing personal problems, whereas explicit support involves actively engaging one\u0026rsquo;s social network to share and discuss stressful experiences (- [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] ).\u003c/p\u003e\u003cp\u003eRegardless of this distinction, previous research consistently identifies social support as a critical factor in sustaining a healthy working life across all age groups. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, as technological advancements reshape society, these changes also redefine the environment of work, opening new avenues for supporting an ageing workforce. In an increasingly digitised work environment, and with a growing ageing workforce, it is crucial to understand how digital technology (e.g., web-based platforms, smartphone, computers) impacts older workers\u0026rsquo; general well-being and their ability to stay in the workforce.\u003c/p\u003e\u003cp\u003eAt the same time, the concept of social support itself is not straightforwardly defined, often used as an umbrella term referring to how relationships foster well-being, self-esteem, and other types of health indicators [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. For example, Cobb\u0026rsquo;s [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] view is that social support provides information on how someone is cared for and acts as a defence mechanism against the impact of stress on health. He argues that social support is an important ally for health and reduces the time needed to manage stress. Lakey and Cohen [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] introduced three influential theoretical perspectives on social support: the stress and coping approach, the social constructionist approach, and the relationship approach. The stress and coping perspective suggest that social support enhances well-being by buffering individuals against the detrimental impacts of stress. In contrast, the social constructionist viewpoint argues that support enhances well-being by fostering self-esteem and self-regulation, irrespective of the presence of stress. The relational perspective proposes that the health outcomes of social support cannot be disentangled from the relational dynamics that often accompany support, including companionship, intimacy, and low social conflict. Finally, these perspectives highlight different mechanisms that can explain the connection between social support and health.\u003c/p\u003e\u003cp\u003eAccording to LaMeres [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], digital technologies are used for data manipulation, storage, transmission, and processing in digital format, all aimed at enhancing quality of life (e.g., web-based platforms, smartphones, computers, digital cameras, digital videos/audios, etc.). These technologies are increasinly recognised as offering a new form of social support, although no clear definitions exist for this type due to the diversity of technologies involved. In this respect,, digital technologies have been examined as vehicles for providing new form of social support. (i.e., online social support), and evidence suggests that they influence health outcomes for older adults in similar ways to traditional forms of support [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] through companionship, coordination, maintaining ties, and casual conversations. However, digital technologies also present challenges. Both negative and positive effects are observed for older workers, and research does not always differentiate between effects for older adults and older workers. For example, Nimrod [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] describes technostress because of interactions with information and communication technology (ICT), which can threaten older adult\u0026rsquo;s well-being. Alcover et al.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] argue that digitalisation (i.e., Artificial Intelligence (AI), robotics, automation) increases job insecurity or negatively affects older workers\u0026rsquo; wellbeing, as they often lack ICT skills or need more time to solve tasks involving ICT compared to younger workers. Finally, other research results indicate that social support helps older adults learn to use digital technologies (i.e., tablet computers) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eNick et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] propose measuring online social support, categorising it based on its functional roles and purposes. They identify four types of online social support from previous theory and research: esteem/emotional support, social companionship, informational support, and instrumental support. Esteem/emotional support involves conveying acceptance, intimacy, care, liking, respect, and similar emotions through verbal and nonverbal cues. Social companionship support fosters a sense of belonging through actions that express inclusiveness or involve spending time together. Informational support encompasses sharing advice, feedback, knowledge, and resources. Instrumental support refers to the provision of practical assistance, including financial assistance, material help, task assistance, and taking on responsibilities. Current theoretical frameworks of online social support build on previous influential perspectives, as many digital technologies now provide social support. For example, AI-based applications (apps) can assist older adults in their daily lives, for instance, by tracking and monitoring health indicators and cognitive functioning [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eEarly research on social support in online environments reveals mixed effects [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Findings suggest that social support via email and online chat is critical for health indicators, but social conditions influence media choice, and individuals continually assess the appropriateness of the social context. Francis et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] uncovered in their qualitative analysis that coping with technical issues from regular ICT use also provides opportunities for both online and traditional social support.\u003c/p\u003e\u003cp\u003eMendel et al.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], through qualitative analysis, also highlight the mixed effects of the interaction between social support and digital technologies. While online social support related to fraud and phishing information may increase safety risks for older adults, mobile tools can also be used to raise awareness, encourage proactive behaviour, and foster learning to manage mobile safety challenges. Similarly, Marston and Musselwhite [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] advocate for the generally positive effects of technological tools in improving older people`s lives, while also identifying social barriers associated with learning to use such tools. Utz and Breuer [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] tested social network sites for providing social support and enhancing well-being. They found that those using social networks reported more online social support than those not using them, with users seeking more advice online. Likewise, Thompson and Atkins's [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] found that technological tools facilitate the sharing of ideas, the creation of meaningful relationships, and the instantaneous sharing of information.\u003c/p\u003e\u003cp\u003eWith respect to an ageing workforce, Thompson and Mayhorn [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] argue that digital technologies can serve as online support mechanisms for older workers by addressing physical demands, mobility concerns, visual acuity, workplace safety, memory limitations, new networking opportunities, and reducing age-related cues that prompt discrimination. Digital technologies are humanised, meaning they can become sources of social support or, conversely, a lack thereof (e.g. older workers may feel that computers restrict them), or alternatively, rely on them for assistance at work). For instance, researchers describe technological tools assisting older workers maintaining productivity, compensating for motor strength through using computer-aided manufacturing or using robotics to alleviate cognitive and physical stress by assisting with precise steps. Thus, the belief in digital social support could be seen as a type of social support shaped by digital technologies.\u003c/p\u003e\u003cp\u003eMoreover, social support is reinforced by social identity theory [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], and empirical research [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] indicates that both online and offline social support depend on group membership, which is particularly relevant for groups in the workplace who rely on mutual support, such as informal caregivers, as they benefit from shared experiences, resources, and a sense of belonging within their peer groups.\u003c/p\u003e\u003cp\u003ePrevious research has often focused on the potential risks and vulnerabilities that digitalisation poses to ageing workers [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] or explored its positive impact on similar concepts to social support like social capital [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. However, there has been little effort to identify types of social support provided through digital technologies specifically for older workers. This scoping review therefore aims to address this gap by exploring how digital technologies used in the work environment affect social support for older workers and identify the types of online social support that arise. Through a comprehensive review of existing research, this scoping review seeks to understand the role of digital technology in enhancing social support for older workers by addressing the following questions: Which digital technologies are most used by older workers and their colleagues to stay connected? How are these digital technologies being used by older workers? Do these digital technologies facilitate and mediate online social support? And how is the use of digital technologies for accessing social support is linked to the health of older workers? By synthesizing these findings, this study seeks to provide a comprehensive analysis of how digitalisation can be used to support and enhance the well-being of older workers.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eThis scoping review follows standard and recognised methodology for systematic reviews reporting by the Joanna Briggs Institute (JBI) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] along with recommendations from Scoping Reviews checklists and the PRISMA extension for scoping reviews (PRISMA-ScR) flow diagram for new systematic reviews, which includes searches of databases and registers only [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. We used Covidence software as a tool for managing references to facilitate title and abstract screening, to conduct full-text reviews and to support data extraction.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eSearch strategy\u003c/h2\u003e\u003cp\u003eA three-phase approach was implemented for the search strategy. First, we identified and defined the main concepts of digital technologies, online social support, and older workers. We followed the definitions of digital technologies provided by LaMeres [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Online social support refers to the use of digital technologies such as social media, online forums (i.e. professional groups/communities), and messaging platforms to manage difficulties, challenges, or serious problems. We considered three types of online social support: emotional support (key terms: empathy, encouragement, validation, concern, affection); informational support (key terms: advice, guidance); instrumental support (key terms: assistance with resources, financial assistance, online help, technical and organisational support). Additionally, we also paid attention to the availability of implicit social support, such as perception of workers of getting along with fellow workers. Social support through digital technology can take diverse forms, such as social media, online platforms, virtual communities, telemedicine platforms, online helpline services (e.g. psychological online services, professional IT or administrative online services, health apps, monitorization apps), facilitating easier connections and communication across distances. Older workers are defined as individuals aged 50 years and above who are employed.\u003c/p\u003e\u003cp\u003eSecondly, following the JBI methodology for scoping reviews PCC (Participants, Concepts, Context) Framework was established. Accordingly, participants (P) are studies involving workers aged 50 and above. The concept (C) is studies on the use of digital technologiesin the work leading to social support. Context (C) is studies conducted in all workplace contexts. PCC informed our inclusion criteria. The search was limited to studies published in English and peer-reviewed scientific articles using quantitative, qualitative, or mixed methods, with no time constraints. The exclusion criteria were defined as studies not concerning working individuals or those not associated with work, studies using analogue technology (i.e., non-digital media such as analogue phone, analogue fax machine), non-English articles, theoretical papers, books, book chapters, reviews, systematic reviews, reports, protocols, and non-peer-reviewed studies (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eInclusion and exclusion criteria\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCC Framework\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInclusion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExclusion\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParticipants\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudies involving workers aged 50 and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNon-working individuals or involving only individuals younger than 50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConcept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudies on the use of digital technologies in the workplace leading to social support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStudies on analogue technology\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eContext\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudies conducted in all workplace contexts and in all countries\u003c/p\u003e\u003cp\u003eEnglish language articles\u003c/p\u003e\u003cp\u003eQuantitative, qualitative, and mixed methods.\u003c/p\u003e\u003cp\u003ePeer-reviewed scientific articles\u003c/p\u003e\u003cp\u003eNo time constraint regarding publication year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStudies not associated with employment\u003c/p\u003e\u003cp\u003eNon-English articles\u003c/p\u003e\u003cp\u003eOther study types (theoretical papers, books, book chapters, reviews, systematic reviews, reports, protocols)\u003c/p\u003e\u003cp\u003eNon-peer reviewed studies\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFinally, search terms were identified based on an initial literature review regarding our main concepts, namely digital technologies, online social support, and older workers. A single syntax search was designed for all databases. Terms were identified as \u0026ldquo;social support\u0026rdquo; OR \u0026rdquo;social assistance\u0026rdquo; OR \u0026rdquo;emotional support\u0026rdquo; OR \u0026rdquo;social aid\u0026rdquo; OR \u0026rdquo;social advice\u0026rdquo; OR \u0026rdquo;social guidance\u0026rdquo; OR \u0026rdquo;instrumental support\u0026rdquo; OR \u0026rdquo;information support\u0026rdquo; OR \u0026rdquo;social help\u0026rdquo; OR \u0026rdquo;financial assistance\u0026rdquo; OR \u0026rdquo;online*\u0026rdquo; OR \u0026rdquo;technical support\u0026rdquo; OR \u0026rdquo;organisational support\u0026rdquo; OR \u0026rdquo;affect* support\u0026rdquo;) AND (\u0026rdquo;digital*\u0026rdquo; OR \u0026rdquo;platform*\u0026rdquo; OR \u0026rdquo;apps*\u0026rdquo; OR \u0026rdquo;tech*\u0026rdquo; OR \u0026rdquo;social media\u0026rdquo; OR \u0026rdquo;chat\u0026rdquo; OR \u0026rdquo;online*\u0026rdquo; OR \u0026rdquo;telemedicine\u0026rdquo; OR \u0026rdquo;cyber\u0026rdquo; OR \u0026rdquo;virtual\u0026rdquo; OR \u0026rdquo;computerized\u0026rdquo; OR \u0026rdquo;computerised\u0026rdquo; OR \u0026rdquo;electronic\u0026rdquo; OR \u0026rdquo;ICT\u0026rdquo;) AND (\u0026rdquo;old* work*\u0026rdquo; OR \u0026rdquo;old* employee*\u0026rdquo; OR \u0026rdquo;old* profession*\u0026rdquo; OR \u0026rdquo;elder work*\u0026rdquo; OR \u0026rdquo;aging work*\u0026rdquo; OR \u0026rdquo;ageing work*\u0026rdquo; OR \u0026rdquo;old* workforce\u0026rdquo; OR \u0026rdquo;aged work*\u0026rdquo; OR \u0026rdquo;senior work*\u0026rdquo;. Searches were undertaken in the databases ERIH, Web of Science, Scopus, PubMed, PsycINFO, Proquest in 04 May 2023 by three reviewers CT, MAM, DG. The search results were uploaded into Covidence.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy selection and data extraction\u003c/h3\u003e\n\u003cp\u003eAll studies identified through database searching were retrieved and then imported and stored in Covidence. Duplicates were automatically removed using Covidence\u0026rsquo;s build-in feature. The titles and abstracts of the identified studies were double screened by 12 reviewers to determine if they met the inclusion criteria. The full texts of eligible studies were then retrieved and assessed independently by two reviewers based on our main research questions and the inclusion and exclusion criteria. Any disagreements were resolved through discussion or with the intervention of a third reviewer.\u003c/p\u003e\u003cp\u003eIn the data extraction phase, 11 reviewers were involved. Two independent reviewers extracted the relevant information from the selected studies into the data extraction chart that we created in Covidence. Any disagreements between reviewers were resolved through discussion and validated by JS and CMT. The data chart included the following items: bibliographical reference, study location, data collection, information about invited and actual participants in the study, age used in the analysis or results of the study, information about whether the participants included both young and older people, and both older adults and workers, gender, population, social support, type of social support, the digital technologies used and type of digital technologies. Additionally, we extracted data about main theories and instruments used in the studies. Extracted data were exported to Microsoft Excel, analysed and presented using descriptive statistics, with a narrative summary presented below.\u003c/p\u003e\n\u003ch3\u003eQuality assessment\u003c/h3\u003e\n\u003cp\u003eAll the included studies were critically appraised for their methodological quality using the Mixed Methods Appraisal Tool (MMAT) Version 2018, developed by Hong et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The MMAT provides comprehensive guidelines for assessing quality across five categories of study designs, including qualitative studies, randomized controlled trials, nonrandomized studies, quantitative descriptive studies, and mixed methods studies). The tool consists of two parts: a checklist with two initial screening questions to confirm the paper is an empirical study (i.e., the clarity of research questions and feasibility of a study to answer them), followed by five criteria for each study design category. The second part provides detailed explanations for each criterion to guide the assessment process.\u003c/p\u003e\u003cp\u003eTwo reviewers independently appraised each study to minimize bias and ensure reliability. Discrepancies between reviewers were resolved through discussion to reach a consensus. For each study, the reviewers completed assessments that included two initial screening questions (\u0026ldquo;Yes\u0026rdquo; = 1 or \u0026ldquo;No\u0026rdquo; = 0) and then assessed a set of five criteria specific (\u0026ldquo;Yes\u0026rdquo;=1 or \u0026ldquo;No\u0026rdquo;=0) to the study design, as outlined by the MMAT. These criteria assess the appropriateness of the methodology, the adequacy of data collection methods, the relevance of the measurements to the research questions, and the coherence between data sources and analysis methods. Finally, for this review, we calculated the percentage of \"Yes\" responses for each study to provide an overview of the methodological quality. No studies were excluded based on this assessment. This quality percentage score was calculated by dividing the number of \"Yes\" answers by the number of applicable criteria and multiplying the result by 100. These quality percentage scores reflect the proportion of applicable MMAT criteria that each study met, indicating the level of methodological rigor according to the tool's framework. Next, the quality percentage scores were averaged for the two initial screening questions and then for each study design to obtain mean quality scores. Studies with scores below 50% were classified as low quality, those between 50% and 79% as moderate quality, and those at or above 80% as high quality. This quantitative measure of quality will help discuss the reliability and validity of the findings from these studies within the broader context of our review.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eSelected Studies\u003c/h2\u003e\u003cp\u003eThe initial database search identified 5,213 studies. After removing duplicates, 4,730 were screened for eligibility, with 378 retrieved for full-text review. Of these, 43 met our pre-established inclusion and exclusion criteria and were selected for data extraction. Studies excluded during the process are detailed in the PRISMA flow-chart (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eQualitative assessment\u003c/h2\u003e\u003cp\u003eOverall, 81% of studies clearly stated research questions and collected appropriate data to answer them. The sample included 13 quantitative non-randomized studies of moderate quality (mean score: 66%), 9 quantitative descriptive studies of moderate quality (mean score: 50%), 2 randomized controlled trials bordering low to moderate quality (mean score: 40%), 9 qualitative studies of moderate quality (mean score: 78%), and 10 high quality mixed-method studies (mean quality: 80%). The lower quality of the quantitative descriptive studies was partly due to their frequent failure to report nonresponses or address the higher risk of nonresponse (\u003cem\u003esee Supplemental material_Quality assessment\u003c/em\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCharacteristics of included studies\u003c/h3\u003e\n\u003cp\u003e\u003cem\u003eAuthors and publishing and collection of data years.\u003c/em\u003e Of the 43 selected studies, the earliest two were published in 1998 [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] and in 2000 [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. All others were published between 2016 and 2023. Of these studies, three used data from the year 2000 or earlier, none had data collected between 2001 and 2014, 12 were based on data collected between 2015 and 2019, and 21 studies used data collected in 2020 or later (in three of these studies, data were collected twice, once in each of the latter two periods). In 11 studies, the data collection year was not stated (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eParticipants\u003c/em\u003e. Regarding the number of participants invited, 19 papers did not report this information, while the remaining studies provided either precise or approximate numbers and described the invitation process. The number of participants ranged from 8 to over 14,000, depending on whether the study was qualitative, quantitative, or mixed methods. Finally, in terms of follow-up studies, only 8 studies included follow-up assessments, with participant numbers ranging from 12 to over 600, depending on the study design [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan additionalcitationids=\"CR39 CR40 CR41 CR42 CR43\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eAge categories used in the analysis or results of the study\u003c/em\u003e. Out of the 43 selected studies, 14 used age ranges (e.g., 19\u0026ndash;63, 40\u0026ndash;65), 13 used mean age (e.g., 42.1), and 18 used age categories (e.g., 18\u0026ndash;25, 26\u0026ndash;40) in the analysis. When assessing whether studies included both younger and older workers, our findings indicate that 34 studies included both, while 8 papers focussed exclusively on older workers. In one paper the age range was not stated [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eType of study.\u003c/em\u003e Regarding the type of study, 10 studies used mixed methods, 10 studies used qualitative methods, and 28 used quantitative methods (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eType of population\u003c/em\u003e. Study populations include workers from various sectors such as public institutions, manufacturing, health care, academia, and other employment sectors. 17 studies included both older adults and older workers, while the remaining studies either included the general population or focussed on one specific group of workers (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eGender.\u003c/em\u003e 21 studies analysed both men and women, two studies only women [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] and one also included a category for non-binary [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. 4 studies did not report gender in their results [\u003cspan additionalcitationids=\"CR48 CR49\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eSocial support (SS).\u003c/em\u003e In 19 studies, SS is explicitly defined, while in the remaining 24 studies, it is implicit, i.e., SS could be inferred from one or more outcome variables. For instance, asking whether employees got on with fellow workers [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] or shared knowledge with people outside the company during the lockdown [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. The source of support (e.g. from colleagues, supervisors, etc.) also varies across the studies (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eDigital\u003c/em\u003e technologies \u003cem\u003e(DT).\u003c/em\u003e DT or technologies examined in the selected studies ranged from data entry work and teleworking to app-based interventions and ICT tools. In 20 studies, the DT is explicitly stated as part of the work or intervention, in 19 studies, its use is inferred, such as through remote work or hybrid working setups, while in the remaining 4 studies studied DT both explicitly and implicitly. For instance, Al Shamari [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] studied the experience with e-learning (an explicit DT) among Saudi Ministry of Health trainers and training coordinators who were forced to work from home (an implicit DT) during COVID-19 (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eData collection method\u003c/em\u003e. All studies mention a method of data collection, which included questionnaires, surveys, interviews, focus groups, or combinations of these methods. The specific data collection method employed is described for each of the 43 studies (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eCountries.\u003c/em\u003e Across the 42 studies that disclosed location, 77 countries were represented [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The majority of research was conducted in European countries (68 instances), followed by countries in Asian/Oceania (8) and North America (1). No relevant studies were identified from South America or Africa. Italy had the highest representation, appearing in seven studies, followed by The Netherlands and Austria, with 5 each (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Supplemental material_Countries).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSelection and description of studies (N\u0026thinsp;=\u0026thinsp;43) for the association between digital technologies and social support specific to older workers.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"13\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAuthor(s)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYear of data collection\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eData collection method\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN (invited / participants/follow-ups\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAge used in the analysis / results*\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eboth young \u0026amp; older workers\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eboth older adults \u0026amp; workers\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eGender**\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003ePopulation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSocial support (SS)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eType of SS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eDigital technologies (DT)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eType of DT\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAborg et al. (1998)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1991, 1992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOnline survey and in-depth interviews\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e153/22/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 19\u0026ndash;63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003epublic institution workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSS from colleagues and supervisors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eData entry type of work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarayon and Karsh (2000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1994/1991-92.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey, semi-structured interviews\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAgency A 149/47/NA Agency B 191/122/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMAge\u0026thinsp;=\u0026thinsp;42.1; SD\u0026thinsp;=\u0026thinsp;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers in public institution\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSS from colleagues and supervisors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eImage and non-image users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeyers and Bagnall (2016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSemi-structured interview\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/10/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 45\u0026ndash;55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eOlder workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eCognitive support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eOnline learning (e.g., the use of technology, hypermedia, independent learning)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMohadis et al. (2016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterview\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/10/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 50\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSocial comparison and competition persuasive principles as SS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eFitSenior application\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVerbrugghe et al. (2016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22084/790/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: Up to 54, 55+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers in the private sector\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSS for sustainable employability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eDevelopment of Healthy Workplaces for all Ages e-guide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArvola (2017)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/107/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: under 50, 50+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eGetting on with fellow-workers and social networks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eimplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTeleworking and the extent that ICT devices and applications were used for work (PC, laptop, tablet PC, smart phone, MS Outlook, MS Office, social networks).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHauk et al. (2019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOnline survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/1216/T2\u0026thinsp;=\u0026thinsp;840/T3\u0026thinsp;=\u0026thinsp;631\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 17\u0026ndash;75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eInstrumental SS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eICT tools\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCalder\u0026oacute;n-G\u0026oacute;mez et al. (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3000/2800/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 16\u0026ndash;34, 35\u0026ndash;54, 55\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003einternet users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eOnline communication with colleagues\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eOnline tools linked to the mobile phone and/or computer, including messaging services, social media, video conference apps, SMS, and email.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChandra et al. (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOnline survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e700/163/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMAge\u0026thinsp;=\u0026thinsp;37.64,\u003c/p\u003e\u003cp\u003eSD\u0026thinsp;=\u0026thinsp;6.76.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eservice sector workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eTechnological spatial intrusion and usefulness of ICT for workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eICT use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDe Leeuw et al. (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSemi-structured interview\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/10/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 52\u0026ndash;63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eHealth information\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eimplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eHealth information technology; electronic health records and eHealth devices\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHandley and Outer (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterview\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/24/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 48\u0026ndash;58; MAge\u0026thinsp;=\u0026thinsp;52.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eKnowledge workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eLack of mentoring and acknowledgment at work through organisational decisions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eWorkers from the IT software sector, film industry, and technology entrepreneurs.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddleton et al. (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2019\u0026ndash;2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eText messages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e464/291/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 17\u0026ndash;30, 31\u0026ndash;40, 41\u0026ndash;50, 51\u0026ndash;60, 61\u0026ndash;70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M, T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eInformational SS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e@Work (app intervention through text messages)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSchmied et al. (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSemi-structured interview\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/17/12 (incl 2 new recruits)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMAge Employed\u0026thinsp;=\u0026thinsp;60;\u003c/p\u003e\u003cp\u003eJust retired\u0026thinsp;=\u0026thinsp;65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eNewly retired workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eEmotional and social support through digital coach\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003ePossibility of working from home and the implementation of a virtual health care coach (Sanbot Elf robot and Sola avatar).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHab\u0026aacute;nik et al. (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSurvey 1:NS/302/NA. Survey 2:NS/284/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 18\u0026ndash;25, 26\u0026ndash;35, 36\u0026ndash;45, 46\u0026ndash;55, 56\u0026ndash;65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSocial contact with co-workers and instrumental SS for remote work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eRemote work, ICT use for work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eBoth implicit and explicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLai et al. (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2017\u0026ndash;2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e265/167/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 21\u0026ndash;30, 31\u0026ndash;40, 41\u0026ndash;50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eEmployee agility and IT competency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eEnterprise Social Media, knowledge management systems, intranets, groupware, and bulletin board systems.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMa et al. (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOnline survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1500/1020/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 55\u0026ndash;60, 61\u0026ndash;65, 66\u0026ndash;70, \u0026gt;\u0026thinsp;70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eInformation and emotional support through social media at work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eexplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eSocial media usage at work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMolino et al. (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFocus-group and questionnaire\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eQual: NS/14/NA Quant: NS/263/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eQual: NS. Quant: Mage\u0026thinsp;=\u0026thinsp;41.44; SD\u0026thinsp;=\u0026thinsp;12.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eManufacturing workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSupervisor SS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eIndustry 4.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRantanen, et al. (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOnline survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1128/162/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMAge\u0026thinsp;=\u0026thinsp;43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003ehome care workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eInformational and instrumental SS through care robots at work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eCare robots in-home care tasks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSantini et al. (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2019 / 2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFocus-group, telephone interview\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/60/27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMAge: Austrian\u0026thinsp;=\u0026thinsp;60.2;\u003c/p\u003e\u003cp\u003eItalian\u0026thinsp;=\u0026thinsp;60;\u003c/p\u003e\u003cp\u003eDutch\u0026thinsp;=\u0026thinsp;65.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers and Retirees\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSocial relationship improvement through digital technology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eVirtual coach\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSederevičiūtė-Pačiauskienė et al. (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ein-depth interviews\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/37/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 19\u0026ndash;59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eTeachers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSupportive collaboration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eimplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eOnline teaching\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTonnessen et al. (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e282/237/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 30\u0026ndash;40, 40\u0026ndash;50, 50\u0026ndash;60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eDigital knowledge sharing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eimplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTeleworking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWrede et al. (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1319/710/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMAge\u0026thinsp;=\u0026thinsp;44.57;\u003c/p\u003e\u003cp\u003eSD\u0026thinsp;=\u0026thinsp;12.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M, non-binary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSS from colleagues\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eE-governement services\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBartkowiak et al. (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2020 / 2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ein-depth interview\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/21/18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eWave 1 AR: 31\u0026ndash;67 Mage\u0026thinsp;=\u0026thinsp;52.04;\u003c/p\u003e\u003cp\u003eWave 2 AR: 35\u0026ndash;67 MAge\u0026thinsp;=\u0026thinsp;58.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSocialization and social contact\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTeleworking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBelostecinic et al. 2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOnline survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e450/377/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 18\u0026ndash;25, 26\u0026ndash;40, 41\u0026ndash;55, 55+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eEmployers' informational and instrumental SS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTeleworking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBusch\u003c/p\u003e\u003cp\u003eet al. 2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42/42/NS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 32\u0026ndash;66; M\u0026thinsp;=\u0026thinsp;52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eSmall business workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSS from partners\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eBlended coaching format (combined face-to-face with tele-sessions, an\u0026nbsp;online diary, and online courses)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eBoth implicit and explicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDanieli et al. (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterview\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60, remained 45.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMAge\u0026thinsp;=\u0026thinsp;55.58;\u003c/p\u003e\u003cp\u003eSD\u0026thinsp;=\u0026thinsp;5.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAR / AC NS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eMHealth AI conversational agent at work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTEO, Therapy Empowerment Opportunity, a mobile personal health care agent with conversational AI, mHealth app.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDe Carlo et al. (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/295/185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMAge\u0026thinsp;=\u0026thinsp;37.6;\u003c/p\u003e\u003cp\u003eSD: 12.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eColleagues and supervisor Interpersonal support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTeleworking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKim et al. (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2018\u0026ndash;2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey and app indicators\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e149/50/46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 40\u0026ndash;65 years,\u003c/p\u003e\u003cp\u003eET group (MAge\u0026thinsp;=\u0026thinsp;47.79, SD\u0026thinsp;=\u0026thinsp;7.01);\u003c/p\u003e\u003cp\u003eST group (MAge\u0026thinsp;=\u0026thinsp;53,27, SD\u0026thinsp;=\u0026thinsp;7.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003emigrant workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSS from team leader through digital technologies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eMobile health app based on monitoring walking Participants used a Fitbit smart watch.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMazzuto et al. (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNot described\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/8/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\"younger\" or \"older\" workers (born before 1980 or after)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eAcademic workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eTraining nd work support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eimplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eDigital technologieswere used at work, and the participants in the education learned how to handle new techonology and safety at work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMemon et al. (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003esemi-structured interview\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41/41/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 21\u0026ndash;30, 31\u0026ndash;40, 41+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eLack of collaboration and coordination from the\u0026nbsp;supervisor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTeleworking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOber (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6000/402/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 18\u0026ndash;24, 25\u0026ndash;34, 35\u0026ndash;44, 45\u0026ndash;54, 55+. ANALYSIS: 18\u0026ndash;24, 25\u0026ndash;34, 35+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M, T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eMotivation to use platforms, open innovation networks, reluctance to share knowledge, and insufficient support from top management\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eOpen innovation platforms networks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScheibe et al. (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6541/1715/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 18\u0026ndash;25, 26\u0026ndash;35, 36\u0026ndash;45, 46\u0026ndash;55, 56+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSocial integration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTeleworking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTaboroši et al. (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/313/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: up to 35, 36+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSocial networks for communication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eSocial media usage in general\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAl Shamari (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOnline survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e498/262/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 26\u0026ndash;76 (Cohorts1946-64, 1965-80, 1981\u0026ndash;1996)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M, T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eLack of relational, emotional, informational, or instrumental SS within training setting at work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eE-learning experience, working from home\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eBoth implicit and explicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMart\u0026iacute;nez-P\u0026eacute;rez et al. (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuant: 2018 Qual: 2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey and focus-group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/504/NS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 21\u0026ndash;64. Mage\u0026thinsp;=\u0026thinsp;37.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eLack of SS from work and lack of instrumental SS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eGeneral ICT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eBoth implicit and explicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFerreira and Gomes (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24144/14298/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: \u0026lt;25, 25\u0026ndash;35, 36\u0026ndash;50, 51\u0026ndash;65, \u0026gt;\u0026thinsp;66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRemote workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003ePerceived organisational support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTeleworking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLopes et al. (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/573/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMAge\u0026thinsp;=\u0026thinsp;46.8, SD\u0026thinsp;=\u0026thinsp;8.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003ePerceived benefits of training (e.g. better relationship with citizens, peers, and chiefs)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eParticipants in digital training field group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOksanen et al. (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2020\u0026ndash;2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4069/1152/656\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 20\u0026ndash;66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSupportive working environment and SS from colleagues and supervisors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTeleworking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePetcu et al. (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/440/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: up to 25, 26\u0026ndash;35, 36\u0026ndash;50, 50+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eRelational communication through online tools between co-workers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eimplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTeleworking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRaišienė et al. (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOnline survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e202/202/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 18\u0026ndash;24, 25\u0026ndash;34, 35\u0026ndash;48, 49\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M, T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eManagement support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTeleworking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSantini et al. (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey and online focus-group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e91/62/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAR: 55+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers before and after retirement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eCoach support through digital app\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eDigital Coaching\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSchneider and Bousbiat (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNS/34/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 55\u0026ndash;58, 59\u0026ndash;62, 63\u0026thinsp;\u0026minus;\u0026thinsp;6;. MAge\u0026thinsp;=\u0026thinsp;61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWorkers who have retired or are about to retire\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eInformational support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eSmartphone and tablet usage, and the\u0026nbsp;use of a robot in their daily life\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZin et al. 2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e170/170/NA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAC: 56\u0026ndash;65, 66\u0026ndash;75, 76\u0026ndash;85, 86\u0026ndash;95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF, M\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eolder adults\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eInformational support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eImplicit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003esmart health watch - wrist-worn wearable technologies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eExplicit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"13\"\u003eNotes: NA\u0026thinsp;=\u0026thinsp;not applicable; NS\u0026thinsp;=\u0026thinsp;not stated; Quant\u0026thinsp;=\u0026thinsp;Quantitative; Qual\u0026thinsp;=\u0026thinsp;Qualitative; SS\u0026thinsp;=\u0026thinsp;social support; DT\u0026thinsp;=\u0026thinsp;digital technologies; ICT\u0026thinsp;=\u0026thinsp;Information and Communications Technology.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"13\"\u003e*Age is reported: AC\u0026thinsp;=\u0026thinsp;age categories, AR\u0026thinsp;=\u0026thinsp;age ranges or Mage\u0026thinsp;=\u0026thinsp;mean age and SD\u0026thinsp;=\u0026thinsp;standard deviations;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"13\"\u003e**We considered older workers from the age of 45 when \u0026rdquo;older workers\u0026rdquo; was mentioned in the study's title (e.g. Meyers and Bagnall [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], Handley and Den Outer [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e];\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e***Gender is reported as categories used in the analysis or results: F\u0026thinsp;=\u0026thinsp;female, M\u0026thinsp;=\u0026thinsp;male, T\u0026thinsp;=\u0026thinsp;total F\u0026thinsp;+\u0026thinsp;M.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eConceptual map of social support for older workers and impact on health\u003c/h3\u003e\n\u003cp\u003eSocial support is a multifaceted concept encompassing various forms of assistance that individuals may receive from others, particularly within the workplace. It is often mediated through the use of digital technologies or provided in the context of remote work. Evidence from prior studies highlights diverse perspectives on how social support is facilitated and how it influences health outcomes [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The literature spans multiple health domains, including physical health (e.g., healthy ageing and healthy activities; [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], mental health (e.g., detachment; Busch et al, 2022; exhaustion; [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]), well-being [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]), social health (44, 60) and organizational outcomes (e.g., job satisfaction; 37)\u003c/p\u003e\u003cp\u003eFurthermore, we have identified that different studies cover one or more of the four types of online support proposed by Nick et al[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], namely esteem/emotional support, social companionship, informational support, and instrumental support. For example, Schmied et al. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] examined the esteem/emotional support type through the potential use of a digital coach for employees nearing retirement and retirees. Their findings indicate that individuals approaching retirement feared losing their workplace social network, and the coach provided a way to stay connected to alternative networks, thereby influencing health outcomes Similarly, Ma et al. [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] found that the direct use of social media at work enhanced both information and emotional support, as well as improved older employees\u0026rsquo; self-efficacy at work.\u003c/p\u003e\u003cp\u003eSeveral studies illustrate instrumental support, demonstrating how supervisors or chiefs use digital technologies to support older workers in tangible ways with practical aid such as task assistance and resource provision or how they obtain this support through training [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. For example, Rantanenet al. [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] highlighted the role of care robots in assisting older home care workers. Employees age increases enthusiasm, but reduces self-efficacy. Lai et al. [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e] highlighted employees\u0026rsquo; agility in collaborative work is enhanced through IT competency development, enterprise social media, and knowledge management systems. Other resourceful instrumental support is health information [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e] and support for sustainable employability [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Similarly, informational support encompasses sharing knowledge, advice, or guidance [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e] with authors who discuss training and instructional content.\u003c/p\u003e\u003cp\u003eRelational support seems to be highlighted directly through supervisor and colleagues support [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] and communication through digital technologies[\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Another type, social companionship, reflects a sense of belonging and collaboration within the working setting [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. For example, Scheibe et al. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] and Calder\u0026oacute;n-G\u0026oacute;mez et al. [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e] examined teamwork and social relationships at work and other highlighting the relational nature of support [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e] [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Scheibe et al. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] report more resilience through feeling more socially integrated in comparison to the younger employees, while Calder\u0026oacute;n-G\u0026oacute;mez et al.report increased communicative activities although very few older workers. Santini et al. [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] emphasize relational support through social relationship improvement by using digital technologies and social contact with co-workers. The AgeWell digital coach was found to improve participants\u0026rsquo; level of self-efficacy, mental well-being, and physical activity when supplemented with human coach support. However, once the human coach stopped their involvement, this positive effects on self-efficacy and mental well-being disappeared.\u003c/p\u003e\u003cp\u003eHowever, insufficient social support may also lead to negative consequences, as attested by several studies [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. For instance, Memon et al. [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e] found that a lack of collaboration and social interaction in remote work environments led to isolation and detachment, adversely affecting older workers\u0026rsquo; mental health and overall well-being. Finally, indirect measures of social support are found in Meyers and Bagnall [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] (e.g. cognitive support; 2017) and Mohadis et al. [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e] (e.g., social comparison and competition persuasive principles as SS; 2016).\u003c/p\u003e\u003cp\u003e\u003cb\u003eDigital\u003c/b\u003e technologies \u003cb\u003eenhancing social support for older workers\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThree types of digital technologies enhance social support for older workers. First of all, there are digital technologies that explicitly aim at enhancing communication, collaboration [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e] and health management [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. For example, messaging services, social media, and video conferencing tools are used to maintain communication and coordination among colleagues, enhancing both emotional and informational support [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Additionally, online learning platforms and applications like hypermedia-based training modules provide cognitive support for older workers by facilitating independent learning and skill development [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Other explicit digital technologies include ICT-driven health management systems, such as electronic health records and mobile health apps like the FitSenior application, which promote health-related social comparison and competition, offering persuasive encouragement through digital channels [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Secondly, teleworking setups, enabled by a range of ICT devices such as laptops, smartphones, and collaborative software [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], allow for continued collaboration and social interaction even when workers are remote [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. Digital technologies like care robots used in healthcare settings also fall into this category, providing informational and instrumental support for older healthcare workers [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Teleworking is a common theme in the studies, with multiple reports indicating that remote work setups improve workers' social support networks through frequent interactions with colleagues over digital platforms [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Moreover, teleworking has been linked to increased employer-provided informational and instrumental support, enhancing older workers' sense of social connection and their ability to access resources [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Habanik et al, 2021; [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e] or indicating less support for older workers [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Finally, blended formats that combine both face-to-face and digital interactions like coaching programs integrate digital platforms for mentoring, online diaries, and tele-sessions alongside traditional methods provide both emotional and instrumental support [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. For example, blended coaching programs for small business workers have been shown to enhance partner support through tele-sessions and online diaries [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Additionally, mobile health apps, such as the AI-powered TEO mHealth app, offer continuous conversational support, further extending the range of digital technologies available to provide support through automation [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Another example is the use of digital coaching apps for retirees or workers transitioning out of the workforce, which provide emotional and informational support to facilitate smoother transitions [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eTheories used in studies and shaping the association between digital\u003c/b\u003e technologies \u003cb\u003eand social support\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn total, 20 studies used a theoretical foundation such as persuasive design [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], learning approaches [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], and systems approach frameworks [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Other studies used psychological theories with social capital [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] or social cognitive theory [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] or conservation of resources theory [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] or human capital theory [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e] or stress theories and well-being [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e], or the theory of planned behaviour [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e] or behavioural change model (COM-B) [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. Out of all, 8 studies combined theories and models, like the theory of acceptance and technology acceptance model [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e], or applied models, such as Middleware\u0026rsquo;s model [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] or job-demands-resources (JD-R) model [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn 16 studies, the concepts used were resilience [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], self-efficacy and behavioural intention [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], spatial intrusion [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], narrative identities [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], open innovation [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], sustainable employability [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], information processing/communication [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], digital divide [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e], work digitalisation [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e] or social support [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eNine of the studies lacked a specific theoretical grounding [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] 573; [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eInstruments used for measuring social support\u003c/h2\u003e\u003cp\u003eThe results regarding social support for older employees' use of digital technology are measured with different types of instruments in the different studies, i.e. the design of the measuring instruments was different. Among the studies, 12 studies used interviews [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan additionalcitationids=\"CR43 CR44\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], and 30 studies used questions and questionnaires to measure social support for older workers' use of digital technology [\u003cspan additionalcitationids=\"CR37 CR38 CR39 CR40\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan additionalcitationids=\"CR46 CR47 CR48 CR49 CR50 CR51 CR52 CR53\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. One study [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] measured frequent use of social support for digital technologies with the intention of measuring social support in older workers' use of digital technology.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInstruments used for measuring the digital\u003c/b\u003e technologies\u003c/p\u003e\u003cp\u003eThe digital technology used by the older employees differed. However, not all studies measured the older employees' attitude, experience or frequency in using digital technology. In total, 20 studies used questions and questionnaires to measure the older employees' experiences and attitudes towards the digital technology [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e,, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. There were six studies that conducted interviews with the older employees to investigate their experiences and attitudes towards the digital technology [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. In six studies, measurements were made to investigate and estimate how often and for how long the older employees used the digital technology [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe scoping review analysed the role of digital technologies in providing social support to older workers, aiming to determine which technologies are most used and their impacts on social support and health and well-being. Notably, most of the studies we reviewed collected data in 2020 or later, coinciding with the COVID-19 pandemic and its aftermath. This timing likely influenced the findings: the pandemic\u0026rsquo;s rapid shift toward remote work and greater reliance on digital communication tools underscored the need for online forms of social support for employees. Our discussion reflects on the dual impacts of these digital technologies, both positive and negative, on older workers\u0026rsquo; social support and health, and situates these findings within existing theoretical frameworks.\u003c/p\u003e\u003cp\u003e\u003cem\u003eDigital\u003c/em\u003e technologies \u003cem\u003eshaping social support and health for older workers\u003c/em\u003e\u003c/p\u003e\u003cp\u003eWith the rise of digital technologies, the delivery of social support has evolved. Digital technologies like teleworking platforms, ICT systems, and mobile health apps, provide new avenues for offering social support. For instance, remote work technology facilitates relational support implicitly through digital knowledge-sharing, enabling workers to maintain professional relationships, exchange knowledge, and receive updates even when physically separated [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. These digital technologies facilitate relational support, both formal and informal exchanges, addressing employees\u0026rsquo; emotional and informational needs remotely [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Explicit forms of relational social support delivered via digital technologies include structured interventions like digital coaching or mobile health apps. Studies have shown that digital coaches, such as the AgeWell digital coach, can promote healthy ageing by enhancing physical activity, mental well-being, and socialization, providing direct support to participants [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Similarly, mobile health apps, like those studied by Kim et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], deliver encouragement, motivation, and health advice through social-cognitive strategies, fostering a sense of community and promoting well-being.\u003c/p\u003e\u003cp\u003eOn the other hand, implicit digital technologies are equally significant. Scheibe et al. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] examined how remote working environments can implicitly foster social integration and support through digital platforms. Workers used remote communication technologies to stay connected and share knowledge, even when such support was not explicitly structured as part of a digital intervention. Similarly, Mart\u0026iacute;nez-P\u0026eacute;rez et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] studied the use of general ICT across various industries, highlighting how digital technologies\u0026mdash;whether providing implicit and explicit instrumental support, or reflecting its absence\u0026mdash;are integral to managing the social dynamics of remote and hybrid work settings, where workers may experience limited support from colleagues and supervisors. Middleton et al. [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e] explored app-based interventions through the @Work program, where workers received informational support through text messages, illustrating how mobile technologies can offer targeted, real-time support. This study underscores the dual role of mobile-based tools in delivering both implicit support (through the tool itself) and explicit support (through messaging content). Other studies, such as Rantanen et al. [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], focus on more advanced digital technologies like care robots in home care tasks. These robots provide both informational and instrumental support, showing how technology is reshaping traditional forms of workplace support by integrating automation into day-to-day tasks. Similarly, Kim et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] explored mobile health apps based on smart technology (e.g., Fitbits) for monitoring physical activity among migrant workers, where digital technologies provide both health-related and social support.\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003ePositive effects on social support\u003c/h2\u003e\u003cp\u003eDigital technologies have increasingly become essential in providing social support to older workers across different contexts and industries. The digital technologies used in these studies often range from basic communication platforms to more sophisticated technologies designed to offer esteem/emotional support, social companionship, informational support, and instrumental support [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], but can also provide a lack of social support. For instance, Aborg et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] examined how workers in public institutions used digital technologies for data entry, where explicit social support came from colleagues and supervisors through the use of online surveys and in-depth interviews. This early study shows how even simple data entry work can be structured to foster support networks through digital means. Similarly, Carayon and Karsh [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] investigated image and non-image users in public institutions, where digital technologies facilitated explicit social support from colleagues and supervisors through both questionnaires and semi-structured interviews, reflecting how ICT tools could be used to support collaboration and communication. A more advanced example is Santini et al. [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], who explored the use of digital coaching apps to support workers both before and after retirement. This explicit form of social support, delivered via mobile apps, shows how digital interventions are tailored to meet the emotional and practical needs of workers transitioning out of the workforce. Likewise, Busch et al. [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] examined blended coaching formats (a mix of face-to-face and tele-sessions) for small business employees, where explicit social support from partners was enhanced through a combination of digital and traditional interactions.\u003c/p\u003e\u003cp\u003eAcceptance of new technologies among older workers is closely linked to the social support they receive, both from colleagues and supervisors. Findings by Molino et al.[\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e] indicate that supervisor support and role clarity are critical in facilitating technology acceptance, which subsequently leads to higher work engagement. Conversely, a lack of organisational support structures limits the efficacy of teleworking for older employees, making it less sustainable for this group without targeted interventions [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Research also highlights the significant role of spousal and relational support outside of work, which is essential for maintaining work-life balance and mental health. Studies by Busch et al. [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] and Memon et al. [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e] indicate that spousal support during periods of remote work enhances goal achievement and reduces stress, while social support from colleagues or family during digital interactions can help mitigate feelings of loneliness and detachment.\u003c/p\u003e\u003cp\u003eFinally, digital technologies that encourage collaboration and communication, such as enterprise social media and knowledge management systems, are also widely used. Lai et al. [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e] showed how these systems help workers enhance agility and IT competency, indirectly supporting social integration through increased collaboration. In summary, digital technologies in the workplace provide varying levels of social support, from explicit, well-structured interventions such as mobile apps and digital coaches to more implicit forms of support embedded in remote work and communication platforms. These digital technologies not only enhance social integration and informational support but also play a crucial role in emotional and instrumental support across different work environments [36,, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eChallenges and negative implications\u003c/h2\u003e\u003cp\u003eDespite these benefits, several studies reveal challenges. Older workers often face a digital divide, where their digital skill levels do not always align with job requirements, leading to feelings of isolation or exclusion. For instance, in teleworking environments, many older employees reported feelings of social deprivation and mental exhaustion, particularly when lacking peer or supervisory support [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Studies also noted that older employees working from home encountered reduced interaction with peers and supervisors, which can decrease job satisfaction and mental well-being [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Furthermore, teleworking and remote work setups can create a sense of isolation if not managed properly, with some workers reporting reduced collaboration and limited interaction with supervisors [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. This detachment can lead to decreased social companionship, a critical component of social support, and can negatively impact employee morale and well-being. Nevertheless, the flexibility and connectivity afforded by digital technologies have the potential to greatly enhance support, particularly when combined with human interactions [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMany older workers express a need for additional training to navigate new digital platforms effectively. Findings by Mazzuto et al. [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] reveal a discrepancy in learning rates, indicating that older workers often require more times and support to adapt to evolving technological tools. This suggests that tailored training programs could play a crucial role in enhancing digital adaptability and sustaining employability among older workers.\u003c/p\u003e\u003cp\u003eThe literature also highlights divergent outcomes regarding the well-being of older workers. These outcomes appear to be shaped by several factors, such as presence or absence of organizational support (6, 47 Ferreira \u0026amp; Gomes (2023), the digital literacy level of older workers, the type of digital technologies employed (79) and the broader implementation. Accordingly, the impact of digital technologies on older workers is not unidimensional but multidimensional, encompassing social, organizational and individual layers.\u003c/p\u003e\u003cp\u003eLimits of the Study\u003c/p\u003e\u003cp\u003eOur study also has several limitations. First, the search was confined to English-language publications. This exclusion may limit the comprehensiveness and generalizability of our findings, as studies published in other languages could provide alternative perspectives or results. The exclusion of non-peer-reviewed sources represents an additional limitation, as grey literature may contain relevant data or studies with non-significant results that are not captured in the published record. Moreover, this review is predominantly based on research conducted in developed countries. The relationships identified may therefore be contingent upon specific contextual factors, e.g., cultural norms that differ in developing nations. Future research is thus needed to validate these findings across a broader range of geographical and economic settings.\u003c/p\u003e\u003cp\u003eThe studies included also reflect considerable variability in designs. However, the dominance of European contexts in the available literature may further limit the generalizability of the findings to other cultural and policy settings. In addition, some studies did not exclusively examine older workers but included broader working populations, which may have diluted age-specific insights. Finally, the absense of standardized instruments for measuring social support remains a significant gap, and addressing this issue should be considered priority for future research.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe article highlights the dualistic impact of digitalisation on social support for older workers, highliting both opportunities and challenges within modern workplaces. On the positive side, digital technologies enable older workers to receive various forms of social support (e.g., esteem/emotional support, social companionship, informational support, and instrumental support) through platforms that promote communication, such as teleworking, enterprise social media, and health-related apps. These technologies facilitate professional connections and provide mental health benefits, often fostering a sense of inclusion and continuous learning and are aligned with Nick and colleagues\u0026rsquo; perspective [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] regarding types of online support. However, digitalisation also introduces challenges, especially for those with limited digital skills, potentially leading to social isolation, technostress, and a feeling of inadequacy in fast-paced digital environments. The reviewed studies highlight that, although digital technologies can bolster older workers' productivity and connectivity, the benefits are contingent on adequate training and organisational support. The research thus points to the need for targeted digital literacy programs and sustained managerial backing to mitigate negative impacts, ensuring that digitalisation enhances rather than hinders the well-being of older employees.\u003c/p\u003e\u003cp\u003eResults also reflect the lens of Lakey and Cohen\u0026rsquo;s [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] three theoretical perspectives on social support. Regarding the stress and coping approach, results indicate that digital technologies such as teleworking platforms and communication apps provide implicit support, reducing the stress of isolation in remote work environments. However, older workers also report stress related to the use of technologies and a digital divide, implying that while these technologies can offer stress relief through connection, they can also introduce stress due to the necessity of digital skill adaptation. Tailored digital literacy programs could mitigate this stress, enabling these technologies to fulfil a more effective stress-buffering role.\u003c/p\u003e\u003cp\u003eThe constructionist approach aligns with the findings in the article that digital technologies provide emotional support and self-efficacy for older workers. For instance, apps that offer digital coaching or feedback boost a sense of autonomy and competence, enhancing well-being independent of stress levels. The development of skills and encouragement through technologies like mobile health apps also reinforces self-esteem, aiding workers in managing their roles effectively, even amid digital transitions.\u003c/p\u003e\u003cp\u003eFinally, the relational approach is illustrated by the use of digital technologies such as enterprise social media, which foster relational support by promising communication and collaboration. Relationships formed or maintained through remote platforms enable emotional and informational exchanges that are essential for social companionship. However, insufficient interaction in remote settings can also leads to isolation, signalling the need to balance digital and in-person interactions to foster low-conflict, meaningful connections that enhance well-being.\u003c/p\u003e\u003cp\u003eIn conclusion, digital technologies are reshaping the landscape of social support by offering both implicit and explicit mechanisms for delivering emotional, informational, and instrumental support. When effectively integrated, these technologies enhance communication, collaboration, and social integration among older workers, thereby contributing to improved work experiences and overall well-being [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003eNot applicable\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors declare that the research was conducted without any commercial or financial relationships that could potentially create a conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eAcknowledgement of support\u003c/h2\u003e\u003cp\u003eThe article was created as part of the CA21107 Work Inequalities in Later Life Redefined by Digitalisation (DIGI-net) project, which is supported by COST ACTION.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was partially supported through the actions within project CA\u003cem\u003e21107 Work Inequalities in Later Life Redefined by Digitalisation (DIGI-net)\u003c/em\u003e, supported by COST ACTION.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAcknowledgment of author contribution: CMT and JS conceived and developed the protocol and concept for this review. DAG, AS, NKY, and MM provided feedback for the protocol. Writing the manuscript: CMT, AS, NKY, YG, HB, MM, GY, JS, KN, GK. Quality assessment: NKY, MM, CMT, JS, AS, YG, HB, GY, GK. CMT, AS, NKY, YG, HB, MM, GY, JS, KN, GK, DAG, and JRG undertook title and abstract screening, full-text screening, and full-text review. All authors extracted the data. CMT, JS, AS, NKY, YG, HB, MAM, GY, KN, and GK synthesized data. CMT led the drafting of the manuscript with input from JS, AS, NKY, YG, HB, MAM, GY, KN, JRG and GK. All authors edited and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eOECD. 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Cogn Technol Work. 2024;26:47\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10111-023-00741-7\u003c/span\u003e\u003cspan address=\"10.1007/s10111-023-00741-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"digitalisation, digital technologies, social support, older workers, health","lastPublishedDoi":"10.21203/rs.3.rs-5547499/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5547499/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e\u003cp\u003eThe rapid digitalisation of workplaces has created challenges and opportunities for older workers. This scoping review examines how digital technologies impact social support for older workers, focusing on emotional, informational, and instrumental support within professional environments. Social support is critical for enhancing well-being and sustaining productivity, especially in ageing workforces, yet the effects of digitalisation on social support dynamics remain underexplored.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis review follows Joanna Briggs Institute and PRISMA-ScR guidelines for a scoping review. A comprehensive search strategy was employed across databases like ERIH, Web of Science, Scopus, and PubMed from anytime to 2023 to identify peer-reviewed studies involving digital technologies used by older workers, generally considered as workers aged 50 years or older. Covidence software facilitated the screening of over 5000 scientific papers, study selection, and data extraction, and the Mixed Methods Appraisal Tool (MMAT) assessed quality. Data synthesis encompassed descriptive statistics and narrative analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOut of the 43 selected studies, findings indicate that digital technologies facilitate multiple types of social support. Remote work technology, messaging apps, and telemedicine enhance implicit and explicit social support, such as emotional connections and informational exchanges. However, digitalisation also introduces challenges, with some older workers experiencing isolation and technostress, highlighting the need for targeted digital literacy support.\u003c/p\u003e\u003ch2\u003eDiscussion\u003c/h2\u003e\u003cp\u003eThe findings of this scoping review highlight the dual impact of digital technologieson social support for older workers. While technologies like remote work platforms and messaging apps facilitate emotional connections and information sharing, they can also lead to technostress or even isolate older workers. Implementing tailored digital literacy programs and providing sustained managerial support are essential to help older employees effectively navigate these technologies, thereby enhancing their well-being and productivity in the workplace.\u003c/p\u003e","manuscriptTitle":"Redefining Social Support: The Effect of Digital Technologies on the Social Support of Older Workers. 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