http://orcid.org/0000-0002-1157-884X
Figures
Abstract
Background
The use of social media in healthcare continues to evolve. The purpose of this scoping review was to summarize existing research on the impact of social media interventions and tools among informal caregivers of critically ill patients after patient admission to the intensive care unit (ICU).
Methods
This review followed established scoping review methods, including an extensive a priori-defined search strategy implemented in the MEDLINE, EMBASE, PsycINFO, CINAHL, and the Cochrane CENTRAL Register of Controlled Trials databases to July 10, 2020. Primary research studies reporting on the use of social media by informal caregivers for critically ill patients were included.
Results
We identified 400 unique citations and thirty-one studies met the inclusion criteria. Nine were interventional trials–four randomized controlled trials (RCTs)–and a majority (n = 14) were conducted (i.e., data collected) between 2013 to 2015. Communication platforms (e.g., Text Messaging, Web Camera) were the most commonly used social media tool (n = 17), followed by social networking sites (e.g., Facebook, Instagram) (n = 6), and content communities (e.g., YouTube, SlideShare) (n = 5). Nine studies’ primary objective was caregiver satisfaction, followed by self-care (n = 6), and health literacy (n = 5). Nearly every study reported an outcome on usage feasibility (e.g., user attitudes, preferences, demographics) (n = 30), and twenty-three studies reported an outcome related to patient and caregiver satisfaction. Among the studies that assessed statistical significance (n = 18), 12 reported statistically significant positive effects of social media use. Overall, 16 of the 31 studies reported positive conclusions (e.g., increased knowledge, satisfaction, involvement) regarding the use of social media among informal caregivers for critically ill patients.
Citation: Cherak SJ, Rosgen BK, Amarbayan M, Plotnikoff K, Wollny K, Stelfox HT, et al. (2020) Impact of social media interventions and tools among informal caregivers of critically ill patients after patient admission to the intensive care unit: A scoping review. PLoS ONE 15(9): e0238803. https://doi.org/10.1371/journal.pone.0238803
Editor: Luigi Lavorgna, Universita degli Studi della Campania Luigi Vanvitelli, ITALY
Received: January 3, 2020; Accepted: August 24, 2020; Published: September 11, 2020
Copyright: © 2020 Cherak et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data underlying the results presented in the study are available from the included studies in the review.
Funding: This work was supported by a CIHR Doctoral Research Award to SC (#394654). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. URL: https://cihr-irsc.gc.ca/e/50513.html.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Social media is defined as “websites and applications that enable users to create and share content or to participate in social networking” [1]. Social media tools are platforms and communities, such as Facebook or Skype, that facilitate quick communication and enable interaction among several users at any given time [2]. Social media participation in older age groups is steadily increasing [3], contributing to over 3.2 billion active users worldwide [4]. In considering the various user-generated content and social networking platforms, the role of social media conveys different meanings between users and non-users, age groups (e.g., millennials), and demographic populations. Since technological change is associated with linguistic and cultural changes, the role of social media is constantly in flux [5].
The use of social media in healthcare for increasing speed of communication, distributing accurate information, and promoting knowledge of support, treatments and self-care options is becoming more widespread [6, 7]. Patient- and family-centered healthcare, which acknowledges that patients and their informal caregivers are central figures in decision-making and delivery of care [8], recognizes that patients and caregivers exist within an online social structure and network of relationships [9]. Social media tools, such as real-time communication platforms, educational material, and self-management guides, are now more commonly incorporated in the decision-making process to aid caregivers with making informed decisions regarding their loved one’s care [10].
Critically ill patients are often unable to communicate their care preferences (e.g., due to mechanical ventilation, coma, etc.) including those that are in line with their individual values and goals [11]. In these situations, critically ill patients rely on their informal caregivers to learn about their diagnosis and treatment options, and to make important decisions on their behalf [12]–these situations can be stressful and distressing for an informal caregiver [13]. Family-centered interventions may improve caregiver’s comprehension, satisfaction, and long-term psychological outcomes during and after a family member’s critical illness [13, 14]. Social media tools as family-centered interventions might allow for personalization, presentation, and participation of informal caregivers in their loved one’s care, engaging them in the decision-making process and promoting better patient and informal caregiver outcomes [2, 15]. Despite their potential value, it is unclear whether social media tools can be meaningfully and systematically deployed in critical care medicine [16]. We therefore asked the question: What is the extent, range, and nature of research evidence on the impact of social media interventions and tools among informal caregivers of critically ill patients?
Methods
This scoping review was conducted and reported as per the Arksey-O’Malley 5-stage scoping review method [17]. The approach for this review followed the Scoping Review Methods Manual by the Joanna Briggs Institute [18]. The Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols (PRISMA-P) guideline was used to develop the protocol [19] (S1 Table). We adhered to the PRISMA-ScR Extension for Scoping Reviews [20] to report findings.
Populations, settings, and study designs
Inclusion criteria were as follows: (1) primary quantitative or qualitative research; (2) reporting on social media use with at least one informal caregiver as an end-user; (3) conducted with informal caregivers of critically ill patients of any age group; and (4) in any language or publication year. Studies were excluded if they were not primary research (e.g., reviews or editorials), did not report on caregiver use of social media, or were not conducted in a critical care population. For the purposes of this review, we defined: (1) a caregiver as any informal (i.e., non-clinical) person who regularly provides support to the patient and is in some way directly implicated in the patient’s care or directly affected by the patient’s health problem (e.g., family, friend); (2) social media as any form of electronic communication that allow users to share information and other content and create online communities; and (3) critically ill patients as any persons who are currently admitted to an intensive care unit (ICU) or had previously been admitted to an ICU. Studies were excluded if only abstracts were available.
Data sources and searches
Comprehensive literature searches were conducted in MEDLINE, EMBASE, PsycINFO, CINAHL, and the Cochrane CENTRAL Register of Controlled Trials. The search strategies for each database were developed with a Medical Librarian (DLL) and were revised after reviewing preliminary search results. The search strategies combined synonyms and subject headings from three concepts: 1) caregivers; 2) critical care; and 3) social media. A search of the Cochrane Database of Systematic Reviews was undertaken to identify review articles related to the research question and their reference lists were screened to identify potential studies missed in the search. All databases were searched from inception to July 10, 2020. Reference lists of included papers were reviewed to identify potential studies missed in the search. No language or date limits were applied. The complete MEDLINE search strategy is shown in S2 Table.
Study selection
After a subset of the team (SC, MA) achieved 100% agreement on a pilot-test of 50 random studies, all titles and abstracts were reviewed independently in duplicate by two reviewers (SC, MA). Any study selected by either reviewer at this stage progressed to the next stage. The full-text of all articles was reviewed independently in duplicate by two reviewers (SC, MA); articles selected by both reviewers at this stage were included in the final review. Disagreements were resolved by discussion or the involvement of a third reviewer (BR) when necessary. References were managed in Endnote X9 (Clarivate Analytics, Philadelphia, PA, USA).
Data charting
Two reviewers (SC, KP) abstracted data independently and in duplicate for each included study using a data collection sheet developed and piloted by the review team. Discrepancies were resolved through discussion with a third reviewer (MA). Information on document characteristics (e.g., year of publication, geographic location), study characteristics (e.g., setting), caregiver group (e.g., spouses, parents, family caregivers), social media tool used (e.g., communication platform, content community, social networking site, blog or microblog), objectives and outcome measures of social media use, statistical significance, and authors’ conclusions were collected. Studies that examined social media as one component of a complex intervention were noted as such.
Data synthesis and analysis
Findings were synthesized descriptively to map different areas of the literature as outlined in the research question. Using a social media framework described in previous research [6], we categorized social media tools into five categories: collaborative projects (e.g., EndNote, Slack), blogs or microblogs (e.g., WordPress, Twitter), content communities (e.g., YouTube, SlideShare), social networking sites (e.g., Facebook, Instagram), and real-time communication platforms (e.g., Text Messaging, Web Camera, FaceTime) (S3 Table). Study objectives and outcomes were classified according to an adaptation from those outlined in Coulter and Ellins [21] proposed framework for strategies to inform, educate and involve patients (S4 Table). The main objective from each study was categorized into one of five categories: to improve health literacy, clinical decision making, self-care, patient safety or other. Outcomes reported in each study were classified as patient and caregiver knowledge, patient and caregiver experience, use of services and cost, health behaviors and health status, and usage feasibility. Studies that reported statistically significant outcomes determined by p<0.05 related to the main objective of the study were classified as “statistically significant.” Studies that reported outcomes that were not statistically significant were classified as “not statistically significant,” and if a study did not assess significance through statistical equations that study was classified as “not assessed.” Descriptive statistics were calculated using STATA IC 15 (StataCorp. Stata Statistical Software: Release 15. College Station, TX: StataCorp LLC).
Results
We screened 400 unique abstracts and reviewed 72 full-text articles; 41 full-text articles were excluded, the most common reasons being that the study did not report original research (n = 15/41) or that the study did not report on social media use (n = 12/41) (Fig 1). Hand searching resulted in the inclusion of seven additional studies. There was 85% agreement on title and abstract screening and 89% agreement on full-text screening.
Description of included studies
The 31 included studies [22–52] were published between 2000 and 2020 and primarily conducted in North America (n = 20, 65%) or Europe (n = 9, 29%), and with neonatal or pediatric critical care populations (n = 23, 74%) (Table 1). Fig 2A depicts the different ICU types from the included studies. The median start date was 2015 (range: 1997–2016) and the median duration was 19 months (range: 3–95 months). Many studies (n = 9, 33%) were interventional studies [22, 23, 27, 29, 30, 32, 33, 39, 48] of which most were conducted in neonatal ICUs (6/9). We included six qualitative studies and most (4/6) were conducted with neonatal or pediatric critical care populations. Caregivers were most commonly parents (n = 19, 61%) [30, 31, 33, 35–38, 41–44, 47–49, 51, 52] and unspecified family caregivers more broadly—which could include parents, but the term was more broadly defined (n = 7, 23%) [23, 24, 26, 27, 32, 39, 50]. One study was specific to mothers [40] and one study was specific to fathers [45]. Few studies reported additional perspectives from members of the clinical care team (e.g., nurses, primary care physicians) (n = 3, 10%) [29, 34, 50] or critical care patients (n = 3, 10%) [22, 28, 49]. More than half of the studies examined real-time communication platforms (e.g., FaceTime, Skype) (n = 17, 55%) [23, 24, 28, 30–40, 47, 51, 52], which accounted for many of the studies conducted with adult populations (3/7, 43%) and most of the studies conducted with neonatal or pediatric populations (14/22, 64%).
A ICU type; B specific social media tool in the included studies.
Social media tools
Included studies were categorized by the type of social media tool used (S3 Table). Fig 2B depicts the different specific social media tools from the included studies. Real-time communication platforms, that allowed user communication with messages, voice, and/or video, were the most common social media tool used (n = 15, 56%), followed by social networking sites (n = 6, 19%) and content communities (n = 5, 16%). Few studies (n = 2, 7%) assessed the use of blog or microblogs and only two studies examined social media use in general. Overall, most social media tools included functions that operated like communication platforms, such that they provided the option for users to post and share experiences. Many studies (n = 8, 30%) included a social media tool as part of a complex intervention, and most of these studies (n = 6/8) used mobile phones to facilitate the social media component. All of these studies (n = 6/6) reported that the ubiquitous nature and technical capacity of mobile phones were strong motivating factors. Several of these studies (n = 5/6) addressed potential misuse of information and privacy concerns over text messaging by an established mobile phone dedicated to the study, and provided recommendations to the clinical care team (i.e., nurses, physicians) for text messaging with informal caregivers.
Objectives of social media use
The most common intended use of social media was for caregiver satisfaction (n = 9, 29%). Most studies that examined caregiver satisfaction used communication platforms (n = 8/9). Social networking sites were often used to improve self-care (n = 2/6, 30%), and content communities were mainly intended to improve patient safety (n = 2/4, 50%). There were few studies that addressed clinical decision making (n = 4, 13%) and half (n = 2/4) used content communities. Five studies (16%) did not fit the framework, and were classified as “other”; three of these studies reported the prevalence of social networking use (n = 1) or of internet use more broadly (n = 2), and two compared mothers and fathers use of information and communication technology (n = 1) or frequency and length of webcam viewing (n = 1).
Outcomes and measures
Usage feasibility and patient and caregiver experience outcomes were most commonly reported (n = 30 and n = 23, respectively) (Table 2). Patient and caregiver knowledge outcomes were reported in 16 studies (52%), and use of services and cost outcomes, and health behaviors and health status outcomes were reported in eight studies each. Among outcomes related to usage feasibility (n = 30), measures of usage and demographics were most common (n = 22, 73%) and were often accompanied by measures of users’ attitudes and preferences (n = 20, 67%). Measures of patient or caregiver satisfaction or of clinician-patient/caregiver communication were most commonly reported for outcomes related to patient and caregiver experience (n = 13 and n = 12, respectively). Fig 3A provides a summary of outcomes as they relate to the study objectives. There were no defining trends between outcomes with regard to objectives for social media use, but measures related to the use of services and cost, or to health behaviors and health status, were generally least reported among any objective. One study reported outcomes related to potential for unintended consequences or harm from social media tools [50].
(A) patient and caregiver focused objectives1,2,3; (B) Authors’ conclusions on social media use with regard to patient and caregiver focused objectives1,2,4. 1Adapted from Coulter and Ellins, 2007; 2Only the main study objective was recorded from a single study; 3More than one outcome category could be recorded from a single study; 4Only one overall conclusion was recorded from each study. Frequency indicated by color: red, very frequent; yellow, moderately frequent; green, infrequent. N, number of studies.
Evaluation of social media use
Fig 4 shows trends of authors’ conclusion by years of data collection, sample size, study design, and statistical significance. A positive effect of social media use was reported by majority of studies within each 2-year timeframe of years of data collection, except for 2013–2015 (Fig 4A). Studies that collected data during and/or after 2016 reported only positive, negative or indeterminate effects of social media use. Majority of studies with a sample size >300 reported a negative effect, and majority of studies with a sample size 100–300 or <100 reported a positive effect (Fig 4B). Prospective observational studies commonly reported a neutral effect and the majority of prospective intervention studies reported a positive effect (Fig 4C). Among the studies that assessed statistical significance, the majority determined that social media use had a positive effect (Fig 4D).
(A) years of data collection1; (B) sample size; (C) study design; (D) statistical significance. 1For eight studies year of publication was used as timeframe of data collection was not reported.
The most common type of study design was interventional (n = 9, 29%)—of which 4 were controlled by randomization (i.e., RCTs)—followed by prospective cohort (n = 8, 26%) and qualitative (n = 6, 19%). Of the quantitative studies (n = 25, 68%), majority assessed statistical significance (n = 20/25) and majority determined there was a significantly positive effect of social media use (n = 12/20). Among the randomized interventions (n = 4), two found a significantly positive effect, one found a significantly negative effect and one did not assess statistical significance. Fig 3B provides a summary of authors’ conclusions of social media use with regard to study objectives. The majority of studies with the objectives of improving health literacy, self-care, patient safety or caregiver satisfaction, reported a statistically significant positive effect. Among the four studies that aimed to improve clinical decision making, one study reported a positive effect but did not assess statistical significance, and three studies reported a negative effect but only two assessed significance.
Discussion
We used scoping review methodology to synthesize the literature on the extent, range, and nature of research evidence on the impact of social media interventions and tools among informal caregivers of critically ill patients. There is a growing body of literature, primarily from neonatal or pediatric populations, suggesting that real-time communication platforms are now commonly used social media tools among informal caregivers of critically ill patients. In contrast, there is very little literature regarding caregiver use of social networking sites, blogs, or content communities. The most common intended use for social media was to improve caregiver satisfaction with the experience and role of an informal caregiver of a critically ill patient. Outcomes related to usage feasibility, such as measures of user’s attitudes, preferences, and demographics, were nearly always reported. Few studies assessed cost-effectiveness of using social media tools with informal caregivers, and outcomes related to health behaviors and health status of either the patient or caregiver were reported infrequently. Although most studies concluded that the use of social media among informal caregivers is beneficial and meaningful, the potential for unintended consequences or harm specific to informal caregivers were not adequately explored. The low reliability and high variability of content shared on social media highlights the importance of control from medical personnel to avoid the spread of “fake news” [53]. The emerging utilization of social media tools among informal caregivers for critically ill patients have practical implications for critical care medicine.
Modern mobile phones are powerful computational devices. The technical capacity of mobile phones to facilitate phone-based health interventions was a motivating factor for several included studies. Mobile phones are also omnipresent and nearly always at hand [54], which makes it possible to increase the number of points of care to virtually any place and time [55]. The combination of the technical capacity, personal nature, and convenient proximity of mobile phones has reduced barriers to adoption and increased acceptance of phone-based health interventions in numerous healthcare settings [56]. The immediacy of access of mobile phones might also be useful to informal caregivers after patient discharge by providing prompt advice and support, which may reduce healthcare costs by preventing hospital or ICU readmission.
Mobile phones in healthcare settings also have disadvantages. With regard to nursing, disruption of workflow, interruption of practice, and improper usage have been reported [57]. For example, in the study conducted by Piscotty and colleagues [58], 67% of nurses checked their mobile phone more than 2 times per shift and 22% checked their mobile phone more than 10 times per shift. Further, possibility of misuse of information that may violate patient privacy remains an unresolved problem [59]. Nursing organizations have responded with guidelines on professional social media use in the workplace [60–62]. Many included studies addressed potential privacy issues by an established mobile phone dedicated to the study, and recommended to refrain from using patient last names and conditions, to keep communications brief, and to destroy caregiver phone numbers after patient discharge [63]. That mobile phones may be useful to facilitate social media interventions in critical care medicine is a noteworthy finding of this review, but further research is needed on how social media strategies can be implemented into practice without violating privacy or ethical considerations.
Support and encouragement can contribute to caregiver confidence, which can promote better understanding of a stressful illness-related situation and enable the caregiver to provide better care [64]. Many included studies found that caregivers reported a more satisfactory critical care experience and increased knowledge of a patient’s condition and long-term treatment options when provided with links to online resources with credible information. In the last decade, several members of the United States Critical Care Societies Collaborative have started using social media [65]. The Society of Critical Care Medicine is one member, which uses web-based education initiatives to provide accurate and reliable information to educate their members and the public [15]. As well, The World Federation of Societies of Intensive and Critical Care Medicine also recognized that social media plays a large role in achieving more and better involvement with other member societies, and actively uses social media to liaise with important groups, such as young clinicians [66]. Considering the differences in how critical care societies use diverse approaches to deliver overlapping educational content can provide a rich opportunity to inform development of future web-based education initiatives, targeted specifically at informal caregivers.
Real-time communication platforms have been studied and implemented in many healthcare settings [67, 68]. Several included studies found that in neonatal ICU populations, parents who were communicating with the clinical care team using videoconferencing instruments (e.g., FaceTime, Skype) felt significantly more satisfied with their infants’ care when they were unable to be physically present. No study conducted in adult ICU populations used a social media tool dedicated entirely to videoconferencing, although most social media tools included functions which operated similar to communication platforms. Further, no included study from any ICU reported the use of communication platforms to engage non-local family members or young children who may benefit from remote communication with their loved one. Since many communication platforms are free to download on most electronic devices and allow for multiple users at once, an important area for future research is the use of communication platforms by entire support groups of both adult and non-adult critical care patients. This type of research is warranted to determine if positive outcomes of communication platforms depend on whether the caregivers’ relationship to the patient is parent-child (i.e., parent providing support to children) versus child-parent (i.e., children providing support to parents).
It is important to recognize that social media tools are exactly that—tools—rather than a substitute for personal interaction with healthcare providers. Recent studies in other healthcare settings have found that patients’ value in-person interaction with healthcare providers more than social media communication, and that healthcare providers are regarded as the most important source of information [69]. Knowledge on the values and preferences of the clinical care team, however, is lacking, and a common concern of many clinicians is that information shared on social media may not always be accurate. More understanding on physician preferences and social media accuracy is important as physicians often rely on patients’ informal caregivers to make decisions regarding the patient’s care, which frequently contributes to caregiver psychological morbidity [70]. Individualized social media interventions adapted to caregiver preferences may improve caregiver’s satisfaction and psychological morbidity [13]. More research on accurate, proper and potential use of social media in critical care medicine is required before implementation into daily practice.
Our review indicates there is untapped potential for social media interventions and tools to provide personalized support to informal caregivers of the critically ill. We recommend future inquiry on this topic examine mental health interventions using social media to determine the effect of social media mental health interventions on psychological outcomes of informal caregivers of the critically ill. This information is particularly relevant to challenges related to restricted visitation and social isolation associated with the COVID-19 pandemic [71]. The large numbers of patients experiencing critical illness and visiting restrictions enacted to prevent the spread of COVID-19 complicate participation of informal caregivers in patient care and recovery [72]. These factors are likely to make mental health consequences of critical illness on informal caregivers more prevalent and severe [73, 74]. Social media interventions and tools may be an effective mode of mental health support for informal caregivers of critically ill patients.
This scoping review has several strengths. We conducted an extensive literature search and screened reference lists of included studies in order to identify the full breadth of available literature on social media use in critical care populations. The search was executed in five bibliographic databases and was not restricted by language or dates. It was intentionally broad to ensure that social media use across all critical care populations were included. We followed rigorous methodology defined by adherence to recommended protocols and reporting criteria for scoping reviews. Further, the interdisciplinary team of a critical care physician, a critical care nurse, and a psychiatric epidemiologist, offered complementary expertise and knowledge. In spite of these strengths, there are limitations to note. We did not search the grey literature nor did we search social media itself, and could have missed studies, though our search strategy was comprehensive and full-text hand searching was completed. As well, the lack of a universal definition for social media, since social media is a relatively new concept that is continually transforming, added complexity to the process of study selection. However, our broad inclusion of study design allowed us to produce a comprehensive summary of the state of the literature on social media use by informal caregivers in critical care medicine. Ultimately, the relatively rapid evolution of social media means studies on usage will nearly exclusively reflect social media use of the past. Though such studies are valuable, it is important to note that the medium of social media is evolving faster than it is being studied.
Conclusions
There is a growing evidence base to support the use of social media among informal caregivers of critically ill patients. There is untapped potential for social media tools to provide personalized support to informal caregivers. Social media tools might enable informal caregivers to gain the knowledge that they need in order to feel empowered, involved, and satisfied. Social media users should exercise caution on applications and networking sites so as not to compromise patient privacy. In sum, social media represents a flexible medium to deliver health information, and the individualized support that caregivers can obtain through using social media may promote an invaluable collaborative relationship when caring for critically ill patients.
Supporting information
S1 Table. Preferred Reporting Items for Systematic review and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR).
https://doi.org/10.1371/journal.pone.0238803.s001
(DOCX)
S3 Table. Categorization of social media tools.
https://doi.org/10.1371/journal.pone.0238803.s003
(DOCX)
S4 Table. Patient and caregiver focused objectives and outcomes.
https://doi.org/10.1371/journal.pone.0238803.s004
(DOCX)
S5 Table. Summarized findings on social media outcomes with regard to patient and caregiver focused objectives.
https://doi.org/10.1371/journal.pone.0238803.s005
(DOCX)
S6 Table. Authors’ conclusions on social media use with regard to patient and caregiver focused objectives.
https://doi.org/10.1371/journal.pone.0238803.s006
(DOCX)
Acknowledgments
We thank Dr. Diane Lorenzetti (University of Calgary) for the development of the search strategies.
References
- 1. Dictionary O. Social media.: Oxford Dictionary; 2019 [cited 2019 October 2]. Available from: https://www.lexico.com/en/definition/social_media.
- 2. Barrett KP, Mac Sweeney R. Social Media in Critical Care. Int Anesthesiol Clin. 2019;57(2):103–17. Epub 2019/03/14. pmid:30864994.
- 3.
Statista. Social media—Statistics & Facts 2019 [cited 2019 October 2]. Available from: https://www.statista.com/topics/1164/social-networks/.
- 4.
Statsita. Leading social networks worldwide as of July 2019, ranked by numbers of active users (in millions). Statista; 2019 [cited 2019 October 2]. Available from: https://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users/.
- 5. Perrin A. Social Media Usage: 2005–2015. Pew Research Ceter. 2015.
- 6. Kaplan AM, Haenlein M. Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons. 2010;53(1):59–68. pmid:45641953.
- 7. Moccia M, Brigo F, Tedeschi G, Bonavita S, Lavorgna L. Neurology and the Internet: a review. Neurol Sci. 2018;39(6):981–7. Epub 2018/03/30. pmid:29594831.
- 8. Mackie BR, Mitchell M, Marshall AP. Patient and family members' perceptions of family participation in care on acute care wards. Scand J Caring Sci. 2019;33(2):359–70. Epub 2018/12/07. pmid:30507038.
- 9. Moorhead SA, Hazlett DE, Harrison L, Carroll JK, Irwin A, Hoving C. A new dimension of health care: systematic review of the uses, benefits, and limitations of social media for health communication. J Med Internet Res. 2013;15(4):e85. Epub 2013/04/26. pmid:23615206; PubMed Central PMCID: PMC3636326.
- 10. Ventola CL. Social media and health care professionals: benefits, risks, and best practices. P T. 2014;39(7):491–520. Epub 2014/08/02. pmid:25083128; PubMed Central PMCID: PMC4103576.
- 11. Anstey MH, Litton E, Jha N, Trevenen ML, Webb S, Mitchell IA. A comparison of the opinions of intensive care unit staff and family members of the treatment intensity received by patients admitted to an intensive care unit: A multicentre survey. Aust Crit Care. 2019;32(5):378–82. Epub 2018/11/18. pmid:30446268.
- 12. White DB, Angus DC, Shields AM, Buddadhumaruk P, Pidro C, Paner C, et al. A Randomized Trial of a Family-Support Intervention in Intensive Care Units. N Engl J Med. 2018;378(25):2365–75. Epub 2018/05/24. pmid:29791247.
- 13. Bibas L, Peretz-Larochelle M, Adhikari NK, Goldfarb MJ, Luk A, Englesakis M, et al. Association of Surrogate Decision-making Interventions for Critically Ill Adults With Patient, Family, and Resource Use Outcomes: A Systematic Review and Meta-analysis. JAMA Netw Open. 2019;2(7):e197229. Epub 2019/07/20. pmid:31322688; PubMed Central PMCID: PMC6646989.
- 14. Fiest KM, McIntosh CJ, Demiantschuk D, Leigh JP, Stelfox HT. Translating evidence to patient care through caregivers: a systematic review of caregiver-mediated interventions. BMC Med. 2018;16(1):105. Epub 2018/07/13. pmid:29996850; PubMed Central PMCID: PMC6042352.
- 15. Barnes SS, Kaul V, Kudchadkar SR. Social Media Engagement and the Critical Care Medicine Community. J Intensive Care Med. 2018:885066618769599. Epub 2018/04/28. pmid:29699469.
- 16. Richardson B, Dol J, Rutledge K, Monaghan J, Orovec A, Howie K, et al. Evaluation of Mobile Apps Targeted to Parents of Infants in the Neonatal Intensive Care Unit: Systematic App Review. JMIR mHealth and uHealth. 2019;7(4):e11620. https://dx.doi.org/10.2196/11620.
- 17. Arksey H. Scoping the field: services for carers of people with mental health problems. Health Soc Care Community. 2003;11(4):335–44. Epub 2003/11/25. pmid:14629205.
- 18. Joanna Briggs I. The Joanna Briggs Institute best practice information sheet: the effectiveness of pelvic floor muscle exercises on urinary incontinence in women following childbirth. Nurs Health Sci. 2011;13(3):378–81. Epub 2011/06/22. pmid:21689258.
- 19. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4:1. Epub 2015/01/03. pmid:25554246; PubMed Central PMCID: PMC4320440.
- 20. Tricco AC, Lillie E, Zarin W, O'Brien KK, Colquhoun H, Levac D, et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med. 2018;169(7):467–73. Epub 2018/09/05. pmid:30178033.
- 21. Coulter A, Ellins J. Effectiveness of strategies for informing, educating, and involving patients. BMJ. 2007;335(7609):24–7. Epub 2007/07/07. pmid:17615222; PubMed Central PMCID: PMC1910640.
- 22. Loudet CIM, Maria Cecilia; Maradeo , Maria Roxana; Fernandez , Silvia Laura; Romero , Maria Victoria; Valenzuela , Graciela Esther; Herrera , Eustaquia Isabel; et al. Reducing pressure ulcers in patients with prolonged acute mechanical ventilation: a quasi-experimental study. Diminuicao das ulceras por pressao em pacientes com ventilacao mecanica aguda prolongada: um estudo quasi-experimental. 2017;29(1):39–46. https://dx.doi.org/10.5935/0103-507X.20170007.
- 23. de Havenon AP, Casey; Tanana, Michael; Wold, Jana; Hoesch, Robert. A pilot study of audiovisual family meetings in the intensive care unit. Journal of critical care. 2015;30(5):881–3. https://dx.doi.org/10.1016/j.jcrc.2015.05.027.
- 24. Hoffmann MH, Anna K.; Burgsteiner Harald; Eller Philipp; Pieber Thomas R.; Amrein Karin. Prioritizing information topics for relatives of critically ill patients: Cross-sectional survey among intensive care unit relatives and professionals. Wiener klinische Wochenschrift. 2018;130(21–22):645–52. https://dx.doi.org/10.1007/s00508-018-1377-1.
- 25. Nguyen Y-LP, Raphael Argaud, Laurent Piquilloud, Lise Guitton, Christophe Tamion, Fabienne Hraiech, Sami ; et al. "ReaNet", the Internet utilization among surrogates of critically ill patients with sepsis. PloS one. 2017;12(3):e0174292. https://dx.doi.org/10.1371/journal.pone.0174292.
- 26. Hetland BM, Natalie Perazzo, Joseph Hickman, Ronald . A qualitative study of factors that influence active family involvement with patient care in the ICU: Survey of critical care nurses. Intensive & critical care nursing. 2018;44:67–75. https://dx.doi.org/10.1016/j.iccn.2017.08.008.
- 27. Mistraletti GU, Michele Mantovani, Elena Silvia Moroni, Benedetta Formenti, Paolo Spanu, Paolo Anania, Stefania ; et al. A family information brochure and dedicated website to improve the ICU experience for patients' relatives: an Italian multicenter before-and-after study. Intensive care medicine. 2017;43(1):69–79. https://dx.doi.org/10.1007/s00134-016-4592-0.
- 28. Shiber JT, Ayesha Northcutt, Ashley . Communicating While Receiving Mechanical Ventilation: Texting With a Smartphone. American journal of critical care: an official publication, American Association of Critical-Care Nurses. 2016;25(2):e38–9. https://dx.doi.org/10.4037/ajcc2016695.
- 29. Robertson A. Effects of a social media website on primary care givers' awareness of music therapy services in a neonatal intensive care unit. The Arts in Psychotherapy. 2016;50:17–21. http://dx.doi.org/10.1016/j.aip.2016.05.006.
- 30. Epstein EGS, Jessica Blackman, Amy Sinkin, Robert A. Testing the Feasibility of Skype and FaceTime Updates With Parents in the Neonatal Intensive Care Unit. American journal of critical care: an official publication, American Association of Critical-Care Nurses. 2015;24(4):290–6. https://dx.doi.org/10.4037/ajcc2015828.
- 31. Flores-Fenlon NS, Ashley Y.; Yeh Amy; Gateau Kameelah; Vanderbilt Douglas L.; Kipke Michele; Friedlich Philippe; et al. Smartphones and Text Messaging are Associated With Higher Parent Quality of Life Scores and Enrollment in Early Intervention After NICU Discharge. Clinical pediatrics. 2019;58(8):903–11. https://dx.doi.org/10.1177/0009922819848080.
- 32. Gund A, Sjoqvist BA, Wigert H, Hentz E, Lindecrantz K, Bry K. A randomized controlled study about the use of eHealth in the home health care of premature infants. BMC Med Inform Decis Mak. 2013;13:22. Epub 2013/02/12. pmid:23394465; PubMed Central PMCID: PMC3583709.
- 33. Globus O, Leibovitch L, Maayan-Metzger A, Schushan-Eisen I, Morag I, Mazkereth R, et al. The use of short message services (SMS) to provide medical updating to parents in the NICU. J Perinatol. 2016;36(9):739–43. Epub 2016/05/20. pmid:27195981.
- 34. Joshi A, Chyou PH, Tirmizi Z, Gross J. Web Camera Use in the Neonatal Intensive Care Unit: Impact on Nursing Workflow. Clin Med Res. 2016;14(1):1–6. Epub 2016/02/13. pmid:26864509; PubMed Central PMCID: PMC4851448.
- 35. Kim HNG, Craig Lee, Young Seok. Paternal and maternal information and communication technology usage as their very low birth weight infants transition home from the NICU. International Journal of Human-Computer Interaction. 2015;31(1):44–54. http://dx.doi.org/10.1080/10447318.2014.959102.
- 36. Lindberg B, Axelsson K., Ohrling K. Taking care of their baby at home but with nursing staff as support: The use of videoconferencing in providing neonatal support to parents of preterm infants. Journal of Neonatal Nursing. 2009;15:47–55.
- 37. Orr TC-Y, Marsha Benoit, Britney Hewitt, Brenda Stinson, Jennifer McGrath, Patrick . Smartphone and Internet Preferences of Parents: Information Needs and Desired Involvement in Infant Care and Pain Management in the NICU. Advances in neonatal care: official journal of the National Association of Neonatal Nurses. 2017;17(2):131–8. https://dx.doi.org/10.1097/ANC.0000000000000349.
- 38. Rhoads SJG, Angela Gauss, C. Heath Mitchell, Anita Pate, Barbara . Web Camera Use of Mothers and Fathers When Viewing Their Hospitalized Neonate. Advances in neonatal care: official journal of the National Association of Neonatal Nurses. 2015;15(6):440–6.
- 39. Robinson CG, Anna Sjoqvist, Bengt-Arne Bry, Kristina . Using telemedicine in the care of newborn infants after discharge from a neonatal intensive care unit reduced the need of hospital visits. Acta paediatrica (Oslo, Norway: 1992). 2016;105(8):902–9. https://dx.doi.org/10.1111/apa.13407.
- 40. Weems MFG I.; Lan R.; DeBaer L. R.; Beeman G. Electronic communication preferences among mothers in the neonatal intensive care unit. Journal of perinatology: official journal of the California Perinatal Association. 2016;36(11):997–1000. https://dx.doi.org/10.1038/jp.2016.125.
- 41. Lakshmanan AS, Eilann McCormick, Marie C. Belfort, Mandy . Parental preference and ability to participate in web-based developmental screening and surveillance: preliminary evidence for preterm infants after NICU discharge. Clinical pediatrics. 2014;53(13):1278–84. https://dx.doi.org/10.1177/0009922814541801.
- 42. Safran CP-W, Grace Emery, Hampers D., Lou. Collaborative Approaches to e-Health: Valuable for Users and Non-users. Studies in health technology and informatics. 2005;116:879–84.
- 43. Coppola GC, Rosalinda Bosco, Andrea Papagna, Sonia . In search of social support in the NICU: features, benefits and antecedents of parents' tendency to share with others the premature birth of their baby. The journal of maternal-fetal & neonatal medicine: the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians. 2013;26(17):1737–41. https://dx.doi.org/10.3109/14767058.2013.798281.
- 44. Gabbert TIM, Boris; Buhrer, Christoph; Garten, Lars. Use of social networking sites by parents of very low birth weight infants: experiences and the potential of a dedicated site. European journal of pediatrics. 2013;172(12):1671–7. https://dx.doi.org/10.1007/s00431-013-2067-7.
- 45. Kim HNW, Tami H.; Li Xueping; Gaylord Mark. Use of Social Media by Fathers of Premature Infants. The Journal of perinatal & neonatal nursing. 2016;30(4):359–66.
- 46. Jones CWL, Mary R. Blogs Written by Families During Their Child's Hospitalization: A Thematic Narrative Analysis. Journal of pediatric nursing. 2018. https://dx.doi.org/10.1016/j.pedn.2018.03.011.
- 47. Braner DAVL Susanna; Hodo Richard; Ibsen Laura A.; Bratton Susan L.; Hollemon Desiree; Goldstein Brahm. Interactive Web sites for families and physicians of pediatric intensive care unit patients: a preliminary report. Pediatric critical care medicine: a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2004;5(5):434–9.
- 48. Gray JE, Safran C, Davis RB, Pompilio-Weitzner G, Stewart JE, Zaccagnini L, et al. Baby CareLink: using the internet and telemedicine to improve care for high-risk infants. Pediatrics. 2000;106(6):1318–24. Epub 2000/01/11. pmid:11099583.
- 49. Badke CM, Essner BS, O'Connell M, Malakooti MR. An Innovative Virtual Reality Experience in the PICU: A Pilot Study. Pediatric critical care medicine: a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2019;20(6):e283–e6. https://dx.doi.org/10.1097/PCC.0000000000001917.
- 50. Das A, Anstey M, Bass F, Blythe D, Buhr H, Campbell L, et al. Internet health information use by surrogate decision makers of patients admitted to the intensive care unit: a multicentre survey. Critical care and resuscitation: journal of the Australasian Academy of Critical Care Medicine. 2019;21(4):305–10.
- 51. Hughes Driscoll CA, Jahrsdoerfer M, Easter L, El-Metwally D. Research: Parental Perceptions on Smartphone Use for Clinical Mobility. Biomedical instrumentation & technology. 2020;54(1):22–7. https://dx.doi.org/10.2345/0899-8205-54.1.22.
- 52. Williams L, I'Anson J, Malarkey M, Purcell A, de Vries N, McKinlay C. Information sharing in neonatal intensive care: Parental perceptions and preferences. Journal of paediatrics and child health. 2020. https://dx.doi.org/10.1111/jpc.14842.
- 53. Lavorgna L, De Stefano M, Sparaco M, Moccia M, Abbadessa G, Montella P, et al. Fake news, influencers and health-related professional participation on the Web: A pilot study on a social-network of people with Multiple Sclerosis. Mult Scler Relat Disord. 2018;25:175–8. Epub 2018/08/11. pmid:30096683.
- 54. Krishna S, Boren SA. Diabetes self-management care via cell phone: a systematic review. J Diabetes Sci Technol. 2008;2(3):509–17. Epub 2008/05/01. pmid:19885219; PubMed Central PMCID: PMC2769746.
- 55. Testa MAT R. R.; Simonson D. C. Patient adherence and accuracy using electronic diaries during remote patient monitoring in type 1 and type 2 diabetes. Diabetes. 2009;58(SUPPL. 1A).
- 56. Kaplan WA. Can the ubiquitous power of mobile phones be used to improve health outcomes in developing countries? Global Health. 2006;2:9. Epub 2006/05/25. pmid:16719925; PubMed Central PMCID: PMC1524730.
- 57. Piscotty R, Voepel-Lewis T, Lee SH, Annis-Emeott A, Lee E, Kalisch B. To tweet or not to tweet? Nurses, social media, and patient care. Nurs Manage. 2013;44(5):52–3. Epub 2013/04/24. pmid:23608943.
- 58. Piscotty RJ Jr., Kalisch B, Gracey-Thomas A. Impact of Healthcare Information Technology on Nursing Practice. J Nurs Scholarsh. 2015;47(4):287–93. Epub 2015/05/08. pmid:25950795.
- 59. Gurol-Urganci I, de Jongh T, Vodopivec-Jamsek V, Atun R, Car J. Mobile phone messaging reminders for attendance at healthcare appointments. Cochrane Database Syst Rev. 2013;(12):CD007458. Epub 2013/12/07. pmid:24310741; PubMed Central PMCID: PMC6485985.
- 60.
Social Media Guidelines for Nurses Registered Nurses’ Association of Ontario [cited 2019 October 3]. Available from: Categorization of objectives and outcomes.
- 61. Morgan C, Barry C, Barnes K. Master's programs in advanced nursing practice: new strategies to enhance course design for subspecialty training in neonatology and pediatrics. Adv Med Educ Pract. 2012;3:129–37. Epub 2012/01/01. pmid:23762011; PubMed Central PMCID: PMC3650880.
- 62. Spector N, Kappel DM. Guidelines for using electronic and social media: the regulatory perspective. Online J Issues Nurs. 2012;17(3):1. Epub 2012/10/06. pmid:23036057.
- 63. Mallow JA, Theeke LA, Theeke E, Mallow BK. The effectiveness of mI SMART: A nurse practitioner led technology intervention for multiple chronic conditions in primary care. Int J Nurs Sci. 2018;5(2):131–7. Epub 2018/03/31. pmid:31406814; PubMed Central PMCID: PMC6626240.
- 64.
Reinhard SC, Given B, Petlick NH, Bemis A. Supporting Family Caregivers in Providing Care. In: Hughes RG, editor. Patient Safety and Quality: An Evidence-Based Handbook for Nurses. Advances in Patient Safety. Rockville (MD)2008.
- 65. Carroll CL, Dangayach NS, Khan R, Carlos WG, Harwayne-Gidansky I, Grewal HS, et al. Lessons Learned From Web- and Social Media-Based Educational Initiatives by Pulmonary, Critical Care, and Sleep Societies. Chest. 2019;155(4):671–9. Epub 2018/12/31. pmid:30594560.
- 66. The World Federation of Societies of Intensive and Critical Care Medicine Newsletter. 2018;4(1).
- 67. Alvarez-Jimenez M, Alcazar-Corcoles MA, Gonzalez-Blanch C, Bendall S, McGorry PD, Gleeson JF. Online, social media and mobile technologies for psychosis treatment: a systematic review on novel user-led interventions. Schizophr Res. 2014;156(1):96–106. Epub 2014/04/22. pmid:24746468.
- 68. Young SD, Rivers C, Lewis B. Methods of using real-time social media technologies for detection and remote monitoring of HIV outcomes. Prev Med. 2014;63:112–5. Epub 2014/02/12. pmid:24513169; PubMed Central PMCID: PMC4031268.
- 69. Smailhodzic E, Hooijsma W, Boonstra A, Langley DJ. Social media use in healthcare: A systematic review of effects on patients and on their relationship with healthcare professionals. BMC Health Serv Res. 2016;16:442. Epub 2016/08/27. pmid:27562728; PubMed Central PMCID: PMC5000484.
- 70. Kon AA, Davidson JE. Retiring the Term Futility in Value-Laden Decisions Regarding Potentially Inappropriate Medical Treatment. Crit Care Nurse. 2017;37(1):9–11. Epub 2017/02/06. pmid:28148610.
- 71. Robert R, Kentish-Barnes N, Boyer A, Laurent A, Azoulay E, Reignier J. Ethical dilemmas due to the Covid-19 pandemic. Ann Intensive Care. 2020;10(1):84. Epub 2020/06/20. pmid:32556826; PubMed Central PMCID: PMC7298921.
- 72. Selman LE, Chao D, Sowden R, Marshall S, Chamberlain C, Koffman J. Bereavement Support on the Frontline of COVID-19: Recommendations for Hospital Clinicians. Journal of pain and symptom management. 2020. https://dx.doi.org/10.1016/j.jpainsymman.2020.04.024.
- 73. Simpson R, Robinson L. Rehabilitation After Critical Illness in People With COVID-19 Infection. Am J Phys Med Rehabil. 2020;99(6):470–4. Epub 2020/04/14. pmid:32282359; PubMed Central PMCID: PMC7253039.
- 74. Phua J, Weng L, Ling L, Egi M, Lim CM, Divatia JV, et al. Intensive care management of coronavirus disease 2019 (COVID-19): challenges and recommendations. Lancet Respir Med. 2020;8(5):506–17. Epub 2020/04/10. pmid:32272080; PubMed Central PMCID: PMC7198848.