https://www.jmir.org/stats/feed
Tweets within the last year: 397 | Total Tweets: | Twimpact Factor (tw7): 0 | Twindex7: 0 ]]> https://www.jmir.org/2019/10/e13440 Thu, 17 Oct 2019 10:15:02 EDT https://www.jmir.org/2019/10/e13440 Background: Health services in many countries are promoting digital-first models of access to general practice based on offering online, video, or telephone consultations before a face-to-face consultation. It is claimed that this will improve access for patients and moderate the workload of doctors. However, improved access could also potentially increase doctors’ workload. Objective: The aim of this study was to explore whether and under what circumstances digital-first access to general practice is likely to decrease or increase general practice workload. Methods: A process map to delineate primary care access pathways was developed and a model to estimate general practice workload constructed in Microsoft Excel (Microsoft Corp). The model was populated using estimates of key variables obtained from a systematic review of published studies. A MEDLINE search was conducted for studies published in English between January 1, 2000, and September 30, 2019. Included papers provided quantitative data about online, telephone, or video consultations for unselected patients requesting a general practice in-hours consultation for any problem. We excluded studies of general practitioners consulting specialists, consultations not conducted by doctors, and consultations conducted after hours, in secondary care, in specialist services, or for a specific health care problem. Data about the following variables were extracted from the included papers to form the model inputs: the proportion of consultations managed digitally, the proportion of digital consultations completed without a subsequent consultation, the proportion of subsequent consultations conducted by telephone rather than face-to-face, consultation duration, and the proportion of digital consultations that represent new demand. The outcome was general practice workload. The model was used to test the likely impact of different digital-first scenarios, based on the best available evidence and the plausible range of estimates from the published studies. The model allows others to test the impact on workload of varying assumptions about model inputs. Results: Digital-first approaches are likely to increase general practice workload unless they are shorter, and a higher proportion of patients are managed without a subsequent consultation than observed in most published studies. In our base-case scenarios (based on the best available evidence), digital-first access models using online, telephone, or video consultations are likely to increase general practitioner workload by 25%, 3%, and 31%, respectively. An important determinant of workload is whether the availability of digital-first approaches changes the demand for general practice consultations, but there is little robust evidence to answer this question. Conclusions: Digital-first approaches to primary care could increase general practice workload unless stringent conditions are met. Justification for these approaches should be based on evidence about the benefits in relation to the costs, rather than assumptions about reductions in workload. Given the potential increase in workload, which in due course could worsen problems of access, these initiatives should be implemented in a staged way alongside careful evaluation.

Tweets within the last year: 332 | Total Tweets: | Twimpact Factor (tw7): 0 | Twindex7: 0 ]]> https://www.jmir.org/2020/6/e18203 Tue, 16 Jun 2020 10:45:45 EDT https://www.jmir.org/2020/6/e18203
Tweets within the last year: 302 | Total Tweets: | Twimpact Factor (tw7): 2 | Twindex7: 0 ]]> https://www.jmir.org/2011/4/e123 Fri, 16 Dec 2011 08:38:26 EST https://www.jmir.org/2011/4/e123 Background: Since the beginning of December 2019, the coronavirus disease (COVID-19) has spread rapidly around the world, which has led to increased discussions across online platforms. These conversations have also included various conspiracies shared by social media users. Amongst them, a popular theory has linked 5G to the spread of COVID-19, leading to misinformation and the burning of 5G towers in the United Kingdom. The understanding of the drivers of fake news and quick policies oriented to isolate and rebate misinformation are keys to combating it. Objective: The aim of this study is to develop an understanding of the drivers of the 5G COVID-19 conspiracy theory and strategies to deal with such misinformation. Methods: This paper performs a social network analysis and content analysis of Twitter data from a 7-day period (Friday, March 27, 2020, to Saturday, April 4, 2020) in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom. Influential users were analyzed through social network graph clusters. The size of the nodes were ranked by their betweenness centrality score, and the graph’s vertices were grouped by cluster using the Clauset-Newman-Moore algorithm. The topics and web sources used were also examined. Results: Social network analysis identified that the two largest network structures consisted of an isolates group and a broadcast group. The analysis also revealed that there was a lack of an authority figure who was actively combating such misinformation. Content analysis revealed that, of 233 sample tweets, 34.8% (n=81) contained views that 5G and COVID-19 were linked, 32.2% (n=75) denounced the conspiracy theory, and 33.0% (n=77) were general tweets not expressing any personal views or opinions. Thus, 65.2% (n=152) of tweets derived from nonconspiracy theory supporters, which suggests that, although the topic attracted high volume, only a handful of users genuinely believed the conspiracy. This paper also shows that fake news websites were the most popular web source shared by users; although, YouTube videos were also shared. The study also identified an account whose sole aim was to spread the conspiracy theory on Twitter. Conclusions: The combination of quick and targeted interventions oriented to delegitimize the sources of fake information is key to reducing their impact. Those users voicing their views against the conspiracy theory, link baiting, or sharing humorous tweets inadvertently raised the profile of the topic, suggesting that policymakers should insist in the efforts of isolating opinions that are based on fake news. Many social media platforms provide users with the ability to report inappropriate content, which should be used. This study is the first to analyze the 5G conspiracy theory in the context of COVID-19 on Twitter offering practical guidance to health authorities in how, in the context of a pandemic, rumors may be combated in the future.

Tweets within the last year: 294 | Total Tweets: | Twimpact Factor (tw7): 0 | Twindex7: 0 ]]> https://www.jmir.org/2020/5/e19458 Wed, 06 May 2020 11:30:06 EDT https://www.jmir.org/2020/5/e19458 Background: Interprofessional team training is needed to improve nurse-physician communication skills that are lacking in clinical practice. Using simulations has proven to be an effective learning approach for team training. Yet, it has logistical constraints that call for the exploration of virtual environments in delivering team training. Objective: This study aimed to evaluate a team training program using virtual reality vs conventional live simulations on medical and nursing students’ communication skill performances and teamwork attitudes. Methods: In June 2018, the authors implemented nurse-physician communication team training using communication tools. A randomized controlled trial study was conducted with 120 undergraduate medical and nursing students who were randomly assigned to undertake team training using virtual reality or live simulations. The participants from both groups were tested on their communication performances through team-based simulation assessments. Their teamwork attitudes were evaluated using interprofessional attitude surveys that were administered before, immediately after, and 2 months after the study interventions. Results: The team-based simulation assessment revealed no significant differences in the communication performance posttest scores (P=.29) between the virtual and simulation groups. Both groups reported significant increases in the interprofessional attitudes posttest scores from the baseline scores, with no significant differences found between the groups over the 3 time points. Conclusions: Our study outcomes did not show an inferiority of team training using virtual reality when compared with live simulations, which supports the potential use of virtual reality to substitute conventional simulations for communication team training. Future studies can leverage the use of artificial intelligence technology in virtual reality to replace costly human-controlled facilitators to achieve better scalability and sustainability of team-based training in interprofessional education. Trial Registration: ClinicalTrials.gov NCT04330924; https://clinicaltrials.gov/ct2/show/NCT04330924

Tweets within the last year: 284 | Total Tweets: | Twimpact Factor (tw7): 0 | Twindex7: 0 ]]> https://www.jmir.org/2020/4/e17279 Wed, 08 Apr 2020 09:00:29 EDT https://www.jmir.org/2020/4/e17279 Background: The integrity of data in a clinical trial is essential, but the current data management process is too complex and highly labor-intensive. As a result, clinical trials are prone to consuming a lot of budget and time, and there is a risk for human-induced error and data falsification. Blockchain technology has the potential to address some of these challenges. Objective: The aim of the study was to validate a system that enables the security of medical data in a clinical trial using blockchain technology. Methods: We have developed a blockchain-based data management system for clinical trials and tested the system through a clinical trial for breast cancer. The project was conducted to demonstrate clinical data management using blockchain technology under the regulatory sandbox enabled by the Japanese Cabinet Office. Results: We verified and validated the data in the clinical trial using the validation protocol and tested its resilience to data tampering. The robustness of the system was also proven by survival with zero downtime for clinical data registration during a Amazon Web Services disruption event in the Tokyo region on August 23, 2019. Conclusions: We show that our system can improve clinical trial data management, enhance trust in the clinical research process, and ease regulator burden. The system will contribute to the sustainability of health care services through the optimization of cost for clinical trials.

Tweets within the last year: 279 | Total Tweets: | Twimpact Factor (tw7): 0 | Twindex7: 0 ]]> https://www.jmir.org/2020/6/e18938 Tue, 02 Jun 2020 09:46:27 EDT https://www.jmir.org/2020/6/e18938 Background: The traditional model of promotion and tenure in the health professions relies heavily on formal scholarship through teaching, research, and service. Institutions consider how much weight to give activities in each of these areas and determine a threshold for advancement. With the emergence of social media, scholars can engage wider audiences in creative ways and have a broader impact. Conventional metrics like the h-index do not account for social media impact. Social media engagement is poorly represented in most curricula vitae (CV) and therefore is undervalued in promotion and tenure reviews. Objective: The objective was to develop crowdsourced guidelines for documenting social media scholarship. These guidelines aimed to provide a structure for documenting a scholar’s general impact on social media, as well as methods of documenting individual social media contributions exemplifying innovation, education, mentorship, advocacy, and dissemination. Methods: To create unifying guidelines, we created a crowdsourced process that capitalized on the strengths of social media and generated a case example of successful use of the medium for academic collaboration. The primary author created a draft of the guidelines and then sought input from users on Twitter via a publicly accessible Google Document. There was no limitation on who could provide input and the work was done in a democratic, collaborative fashion. Contributors edited the draft over a period of 1 week (September 12-18, 2020). The primary and secondary authors then revised the draft to make it more concise. The guidelines and manuscript were then distributed to the contributors for edits and adopted by the group. All contributors were given the opportunity to serve as coauthors on the publication and were told upfront that authorship would depend on whether they were able to document the ways in which they met the 4 International Committee of Medical Journal Editors authorship criteria. Results: We developed 2 sets of guidelines: Guidelines for Listing All Social Media Scholarship Under Public Scholarship (in Research/Scholarship Section of CV) and Guidelines for Listing Social Media Scholarship Under Research, Teaching, and Service Sections of CV. Institutions can choose which set fits their existing CV format. Conclusions: With more uniformity, scholars can better represent the full scope and impact of their work. These guidelines are not intended to dictate how individual institutions should weigh social media contributions within promotion and tenure cases. Instead, by providing an initial set of guidelines, we hope to provide scholars and their institutions with a common format and language to document social media scholarship.

Tweets within the last year: 202 | Total Tweets: | Twimpact Factor (tw7): 0 | Twindex7: 0 ]]> https://www.jmir.org/2020/12/e25070 Wed, 02 Dec 2020 09:45:57 EST https://www.jmir.org/2020/12/e25070 Background: Respecting patient privacy and confidentiality is critical for doctor-patient relationships and public trust in medical professionals. The frequency of potentially identifiable disclosures online during periods of active engagement is unknown. Objective: The objective of this study was to quantify potentially identifiable content shared on social media by physicians and other health care providers using the hashtag #ShareAStoryInOneTweet. Methods: We accessed and searched Twitter’s API using Symplur software for tweets that included the hashtag #ShareAStoryInOneTweet. We identified 1206 tweets by doctors, nurses, and other health professionals out of 43,374 tweets shared in May 2018. Tweet content was evaluated in January 2019 to determine the incidence of instances where names or potentially identifiable information about patients were shared; content analysis of tweets in which information about others had been disclosed was performed. The study also evaluated whether participants raised concerns about privacy breaches and estimated the frequency of deleted tweets. The study used dual, blinded coding for a 10% sample to estimate intercoder reliability using Cohen κ statistic for identifying the potential identifiability of tweet content. Results: Health care professionals (n=656) disclosing information about others included 486 doctors (74.1%) and 98 nurses (14.9%). Health care professionals sharing stories about patient care disclosed the time frame in 95 tweets (95/754, 12.6%) and included patient names in 15 tweets (15/754, 2.0%). It is estimated that friends or families could likely identify the clinical scenario described in 242 of the 754 tweets (32.1%). Among 348 tweets about potentially living patients, it was estimated that 162 (46.6%) were likely identifiable by patients. Intercoder reliability in rating the potential identifiability demonstrated 86.8% agreement, with a Cohen κ of 0.8 suggesting substantial agreement. We also identified 78 out of 754 tweets (6.5%) that had been deleted on the website but were still viewable in the analytics software data set. Conclusions: During periods of active sharing online, nurses, physicians, and other health professionals may sometimes share more information than patients or families might expect. More study is needed to determine whether similar events arise frequently and to understand how to best ensure that patients’ rights are adequately respected.

Tweets within the last year: 182 | Total Tweets: | Twimpact Factor (tw7): 0 | Twindex7: 0 ]]> https://www.jmir.org/2020/9/e19746 Tue, 01 Sep 2020 10:00:02 EDT https://www.jmir.org/2020/9/e19746 Background: Video-mediated clinical consultations offer potential benefits over conventional face-to-face in terms of access, convenience, and sometimes cost. The improved technical quality and dependability of video-mediated consultations has opened up the possibility for more widespread use. However, questions remain regarding clinical quality and safety. Video-mediated consultations are sometimes criticized for being not as good as face-to-face, but there has been little previous in-depth research on their interactional dynamics, and no agreement on what a good video consultation looks like. Objective: Using conversation analysis, this study aimed to identify and analyze the communication strategies through which video-mediated consultations are accomplished and to produce recommendations for patients and clinicians to improve the communicative quality of such consultations. Methods: We conducted an in-depth analysis of the clinician-patient interaction in a sample of video-mediated consultations and a comparison sample of face-to-face consultations drawn from 4 clinical settings across 2 trusts (1 community and 1 acute care) in the UK National Health Service. The video dataset consisted of 37 recordings of video-mediated consultations (with diabetes, antenatal diabetes, cancer, and heart failure patients), 28 matched audio recordings of face-to-face consultations, and fieldnotes from before and after each consultation. We also conducted 37 interviews with staff and 26 interviews with patients. Using linguistic ethnography (combining analysis of communication with an appreciation of the context in which it takes place), we examined in detail how video interaction was mediated by 2 software platforms (Skype and FaceTime). Results: Patients had been selected by their clinician as appropriate for video-mediated consultation. Most consultations in our sample were technically and clinically unproblematic. However, we identified 3 interactional challenges: (1) opening the video consultation, (2) dealing with disruption to conversational flow (eg, technical issues with audio and/or video), and (3) conducting an examination. Operational and technological issues were the exception rather than the norm. In all but 1 case, both clinicians and patients (deliberately or intuitively) used established communication strategies to successfully negotiate these challenges. Remote physical examinations required the patient (and, in some cases, a relative) to simultaneously follow instructions and manipulate technology (eg, camera) to make it possible for the clinician to see and hear adequately. Conclusions: A remote video link alters how patients and clinicians interact and may adversely affect the flow of conversation. However, our data suggest that when such problems occur, clinicians and patients can work collaboratively to find ways to overcome them. There is potential for a limited physical examination to be undertaken remotely with some patients and in some conditions, but this appears to need complex interactional work by the patient and/or their relatives. We offer preliminary guidance for patients and clinicians on what is and is not feasible when consulting via a video link.

Tweets within the last year: 173 | Total Tweets: | Twimpact Factor (tw7): 0 | Twindex7: 0 ]]> https://www.jmir.org/2020/5/e18378 Mon, 11 May 2020 09:00:06 EDT https://www.jmir.org/2020/5/e18378 P<.001). Also, no patients initially reporting low or no anxiety before participation reported an increase to high or extreme anxiety after participation. Conclusions: This study demonstrates that breast cancer patients’ perceived knowledge increases and their anxiety decreases by participation in a Twitter social media support group.

Tweets within the last year: 173 | Total Tweets: | Twimpact Factor (tw7): 17 | Twindex7: 0 ]]> https://www.jmir.org/2015/7/e188 Thu, 30 Jul 2015 10:00:04 EDT https://www.jmir.org/2015/7/e188