Number Of Clicks Research Articles

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Headlines that click. Influence of formulation features on selection of online headlines Digitization and the emergence of new media have led to major changes in news production and consumption. The question of what grabs the public’s attention is more relevant than ever. Strategies used to arouse the interest of the news user include headline formulation. This research examined which features of a headline cause the news user to click. For this, 2028 online news headlines from the Dutch newspaper Algemeen Dagblad which came from A/B tests were used. By means of a content analysis, the headlines were analyzed on discursively emphasizing news values (Elite, Proximity, Personalization, Consonance, Unusuality, Negativity, Impact and Superlativeness) and the use of Forward referencing. We have investigated to what extent the use of these stylistic features in a headline influences the number of clicks. The results of this study showed that the discursive construal of Elite, Unusuality, Negativity and Impact had a positive effect on the headline performance.

Case Study: Postruth Construction During The Covid 19 Pandemic

This study aims to propose post truth as one of the constructions of transhumanism. To make it easy to understand, the research took case studies in cyberspace related to Covid-19 in Indonesia. Fairclough's critical discourse analysis method is used to analyze post truth on Instagram social media. The results show that post truth as a construction of transhumanism has several arrangements. First, there is a post truth agent, namely the implementing party or subject who does post truth, this shows that the existence of digital technology makes humans have an ambivalent identity. Second, momentum, in this case of the covid pandemic and hot issues (disputes between regional leaders as the time for discourse to appear), momentum is the key that post truth can occur. This shows that technology is used to understand how we co-create human experience. Finally, people who concentrate on digital technology and cyberspace currently operate with the logic of surveillance capitalism, meaning that everything is measured by the number of clicks, engagement, and the duration of the audience watching. We believe that these results have the potential to cause bias in the truth of information to the public, so this study suggests that public authorities should take all the necessary measures to enhance the literacy public to mitigating the negative impacts caused due to the post truth.

Usability of a perioperative medication-related clinical decision support software application: a randomized controlled trial.

We developed a comprehensive, medication-related clinical decision support (CDS) software prototype for use in the operating room. The purpose of this study was to compare the usability of the CDS software to the current standard electronic health record (EHR) medication administration and documentation workflow. The primary outcome was the time taken to complete all simulation tasks. Secondary outcomes were the total number of mouse clicks and the total distance traveled on the screen in pixels. Forty participants were randomized and assigned to complete 7 simulation tasks in 1 of 2 groups: (1) the CDS group (n = 20), who completed tasks using the CDS and (2) the Control group (n = 20), who completed tasks using the standard medication workflow with retrospective manual documentation in our anesthesia information management system. Blinding was not possible. We video- and audio-recorded the participants to capture quantitative data (time on task, mouse clicks, and pixels traveled on the screen) and qualitative data (think-aloud verbalization). The CDS group mean total task time (402.2 ± 85.9 s) was less than the Control group (509.8 ± 103.6 s), with a mean difference of 107.6 s (95% confidence interval [CI], 60.5-179.5 s, P < .001). The CDS group used fewer mouse clicks (26.4 ± 4.5 clicks) than the Control group (56.0 ± 15.0 clicks) with a mean difference of 29.6 clicks (95% CI, 23.2-37.6, P < .001). The CDS group had fewer pixels traveled on the computer monitor (59.5 ± 20.0 thousand pixels) than the Control group (109.3 ± 40.8 thousand pixels) with a mean difference of 49.8 thousand pixels (95% CI, 33.0-73.7, P < .001). The perioperative medication-related CDS software prototype substantially outperformed standard EHR workflow by decreasing task time and improving efficiency and quality of care in a simulation setting.

Efficiency and Safety of Electronic Health Records in Switzerland-A Comparative Analysis of 2 Commercial Systems in Hospitals.

Differences in efficiency and safety between 2 electronic health record (systems A and B) in Swiss hospitals were investigated. In a scenario-based usability test under experimental conditions, a total of 100 physicians at 4 hospitals were asked to complete typical routine tasks, like medication or imaging orders. Differences in number of mouse clicks and time-on-task as indicators of efficiency and error type, error count, and rate as indicators of patient safety between hospital sites were analyzed. Time-on-task and clicks were correlated with error count. There were differences in efficiency and safety between hospitals. Overall, physicians working with system B required less clicks (A: 511, B: 442, P = 0.001) and time (A: 2055 seconds, B: 1713 seconds, P = 0.055) and made fewer errors (A: 40%, B: 27%, P &lt; 0.001). No participant completed all tasks correctly. The most frequent error in medication and radiology ordering was a wrong dose and a wrong level, respectively. Time errors were particularly prevalent in laboratory orders. Higher error counts coincided with longer time-on-task (r = 0.50, P &lt; 0.001) and more clicks (r = 0.47, P &lt; 0.001). The variations in clicks, time, and errors are likely due to naive functionality and design of the systems and differences in their implementation. The high error rates coincide with inefficiency and jeopardize patient safety and produce economic costs and burden on physicians. The results raise usability concerns with potential for severe patient harm. A deeper understanding of differences as well as regulative guidelines and policy making are needed.

Impact of music on the effectiveness of Facebook ads

Facebook is the most popular social media platform in Poland. As a result, it is often used in advertising campaigns by various types of organizations. The effectiveness of these campaigns depends on many factors, including advertising creation. Video ads are dynamic and may contain music. Music in advertising can be aimed at audience attention, persuasion, user interest and sales. Music influences the emotions of the audience, and these are an important factor in making a purchase decision. It can also increase the rememberability of an ad. Its beat is important, as well as content matching. On the other hand, social media audiences may not play music in ads, which often happens when quickly browsing applications such as Facebook, especially on mobile devices. The lack of background music in the video can therefore also make a difference. The aim of the article is to determine the impact of music on the effectiveness of Facebook ads. As a research method the test of four advertising campaigns was used. The video ads differed only in the background music (the remaining settings and the creation of the ads were identical): the first had no musical background, the second had rock music timed with the video beat, the third - the same rock music not timed with the video beat, and the fourth one had a calm music as background music, less suited to the content (the video required rather dynamic music). It has been hypothesized that music or the lack of it in the video ad, its type and timing (or not) with the beat of the ad’s video have an impact on the effectiveness of the Facebook ads. It affects, among others on the reach metric, impressions, post engagement, number of clicks on the ad, cost of clicks, click rate, video plays and video plays costs.

Remote detection of Cannabis-related impairments in performance?

Researchers have traditionally studied the effects of psychoactive drugs such as Cannabis in controlled laboratory settings or relied on retrospective self-reports to measure impairment. However, advances in technology afford opportunities to conduct assessments remotely. We considered whether objective click-stream data (time and number of clicks spent on a webpage) during an online survey could supplement self-reports of substance use problems. The clickstream data of participants (n = 236) were examined as they completed an online study which included validated psychometric tests (Cannabis Use Disorders Identification Test-Revised, Grit-O, Kessler Psychological Distress Scale, and Brief Self Control Scale). Clickstream data were compared to self-reported Cannabis use. People reporting Cannabis use within the last 4weeks required more time and more clicks to complete the online survey, and this was specifically associated with reported frequency of use, duration of impairment, and problems with memory and concentration. Longer amounts of time and more clicks on the online questionnaire were associated with more recent Cannabis use rather than demographic factors or stimulant use. These results imply clickstream data remotely detected indecision or other deficits associated with previous Cannabis use.

Design of a Panoramic Virtual Dynamic Display System for Digital Museums Based on Visual Interaction Technology

To address the spatial and temporal limitations of historical museums, a panoramic virtual dynamic display system for digital museums is designed using visual interactive technology. The VM file is generated by using the Digital Museum Design module to obtain a list of available objects, and the VM file is analysed by the Digital Museum View module to stretch and change the two-dimensional flat map into a three-dimensional spatial map for viewers to browse. The system software designs the technical construction process of the digital museum, uses a linearisation algorithm to calculate the number of clicks, visualises the font according to the number of clicks reflecting the weights, and builds a tag cloud component to provide interactive services to facilitate efficient understanding of the museum information by the viewer.

A Mobile App for Advance Care Planning and Advance Directives (Accordons-nous): Development and Usability Study.

BackgroundAdvance care planning, including advance directives, is an important tool that allows patients to express their preferences for care if they are no longer able to express themselves. We developed Accordons-nous, a smartphone app that informs patients about advance care planning and advance directives, facilitates communication on these sensitive topics, and helps patients express their values and preferences for care.ObjectiveThe first objective of this study is to conduct a usability test of this app. The second objective is to collect users’ critical opinions on the usability and relevance of the tool.MethodsWe conducted a usability test by means of a think-aloud method, asking 10 representative patients to complete 7 browsing tasks. We double coded the filmed sessions to obtain descriptive data on task completion (with or without help), time spent, number of clicks, and the types of problems encountered. We assessed the severity of the problems encountered and identified the modifications needed to address these problems. We evaluated the readability of the app using Scolarius, a French equivalent of the Flesch Reading Ease test. By means of a posttest questionnaire, we asked participants to assess the app’s usability (System Usability Scale), relevance (Mobile App Rating Scale, section F), and whether they would recommend the app to the target groups: patients, health professionals, and patients’ caring relatives.ResultsParticipants completed the 7 think-aloud tasks in 80% (56/70) of the cases without any help from the experimenter, in 16% (11/70) of the cases with some help, and failed in 4% (3/70) of the cases. The analysis of failures and difficulties encountered revealed a series of major usability problems that could be addressed with minor modifications to the app. Accordons-nous obtained high scores on readability (overall score of 87.4 on Scolarius test, corresponding to elementary school level), usability (85.3/100 on System Usability Scale test), relevance (4.3/5 on the Mobile App Rating Scale, section F), and overall subjective endorsement on 3 I would recommend questions (4.7/5).ConclusionsThis usability test helped us make the final changes to our app before its official launch.

Comparison of Patient Adverse Drug Reaction Reporting Systems in Nine Selected Countries.

Patients are recognized as important players in the pharmacovigilance system. This study aims to describe and compare the characteristics of patient reporting systems, reporting forms, awareness raising-activities, and the statistics related to patient reporting in the selected countries. Fifteen countries (eight Western countries and seven Asian countries) were purposively selected. A questionnaire survey was distributed to national pharmacovigilance authorities in those countries. Nine countries (five Western countries and four Asian countries) returned the questionnaire. A review of the websites of national pharmacovigilance centres was conducted. The proportion of patient reports in the selected Western countries ranged from 57.83% to 14.37%, while it was accounted for less than 1% in the selected Asian countries. Currently, patients in all nine countries can report adverse drug reactions online via a website. The number of clicks from the national pharmacovigilance website to reach the online reporting form range from one to five clicks. Countries with higher patient reporting rates seemed to share the following characteristics; provision of feedback, engagement with patient organizations, and implementation of several activities to raise the awareness of the general public on the importance of pharmacovigilance. To increase the number of patient reports, the strengths of each country’s system should be adopted.

Use of a Paid Digital Marketing Campaign to Promote a Mobile Health App to Encourage Parent-Engaged Developmental Monitoring: Implementation Study.

BackgroundThe internet has become an increasingly popular medium for parents to obtain health information. More studies investigating the impact of paid digital marketing campaigns for parents on promoting children’s healthy development are needed.ObjectiveThis study aims to explore the outcomes of a paid digital marketing campaign, which occurred from 2018 to 2020, to promote messages about parent-engaged developmental monitoring and ultimately direct parents to the Centers for Disease Control and Prevention’s (CDC’s) Milestone Tracker app, a mobile health (mHealth) app developed by the CDC.MethodsThe paid digital marketing campaign occurred in 3 phases from 2018 to 2020. In each phase, 24 to 36 marketing messages, in English and Spanish, were created and disseminated using Google’s Universal App Campaigns and Facebook Ads Manager. Outcomes were measured using impressions, clicks, and install data. Return on investment was measured using click-through rate (CTR), cost per click, and cost per install metrics.ResultsThe Google-driven marketing messages garnered a total of 4,879,722 impressions (n=1,991,250, 40.81% for English and n=2,888,472, 59.19% for Spanish). The messages resulted in a total of 73,956 clicks (n=44,328, 59.94% for English and n=29,628, 40.06% for Spanish), with a total average CTR of 1.52% (2.22% for English and 1.03% for Spanish). From these clicks, there were 13,707 installs (n=9765, 71.24% for English and n=3942, 28.76% for Spanish) of the CDC’s Milestone Tracker app on Google Play Store. The total average cost per install was US $0.93 across all phases. The phase 3 headline “Track your child’s development” generated the highest CTR of 3.23% for both English and Spanish audiences. The Facebook-driven marketing messages garnered 2,434,320 impressions (n=1,612,934, 66.26% for English and n=821,386, 33.74% for Spanish). The messages resulted in 44,698 clicks (n=33,353, 74.62% for English and n=11,345, 25.38% for Spanish), with an average CTR of 1.84% (2.07% for English and 1.38% for Spanish). In all 3 phases, animated graphics generated the greatest number of clicks among both English and Spanish audiences on Facebook when compared with other types of images.ConclusionsThese paid digital marketing campaigns can increase targeted message exposure about parent-engaged developmental monitoring and direct a parent audience to an mHealth app. Digital marketing platforms provide helpful metrics that can be used to assess the reach, engagement, and cost-effectiveness of this effort. The results from this study suggest that paid digital marketing can be an effective strategy and can inform future digital marketing activities to promote mHealth apps targeting parents of young children.

Unethical Practices and Effects of Digital Journalism in the COVID-19 Era: The Case of TRNC

The coronavirus disease (COVID-19) has spread to many countries and has been causing serious repercussions as a pandemic. The use of digital technologies has increased significantly during the pandemic and they have helped transform people’s lives. In this study, COVID-19-related news disseminated by four news sites in Turkish Republic of Northern Cyprus (TRNC) were analyzed. It was investigated whether news sites are broadcast in accordance with ethical principles. Semi-structured interviews were held with communication specialists and psychologists to identify the reasons, effects, and prevention methods of ethical violations on digital journal news. It was found that ethical principles are not completely considered owing to the expectations to increase the number of clicks and profits of the four news sites examined. It is recommended that trainings should be conducted on ethical principles, personal rights, and awareness creation. Additionally, revisions should be made in relevant laws and an “Internet News Site Ethics Committee” should be established.

A reply to Madera et al.'s "A method for optimizing a bidding strategy for online advertising through the use of intuitionistic fuzzy systems"

In 2016, Madera et al. tested the performance of a fuzzy inference system against the Google Ads algorithms for optimizing the number of clicks, the click through rate (CTR) and the average cost per clicks to lower the cost of an advertising campaign [7]. The results of their experiments suggested that the implementation of their fuzzy inference system outperformed the Google Ads algorithms in terms of the obtained number of clicks and cost per clicks. While the research idea is with no doubts an interesting and valuable contribution to the fields of digital marketing research, in the opinion of the authors, their experimental setup was flawed. However, applying a few adjustments can lead to valid findings. This paper reflects on the flaws and suggests enhancements to correct them.

Optimal Search Engine Marketing Strategy Customer Behaviour (Case studies from Saudi Arabia): استراتيجية التسويق الأمثل عبر محرك البحث: فهم سلوك العملاء (دراسات حالة من المملكة العربية السعودية)

In the era of the information age, it is normal for a business to have an online attendance on the Internet. However, existence alone is insufficient; the business has to be obviously visible on the search engine whenever a user searches for a product or service provided by that type of business in order to survive and thrive in a competitive market. Thus, the significance of an optimal search engine marketing strategy is extremely important for marketers in particular and for businesses. This study, two case studies from Saudi Arabia were selected to explore this subject. The essay considered how the two selected case studies use Search Engine Optimization (SEO) and paid listings such as Pay Per Click (PPC). Data was gathered from secondary data such as that provided by government departments and business reports. The objective of this study is to understand and explore the massive contribution of paid listings and SEO as search engine tools, to examine how both can serve to raise the number of user/potential customer visits to business websites and to determine what the major challenges are with respect to when and why marketers should use paid listings and/or SEO. This Study found that both case studies invest a low budget in their SEO. In contrast, they both devoted a larger part of their search engine marketing budgets to PPC. However, it was found that SEO brings a higher number of clicks compared to PPC, suggesting that more visitors/users that business could be converted into actual customers. The recommendations of this study can be used to guide the marketers to correct their choice of an optimal search engine marketing strategy, in turn allowing businesses to more accurately determine their online marketing budget.

Price Transparency for Primary Hip & Knee Arthroplasty: An Overview of the Top 50 US News and World Report Orthopedic Hospitals

BackgroundThe Centers for Medicare and Medicaid Services (CMS) has mandated all hospitals to publish the charges of 300 common procedures to provide price transparency. The aims of our study are to evaluate 50 top orthopedic hospitals to determine compliance with this mandate and to assess the ease of finding cost information for arthroplasty procedures. MethodsThe websites of the top 50 US News and World Report (USNWR) orthopedic hospitals were searched to find publicly accessible procedural charges. Data included the number of clicks to locate pricing documents, number of files provided, and number of data rows pertaining to arthroplasty. Charge data was queried based on Diagnosis related group (DRG) codes (469, 470), Current Procedural Technology (CPT) codes (27130, 27477), and keyword searches (“arthroplasty”, “total hip”, and “total knee”). ResultsForty-four (88%) of the top 50 USNWR Orthopedic institutions had publicly accessible files containing cost information. Thirty three of the 44 institutions provided results with DRG search while less than 10 institutions used CPT and keyword searches. There was an average of 226,190 (range 304-1,121,876) rows of data per file. Average charges varied depending on the use of DRG, CPT or keyword searches ($6,663-$117,072). ConclusionThe majority of compliant hospitals published large data files requiring the use of DRG codes to find cost information with extreme variation in resultant charges provided. These findings underscore the lack of direct patient benefit afforded by the current mandate, as pricing determinations require expert knowledge in medical coding and have a high variability in the reported charges.

The early history of clicks in Nguni

AbstractLanguage contact between migrating Bantu speakers and resident Khoisan speakers has resulted in the adoption of clicks in various southern African Bantu languages. This paper uses the comparative method to show that for one particular cluster of Bantu click languages, the Nguni languages, a large number of phonemic clicks can be reconstructed to its putative ancestor Proto-Nguni, including a palatal click rarely found in Bantu languages and no longer used as such in any living Nguni language. Although clicks have undergone subsequent developments in individual Nguni languages, no new click phonemes were acquired through language contact, showing that clicks were already present very early in the history of the Nguni languages. This relative chronology provides new insights into how the relations between Bantu- and Khoisan-speaking communities in southern Africa developed over time.

Upper confidence bound integrated genetic algorithm‐optimized long short‐term memory network for click‐through rate prediction

AbstractData on online advertising is rising rapidly due to the fast development of science and technology. Click‐through rate (CTR) prediction has become a critical task regarding the digital advertising industry and a key element in increasing advertising profits and user experience. Therefore, this article describes the problem of CTR prediction as a function of sequence classification tasks. Then, we proposed a novel optimization strategy to solve the high‐dimensional problem and find a subset of relevant variables to ensure high performance of our model and maximize the number of clicks. Here, we introduced a feature selection and hyper‐parameter optimization approach using genetic algorithms (GA) and the upper confidence bound (UCB) model to optimize micro‐targeting technology, along with the long short‐term memory (LSTM) network‐based CTR prediction model. The efficiency of the proposed UCB‐LSTM‐GA model and two hybrid models, namely LSTM‐GA and LSTM‐PSO, is evaluated by comparing them to each other and to other machine‐learning‐based classification methods, including LSTM using a UCB algorithm (UCB‐LSTM), High‐order Attentive Factorization Machine (HoAFM), genetic algorithm‐artificial neural network (GA‐ANN), and a feature interaction graph neural network model (Fi‐GNN). Our solution achieved as high as 87%, 89%, and 92% for respectively accuracy, precision, and recall, using the popular python tools with real Avazu datasets.

Out of the spotlight: Four years of Italian coach market prices

Analogous to Germany and France, Italian coach market radically changed after liberalisation (2014). Liberalisation led to new routes, increased frequencies, mergers, and withdrawals. The paper analyses market trends from four years of real ticket prices collected through collaboration with www.checkmybus.it. The dataset, consisting of monthly average prices and the number of clicks by company and by city-pair, is enriched with spatial information, including the separation of airport routes. Results show that sub-national markets had different trends, with the growth of offer on routes linked to network expansion of the early liberalisation slowing down. Contrarily, the historical routes to the Centre and South remain stable. Interestingly, larger (Top-5) companies' prices are below market average up to 5–10% less. Smaller companies operate often on niche routes, with fewer economies of scale and thus maintain higher prices. This trend switched during the COVID pandemic. A further comparison with rail prices showed that coaches were able to reduce the price gap at least with conventional trains, from −50% (average for 2017–2020) to −20% for the second semester of 2020. This is a sign of the ability of the coach sector to adapt to the shock, by reducing capacity and concentrating on more competitive routes.

Text Messaging Intervention for Mental Wellness in American Indian and Alaska Native Teens and Young Adults (BRAVE Study): Analysis of User Engagement Patterns.

BackgroundMany American Indian and Alaska Native (AI/AN or Native) communities express concern about high rates of suicide and poor mental health. Technology-based health interventions that nurture resilience, coping skills, connectedness, and help-seeking skills may be an effective strategy for promoting health and wellbeing among AI/AN youth. The Northwest Portland Area Indian Health Board designed the BRAVE intervention for AI/AN youth. BRAVE is delivered via SMS text messaging and includes role model videos, mental wellness strategies, links to culturally relevant resources, and social support from family and friends.ObjectiveThe aim of this study is to explore system data from the BRAVE intervention to determine patterns of user engagement and differences in psychosocial outcomes based on the number of clicks on BRAVE content.MethodsThe BRAVE study included 1030 AI/AN teens and young adults nationwide (15 to 24 years old). The message series in the BRAVE and STEM study arms included 3 to 5 SMS text messages per week, featuring 1 role model video and 1 image per week. Messages were sent out via Mobile Commons (Upland Software Inc), a mobile messaging provider that supports text, picture, and video SMS.ResultsOf the 509 participants in the original BRAVE analysis, 270 had sufficient data to analyze user engagement, with at least 1 trackable click on a study SMS text message. Of the 270, 184 (68.1%) were female, 50 (18.5%) were male, and 36 (13.3%) selected another gender category. The average participant was 20.6 years old, with a minimum and maximum age of 15 and 26 years. Most participants had relatively low engagement measured by the number of clicks (median 2; mean 3.4), although others clicked message content as many as 49 times. Users engaged most frequently with the YouTube-based content (viewing 1 of 7 role model videos), with 64.8% (175/270) of total clicks coming from the role model videos, and earlier episodes receiving the highest number of clicks. Most baseline psychosocial measures were not significantly associated with the number of links clicked. However, help-seeking behavior was highly significant (P<.001), with a rate ratio of 0.82 (0.73, 0.92), indicating that each 1-unit increase in help-seeking score at baseline was associated with an 18% decrease in the expected number of study content clicks.ConclusionsThis is the first study to set initial standards for assessing user engagement in an mHealth intervention. Our work underscores the feasibility of exploring the impact of engagement on intended outcomes, allowing for more precise exploration of the dose-response relationship that may be realized through these low-touch interventions that offer promising potential for reaching high numbers of program participants.Trial RegistrationClinicalTrials.gov NCT04979481; https://clinicaltrials.gov/ct2/show/NCT04979481

DFM-GCN: A Multi-Task Learning Recommendation Based on a Deep Graph Neural Network

Among the inherent problems in recommendation systems are data sparseness and cold starts; the solutions to which lie in the introduction of knowledge graphs to improve the performance of the recommendation systems. The results in previous research, however, suffer from problems such as data compression, information damage, and insufficient learning. Therefore, a DeepFM Graph Convolutional Network (DFM-GCN) model was proposed to alleviate the above issues. The prediction of the click-through rate (CTR) is critical in recommendation systems where the task is to estimate the probability that a user will click on a recommended item. In many recommendation systems, the goal is to maximize the number of clicks so the items returned to a user can be ranked by an estimated CTR. The DFM-GCN model consists of three parts: the left part DeepFM is used to capture the interactive information between the users and items; the deep neural network is used in the middle to model the left and right parts; and the right one obtains a better item representation vector by the GCN. In an effort to verify the validity and precision of the model built in this research, and based on the public datasets ml1m-kg20m and ml1m-kg1m, a performance comparison experiment was designed. It used multiple comparison models and the MKR and FM_MKR algorithms as well as the DFM-GCN algorithm constructed in this paper. Having achieved a state-of-the-art performance, the experimental results of the AUC and f1 values verified by the CTR as well as the accuracy, recall, and f1 values of the top-k showed that the proposed approach was excellent and more effective when compared with different recommendation algorithms.

Using Social Media to Engage Knowledge Users in Health Research Priority Setting: Scoping Review.

BackgroundThe need to include individuals with lived experience (ie, patients, family members, caregivers, researchers, and clinicians) in health research priority setting is becoming increasingly recognized. Social media–based methods represent a means to elicit and prioritize the research interests of such individuals, but there remains sparse methodological guidance on how best to conduct these social media efforts and assess their effectiveness.ObjectiveThis review aims to identify social media strategies that enhance participation in priority-setting research, collate metrics assessing the effectiveness of social media campaigns, and summarize the benefits and limitations of social media–based research approaches, as well as recommendations for prospective campaigns.MethodsWe searched PubMed, Embase, Cochrane Library, Scopus, and Web of Science from database inception until September 2021. Two reviewers independently screened all titles and abstracts, as well as full texts for studies that implemented and evaluated social media strategies aimed at engaging knowledge users in research priority setting. We subsequently conducted a thematic analysis to aggregate study data by related codes and themes.ResultsA total of 23 papers reporting on 22 unique studies were included. These studies used Facebook, Twitter, Reddit, websites, video-calling platforms, emails, blogs, e-newsletters, and web-based forums to engage with health research stakeholders. Priority-setting engagement strategies included paid platform–based advertisements, email-embedded survey links, and question-and-answer forums. Dissemination techniques for priority-setting surveys included snowball sampling and the circulation of participation opportunities via internal members’ and external organizations’ social media platforms. Social media campaign effectiveness was directly assessed as number of clicks and impressions on posts, frequency of viewed posts, volume of comments and replies, number of times individuals searched for a campaign page, and number of times a hashtag was used. Campaign effectiveness was indirectly assessed as numbers of priority-setting survey responses and visits to external survey administration sites. Recommendations to enhance engagement included the use of social media group moderators, opportunities for peer-to-peer interaction, and the establishment of a consistent tone and brand.ConclusionsSocial media may increase the speed and reach of priority-setting participation opportunities leading to the development of research agendas informed by patients, family caregivers, clinicians, and researchers. Perceived limitations of the approach include underrepresentation of certain demographic groups and addressing such limitations will enhance the inclusion of diverse research priority opinions in future research agendas.