Ethical Issues in Social Media Research for Public Health.

Social media (SM) offer huge potential for public health research, serving as a vehicle for surveillance, delivery of health interventions, recruitment to trials, collection of data, and dissemination. However, the networked nature of the data means they are riddled with ethical challenges, and no clear consensus has emerged as to the ethical handling of such data. This article outlines the key ethical concerns for public health researchers using SM and discusses how these concerns might best be addressed. Key issues discussed include privacy; anonymity and confidentiality; authenticity; the rapidly changing SM environment; informed consent; recruitment, voluntary participation, and sampling; minimizing harm; and data security and management. Despite the obvious need, producing a set of prescriptive guidelines for researchers using SM is difficult because the field is evolving quickly. What is clear, however, is that the ethical issues connected to SM-related public health research are also growing. Most importantly, public health researchers must work within the ethical principles set out by the Declaration of Helsinki that protect individual users first and foremost.

Untapped resource: the simulation-based healthcare environment as a means to study human stress.

The effects of 'stress' within the healthcare professions are wide-reaching, not least of all within the field of simulation-based healthcare education. Whilst this popular method of experiential learning offers a 'safe space' for participants to develop their skillset, it also has a more surreptitious action; namely, the incubation of simulation-related stress. Currently, research concerning the complex relationship between stress, learning, and performance is ambiguous, leaving fertile ground for simulationists to debate what level of stress is appropriate for an optimised educational experience. In this narrative review, we examine the human response to stress and outline the various methods that have been used by researchers to measure stress in a quantifiable and standardised way. We then provide a brief overview of simulation-based healthcare education before describing why stress responses have been of interest to healthcare educationalists for some time. Finally, we outline how simulation education environments might provide an ideal environment for studying the human response to stress generally, with ramifications extending beyond the field of medical education.

A performance comparison of eight commercially available automatic classifiers for facial affect recognition.

In the wake of rapid advances in automatic affect analysis, commercial automatic classifiers for facial affect recognition have attracted considerable attention in recent years. While several options now exist to analyze dynamic video data, less is known about the relative performance of these classifiers, in particular when facial expressions are spontaneous rather than posed. In the present work, we tested eight out-of-the-box automatic classifiers, and compared their emotion recognition performance to that of human observers. A total of 937 videos were sampled from two large databases that conveyed the basic six emotions (happiness, sadness, anger, fear, surprise, and disgust) either in posed (BU-4DFE) or spontaneous (UT-Dallas) form. Results revealed a recognition advantage for human observers over automatic classification. Among the eight classifiers, there was considerable variance in recognition accuracy ranging from 48% to 62%. Subsequent analyses per type of expression revealed that performance by the two best performing classifiers approximated those of human observers, suggesting high agreement for posed expressions. However, classification accuracy was consistently lower (although above chance level) for spontaneous affective behavior. The findings indicate potential shortcomings of existing out-of-the-box classifiers for measuring emotions, and highlight the need for more spontaneous facial databases that can act as a benchmark in the training and testing of automatic emotion recognition systems. We further discuss some limitations of analyzing facial expressions that have been recorded in controlled environments.

Social Context Disambiguates the Interpretation of Laughter.

Despite being a pan-cultural phenomenon, laughter is arguably the least understood behaviour deployed in social interaction. As well as being a response to humour, it has other important functions including promoting social affiliation, developing cooperation and regulating competitive behaviours. This multi-functional feature of laughter marks it as an adaptive behaviour central to facilitating social cohesion. However, it is not clear how laughter achieves this social cohesion. We consider two approaches to understanding how laughter facilitates social cohesion - the 'representational' approach and the 'affect-induction' approach. The representational approach suggests that laughter conveys information about the expresser's emotional state, and the listener decodes this information to gain knowledge about the laugher's felt state. The affect-induction approach views laughter as a tool to influence the affective state of listeners. We describe a modified version of the affect-induction approach, in which laughter is combined with additional factors - including social context, verbal information, other social signals and knowledge of the listener's emotional state - to influence an interaction partner. This view asserts that laughter by itself is ambiguous: the same laughter may induce positive or negative affect in a listener, with the outcome determined by the combination of these additional factors. Here we describe two experiments exploring which of these approaches accurately describes laughter. Participants judged the genuineness of audio-video recordings of social interactions containing laughter. Unknown to the participants the recordings contained either the original laughter or replacement laughter from a different part of the interaction. When replacement laughter was matched for intensity, genuineness judgements were similar to judgements of the original unmodified recordings. When replacement laughter was not matched for intensity, genuineness judgements were generally significantly lower. These results support the affect-induction view of laughter by suggesting that laughter is inherently underdetermined and ambiguous, and that its interpretation is determined by the context in which it occurs.

Tweet for Behavior Change: Using Social Media for the Dissemination of Public Health Messages.

BACKGROUND: Social media public health campaigns have the advantage of tailored messaging at low cost and large reach, but little is known about what would determine their feasibility as tools for inducing attitude and behavior change. OBJECTIVE: The aim of this study was to test the feasibility of designing, implementing, and evaluating a social media-enabled intervention for skin cancer prevention. METHODS: A quasi-experimental feasibility study used social media (Twitter) to disseminate different message "frames" related to care in the sun and cancer prevention. Phase 1 utilized the Northern Ireland cancer charity's Twitter platform (May 1 to July 14, 2015). Following a 2-week "washout" period, Phase 2 commenced (August 1 to September 30, 2015) using a bespoke Twitter platform. Phase 2 also included a Thunderclap, whereby users allowed their social media accounts to automatically post a bespoke message on their behalf. Message frames were categorized into 5 broad categories: humor, shock or disgust, informative, personal stories, and opportunistic. Seed users with a notable following were contacted to be "influencers" in retweeting campaign content. A pre- and postintervention Web-based survey recorded skin cancer prevention knowledge and attitudes in Northern Ireland (population 1.8 million). RESULTS: There were a total of 417,678 tweet impressions, 11,213 engagements, and 1211 retweets related to our campaign. Shocking messages generated the greatest impressions (shock, n=2369; informative, n=2258; humorous, n=1458; story, n=1680), whereas humorous messages generated greater engagement (humorous, n=148; shock, n=147; story, n=117; informative, n=100) and greater engagement rates compared with story tweets. Informative messages, resulted in the greatest number of shares (informative, n=17; humorous, n=10; shock, n=9; story, n=7). The study findings included improved knowledge of skin cancer severity in a pre- and postintervention Web-based survey, with greater awareness that skin cancer is the most common form of cancer (preintervention: 28.4% [95/335] vs postintervention: 39.3% [168/428] answered "True") and that melanoma is most serious (49.1% [165/336] vs 55.5% [238/429]). The results also show improved attitudes toward ultraviolet (UV) exposure and skin cancer with a reduction in agreement that respondents "like to tan" (60.5% [202/334] vs 55.6% [238/428]). CONCLUSIONS: Social media-disseminated public health messages reached more than 23% of the Northern Ireland population. A Web-based survey suggested that the campaign might have contributed to improved knowledge and attitudes toward skin cancer among the target population. Findings suggested that shocking and humorous messages generated greatest impressions and engagement, but information-based messages were likely to be shared most. The extent of behavioral change as a result of the campaign remains to be explored, however, the change of attitudes and knowledge is promising. Social media is an inexpensive, effective method for delivering public health messages. However, existing and traditional process evaluation methods may not be suitable for social media.

Modeling continuous self-report measures of perceived emotion using generalized additive mixed models.

Emotion research has long been dominated by the "standard method" of displaying posed or acted static images of facial expressions of emotion. While this method has been useful, it is unable to investigate the dynamic nature of emotion expression. Although continuous self-report traces have enabled the measurement of dynamic expressions of emotion, a consensus has not been reached on the correct statistical techniques that permit inferences to be made with such measures. We propose generalized additive models and generalized additive mixed models as techniques that can account for the dynamic nature of such continuous measures. These models allow us to hold constant shared components of responses that are due to perceived emotion across time, while enabling inference concerning linear differences between groups. The generalized additive mixed model approach is preferred, as it can account for autocorrelation in time series data and allows emotion decoding participants to be modeled as random effects. To increase confidence in linear differences, we assess the methods that address interactions between categorical variables and dynamic changes over time. In addition, we provide comments on the use of generalized additive models to assess the effect size of shared perceived emotion and discuss sample sizes. Finally, we address additional uses, the inference of feature detection, continuous variable interactions, and measurement of ambiguity.

Keeping it real! Enhancing realism in standardised patient OSCE stations.

BACKGROUND: Objective structured clinical examinations (OSCEs) are a commonly used method of assessing clinical competency in health care education. They can provide an opportunity to observe candidates interacting with patients. There are many challenges in using real patients in OSCEs, and increasingly standardised patients are being used as a preference. However, by using standardised patients there is a risk of making the encounter artificial and removed from actual clinical practice. CONTEXT: Efforts made in terms of cognitive, auditory, visual, tactile, psychological and emotional cues can minimise the differences between a simulated and real clinical scenario. However, a number of factors, including feasibility, cost and usability, need to be considered if such techniques are to be practicable within an OSCE framework. INNOVATION: This article describes a series of techniques that have been used in our institution to enhance the realism of a standardised patient encounter in an OSCE. Efforts in preparing standardised patient roles, and how they portray these roles, will be considered. A wide variety of equipment can also be used in combination with a patient and the surrounding environment, which can further enhance the authenticity of the simulated scenario. IMPLICATIONS: By enhancing the realism in simulated patient OSCE encounters, there is potential to trigger more authentic conscious responses from candidates and implicit reactions that the candidates themselves may be less aware of. Furthermore, using such techniques may allow faculty members to select scenarios that were previously not thought possible in an OSCE.

Cross-cultural patterns in dynamic ratings of positive and negative natural emotional behaviour.

BACKGROUND: Studies of cross-cultural variations in the perception of emotion have typically compared rates of recognition of static posed stimulus photographs. That research has provided evidence for universality in the recognition of a range of emotions but also for some systematic cross-cultural variation in the interpretation of emotional expression. However, questions remain about how widely such findings can be generalised to real life emotional situations. The present study provides the first evidence that the previously reported interplay between universal and cultural influences extends to ratings of natural, dynamic emotional stimuli. METHODOLOGY/PRINCIPAL FINDINGS: Participants from Northern Ireland, Serbia, Guatemala and Peru used a computer based tool to continuously rate the strength of positive and negative emotion being displayed in twelve short video sequences by people from the United Kingdom engaged in emotional conversations. Generalized additive mixed models were developed to assess the differences in perception of emotion between countries and sexes. Our results indicate that the temporal pattern of ratings is similar across cultures for a range of emotions and social contexts. However, there are systematic differences in intensity ratings between the countries, with participants from Northern Ireland making the most extreme ratings in the majority of the clips. CONCLUSIONS/SIGNIFICANCE: The results indicate that there is strong agreement across cultures in the valence and patterns of ratings of natural emotional situations but that participants from different cultures show systematic variation in the intensity with which they rate emotion. Results are discussed in terms of both 'in-group advantage' and 'display rules' approaches. This study indicates that examples of natural spontaneous emotional behaviour can be used to study cross-cultural variations in the perception of emotion.