Dataset Information

Psychiatry Outpatients' Willingness to Share Social Media Posts and Smartphone Data for Research and Clinical Purposes: Survey Study.

ABSTRACT: BACKGROUND:Psychiatry research has begun to leverage data collected from patients' social media and smartphone use. However, information regarding the feasibility of utilizing such data in an outpatient setting and the acceptability of such data in research and practice is limited. OBJECTIVE:This study aimed at understanding the outpatients' willingness to have information from their social media posts and their smartphones used for clinical or research purposes. METHODS:In this survey study, we surveyed patients (N=238) in an outpatient clinic waiting room. Willingness to share social media and passive smartphone data was summarized for the sample as a whole and broken down by sex, age, and race. RESULTS:Most patients who had a social media account and who were receiving talk therapy treatment (74.4%, 99/133) indicated that they would be willing to share their social media posts with their therapists. The percentage of patients willing to share passive smartphone data with researchers varied from 40.8% (82/201) to 60.7% (122/201) depending on the parameter, with sleep duration being the parameter with the highest percentage of patients willing to share. A total of 30.4% of patients indicated that media stories of social media privacy breaches made them more hesitant about sharing passive smartphone data with researchers. Sex and race were associated with willingness to share smartphone data, with men and whites being the most willing to share. CONCLUSIONS:Our results indicate that most patients in a psychiatric outpatient setting would share social media and passive smartphone data and that further research elucidating patterns of willingness to share passive data is needed.

SUBMITTER: Rieger A

PROVIDER: S-EPMC6754680 | biostudies-other | 2019 Aug

REPOSITORIES: biostudies-other

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Psychiatry Outpatients' Willingness to Share Social Media Posts and Smartphone Data for Research and Clinical Purposes: Survey Study.

Rieger Agnes A Gaines Averi A Barnett Ian I Baldassano Claudia Frances CF Connolly Gibbons Mary Beth MB Crits-Christoph Paul P

JMIR formative research 20190829 3

<h4>Background</h4>Psychiatry research has begun to leverage data collected from patients' social media and smartphone use. However, information regarding the feasibility of utilizing such data in an outpatient setting and the acceptability of such data in research and practice is limited.<h4>Objective</h4>This study aimed at understanding the outpatients' willingness to have information from their social media posts and their smartphones used for clinical or research purposes.<h4>Methods</h4>In ...[more]

PMID: 31493326

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Project description:BackgroundThe proliferation of vaccine misinformation on social media has seriously corrupted the public's confidence in vaccination. Proactively sharing provaccination messages on social media is a cost-effective way to enhance global vaccination rates and resist vaccine misinformation. However, few strategies for encouraging the public to proactively share vaccine-related knowledge on social media have been developed.ObjectiveThis research examines the effect of value type (individual vs collective) and message framing (gain vs loss) on influenza vaccination intention (experiment 1) and the willingness to share provaccination messages (experiment 2) among Chinese adults during the COVID-19 pandemic. The primary aim was to evaluate whether messages that emphasized collective value were more effective in increasing the willingness to share than messages that emphasized individual value.MethodsWe enrolled 450 Chinese adults for experiment 1 (n=250, 55.6%) and experiment 2 (n=200, 44.4%). Participants were randomly assigned to individual-gain, individual-loss, collective-gain, or collective-loss conditions with regard to the message in each experiment using the online survey platform's randomization function. Experiment 1 also included a control group. The primary outcome was influenza vaccination intention in experiment 1 and the willingness to share provaccination messages in experiment 2.ResultsThe valid sample included 213 adults in experiment 1 (females: n=151, 70.9%; mean age 29 [SD 9] years; at least some college education: n=202, 94.8%; single: n=131, 61.5%) and 171 adults in experiment 2 (females: n=106, 62.0%; mean age 28 [SD 7] years; at least some college education: n=163, 95.3%; single: n=95, 55.6%). Influenza vaccination intention was stronger in the individual-value conditions than in the collective-value conditions (F3,166=4.96, P=.03, η2=0.03). The reverse result was found for the willingness to share provaccination messages (F3,165=6.87, P=.01, η2=0.04). Specifically, participants who received a message emphasizing collective value had a higher intention to share the message than participants who read a message emphasizing individual value (F3,165=6.87, P=.01, η2=0.04), and the perceived responsibility for message sharing played a mediating role (indirect effect=0.23, 95% lower limit confidence interval [LLCI] 0.41, 95% upper limit confidence interval [ULCI] 0.07). In addition, gain framing facilitated influenza vaccination intention more than loss framing (F3,166=5.96, P=.02, η2=0.04). However, experiment 2 did not find that message framing affected message-sharing willingness. Neither experiment found an interaction between value type and message framing.ConclusionsStrengthened individual value rather than collective value is more likely to persuade Chinese adults to vaccinate. However, these adults are more likely to share a message that emphasizes collective rather than individual value, and the perceived responsibility for message sharing plays a mediating role.

Project description:BackgroundPatient-based analysis of social media is a growing research field with the aim of delivering precision medicine but it requires accurate classification of posts relating to patients' experiences. We motivate the need for this type of classification as a pre-processing step for further analysis of social media data in the context of related work in this area. In this paper we present experiments for a three-way document classification by patient voice, professional voice or other. We present results for a convolutional neural network classifier trained on English data from two different data sources (Reddit and Twitter) and two domains (cardiovascular and skin diseases).ResultsWe found that document classification by patient voice, professional voice or other can be done consistently manually (0.92 accuracy). Annotators agreed roughly equally for each domain (cardiovascular and skin) but they agreed more when annotating Reddit posts compared to Twitter posts. Best classification performance was obtained when training two separate classifiers for each data source, one for Reddit and one for Twitter posts, when evaluating on in-source test data for both test sets combined with an overall accuracy of 0.95 (and macro-average F1 of 0.92) and an F1-score of 0.95 for patient voice only.ConclusionThe main conclusion resulting from this work is that combining social media data from platforms with different characteristics for training a patient and professional voice classifier does not result in best possible performance. We showed that it is best to train separate models per data source (Reddit and Twitter) instead of a model using the combined training data from both sources. We also found that it is preferable to train separate models per domain (cardiovascular and skin) while showing that the difference to the combined model is only minor (0.01 accuracy). Our highest overall F1-score (0.95) obtained for classifying posts as patient voice is a very good starting point for further analysis of social media data reflecting the experience of patients.

Dataset Information

Psychiatry Outpatients' Willingness to Share Social Media Posts and Smartphone Data for Research and Clinical Purposes: Survey Study.

Publications

Psychiatry Outpatients' Willingness to Share Social Media Posts and Smartphone Data for Research and Clinical Purposes: Survey Study.

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