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1.
Z Psychosom Med Psychother ; 65(3): 272-287, 2019 Sep.
Artigo em Alemão | MEDLINE | ID: mdl-31477000

RESUMO

Development of an evaluation system for online self-help groups by using the example of German-speaking cancer forums Objectives: This paper pursues the question how the quality of forums can be evaluated. Therefor a grading system was designed and 23 German-speaking cancer forums were evaluated by content and formal criteria Methods: Using a keyword-based internet search, 23 forums were identified. Data was gathered about: number of themes, posts and members, structure, key subjects and type of financing. Furthermore, an evaluation system was developed, with which the forums where assessed. Results: The forums were divided in forums with (n = 10) and without (n = 9) focus on a type of cancer. Four are health portals with forum-function. The quality of online cancer forums is heterogeneous, the evaluation resulted an average quality index of 2.7 for the total cancer forums Conclusion: A good information editing, moderation, data protection and transparency are important quality criteria. The evaluation of forums may help the patients, to autonomously value the quality of the presented information.


Assuntos
Internet , Linguagem , Neoplasias , Avaliação de Programas e Projetos de Saúde/métodos , Grupos de Autoajuda/normas , Mídias Sociais/normas , Alemanha , Humanos
4.
Stud Health Technol Inform ; 264: 50-54, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31437883

RESUMO

Suicide is a growing public health concern in online communities. In this paper, we analyze online communications on the topic of suicide in the social networking platform, Reddit. We combine lexical text characteristics with semantic information to identify comments with features of suicide attempts and methods. Then, we develop a set of machine learning methods to automatically extract suicide methods and classify the user comments. Our classification methods performance varied between suicide experiences, with F1-scores up to 0.92 for "drugs" and greater than 0.82 for "hanging" and "other methods". Our exploratory analysis reveals that the most frequent reported suicide methods are drug overdose, hanging, and wrist-cutting.


Assuntos
Saúde Mental , Mídias Sociais , Rede Social , Tentativa de Suicídio , Sobreviventes , Humanos , Aprendizado de Máquina
5.
Stud Health Technol Inform ; 264: 60-64, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31437885

RESUMO

We report initial experiments for analyzing social media through an NLP annotation tool on web posts about medications of current interests (baclofen, levothyroxine and vaccines) and summaries of product characteristics (SPCs). We conducted supervised experiments on a subset of messages annotated by experts according to positive or negative misuse; results ranged from 0.62 to 0.91 of F-score. We also annotated both SPCs and another set of posts to compare MedDRA annotations in each source. A pharmacovigilance expert checked the output and confirmed that entities not found in SCPs might express drug misuse or unknown ADRs.


Assuntos
Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Farmacovigilância , Mídias Sociais , Coleta de Dados , Humanos
6.
Stud Health Technol Inform ; 264: 1520-1521, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438211

RESUMO

In this study we developed an ontology for accessing online health information related to pregnancy. Social media data and the categories in the literature on pregnancy information were used to collect terms for identifying class and class hierarchy. The developed ontology included 241 classes and 788 synonyms, with six superclasses. This ontology can be used to provide appropriate information based on a needs assessment.


Assuntos
Gestão da Informação em Saúde , Mídias Sociais , Feminino , Humanos , Determinação de Necessidades de Cuidados de Saúde , Gravidez
7.
Stud Health Technol Inform ; 264: 959-963, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438066

RESUMO

Pre-Exposure Prophylaxis (PrEP) is an approach for preventing the human immunodeficiency virus (HIV), which entails the administration of antiretroviral medication to high-risk seronegative persons. If taken correctly, PrEP can reduce HIV infection risk by more than 90%. The aim of this study was to identify and examine PrEP-related perceptions and trends discussed on Twitter. Using open-source technologies, text-mining and interactive visualisation techniques, a comprehensive data gathering and analytics Web-based platform was developed to facilitate the study objectives. Our results demonstrate that monitoring of PrEP-related discussions on Twitter can be detected over time and valuable insights can be obtained concerning issues of PrEP awareness, expressed opinions, perceived barriers and key discussion points on its adoption. The proposed platform could support public-health professionals and policy makers in PrEP monitoring, facilitating informed decision making and strategy planning for efficient HIV combination prevention.


Assuntos
Infecções por HIV , Profilaxia Pré-Exposição , Mídias Sociais , Fármacos Anti-HIV , Conscientização , Infecções por HIV/cirurgia , Humanos
8.
Stud Health Technol Inform ; 264: 964-968, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438067

RESUMO

Social media are proposed as a complementary data source for detection and characterisation of adverse drug reactions. While signal detection algorithms were implemented for generating signals in pharmacovigilance databases, the implementation of a graphical user interface supporting the selection and display of algorithms' results is not documented in the medical literature. Although collecting information on the chronology and the impact of adverse drug reactions is desirable to enable causality and quality assessment of potential signals detected in patients' posts, no tool has been proposed yet to consider such data. We describe here two approaches, and the corresponding tools we implemented for: (1) quantitative approach based on signal detection algorithms, and (2) qualitative approach based on expert review of patient's posts. Future work will focus on implementing other statistical methods, exploring the complementarity of both approaches on a larger scale, and prioritizing the posts to manually evaluate after applying appropriate signal detection methods.


Assuntos
Mídias Sociais , Tiofenos/efeitos adversos , Sistemas de Notificação de Reações Adversas a Medicamentos , Humanos , Farmacovigilância
9.
Stud Health Technol Inform ; 264: 1065-1069, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438088

RESUMO

Social media presents a rich opportunity to gather health information with limited intervention through the analysis of completely unstructured and unlabeled microposts. We sought to estimate the health-related quality of life (HRQOL) of Twitter users using automated semantic processing methods. We collected tweets from 878 Twitter users recruited through online solicitation and in-person contact with patients. All participants completed the four-item Centers for Disease Control Healthy Days Questionnaire at the time of enrollment and 30 days later to measure "ground truth" HRQOL. We used a combination of document frequency analysis, sentiment analysis, topic analysis, and concept mapping to extract features from tweets, which we then used to estimate dichotomized HRQOL ("high" vs. "low") using logistic regression. Binary HRQOL status was estimated with moderate performance (AUC = 0.64). This result indicates that free-range social media data only offers a window into HRQOL, but does not afford direct access to current health status.


Assuntos
Mídias Sociais , Coleta de Dados , Nível de Saúde , Humanos , Qualidade de Vida , Semântica
10.
Stud Health Technol Inform ; 264: 1688-1689, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438294

RESUMO

This paper presents findings from a series of focus groups which is exploring the implications of, and stakeholder requirements for, integrating social media technologies and 'smart home' technologies to connect older adults with their formal support networks (i.e. to healthcare and social service providers) thus enabling them to live independently at home.


Assuntos
Serviços de Assistência Domiciliar , Mídias Sociais , Idoso , Assistência à Saúde , Grupos Focais , Humanos , Tecnologia
11.
Stud Health Technol Inform ; 264: 1208-1212, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438117

RESUMO

Sentiment analysis has been increasingly used to analyze online social media data such as tweets and health forum posts. However, previous studies often adopted existing, general-purpose sentiment analyzers developed in non-healthcare domains, without assessing their validity and without customizing them for the specific study context. In this work, we empirically evaluated three general-purpose sentiment analyzers popularly used in previous studies (Stanford Core NLP Sentiment Analysis, TextBlob, and VADER), based on two online health datasets and a general-purpose dataset as the baseline. We illustrate that none of these general-purpose sentiment analyzers were able to produce satisfactory classifications of sentiment polarity. Further, these sentiment analyzers generated inconsistent results when applied to the same dataset, and their performance varies to a great extent across the two health datasets. Significant future work is therefore needed to develop context-specific sentiment analysis tools for analyzing online health data.


Assuntos
Mídias Sociais
12.
Stud Health Technol Inform ; 264: 1228-1232, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438121

RESUMO

Unhealthy behaviors are a socioeconomic burden and lead to the development of chronic diseases. Relapse is a common issue that most individuals deal with as they adopt and sustain a positive healthy lifestyle. Proper identification of behavioral transitions can help design agile, adaptive, and just-in-time interventions. In this paper, we present a methodology that integrates qualitative coding, machine learning, and formal data analysis using stage transition probabilities and linguistics-based text analysis to track shifts in stages of behavior change as embedded in journal entries recorded by users in an online community for tobacco cessation. Results indicate that our semi-automated stage identification method has an accuracy of 90%. Further analysis revealed stage-specific language features and transition probabilities. Implications for targeted social interventions are discussed.


Assuntos
Mídias Sociais , Humanos , Linguística , Aprendizado de Máquina
13.
Stud Health Technol Inform ; 264: 1293-1297, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438134

RESUMO

Among American women, the rate of breast cancer is only second to lung cancer. An estimated 12.4% women will develop breast cancer over the course of their lifetime. The widespread use of social media across the socio-economic spectrum offers unparalleled ways to facilitate information sharing, in particular as it pertains to health. Social media is also used by many healthcare stakeholders, ranging from government agencies to healthcare industry, to disseminate health information and to engage patients. The purpose of this study is to investigate people's perceptions and attitudes related to breast cancer, especially those that are related to physical activities, on Twitter. To achieve this, we first identified and collected tweets related to breast cancer; and then used topic modeling and sentiment analysis techniques to understand discussion themes and quantify Twitter users' perceptions and emotions with respect tobreast cancer to answer 5 research questions.


Assuntos
Neoplasias da Mama , Mídias Sociais , Atitude , Coleta de Dados , Feminino , Humanos
14.
Stud Health Technol Inform ; 264: 1342-1346, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438144

RESUMO

The purpose of this study is to describe the effect of education in professional boundaries on the use and management of social media by using quantitative survey methods to ask "What are the social networking behaviours of student nurses following education in professional boundaries? Findings from this research indicate that student nurses are active SNS users, primarily for personal engagement. Facebook is overwhelmingly the most popular SNS, with snapchat and Instagram also commonly used. While students primarily used SNS for personal reasons, many reported SNS use for educational / professional purposes as well, including to discuss academic related topics. Most students responded that they were aware of privacy settings on SNS, however there is a discrepancy between awareness of privacy settings and the number of students implementing the privacy features.


Assuntos
Mídias Sociais , Estudantes de Enfermagem , Atitude , Humanos , Privacidade , Rede Social
15.
Stud Health Technol Inform ; 264: 1468-1469, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438185

RESUMO

The trauma of cancer often leaves survivors with PTSD. Tweets posted on Twitter usually reflect the users' psychological state, which is convenient for data collection. However, Twitter also contains a mix of noisy and genuine tweets. The process of manually identifying genuine tweets is expensive and time-consuming. Thus, we propose a knowledge transfer technique to filter out unrelated tweets. Our experiments show that our model outperforms the baselines.


Assuntos
Sobreviventes de Câncer , Neoplasias , Mídias Sociais , Transtornos de Estresse Pós-Traumáticos , Coleta de Dados , Humanos
16.
An Bras Dermatol ; 94(3): 298-303, 2019 Jul 29.
Artigo em Inglês | MEDLINE | ID: mdl-31365658

RESUMO

BACKGROUND: Hidradenitis suppurativa is a complex and infrequent autoinflammatory disease that impacts on quality of life. Its pathogenesis is not fully understood, which limits the development of curative treatments. OBJECTIVES: To evaluate clinical and quality of life aspects of hidradenitis suppurativa patients from a social group on the Internet. METHODS: A cross-sectional, Internet-based survey study among participants in a discussion group (Facebook) of individuals with hidradenitis suppurativa. Patients were asked to answer a questionnaire about clinical-demographic aspects and quality of life (DLQI-BRA). RESULTS: A total of 390 individuals agreed to participate in the study, 82% of them female, median age (p25-p75), of 31 (25-37) years old, disease onset at 15 (13-23) years, family member affected in 20% of cases, overweight (BMI 29 [25-33]) kg/m2 and severe impact on quality of life (DLQI 20 [13-25]). Regarding Hurley's classification, the participants provided information that enabled classification into: I (19%), II (52%) and III (29%). More severe cases were associated with males (OR = 1.69), higher weight (BMI: OR = 1.03) non-white color (OR = 1.43) and higher frequency of other autoinflammatory diseases (OR = 1.37). STUDY LIMITATIONS: Voluntary adherence survey with self-completion of the questionnaire by 390 from about 1600 group members. CONCLUSIONS: Hidradenitis suppurativa patients who participated in a social network group had onset of the disease after puberty, with a predominance in females and overweight people, with great impact on the quality of life.


Assuntos
Pesquisa Participativa Baseada na Comunidade/métodos , Hidradenite Supurativa/psicologia , Qualidade de Vida , Mídias Sociais , Adulto , Idoso , Índice de Massa Corporal , Comorbidade , Estudos Transversais , Feminino , Hidradenite Supurativa/terapia , Humanos , Internet , Masculino , Pessoa de Meia-Idade , Índice de Gravidade de Doença , Fatores Sexuais , Inquéritos e Questionários
18.
Stud Health Technol Inform ; 264: 1542-1543, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438222

RESUMO

The CrowdHEALTH project intends to integrate high volumes of health-related heterogeneous data from multiple sources with the aim of supporting policy making decisions. The European Federation of Medical Informatics supports the development of an effective Communication and Collaboration Plan.A dissemination strategy has been applied for this purpose considering appropriate messages, target audience, tools, and channels to achieve the highest impact and the first results of social media dissemination are presented here.


Assuntos
Mídias Sociais , Tomada de Decisões , Políticas , Formulação de Políticas
19.
Stud Health Technol Inform ; 264: 323-327, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31437938

RESUMO

Despite the high consumption of dietary supplements (DS), few reliable, relevant, and comprehensive online resources could satisfy information seekers. This research study aims to understand consumer information needs on DS using topic modeling, and to evaluate accuracy in correctly identifying topics from social media. We retrieved 16,095 unique questions posted on Yahoo! Answers relating to 438 unique DS ingredients mentioned in sub-section, "Alternative medicine" under the section, "Health" . We implemented an unsupervised topic modeling method, Correlation Explanation (CorEx) to unveil the various topics in which consumers are most interested. We manually reviewed the keywords of all the 200 topics generated by CorEx and assigned them to 38 health-related categories, corresponding to 12 higher-level groups. We found high accuracy (90-100%) in identifying questions that correctly align with the selected topics. The results could guide us to generate a more comprehensive and structured DS resource based on consumers' information needs.


Assuntos
Mídias Sociais , Suplementos Nutricionais
20.
Stud Health Technol Inform ; 264: 333-337, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31437940

RESUMO

Social media may serve as an important platform for the monitoring of population-level opioid abuse in near real-time. Our objectives for this study were to (i) manually characterize a sample of opioid-mentioning Twitter posts, (ii) compare the rates of abuse/misuse related posts between prescription and illicit opiods, and (iii) to implement and evaluate the performances ofsupervised machine learning algorithms for the characterization of opioid-related chatter, which can potentially automate social media based monitoring in the future.. We annotated a total of 9006 tweets into four categories, trained several machine learning algorithms and compared their performances. Deep convolutional neural networks marginally outperformed support vector machines and random forests, with an accuracy of 70.4%. Lack of context in tweets and data imbalance resulted in misclassification of many tweets to the majority class. The automatic classification experiments produced promising results, although there is room for improvement.


Assuntos
Mídias Sociais , Analgésicos Opioides , Ciência de Dados , Humanos , Aprendizado de Máquina , Transtornos Relacionados ao Uso de Opioides
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