Developing a clinical decision support system software prototype that assists in the management of patients with self-harm in the emergency department: protocol of the PERMANENS project.

BACKGROUND: Self-harm presents a significant public health challenge. Emergency departments (EDs) are crucial healthcare settings in managing self-harm, but clinician uncertainty in risk assessment may contribute to ineffective care. Clinical Decision Support Systems (CDSSs) show promise in enhancing care processes, but their effective implementation in self-harm management remains unexplored. METHODS: PERMANENS comprises a combination of methodologies and study designs aimed at developing a CDSS prototype that assists clinicians in the personalized assessment and management of ED patients presenting with self-harm. Ensemble prediction models will be constructed by applying machine learning techniques on electronic registry data from four sites, i.e., Catalonia (Spain), Ireland, Norway, and Sweden. These models will predict key adverse outcomes including self-harm repetition, suicide, premature death, and lack of post-discharge care. Available registry data include routinely collected electronic health record data, mortality data, and administrative data, and will be harmonized using the OMOP Common Data Model, ensuring consistency in terminologies, vocabularies and coding schemes. A clinical knowledge base of effective suicide prevention interventions will be developed rooted in a systematic review of clinical practice guidelines, including quality assessment of guidelines using the AGREE II tool. The CDSS software prototype will include a backend that integrates the prediction models and the clinical knowledge base to enable accurate patient risk stratification and subsequent intervention allocation. The CDSS frontend will enable personalized risk assessment and will provide tailored treatment plans, following a tiered evidence-based approach. Implementation research will ensure the CDSS' practical functionality and feasibility, and will include periodic meetings with user-advisory groups, mixed-methods research to identify currently unmet needs in self-harm risk assessment, and small-scale usability testing of the CDSS prototype software. DISCUSSION: Through the development of the proposed CDSS software prototype, PERMANENS aims to standardize care, enhance clinician confidence, improve patient satisfaction, and increase treatment compliance. The routine integration of CDSS for self-harm risk assessment within healthcare systems holds significant potential in effectively reducing suicide mortality rates by facilitating personalized and timely delivery of effective interventions on a large scale for individuals at risk of suicide.

Evaluating Behavioral and Linguistic Changes During Drug Treatment for Depression Using Tweets in Spanish: Pairwise Comparison Study.

BACKGROUND: Depressive disorders are the most common mental illnesses, and they constitute the leading cause of disability worldwide. Selective serotonin reuptake inhibitors (SSRIs) are the most commonly prescribed drugs for the treatment of depressive disorders. Some people share information about their experiences with antidepressants on social media platforms such as Twitter. Analysis of the messages posted by Twitter users under SSRI treatment can yield useful information on how these antidepressants affect users' behavior. OBJECTIVE: This study aims to compare the behavioral and linguistic characteristics of the tweets posted while users were likely to be under SSRI treatment, in comparison to the tweets posted by the same users when they were less likely to be taking this medication. METHODS: In the first step, the timelines of Twitter users mentioning SSRI antidepressants in their tweets were selected using a list of 128 generic and brand names of SSRIs. In the second step, two datasets of tweets were created, the in-treatment dataset (made up of the tweets posted throughout the 30 days after mentioning an SSRI) and the unknown-treatment dataset (made up of tweets posted more than 90 days before or more than 90 days after any tweet mentioning an SSRI). For each user, the changes in behavioral and linguistic features between the tweets classified in these two datasets were analyzed. 186 users and their timelines with 668,842 tweets were finally included in the study. RESULTS: The number of tweets generated per day by the users when they were in treatment was higher than it was when they were in the unknown-treatment period (P=.001). When the users were in treatment, the mean percentage of tweets posted during the daytime (from 8 AM to midnight) increased in comparison to the unknown-treatment period (P=.002). The number of characters and words per tweet was higher when the users were in treatment (P=.03 and P=.02, respectively). Regarding linguistic features, the percentage of pronouns that were first-person singular was higher when users were in treatment (P=.008). CONCLUSIONS: Behavioral and linguistic changes have been detected when users with depression are taking antidepressant medication. These features can provide interesting insights for monitoring the evolution of this disease, as well as offering additional information related to treatment adherence. This information may be especially useful in patients who are receiving long-term treatments such as people suffering from depression.

Detecting Signs of Depression in Tweets in Spanish: Behavioral and Linguistic Analysis.

BACKGROUND: Mental disorders have become a major concern in public health, and they are one of the main causes of the overall disease burden worldwide. Social media platforms allow us to observe the activities, thoughts, and feelings of people's daily lives, including those of patients suffering from mental disorders. There are studies that have analyzed the influence of mental disorders, including depression, in the behavior of social media users, but they have been usually focused on messages written in English. OBJECTIVE: The study aimed to identify the linguistic features of tweets in Spanish and the behavioral patterns of Twitter users who generate them, which could suggest signs of depression. METHODS: This study was developed in 2 steps. In the first step, the selection of users and the compilation of tweets were performed. A total of 3 datasets of tweets were created, a depressive users dataset (made up of the timeline of 90 users who explicitly mentioned that they suffer from depression), a depressive tweets dataset (a manual selection of tweets from the previous users, which included expressions indicative of depression), and a control dataset (made up of the timeline of 450 randomly selected users). In the second step, the comparison and analysis of the 3 datasets of tweets were carried out. RESULTS: In comparison with the control dataset, the depressive users are less active in posting tweets, doing it more frequently between 23:00 and 6:00 (P<.001). The percentage of nouns used by the control dataset almost doubles that of the depressive users (P<.001). By contrast, the use of verbs is more common in the depressive users dataset (P<.001). The first-person singular pronoun was by far the most used in the depressive users dataset (80%), and the first- and the second-person plural pronouns were the least frequent (0.4% in both cases), this distribution being different from that of the control dataset (P<.001). Emotions related to sadness, anger, and disgust were more common in the depressive users and depressive tweets datasets, with significant differences when comparing these datasets with the control dataset (P<.001). As for negation words, they were detected in 34% and 46% of tweets in among depressive users and in depressive tweets, respectively, which are significantly different from the control dataset (P<.001). Negative polarity was more frequent in the depressive users (54%) and depressive tweets (65%) datasets than in the control dataset (43.5%; P<.001). CONCLUSIONS: Twitter users who are potentially suffering from depression modify the general characteristics of their language and the way they interact on social media. On the basis of these changes, these users can be monitored and supported, thus introducing new opportunities for studying depression and providing additional health care services to people with this disorder.

Premature Death, Suicide, and Nonlethal Intentional Self-Harm After Psychiatric Discharge.

Importance: There is a need for representative research on serious adverse outcomes following discharge from psychiatric hospitalization. Objective: To compare rates of premature death, suicide, and nonlethal intentional self-harm after psychiatric discharge with rates in the general population and investigate associations of these outcomes with relevant variables associated with the index psychiatric hospitalization. Design, Setting, and Participants: This retrospective cohort study included all residents from Catalonia, Spain (7.6 million population), who had psychiatric hospitalizations between January 1, 2014, and December 31, 2018, and were older than 10 years at the index (first) hospitalization. Follow-up was until December 31, 2019. Statistical analysis was performed from December 1, 2022, through April 11, 2024. Exposures: Socioeconomic status, psychiatric diagnoses, duration of index hospitalization, and number of previous psychiatric hospitalizations. Main Outcomes and Measures: Postdischarge premature death (ie, all-cause death before age 70 years) and suicide (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10] code range X60-X84), identified using mortality data, and postdischarge nonlethal intentional self-harm, identified using electronic health record and self-harm case register data. Standardized mortality ratios (SMRs) compared rates of premature death and suicide between the cohort and the general population. Fully adjusted, multivariable, cause-specific Cox proportional hazards regression models for the 3 outcomes were fitted. Results: A total of 49 108 patients discharged from psychiatric hospitalization were included (25 833 males [52.6%]; mean [SD] age at discharge, 44.2 [18.2] years). During follow-up, 2260 patients (4.6%) died prematurely, 437 (0.9%) died by suicide, and 4752 (9.7%) had an episode of nonlethal intentional self-harm. The overall SMR for premature death was 7.5 (95% CI, 7.2-7.9). For suicide, SMR was 32.9 (95% CI, 29.9-36.0) overall and was especially high among females (47.6 [95% CI, 40.2-54.9]). In fully adjusted sex-stratified hazard models, postdischarge premature death was associated with cognitive disorders (adjusted hazard ratio [AHR], 2.89 [95% CI, 2.24-3.74] for females; 2.59 [95% CI, 2.17-3.08] for males) and alcohol-related disorders (AHR, 1.41 [95% CI, 1.18-1.70] for females; 1.22 [95% CI, 1.09-1.37] for males). Postdischarge suicide was associated with postdischarge intentional self-harm (AHR, 2.83 [95% CI, 1.97-4.05] for females; 3.29 [95% CI, 2.47-4.40] for males), with depressive disorders (AHR, 2.13 [95% CI, 1.52-2.97]) and adjustment disorders (AHR, 1.94 [95% CI, 1.32-2.83]) among males, and with bipolar disorder among females (AHR, 1.94 [95% CI, 1.21-3.09]). Postdischarge intentional self-harm was associated with index admissions for intentional self-harm (AHR, 1.95 [95% CI, 1.73-2.21] for females; 2.62 [95% CI, 2.20-3.13] for males) as well as for adjustment disorders (AHR, 1.48 [95% CI, 1.33-1.65] for females; 1.99 [95% CI, 1.74-2.27] for males), anxiety disorders (AHR, 1.24 [95% CI, 1.10-1.39] for females; 1.36 [95% CI, 1.18-1.58] for males), depressive disorders (AHR, 1.54 [95% CI, 1.40-1.69] for females; 1.80 [95% CI, 1.58-2.04] for males), and personality disorders (AHR, 1.59 [95% CI, 1.46-1.73] for females; 1.43 [95% CI, 1.28-1.60] for males). Conclusions and Relevance: In this cohort study of patients discharged from psychiatric hospitalization, risk for premature death and suicide was significantly higher compared with the general population, suggesting individuals discharged from psychiatric inpatient care are a vulnerable population for premature death and suicidal behavior.

Treatment of systemic lupus erythematosus: Analysis of treatment patterns in adult and paediatric patients across four European countries.

OBJECTIVE: Multiple treatment options are recommended for Systemic Lupus Erythematosus (SLE) by clinical guidelines. This study aimed to explore SLE treatment patterns as there is limited real-world data of SLE medication utilisation, especially in childhood-onset SLE (cSLE). METHODS: We conducted a longitudinal cohort study using five routinely collected healthcare databases from four European countries (United Kingdom, France, Germany, and Spain). We described the characteristics of adult and paediatric patients at time of SLE diagnosis. We calculated the percentage of patients commencing SLE treatments in the first month and year after diagnosis, reported number of prescriptions, starting dose, cumulative dose, and duration of each treatment, and characterised the line of therapy. RESULTS: We characterised 11,255 patients with a first diagnosis of SLE and included 5718 in our medication utilisation analyses. The majority of adult SLE patients were female (range 80-88 %), with median age of 49 to 54 years at diagnosis. In the paediatric cohort (n = 378), 66-83 % of SLE patients were female, with median age of 12 to 16 years at diagnosis. Hydroxychloroquine and glucocorticoids were common first-line treatments in both adults and children, with second-line treatments including mycophenolate mofetil and methotrexate. Few cases of monoclonal antibody use were seen in either cohort. Initial glucocorticoid dosing in paediatric patients was often higher than in adults. CONCLUSION: Treatment choices for adult SLE patients across four European countries were in line with recent therapeutic consensus guidelines. High glucocorticoid prescriptions in paediatric patients suggests the need for steroid-sparing treatment alternatives and paediatric specific guidelines.

Incident Use of Hydroxychloroquine for the Treatment of Rheumatoid Arthritis and Systemic Lupus Erythematosus During the COVID-19 Pandemic.

OBJECTIVE: We studied whether the use of hydroxychloroquine (HCQ) for COVID-19 resulted in supply shortages for patients with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). METHODS: We used US claims data (IQVIA PHARMETRICS® Plus for Academics [PHARMETRICS]) and hospital electronic records from Spain (Institut Municipal d'Assistència Sanitària Information System [IMASIS]) to estimate monthly rates of HCQ use between January 2019 and March 2022, in the general population and in patients with RA and SLE. Methotrexate (MTX) use was estimated as a control. RESULTS: More than 13.5 million individuals (13,311,811 PHARMETRICS, 207,646 IMASIS) were included in the general population cohort. RA and SLE cohorts enrolled 135,259 and 39,295 patients, respectively, in PHARMETRICS. Incidence of MTX and HCQ were stable before March 2020. On March 2020, the incidence of HCQ increased by 9- and 67-fold in PHARMETRICS and IMASIS, respectively, and decreased in May 2020. Usage rates of HCQ went back to prepandemic trends in Spain but remained high in the United States, mimicking waves of COVID-19. No significant changes in HCQ use were noted among patients with RA and SLE. MTX use rates decreased during HCQ approval period for COVID-19 treatment. CONCLUSION: Use of HCQ increased dramatically in the general population in both Spain and the United States during March and April 2020. Whereas Spain returned to prepandemic rates after the first wave, use of HCQ remained high and followed waves of COVID-19 in the United States. However, we found no evidence of general shortages in the use of HCQ for both RA and SLE in the United States.

How medical doctors and students should use Social Media: a review of the main guidelines for proposing practical recommendations.

Social Media has grown exponentially and in the last few years there has been an increasing use amongst medical doctors and students. There is intense debate about the complexities of ensuring medical professionalism in the digital age and especially on using open and massive online services. The objectives of this paper are: first, to gather the main recommendations on using Social Media platforms and websites by medical doctors and students, which are proposed by several international organizations, institutions and universities of reference and second, to propose a set of practical recommendations, based on the comparison of the statements and items of the guidelines, in order to find agreements and differences among them and select the most common and practical items stated. A Decalogue of good practices has been drawn up, pointing out the most important aspects that should be considered, highlighting the relevance of maintaining professional behavior in these environments, taking into account the advantages and drawbacks when using them.

Comparing the Clinical Characteristics and Mortality of Residential and Non-Residential Older People with COVID-19: Retrospective Observational Study.

Nursing homes have accounted for a significant part of SARS-CoV-2 mortality, causing great social alarm. Using data collected from electronic medical records of 1,319,839 institutionalised and non-institutionalised persons ≥ 65 years, the present study investigated the epidemiology and differential characteristics between these two population groups. Our results showed that the form of presentation of the epidemic outbreak, as well as some risk factors, are different among the elderly institutionalised population with respect to those who are not. In addition to a twenty-fold increase in the rate of adjusted mortality among institutionalised individuals, the peak incidence was delayed by approximately three weeks. Having dementia was shown to be a risk factor for death, and, unlike the non-institutionalised group, neither obesity nor age were shown to be significantly associated with the risk of death among the institutionalised. These differential characteristics should be able to guide the actions to be taken by the health administration in the event of a similar infectious situation among institutionalised elderly people.

Exploring the Association of Cancer and Depression in Electronic Health Records: Combining Encoded Diagnosis and Mining Free-Text Clinical Notes.

BACKGROUND: A cancer diagnosis is a source of psychological and emotional stress, which are often maintained for sustained periods of time that may lead to depressive disorders. Depression is one of the most common psychological conditions in patients with cancer. According to the Global Cancer Observatory, breast and colorectal cancers are the most prevalent cancers in both sexes and across all age groups in Spain. OBJECTIVE: This study aimed to compare the prevalence of depression in patients before and after the diagnosis of breast or colorectal cancer, as well as to assess the usefulness of the analysis of free-text clinical notes in 2 languages (Spanish or Catalan) for detecting depression in combination with encoded diagnoses. METHODS: We carried out an analysis of the electronic health records from a general hospital by considering the different sources of clinical information related to depression in patients with breast and colorectal cancer. This analysis included ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification) diagnosis codes and unstructured information extracted by mining free-text clinical notes via natural language processing tools based on Systematized Nomenclature of Medicine Clinical Terms that mentions symptoms and drugs used for the treatment of depression. RESULTS: We observed that the percentage of patients diagnosed with depressive disorders significantly increased after cancer diagnosis in the 2 types of cancer considered-breast and colorectal cancers. We managed to identify a higher number of patients with depression by mining free-text clinical notes than the group selected exclusively on ICD-9-CM codes, increasing the number of patients diagnosed with depression by 34.8% (441/1269). In addition, the number of patients with depression who received chemotherapy was higher than those who did not receive this treatment, with significant differences (P<.001). CONCLUSIONS: This study provides new clinical evidence of the depression-cancer comorbidity and supports the use of natural language processing for extracting and analyzing free-text clinical notes from electronic health records, contributing to the identification of additional clinical data that complements those provided by coded data to improve the management of these patients.

Clinical Characterization of Patients With COVID-19 in Primary Care in Catalonia: Retrospective Observational Study.

BACKGROUND: The country of Spain has one of the highest incidences of COVID-19, with more than 1,000,000 cases as of the end of October 2020. Patients with a history of chronic conditions, obesity, and cancer are at greater risk from COVID-19; moreover, concerns surrounding the use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin type II receptor blockers (ARBs) and its relationship to COVID-19 susceptibility have increased since the beginning of the pandemic. OBJECTIVE: The objectives of this study were to compare the characteristics of patients diagnosed with COVID-19 to those of patients without COVID-19 in primary care; to determine the risk factors associated with the outcome of mortality; and to determine the potential influence of certain medications, such as ACEIs and ARBs, on the mortality of patients with COVID-19. METHODS: An observational retrospective study of patients diagnosed with COVID-19 in the Catalan Central Region of Spain between March 1 and August 17, 2020, was conducted. The data were obtained from the Primary Care Services Information Technologies System of the Catalan Institute of Health in Barcelona, Spain. RESULTS: The study population included 348,596 patients (aged >15 years) registered in the Primary Care Services Information Technologies System of the Catalan Central Region. The mean age of the patients was 49.53 years (SD 19.42), and 31.17% of the patients were aged ≥60 years. 175,484/348,596 patients (50.34%) were women. A total of 23,844/348,596 patients (6.84%) in the population studied were diagnosed with COVID-19 during the study period, and the most common clinical conditions of these patients were hypertension (5267 patients, 22.1%) and obesity (5181 patients, 21.7%). Overall, 2680/348,596 patients in the study population (0.77%) died during the study period. The number of deaths among patients without COVID-19 was 1825/324,752 (0.56%; mean age 80.6 years, SD 13.3), while among patients diagnosed with COVID-19, the number of deaths was 855/23,844 (3.58%; mean age 83.0 years, SD 10.80) with an OR of 6.58 (95% CI 6.06-7.15). CONCLUSIONS: We observed that women were more likely to contract COVID-19 than men. In addition, our study did not show that hypertension, obesity, or being treated with ACEIs or ARBs was linked to an increase in mortality in patients with COVID-19. Age is the main factor associated with mortality in patients infected with SARS-CoV-2.

[Concept and applications of the Web 3.0: an introduction for medical doctors]. / Concepto y aplicaciones de la Web 3.0: una introducción para médicos.

The development of the Internet is continuous and appears to be never-ending, although with the arrival of Web 3.0 it could be said that the Internet is what its creators intended it to be from the first moment, an extraordinary and immense organised, understandable, and easy to access data base, characteristics still not achieved. The innovations and services included in Web 3.0 will result, in the first place, in better, faster and safer access to quality information. In the second place it should provide better personalisation of the health services that Internet users access, avoiding irrelevant information that may contain wrong, false and dangerous recommendations. However, these changes will have to be accompanied by the legal requirements common to the information society, by the ethical aspects associated with medical care, guaranteeing and contributing, in all cases, to improving the doctor-patient relationship.

Clinical-Based and Expert Selection of Terms Related to Depression for Twitter Streaming and Language Analysis.

People use language to express their thoughts and feelings, unveiling important aspects of their psychological traits and social interactions. Although there are several studies describing methodologies to create a collection of words in English related to depression and other conditions, in most of them the selection of words is not clinical or expert based. The objective of this study is twofold: firstly, to introduce a comprehensive collection of Spanish words commonly used by patients suffering from depression, which will be available as a free open source for research purposes (GitHub), and secondly, to study the usefulness of this collection of words in identifying social media posts that could be indicative of patients suffering from depression. The level of agreement among medical doctors to determine the best words that should be used to select tweets related to depression was low. This finding may be due to the complexity of depression and the extraordinary diversity in the way people express themselves when describing their illness. It is critical to perform a thorough analysis of the specific language used in each condition, before deciding the best words to be used for filtering the tweets in each disease. As our study shows, the words supposedly more linked to depression are very common words used in other contexts, and consequently less specific for detecting depressive users. In addition, grammatical gender forms should be considered when analysing some languages such as Spanish.

[Health information on the Internet and trust marks as quality indicators: vaccines case study]. / Información sobre salud en internet y sellos de confianza como indicadores de calidad: el caso de las vacunas.

OBJECTIVES: To find out the prevalence of quality trust marks present in websites and to analyse the quality of these websites displaying trust marks compared with those that do not display them, in order to put forward these trust marks as a quality indicator. DESIGN: Cross-sectional study. SETTING: Internet. PARTICIPANTS: Websites on vaccines. MAIN MEASURES: Using "vacunas OR vaccines" as key words, the features of 40 web pages were analysed. These web pages were selected from the page results of two search engines, Google and Yahoo! RESULTS: Based on a total of 9 criteria, the average score of criteria fulfilled was 7 (95% CI 3.96-10.04) points for the web pages offered by Yahoo! and 7.3 (95% CI 3.86-10.74) offered by Google. Amongst web pages offered by Yahoo!, there were three with clearly inaccurate information, while there were four in the pages offered by Google. Trust marks were displayed in 20% and 30% medical web pages, respectively, and their presence reached statistical significance (P=0.033) when fulfilling the quality criteria compared with web pages where trust marks were not displayed. CONCLUSIONS: A wide variety of web pages was obtained by search engines and a large number of them with useless information. Although the websites analysed had a good quality, between 15% and 20% showed inaccurate information. Websites where trust marks were displayed had more quality than those that did not display one and none of them were included amongst those where inaccurate information was found.

Using Electronic Health Records to Assess Depression and Cancer Comorbidities.

Comorbid diseases are an important concern in oncology since they can affect the choice and effectiveness of treatment. What is particularly relevant is the fact that the diagnosis of depression in cancer patients has an important impact on the quality of life of these patients. Although there is no consensus about a specific relationship of depression with certain cancer types, some authors have proposed that depression constitutes a risk factor for cancer. The objective of this study is to identify the presence of comorbidities in a massive EHR system, between depression and the 10 most common cancers in women and men and to determine if there is a preferred temporal ordering in the co-occurrence of these diseases. All the cancers studied showed a significant co-occurrence with depression, more specifically, twice more frequent than what could be expected by chance. A preferred directionality was identified between some of the comorbid diseases, such as breast cancer followed by depression, and depression followed by either stomach cancer, colorectal cancer or lung cancer. Future work will address other potential factors that have an influence on the likelihood of suffering from depression in patients with cancer, such as drug therapies received, exposure to substance of abuse or other comorbidities.

Text mining and expert curation to develop a database on psychiatric diseases and their genes.

Database URL: http://www.psygenet.org. PsyGeNET corpus: http://www.psygenet.org/ds/PsyGeNET/results/psygenetCorpus.tar.

Quality labelling of medical web content.

As the number of medical websites in various languages increases, it is increasingly necessary to establish specific criteria and control measures that give consumers some guarantee that the health websites they are visiting meet a minimum level of quality standards. Further, reassurance is needed that the professionals offering the information are suitably qualified. The paper briefly presents the current mechanisms for labelling medical web content and introduces the work done in the EC-funded project Quatro. This has defined a vocabulary for quality labels and a schema to deliver them in a machine-processable format. In addition, the paper proposes the development of a labelling platform that will assist the work of medical labelling agencies in automating, up to a certain level, the retrieval of unlabelled medical websites and their labelling, and the monitoring of labelled websites as to whether they are still satisfying the criteria.

MedIEQ-Quality labelling of medical web content using multilingual information extraction.

Quality of Internet health information is essential because it has the potential to benefit or harm a large number of people and it is therefore essential to provide consumers with some tools to aid them in assessing the nature of the information they are accessing and how they should use it without jeopardizing their relationship with their doctor. Organizations around the world are working on establishing standards of quality in the accreditation of health-related web content. For the full success of these initiatives, they must be equipped with technologies that enable the automation of the rating process and allow the continuous monitoring of labelled web sites alerting the labelling agency. In this paper we describe the European project MedIEQ (Quality Labelling of Medical Web Content Using Multilingual Information Extraction) that integrates the efforts of relevant organizations on medical quality labelling, multilingual information retrieval and extraction and semantic resources, from six different European countries (Spain, Germany, Greece, Finland, Czech Republic and Switzerland). The main objectives of MedIEQ are: first, to develop a scheme for the quality labelling of medical web content and provide the tools supporting the creation, maintenance and access of labelling data according to this scheme and second, to specify a methodology for the content analysis of medical web sites according to the MedIEQ scheme and develop the tools that will implement it.

[Healthy eating support groups on Facebook: content and features]. / Grupos sobre alimentación saludable en Facebook: características y contenidos.

OBJECTIVE: To determine the features and use of groups related to healthy eating on Facebook. METHOD: We carried out a cross-sectional study through the Internet. Using the API on Facebook, we included open groups related to healthy eating in the Spanish language. The variables studied were name, description, category, the number and gender of users, date of creation, number of posts, content of the first 20 posts, and the most recent update. RESULTS: We selected 281 open groups for inclusion in the study. Of these, 125 were excluded because the content was unrelated to healthy eating. Finally 156 groups were studied with 14,619 users (10,373 women [71%] and 3,919 men [26.8%]). Dietary products were promoted by 40% of the groups. CONCLUSIONS: Facebook is used as a means of communication and for sharing health information. Because many of these groups promote dietary products, their usefulness for health education is doubtful. Health organizations should participate in social media.

Applying Semantic Web technologies to improve the retrieval, credibility and use of health-related web resources.

The number of health-related websites is increasing day-by-day; however, their quality is variable and difficult to assess. Various "trust marks" and filtering portals have been created in order to assist consumers in retrieving quality medical information. Consumers are using search engines as the main tool to get health information; however, the major problem is that the meaning of the web content is not machine-readable in the sense that computers cannot understand words and sentences as humans can. In addition, trust marks are invisible to search engines, thus limiting their usefulness in practice. During the last five years there have been different attempts to use Semantic Web tools to label health-related web resources to help internet users identify trustworthy resources. This paper discusses how Semantic Web technologies can be applied in practice to generate machine-readable labels and display their content, as well as to empower end-users by providing them with the infrastructure for expressing and sharing their opinions on the quality of health-related web resources.