The association between internet use and the choice of medical institution among Chinese older adults.

BACKGROUND: As older people have complex medical needs and still encounter challenges in accessing online health information, the relationship between Internet use and the choice of medical institution made by them is unclear, and we aimed to examine this relationship. METHODS: Data from the newly released 2020 China Family Panel Survey database were used. Furthermore, we used descriptive statistics to analyze the background characteristics of the sample and a logistic regression model to estimate the impact of Internet use on the choice of medical institution made by older adults. We conducted a stratified analysis to explore the influence of different characteristics on the relationship between Internet use and the choice of medical institution. RESULTS: Totally 4,948 older adults were included. Multivariate logistic regression showed that, compared to non-Internet users, Internet users were less likely to choose community health service centers over general hospitals (P < 0.001, OR = 0.667, 95CI%: 0.558-0.797). The subgroup analyses found that Internet use only had an impact on the choice of medical institution in older adults aged 65-69 years, those with partners, those with primary or secondary education, those residing in urban areas, those without medical insurance, those with a self-rated health status as average or healthy, those with unchanged or better health trend, and those without chronic disease. The effect of Internet use on the choice of medical institution did not differ by sex, satisfaction, or trust in doctors. CONCLUSION: Internet use may significantly affect older adults' tendency to choose general hospitals to meet their daily medical needs. The subgroup analyses indicated that different characteristics of older people affected this association.

Highly public anti-Black violence is associated with poor mental health days for Black Americans.

Highly public anti-Black violence in the United States may cause widely experienced distress for Black Americans. This study identifies 49 publicized incidents of racial violence and quantifies national interest based on Google searches; incidents include police killings of Black individuals, decisions not to indict or convict the officer involved, and hate crime murders. Weekly time series of population mental health are produced for 2012 through 2017 using two sources: 1) Google Trends as national search volume for psychological distress terms and 2) the Behavioral Risk Factor Surveillance System (BRFSS) as average poor mental health days in the past 30 d among Black respondents (mean weekly sample size of 696). Autoregressive moving average (ARMA) models accounted for autocorrelation, monthly unemployment, season and year effects, 52-wk lags, news-related searches for suicide (for Google Trends), and depression prevalence and percent female (for BRFSS). National search interest varied more than 100-fold between racial violence incidents. Black BRFSS respondents reported 0.26 more poor mental health days during weeks with two or more racial incidents relative to none, and 0.13 more days with each log10 increase in national interest. Estimates were robust to sensitivity tests, including controlling for monthly number of Black homicide victims and weekly search interest in riots. As expected, racial incidents did not predict average poor mental health days among White BRFSS respondents. Results with national psychological distress from Google Trends were mixed but generally unsupportive of hypotheses. Reducing anti-Black violence may benefit Black Americans' mental health nationally.

Evaluating the primary use, strengths and weaknesses of pelvic floor muscle training devices available online.

AIMS: Treatment for urinary incontinence (UI) includes pelvic floor muscle training (PFMT). There is limited data appraising the characteristics of PFMT devices. We aimed to ascertain the primary use, strengths and weaknesses of PFMT devices available online, through evaluation of consumer reviews. METHODS: We performed an analysis of PFMT devices on Amazon.com. Four key device categories were recognized. Reviews from the five most frequently-reviewed products per category were analyzed (n = 20). W characterized device use, strengths and weaknesses using thematic analysis. RESULTS: We evaluated 2574 PFMT device reviews including 1168 vibrating Kegel balls, 750 non-vibrating Kegel balls, 411 pelvic floor or thigh exercisers, and 245 electric probes. Non-vibrating Kegel balls were rated highest (4.6/5 stars), followed by vibrating Kegel balls, electric probes and pelvic floor or thigh exercisers (4.4/5, 4.1/5, and 3.8/5 stars, respectively). Most reviews were positive (77%) or negative (16%) with few neutral (7%). While all were marketed to treat UI, most reviews did not mention the intended use. Vibrating and non-vibrating Kegel balls and electric probes were most likely to be used for UI, and pelvic floor or thigh exercisers for toning. Some used non-vibrating and vibrating Kegel balls for sexual function. Electric probes were the most beneficial device for incontinence control (27%, 67/245). Twenty-five percent of all product reviews praised device ease of use and good quality or design. A minority of reviewers found products difficult to use, of poor quality or design and uncomfortable. CONCLUSION: Consumers utilized online PFMT devices for multiple purposes, including UI, toning and sexual function. Reviewers generally praised PFMT products, particularly electric probes for UI.

Comparison of online and face-to-face valuation of the EQ-5D-5L using composite time trade-off.

OBJECTIVE: The aim of this study was to compare online, unsupervised and face-to-face (F2F), supervised valuation of EQ-5D-5L health states using composite time trade-off (cTTO) tasks. METHODS: The official EuroQol experimental design and valuation protocol for the EQ-5D-5L of 86 health states were implemented in interviewer-assisted, F2F and unsupervised, online studies. Validity of preferences was assessed using prevalence of inconsistent valuations and expected patterns of TTO values. Respondent task engagement was measured using number of trade-offs and time per task. Trading patterns such as better-than-dead only was compared between modes. Value sets were generated using linear regression with a random intercept (RILR). Value set characteristics such as range of scale and dimension ranking were evaluated between modes. RESULTS: Five hundred one online and 1,134 F2F respondents completed the surveys. Mean elicited TTO values were higher online than F2F when compared by health state severity. Compared to F2F, a larger proportion of online respondents did not assign the poorest EQ-5D-5L health state (i.e., 55555) the lowest TTO value ([Online] 41.3% [F2F] 12.2%) (p < 0.001). A higher percentage of online cTTO tasks were completed in 3 trade-offs or fewer ([Online] 15.8% [F2F] 3.7%), (p < 0.001). When modeled using the RILR, the F2F range of scale was larger than online ([Online] 0.600 [F2F] 1.307) and the respective dimension rankings differed. CONCLUSIONS: Compared to F2F data, TTO tasks conducted online had more inconsistencies and decreased engagement, which contributed to compromised data quality. This study illustrates the challenges of conducting online valuation studies using the TTO approach.

Role of Health Literacy in Health-Related Information-Seeking Behavior Online: Cross-sectional Study.

BACKGROUND: The internet has emerged as a main venue of health information delivery and health-related activities. However, few studies have examined how health literacy determines online health-related behavior. OBJECTIVE: The aim of this study was to investigate the current level of health-related information-seeking using the internet and how health literacy, access to technology, and sociodemographic characteristics impact health-related information-seeking behavior. METHODS: We conducted a cross-sectional study through a survey with Minnesotan adults (N=614) to examine their health literacy, access to technology, and health-related information-seeking internet use. We used multivariate regression analysis to assess the relationship between health-related information-seeking on the internet and health literacy and access to technology, controlling for sociodemographic characteristics. RESULTS: Better health literacy (ß=.35, SE 0.12) and greater access to technological devices (eg, mobile phone and computer or tablet PC; ß=.06, SE 0.19) were both associated with more health-related information-seeking behavior on the internet after adjusting for all other sociodemographic characteristics. Possession of a graduate degree (ß=.28, SE 0.07), female gender (ß=.15, SE 0.05), poor health (ß=.22, SE 0.06), participation in social groups (ß=.13, SE 0.05), and having an annual health exam (ß=.35, SE 0.12) were all associated with online health-related information-seeking. CONCLUSIONS: Our findings indicate that access to online health-related information is not uniformly distributed throughout the population, which may exacerbate disparities in health and health care. Research, policy, and practice attention are needed to address the disparities in access to health information as well as to ensure the quality of the information and improve health literacy.

Willingness to Adopt Health Information Among Social Question-and-Answer Community Users in China: Cross-sectional Survey Study.

BACKGROUND: COVID-19 has spread around the world and has increased the public's need for health information in the process. Meanwhile, in the context of lockdowns and other measures for preventing SARS-CoV-2 spread, the internet has surged as a web-based resource for health information. Under these conditions, social question-and-answer communities (SQACs) are playing an increasingly important role in improving public health literacy. There is great theoretical and practical significance in exploring the influencing factors of SQAC users' willingness to adopt health information. OBJECTIVE: The aim of this study was to establish an extended unified theory of acceptance and use of technology model that could analyze the influence factors of SQAC users' willingness to adopt health information. Particularly, we tried to test the moderating effects that different demographic characteristics had on the variables' influences. METHODS: This study was conducted by administering a web-based questionnaire survey and analyzing the responses from a final total of 598 valid questionnaires after invalid data were cleaned. By using structural equation modelling, the influencing factors of SQAC users' willingness to adopt health information were analyzed. The moderating effects of variables were verified via hierarchical regression. RESULTS: Performance expectation (ß=.282; P<.001), social influence (ß=.238; P=.02), and facilitating conditions (ß=.279; P=.002) positively affected users' willingness to adopt health information, whereas effort expectancy (P=.79) and perceived risk (P=.41) had no significant effects. Gender had a significant moderating effect in the structural equation model (P<.001). CONCLUSIONS: SQAC users' willingness to adopt health information was evidently affected by multiple factors, such as performance expectation, social influence, and facilitating conditions. The structural equation model proposed in this study has a good fitting degree and good explanatory power for users' willingness to adopt health information. Suggestions were provided for SQAC operators and health management agencies based on our research results.

Husbands' Knowledge of Breast Cancer and Their Wives' Attitudes and Practices Related to Breast Cancer Screening in Saudi Arabia: Cross-sectional Online Survey.

BACKGROUND: Despite Saudi Arabia's free and well-established cancer care program, breast cancer incidence and mortality are rising. Husbands' knowledge, and wives' attitudes and practices related to breast cancer screening are not well understood in Saudi Arabia. OBJECTIVE: The aim of this study was to investigate husbands' knowledge, and wives' attitudes and practices related to breast cancer screening in Saudi Arabia. METHODS: This cross-sectional study collected data from 403 husbands in the holy city of Makkah through an online self-reported questionnaire over a period of 2 months, from May 6 to July 7, 2020. Tabulation, bivariate, and multiple regression analyses were the major tools used for data analysis. Multivariate logistic regressions were used to examine the association between husbands' knowledge and wives' behavior regarding breast cancer screening methods. RESULTS: Husbands' knowledge score (a 1-point increase) was significantly associated with the wives' utilization of mammograms (adjusted odds ratio [AOR] 1.089, 95% CI 1.024-1.159) and breast self-examination (AOR 1.177, 95% CI 1.105-1.255). Husbands' knowledge also influenced the wives' attitudes toward learning about breast self-examination (AOR 1.138, 95% CI 1.084-1.195). There was no significant association between husbands' knowledge and wives' utilization of clinical breast examination. However, richer husbands showed a socioeconomic gradient concerning their wives' utilization of clinical breast examinations (AOR 2.603, 95% CI 1.269-5.341). CONCLUSIONS: Overall, husbands' knowledge of breast cancer influences wives' attitudes and practices related to breast cancer screening methods in Saudi Arabia. Thus, interventions delivered to husbands might increase breast cancer awareness and survival.

Differences in Basic Life Support Knowledge Between Junior Medical Students and Lay People: Web-Based Questionnaire Study.

BACKGROUND: Early cardiopulmonary resuscitation and prompt defibrillation markedly increase the survival rate in the event of out-of-hospital cardiac arrest (OHCA). As future health care professionals, medical students should be trained to efficiently manage an unexpectedly encountered OHCA. OBJECTIVE: Our aim was to assess basic life support (BLS) knowledge in junior medical students at the University of Geneva Faculty of Medicine (UGFM) and to compare it with that of the general population. METHODS: Junior UGFM students and lay people who had registered for BLS classes given by a Red Cross-affiliated center were sent invitation links to complete a web-based questionnaire. The primary outcome was the between-group difference in a 10-question score regarding cardiopulmonary resuscitation knowledge. Secondary outcomes were the differences in the rate of correct answers for each individual question, the level of self-assessed confidence in the ability to perform resuscitation, and a 6-question score, "essential BLS knowledge," which only contains key elements of the chain of survival. Continuous variables were first analyzed using the Student t test, then by multivariable linear regression. Fisher exact test was used for between-groups comparison of binary variables. RESULTS: The mean score was higher in medical students than in lay people for both the 10-question score (mean 5.8, SD 1.7 vs mean 4.2, SD 1.7; P<.001) and 6-question score (mean 3.0, SD 1.1 vs mean 2.0, SD 1.0; P<.001). Participants who were younger or already trained scored consistently better. Although the phone number of the emergency medical dispatch center was well known in both groups (medical students, 75/80, 94% vs lay people, 51/62, 82%; P=.06), most participants were unable to identify the criteria used to recognize OHCA, and almost none were able to correctly reorganize the BLS sequence. Medical students felt more confident than lay people in their ability to perform resuscitation (mean 4.7, SD 2.2 vs mean 3.1, SD 2.1; P<.001). Female gender and older age were associated with lower confidence, while participants who had already attended a BLS course prior to taking the questionnaire felt more confident. CONCLUSIONS: Although junior medical students were more knowledgeable than lay people regarding BLS procedures, the proportion of correct answers was low in both groups, and changes in BLS education policy should be considered.

Quantitative Methods for Analyzing Intimate Partner Violence in Microblogs: Observational Study.

BACKGROUND: Social media is a rich, virtually untapped source of data on the dynamics of intimate partner violence, one that is both global in scale and intimate in detail. OBJECTIVE: The aim of this study is to use machine learning and other computational methods to analyze social media data for the reasons victims give for staying in or leaving abusive relationships. METHODS: Human annotation, part-of-speech tagging, and machine learning predictive models, including support vector machines, were used on a Twitter data set of 8767 #WhyIStayed and #WhyILeft tweets each. RESULTS: Our methods explored whether we can analyze micronarratives that include details about victims, abusers, and other stakeholders, the actions that constitute abuse, and how the stakeholders respond. CONCLUSIONS: Our findings are consistent across various machine learning methods, which correspond to observations in the clinical literature, and affirm the relevance of natural language processing and machine learning for exploring issues of societal importance in social media.

Physicians' Perceptions of the Use of a Chatbot for Information Seeking: Qualitative Study.

BACKGROUND: Seeking medical information can be an issue for physicians. In the specific context of medical practice, chatbots are hypothesized to present additional value for providing information quickly, particularly as far as drug risk minimization measures are concerned. OBJECTIVE: This qualitative study aimed to elicit physicians' perceptions of a pilot version of a chatbot used in the context of drug information and risk minimization measures. METHODS: General practitioners and specialists were recruited across France to participate in individual semistructured interviews. Interviews were recorded, transcribed, and analyzed using a horizontal thematic analysis approach. RESULTS: Eight general practitioners and 2 specialists participated. The tone and ergonomics of the pilot version were appreciated by physicians. However, all participants emphasized the importance of getting exhaustive, trustworthy answers when interacting with a chatbot. CONCLUSIONS: The chatbot was perceived as a useful and innovative tool that could easily be integrated into routine medical practice and could help health professionals when seeking information on drug and risk minimization measures.

Internet Use in Old Age: Results of a German Population-Representative Survey.

BACKGROUND: The internet has the potential to foster healthy lifestyles and to support chronic disease management. Older adults could benefit from using the internet and other information and communication technology to access health-related information and interventions available online. OBJECTIVE: The aim of this study was to investigate factors influencing internet use in older and oldest age groups and to determine the frequency of internet use for health-related purposes. METHODS: Using data from a nationally representative telephone survey of older adults aged 75 years and over, a sample of 999 people was assessed using structured clinical interviews. Descriptive and binary logistic regression analyses were performed. RESULTS: Overall, 42.6% (418/999) of participants used the internet. Among those, 55.7% (233/417) searched the internet for health-related information. Regression analyses revealed that internet use was significantly associated with younger age (odds ratio [OR] 0.89, 95% CI 0.85-0.92; P<.001), male gender (OR 2.84, 95% CI 2.02-4.00; P<.001), higher education levels (OR 6.69, 95% CI 4.48-9.99; P<.001), a wider social network (OR 1.04, 95% CI 1.01-1.07; P=.01), higher health-related quality of life (OR 1.02, 95% CI 1.00-1.03; P=.006), lower levels of depressive symptoms (OR 0.89, 95% CI 0.80-0.99; P=.04), and higher rates of chronic illness (OR 1.12, 95% CI 1.04-1.21; P<.004). CONCLUSIONS: This study provides population-representative data on internet use in old age in Germany. People in the older and oldest age groups participate in online activities. Understanding the factors that are associated with older adults internet use can contribute to developing tailored interventions and eHealth (electronic health) services to improve well-being in older adults.

Detection of Suicidality Among Opioid Users on Reddit: Machine Learning-Based Approach.

BACKGROUND: In recent years, both suicide and overdose rates have been increasing. Many individuals who struggle with opioid use disorder are prone to suicidal ideation; this may often result in overdose. However, these fatal overdoses are difficult to classify as intentional or unintentional. Intentional overdose is difficult to detect, partially due to the lack of predictors and social stigmas that push individuals away from seeking help. These individuals may instead use web-based means to articulate their concerns. OBJECTIVE: This study aimed to extract posts of suicidality among opioid users on Reddit using machine learning methods. The performance of the models is derivative of the data purity, and the results will help us to better understand the rationale of these users, providing new insights into individuals who are part of the opioid epidemic. METHODS: Reddit posts between June 2017 and June 2018 were collected from r/suicidewatch, r/depression, a set of opioid-related subreddits, and a control subreddit set. We first classified suicidal versus nonsuicidal languages and then classified users with opioid usage versus those without opioid usage. Several traditional baselines and neural network (NN) text classifiers were trained using subreddit names as the labels and combinations of semantic inputs. We then attempted to extract out-of-sample data belonging to the intersection of suicide ideation and opioid abuse. Amazon Mechanical Turk was used to provide labels for the out-of-sample data. RESULTS: Classification results were at least 90% across all models for at least one combination of input; the best classifier was convolutional neural network, which obtained an F1 score of 96.6%. When predicting out-of-sample data for posts containing both suicidal ideation and signs of opioid addiction, NN classifiers produced more false positives and traditional methods produced more false negatives, which is less desirable for predicting suicidal sentiments. CONCLUSIONS: Opioid abuse is linked to the risk of unintentional overdose and suicide risk. Social media platforms such as Reddit contain metadata that can aid machine learning and provide information at a personal level that cannot be obtained elsewhere. We demonstrate that it is possible to use NNs as a tool to predict an out-of-sample target with a model built from data sets labeled by characteristics we wish to distinguish in the out-of-sample target.

Cancer screenings during the COVID-19 pandemic: An analysis of public interest trends.

INTRODUCTION: The Coronavirus Disease 2019 (COVID-19) pandemic has impacted breast, colon, prostate, and lung cancer screenings in the U.S. by decreasing screening numbers.​We believe multiple types of cancer screenings may have been impacted during the pandemic as a result of cancellations of elective procedures and patient fear of seeking cancer screenings during a pandemic and that Google Trends may be a marker to estimate screening usage. METHODS: Google Trends (trends.google.com) was utilized to assess public interest in multiple cancer types. We then constructed a forecasting model to determine the expected search interest had the pandemic not occurred. We then compared our models to actual screening usage during the pandemic. RESULTS: Public interest in cancer screenings decreased precipitously at the onset of the COVID-19 pandemic. We found that the Google Trends estimated the decrease in mammogram usage 25.8% below the actual value. Similarly, Google Trends estimated the decrease in colon cancer screening usage 9.7% below the true value. DISCUSSION: We found the decrease in public interest in breast and colon cancer screenings slightly underestimated the actual screening usage numbers, suggesting Google Trends may be utilized as an indicator for human behavior regarding cancer screening, particularly with colon and breast cancer screenings. If the negative trend in cancer screening continues and missed screenings are not appropriately corrected for, socioeconomic and racial disparities in cancer diagnoses, morbidity, and mortality will widen.

Feasibility and reliability of a web-based smartphone application for joint position measurement.

OBJECTIVE: Measurement of joint angles is usually performed using a simple goniometer, which can often be time-consuming and inaccurate, however smartphones can measure angles, this technology could be used to measure joint position. Studies of smartphone applications for this purpose lack consistency and homogeneity. The aim of the current study is to analyse the reliability and accuracy of 3 inertial motion unit-based smartphone applications for goniometric measurement, using 3 different industry standards as external controls. METHODS: In the first 2 phases of the study, measurements of angles between 90° and 165° (simulating knee extension) using 3 smartphone applications were analysed against the 3 industry standards. In the third phase, the smartphone's raw data was individually analysed against a digital inclinometer across the x, y and z axes. RESULTS AND CONCLUSION: Results from the 3 phases of this study indicate a high degree of reliability and validity of the applications compared with the industry standards, with no clinically significant deviations. Thus, this technology could be used in a clinical setting. However, further clinical research, focussing on joint motions with greater than a single degree of freedom, is required before the use of such applications for joint position measurement in clinical practice.

Wikipedia, Google Trends and Diet: Assessment of Temporal Trends in the Internet Users' Searches in Italy before and during COVID-19 Pandemic.

We obtained data from Google Trends and Wikipedia in order to assess whether an analysis of Internet searches could provide information on the Internet users' behaviour/interest in diets. Differences in seasonality, year and before/during COVID-19 pandemic were assessed. From Wikipedia, we extracted the number of times a page is viewed by users, aggregated on monthly and seasonal bases. We also used Google Trends to evaluate the frequency of the users' web searches. The Mediterranean diet was the most frequently (33.9%), followed by the pescatarian diet (9.0%). Statistically, significant seasonal differences were found for the Mediterranean, vegetarian, Atkins, Scarsdale, and zone diets and pescetarianism. The most commonly searched diet and consequent diet-related queries on Google resulted to be: Dukan diet, Dukan and weight loss. Ketogenic, FODMAP and intermittent fasting diets were statistically more frequently searched during the pandemic compared with before. Our data show a different trend of searches based on the seasonality, year and the pandemic. These data could be useful for scientists, practitioners and policy makers because they can inform educational campaigns via the Internet, especially in periods when the population is more receptive.

Use Internet search data to accurately track state level influenza epidemics.

For epidemics control and prevention, timely insights of potential hot spots are invaluable. Alternative to traditional epidemic surveillance, which often lags behind real time by weeks, big data from the Internet provide important information of the current epidemic trends. Here we present a methodology, ARGOX (Augmented Regression with GOogle data CROSS space), for accurate real-time tracking of state-level influenza epidemics in the United States. ARGOX combines Internet search data at the national, regional and state levels with traditional influenza surveillance data from the Centers for Disease Control and Prevention, and accounts for both the spatial correlation structure of state-level influenza activities and the evolution of people's Internet search pattern. ARGOX achieves on average 28% error reduction over the best alternative for real-time state-level influenza estimation for 2014 to 2020. ARGOX is robust and reliable and can be potentially applied to track county- and city-level influenza activity and other infectious diseases.

The rise of online sports betting, its fallout, and the onset of a new profile in gambling disorder: young people.

HYPOTHESIS: Since 2015 the gambling trend may have changed among young people between 18 and 30 years old. METHODOLOGY: Range of document review techniques obtained by therapeutic data regarding the personal development of each person in rehabilitation to analyze 13 different variables. FINDINGS: Due to the new regulations legalizing online gambling in Spain, and the constant increase in its advertising, a shift could have taken place in the gamblers' profile: a preference for online sports betting and placing other bets using devices connected to the Internet, such as smartphones, laptops, tablets, and similar technologies. Gamblers who use online media to place their bets also incur debts over the Internet. We find a possible proliferation of online betting services, that could imply an increase of social, psychological, and family relationship problems affecting young gamblers, which may constitute a new profile of gambling disorder.

Internet searches by the Spanish population for unqualified information on the treatment of osteoarthritis. / Búsqueda en Internet de información no cualificada sobre el tratamiento de la artrosis por la población española.

OBJECTIVE: There is a current trend in the population to search the Internet for unqualified medical information that may affect the recommendations given in specialist consultation. The aim of this study was to analyse the tendency of the Spanish population to search the Internet for unqualified information on current treatments for osteoarthritis. MATERIAL AND METHOD: Google Trends was used analyse the information gathered from the Internet, combining potential key search terms related to the current treatment of osteoarthritis. For each term the relative search volume was calculated, and its trend between 2009 and 2019. Spearman's correlation was used to study the direction of the trend. RESULTS: All the infiltration methods had increasing trends and no statistically significant differences were found between them (P=.769). The term that showed the best correlation over time was «prp¼ with Spearman's correlation =.90, and the term with the highest relative search volume was «growth factors¼. Prosthetic treatment generated more interest than conservative treatments, where there was more interest in knee replacement than hip replacement (P<.001). CONCLUSION: In Spain, the search for unqualified information on the treatment of osteoarthritis has increased over the past 10 years. There is more interest in prosthetic treatment than the more conservative treatments. There is more interest in knee replacement than hip replacement. There are no differences with regard to the different methods of joint injections.

The association between internet searches and suicide in Spain.

Apart from disease, suicide has been the first cause of death in Spain since it overcame the victims of traffic accidents in the year 2007. Nevertheless, in spite of the high number of people affected by it every year, it is an almost silenced issue in this country. In the present research work we make use of Internet suicide-related search terms and official suicide rates for Spain to analyze whether these searches are related to actual suicides between 2004 and 2017. We find that the search terms "commit suicide", "commit suicide without pain" and "suicide" (as search term and as topic) are positively related to actual suicide rates. Thus, the Internet seems to be a consult tool for potential suicide victims in Spain which, joined to an increasing trend in the use of the Internet by the Spanish population, opens the gate for interventions through the results obtained in these Internet searches.