Dataset Information

Use of Twitter to monitor attitudes toward depression and schizophrenia: an exploratory study.

ABSTRACT: Introduction. The paper reports on an exploratory study of the usefulness of Twitter for unobtrusive assessment of stigmatizing attitudes in the community. Materials and Methods. Tweets with the hashtags #depression or #schizophrenia posted on Twitter during a 7-day period were collected. Tweets were categorised based on their content and user information and also on the extent to which they indicated a stigmatising attitude towards depression or schizophrenia (stigmatising, personal experience of stigma, supportive, neutral, or anti-stigma). Tweets that indicated stigmatising attitudes or personal experiences of stigma were further grouped into the following subthemes: social distance, dangerousness, snap out of it, personal weakness, inaccurate beliefs, mocking or trivializing, and self-stigma. Results and Discussion. Tweets on depression mostly related to resources for consumers (34%), or advertised services or products for individuals with depression (20%). The majority of schizophrenia tweets aimed to increase awareness of schizophrenia (29%) or reported on research findings (22%). Tweets on depression were largely supportive (65%) or neutral (27%). A number of tweets were specifically anti-stigma (7%). Less than 1% of tweets reflected stigmatising attitudes (0.7%) or personal experience of stigma (0.1%). More than one third of the tweets which reflected stigmatising attitudes were mocking or trivialising towards individuals with depression (37%). The attitude that individuals with depression should "snap out of it" was evident in 30% of the stigmatising tweets. The majority of tweets relating to schizophrenia were categorised as supportive (42%) or neutral (43%). Almost 10% of tweets were explicitly anti-stigma. The percentage of tweets showing stigmatising attitudes was 5%, while less than 1% of tweets described personal experiences of stigmatising attitudes towards individuals with schizophrenia. Of the tweets that indicated stigmatising attitudes, most reflected inaccurate beliefs about schizophrenia being multiple personality disorder (52%) or mocked or trivialised individuals with schizophrenia (33%). Conclusions. The study supports the use of analysis of Twitter content to unobtrusively measure attitudes towards mental illness, both supportive and stigmatising. The results of the study may be useful in assisting mental health promotion and advocacy organisations to provide information about resources and support, raise awareness and counter common stigmatising attitudes.

SUBMITTER: Reavley NJ

PROVIDER: S-EPMC4217192 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Use of Twitter to monitor attitudes toward depression and schizophrenia: an exploratory study.

Reavley Nicola J NJ Pilkington Pamela D PD

PeerJ 20141028

Introduction. The paper reports on an exploratory study of the usefulness of Twitter for unobtrusive assessment of stigmatizing attitudes in the community. Materials and Methods. Tweets with the hashtags #depression or #schizophrenia posted on Twitter during a 7-day period were collected. Tweets were categorised based on their content and user information and also on the extent to which they indicated a stigmatising attitude towards depression or schizophrenia (stigmatising, personal experience ...[more]

PMID: 25374786

Similar Datasets

Project description:BACKGROUND:Despite the significant body of evidence on the efficacy and cost-effectiveness of internet interventions, the implementation of such programs in Portugal is virtually non-existent. In addition, Portuguese psychologists' use and their attitudes towards such interventions is largely unknown. OBJECTIVE:The aim of this study was to explore Portuguese psychologists' knowledge, training, use and attitudes towards internet interventions; to investigate perceived advantages and limitations of such interventions; identify potential drivers and barriers impacting implementation; and study potential factors associated to previous use and attitudes towards internet interventions. METHODS:An online cross-sectional survey was developed by the authors and disseminated by the Portuguese Psychologists Association to its members. RESULTS:A total of 1077 members of the Portuguese Psychologists Association responded to the questionnaire between November 2018 and February 2019. Of these, 37.2% (N=363) were familiar with internet interventions and 19.2% (N=188) considered having the necessary training to work within the field. 29.6% (N=319) of participants reported to have used some form of digital technology to deliver care in the past. Telephone (23.8%; N=256), e-mail (16.2%; N=175) and SMS (16.1%; N=173) services were among the most adopted forms of digital technology, while guided (1.3%; N=14) and unguided (1.5%; N=16) internet interventions were rarely used. Accessibility (79.9%; N=860), convenience (45.7%; N=492) and cost-effectiveness (45.5%; N=490) were considered the most important advantages of internet interventions. Conversely, ethical concerns (40.7%; N=438), client's ICT illiteracy (43.2%; N=465) and negative attitudes towards internet interventions (37%; N=398) were identified as the main limitations. An assessment of participants attitudes towards internet interventions revealed a slightly negative/neutral stance (Median=46.21; SD=15.06) and revealed greater acceptability towards blended treatment interventions (62.9%; N=615) when compared to standalone internet interventions (18.6%; N=181). Significant associations were found between knowledge (?24=90.4; P<.001), training (?24=94.6; P<.001), attitudes (?23=38.4; P<.001) and previous use of internet interventions and between knowledge (?212=109.7; P<.001), training (?212=64.7; P<.001) and attitudes towards such interventions, with psychologists reporting to be ignorant and not having adequate training in the field, being more likely to present more negative attitudes towards these interventions and not having prior experience in its implementation. CONCLUSIONS:This study revealed that most Portuguese psychologists are not familiar with and have no training or prior experience using internet interventions and had a slightly negative/neutral attitude towards such interventions. There was greater acceptability towards blended treatment interventions compared to standalone internet interventions. Lack of knowledge and training were identified as the main barriers to overcome, underlining the need of promoting awareness and training initiatives to ensure internet interventions successful implementation.

Project description:Background: Various health benefits from the ownership of companion dogs have been studied from a One Health perspective. However, the preventive effects on depression are unclear, with inconsistent results across studies. We hypothesized that heterogeneity among owners would be related to the mixed results. Specifically, the difference in the strength of the bond between the owners and their companion dogs would modify the effect of dog ownership. As an exploratory study, we compared the depression symptoms of the owners with favorable attitudes toward their dogs, with those of the owners with unfavorable attitudes, to investigate the potential effect modification of owners' attitudes on the association between the ownership and depression symptom. Methods: We conducted a web-based questionnaire survey of 654 19- to 39-year-old adults who had companion dogs in Seoul, South Korea, where a major health burden is depression among young adults. We measured the owners' attitudes toward their dogs using the modified Pet Attitude Scale (PAS-M) and their depression symptoms using the short version of the Center for Epidemiologic Studies depression scale (CESD-10). Demographic and socioeconomic factors were measured to adjust for the association between attitude and depression symptoms. Multivariate logistic regression models were used in this study. Results: The owners who had less favorable attitudes toward their dogs (lower PAS-M scores) tended to have depression symptoms. The direction and significance were maintained either when the PAS-M variable was used as a continuous variable (odds ratio (OR) for one score increase in PAS-M was 0.95 (95% confidence interval (CI) = 0.94-0.96)) or as a categorical variable (OR for lower PAS-M was 3.19 (95% CI = 2.28 -4.47)). Conclusion: We found a positive significant association between owners' depression symptoms and unfavorable attitudes toward their dogs, although causal direction could not be determined. Future studies should investigate the potential causal link.

Project description:BACKGROUND: Under-recognition of depression is common in many countries. Education of medical staff, focusing on their attitudes towards depression, may be necessary to change their behavior and enhance recognition of depression. Several studies have previously reported on attitudes toward depression among general physicians. However, little is known about attitudes of non-psychiatric doctors in Japan. In the present study, we surveyed non-psychiatric doctors' attitude toward depression. METHODS: The inclusion criteria of participants in the present study were as follows: 1) Japanese non-psychiatric doctors and 2) attendees in educational opportunities regarding depression care. We conveniently approached two populations: 1) a workshop to depression care for non-psychiatric doctors and 2) a general physician-psychiatrist (G-P) network group. We contacted 367 subjects. Attitudes toward depression were measured using the Depression Attitude Questionnaire (DAQ), a 20-item self-report questionnaire developed for general physicians. We report scores of each DAQ item and factors derived from exploratory factor analysis. RESULTS: We received responses from 230 subjects, and we used DAQ data from 187 non-psychiatric doctors who met the inclusion criteria. All non-psychiatric doctors (n = 187) disagreed with "I feel comfortable in dealing with depressed patients' needs," while 60 % (n = 112) agreed with "Working with depressed patients is heavy going." Factor analysis indicated these items comprised a factor termed "Depression should be treated by psychiatrists" - to which 54 % of doctors (n = 101) agreed. Meanwhile, 67 % of doctors (n = 126) thought that nurses could be useful in depressed patient support. The three factors derived from the Japanese DAQ differed from models previously derived from British GP samples. The attitude of Japanese non-psychiatric doctors concerning whether depression should be treated by psychiatrists was markedly different to that of British GPs. CONCLUSIONS: Japanese non-psychiatric doctors believe that depression care is beyond the scope of their duties. It is suggested that educational programs or guidelines for depression care developed in other countries such as the UK are not directly adaptable for Japanese non-psychiatric doctors. Developing a focused educational program that motivates non-psychiatric doctors to play a role in depression care is necessary to enhance recognition and treatment of depression in Japan.

Project description:BackgroundIn the United States, the rapidly evolving COVID-19 outbreak, the shortage of available testing, and the delay of test results present challenges for actively monitoring its spread based on testing alone.ObjectiveThe objective of this study was to develop, evaluate, and deploy an automatic natural language processing pipeline to collect user-generated Twitter data as a complementary resource for identifying potential cases of COVID-19 in the United States that are not based on testing and, thus, may not have been reported to the Centers for Disease Control and Prevention.MethodsBeginning January 23, 2020, we collected English tweets from the Twitter Streaming application programming interface that mention keywords related to COVID-19. We applied handwritten regular expressions to identify tweets indicating that the user potentially has been exposed to COVID-19. We automatically filtered out "reported speech" (eg, quotations, news headlines) from the tweets that matched the regular expressions, and two annotators annotated a random sample of 8976 tweets that are geo-tagged or have profile location metadata, distinguishing tweets that self-report potential cases of COVID-19 from those that do not. We used the annotated tweets to train and evaluate deep neural network classifiers based on bidirectional encoder representations from transformers (BERT). Finally, we deployed the automatic pipeline on more than 85 million unlabeled tweets that were continuously collected between March 1 and August 21, 2020.ResultsInterannotator agreement, based on dual annotations for 3644 (41%) of the 8976 tweets, was 0.77 (Cohen κ). A deep neural network classifier, based on a BERT model that was pretrained on tweets related to COVID-19, achieved an F1-score of 0.76 (precision=0.76, recall=0.76) for detecting tweets that self-report potential cases of COVID-19. Upon deploying our automatic pipeline, we identified 13,714 tweets that self-report potential cases of COVID-19 and have US state-level geolocations.ConclusionsWe have made the 13,714 tweets identified in this study, along with each tweet's time stamp and US state-level geolocation, publicly available to download. This data set presents the opportunity for future work to assess the utility of Twitter data as a complementary resource for tracking the spread of COVID-19.

Dataset Information

Use of Twitter to monitor attitudes toward depression and schizophrenia: an exploratory study.

Publications

Use of Twitter to monitor attitudes toward depression and schizophrenia: an exploratory study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets