Mapping Phenomena Relevant to Adolescent Emotion Regulation: A Text-Mining Systematic Review.
Ontology highlight
ABSTRACT: Supplementary information
The online version contains supplementary material available at 10.1007/s40894-021-00160-7.
SUBMITTER: van Lissa CJ
PROVIDER: S-EPMC8138847 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Therapeutic Change Process Research (TCPR) connects within-therapeutic change processes to outcomes. The labour intensity of qualitative methods limit their use to small scale studies. Automated text-analyses (e.g. text mining) provide means for analysing large scale text patterns. We aimed to provide an overview of the frequently used qualitative text-based TCPR methods and assess the extent to which these methods are reliable and valid, and have potential for automation. We systematically reviewed PsycINFO, Scopus, and Web of Science to identify articles concerning change processes and text or language. We evaluated the reliability and validity based on replicability, the availability of code books, training data and inter-rater reliability, and evaluated the potential for automation based on the example- and rule-based approach. From 318 articles we identified four often used methods: Innovative Moments Coding Scheme, the Narrative Process Coding Scheme, Assimilation of Problematic Experiences Scale, and Conversation Analysis. The reliability and validity of the first three is sufficient to hold promise for automation. While some text features (content, grammar) lend themselves for automation through a rule-based approach, it should be possible to automate higher order constructs (e.g. schemas) when sufficient annotated data for an example-based approach are available.
| S-EPMC6894756 | biostudies-literature
Project description:BackgroundThe large and growing number of published studies, and their increasing rate of publication, makes the task of identifying relevant studies in an unbiased way for inclusion in systematic reviews both complex and time consuming. Text mining has been offered as a potential solution: through automating some of the screening process, reviewer time can be saved. The evidence base around the use of text mining for screening has not yet been pulled together systematically; this systematic review fills that research gap. Focusing mainly on non-technical issues, the review aims to increase awareness of the potential of these technologies and promote further collaborative research between the computer science and systematic review communities.MethodsFive research questions led our review: what is the state of the evidence base; how has workload reduction been evaluated; what are the purposes of semi-automation and how effective are they; how have key contextual problems of applying text mining to the systematic review field been addressed; and what challenges to implementation have emerged? We answered these questions using standard systematic review methods: systematic and exhaustive searching, quality-assured data extraction and a narrative synthesis to synthesise findings.ResultsThe evidence base is active and diverse; there is almost no replication between studies or collaboration between research teams and, whilst it is difficult to establish any overall conclusions about best approaches, it is clear that efficiencies and reductions in workload are potentially achievable. On the whole, most suggested that a saving in workload of between 30% and 70% might be possible, though sometimes the saving in workload is accompanied by the loss of 5% of relevant studies (i.e. a 95% recall).ConclusionsUsing text mining to prioritise the order in which items are screened should be considered safe and ready for use in 'live' reviews. The use of text mining as a 'second screener' may also be used cautiously. The use of text mining to eliminate studies automatically should be considered promising, but not yet fully proven. In highly technical/clinical areas, it may be used with a high degree of confidence; but more developmental and evaluative work is needed in other disciplines.
| S-EPMC4320539 | biostudies-literature
Project description:BACKGROUND:Precision oncology involves analysis of individual cancer samples to understand the genes and pathways involved in the development and progression of a cancer. To improve patient care, knowledge of diagnostic, prognostic, predisposing, and drug response markers is essential. Several knowledgebases have been created by different groups to collate evidence for these associations. These include the open-access Clinical Interpretation of Variants in Cancer (CIViC) knowledgebase. These databases rely on time-consuming manual curation from skilled experts who read and interpret the relevant biomedical literature. METHODS:To aid in this curation and provide the greatest coverage for these databases, particularly CIViC, we propose the use of text mining approaches to extract these clinically relevant biomarkers from all available published literature. To this end, a group of cancer genomics experts annotated sentences that discussed biomarkers with their clinical associations and achieved good inter-annotator agreement. We then used a supervised learning approach to construct the CIViCmine knowledgebase. RESULTS:We extracted 121,589 relevant sentences from PubMed abstracts and PubMed Central Open Access full-text papers. CIViCmine contains over 87,412 biomarkers associated with 8035 genes, 337 drugs, and 572 cancer types, representing 25,818 abstracts and 39,795 full-text publications. CONCLUSIONS:Through integration with CIVIC, we provide a prioritized list of curatable clinically relevant cancer biomarkers as well as a resource that is valuable to other knowledgebases and precision cancer analysts in general. All data is publically available and distributed with a Creative Commons Zero license. The CIViCmine knowledgebase is available at http://bionlp.bcgsc.ca/civicmine/.
| S-EPMC6891984 | biostudies-literature
Project description:BACKGROUND:Research on the neural correlates associated with risk for suicidal ideation (SI) has been limited, particularly in one increasingly at-risk group-adolescents. Previous research with adolescents indicates that poor emotion regulation skills are linked with SI, but these studies have not previously examined neural activation in service of emotion regulation between those with and without SI histories. METHODS:Here we examine whether SI is associated with neural responses during an emotion regulation functional magnetic resonance imaging task in a group of adolescents (N = 49) 13 to 20 years of age (mean = 16.95). RESULTS:While there were no differences between youths with and without SI in self-reported emotional responses to negative pictures, youths with SI activated the dorsolateral prefrontal cortex more than youths without SI on trials in which they attempted to regulate their emotional responses compared with trials in which they passively viewed negative pictures. In contrast, during passive viewing of negative stimuli, youths with SI activated the dorsolateral prefrontal cortex, temporoparietal junction, and cerebellum less than same-age control subjects. CONCLUSIONS:These findings were robust to control subjects for depression and adversity exposure and are consistent with the idea that youths with SI have disrupted emotion regulation, potentially related to differences in recruitment of top-down control regions. In contrast, youths without SI activated regions implicated in emotion regulation even when not directed to effortfully control their emotional response. This is the first study to examine neural function during emotion regulation as a potential neural correlate of risk for SI in adolescents.
| S-EPMC5851479 | biostudies-literature
Project description:With the continuous development of information technology, more and more people have become to use online dating apps, and the trend has been exacerbated by the COVID-19 pandemic in these years. However, there is a phenomenon that most of user reviews of mainstream dating apps are negative. To study this phenomenon, we have used topic model to mine negative reviews of mainstream dating apps, and constructed a two-stage machine learning model using data dimensionality reduction and text classification to classify user reviews of dating apps. The research results show that: firstly, the reasons for the current negative reviews of dating apps are mainly concentrated in the charging mechanism, fake accounts, subscription and advertising push mechanism and matching mechanism in the apps, proposed corresponding improvement suggestions are proposed by us; secondly, using principal component analysis to reduce the dimensionality of the text vector, and then using XGBoost model to learn the low-dimensional data after oversampling, a better classification accuracy of user reviews can be obtained. We hope These findings can help dating apps operators to improve services and achieve sustainable business operations of their apps.
| S-EPMC10132638 | biostudies-literature
Project description:MotivationExposure to pesticides may lead to adverse health effects in human populations, in particular vulnerable groups. The main long-term health concerns are neurodevelopmental disorders, carcinogenicity as well as endocrine disruption possibly leading to reproductive and metabolic disorders. Adverse outcome pathways (AOP) consist in linear representations of mechanistic perturbations at different levels of the biological organization. Although AOPs are chemical-agnostic, they can provide a better understanding of the Mode of Action of pesticides and can support a rational identification of effect markers.ResultsWith the increasing amount of scientific literature and the development of biological databases, investigation of putative links between pesticides, from various chemical groups and AOPs using the biological events present in the AOP-Wiki database is now feasible. To identify co-occurrence between a specific pesticide and a biological event in scientific abstracts from the PubMed database, we used an updated version of the artificial intelligence-based AOP-helpFinder tool. This allowed us to decipher multiple links between the studied substances and molecular initiating events, key events and adverse outcomes. These results were collected, structured and presented in a web application named AOP4EUpest that can support regulatory assessment of the prioritized pesticides and trigger new epidemiological and experimental studies.Availability and implementationhttp://www.biomedicale.parisdescartes.fr/aop4EUpest/home.php.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC7520043 | biostudies-literature
Project description:Risky sexual behavior can lead to negative outcomes (e.g., pregnancy, sexually transmitted infections). Adolescents may engage in risky sex less often if families talk about sexual safety or if adolescents engage in emotion regulation (ER) skills, however research is lacking on how ER may be a barrier to sexual health communication. This exploratory study was a secondary analysis of baseline information from 420 American adolescents referred for mental health symptoms and their parents regarding ER and sexual health communication. Significant differences emerged on adolescent ER between families that talk about sexual health and those that do not.
| S-EPMC8170856 | biostudies-literature
Project description:BACKGROUND:Platinum resistance is an important cause of clinical recurrence and death for ovarian cancer. This study tries to systematically explore the molecular mechanisms for platinum resistance in ovarian cancer and identify regulatory genes and pathways via text mining and other methods. METHODS:Genes in abstracts of associated literatures were identified. Gene ontology and protein-protein interaction (PPI) network analysis were performed. Then co-occurrence between genes and ovarian cancer subtypes were carried out followed by cluster analysis. RESULTS:Genes with highest frequencies are mostly involved in DNA repair, apoptosis, metal transport and drug detoxification, which are closely related to platinum resistance. Gene ontology analysis confirms this result. Some proteins such as TP53, HSP90, ESR1, AKT1, BRCA1, EGFR and CTNNB1 work as hub nodes in PPI network. According to cluster analysis, specific genes were highlighted in each subtype of ovarian cancer, indicating that various subtypes may have different resistance mechanisms respectively. CONCLUSIONS:Platinum resistance in ovarian cancer involves complicated signaling pathways and different subtypes may have specific mechanisms. Text mining, combined with other bio-information methods, is an effective way for systematic analysis.
| S-EPMC7066848 | biostudies-literature
Project description:Background: Major Depressive Disorder (MDD) is a highly prevalent, recurrent, and potentially chronic disorder. Identifying risk factors and underlying mechanisms to inform preventive and therapeutic interventions is therefore imperative. Emotion regulation is a proposed factor in the development and maintenance of MDD. The aim of the present review was to summarize and synthesize research on self-reported emotion regulation strategy use and emotion regulation abilities in adults diagnosed with current and remitted MDD. Methods: Seventy-two eligible studies were retrieved from databases through a systematic literature search. Group differences between individuals with current MDD, remitted MDD, and healthy controls were calculated using meta-analytic procedures. Meta-regression analyses investigated potential moderator effects on emotion regulation difficulties. Results: Results indicated that individuals with current MDD report higher maladaptive emotion regulation strategy use for avoidance (Hedges' g = 1.3), rumination (g = 2.1), and suppression (g = 1.1) compared to healthy controls. Also, they reported lower adaptive emotion regulation strategy use for acceptance (g = -1.0), problem solving (g = -1.0), and reappraisal (g = -0.7). Individuals with current MDD reported limited general emotion regulation abilities, indicated by higher alexithymia (g = 1.45), lower emotional awareness (g = -0.95), emotional clarity (g = -1.50) and emotional tolerance (g = -1.89). Similar results were found in individuals with remitted MDD for avoidance (g = 1.0), rumination (g = 1.1), suppression (g = 0.6), and general emotion regulation abilities. However, no difference was found between individuals with remitted MDD and healthy controls for adaptive emotion regulation strategies. Meta-regression analyses suggest that age of illness onset, comorbid anxiety and duration of remission influence emotion regulation. Conclusion: The present review and meta-analysis indicates that individuals with current and remitted MDD have difficulties with emotion regulation compared to individuals who have never been depressed. Although depressive symptoms improve, emotion regulation difficulties may continue, and could be a contributing factor to relapse. Our findings inform future research on emotion regulation and psychotherapeutic interventions.
| S-EPMC5968125 | biostudies-literature
Project description:BackgroundSomatic symptoms and related disorders (SSD) are prevalent phenomena in the health-care system. Disturbances in emotion regulation (ER) are commonly observed in patients suffering from SSD.ObjectivesThis review aimed to examine ER processes that characterize SSD by a systematic analysis of the available empirical studies.Data sourcesPsycINFO and PubMed databases for the articles published between January 1985 and June 2018.Search terms"emotion/al regulation" or "affect regulation" and various forms of SSD.Study eligibility criteriaEmpirical studies that a) assigned adolescent or adult patients suffering from SSD based on a clinical diagnosis, and b) examined the relationship between ER and SSD, were included.Study synthesis methodsA tabular summary of the articles was generated according to study characteristics, study quality, variables, and findings. The findings were organized based on ER variables used in the articles and diagnoses of SSD, which were then re-organized under the main constituents of ER (attention, body, and knowledge).ResultsThe findings of the 64 articles largely supported the association between SSD and disturbances in ER, which are usually shared by different diagnoses of SSD. The results indicate that patients show a reduced engagement with cognitive content of emotions. On the other hand, bodily constituents of ER seem to depict an over-reactive pattern. Similarly, the patients tend to encounter difficulties in flexibly disengaging their (spontaneous) attention from emotional material.LimitationsThere is a scarcity of longitudinal designs, randomized controlled trials, experiments, and diary studies suited to investigate the short- and long-term causal relationship between ER and SSD. Symptoms of SSD and measures to assess emotion regulation are heterogeneous.Conclusions and implicationsAssessment of ER processes is potentially useful to understand SSD and for treatment planning. Furthermore, a concurrent investigation of the dynamic interaction of the ER modalities promises insights for better understanding of the role of ER in development, course, and maintenance of SSD.
| S-EPMC6555516 | biostudies-literature