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Journal articles on the topic 'Anxiety detection'

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1

Tyrer, Peter, and Helen Tyrer. "Health anxiety: detection and treatment." BJPsych Advances 24, no. 1 (2018): 66–72. http://dx.doi.org/10.1192/bja.2017.5.

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SUMMARYHealth anxiety is an important new diagnosis that is increasing in frequency because of changing attitudes towards health, particularly excessive use of health information on the internet (cyberchondria). People with abnormal health anxiety become over-diligent monitors of their health, misinterpret most somatic sensations as evidence of disease, consult medical professionals unnecessarily and frequently, and are often over-investigated. Relatively few patients with health anxiety present to psychiatrists; most are seen in primary and secondary medical care. This paper reviews the diagn
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Hickey, Blake Anthony, Taryn Chalmers, Phillip Newton, et al. "Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review." Sensors 21, no. 10 (2021): 3461. http://dx.doi.org/10.3390/s21103461.

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Recently, there has been an increase in the production of devices to monitor mental health and stress as means for expediting detection, and subsequent management of these conditions. The objective of this review is to identify and critically appraise the most recent smart devices and wearable technologies used to identify depression, anxiety, and stress, and the physiological process(es) linked to their detection. The MEDLINE, CINAHL, Cochrane Central, and PsycINFO databases were used to identify studies which utilised smart devices and wearable technologies to detect or monitor anxiety, depr
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Berggren, Nick, Thomas Blonievsky, and Nazanin Derakshan. "Enhanced visual detection in trait anxiety." Emotion 15, no. 4 (2015): 477–83. http://dx.doi.org/10.1037/a0039449.

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Badner, Neal H., Warren R. Nielson, Shirley Munk, Caroline Kwiatkowska, and Adrian W. Gelb. "Preoperative anxiety: detection and contributing factors." Canadian Journal of Anaesthesia 37, no. 4 (1990): 444–47. http://dx.doi.org/10.1007/bf03005624.

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Gregory, Sally M., and Anthony Lambert. "Anxiety, conscious awareness and change detection." Consciousness and Cognition 21, no. 1 (2012): 69–79. http://dx.doi.org/10.1016/j.concog.2011.09.009.

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Palanisamy, Kamini Kamakshi, and Arthi Rengaraj. "Detection of Anxiety-Based Epileptic Seizures in EEG Signals Using Fuzzy Features and Parrot Optimization-Tuned LSTM." Brain Sciences 14, no. 8 (2024): 848. http://dx.doi.org/10.3390/brainsci14080848.

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In humans, epilepsy is diagnosed through electroencephalography (EEG) signals. Epileptic seizures (ESs) arise due to anxiety. The detection of anxiety-based seizures is challenging for radiologists, and there is a limited availability of anxiety-based EEG signals. Data augmentation methods are required to increase the number of novel samples. An epileptic seizure arises due to anxiety, which manifests as variations in EEG signal patterns consisting of changes in the size and shape of the signal. In this study, anxiety EEG signals were synthesized by applying data augmentation methods such as r
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Priasmoro, Dian Pitaloka, Ikhwan Yuda Kusuma, and Yuni Asri. "Social anxiety disorder: prevalence and dominant factor among adolescents in urban and rural school." International Journal of Public Health Science (IJPHS) 13, no. 2 (2025): 919–26. https://doi.org/10.11591/ijphs.v13i2.23610.

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In the age range of 16-18 years, commonly known as adolescence, individuals undergo a period of self-discovery in their socio-emotional development. Failures during this process can lead to individuals experiencing anxiety in social interactions, which can have a negative impact on their mental health. The Indonesia National Adolescent Mental Health Survey (I-NAMHS), findings also indicate that the most prevalent mental disorder among adolescents is anxiety disorder (a combination of social phobia and generalized anxiety disorder), is equivalent to 15.5 million. The widespread use of the inter
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Sharif, Mohammad O. "Guest Editorial - Dental anxiety: detection and management." Journal of Applied Oral Science 18, no. 2 (2010): i. http://dx.doi.org/10.1590/s1678-77572010000200001.

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Byrne, Angela, and Michael W. Eysenck. "Trait anxiety, anxious mood, and threat detection." Cognition & Emotion 9, no. 6 (1995): 549–62. http://dx.doi.org/10.1080/02699939508408982.

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Stein, Dan J., and Randolph M. Nesse. "Threat detection, precautionary responses, and anxiety disorders." Neuroscience & Biobehavioral Reviews 35, no. 4 (2011): 1075–79. http://dx.doi.org/10.1016/j.neubiorev.2010.11.012.

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Smith, Marianne, Todd Ingram, and Veronica Brighton. "Detection and Assessment of Late-Life Anxiety." Journal of Gerontological Nursing 35, no. 7 (2009): 9–15. http://dx.doi.org/10.3928/00989134-20090527-02.

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Tlachac, ML, Michael Heinz, Miranda Reisch, and Samuel S. Ogden. "Symptom Detection with Text Message Log Distributions for Holistic Depression and Anxiety Screening." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 8, no. 1 (2024): 1–28. http://dx.doi.org/10.1145/3643554.

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Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD) are both heterogeneous in their clinical presentations, manifesting with unique symptom profiles. Despite this, prior digital phenotype research has primarily focused on disorder-level detection rather than symptom-level detection. In this research, we predict the existence of individual symptoms of MDD and GAD with SMS log metadata, and ensemble these symptom-level classifiers to screen for depression and anxiety, thus accounting for disorder heterogeneity. Further, we collect an additional dataset of retrospectively harve
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Okmayura, Finanta, Vitriani Vitriani, and Melly Novalia. "Dempster Shafer Algorithm For Expert System Early Detection of Anxiety Disorders." Lontar Komputer : Jurnal Ilmiah Teknologi Informasi 12, no. 2 (2021): 112. http://dx.doi.org/10.24843/lkjiti.2021.v12.i02.p05.

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Anxiety is an excessive anxiety disorder that is often found in psychology. Some people generally do not realize that they may have symptoms of this anxiety disorder. If ignored and continued continuously, it can interfere with one's activities, reduce academic achievement, and disrupt psychological conditions that affect their lives. This expert system for early detection of anxiety disorders is carried out using forward chaining tracing techniques to explore the knowledge base, and the inference motor is the Dempster Shafer algorithm. Dempster Shafer calculation is done by combining symptom
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Roslan, Nur Rowaidah, Mohd Fadhli Mohd Fauzi, Lim Wan Teng, and Abdul Ghani Nur Azurah. "Maternal Mental Health following Ultrasonographic Detection of Fetal Structural Anomaly in the Midst of the COVID-19 Pandemic." International Journal of Environmental Research and Public Health 18, no. 24 (2021): 12900. http://dx.doi.org/10.3390/ijerph182412900.

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Prenatal ultrasonographic detection of fetal structural anomaly may adversely affect maternal mental health throughout pregnancy, particularly in the current COVID-19 pandemic. This study aims to prospectively assess maternal stress, anxiety, and depression following ultrasonographic detection of fetal structural anomaly from diagnosis until delivery during the COVID-19 pandemic. A total of 141 pregnant women at a tertiary hospital who underwent detailed scans between 16 and 24 gestational weeks were included and categorized into the study (anomaly finding, n = 65) and comparison (normal findi
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Nawindah, Nawindah. "Early Detection Level to Students Anxiety Using Fuzzy Sugeno Method." NUANSA INFORMATIKA 19, no. 1 (2025): 61–65. https://doi.org/10.25134/ilkom.v19i1.311.

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Anxiety disorders are generally common, especially in adolescents. In institutions that provide non-formal education such as Learning activity group or Sanggar Kegiatan Belajar (SKB), students often face complex problems ranging from family problems, problems in teaching and learning activities and problems at work. For this reason, further treatment is needed to overcome the problems faced. One of them is counseling activities, this activity is really needed to help students find the right solution. However, the teaching staff, both tutors and teachers who teach, do not yet have the basic kno
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Whitmore, Carly, Sarah Neil-Sztramko, Sebastien Grenier, et al. "Factors associated with anxiety and fear of falling in older adults: A rapid systematic review of reviews." PLOS ONE 19, no. 12 (2024): e0315185. https://doi.org/10.1371/journal.pone.0315185.

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Background Anxiety disorders are prevalent amongst older adults and negatively impact their quality-of-life and health. Anxiety disorders often go undetected or are misattributed to age-related changes. The aim of this systematic review of reviews, was to synthesize existing evidence on risk factors associated with anxiety in older adults to improve opportunities for early detection and intervention. Methods A rapid systematic review of reviews was performed. Studies were included if they were systematic reviews, specific to older adults, reported modifiable or non-modifiable factors associate
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Wankar, Srushti Rajendra. "Real Time Depression and Anxiety Detection Using Machine Learning." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30436.

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Depression affects a staggering 264 million individuals worldwide, constituting a significant cause of disability. The detrimental impact of a negative workplace environment extends beyond productivity loss to encompass physical and medical ailments. Unfortunately, individuals often refrain from seeking help due to the pervasive stigma surrounding mental health issues. Leveraging the potential of machine learning, we have embarked on a journey to predict depression using diverse algorithms. Our study draws upon routine survey data, delving into factors such as home and workplace environments,
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18

Minnick, Mark R., Koraly E. Pérez-Edgar, and José A. Soto. "A Disruption in the Balance of Attentional Systems Plays a Role in Trait Anxiety." Brain Sciences 10, no. 10 (2020): 761. http://dx.doi.org/10.3390/brainsci10100761.

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Elevated levels of anxiety are associated with attentional threat biases and inefficient attentional control, with the latter requiring sustained cognitive effort. The current study assessed self-reported and behavioral evidence of attentional functioning, along with electrodermal activity (EDA; measured via changes in skin conductance level [SCL reactivity]) as an index of sympathetic arousal, to examine whether these vulnerabilities are evident among individuals with elevated trait anxiety (non-clinical). Fifty-nine participants completed a working memory span task measuring attentional cont
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Pasupuleti, Murali Krishna. "Mental Health Monitoring from Social Media Using Emotion-Aware NLP Models." International Journal of Academic and Industrial Research Innovations(IJAIRI) 05, no. 05 (2025): 474–85. https://doi.org/10.62311/nesx/rphcr9.

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Abstract: Mental health disorders are on the rise globally, and early detection through non-invasive means has become a critical public health need. Social media platforms serve as real-time expressions of public emotions and personal states, offering a rich source for mental health assessment. This study explores the use of emotion-aware natural language processing (NLP) models, including RoBERTa, BERTweet, and DistilBERT, for detecting signs of depression, anxiety, and emotional distress from Twitter and Reddit posts. Using fine-tuned models on annotated mental health datasets, we evaluate p
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Lee, Seungji, Taejun Lee, Taeyang Yang, Changrak Yoon, and Sung-Phil Kim. "Detection of Drivers’ Anxiety Invoked by Driving Situations Using Multimodal Biosignals." Processes 8, no. 2 (2020): 155. http://dx.doi.org/10.3390/pr8020155.

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It has become increasingly important to monitor drivers’ negative emotions during driving to prevent accidents. Despite drivers’ anxiety being critical for safe driving, there is a lack of systematic approaches to detect anxiety in driving situations. This study employed multimodal biosignals, including electroencephalography (EEG), photoplethysmography (PPG), electrodermal activity (EDA) and pupil size to estimate anxiety under various driving situations. Thirty-one drivers, with at least one year of driving experience, watched a set of thirty black box videos including anxiety-invoking event
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Shishkova, V. N., Yu G. Dranitsyna, and O. M. Drapkina. "Algorithms for the management of patients with anxiety in the internist’s practice." Cardiovascular Therapy and Prevention 22, no. 2 (2023): 3526. http://dx.doi.org/10.15829/1728-8800-2023-3526.

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The development of guidelines for the detection and further management of patients with anxiety for outpatient physicians is relevant due to the high incidence of anxiety disorders in patients with non-communicable diseases, including cardiovascular diseases, deterioration in quality of life and an increase in adverse outcomes in patients with anxiety. In addition, there is an insufficient awareness of outpatient doctors about the importance of diagnosing and treating anxiety disorders. The aim was to present original "Algorithms for the Management of Patients with Anxiety in the Internist’s P
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Al-Nafjan, Abeer, and Mashael Aldayel. "Anxiety Detection System Based on Galvanic Skin Response Signals." Applied Sciences 14, no. 23 (2024): 10788. http://dx.doi.org/10.3390/app142310788.

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Anxiety is a significant mental health concern that can be effectively monitored using physiological signals such as galvanic skin response (GSR). While the potential of machine learning (ML) algorithms to enhance the classification of anxiety based on GSR signals is promising, their effectiveness in this context remains largely underexplored. This study addresses this gap by investigating the performance of three commonly used ML algorithms, support vector machine (SVM), K-nearest neighbor (KNN), and random forest (RF), in classifying anxiety and stress activity using a benchmark dataset. We
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Lavedán Santamaría, Ana, Olga Masot, Olga Canet Velez, Teresa Botigué, Tània Cemeli Sánchez, and Judith Roca. "Diagnostic Concordance between the Visual Analogue Anxiety Scale (VAS-A) and the State-Trait Anxiety Inventory (STAI) in Nursing Students during the COVID-19 Pandemic." International Journal of Environmental Research and Public Health 19, no. 12 (2022): 7053. http://dx.doi.org/10.3390/ijerph19127053.

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Anxiety is one of the most common problems among nursing students. The State-Trait Anxiety Inventory (STAI) is used to detect anxiety in this population; however, its length hinders speedy detection. For this reason, a faster and more efficient instrument is needed for early detection. This study aimed to determine the relationship between the anxiety measurement scales State-Trait Anxiety Inventory (STAI) and the Visual Analogue Scale for Anxiety (VAS-A) by establishing a discrimination threshold through the contrast of true positive rates (VPR) and false positive rates (FPR). To this end, a
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Sajja, Guna Sekhar. "Machine Learning based Detection of Depression and Anxiety." International Journal of Computer Applications 183, no. 45 (2021): 20–23. http://dx.doi.org/10.5120/ijca2021921856.

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25

Jyothirmayi, M., M. Sidharth, B. Vijay, Ritik Khandelwal, K. Raju, and P. A. Dinesh. "Early Detection and Analysis of Anxiety in Adolescents." Mathematical Models and Computer Simulations 15, no. 5 (2023): 956–67. http://dx.doi.org/10.1134/s2070048223050150.

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MA, Yuanxiao, and Xu CHEN. "The functional mechanism of oxytocin in anxiety detection and extinction among anxiety-susceptible groups." Advances in Psychological Science 31, no. 1 (2023): 10. http://dx.doi.org/10.3724/sp.j.1042.2023.00010.

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Wang, Huasang, Othmane Atif, Jirong Tian, Jonguk Lee, Daihee Park, and Yongwha Chung. "Multi-level Hierarchical Complex Behavior Monitoring System for Dog Psychological Separation Anxiety Symptoms." Sensors 22, no. 4 (2022): 1556. http://dx.doi.org/10.3390/s22041556.

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An increasing number of people own dogs due to the emotional benefits they bring to their owners. However, many owners are forced to leave their dogs at home alone, increasing the risk of developing psychological disorders such as separation anxiety, typically accompanied by complex behavioral symptoms including excessive vocalization and destructive behavior. Hence, this work proposes a multi-level hierarchical early detection system for psychological Separation Anxiety (SA) symptoms detection that automatically monitors home-alone dogs starting from the most fundamental postures, followed by
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Qin, Jinghui, Changsong Liu, Tianchi Tang, et al. "Mental-Perceiver: Audio-Textual Multi-Modal Learning for Estimating Mental Disorders." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 23 (2025): 25029–37. https://doi.org/10.1609/aaai.v39i23.34687.

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Mental disorders, such as anxiety and depression, have become a global concern that affects people of all ages. Early detection and treatment are crucial to mitigate the negative effects these disorders can have on daily life. Although AI-based detection methods show promise, progress is hindered by the lack of publicly available large-scale datasets. To address this, we introduce the Multi-Modal Psychological assessment corpus (MMPsy), a large-scale dataset containing audio recordings and transcripts from Mandarin-speaking adolescents undergoing automated anxiety/depression assessment intervi
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Arfiyanti, Nisa Annisa, Melyana Nurul Widyawati, and Kurnianingsih Kurnianingsih. "Application of Calm Pregnancy Based on Artificial Intelligence as an Early Anxiety Detection and Recommendations for Pregnant Women." Jurnal Keperawatan Silampari 7, no. 1 (2023): 200–208. http://dx.doi.org/10.31539/jks.v7i1.5871.

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This research aims to develop and test the Calm Pregnant application for early detection and recommendations for anxiety. The method used in this research uses two stages. The first stage is research and development (R&D), which aims to develop products whose quality will be tested. The trial results show that the Calm Pregnancy Application is relevant as a medium in speeding up early detection of anxiety by a difference of 172.65 seconds, speeding up the provision of recommendations to pregnant women by a difference of 250.79 seconds, and being able to get feedback from midwives directly.
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Liu, Changhe, Na Hua, Yanli Zhang, and Cuirong Wang. "Predictive Significance of High-Sensitivity C-Reactive Protein Combined with Homocysteine for Coronary Heart Disease in Patients with Anxiety Disorders." BioMed Research International 2022 (August 23, 2022): 1–8. http://dx.doi.org/10.1155/2022/7657347.

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Background. Currently, there are few studies on biomarkers for predicting coronary heart disease (CHD) with anxiety disorders. Objective. To explore risk factors and investigate the predictive value of common clinical peripheral blood indicators, such as high-sensitivity C-reactive protein (hs-CRP) and homocysteine (Hcy) for CHD patients with anxiety disorders. Methods. One hundred fifty-three hospitalized patients with chest pain as the main symptom and a Hamilton Anxiety Scale score > 14 were recruited from October 2020 to September 2021 in the hospital. Then, they were divided into an an
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Junli Zheng, Meilian Jiang, Kai Zheng, et al. "Psychological Status and its Influencing Factors of Staff in a District of Shenzhen: A Retrospective Study." Actas Españolas de Psiquiatría 53, no. 1 (2025): 119–25. https://doi.org/10.62641/aep.v53i1.1699.

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Background: Anxiety, depression, and sleep disorders, as psychological and emotional diseases, have serious impact on people's physical and mental health, and receive increasing academic attention. This study aimed to examine anxiety, depression, and sleep disorder of staff in a district of Shenzhen and to provide the basis for the development of targeted intervention measures to improve the psychological status of cadres. Methods: Based on the psychological evaluation data of staff cadres in a district of Shenzhen City obtained from January to December 2020, a stratified sampling method was a
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Zhang, L., Y. L. He, H. Ma, Z. N. Liu, F. J. Jia, and M. Y. Zhang. "FC30-06 - Prevalence of depressive - anxiety disorders of gastroenterology outpatients in five cities cross China." European Psychiatry 26, S2 (2011): 1988. http://dx.doi.org/10.1016/s0924-9338(11)73691-4.

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IntroductionDepression and anxiety disorders are prevalent mental disorders in China. But some those patients do not seek help from psychiatrists firstly but see internists first.Objectives and aimsThis study aimed to investigate the prevalence of depressive - anxiety disorders in gastroenterology outpatients and assess the detection rate provided by physicians in China.MethodsA multicenter, hospital-based cross-sectional study was carried on in the 15 large general hospitals of five cities cross China. A total of 1995 gastroenterological outpatients were screened by Hospital Anxiety and Depre
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Senanayake, Ashala, and Sidath Liyanage. "A Narrative Review on Human Anxiety Detection in Social Media using Natural Language Processing." Journal of Desk Research Review and Analysis 1, no. 2 (2023): 103–9. http://dx.doi.org/10.4038/jdrra.v1i2.20.

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Currently, with the boundless proliferation of social media platforms, it is undoubted that the world is in the middle of a significant phase of social media evolution. These virtually created user environments allow users to create, share, and interact with content. Most people who interact with social media make a pitch to share their mood, tension, feelings, and behaviour unhesitatingly with the community. Mostly, these data can be taken as a mirror that reflects the mental health status of a person, such as stress, anxiety, and suffering. With increased social media penetration, people ten
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Pal, Rishi, Deepak Adhikari, Md Belal Bin Heyat, et al. "A Novel Smart Belt for Anxiety Detection, Classification, and Reduction Using IIoMT on Students’ Cardiac Signal and MSY." Bioengineering 9, no. 12 (2022): 793. http://dx.doi.org/10.3390/bioengineering9120793.

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The prevalence of anxiety among university students is increasing, resulting in the negative impact on their academic and social (behavioral and emotional) development. In order for students to have competitive academic performance, the cognitive function should be strengthened by detecting and handling anxiety. Over a period of 6 weeks, this study examined how to detect anxiety and how Mano Shakti Yoga (MSY) helps reduce anxiety. Relying on cardiac signals, this study follows an integrated detection-estimation-reduction framework for anxiety using the Intelligent Internet of Medical Things (I
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Xu, Guozheng, Xiang Gao, Lizheng Pan, et al. "Anxiety detection and training task adaptation in robot-assisted active stroke rehabilitation." International Journal of Advanced Robotic Systems 15, no. 6 (2018): 172988141880643. http://dx.doi.org/10.1177/1729881418806433.

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In the therapist-centered rehabilitation program, the experienced therapists can observe emotional changes of stroke patients and make corresponding decisions on their intervention strategies. Likewise, robotic-assisted stroke rehabilitation systems will be more appreciated if they can also perceive emotional states of the stroke patients and enhance their engagements by exploring emotion-based dynamic difficulty adjustments. Nevertheless, few research have addressed this issue. A two-phase pilot study with anxiety as the target emotion state was conducted in this article. In phase I, the moto
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Avhustiuk, Mariia M. "PSYCHOLOGICAL ASSISTANCE IN REDUCING ENGLISH LANGUAGE ANXIETY IN UNIVERSITY STUDENTS." Scientific Notes of Ostroh Academy National University: Psychology Series 1 (January 28, 2021): 26–34. http://dx.doi.org/10.25264/2415-7384-2021-12-26-34.

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The aim of the paper is to outline some possible ways of psychological assistance in defining and reducing foreign language anxiety in university students. In this context the analysis focuses on a theoretical study of language anxiety in the psychological literature and states its role in learning foreign languages and studying in university in general, highlights and explains some reasons of language anxiety, analyses its peculiarities and effect on the efficacy of learning foreign languages. Moreover, we aim at defining some possible ways of detection, prevention, and reducing foreign langu
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Wulandari, Desy, Wisnu Barlianto, and Susanto Nugroho. "EARLY DETECTION AND COUNSELLING OF ANXIETY DISORDERS IN CHILDREN WITH SYSTEMIC LUPUS ERYTHEMATOSUS." Jurnal Pengabdian Masyarakat Dalam Kesehatan 7, no. 1 (2025): 1–7. https://doi.org/10.20473/jpmk.v7i1.62680.

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Introduction: Paediatric Systemic Lupus Erythematosus (pSLE) is a chronic autoimmune disease that affects the quality of life of patients. Anxiety is a mental health problem that is rarely addressed in Indonesia. There are still many instances of children and adolescents with anxiety due to the duration of therapy, the severity of the disease, psychological conditions, and support from the environment and family. Therefore, the detection of anxiety disorders in children and adolescents really needs to be improved. This community service activity aims to provide counselling on anxiety detection
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Grillon, C., O. J. Robinson, K. O'Connell, et al. "Clinical anxiety promotes excessive response inhibition." Psychological Medicine 47, no. 3 (2016): 484–94. http://dx.doi.org/10.1017/s0033291716002555.

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BackgroundLaboratory tasks to delineate anxiety disorder features are used to refine classification and inform our understanding of etiological mechanisms. The present study examines laboratory measures of response inhibition, specifically the inhibition of a pre-potent motor response, in clinical anxiety. Data on associations between anxiety and response inhibition remain inconsistent, perhaps because of dissociable effects of clinical anxiety and experimentally manipulated state anxiety. Few studies directly assess the independent and interacting effects of these two anxiety types (state v.
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Hylan, Jessica. "Factors influencing health anxiety." BPS Branch Awards 1, no. 1 (2023): 15–18. http://dx.doi.org/10.53841/bpsba.2023.1.1.15.

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Health anxiety can have a detrimental impact to psychological wellbeing and is linked to increased healthcare utilisation and associated costs for healthcare providers. This study investigated relationships between health anxiety and age, gender, trait anxiety, medical care-seeking, and serious illness diagnosis in the individual and their blood relatives. A cross-sectional, correlational design was used to assess these relationships across a sample of 108 adult participants. Analysis revealed significant associations between health anxiety and age, gender, and trait anxiety. It is concluded t
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Maraza Quispe, Benjamin, Luis Alfaro Casas, Olga Melina Alejandro Oviedo, et al. "Biofeedback of states of anxiety through automated detection processes using different technologies." International Journal of Engineering & Technology 7, no. 3 (2018): 1609. http://dx.doi.org/10.14419/ijet.v7i3.15041.

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In this work, a system model is proposed, which applies biofeedback techniques, through automatic detection procedures, using different technologies, constituted by a system formed by a prototype based on a set of "Arduino" microcontrollers, which monitor the levels of anxiety, using as a measurement technique, the Body Temperature Variables, and the Galvanic Skin Response. The measurement is validated by comparing Zung's self-report and depressive symptoms scale, which offers diagnostic approaches, which comprise most of the characteristics of anxiety or depression, involving affective, physi
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Yu, Hao, Yan Zhao, and Yawen Li. "Analysis of Early Warning Diagnostic Indexes and Influencing Factors of Anxiety and Depression in Patients with Arrhythmia." Evidence-Based Complementary and Alternative Medicine 2022 (October 15, 2022): 1–7. http://dx.doi.org/10.1155/2022/2061340.

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Objective. Arrhythmia patients complicated with psychological problems are very common in clinics. The imbalance of autonomic nervous regulation of the heart caused by anxiety and depression will further promote the occurrence and development of arrhythmia. For nonorganic heart disease, β receptor blockers combined with antianxiety drugs have a good effect. Therefore, it is necessary to analyze the influencing factors of anxiety and depression in patients with arrhythmias. Methods. We included 150 patients with arrhythmia and divided them into observation groups (80 patients with anxiety and d
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Miranda, Darién, Bert Arnrich, and Jesús Favela. "Detecting Anxiety States when Caring for People with Dementia." Methods of Information in Medicine 56, no. 01 (2017): 55–62. http://dx.doi.org/10.3414/me15-02-0012.

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SummaryBackground: Caregiving is a complex, stressful activity, which frequently leads to anxiety and the development of depressive disorders. Recent advances in wearable sensing allows to monitor relevant physiological data of the caregiver for detecting anxiety spans and for enacting coping strategies to reduce their anxiety when needed.Objectives: This work proposes a method to infer anxiety states of caregivers when caring for people with dementia, by using physiological data.Methods: A model using Markov chains for detecting internal anxiety states is proposed. The model is tested with a
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Tian, Yali, Haojiang Zuo, Fang Wang, Ailin Wei, and Ka Li. "Application of Polystyrene Nanofiber in Detection of Anxiety-Related Bio-Marker Cortisol." Science of Advanced Materials 13, no. 9 (2021): 1724–31. http://dx.doi.org/10.1166/sam.2021.4107.

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This work aimed to explore the correlation between plasma cortisol level and the occurrence of anxiety through the polystyrene (PS) nano-fiber solid phase extraction technology. The PS nano-fibers were prepared, and its characterization was performed to detect its adsorption selectivity and blood compatibility. 32 anxiety patients treated in the hospital were recruited as the research subjects, with another 35 mentally healthy people as controls. The Hamilton Anxiety (HAMA) Scale, Symptom checklist-90 (SCL-90) scale, and Eysenck personality questionnaire (EPQ) were used to analyze the anxiety
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C., YOSEPU. "Anxiety and Stress Detection through Speech Recognition using CNN." IJRSET MARCH Volume 10 Issue 3 10, no. 3 (2023): 1–4. https://doi.org/10.5281/zenodo.8401678.

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Stress is a feeling of emotional tension. It canhaveaninfluenceonourmentalhealth and for the people around us. While anxiety is a natural reaction tostresswhichcanbefearfulthiscanleadtopanicattacks. These mental issues have to be addressed byeveryone.Thispaperexplainshowweareusingvocal/audiodatasettodetectstressandanxietyinaperson.Wehavedevelopedastressandanxietydetection model using deep neural network. Here audiodatasets is considered from Kaggle in which the audioconsists of 7 emotions i.e., joy, fear, disgust, neutral,sadness, surprised and anger. These audio datasets areused to train and
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Ancillon, Lou, Mohamed Elgendi, and Carlo Menon. "Machine Learning for Anxiety Detection Using Biosignals: A Review." Diagnostics 12, no. 8 (2022): 1794. http://dx.doi.org/10.3390/diagnostics12081794.

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Anxiety disorder (AD) is a major mental health illness. However, due to the many symptoms and confounding factors associated with AD, it is difficult to diagnose, and patients remain untreated for a long time. Therefore, researchers have become increasingly interested in non-invasive biosignals, such as electroencephalography (EEG), electrocardiogram (ECG), electrodermal response (EDA), and respiration (RSP). Applying machine learning to these signals enables clinicians to recognize patterns of anxiety and differentiate a sick patient from a healthy one. Further, models with multiple and diver
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Tan, Yuyang, Qinwei Zeng, and Hongchang Zhang. "Research on anxiety detection based on personalized data markers." Journal of Physics: Conference Series 1948, no. 1 (2021): 012035. http://dx.doi.org/10.1088/1742-6596/1948/1/012035.

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Dupuis, G., M. C. Lambany, E. Kennedy, J. Perrault, D. Millette, and P. David. "ANXIETY AND DEPRESSION DETECTION VIA QUALITY OF LIFE MEASUREMENT." Journal of Cardiopulmonary Rehabilitation 9, no. 10 (1989): 424. http://dx.doi.org/10.1097/00008483-198910200-00066.

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Rossignol, M., S. Campanella, and P. Philippot. "Electrophysiological correlates of emotional face detection in social anxiety." NeuroImage 47 (July 2009): S181. http://dx.doi.org/10.1016/s1053-8119(09)71993-7.

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Giannakakis, G., M. Pediaditis, D. Manousos, et al. "Stress and anxiety detection using facial cues from videos." Biomedical Signal Processing and Control 31 (January 2017): 89–101. http://dx.doi.org/10.1016/j.bspc.2016.06.020.

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Wang, Mei, Songzhi Zhang, Yuanjie Lv, and Huimin Lu. "Anxiety Level Detection Using BCI of Miner’s Smart Helmet." Mobile Networks and Applications 23, no. 2 (2017): 336–43. http://dx.doi.org/10.1007/s11036-017-0935-5.

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