Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses
Abstract
:1. Introduction
2. State-of-the-Art
Research Gap
3. Methodology and Design
3.1. Methodology Overview
3.2. Data Collection
3.3. Data Preprocessing
3.4. Parameters Discovery
3.5. Validation
3.6. Visualization and Reporting
4. Results: Parameter Discovery for Psychological Heath (Drugs and Treatments)
4.1. Overview and Taxonomy
4.2. Diseases and Disorders
Postpartum Depression
4.3. Individual Factors
4.3.1. Anxiety
4.3.2. Sadness
4.3.3. Poor Concentration
4.3.4. Poor Memory
4.3.5. Loss of Appetite
4.3.6. Fear of Medicine
4.4. Social and Economic Factors
4.4.1. Poverty
4.4.2. Unemployment and Insufficient Finances
4.4.3. High Cost of Healthcare
4.4.4. Loss of Loved Ones
4.4.5. Forensic Psychiatry
4.4.6. Social Depression
4.5. Treatment Options
4.5.1. Walking
4.5.2. Optimism
4.5.3. Good Company
4.5.4. Pendulum Technique
4.5.5. Spirituality
4.5.6. Antioxidants
4.5.7. Painkillers and Antidepressants
4.5.8. Community-Supported Therapies
4.5.9. Psychotherapy and Medication
4.6. Treatment Limitations
4.6.1. Antidepressant Limitations
4.6.2. Negative Effects of Antidepressant
4.7. Parameter-Drug Associations (Drugs and Treatments)
5. Results: Parameter Discovery for Psychological Heath (Causes and Effects)
5.1. Overview and Taxonomy
5.2. Diseases and Disorders
5.2.1. Attachment Disorder
5.2.2. Insomnia
5.2.3. Obsessive-Compulsive Disorder (OCD)
5.2.4. Post-Surgery Depression
5.2.5. Chronic Physiological Diseases
5.3. Individual Factors
5.3.1. Fear
5.3.2. Sadness
5.3.3. Loneliness
5.3.4. Lacking Passion
5.3.5. Suppressing Emotions
5.3.6. Negative Emotions
5.3.7. Devil (Negative Thoughts)
5.3.8. Lacking Inner Peace
5.4. Social and Economic Factors
5.4.1. Study
5.4.2. Work
5.4.3. Lifestyles
5.4.4. High Cost of Healthcare
5.4.5. Seasonal Depression (Seasonal Effective Disorder)
5.5. Treatment Options
5.5.1. Emotional Release (Psychotherapy)
5.5.2. Good Friends
5.5.3. Spirituality
5.5.4. Surgery
5.6. Parameter-Drug Associations (Causes and Effects)
6. Results: Parameter Discovery for Psychological Heath (Drug Abuse)
6.1. Overview and Taxonomy
6.2. Drug Abuse
6.2.1. Bipolar Disorder
6.2.2. University Exams
6.2.3. Death of Loved Ones
6.2.4. Addiction
6.2.5. Suicide
6.2.6. Flakka Drug
6.3. Parameter-Drug Associations (Drug Abuse)
7. Discussion
8. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Alaql, A.A.; AlQurashi, F.; Mehmood, R. Data-Driven Deep Journalism to Discover Age Dynamics in Multi-Generational Labour Markets from LinkedIn Media. J. Media 2023, 4, 120–145. [Google Scholar] [CrossRef]
- Dybdahl, R.; Lien, L. Mental health is an integral part of the sustainable development goals. Prev. Med. Commun. Health 2018, 1, 1–3. [Google Scholar] [CrossRef] [Green Version]
- Albano, G.D.; Malta, G.; La Spina, C.; Rifiorito, A.; Provenzano, V.; Triolo, V.; Vaiano, F.; Bertol, E.; Zerbo, S.; Argo, A. Toxicological Findings of Self-Poisoning Suicidal Deaths: A Systematic Review by Countries. Toxics 2022, 10, 654. [Google Scholar] [CrossRef] [PubMed]
- Xu, X.; Shrestha, S.S.; Trivers, K.F.; Neff, L.; Armour, B.S.; King, B.A. U.S. healthcare spending attributable to cigarette smoking in 2014. Prev. Med. 2021, 150, 106529. [Google Scholar] [CrossRef]
- American Addiction Centers. Addiction Statistics. Drug & Substance Abuse Statistics. Available online: https://americanaddictioncenters.org/rehab-guide/addiction-statistics (accessed on 13 August 2022).
- Schächinger, H.; Grob, M.; Ritz, R.; Solér, M. Mental stress increases right heart afterload in severe pulmonary hypertension. Clin. Physiol. Funct. Imaging 2000, 20, 483–487. [Google Scholar] [CrossRef]
- Volpato, E.; Toniolo, S.; Pagnini, F.; Banfi, P. The Relationship Between Anxiety, Depression and Treatment Adherence in Chronic Obstructive Pulmonary Disease: A Systematic Review. Int. J. Chronic Obstr. Pulm. Dis. 2021, 16, 2001–2021. [Google Scholar] [CrossRef]
- Altuntaś, S.Ç.; Hocaoǧlu, Ç. Effects of Chronic Suppression or Oversuppression of Thyroid-Stimulating Hormone on Psychological Symptoms and Sleep Quality in Patients with Differentiated Thyroid Cancer. Horm. Metab. Res. 2021, 53, 683–691. [Google Scholar] [CrossRef]
- Rodriguez-Ayllon, M.; Cadenas-Sanchez, C.; Esteban-Cornejo, I.; Migueles, J.; Mora-Gonzalez, J.; Henriksson, P.; Martín-Matillas, M.; Mena-Molina, A.; Molina-García, P.; Estévez-López, F.; et al. Physical fitness and psychological health in overweight/obese children: A cross-sectional study from the ActiveBrains project. J. Sci. Med. Sport 2018, 21, 179–184. [Google Scholar] [CrossRef]
- Tubbs, A.S.; Khader, W.; Fernandez, F.-X.; Grandner, M.A. The common denominators of sleep, obesity, and psychopathology. Curr. Opin. Psychol. 2019, 34, 84–88. [Google Scholar] [CrossRef]
- Taylor, G.M.; Treur, J.L. An application of the stress-diathesis model: A review about the association between smoking tobacco, smoking cessation, and mental health. Int. J. Clin. Health Psychol. 2023, 23, 100335. [Google Scholar] [CrossRef]
- Jing, X.; Lu, L.; Yao, Y. Personality modifies the effect of post-traumatic stress disorder (PTSD) and society support on depression-anxiety-stress in the residents undergone catastrophic flooding in Henan, China. Med. Pract. 2022, 73, 305–314. [Google Scholar] [CrossRef]
- Ramirez, G.; Hooper, S.Y.; Kersting, N.B.; Ferguson, R.; Yeager, D. Teacher Math Anxiety Relates to Adolescent Students’ Math Achievement. AERA Open 2018, 4, 1–13. [Google Scholar] [CrossRef] [Green Version]
- Salari, N.; Hosseinian-Far, A.; Jalali, R.; Vaisi-Raygani, A.; Rasoulpoor, S.; Mohammadi, M.; Rasoulpoor, S.; Khaledi-Paveh, B. Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: A systematic review and meta-analysis. Glob. Health 2020, 16, 57. [Google Scholar] [CrossRef]
- Zhang, C.; Ye, M.; Fu, Y.; Yang, M.; Luo, F.; Yuan, J.; Tao, Q. The Psychological Impact of the COVID-19 Pandemic on Teenagers in China. J. Adolesc. Health 2020, 67, 747–755. [Google Scholar] [CrossRef]
- Alswedani, S.; Mehmood, R.; Katib, I.; Altowaijri, S.M. Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses. Preprints 2023, 2023010415. [Google Scholar] [CrossRef]
- Hagger, V.; Trawley, S.; Hendrieckx, C.; Browne, J.L.; Cameron, F.; Pouwer, F.; Skinner, T.; Speight, J. Diabetes MILES Youth–Australia: Methods and sample characteristics of a national survey of the psychological aspects of living with type 1 diabetes in Australian youth and their parents. BMC Psychol. 2016, 4, 42. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Schmidt, A.M.; Golden, S.D.; Gottfredson, N.C.; Ennett, S.T.; Aiello, A.E.; Ribisl, K.M. Psychological Health and Smoking in Young Adulthood. Emerg. Adulthood 2019, 9, 320–329. [Google Scholar] [CrossRef]
- Bryant, R.A. Post-Traumatic Stress Disorder: A State-of-the-Art Review of Evidence and Challenges. World Psychiatry 2019, 18, 259–269. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bremner, J.D. Traumatic stress: Effects on the brain. Dialog-Clin. Neurosci. 2006, 8, 445–461. [Google Scholar] [CrossRef] [PubMed]
- Kellett, S.; Bee, C.; Aadahl, V.; Headley, E.; Delgadillo, J. A pragmatic patient preference trial of cognitive behavioural versus cognitive analytic guided self-help for anxiety disorders. Behav. Cogn. Psychother. 2020, 49, 104–111. [Google Scholar] [CrossRef]
- Daviu, N.; Bruchas, M.R.; Moghaddam, B.; Sandi, C.; Beyeler, A. Neurobiological links between stress and anxiety. Neurobiol. Stress 2019, 11, 100191. [Google Scholar] [CrossRef]
- Karrer, T.M.; Bassett, D.S.; Derntl, B.; Gruber, O.; Aleman, A.; Jardri, R.; Laird, A.R.; Fox, P.T.; Eickhoff, S.B.; Grisel, O.; et al. Brain-based ranking of cognitive domains to predict schizophrenia. Hum. Brain Mapp. 2019, 40, 4487–4507. [Google Scholar] [CrossRef] [Green Version]
- Cannizzaro, E.; Lavanco, G.; Castelli, V.; Cirrincione, L.; Di Majo, D.; Martines, F.; Argo, A.; Plescia, F. Alcohol and Nicotine Use among Adolescents: An Observational Study in a Sicilian Cohort of High School Students. Int. J. Environ. Res. Public Health 2022, 19, 6152. [Google Scholar] [CrossRef]
- Çelik, N.; Ceylan, B.; Ünsal, A.; Çağan, Ö. Depression in health college students: Relationship factors and sleep quality. Psychol. Health Med. 2018, 24, 625–630. [Google Scholar] [CrossRef]
- Kirubasankar, A.; Nagarajan, P.; Kandasamy, P.; Kattimani, S. More students with anxiety disorders in urban schools than in rural schools: A comparative study from Union Territory, India. Asian J. Psychiatry 2020, 56, 102529. [Google Scholar] [CrossRef]
- Mao, Y.; Zhang, N.; Liu, J.; Zhu, B.; He, R.; Wang, X. A systematic review of depression and anxiety in medical students in China. BMC Med. Educ. 2019, 19, 327. [Google Scholar] [CrossRef] [Green Version]
- Quek, T.T.-C.; Tam, W.W.-S.; Tran, B.X.; Zhang, M.; Ho, C.S.-H. The Global Prevalence of Anxiety Among Medical Students: A Meta-Analysis. Int. J. Environ. Res. Public Health 2019, 16, 2735. [Google Scholar] [CrossRef] [Green Version]
- Capone, V.; Joshanloo, M.; Park, M.S.-A. Burnout, depression, efficacy beliefs, and work-related variables among school teachers. Int. J. Educ. Res. 2019, 95, 97–108. [Google Scholar] [CrossRef]
- Jeon, L.; Buettner, C.K.; Grant, A.A. Early Childhood Teachers’ Psychological Well-Being: Exploring Potential Predictors of Depression, Stress, and Emotional Exhaustion. Early Educ. Dev. 2017, 29, 53–69. [Google Scholar] [CrossRef]
- Gianfredi, V.; Provenzano, S.; Santangelo, O.E. What can internet users’ behaviours reveal about the mental health impacts of the COVID-19 pandemic? A systematic review. Public Health 2021, 198, 44–52. [Google Scholar] [CrossRef]
- Ding, Y.; Wang, T. Mental Health Management of English Teachers in English Teaching Under the COVID-19 Era. Front. Psychol. 2022, 13, 916886. [Google Scholar] [CrossRef] [PubMed]
- Huckins, J.F.; Dasilva, A.W.; Wang, W.; Hedlund, E.; Rogers, C.; Nepal, S.K.; Wu, J.; Obuchi, M.; Murphy, E.I.; Meyer, M.L.; et al. Mental Health and Behavior of College Students During the Early Phases of the COVID-19 Pandemic: Longitudinal Smartphone and Ecological Momentary Assessment Study. J. Med. Internet Res. 2020, 22, e20185. [Google Scholar] [CrossRef] [PubMed]
- Zhou, S.-J.; Zhang, L.-G.; Wang, L.-L.; Guo, Z.-C.; Wang, J.-Q.; Chen, J.-C.; Liu, M.; Chen, X.; Chen, J.-X. Prevalence and socio-demographic correlates of psychological health problems in Chinese adolescents during the outbreak of COVID-19. Eur. Child Adolesc. Psychiatry 2020, 29, 749–758. [Google Scholar] [CrossRef] [PubMed]
- Alswedani, S.; Mehmood, R.; Katib, I. Sustainable Participatory Governance: Data-Driven Discovery of Parameters for Planning Online and In-Class Education in Saudi Arabia During COVID-19. Front. Sustain. Cities 2022, 4, 97. [Google Scholar] [CrossRef]
- Alswedani, S.; Katib, I.; Abozinadah, E.; Mehmood, R. Discovering Urban Governance Parameters for Online Learning in Saudi Arabia During COVID-19 Using Topic Modeling of Twitter Data. Front. Sustain. Cities 2022, 4, 751681. [Google Scholar] [CrossRef]
- Browning, M.H.E.M.; Larson, L.R.; Sharaievska, I.; Rigolon, A.; McAnirlin, O.; Mullenbach, L.; Cloutier, S.; Vu, T.M.; Thomsen, J.; Reigner, N.; et al. Psychological impacts from COVID-19 among university students: Risk factors across seven states in the United States. PLoS ONE 2021, 16, e0245327. [Google Scholar] [CrossRef]
- Zhang, Y.; Lyu, H.; Liu, Y.; Zhang, X.; Wang, Y.; Luo, J. Monitoring Depression Trends on Twitter During the COVID-19 Pandemic: Observational Study. JMIR Infodemiology 2021, 1, e26769. [Google Scholar] [CrossRef]
- Fatima, I.; Mukhtar, H.; Ahmad, H.F.; Rajpoot, K. Analysis of user-generated content from online social communities to characterise and predict depression degree. J. Inf. Sci. 2017, 44, 683–695. [Google Scholar] [CrossRef]
- Islam, R.; Kabir, M.A.; Ahmed, A.; Kamal, A.R.M.; Wang, H.; Ulhaq, A. Depression detection from social network data using machine learning techniques. Health Inf. Sci. Syst. 2018, 6, 8. [Google Scholar] [CrossRef]
- Wang, X.; Zhang, C.; Ji, Y.; Sun, L.; Wu, L.; Bao, Z. A Depression Detection Model Based on Sentiment Analysis in Micro-Blog Social Network. In Trends and Applications in Knowledge Discovery and Data Mining, Proceedings of the PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Gold Coast, QLD, Australia, April 14–17 2013, Revised Selected Papers 17; Springer: Berlin/Heidelberg, Germany, 2013. [Google Scholar] [CrossRef]
- Medhat, W.; Hassan, A.; Korashy, H. Sentiment analysis algorithms and applications: A survey. Ain Shams Eng. J. 2014, 5, 1093–1113. [Google Scholar] [CrossRef] [Green Version]
- Fatimah, N.; Budi, I.; Santoso, A.B.; Putra, P.K. Analysis of Mental Health During the COVID-19 Pandemic in Indonesia using Twitter Data. In Proceedings of the 2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA), Bandung, Indonesia, 29–30 September 2021. [Google Scholar] [CrossRef]
- Tong, L.; Liu, Z.; Jiang, Z.; Zhou, F.; Chen, L.; Lyu, J.; Zhang, X.; Zhang, Q.; Sadka, A.; Wang, Y.; et al. Cost-sensitive Boosting Pruning Trees for depression detection on Twitter. IEEE Trans. Affect. Comput. 2022. early access. [Google Scholar] [CrossRef]
- Chen, X.; Sykora, M.D.; Jackson, T.W.; Elayan, S. What about Mood Swings. In WWW ‘18: Companion Proceedings of the Web Conference 2018; Association for Computing Machinery (ACM): New York, NY, USA, 2018; pp. 1653–1660. [Google Scholar] [CrossRef] [Green Version]
- Ismail, N.H.; Liu, N.; Du, M.; He, Z.; Hu, X. A deep learning approach for identifying cancer survivors living with post-traumatic stress disorder on Twitter. BMC Med. Informatics Decis. Mak. 2020, 20, 254. [Google Scholar] [CrossRef]
- Roy, K.; Lokala, U.; Khandelwal, V.; Sheth, A. “Is Depression Related to Cannabis?”: A Knowledge-Infused Model for Entity and Relation Extraction with Limited Supervision. arXiv 2021, arXiv:2102.01222. [Google Scholar]
- Alabdulkreem, E. Prediction of depressed Arab women using their tweets. J. Decis. Syst. 2020, 30, 102–117. [Google Scholar] [CrossRef]
- Almouzini, S.; Khemakhem, M.; Alageel, A. Detecting Arabic Depressed Users from Twitter Data. Procedia Comput. Sci. 2019, 163, 257–265. [Google Scholar] [CrossRef]
- Sievert, C.; Shirley, K.E. LDAvis: A Method for Visualizing and Interpreting Topics. In Proceedings of the Workshop on Interactive Language Learning, Visualization, and Interfaces, Baltimore, MD, USA, 27 June 2014. [Google Scholar]
- pyLDAvis—pyLDAvis 2.1.2 Documentation. Available online: https://pyldavis.readthedocs.io/en/latest/readme.html (accessed on 16 March 2022).
- National Institute of Mental Health. Anxiety Disorders. Available online: https://www.nimh.nih.gov/health/topics/anxiety-disorders (accessed on 23 February 2023).
- Mayo Clinic. Anxiety Disorders—Symptoms and Causes. Available online: https://www.mayoclinic.org/diseases-conditions/anxiety/symptoms-causes/syc-20350961 (accessed on 23 February 2023).
- Arboleda-Flórez, J. Forensic psychiatry: Contemporary scope, challenges and controversies. World Psychiatry 2006, 5, 87–91. [Google Scholar]
- Bradford, J.; Glancy, G. Forensic Psychiatry. Int. Encycl. Soc. Behav. Sci. 2001, 5740–5745. [Google Scholar] [CrossRef]
- Souri, H.; Hasanirad, T. Relationship between Resilience, Optimism and Psychological Well-Being in Students of Medicine. Procedia-Soc. Behav. Sci. 2011, 30, 1541–1544. [Google Scholar] [CrossRef] [Green Version]
- Gartlehner, G.; Nussbaumer-Streit, B.; Gaynes, B.N.; Forneris, C.A.; Morgan, L.C.; Greenblatt, A.; Wipplinger, J.; Lux, L.J.; Van Noord, M.G.; Winkler, D. Second-Generation Antidepressants for Preventing Seasonal Affective Disorder in Adults. Cochrane Database Syst. Rev. 2019, 2019. [Google Scholar] [CrossRef] [PubMed]
- Leventhal, A.M. Sadness, Depression, and Avoidance Behavior. Behav. Modif. 2008, 32, 759–779. [Google Scholar] [CrossRef]
- Benca, R.M.; Peterson, M.J. Insomnia and depression. Sleep Med. 2008, 9 (Suppl. 1), S3–S9. [Google Scholar] [CrossRef] [PubMed]
- Johns Hopkins Medicine. Depression and Sleep: Understanding the Connection. Available online: https://www.hopkinsmedicine.org/health/wellness-and-prevention/depression-and-sleep-understanding-the-connection (accessed on 25 December 2022).
- Mayo Clinic. Melatonin. Available online: https://www.mayoclinic.org/drugs-supplements-melatonin/art-20363071 (accessed on 25 December 2022).
- Serdarevic, M.; Osborne, V.; Striley, C.W.; Cottler, L.B. The association between insomnia and prescription opioid use: Results from a community sample in Northeast Florida. Sleep Health 2017, 3, 368–372. [Google Scholar] [CrossRef] [PubMed]
- Bigatti, S.M.; Hernandez, A.M.; Cronan, T.A.; Rand, K.L. Sleep disturbances in fibromyalgia syndrome: Relationship to pain and depression. Arthritis Rheum. 2008, 59, 961–967. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cheatle, M.D.; Foster, S.; Pinkett, A.; Lesneski, M.; Qu, D.; Dhingra, L. Assessing and Managing Sleep Disturbance in Patients with Chronic Pain. Anesthesiol. Clin. 2016, 34, 379–393. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- National Institute of Mental Health. Bipolar Disorder. Available online: https://www.nimh.nih.gov/health/topics/bipolar-disorder (accessed on 23 February 2023).
- Mayo Clinic Staff. Drug Addiction (Substance Use Disorder). Available online: https://www.mayoclinic.org/diseases-conditions/drug-addiction/symptoms-causes/syc-20365112 (accessed on 23 February 2023).
- Patocka, J.; Zhao, B.; Wu, W.; Klimova, B.; Valis, M.; Nepovimova, E.; Kuca, K. Flakka: New Dangerous Synthetic Cathinone on the Drug Scene. Int. J. Mol. Sci. 2020, 21, 8185. [Google Scholar] [CrossRef]
- Onaolapo, O.J.; Onaolapo, A.Y. Melatonin in drug addiction and addiction management: Exploring an evolving multidimensional relationship. World J. Psychiatry 2018, 8, 64–74. [Google Scholar] [CrossRef]
- Jia, S.; Guo, X.; Chen, Z.; Li, S.; Liu, X.-A. The roles of the circadian hormone melatonin in drug addiction. Pharmacol. Res. 2022, 183, 106371. [Google Scholar] [CrossRef]
- Song, J.; Park, J.H.; Han, D.H.; Roh, S.; Son, J.H.; Choi, T.Y.; Lee, H.; Kim, T.H.; Lee, Y.S. Comparative study of the effects of bupropion and escitalopram on Internet gaming disorder. Psychiatry Clin. Neurosci. 2016, 70, 527–535. [Google Scholar] [CrossRef]
- Alahmari, N.; Alswedani, S.; Alzahrani, A.; Katib, I.; Albeshri, A.; Mehmood, R. Musawah: A Data-Driven AI Approach and Tool to Co-Create Healthcare Services with a Case Study on Cancer Disease in Saudi Arabia. Sustainability 2022, 14, 3313. [Google Scholar] [CrossRef]
- Alqahtani, E.; Janbi, N.; Sharaf, S.; Mehmood, R. Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling. Sustainability 2022, 14, 13534. [Google Scholar] [CrossRef]
- Ahmad, I.; Alqurashi, F.; Abozinadah, E.; Mehmood, R. Deep Journalism and DeepJournal V1.0: A Data-Driven Deep Learning Approach to Discover Parameters for Transportation. Sustainability 2022, 14, 5711. [Google Scholar] [CrossRef]
- Alsahafi, R.; Alzahrani, A.; Mehmood, R. Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations. Sustainability 2023, 15, 4166. [Google Scholar] [CrossRef]
- Alomari, E.; Katib, I.; Albeshri, A.; Yigitcanlar, T.; Mehmood, R.; Sa, A.A. Iktishaf+: A Big Data Tool with Automatic Labeling for Road Traffic Social Sensing and Event Detection Using Distributed Machine Learning. Sensors 2021, 21, 2993. [Google Scholar] [CrossRef]
- Alaql, A.A.; Alqurashi, F.; Mehmood, R. Multi-Generational Labour Markets: Data-Driven Discovery of Multi-Perspective System Parameters Using Machine Learning. arXiv 2023, arXiv:2302.10146. [Google Scholar]
- Alomari, E.; Katib, I.; Albeshri, A.; Mehmood, R. COVID-19: Detecting Government Pandemic Measures and Public Concerns from Twitter Arabic Data Using Distributed Machine Learning. Int. J. Environ. Res. Public Health 2021, 18, 282. [Google Scholar] [CrossRef]
Macro-Parameter | Parameters | No. | (%) | Keywords |
---|---|---|---|---|
Diseases and Disorders | Postpartum Depression | 29 | 2 | depression, state, birth, gloom, death, different, especially, depression, medicine, mother, afflict, women, usually, sadness, husband, advise, hate, postpartum, call, first |
Individual Factors | Anxiety | 14 | 3.1 | medicine, anxiety, depression, psychological, depression, psychological, possible, doctor, limit, pharmaceutical, blessing, obsessive-compulsive disorder, sleep, pain, treatment, great, health, book, dose |
Sadness | 18 | 2.8 | depression, treatment, sadness, time, psychological, anti (depression), symptoms, psychological, how, pills, treatment, wonder, deep, disappointed, hopes, wound, in, re-in, psychiatric, heal | |
Poor Concentration | 19 | 2.8 | depression, pharmaceutical, medicine, treatment, disorder, anti (depression), self, causes, pills, diabetes, a lot, deficiency, anxiety, prescription, diseases, praise be to God, treatment, psychological, depression, dangerous | |
Poor Memory | 10 | 3.6 | depression, memory, medicine, anti (depression), pills, patient, brain, cause, anti (depression), try, because, others, weakness, concentration, important, cause, dangerous, that, unknowingly, effects | |
Loss of Appetite | 27 | 2.4 | biscuits, psychological, treatment, medicine, depression, eat, thing, take, alone, light, first, sat, in, number, coffee, chocolate, food, great, dispute, side | |
Fear of Medicine | 3 | 5.1 | fear, medicine, need, length, take, mind, intense, went, decided, thoughts, feelings, now, have, take, no, help, feelings, wellness, end | |
Social and Economic Factors | Poverty | 26 | 2.5 | sadness, say, receive, pain, quantity, children, tears, tell, pension, stolen, waiting, bear, medicines, diseases, depression, psychological, fear, dwelling, strong, psychological |
Unemployment and Insufficient Finances | 2 | 6.5 | once, depression, pills, good, unfortunately, work, difficult, peace, condition, help, tired, tried, mercy, blessings, prison, sons and daughters, suicide, bring, have, seeker | |
High Cost of Healthcare | 4 | 4.2 | mother, depression, thinking, swear, great, please, keep, diabetes, pay, pay her medication, incapacitated, sleep, electricity, income, sick, tightness, elderly widow, cheer, hypertension, bill | |
Loss of Loved Ones | 21 | 2.8 | pills, depression, period, feeling, lost, most important, depression, best, sleep, matter, medicine, even, life, living, death, friend, desire, I, Iniesta, wife | |
Forensic Psychiatry | 24 | 2.7 | psychiatry, medicine, treatment, and treatment, doctor, patients, pain, services, related, addition, knowledge, provision, efficiency, facilitation, medication, interaction, pertaining, trial, including, specifically | |
Social Depression | 22 | 2.8 | depression, pharmaceutical, depression, has, people, stay, treatment, sick, psychological, weight, take, treatment, medication, anti (depression), bigger, life, city, increase, when, stress | |
25 | 2.6 | |||
Treatment Options | Walking | 15 | 3.1 | prescribe, body, walking, negativity, psychological, energy, nature, anxiety, needs, pharmaceutical, diseases, fear, equivalent, work, painkillers, emptying, endorphins, sedatives, secrete, reduce |
Optimism | 17 | 2.9 | midst, happiness, sadness, worry, night, eye, place, water, thirst, make, cross, thunder, blackness, bridge, darkness, sight, make, grow, chagrin, whiteness | |
Good Company | 16 | 3 | depression, anti (depression), best, friend, anti (depressants), normal, possible, and then, remains, do, good, small, defect, floor, fifth, job, take, remains, introductions | |
Pendulum Technique | 28 | 2.3 | fear, then, question, pendulum, yourself, effectiveness, know, answer, write, ask, feelings, attachment, ready, mention, answer, sharp, intention, depression, anti (depressants), sun | |
Spirituality | 1 | 6.9 | heart, fear, right, medicine, world, heart, it, work, trust, remembrance, goodness, womb, infiltrate, cut off, cheap, boredom, affliction, depression, and as long as, stream | |
23 | 2.7 | |||
30 | 1.5 | |||
Antioxidants | 11 | 3.5 | coffee, psychological, depression, oxidation, treatment, anti (depression), condition, people, helps, most, moods, relieve, improve, simple, anti (oxidants), richness, fruits, combined, plus, vegetables | |
Painkillers and Antidepressants | 7 | 3.6 | depression, medicine, disease, treatment, patient, psychiatric, medication, pharmaceutical, psychological, anti (depression), instead of, doctor, depression, for a patient, Cipralex, painkiller, body, give, Celebrex, hurt | |
Community-Supported Therapies | 9 | 3.6 | diseases, psychological, group, lack of, society, life, interfering, faith, suffer, medicine, stigma, factors, the factors, deficiency, hereditary, healthy, therefore, requires, support, sport | |
Psychotherapy and Medication | 6 | 3.9 | psychiatric, pharmaceutical, treatment, psychiatric, treatment, diseases, depression, psychological, health, behavioral, drugs, doctor, psychiatric, medicinal, medicine, disease, drug, illness, pharmaceutical, psychiatrists | |
13 | 3 | |||
Treatment Limitations | Antidepressant Limitations | 5 | 4 | depression, medicine, truth, relieve, reality, yourself, but, natural, throughout, dealing, mind, so, crises, those, right, exaggerating, delight, emotion, happiness, nervousness, help |
Negative Effects of Antidepressant | 8 | 3.6 | depression, medicine, depression, anti (depressants), medicines, best, people, psychological, sadness, medicine, possible, pill, condition, psychological, actually, disease, diseases, there is, nervousness, causes | |
20 | 2.8 | |||
12 | 3.4 |
Macro-Parameter | Parameter | No. | (%) | Keywords |
---|---|---|---|---|
Diseases and Disorders | Attachment Disorder | 8 | 3.8 | psychological, possible, health, family, live, your life, hospital, person, story, song, reality, well-being, success, locked up, lost, attachment, audience, money, sung by her |
Insomnia | 12 | 3.2 | sleep, sadness, Lord, anxiety, doctor, eye, fear, depression, symptoms, from me, I am, fear, name, diaspora, myself, when, teach, blessings, matter | |
24 | 2.5 | |||
Obsessive Compulsive Disorder (OCD) | 30 | 2.2 | miss, pleasure, sleep, feeling, fear, way, daily, instead, comfort, concentration, my life, depression, thinking, habit, calm, depression, self, review, mental, practice | |
Post-Surgery Depression | 23 | 2.6 | operation, depression, feeling, eating, person, specific, effect, negative, always, time, stomach, eat, medical, happen, food, support, loneliness, for you, eat, get out | |
Chronic physiological Diseases | 9 | 3.7 | depression, depression, cause, psychological, sick, chronic, king, medical, brain, fear, diseases, Salman, suffering, surgical, cause, city, relationship, psychological, nerves, compensate | |
Individual Factors | Fear | 16 | 2.9 | leave, care, fear, increase, weight, about you, subject, sleep, diseases, poverty, keep away, think, and so on, difference, fear, doctor, health, face, your fear, sources |
Sadness | 19 | 2.9 | world, I can, depression, wish, real, people, complete, me, normal, age, try, need, needs, work, fear, person, I, years, time, stay | |
Loneliness | 4 | 4.6 | wish, heart, alone, sadness, ok, pass, loneliness, mind, stage, fear, focus, nights, human, thinking, anxiety, unknown, details, compensate, trust, calm down | |
Lacking Passion | 11 | 3.3 | depression, want, need, myself, be, times, moment, desire, overwhelming, disappear, the world, have, presence, heavy, exist, feel, want, depression, sadness, view | |
15 | 2.9 | |||
Suppressing Emotions | 17 | 2.9 | sadness, sorrow, physical, cause, after, able, personality, disease, experience, sleep, possible, upset/angry, need, your chest, was not, wish, tell, say, inside, live | |
Negative Emotions | 21 | 2.7 | depression, condition, people, this, because, human, life, depression, psychological, crying, sleep, conversation, life, yourself, have, sadness, anxiety, permanent, phrase, love | |
Devil (Negative Thoughts) | 22 | 2.7 | most important, sadness, anxiety, whirlpool, fear, heart, devil, life, comfortable, bad, sorrows, stable, caused, current, last, past, make, tense, destroy, cultivate | |
Lacking Inner Peace | 29 | 2.2 | life, peace, anxiety, insomnia, stay away, in you, people, many, things, topic, anger, inside me, focus, your Lord, struggle, fear, anxiety, psychological, joy | |
Social and Economic Factors | Study | 6 | 4.2 | concern, problem, subject, permission, fear, cause, psychological, lead, schools, academic, level, impact, delay, space, going, coming, elite, to school, disability, counsellors |
7 | 4 | |||
14 | 2.9 | |||
Work | 5 | 4.5 | depression, limit, need, possible, permanence, depressed, length, fear, came, no one, praise be to God, literally, still, life, sufficiency, society, psychological, coming, deficiency | |
Lifestyles | 25 | 2.5 | time, depression, sadness, cause, grace, speech, problems, know, silence, understood, inside, pretended, stupid, committed, smiled, answered, wellness, weight, in relation to, hospital | |
High Cost of Healthcare | 26 | 2.4 | depression, myself, knew, make, I don’t have, session, depression, psychological, period, good, for depression, seasons, diseases, suffering, fear, difficult, home, street, family, life | |
Seasonal Depression | 2 | 5.7 | depression, Saturday, gloom, depression, severe, I have, birth, feel, winter, weather, spray, period, know, month, offender, people, cause, feel, atmosphere, inside | |
18 | 2.9% | |||
Treatment Options | Emotional Release (Psychotherapy) | 1 | 6.3 | depression, life, fear, hair, remove, cut, winter, sleep, name, family, wake up, satiate, inside, side, entered, smell, bring, come, answer, people |
Good Friends | 10 | 3.4 | depression, better, anxiety, person, can, deeper, seriously, kidding, inside you, collect, spontaneity, quest, reach, continuity, wonderful, include you, the two things, the mother, cause, not happened | |
13 | 3 | |||
Spirituality | 20 | 2.8 | death, refuge, sleep, I seek refuge, sadness, psychological, spirit, joy, heart, rest, life, body, soul, society, anxiety, question, injustice, conditions, blackness, break | |
Surgery | 3 | 5.6 | operation, depression, sadness, hours, surgery, success, suffering, future, sleep, psychological, medical, patient, mood, Salman, natural, first, thinking, anxiety, excess, permanent |
Parameter | No. | (%) | Keywords |
Bipolar Disorder | 1 | 16.1 | gloom, mood, sadness, person, strange, degree, moment, condition, word, enter, logical, random, transform, waves, endurance, need, tears, moments, reassurance, understanding |
University Exams | 2 | 13.9 | once, depression, condition, fine, pills, work, tried, unfortunately, help, peace, family, suicide, prison, answer, mercy, cut, tired, have, difficult, see |
Death of Loved Ones | 6 | 4.4 | pills, depression, matter, feeling, period, depression, life, better, more important, medicine, even, death, lived, lost, sleep, go, desire, resistance, Kharkhi, pillow |
Addiction | 7 | 3.6 | trance, the person, person, world, happiness, truth, most important, drugs (illegal drugs), self, far, realistic, fact, closer, weakness, close, health, knowledge, narcissist, connection, dots |
8 | 3.6 | ||
24 | 1.5 | ||
Suicide | 19 | 1.7 | depression, pills, psychological, human, diseases, feel, psychological, people, love, mood, a lot, disease, depression, cause, illness, brain, excess, addiction, psychological, anxiety |
25 | 1.5 | ||
28 | 1.3 | ||
Flakka Drug | 26 | 1.5 | depression, fear, love, potion, intense, new, take, feeling, problem, desire, alone, therefore, withdrawal, dope, lethargy, drug, to withdraw, attempt, symptoms, depression |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Alswedani, S.; Mehmood, R.; Katib, I.; Altowaijri, S.M. Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses. Toxics 2023, 11, 287. https://doi.org/10.3390/toxics11030287
Alswedani S, Mehmood R, Katib I, Altowaijri SM. Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses. Toxics. 2023; 11(3):287. https://doi.org/10.3390/toxics11030287
Chicago/Turabian StyleAlswedani, Sarah, Rashid Mehmood, Iyad Katib, and Saleh M. Altowaijri. 2023. "Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses" Toxics 11, no. 3: 287. https://doi.org/10.3390/toxics11030287