feliz
feliz
  • Users Online: 1755
  • Print this page
  • Email this page


 
 Table of Contents  
LETTER TO EDITOR
Year : 2022  |  Volume : 6  |  Issue : 3  |  Page : 294-295

Big data, artificial intelligence, and the future of mental health research


Department of Psychology, University of Porto, Porto, Portugal

Date of Submission24-Feb-2022
Date of Decision25-Feb-2022
Date of Acceptance17-Mar-2022
Date of Web Publication31-Oct-2022

Correspondence Address:
Mr. Braulio Oliveira de Araujo
University of Porto, Porto
Portugal
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/aip.aip_35_22

Rights and Permissions

How to cite this article:
Bezerra Lins SL, de Araujo BO. Big data, artificial intelligence, and the future of mental health research. Ann Indian Psychiatry 2022;6:294-5

How to cite this URL:
Bezerra Lins SL, de Araujo BO. Big data, artificial intelligence, and the future of mental health research. Ann Indian Psychiatry [serial online] 2022 [cited 2022 Dec 10];6:294-5. Available from: https://www.anip.co.in/text.asp?2022/6/3/294/360078



Sir,

It is undeniable that with advances in big data, artificial intelligence (AI) can make better predictions and decisions about human behavior. Thus, this ability is reflected in the field of mental health science, with significant advantages that AI can provide for data management, becoming indispensable for any researcher and health professional to handle large amounts of data.

This feature has been introduced on investigations because of AI's potential to generate significant results that would be impossible to have with a smaller volume of data.[1] Hence, new discoveries can be made more quickly and precisely than previously. Furthermore, AI can be applied in several mental health fields because of its potential to understand complex events like a pandemic and its pattern recognition.[2] Thereby, those features make the analysis process less exhaustive and allow the researcher to focus on critical issues, providing more reliable information to the analysis process.

In particular, progress has been made when influenza-related search queries on Google were automatically detected, providing a large amount of data, which propitiates predictions to reduce the process of spreading the virus of influenza.[3] Similarly, big data could be used for interventions surrounding the impact of a pandemic on people's behavior worldwide. Thus, AI is a promising tool for getting more vast mental health results.

In fact, large amounts of data processed by AI have already been used in psychological studies concerning the human mind. First, big data were used to analyze that people with serious mental illness, such as schizophrenia, suffer from higher mortality, providing comparisons on age, diagnosis, gender, and ethnicity.[4] One year later, the same author discovered through big data that people with that severe condition also have a lower life expectancy than smokers. As so, AI was used to show the reality surrounding the late diagnosis of bipolar disorder.[5]

Thus, big data are a growing tendency on studies about the human mind and behavior, as although AI cannot replace the role of investigator, it is expected to revolutionize mental health science by changing the way investigators collect and analyze data. Hence, this transition will be based on algorithm analysis, avoiding bias on the intervention, and focusing on the information provided by big data.

Ergo, we predict that future researchers shall learn how to program and articulate data analysis, because of the growth of big data, with more extensive and diverse databases, making AI one of the columns of most investigations. In fact, we may say that AI will end psychological science as we know it and bring the advent of structural changes in how to learn and execute investigations. Therefore, AI is the propellant to overcome contemporary psychology and introduce postmodernity psychology. This new era is coming and will allow investigators to accomplish more precise and vast studies, with more applicable results to a broader part of the population.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Haugeland J. Mind Design II: Philosophy, Psychology, Artificial Intelligence. 2nd Revised Edition. Cambridge, Massachusetts: MIT Press; 1997.  Back to cited text no. 1
    
2.
Vaishya R, Javaid M, Khan IH, Haleem A. Artificial Intelligence (AI) applications for COVID-19 pandemic. Diabetes Metab Syndr 2020;14:337-9.  Back to cited text no. 2
    
3.
Ginsberg J, Mohebbi MH, Patel RS, Brammer L, Smolinski MS, Brilliant L. Detecting influenza epidemics using search engine query data. Nature 2009;457:1012-4.  Back to cited text no. 3
    
4.
Chang CK, Hayes RD, Broadbent M, Fernandes AC, Lee W, Hotopf M, et al. All-cause mortality among people with serious mental illness (SMI), substance use disorders, and depressive disorders in southeast London: a cohort study. BMC psychiatry, 2010;10:1-7.  Back to cited text no. 4
    
5.
Chang CK, Hayes RD, Perera G, Broadbent MT, Fernandes AC, Lee WE, et al. Life expectancy at birth for people with serious mental illness and other major disorders from a secondary mental health care case register in London. PLoS One 2011;6:e19590.  Back to cited text no. 5
    




 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
References

 Article Access Statistics
    Viewed176    
    Printed6    
    Emailed0    
    PDF Downloaded31    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]