Abstract
Background:
The field of journalism has undergone substantial transformation with the integration of artificial intelligence (AI), leveraging technologies like natural language processing and automated reporting. These advancements enhance information processing speed, enable personalised content delivery and improve data analysis capabilities, thereby reshaping journalism practices.
Purpose:
Despite the benefits AI offers, concerns persist regarding its impact on job security and the mental health of journalists. Rapid technological changes can lead to increased job insecurity, altered job roles and heightened pressure to adapt, potentially affecting journalists’ mental well-being.
Methods:
This study utilises the Depression, Anxiety, and Stress Scale (DASS-21) to assess levels of depression, anxiety and stress among 500 journalists from various media organisations that have integrated AI technologies. Quantitative data analysis explores the relationship between AI integration and mental health outcomes.
Results:
The findings indicate significant correlations between the perceived threat of AI replacing jobs and higher levels of depression among journalists. Mixed effects were observed regarding the impact of AI integration on job roles, with associations found between AI integration and both increased depression and reduced stress levels.
Conclusion:
AI integration in journalism presents both opportunities and challenges for journalists’ mental health. Strategies to address job security concerns, enhance comfort with AI tools through training and establish mental health support systems are crucial for fostering a supportive environment in AI-driven newsrooms.
Keywords
Background
The field of journalism has experienced significant changes with the advent of artificial intelligence (AI). AI technologies, such as natural language processing, machine learning and automated reporting, have revolutionised the way news is produced and disseminated. These advancements enable faster information processing, personalised content delivery and enhanced data analysis capabilities, reshaping the landscape of journalism. 1 AI-driven tools like automated news writing (e.g. Automated Insights’ Word by Narrative Science) have become integral to modern journalism, increasing efficiency and productivity. 2
Problem Statement
Despite the advantages AI brings to journalism, its integration raises concerns about job security and the mental health of journalists. The rapid technological changes can lead to increased job insecurity, altered job roles and heightened pressure to adapt, potentially impacting journalists’ mental health. The fear of job loss due to AI is a growing concern among journalists, necessitating an investigation into how these changes affect their levels of depression, anxiety and stress.
Objectives
This study aims to use the Depression, Anxiety, and Stress Scale (DASS-21) questionnaire to assess the levels of depression, anxiety and stress among journalists, focusing on the impact of AI integration on their mental health. The specific objectives are: To measure the levels of depression, anxiety and stress among journalists using the DASS-21 questionnaire. To examine the relationship between AI integration in journalism and the levels of depression, anxiety and stress among journalists. To identify factors contributing to depression, anxiety and stress among journalists in the context of AI integration. To provide recommendations for news organisations to support journalists’ mental health.
Significance of the Study
This research contributes to understanding the mental health impact of AI on journalists. It provides empirical data on the levels of depression, anxiety and stress, informing news organisations and policymakers about the need for mental health support and interventions. The findings will help develop strategies to create a healthier working environment for journalists, ensuring their well-being in an AI-driven industry.
Literature Review
AI in Journalism
AI technologies have become increasingly prevalent in journalism, offering tools for automated reporting, data analysis and content personalisation. Automated reporting systems, such as Wordsmith and Quill, can generate news stories from structured data with minimal human intervention, increasing efficiency and reducing costs. 3 AI also enhances data journalism by enabling journalists to analyse large datasets and extract meaningful insights, as seen in platforms like Google’s Pinpoint. 4 These technologies facilitate more comprehensive and timely news coverage, meeting the demands of a fast-paced media landscape.
However, the integration of AI in journalism is not without challenges. There are concerns about the potential loss of jobs due to automation, the ethical implications of AI-generated content and the reliability of AI tools in maintaining journalistic standards. 5 The shift towards AI-driven journalism requires journalists to acquire new skills and adapt to changing job roles, which can be a source of stress and anxiety.
Mental Health Impact of AI
The mental health impact of AI on workers has been a topic of growing interest across various fields. In journalism, the rapid technological advancements and the constant pressure to adapt can lead to increased levels of stress and anxiety. 6 AI-induced job insecurity, the fear of being replaced by machines and the need to continuously update skills contribute to mental health challenges among journalists.
Theoretical perspectives on technology and mental health suggest that the adoption of new technologies can lead to psychological stress due to uncertainty and the need for continuous adaptation. 7 The job demands-resources model (JD-R model) posits that while technology can reduce job demands by automating routine tasks, it can also increase demands by requiring new skills and increasing the pace of work. 8 Understanding these dynamics in the context of AI in journalism is crucial for developing strategies to mitigate its negative mental health impact.
DASS-21 Scale
The DASS-21 is a widely used instrument for measuring mental health. It consists of 21 self-report items, divided into three subscales measuring depression, anxiety and stress. 9 The DASS-21 has been validated in various occupational settings, making it a suitable tool for assessing the mental health of journalists. Previous studies have used the DASS-21 scale to evaluate mental health in high-stress professions, demonstrating its reliability and validity. 10 Using the DASS-21 scale in this study provides a standardised method to assess the mental health impact of AI on journalists.
Methodology
Research Design
This study employs a quantitative research design to assess the levels of depression, anxiety and stress among journalists using the DASS-21 questionnaire. This study also explores the relationship between AI integration and journalists’ mental health.
Sample
The sample for this study consists of 500 journalists working in various media organisations that have integrated AI technologies. A stratified sampling method is used to ensure representation from different types of media (e.g. print, online, broadcast) and job roles (e.g. reporters, editors, data journalists). The sample size is determined based on the need for statistical power in the quantitative analysis.
Data Collection
A structured survey using the DASS-21 questionnaire is administered to the selected journalists. The DASS-21 consists of 21 items, divided into three subscales measuring depression, anxiety and stress. Respondents rate the extent to which they have experienced each state over the past week on a 4-point Likert scale. The survey also includes demographic questions and items related to AI usage in their work (e.g. frequency of AI tool usage, perceived impact of AI on job roles).
Data Analysis
The analysis indicates in Table 1 that the perceived threat of AI replacing jobs is significantly correlated with higher levels of depression, reflecting concerns about job security. The impact of AI integration on job roles shows a significant positive correlation with depression and a significant negative correlation with stress, suggesting mixed effects on mental health. Comfort with AI tools is negatively correlated with anxiety, indicating that familiarity and ease with AI may alleviate some anxiety. However, the frequency of AI tool use does not show significant correlations with depression, anxiety, or stress.
These findings suggest that while AI integration can have both positive and negative effects on employees’ mental health, the perceived threat of job replacement and the comfort level with AI tools play crucial roles. Organisations should address job security concerns and provide training to increase comfort with AI tools to mitigate adverse mental health effects.
This study aligns with previous research indicating that job insecurity and technological changes can impact mental health.11, 12 The significant relationship between AI integration and stress reduction supports findings by Lee et al. (2021) on the potential benefits of well-integrated AI systems.13
The regression analysis in Tables 2 to 4 reveal that the integration of AI in job roles, concerns about AI replacing jobs and comfort with using AI tools significantly influence levels of depression among employees. The model explains approximately 11.3% of the variance in depression levels (R square = 0.113).
Correlations Between AI Tool Use, Comfort, Perceived Threat, and Mental Health Outcomes.
Model Summary.
ANOVA Table.
Regression Coefficients.
The strongest predictor is the concern that AI could replace one’s job in the future (beta = 0.324, p < .001), followed by the impact of AI integration on the job role (beta = 0.287, p < .001). Comfort with using AI tools also has a significant but smaller effect on depression (beta = 0.104, p = .018).
The regression analysis in Tables 5 to 7 reveal that the integration of AI in job roles, concerns about AI replacing jobs and comfort with using AI tools do not significantly influence levels of stress among employees. The model explains only 1.2% of the variance in stress levels (R square = 0.012), and the overall regression model is not statistically significant (p = .113).
Model Summary.
ANOVA Table.
Regression Coefficients.
ANOVA Tables for Mental Health Outcomes.
However, the analysis shows that the impact of AI integration on job roles has a statistically significant but negative effect on stress levels (p = .023), indicating that better AI integration might reduce stress. The other variables (concerns about AI replacing jobs and comfort with AI tools) do not show significant effects on stress.
These findings suggest that while AI-related factors might be relevant for other aspects of employee well-being, they do not appear to significantly impact stress levels in this sample. Improved AI integration could potentially help reduce stress, but further research is needed to explore these relationships more deeply.
Depression: As in Table 8, there is a statistically significant difference in depression levels based on how AI integration has impacted the job role (p = .002). This suggests that the way AI integration affects job roles is associated with varying levels of depression among employees.
Anxiety: As in Table 8, there is no statistically significant difference in anxiety levels based on how AI integration has impacted the job role (p = .404). This suggests that AI integration does not significantly affect anxiety levels among employees.
Stress: As in Table 8, there is a statistically significant difference in stress levels based on how AI integration has impacted the job role (p = .029). This suggests that the way AI integration affects job roles is associated with varying levels of stress among employees.
Conclusion
This study investigated the impact of AI integration in journalism on journalists’ mental health, focusing on depression, anxiety and stress. The findings reveal that AI integration can have both positive and negative effects on mental health.
Perceived Threat of AI Replacing Jobs and Mental Health
A key finding is that the perceived threat of AI replacing jobs was significantly correlated with higher levels of depression, highlighting concerns about job security.11, 12 This aligns with previous research indicating that job insecurity and technological changes can negatively impact mental health. Organisations should address these concerns by providing clear communication about the future of jobs and by investing in training and development programmes that equip journalists with the skills needed to thrive in the AI-powered newsroom.
Impact of AI Integration on Job Roles and Mental Health
The impact of AI integration on job roles showed mixed effects on mental health. There was a significant positive correlation with depression, suggesting that some journalists may experience negative emotions as their jobs change due to AI integration. However, there was also a significant negative correlation with stress, indicating that well-integrated AI systems may help to alleviate stress. These findings suggest that the way AI is integrated into journalism plays a crucial role in its impact on mental health.
Comfort with AI Tools and Mental Health
Comfort with AI tools was negatively correlated with anxiety, suggesting that familiarity with AI may alleviate some anxiety. This finding highlights the importance of training and education programmes that help journalists develop their understanding and proficiency in using AI tools.
Connecting with Existing Research
The results indicate a complex interplay between AI integration and mental health outcomes. The significant positive correlations between the perceived threat of AI replacing jobs and depression suggest that concerns about job security can negatively impact mental health, aligning with previous research on job insecurity and mental health. 11 The weak but significant negative correlation between AI integration and stress suggests that well-integrated AI tools may reduce stress. 12
However, the weak and mostly non-significant correlations between AI tool use frequency or comfort and mental health outcomes indicate that these factors alone may not be strong predictors of mental health. This aligns with Williams and Cooper’s (2019) findings on the varied impacts of technology on workplace anxiety.14
Future research should consider longitudinal studies to explore the causal relationships between AI integration and mental health and investigate other potential moderating variables such as organisational support and employee resilience.
Recommendations
Based on the findings, the following recommendations are proposed to mitigate the negative mental health impacts of AI integration in journalism:
Job security assurance: News organisations should provide clear communication and assurance about job security to alleviate fears of AI replacing jobs. Training programmes: Implement comprehensive training programmes to increase journalists’ comfort with AI tools and technologies. Mental health support: Establish mental health support systems, including counselling and stress management workshops, to help journalists cope with the changes. Collaborative AI integration: Involve journalists in the AI integration process to ensure that the tools complement their work rather than replace it, fostering a sense of control and collaboration. Regular feedback: Create channels for regular feedback from journalists regarding AI tools and their impact on work, allowing for continuous improvement and adjustment.
Future Research
Future research could explore the following:
Specific AI integration strategies that promote mental well-being: More research is needed to identify specific AI integration strategies that are most likely to promote mental well-being among journalists. This could involve investigating factors such as the level of autonomy that journalists retain over their work, the transparency of AI decision-making processes and the availability of training and support for journalists. Long-term effects of AI on journalists’ mental health: This study examined the relationship between AI integration and mental health at a single point in time. Longitudinal studies are needed to track the long-term effects of AI on journalists’ mental health. This would help to provide a more nuanced understanding of how AI integration shapes journalists’ well-being over time. Mental health impacts on different journalist roles: This study looked at journalists in general. Future research could explore how AI integration impacts the mental health of different types of journalists, such as investigative reporters, data journalists and beat reporters. This would provide a more targeted understanding of the challenges and opportunities that AI presents for different segments of the journalism workforce.
In conclusion, the findings of this study suggest that AI integration can have both positive and negative effects on journalists’ mental health. By addressing job security concerns, promoting mental health awareness, focusing on human-AI collaboration, investing in training and education and monitoring and adapting AI integration strategies, news organisations can help to mitigate the negative effects of AI and promote the mental well-being of their journalists. Further research is needed to explore specific AI integration strategies that promote mental well-being, the long-term effects of AI on journalists’ mental health and the mental health impacts on different journalist roles.
Footnotes
Acknowledgement
The authors extend their gratitude to the participants and the concerned authorities for permitting the researcher to conduct this study. The authors also acknowledge the support of staff and colleagues who provided a conducive environment to carry on with this research work.
Authors’ Contributions
Akshay Upadhyay: Conceptualization, data collection, analysis, writing and research methodology design—original draft preparation, and visualization. Mayura Bijale: Supervision, review, and editing of the manuscript. Kashif Hasan (Corresponding Author): Supervision, review, and editing of the manuscript, data analysis and interpretation, overall guidance throughout the research process, and final approval of the version to be submitted.
Statement of Ethics
This study was performed in line with the principles of ICMR and World Medical Association Declaration of Helsinki.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to research, authorship and/or publication of this article.
Funding
The authors received no financial support for research, authorship and/or publication of this article.
Informed Consent
Written informed consent was taken from professionals to participate in this study. Participants were briefed about their voluntary participation and confidentiality of their responses. No incentive was provided for their participation.
ICMJE Statement
The manuscript complies with ICMJE guidelines.
