Exploring the Role of the Internet, Care Quality and Communication in Shaping Mental Health: Analysis of the Health Information National Trends Survey

Choudhury, Avishek; Asan, Onur; Alelyani, Turki

doi:10.1109/jbhi.2021.3087083

Cited by 13 publications

(7 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the context of our study, people are inclined to use ChatGPT, a technology not specifically designed for health care applications, for self-diagnosis, as they perceive it to be useful and easy to use. Similarly, as evidenced by our prior study on internet use and mental health, people often turn to online sources for self-diagnosis and health information, despite the potential negative impact on mental health [ 41 ]. The reliance on these sources can be attributed to “curiosity gap” theory [ 42 ], which suggests that individuals are motivated to seek information to reduce uncertainty, even when the information may not be entirely accurate or reliable.…”

Section: Discussionmentioning

confidence: 83%

User Intentions to Use ChatGPT for Self-Diagnosis and Health-Related Purposes: Cross-sectional Survey Study

Shahsavar¹,

Choudhury²

2023

JMIR Hum Factors

Self Cite

122

View full text Add to dashboard Cite

Background With the rapid advancement of artificial intelligence (AI) technologies, AI-powered chatbots, such as Chat Generative Pretrained Transformer (ChatGPT), have emerged as potential tools for various applications, including health care. However, ChatGPT is not specifically designed for health care purposes, and its use for self-diagnosis raises concerns regarding its adoption’s potential risks and benefits. Users are increasingly inclined to use ChatGPT for self-diagnosis, necessitating a deeper understanding of the factors driving this trend. Objective This study aims to investigate the factors influencing users’ perception of decision-making processes and intentions to use ChatGPT for self-diagnosis and to explore the implications of these findings for the safe and effective integration of AI chatbots in health care. Methods A cross-sectional survey design was used, and data were collected from 607 participants. The relationships between performance expectancy, risk-reward appraisal, decision-making, and intention to use ChatGPT for self-diagnosis were analyzed using partial least squares structural equation modeling (PLS-SEM). Results Most respondents were willing to use ChatGPT for self-diagnosis (n=476, 78.4%). The model demonstrated satisfactory explanatory power, accounting for 52.4% of the variance in decision-making and 38.1% in the intent to use ChatGPT for self-diagnosis. The results supported all 3 hypotheses: The higher performance expectancy of ChatGPT (β=.547, 95% CI 0.474-0.620) and positive risk-reward appraisals (β=.245, 95% CI 0.161-0.325) were positively associated with the improved perception of decision-making outcomes among users, and enhanced perception of decision-making processes involving ChatGPT positively impacted users’ intentions to use the technology for self-diagnosis (β=.565, 95% CI 0.498-0.628). Conclusions Our research investigated factors influencing users’ intentions to use ChatGPT for self-diagnosis and health-related purposes. Even though the technology is not specifically designed for health care, people are inclined to use ChatGPT in health care contexts. Instead of solely focusing on discouraging its use for health care purposes, we advocate for improving the technology and adapting it for suitable health care applications. Our study highlights the importance of collaboration among AI developers, health care providers, and policy makers in ensuring AI chatbots’ safe and responsible use in health care. By understanding users’ expectations and decision-making processes, we can develop AI chatbots, such as ChatGPT, that are tailored to human needs, providing reliable and verified health information sources. This approach not only enhances health care accessibility but also improves health literacy and awareness. As the field of AI chatbots in health care continues to evolve, future research should explore the long-term effects of using AI chatbots for self-diagnosis and investigate their potential integration with other digital health interventions to optimize patient care and outcomes. In doing so, we can ensure that AI chatbots, including ChatGPT, are designed and implemented to safeguard users’ well-being and support positive health outcomes in health care settings.

show abstract

Section: Discussionmentioning

confidence: 83%

User Intentions to Use ChatGPT for Self-Diagnosis and Health-Related Purposes: Cross-sectional Survey Study

Shahsavar¹,

Choudhury²

2023

JMIR Hum Factors

Self Cite

122

View full text Add to dashboard Cite

show abstract

“…Interview findings showed that most participants felt positively about the website, as it was a trustworthy source of mental health information and had helpful stress reduction features. Studies have confirmed that individuals seeking mental health resources online are concerned about the trustworthiness and credibility of e-mental health, as well as the effectiveness of self-help strategies [ 60 - 62 ], and as shown by another study, a lack of trust in a single online source can contribute to health information seekers’ stress [ 63 ].…”

Section: Discussionmentioning

confidence: 99%

An e–Mental Health Resource for COVID-19–Associated Stress Reduction: Mixed Methods Study of Reach, Usability, and User Perceptions

Minian¹,

Gayapersad²,

Saiva³

et al. 2022

JMIR Ment Health

View full text Add to dashboard Cite

Background COVID-19 and its public health response are having a profound effect on people’s mental health. To provide support during these times, Canada’s largest mental health and addiction teaching hospital (Centre for Addiction and Mental Health [CAMH]) launched the Mental Health and COVID-19 Pandemic website on March 18, 2020. This website was designed to be a nonstigmatizing psychoeducational resource for people experiencing mild to moderate distress due to COVID-19 and the public health response to the pandemic. Objective The aim of this study was to examine the reach, usability, and user perceptions of the CAMH Mental Health and COVID-19 Pandemic website. Methods This study used a mixed methods sequential explanatory design approach, which consisted of the following 2 distinct phases: (1) quantitative data collection and analysis and (2) qualitative semistructured interviews. In phase 1, we analyzed Google Analytics data to understand how many people visited the website and which were the most visited pages. We conducted a survey to identify users’ sociodemographic backgrounds, and assess the usability of the website using the System Usability Scale and users’ subjective stress levels using the Perceived Stress Scale (PSS-10). For phase 2, we conducted semistructured interviews to explore user experiences; user motivation, engagement, satisfaction, and perception of the stress reduction strategies; reflections of the website’s functionality, ease of use, navigation, and design; and recommendations for improvement. Results Google Analytics results showed 146,978 unique users from June 2020 to March 2021. Most users were from Canada (130,066, 88.5%). Between February 20, 2021, and June 4, 2021, 152 users completed the survey. Most users identified as white, female, and having at least a college degree. Based on the PSS-10 scores, most participants were experiencing moderate to high stress when they visited the website. Users rated the usability of the website as acceptable. Ten users completed in-depth interviews between May 2021 and June 2021. Positive feedback related to the content was that the website was a trustworthy source of mental health information with helpful evidence-based stress reduction strategies. Areas for improvement included the text heavy design of the website, wider dissemination/marketing, and greater accessibility of the website to meet the needs of diverse populations. Conclusions Adding stress reduction resources to a website from a well-respected institution may be a practical method to increase awareness and access to evidence-based stress reduction resources during times of crisis, where there is severe disruption to usual health care contacts. Efforts to ensure that these resources are more widely accessed, especially by diverse populations, are needed.

show abstract

“…Despite this broadening digital health landscape, our understanding of the internet's influence on patients remains limited, particularly in relation to GIC patients. As we delve into the digital age, the internet's 'double-edged sword' nature becomes apparent 25 . On the one hand, patients can gain substantial insight into their condition from reputable medical sources.…”

Section: Introductionmentioning

confidence: 99%

“…For example, a newly diagnosed pancreatic cancer patient may find reliable information on treatment options, survival rates, and lifestyle adjustments, which can bring a sense of control and reduce anxiety. However, on the flip side, they could stumble upon misleading information that can exacerbate their worries 25 . Suppose the same patient comes across a website claiming an extremely low survival rate without clarifying that it refers to late-stage cases; the patient may misinterpret this as a blanket statement, inducing panic and despair.…”

Section: Introductionmentioning

confidence: 99%

Exploring the determinants influencing suicidal ideation and depression in gastrointestinal cancer patients

Choudhury,

Shahsavar

2023

Sci Rep

Self Cite

View full text Add to dashboard Cite

Studies have shown a heightened prevalence of depression and suicidal ideation among patients with Gastrointestinal Cancer (GIC). GIC patients are at a 1.5- to threefold increased risk of suicide and depression compared to other cancer patients. This study investigates the interplay of internet use, family burden, and emotional support on mental health (depression) and suicidal ideation among patients with GIC. The study involves 202 respondents of which 78 were undergoing GIC treatment during this study. Using structural equation modeling, our findings indicate a substantial negative correlation between mental health and suicidal ideation. Overall, suicidal ideation (median score) was noticeably lower in patient who completed their treatment with noticeable individuals with exceptionally high SI even after completing the treatment. Notably, participants who had completed their treatment demonstrated a significantly stronger correlation between emotional support and mental health compared to those who were still undergoing treatment. Age was found to moderate the mental health-suicidal ideation link significantly. Internet usage for health-related information was also inversely correlated with mental health (directly) and suicidal ideation (indirectly). We noted that the influence of emotional support on mental health was significantly higher among individuals who completed their treatment compared to those who were undergoing their GIC treatment. Family burden emerged as significant negative influences on mental health, while emotional support positively impacted mental health. The findings of this study contribute towards a deeper understanding of suicide risk factors in GIC patients, potentially shaping more effective preventive strategies.

show abstract

Exploring the Role of the Internet, Care Quality and Communication in Shaping Mental Health: Analysis of the Health Information National Trends Survey

Cited by 13 publications

References 65 publications

User Intentions to Use ChatGPT for Self-Diagnosis and Health-Related Purposes: Cross-sectional Survey Study

User Intentions to Use ChatGPT for Self-Diagnosis and Health-Related Purposes: Cross-sectional Survey Study

An e–Mental Health Resource for COVID-19–Associated Stress Reduction: Mixed Methods Study of Reach, Usability, and User Perceptions

Exploring the determinants influencing suicidal ideation and depression in gastrointestinal cancer patients

Contact Info

Product

Resources

About