Self-diagnosis
Prevalence of the internet
### Prevalence of the internet

The [Internet](/wiki/Internet "Internet") and other connected resources have become popular places to start the self\-diagnosis process. The availability of medical information online allows patients to have greater access to medical knowledge.

#### Smartphone applications

There are a multitude of medical and health apps available on both the [Apple App Store](/wiki/App_Store_%28iOS/iPadOS%29 "App Store (iOS/iPadOS)") and [Google Play Store](/wiki/Google_Play "Google Play") that can be used for self\-diagnosing purposes. Approximately 20% of smartphone users have a health\-related application downloaded onto their device.

Experts have criticized the creators of such medical apps as promoting a false sense of credibility in order to increase the number of downloads. For example, these apps will often use widely recognized medical symbols such as the red cross or a [stethoscope](/wiki/Stethoscope "Stethoscope") on their [thumbnails](/wiki/Thumbnail "Thumbnail") and diagnostic pages, as well as emphasize terms such as "[algorithm](/wiki/Algorithm "Algorithm")", "[sensors](/wiki/Sensor "Sensor")", and "computer" in the diagnosis process to convey a sense of scientific objectivity. Lupton and Jutel, in their analysis of 35 self\-diagnosis apps, argue that these techniques portray self\-diagnosis apps as having an augmented authority in determining diagnoses.

In relation to the amount of power that health\-related smartphone apps have in determining a diagnosis, researchers have emphasized the importance of using such apps judiciously. In order to maintain a balance between patient agency and professional medical authority, many self\-diagnosis applications remind users of the incomplete medical certainty of the diagnosis provided and to encourage them to obtain secondary professional medical advice from a doctor or specialist. Additionally, the sources of application diagnosis information can often be difficult to determine or verify. There have been cases where certain health\-related applications made claims to receiving significant contributions of content from prestigious educational institutions to increase downloads, but little information was provided as to the extent and verifiability of such contributions.

#### Use of chatbots

A recent technology that has started to take hold in the realm of self\-diagnosis is the utilization of [chatbot](/wiki/Chatbot "Chatbot")\-based symptom checker (CSC) applications. CSCs were designed to combat the problem of extended wait times to see a doctor and the unavailability of punctual medical advice. Patients have also utilized chatbots to determine severity of their potential diagnosis before going through the process of seeing a doctor and incurring the financial strain that can come with it. Chatbots utilize [artificial intelligence](/wiki/Artificial_intelligence "Artificial intelligence") (AI) in order to assist patients in their medical concerns during all hours of the day. The operational mechanism of CSCs is a text\-to\-text system, where the chatbot asks a series of health\-related questions in order to determine a diagnosis. The effectiveness of chatbots in the process of self\-diagnosis is still highly debated among researchers.

Studies have found that users have varying opinions on the required input for chatbot websites and applications. In some cases, chatbots offer limited space to input multiple symptoms and locations of symptoms for diagnosis determination. Interfaces have presented users with a "pre\-structured symptom selection list" which has forced users to be more general with their responses than they would prefer. Other users have felt that questions asked by self\-diagnosing chatbots require too much detail, leaving them confused or overwhelmed.

People are also using AI chatbots for self\-diagnosis.

#### Social media

Social media has started to take on a particularly important role in the process of self\-diagnosis, especially the diagnosis of [mental health](/wiki/Mental_health "Mental health") disorders. Social media users seeking answers often self\-diagnose after resonating with a particular trait of a disorder that has been mentioned in a social media post. Self\-diagnosis through social media is generally more prevalent in individuals who have [obsessive–compulsive disorder](/wiki/Obsessive%E2%80%93compulsive_disorder "Obsessive–compulsive disorder") (OCD), [anxiety](/wiki/Anxiety_disorder "Anxiety disorder"), [depression](/wiki/Depression_%28mood%29 "Depression (mood)"), or other complex trauma.

Increased access to the ability to self\-diagnose via the Internet can have benefits for patient\-doctor communication. By assessing a patient's self\-diagnosis, a medical professional can see with which specific traits of a disease the patient identified and can work with them to create a potentially more effective diagnosis and treatment.

Self\-diagnosis through social media may have some drawbacks associated with it. Some social media postings can simplify a diagnosis, leading to a spread of [misinformation](/wiki/Misinformation "Misinformation") about the emphasized disease. Some online self\-diagnosis tests state that common, broad symptoms, like anxiety and mood swings, are definite indicators of specific disorders, causing social media users to report such posts for inaccuracy. People who publish health\-related posts on the self\-diagnosis of health issues may not have verified medical credentials even though they have posed their post as providing expert advice. Journalist and author Doreen Dodgen\-Magee considers self\-diagnosis tests to work due to confirmation bias, which was witnessed when there was a statistical increase in the number of teenage girls approaching their doctors with a concern they had [Tourette syndrome](/wiki/Tourette_syndrome "Tourette syndrome") after multiple videos naming broad symptoms as signs of Tourettes went viral on [TikTok](/wiki/TikTok "TikTok").


What are smartphone applications used for in the context of self-diagnosis?