Self-Testing for Dementia: A Phenomenological Analysis of Fear

Following the growing economic relevance of mobile health (mHealth) and the increasing global prevalence of dementia, self-testing apps for dementia and mild neurocognitive disorder (MCD) have been developed and advertised. The apps' promise of a quick and easy tool has been criticized in the literature from a variety of angles, but as we argue in this article, the celebratory characterization of self-testing also stands in disbalance to the various kinds of fears that may be connected to taking the test. By drawing on Sara Ahmed's phenomenological theory on emotions and by referring to illustrative experiences from two users with a particular dementia self-testing app, we explore four dimensions of fear derived from phenomenology: performative, ontological, embodied, and temporal dimensions. We argue that fear (1) motivates one to take the self-test and to try to take control over one's health; (2) is shaped by and shapes the ways in which we make sense of ourselves and others as cognitively deficient; (3) constructs and is constructed by our differently embodied presence in the world; and that (4) testing makes a fearful future self as cognitively deficient more tangible. In outlining these different dimensions of fear, this article expands the understanding of the meaning of experiencing self-testing in comparison to the mostly quantitative literature on this topic.

GPs' attitudes towards and experiences of using the Dermabuddy health app for the management of patients with dermatological conditions: a descriptive cross-sectional study

BACKGROUND

Dermatological presentations are common in primary care. The digital health space is growing in investment, revenue, and in usership numbers. Doctors utilise mobile health apps for referencing, communicating, and for clinical decision making. Dermabuddy is a secure mobile health app by which information and expertise around skin problems can be shared among a group of medical professionals with the aim of finding the best treatment and management plan.

AIM

To assess the utility of the Dermabuddy health app for GPs and associated trainees in the Republic of Ireland.

DESIGN & SETTING

This is a descriptive cross-sectional study, which involved a survey link distributed by email to GPs with Irish Medical Council membership.

METHOD

GPs were surveyed on their experiences of using the dermatology mobile application, Dermabuddy.

RESULTS

In total, 203 members took this questionnaire (13.5% response rate). Ninety-six per cent who responded to the statement, 'The app was easy to use', agreed it was 'easy' or 'very easy'. Eighty-seven per cent of those who responded to the statement, 'I would use this app again', agreed they 'definitely would'. Fifty-eight per cent of those who responded to the statement, 'The app is useful for my healthcare practice', gave it a five-star rating. The content of 36 comments included advice for improvement and positive feedback.

CONCLUSION

The Dermabuddy app was well received by participants in this study. Across all sections of the questionnaire looking at aspects of the app, including ease of use, interface and satisfaction, and usefulness, there was a positive response. Mobile health apps, such as Dermabuddy, may provide alternative solutions to meet the rising challenge of managing patients with dermatological conditions in primary care.

Healthcare workers' perceptions about the use of mobile health technologies in public health facilities in Lagos, Nigeria

Background

Mobile health has enormous potential in healthcare due to the increasing use of mobile phones in low- and middle-income countries; its effective deployment, uptake, and utilization may result in improved health outcomes, including a reduction in neonatal deaths. However, there is a suboptimal uptake of mobile health technologies among healthcare workers in low-resource settings like Nigeria, which are often context-specific.

Objective

To investigate healthcare workers' perceptions of mobile health technologies in public health facilities in Lagos, Nigeria.

Method

A qualitative study was conducted, and data were collected through six focus group discussions with 26 healthcare workers (doctors, nurses, and community health extension workers) from three public health facilities in Lagos, Nigeria. The collected data were analyzed using a thematic approach, where themes and subthemes were created.

Results

Although the participants acknowledged that mobile health enhances patient-provider communication and saves time, they identified altering of healthcare workers' routine practices, information overload, power and network failure, skepticism, lack of trust, and concerns over diagnostic accuracy as potential barriers to its uptake.

Conclusion

Addressing healthcare workers' perceptions of mobile health technologies may enhance the deployment and uptake of such solutions in Nigeria and similar low-resource settings. Developers and implementers of such can use them to create new or enhance existing mobile health solutions to better meet the needs and requirements of healthcare workers in low- to middle-income health settings, such as Lagos, Nigeria.

Assessment of a Digital Symptom Checker Tool's Accuracy in Suggesting Reproductive Health Conditions: Clinical Vignettes Study

BACKGROUND

Reproductive health conditions such as endometriosis, uterine fibroids, and polycystic ovary syndrome (PCOS) affect a large proportion of women and people who menstruate worldwide. Prevalence estimates for these conditions range from 5% to 40% of women of reproductive age. Long diagnostic delays, up to 12 years, are common and contribute to health complications and increased health care costs. Symptom checker apps provide users with information and tools to better understand their symptoms and thus have the potential to reduce the time to diagnosis for reproductive health conditions.

OBJECTIVE

This study aimed to evaluate the agreement between clinicians and 3 symptom checkers (developed by Flo Health UK Limited) in assessing symptoms of endometriosis, uterine fibroids, and PCOS using vignettes. We also aimed to present a robust example of vignette case creation, review, and classification in the context of predeployment testing and validation of digital health symptom checker tools.

METHODS

Independent general practitioners were recruited to create clinical case vignettes of simulated users for the purpose of testing each condition symptom checker; vignettes created for each condition contained a mixture of condition-positive and condition-negative outcomes. A second panel of general practitioners then reviewed, approved, and modified (if necessary) each vignette. A third group of general practitioners reviewed each vignette case and designated a final classification. Vignettes were then entered into the symptom checkers by a fourth, different group of general practitioners. The outcomes of each symptom checker were then compared with the final classification of each vignette to produce accuracy metrics including percent agreement, sensitivity, specificity, positive predictive value, and negative predictive value.

RESULTS

A total of 24 cases were created per condition. Overall, exact matches between the vignette general practitioner classification and the symptom checker outcome were 83% (n=20) for endometriosis, 83% (n=20) for uterine fibroids, and 88% (n=21) for PCOS. For each symptom checker, sensitivity was reported as 81.8% for endometriosis, 84.6% for uterine fibroids, and 100% for PCOS; specificity was reported as 84.6% for endometriosis, 81.8% for uterine fibroids, and 75% for PCOS; positive predictive value was reported as 81.8% for endometriosis, 84.6% for uterine fibroids, 80% for PCOS; and negative predictive value was reported as 84.6% for endometriosis, 81.8% for uterine fibroids, and 100% for PCOS.

CONCLUSIONS

The single-condition symptom checkers have high levels of agreement with general practitioner classification for endometriosis, uterine fibroids, and PCOS. Given long delays in diagnosis for many reproductive health conditions, which lead to increased medical costs and potential health complications for individuals and health care providers, innovative health apps and symptom checkers hold the potential to improve care pathways.

Triage and Diagnostic Accuracy of Online Symptom Checkers: Systematic Review

BACKGROUND

In the context of a deepening global shortage of health workers and, in particular, the COVID-19 pandemic, there is growing international interest in, and use of, online symptom checkers (OSCs). However, the evidence surrounding the triage and diagnostic accuracy of these tools remains inconclusive.

OBJECTIVE

This systematic review aimed to summarize the existing peer-reviewed literature evaluating the triage accuracy (directing users to appropriate services based on their presenting symptoms) and diagnostic accuracy of OSCs aimed at lay users for general health concerns.

METHODS

Searches were conducted in MEDLINE, Embase, CINAHL, Health Management Information Consortium (HMIC), and Web of Science, as well as the citations of the studies selected for full-text screening. We included peer-reviewed studies published in English between January 1, 2010, and February 16, 2022, with a controlled and quantitative assessment of either or both triage and diagnostic accuracy of OSCs directed at lay users. We excluded tools supporting health care professionals, as well as disease- or specialty-specific OSCs. Screening and data extraction were carried out independently by 2 reviewers for each study. We performed a descriptive narrative synthesis.

RESULTS

A total of 21,296 studies were identified, of which 14 (0.07%) were included. The included studies used clinical vignettes, medical records, or direct input by patients. Of the 14 studies, 6 (43%) reported on triage and diagnostic accuracy, 7 (50%) focused on triage accuracy, and 1 (7%) focused on diagnostic accuracy. These outcomes were assessed based on the diagnostic and triage recommendations attached to the vignette in the case of vignette studies or on those provided by nurses or general practitioners, including through face-to-face and telephone consultations. Both diagnostic accuracy and triage accuracy varied greatly among OSCs. Overall diagnostic accuracy was deemed to be low and was almost always lower than that of the comparator. Similarly, most of the studies (9/13, 69 %) showed suboptimal triage accuracy overall, with a few exceptions (4/13, 31%). The main variables affecting the levels of diagnostic and triage accuracy were the severity and urgency of the condition, the use of artificial intelligence algorithms, and demographic questions. However, the impact of each variable differed across tools and studies, making it difficult to draw any solid conclusions. All included studies had at least one area with unclear risk of bias according to the revised Quality Assessment of Diagnostic Accuracy Studies-2 tool.

CONCLUSIONS

Although OSCs have potential to provide accessible and accurate health advice and triage recommendations to users, more research is needed to validate their triage and diagnostic accuracy before widescale adoption in community and health care settings. Future studies should aim to use a common methodology and agreed standard for evaluation to facilitate objective benchmarking and validation.

TRIAL REGISTRATION

PROSPERO CRD42020215210; https://tinyurl.com/3949zw83.

Ethical, legal, and social aspects of symptom checker applications: a scoping review

Symptom Checker Applications (SCA) are mobile applications often designed for the end-user to assist with symptom assessment and self-triage. SCA are meant to provide the user with easily accessible information about their own health conditions. However, SCA raise questions regarding ethical, legal, and social aspects (ELSA), for example, regarding fair access to this new technology. The aim of this scoping review is to identify the ELSA of SCA in the scientific literature. A scoping review was conducted to identify the ELSA of SCA. Ten databases (e.g., Web of Science and PubMed) were used. Studies on SCA that address ELSA, written in English or German, were included in the review. The ELSA of SCA were extracted and synthesized using qualitative content analysis. A total of 25,061 references were identified, of which 39 were included in the analysis. The identified aspects were allotted to three main categories: (1) Technology; (2) Individual Level; and (3) Healthcare system. The results show that there are controversial debates in the literature on the ethical and social challenges of SCA usage. Furthermore, the debates are characterised by a lack of a specific legal perspective and empirical data. The review provides an overview on the spectrum of ELSA regarding SCA. It offers guidance to stakeholders in the healthcare system, for example, patients, healthcare professionals, and insurance providers and could be used in future empirical research to investigate the perspectives of those affected, such as users.

Decision-Making in the Pediatric Emergency Department-A Survey of Guidance Strategies among Residents

(1) Introduction: Working in an emergency department requires fast and straightforward decisions. Therefore, decision guidance represents an essential tool for successful patient-centered care. Beyond the residents' own knowledge and experience, printed books have been the primary source of information in the past. The aim of this study was to discover which strategies current residents use the most and to identify alternative quick reference strategies in the digital age. (2) Materials and Methods: This study analyzed the responses of a short questionnaire directed at 41 residents in a single pediatric emergency department (32 pediatric and 9 pediatric surgery residents) over a period of one month. (3) Results: Thirty-three (80.5%) residents answered the entire questionnaire. Strikingly, responses indicated that printed books are still pivotal in guiding decision-making. In addition, the acquisition of information via computers or smartphones plays an increasing role. However, the opinion and council of the attending physician is still of great value to the residents and is not to be underestimated. Overall, most of the residents would prefer to have access to a specially designed smartphone application. (4) Conclusions: Certainty and validity are essential in decision-making in a pediatric emergency department. Although printed books and attending physicians are still considered as reliable sources of information, internet-based information plays an increasing role. In order to provide the best up-to-date and most recent information, a validated and consistently updated smartphone application could be a useful option.

User Perception of New E-Health Challenges: Implications for the Care Process

Establishing new models of health care and new forms of professional health-patient communication are lines of development in the field of health care. The onset of the COVID-19 pandemic has accelerated the evolution of information systems and communication platforms to guarantee continuity of care and compliance with social distancing measures. Our objective in this article was, firstly, to know the expectations of patients treated in the healthcare processes "cervical cancer" and "pregnancy, childbirth and puerperium" regarding online access to their clinical history and follow-up in the care process. Secondly, we analyzed times involved in the cervical cancer process to find points of improvement in waiting times when digital tools were used for communication with the patient. A descriptive cross-sectional study was carried out on 120 women included in any of the aforementioned processes using a hetero-administered questionnaire. The analysis of times was carried out using the Business Intelligence tool Biwer Analytics®. Patients showed interest in knowing their results before the appointment with the doctor and would avoid appointments with their doctor if the right conditions were met. Most recognized that this action would relieve their restlessness and anxiety. They were highly interested in receiving recommendations to improve their health status. It was estimated that there was room for improvement in the times involved in the care process, which could be shortened by 34.48 days if communication of results were through digital information access technologies. This would favor the optimization of time, resources and user perception.

A Review of the Quality and Impact of Mobile Health Apps

Mobile health applications (apps) have transformed the possibilities for health promotion and disease self-management; however, their promise is not fully realized owing to their reliance on commercial ecosystems for development and distribution. This review provides an overview of the types of mobile health apps and describes key stakeholders in terms of how apps are used, developed, and regulated. I outline key challenges facing consumers, public health professionals, and policy makers in evaluating the quality of health apps and summarize what is known about the impact of apps on health outcomes and health equity. I suggest that factors within the wider mobile ecosystem largely define the impact of health apps and, most notably, practices around the collection and commercialization of user data. Finally, I suggest that upstream public health strategies, grounded in an understanding of corporate influences on health, are necessary to promote healthy digital environments in which mobile health app innovation can flourish. Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

An observational study of a cross platform risk assessment mobile application in a forensic inpatient setting

Consumer-focused healthcare mobile applications have seen widespread adoption in recent years. Enterprise mobile applications in hospital settings have been slower to gain traction. In this study we examine the Dynamic Appraisal of Situational Aggression: Inpatient version (DASA), a short-term risk assessment tool which is well validated and widely used in the prediction of violent incidents, within an inpatient forensic setting. The application was piloted over a period of three months, collecting 847 total DASA scores on 21 different patients. Time stamping allowed for accurate correlation between risk assessment scoring and the violent risk incidents. The internal validity of the app was measured using Cronbach's alpha and was calculated at 0.798 indicating good internal validity. Using violent incidents as the dependent factor and the total DASA score as the independent factor, predictive validity of the app was calculated at 0.85, p = 0.007. The use of this application in a forensic setting was successful with good internal and predictive validity. A major benefit of this form of data collection was the electronic time stamping so that the correlation between risk estimation and events could be more closely correlated. Deployment of such an application in a general hospital setting would bring its own challenges but would be useful in other types of risk assessment and screening tools.

Screening accuracy of a 14-day smartphone ambulatory assessment of depression symptoms and mood dynamics in a general population sample: Comparison with the PHQ-9 depression screening

Introduction

Major depression affects over 300 million people worldwide, but cases are often detected late or remain undetected. This increases the risk of symptom deterioration and chronification. Consequently, there is a high demand for low threshold but clinically sound approaches to depression detection. Recent studies show a great willingness among users of mobile health apps to assess daily depression symptoms. In this pilot study, we present a provisional validation of the depression screening app Moodpath. The app offers a 14-day ambulatory assessment (AA) of depression symptoms based on the ICD-10 criteria as well as ecologically momentary mood ratings that allow the study of short-term mood dynamics.

Materials and methods

N = 113 Moodpath users were selected through consecutive sampling and filled out the Patient Health Questionnaire (PHQ-9) after completing 14 days of AA with 3 question blocks (morning, midday, and evening) per day. The psychometric properties (sensitivity, specificity, accuracy) of the ambulatory Moodpath screening were assessed based on the retrospective PHQ-9 screening result. In addition, several indicators of mood dynamics (e.g. average, inertia, instability), were calculated and investigated for their individual and incremental predictive value using regression models.

Results

We found a strong linear relationship between the PHQ-9 score and the AA Moodpath depression score (r = .76, p < .001). The app-based screening demonstrated a high sensitivity (.879) and acceptable specificity (.745). Different indicators of mood dynamics covered substantial amounts of PHQ-9 variance, depending on the number of days with mood data that were included in the analyses.

Discussion

AA and PHQ-9 shared a large proportion of variance but may not measure exactly the same construct. This may be due to the differences in the underlying diagnostic systems or due to differences in momentary and retrospective assessments. Further validation through structured clinical interviews is indicated. The results suggest that ambulatory assessed mood indicators are a promising addition to multimodal depression screening tools. Improving app-based AA screenings requires adapted screening algorithms and corresponding methods for the analysis of dynamic processes over time.

A Comparison of Artificial Intelligence and Human Doctors for the Purpose of Triage and Diagnosis

AI virtual assistants have significant potential to alleviate the pressure on overly burdened healthcare systems by enabling patients to self-assess their symptoms and to seek further care when appropriate. For these systems to make a meaningful contribution to healthcare globally, they must be trusted by patients and healthcare professionals alike, and service the needs of patients in diverse regions and segments of the population. We developed an AI virtual assistant which provides patients with triage and diagnostic information. Crucially, the system is based on a generative model, which allows for relatively straightforward re-parameterization to reflect local disease and risk factor burden in diverse regions and population segments. This is an appealing property, particularly when considering the potential of AI systems to improve the provision of healthcare on a global scale in many regions and for both developing and developed countries. We performed a prospective validation study of the accuracy and safety of the AI system and human doctors. Importantly, we assessed the accuracy and safety of both the AI and human doctors independently against identical clinical cases and, unlike previous studies, also accounted for the information gathering process of both agents. Overall, we found that the AI system is able to provide patients with triage and diagnostic information with a level of clinical accuracy and safety comparable to that of human doctors. Through this approach and study, we hope to start building trust in AI-powered systems by directly comparing their performance to human doctors, who do not always agree with each other on the cause of patients’ symptoms or the most appropriate triage recommendation.

Limited evidence of benefits of patient operated intelligent primary care triage tools: findings of a literature review

Introduction

There is consistent evidence that the workload in general practices is substantially increasing. The digitalisation of healthcare including the use of artificial intelligence has been suggested as a solution to this problem. We wanted to explore the features of intelligent online triage tools in primary care by conducting a literature review.

Method

A systematic literature search strategy was formulated and conducted in the PubMed database and the Cochrane Library. Articles were selected according to inclusion/exclusion criteria. Results and data were systematically extracted and thematically analysed. 17 articles of that reported large multimethod studies or smaller diagnostic accuracy tests on clinical vignettes were included. Reviews and expert opinions were also considered.

Results

There was limited evidence on the actual effects and performance of triage tools in primary care. Several aspects can guide further development: concepts of system design, system implementation and diagnostic performance. The most important findings were: a need to formulate evaluation guidelines and regulations; their assumed potential has not yet been met; a risk of increased or redistribution of workloads and the available symptom checker systems seem overly risk averse and should be tested in real-life settings.

Conclusion

This review identified several features associated with the design and implementation of intelligent online triage tools in a primary care context, although most of the investigated systems seemed underdeveloped and offered limited benefits. Current online triage systems should not be used by individuals who have reasonable access to traditional healthcare. Systems used should be strictly evaluated and regulated like other medical products.

The quality of diagnosis and triage advice provided by free online symptom checkers and apps in Australia

OBJECTIVES

To investigate the quality of diagnostic and triage advice provided by free website and mobile application symptom checkers (SCs) accessible in Australia.

DESIGN

36 SCs providing medical diagnosis or triage advice were tested with 48 medical condition vignettes (1170 diagnosis vignette tests, 688 triage vignette tests).

MAIN OUTCOME MEASURES

Correct diagnosis advice (provided in first, the top three or top ten diagnosis results); correct triage advice (appropriate triage category recommended).

RESULTS

The 27 diagnostic SCs listed the correct diagnosis first in 421 of 1170 SC vignette tests (36%; 95% CI, 31-42%), among the top three results in 606 tests (52%; 95% CI, 47-59%), and among the top ten results in 681 tests (58%; 95% CI, 53-65%). SCs using artificial intelligence algorithms listed the correct diagnosis first in 46% of tests (95% CI, 40-57%), compared with 32% (95% CI, 26-38%) for other SCs. The mean rate of first correct results for individual SCs ranged between 12% and 61%. The 19 triage SCs provided correct advice for 338 of 688 vignette tests (49%; 95% CI, 44-54%). Appropriate triage advice was more frequent for emergency care (63%; 95% CI, 52-71%) and urgent care vignette tests (56%; 95% CI, 52-75%) than for non-urgent care (30%; 95% CI, 11-39%) and self-care tests (40%; 95% CI, 26-49%).

CONCLUSION

The quality of diagnostic advice varied between SCs, and triage advice was generally risk-averse, often recommending more urgent care than appropriate.

Patient Perspectives on the Usefulness of an Artificial Intelligence-Assisted Symptom Checker: Cross-Sectional Survey Study

Background

Patients are increasingly seeking Web-based symptom checkers to obtain diagnoses. However, little is known about the characteristics of the patients who use these resources, their rationale for use, and whether they find them accurate and useful.

Objective

The study aimed to examine patients’ experiences using an artificial intelligence (AI)–assisted online symptom checker.

Methods

An online survey was administered between March 2, 2018, through March 15, 2018, to US users of the Isabel Symptom Checker within 6 months of their use. User characteristics, experiences of symptom checker use, experiences discussing results with physicians, and prior personal history of experiencing a diagnostic error were collected.

Results

A total of 329 usable responses was obtained. The mean respondent age was 48.0 (SD 16.7) years; most were women (230/304, 75.7%) and white (271/304, 89.1%). Patients most commonly used the symptom checker to better understand the causes of their symptoms (232/304, 76.3%), followed by for deciding whether to seek care (101/304, 33.2%) or where (eg, primary or urgent care: 63/304, 20.7%), obtaining medical advice without going to a doctor (48/304, 15.8%), and understanding their diagnoses better (39/304, 12.8%). Most patients reported receiving useful information for their health problems (274/304, 90.1%), with half reporting positive health effects (154/302, 51.0%). Most patients perceived it to be useful as a diagnostic tool (253/301, 84.1%), as a tool providing insights leading them closer to correct diagnoses (231/303, 76.2%), and reported they would use it again (278/304, 91.4%). Patients who discussed findings with their physicians (103/213, 48.4%) more often felt physicians were interested (42/103, 40.8%) than not interested in learning about the tool’s results (24/103, 23.3%) and more often felt physicians were open (62/103, 60.2%) than not open (21/103, 20.4%) to discussing the results. Compared with patients who had not previously experienced diagnostic errors (missed or delayed diagnoses: 123/304, 40.5%), patients who had previously experienced diagnostic errors (181/304, 59.5%) were more likely to use the symptom checker to determine where they should seek care (15/123, 12.2% vs 48/181, 26.5%; P=.002), but they less often felt that physicians were interested in discussing the tool’s results (20/34, 59% vs 22/69, 32%; P=.04).

Conclusions

Despite ongoing concerns about symptom checker accuracy, a large patient-user group perceived an AI-assisted symptom checker as useful for diagnosis. Formal validation studies evaluating symptom checker accuracy and effectiveness in real-world practice could provide additional useful information about their benefit.

Evaluating a mobile application for improving clinical laboratory test ordering and diagnosis

Objective

Mobile applications for improving diagnostic decision making often lack clinical evaluation. We evaluated if a mobile application improves generalist physicians' appropriate laboratory test ordering and diagnosis decisions and assessed if physicians perceive it as useful for learning.

Methods

In an experimental, vignette study, physicians diagnosed 8 patient vignettes with normal prothrombin times (PT) and abnormal partial thromboplastin times (PTT). Physicians made test ordering and diagnosis decisions for 4 vignettes using each resource: a mobile app, PTT Advisor, developed by the Centers for Disease Control and Prevention (CDC)'s Clinical Laboratory Integration into Healthcare Collaborative (CLIHC); and usual clinical decision support. Then, physicians answered questions regarding their perceptions of the app's usefulness for diagnostic decision making and learning using a modified Kirkpatrick Training Evaluation Framework.

Results

Data from 368 vignettes solved by 46 physicians at 7 US health care institutions show advantages for using PTT Advisor over usual clinical decision support on test ordering and diagnostic decision accuracy (82.6 vs 70.2% correct; P < .001), confidence in decisions (7.5 vs 6.3 out of 10; P < .001), and vignette completion time (3:02 vs 3:53 min.; P = .06). Physicians reported positive perceptions of the app's potential for improved clinical decision making, and recommended it be used to address broader diagnostic challenges.

Conclusions

A mobile app, PTT Advisor, may contribute to better test ordering and diagnosis, serve as a learning tool for diagnostic evaluation of certain clinical disorders, and improve patient outcomes. Similar methods could be useful for evaluating apps aimed at improving testing and diagnosis for other conditions.

The Use of Artificially Intelligent Self-Diagnosing Digital Platforms by the General Public: Scoping Review

Background

Self-diagnosis is the process of diagnosing or identifying a medical condition in oneself. Artificially intelligent digital platforms for self-diagnosis are becoming widely available and are used by the general public; however, little is known about the body of knowledge surrounding this technology.

Objective

The objectives of this scoping review were to (1) systematically map the extent and nature of the literature and topic areas pertaining to digital platforms that use computerized algorithms to provide users with a list of potential diagnoses and (2) identify key knowledge gaps.

Methods

The following databases were searched: PubMed (Medline), Scopus, Association for Computing Machinery Digital Library, Institute of Electrical and Electronics Engineers, Google Scholar, Open Grey, and ProQuest Dissertations and Theses. The search strategy was developed and refined with the assistance of a librarian and consisted of 3 main concepts: (1) self-diagnosis; (2) digital platforms; and (3) public or patients. The search generated 2536 articles from which 217 were duplicates. Following the Tricco et al 2018 checklist, 2 researchers screened the titles and abstracts (n=2316) and full texts (n=104), independently. A total of 19 articles were included for review, and data were retrieved following a data-charting form that was pretested by the research team.

Results

The included articles were mainly conducted in the United States (n=10) or the United Kingdom (n=4). Among the articles, topic areas included accuracy or correspondence with a doctor’s diagnosis (n=6), commentaries (n=2), regulation (n=3), sociological (n=2), user experience (n=2), theoretical (n=1), privacy and security (n=1), ethical (n=1), and design (n=1). Individuals who do not have access to health care and perceive to have a stigmatizing condition are more likely to use this technology. The accuracy of this technology varied substantially based on the disease examined and platform used. Women and those with higher education were more likely to choose the right diagnosis out of the potential list of diagnoses. Regulation of this technology is lacking in most parts of the world; however, they are currently under development.

Conclusions

There are prominent research gaps in the literature surrounding the use of artificially intelligent self-diagnosing digital platforms. Given the variety of digital platforms and the wide array of diseases they cover, measuring accuracy is cumbersome. More research is needed to understand the user experience and inform regulations.

A Smartphone Application for Automated Decision Support in Cognitive Task Based Evaluation of Central Nervous System Motor Disorders

BACKGROUND AND OBJECTIVE

New technology enables constant boost to the powers of mobile devices, which in the previous years have transformed from simple mobile phones to smart phones. Computational powers of these electronics enable actions that previously were possible only for computers. By the use of special applications, we may benefit from sensors and multimedia capabilities of operating systems. Therefore, a new era for devoted implementations opens, in which a smart application can take a role of computing system to estimate the symptoms of diseases by evaluating signals coming from a human body.

METHODS

We propose a model of an application implemented for mobile android systems, which can be used for examination of central nervous system motor disorders occurring in patients suffering from Huntington (HD), Alzheimer, or Parkinson diseases. In particular, the model tracks tremors (involuntary movements), and cognitive (memory loss or dementia) impairments using touch and visual stimulus modalities. The proposed model interprets the symptoms from human bodies that indicate one of the diseases of the nervous system. Pre-processing of collected data for feature extraction is executed on a mobile device by using core functionality and methods provided in android's application programming interface. The information is evaluated by a back-propagation neural network classifier and the result is presented to the end user. The system is able to contact medical supervision and provide an assistance from the clinic.

RESULTS

The system uses a collected dataset of 1928 records, taken from 11 HD patients and 11 healthy persons in Lithuania, to gather statistics about examinations and presents the results as medical evaluation with prediction on the state of health. The accuracy of recognition of early, prodromal symptoms for central nervous system motor disorders is 86.4% (F-measure 0.859). The app (available on Google Play) is easy to use and is efficient tool for decision support in medical examinations.

CONCLUSIONS

The use of intelligent apps which can help to evaluate neurodegenerative disorders is an important enhancement to medical diagnosis. The developed smartphone app supports the doctor with additional results that are easy to compare with other examinations. This kind of examination is a nice change from classic stereotypes, especially for younger age patients, who are used to various aspects of information technology.

Beyond Dr. Google: the evidence on consumer-facing digital tools for diagnosis

Over a third of adults go online to diagnose their health condition. Direct-to-consumer (DTC), interactive, diagnostic apps with information personalization capabilities beyond those of static search engines are rapidly proliferating. While these apps promise faster, more convenient and more accurate information to improve diagnosis, little is known about the state of the evidence on their performance or the methods used to evaluate them. We conducted a scoping review of the peer-reviewed and gray literature for the period January 1, 2014–June 30, 2017. We found that the largest category of evaluations involved symptom checkers that applied algorithms to user-answered questions, followed by sensor-driven apps that applied algorithms to smartphone photos, with a handful of evaluations examining crowdsourcing. The most common clinical areas evaluated were dermatology and general diagnostic and triage advice for a range of conditions. Evaluations were highly variable in methodology and conclusions, with about half describing app characteristics and half examining actual performance. Apps were found to vary widely in functionality, accuracy, safety and effectiveness, although the usefulness of this evidence was limited by a frequent failure to provide results by named individual app. Overall, the current evidence base on DTC, interactive diagnostic apps is sparse in scope, uneven in the information provided and inconclusive with respect to safety and effectiveness, with no studies of clinical risks and benefits involving real-world consumer use. Given that DTC diagnostic apps are rapidly evolving, rigorous and standardized evaluations are essential to inform decisions by clinicians, patients, policymakers and other stakeholders.

From second to hundredth opinion in medicine: A global consultation platform for physicians

Serious medical diagnostic errors lead to adverse patient outcomes and increased healthcare costs. The use of virtual online consultation platforms may lead to better-informed physicians and reduce the incidence of diagnostic errors. Our aim was to assess the usage characteristics of an online, physician-to-physician, no-cost, medical consultation platform, Medscape Consult, from November 2015 through October 2017. Physicians creating original content were noted as “presenters” and those following up as “responders”. During the study period, 37,706 physician users generated a combined 117,346 presentations and responses. The physicians had an average age of 56 years and were from 171 countries on every continent. Over 90% of all presentations received responses with the median time to first response of 1.5 h. Overall, computer- and device-based medical consultation has the capacity to rapidly reach a global medical community and may play a role in the reduction of diagnostic errors.

Leaving patients to their own devices? Smart technology, safety and therapeutic relationships

BACKGROUND

This debate article explores how smart technologies may create a double-edged sword for patient safety and effective therapeutic relationships. Increasing utilization of health monitoring devices by patients will likely become an important aspect of self-care and preventive medicine. It may also help to enhance accurate symptom reports, diagnoses, and prompt referral to specialist care where appropriate. However, the development, marketing, and use of such technology raise significant ethical implications for therapeutic relationships and patient safety.

MAIN TEXT

Drawing on lessons learned from other direct-to-consumer health products such as genetic testing, this article explores how smart technology can also pose regulatory challenges and encourage overutilization of healthcare services. In order for smart technology to promote safer care and effective therapeutic encounters, the technology and its utilization must be safe.

CONCLUSION

This article argues for unified regulatory guidelines and better education for both healthcare providers and patients regarding the benefits and risks of these devices.

A health app developer's guide to law and policy: a multi-sector policy analysis

Background

Apps targeted at health and wellbeing sit in a rapidly growing industry associated with widespread optimism about their potential to deliver accessible and cost-effective healthcare. App developers might not be aware of all the regulatory requirements and best practice principles are emergent. Health apps are regulated in order to minimise their potential for harm due to, for example, loss of personal health privacy, financial costs, and health harms from delayed or unnecessary diagnosis, monitoring and treatment. We aimed to produce a comprehensive guide to assist app developers in producing health apps that are legally compliant and in keeping with high professional standards of user protection.

Methods

We conducted a case study analysis of the Australian and related international policy environment for mental health apps to identify relevant sectors, policy actors, and policy solutions.

Results

We identified 29 policies produced by governments and non-government organisations that provide oversight of health apps. In consultation with stakeholders, we developed an interactive tool targeted at app developers, summarising key features of the policy environment and highlighting legislative, industry and professional standards around seven relevant domains: privacy, security, content, promotion and advertising, consumer finances, medical device efficacy and safety, and professional ethics. We annotated this developer guidance tool with information about: the relevance of each domain; existing legislative and non-legislative guidance; critiques of existing policy; recommendations for developers; and suggestions for other key stakeholders.

Conclusions

We anticipate that mental health apps developed in accordance with this tool will be more likely to conform to regulatory requirements, protect consumer privacy, protect consumer finances, and deliver health benefit; and less likely to attract regulatory penalties, offend consumers and communities, mislead consumers, or deliver health harms. We encourage government, industry and consumer organisations to use and publicise the tool.

Electronic supplementary material

The online version of this article (10.1186/s12911-017-0535-0) contains supplementary material, which is available to authorized users.

Patient portals and health apps: Pitfalls, promises, and what one might learn from the other

Widespread use of health information technology (IT) could potentially increase patients' access to their health information and facilitate future goals of advancing patient-centered care. Despite having increased access to their health data, patients do not always understand this information or its implications, and digital health data can be difficult to navigate when displayed in a small-format, complex interface. In this paper, we discuss two forms of patient-facing health IT tools-patient portals and applications (apps)-and highlight how, despite several limitations of each, combining high-yield features of mobile health (mHealth) apps with portals could increase patient engagement and self-management and be more effective than either of them alone. Patient portal adoption is variable, and due to design and interface limitations and health literacy issues, many people find the portal difficult to use. Conversely, apps have experienced rapid adoption and traditionally have more consumer-friendly features with easy log-in access, real-time tracking, and simplified data display. These features make the applications more intuitive and easy-to-use than patient portals. While apps have their own limitations and might serve different purposes, patient portals could adopt some high-yield features and functions of apps that lead to engagement success with patients. We thus suggest that to improve user experience with future portals, developers could look towards mHealth apps in design, function, and user interface. Adding new features to portals may improve their use and empower patients to track their overall health and disease states. Nevertheless, both these health IT tools should be subjected to rigorous evaluation to ensure they meet their potential in improving patient outcomes.

New Kinds of (Ab)normal?: Public Pedagogies, Affect, and Youth Mental Health in the Digital Age

Academic, policy, and public concerns are intensifying around how to respond to increasing mental health problems amongst young people in OECD countries such as the UK and Australia. In this paper we make the case that public knowledge about mental health promotion, help-seeking, support and recovery can be understood as an enactment of public pedagogy—as knowledge practices and processes that are produced within and beyond formal spaces of learning. We explore the question of how new pedagogic modes of address are produced through digital technologies—social media, gamified therapies, e-mental health literacy, wearable technology—as they invite particular ways of knowing embodied distress as “mental illness or ill health.” The rapid growth of formal and informal pedagogical sites for learning about youth mental health raises questions about the affective arrangements that produce new kinds of (ab)normal in the digital era. Through a posthumanist perspective that connects critical mental health studies and public pedagogy, this paper offers an original contribution that theorises pedagogic sites within the cultural formation of public-personal knowledge about mental (ill) health.

Challenges in Assessing Mobile Health App Quality: A Systematic Review of Prevalent and Innovative Methods

CONTEXT

Mobile apps are poised to become a major source of health guidance; however, concerns about their quality and safety remain. Governments, clinicians, and health researchers are struggling to determine how to adequately evaluate the content and function of mobile health apps to guide consumers toward apps that will effectively and safely support their health. Researchers are both adapting existing research methods, such as those for systematic reviews, and exploring novel methods toward this aim. The purpose of this systematic review was to describe prevalent and emerging methods for searching, data extraction, and analysis in the context of mobile health apps and commercial app stores.

EVIDENCE ACQUISITION

A systematic search was conducted on April 6, 2016, according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, for published studies that evaluated health-related apps targeted at consumers in a commercial app store, and a descriptive content analysis of their methods was performed.

EVIDENCE SYNTHESIS

Although the majority of studies self-identified as "reviews" or "systematic reviews," their claims to have performed an exhaustive, replicable, and systematic search and data extraction are unsupported, given the nature of commercial app stores' search engines and personalized app content. Currently, studies of health-related app content are largely descriptive, and most use surrogate and one-dimensional outcome measures for app content quality.

CONCLUSIONS

This field is rapidly developing, and innovative methods for systematic searches, multidimensional quality assessment, and contextualizing content assessment are emerging. Areas for future methodologic development are highlighted, including expanding definitions of app "content" and assessing risk of bias.

Mobile phone exposure influences some erythrocytes parameters in vitro. A novel source of preanalytical variability?

BACKGROUND

The effect of radiofrequency exposure on human health and health care equipment is a matter of ongoing debate. This study was planned to investigate the influence of radiofrequency (RF) waves emitted by a commercial mobile phone on red blood cells (RBC) in vitro.

METHODS

The study population consisted of 16 ostensibly healthy volunteers. Two whole blood specimens were collected from each volunteer. One sample was placed in a plastic rack, 1 cm distant from the chassis of a commercial mobile phone which was activated by a remote phone call lasting 30 min. The other blood sample was placed in another plastic rack, but was kept distant from any type of RF source. The main RBC parameters including RBC count, hematocrit (Ht), hemoglobin, mean corpuscular platelet volume (MPV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC) and RBC distribution width (RDW-CV) were assessed with an Advia 2120.

RESULTS

The exposure of whole blood to the mobile phone call significantly increased Ht, hemoglobin, MCV and MCH, whereas the RBC count, MCHC and RDW-CV remained unchanged. A significant correlation was observed between variation of Ht and those of hemoglobin (p=0.008), MCV (p=0.009) or MCH (p=0.037), as well as between hemoglobin and MCV (p=0.048). Increased values were found in 13/16 (81%) samples for both Ht and hemoglobin, 14/16 (88%) samples for MCH and 16/16 (100%) samples for MCV.

CONCLUSIONS

These results suggest that close mobile phone exposure may be an unappreciated and possibly underestimated cause of preanalytical bias in RBC testing.

'It's like having a physician in your pocket!' A critical analysis of self-diagnosis smartphone apps

More than 100,000 mobile phone software applications ('apps') have been designed for the dissemination of health and medical information and healthcare and public health initiatives. This article presents a critical analysis of self-diagnosis smartphone apps directed at lay people that were available on the Apple App Store and Google Play in mid-April 2014. The objective of the analysis is to contribute to the sociology of diagnosis and to critical digital health studies by investigating the phenomenon of digitised diagnosis via apps. We adopted a perspective that views apps as sociocultural artefacts. Our analysis of self-diagnosis apps suggests that they inhabit a contested and ambiguous site of meaning and practice. We found that app developers combined claims to medical expertise in conjunction with appeals to algorithmic authority to promote their apps to potential users. While the developers also used appeals to patient engagement as part of their promotional efforts, these were undermined by routine disclaimers that users should seek medical advice to effect a diagnosis. More research is required to investigate how lay people are negotiating the use of these apps, the implications for privacy of their personal data and the possible effects on the doctor-patient relationship and medical authority in relation to diagnosis.