RESUMEN
Mental health apps bring unprecedented benefits and risks to individual and public health. A thorough evaluation of these apps involves considering two aspects that are often neglected: the algorithms they deploy and the functions they perform. We focus on mental health apps based on black box algorithms, explore their forms of opacity, discuss the implications derived from their opacity, and propose how to use their outcomes in mental healthcare, self-care practices, and research. We argue that there is a relevant distinction between functions performed by algorithms in mental health apps, and we focus on the functions of analysis and generation of advice. When performing analytic functions, such as identifying patterns and making predictions concerning people's emotions, thoughts, and behaviors, black box algorithms can be better than other algorithms to provide information to identify early signs of relapse, support diagnostic processes, and improve research by generating outcomes that lead to a better understanding of mental health. However, when carrying out the function of providing mental health advice, black box algorithms have the potential to deliver unforeseen advice that may harm users. We argue that the outcomes of these apps may be trustworthy as a complementary source of information, but express caution about black box algorithms that give advice directly to users. To reap the benefits of mental health apps based on black box algorithms and avoid unintended consequences, we critically need to know whether these algorithms are fulfilling the function of providing mental health advice.
Asunto(s)
Aplicaciones Móviles , Telemedicina , Humanos , Salud Mental , EmocionesRESUMEN
Objectives: We face the impossibility of having enough COVID-19 vaccines for everyone in the near future. This study aims to contribute to the debate on equitable global access to COVID-19 vaccines, tackling key ethical discussions and policy challenges regarding early phases of COVAX, the global cooperation mechanism for supporting fair vaccine allocation. Methods: We conducted in-depth interviews with twelve experts and a literature research on academic articles, media sources and public statements. We built a data analysis matrix and conducted a thematic analysis. Results: Our findings show, first, that interviewed experts who hold different views on vaccine allocation, including moderate nationalist perspectives, agree on joining a global cooperation mechanism. Second, incentives to join COVAX vary greatly among countries. Third, specific barriers to COVAX emerged in the early implementation phase. And fourth, countries might be trapped in a zero-sum game regarding the global vaccine supply. Conclusion: We present findings that enrich analyses of early phases of COVAX (April 2020-21), we introduce three ethical discussions that provide a common ground for equitable access to COVID-19 vaccines, and we highlight policy challenges.