Introduction After COVID-19, a global mental health crisis affects young people, with one in five youth experiencing mental health problems worldwide. Delivering mental health interventions via mobile devices is a promising strategy to address the treatment gap. Mental health apps are effective for adolescent and young adult samples, but face challenges such as low real-world reach and under-representation of minoritised youth. To increase digital health uptake, including among minoritised youth, there is a need for diversity, equity and inclusion (DEI) considerations in the development and evaluation of mental health apps. How well DEI is integrated into youth mental health apps has not been comprehensively assessed. This scoping review aims to examine to what extent DEI considerations are integrated into the design and evaluation of youth mental health apps and report on youth, caregiver and other stakeholder involvement. Methods and analysis We will identify studies published in English from 2009 to 29 September 2023 on apps for mental health in youth. We will use PubMed, Global Health, APA PsycINFO, SCOPUS, CINAHL PLUS and the Cochrane Database and will report according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Scoping Review Extension guidelines. Papers eligible for inclusion must be peer-reviewed publications in English involving smartphone applications used by adolescents or young adults aged 10–25, with a focus on depression, anxiety or suicidal ideation. Two independent reviewers will review and extract articles using a template developed by the authors. We will analyse the data using narrative synthesis and descriptive statistics. This study will identify gaps in the literature and provide a roadmap for equitable and inclusive mental health apps for youth. Ethics and dissemination Ethics approval is not required. Findings will be disseminated through academic, industry, community networks and scientific publications.

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Introduction Health behaviours such as exercise and diet strongly influence well-being and disease risk, providing the opportunity for interventions tailored to diverse individual contexts. Precise behaviour interventions are critical during adolescence and young adulthood (ages 10-25), a formative period shaping lifelong well-being. We will conduct a systematic review of just-in-time adaptive interventions (JITAIs) for health behaviour and well-being in adolescents and young adults (AYAs). A JITAI is an emerging digital health design that provides precise health support by monitoring and adjusting to individual, specific and evolving contexts in real time. Despite demonstrated potential, no published reviews have explored how JITAIs can dynamically adapt to intersectional health factors of diverse AYAs. We will identify the JITAIs' distal and proximal outcomes and their tailoring mechanisms, and report their effectiveness. We will also explore studies' considerations of health equity. This will form a comprehensive assessment of JITAIs and their role in promoting health behaviours of AYAs. We will integrate evidence to guide the development and implementation of precise, effective and equitable digital health interventions for AYAs. Methods and analysis In adherence to Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines, we will conduct a systematic search across multiple databases, including CENTRAL, MEDLINE and WHO Global Index Medicus. We will include peer-reviewed studies on JITAIs targeting health of AYAs in multiple languages. Two independent reviewers will conduct screening and data extraction of study and participant characteristics, JITAI designs, health outcome measures and equity considerations. We will provide a narrative synthesis of findings and, if data allows, conduct a meta-analysis. Ethics and dissemination As we will not collect primary data, we do not require ethical approval. We will disseminate the review findings through peer-reviewed journal publication, conferences and stakeholder meetings to inform participatory research. PROSPERO registration number CRD42023473117.

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Personas inform design by representing diverse user needs. Since their initial application in commercial technology contexts, personas have been adopted in several research domains for public good, such as health, accessibility, politics and civic society, education, sustainability, cybersecurity, and criminology. In this review paper, we analyzed 58 research studies that created personas in these domains, referred to as Personas for Social Good (PFSG). In most studies, PFSG was primarily exploratory and focused on initial methodology development. More than half (59%) neglected to discuss concerns with stereotyping or evaluate how personas contributed to improving social concerns in their respective domains. To facilitate a shift towards more socially conscious persona applications, we identified and critically examined the most comprehensive PFSG domain applications in our sample. Based on their strengths, we present an ecological framework to guide researchers in holistically aligning persona creation efforts with addressing critical social challenges.@en

Racial disparities in maternal health are alarming and persistent. Use of electroencephalography (EEG) and event-related potentials (ERPs) to understand the maternal brain can improve our knowledge of maternal health by providing insight into mechanisms underlying maternal well-being, including implications for child development. However, systematic racial bias exists in EEG methodology—particularly for Black individuals—and in psychological and health research broadly. This paper discusses these biases in the context of EEG/ERP research on the maternal brain. First, we assess the racial/ethnic diversity of existing ERP studies of maternal neural responding to infant/child emotional expressions, using papers from a recent meta-analysis, finding that the majority of mothers represented in this research are of White/European ancestry and that the racially and ethnically diverse samples that are present are limited in terms of geography. Therefore, our current knowledge base in this area may be biased and not generalizable across racially diverse mothers. We outline factors underlying this problem, beginning with the racial bias in EEG equipment that systematically excludes individuals of African descent, and also considering factors specific to research with mothers. Finally, we highlight recent innovations to EEG hardware to better accommodate diverse hairstyles and textures, and other important steps to increase racial and ethnic representativeness in EEG/ERP research with mothers. We urge EEG/ERP researchers who study the maternal brain—including our own research group—to take action to increase racial diversity so that this research area can confidently inform understanding of maternal health and contribute to minimizing maternal health disparities.@en

Background: Personas are a technique for enhanced understanding of users and customers to improve the user-centered design of systems and products. Their creation can be categorized using three persona creation methodologies: Qualitative, Quantitative, and Mixed Methods. Despite the apparent differences in these methodologies, no previous review has systemically compared and contrasted the strengths and weaknesses of each of these methodologies for persona development. Method: This manuscript maps and navigates persona literature to identify the benefits and challenges of these three persona creation methodologies. Furthermore, the strategies and opportunities of the different methodologies are presented. Results: The results summarize the strengths and weaknesses of each of the three principal persona creation methodologies and offer suggestions of the benefits of their employment. Conclusion: In conclusion, we offer insights into the construction and usage of personas for practitioners and researchers, and we propose a framework to determine which persona creation methodology is most suitable for a given context.@en

Derived from the notion of algorithmic bias, it is possible that creating user segments such as personas from data results in over- or under-representing certain segments (FAIRNESS), does not properly represent the diversity of the user populations (DIVERSITY), or produces inconsistent results when hyperparameters are changed (CONSISTENCY). Collecting user data on 363M video views from a global news and media organization, we compare personas created from this data using different algorithms. Results indicate that the algorithms fall into two groups: those that generate personas with low diversity-high fairness and those that generate personas with high diversity-low fairness. The algorithms that rank high on diversity tend to rank low on fairness (Spearman's correlation: -0.83). The algorithm that best balances diversity, fairness, and consistency is Spectral Embedding. The results imply that the choice of algorithm is a crucial step in data-driven user segmentation, because the algorithm fundamentally impacts the demographic attributes of the generated personas and thus influences how decision makers view the user population. The results have implications for algorithmic bias in user segmentation and creating user segments that not only consider commercial segmentation criteria but also consider criteria derived from ethical discussions in the computing community.@en

This chapter surveys the literature on the quantitative effects of early childhood arts and music education on childhood development. First, the authors establish a theoretical framework that explains the potential role of arts and music education, focusing on its effects on three mechanisms behind childhood development: (1) habit formation, (2) brain development, and (3) socialization. Second, they discuss available evidence in each of these areas, focusing on causal experiments and the importance of reaching children early in their development. Third, they explore the role of technology as a mediating force behind childhood development and provide suggestions for how technology can be used to accelerate and improve the learning process for children in years to come.@en

Gender-based violence (GBV) is that perpetrated based on sex, gender identity, or perceived adherence to socially defined gender norms. This human rights violation is disproportionately experienced by HIV key populations including female sex workers (FSW), people who inject drugs (PWID), and men who have sex with men (MSM). Consequently, addressing GBV is a global priority in HIV response. There is limited consensus about optimal interventions and little known about effectiveness. Our systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and was registered in International Prospective Register of Systematic Reviews. Peer-reviewed and non-peer-reviewed literature were searched for articles that described a GBV prevention or response intervention specifically for key populations including FSW, PWID, and MSM. Results were organized by level(s) of implementation and pillars of a comprehensive GBV response: prevention, survivor support, and accountability/justice. Of 4,287 articles following removal of duplicates, 32 unique interventions (21 FSW, seven PWID, and nine MSM, not mutually exclusive) met inclusion criteria, representing 13 countries. Multisectoral interventions blended empowerment, advocacy, and crisis response with reductions in violence. Individual-level interventions included violence screening and response services. Violence-related safety promotion and risk reduction counseling within HIV risk reduction programming reduced violence. Quantitative evaluations were limited. Violence prevention and response interventions for FSW, PWID, and MSM span individual, community, and multisectoral levels with evidence of promising practices at each level. The strongest evidence supported addressing violence in the context of sexually transmitted infection/HIV risk reduction. As interventions continue to emerge, the rigor of accompanying evaluations must simultaneously advance to enable clarity on the health and safety impact of GBV prevention and response programming.@en

Personas represent the needs of users in diverse populations and impact design by endearing empathy and improving communication. While personas have been lauded for their benefits, we could locate no prior review of persona use cases in design, prompting the question: how are personas actually used to achieve these benefits? To address this question, we review 95 articles containing persona application across multiple domains, and identify software development, healthcare, and higher education as the top domains that employ personas. We then present a three-stage design hierarchy of persona usage to describe how personas are used in design tasks. Finally, we assess the increasing trend of persona initiatives aimed towards social good rather than solely commercial interests. Our findings establish a roadmap of best practices for how practitioners can innovatively employ personas to increase the value of designs and highlight avenues of using personas for socially impactful purposes.@en

Data-driven personas are a significant advancement in the fields of human-centered informatics and human-computer interaction. Data-driven personas enhance user understanding by combining the empathy inherent with personas with the rationality inherent in analytics using computational methods. Via the employment of these computational methods, the data-driven persona method permits the use of large-scale user data, which is a novel advancement in persona creation. A common approach for increasing stakeholder engagement about audiences, customers, or users, persona creation remained relatively unchanged for several decades. However, the availability of digital user data, data science algorithms, and easy access to analytics platforms provide avenues and opportunities to enhance personas from often sketchy representations of user segments to precise, actionable, interactive decision-making tools—data-driven personas! Using the data-driven approach, the persona profile can serve as an interface to a fully functional analytics system that can present user representation at various levels of information granularity for more task-aligned user insights. We trace the techniques that have enabled the development of data-driven personas and then conceptually frame how one can leverage data-driven personas as tools for both empathizing with and understanding of users. Presenting a conceptual framework consisting of (a) persona benefits, (b) analytics benefits, and (c) decision-making outcomes, we illustrate applying this framework via practical use cases in areas of system design, digital marketing, and content creation to demonstrate the application of data-driven personas in practical applied situations. We then present an overview of a fully functional data-driven persona system as an example of multi-level information aggregation needed for decision making about users. We demonstrate that data-driven personas systems can provide critical, empathetic, and user understanding functionalities for anyone needing such insights.@en

Persona is a technique for enhancing user understanding and improving the user-centered design of digital products. Persona creation has traditionally been divided into Qualitative, Quantitative, and Mixed Methods approaches. However, no literature systematically contrasts the strengths and weaknesses of these approaches. We review the literature to map the strengths and weaknesses of these approaches and evaluate the potential of personas for the domain of digital innovation. We provide insights for better creation and use of personas by both researchers and practitioners, especially those that are new to personas, deploying personas in a new domain, or familiar with only one of the persona creation approaches.@en

Practitioners in user-centric industries have increasingly recognized the applicability of personas. However, the methods used to create personas in different domains remain inconsistent and unsystematic. We analyzed 51 studies focused on designing personas for professional purposes and find the practice most prevalent in the user experience (UX) design, healthcare, market research, and social media strategy domains. Within these domains, UX design personas are characterized by their focus on user activity and goals, market research personas on customers' lifestyles, health personas on medical patients' physical symptoms, and social media strategy personas on interactions within online communities. We identify and compare the elements in the personas. Based on this, we provide guidelines for professionals interested in developing personas for recruiting users, understanding barriers to positive user experience, and building online communities, including how to represent persona details related to lifestyle, contexts of product usage, and scaling of online data.@en

Data-driven persona development unifies methodologies for creating robust personas from the behaviors and demographics of user segments. Data-driven personas have gained popularity in human-computer interaction due to digital trends such as personified big data, online analytics, and the evolution of data science algorithms. Even with its increasing popularity, there is a lack of a systematic understanding of the research on the topic. To address this gap, we review 77 data-driven persona research articles from 2005–2020. The results indicate three periods: (1) Quantification (2005–2008), which consists of the first experiments with data-driven methods, (2) Diversification (2009–2014), which involves more pluralistic use of data and algorithms, and (3) Digitalization (2015–present), marked by the abundance of online user data and the rapid development of data science algorithms and software. Despite consistent work on data-driven personas, there remain many research gaps concerning (a) shared resources, (b) evaluation methods, (c) standardization, (d) consideration for inclusivity, and (e) risk of losing in-depth user insights. We encourage organizations to realistically assess their data-driven persona development readiness to gain value from data-driven personas.@en

Quantitative persona creation (QPC) has tremendous potential, as HCI researchers and practitioners can leverage user data from online analytics and digital media platforms to better understand their users and customers. However, there is a lack of a systematic overview of the QPC methods and progress made, with no standard methodology or known best practices. To address this gap, we review 49 QPC research articles from 2005 to 2019. Results indicate three stages of QPC research: Emergence, Diversification, and Sophistication. Sharing resources, such as datasets, code, and algorithms, is crucial to achieving the next stage (Maturity). For practitioners, we provide guiding questions for assessing QPC readiness in organizations.@en

Following the proliferation of personified big data and data science algorithms, data-driven user personas (DDPs) are becoming more common in persona design. However, the DDP templates are seemingly diverse and fragmented, prompting a need for a synthesis of the information included in these personas. Analyzing 31 templates for DDPs, we find that DDPs vary greatly by their information richness, as the most informative layout has more than 300% more information categories than the least informative layout. We also find that graphical complexity and information richness do not necessarily correlate. Furthermore, the chosen persona development method may carry over to the information presentation, with quantitative data typically presented as scores, metrics, or tables and qualitative data as text-rich narratives. We did not find one “general template” for DDPs and defining this is difficult due to the variety of the outputs of different methods as well as different information needs of the persona users.@en