Kathleen Guan
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19 records found
1
Journal article
(2026)
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Caroline A. Figueroa, Kathleen W. Guan, Dimpy Gupta, Neslihan Can, Kayla Green, Jiwon Jung, Eva Thalassinou, Gerben Kuiper, Niko Vegt
Introduction: Mental health issues among young people have surged post-COVID-19. Mental health apps can offer accessible preventive support on a large scale, yet the perspective of minoritized youth–such as those from low socioeconomic and ethnic/racial backgrounds–are underexplored. This risks low uptake and effectiveness, and exacerbating health inequities. This study aimed to understand the needs and concerns of minoritized youth in the Netherlands using a participatory approach. Methods: We conducted 3 co-creation sessions with 17 adolescents (16 females, majority Dutch Moroccan background) aged 11–22 years, recruited through community centers in lower-income neighborhoods in The Netherlands, with the help of community workers. We also organized a discussion session with 26 preventive youth workers to explore their perspectives regarding implementation. A subset of youth (n = 10) analyzed the data in 2 co-thematic analysis workshops. We compared youth and researcher themes. Results: Youth saw data-driven mental health apps as useful for short-term stress relief through motivational quotes, social activity suggestions, and homework support, but unable to solve more severe issues. In the co-analysis, youth analyzed based on emotion and functions, whereas researchers employed a more technical lens. Key themes included identity-based (such as religion, gender, and age) and contextual tailoring (to school/home schedules), compassionate communication as opposed to fake support (robots), safety, and the role of social media. Conclusion: These findings highlight the need to examine how app design for young people can prioritize authentic, compassionate communication, safety–including transparency about data–tailoring to identify aspects, adapting the timing and frequency of notifications, and integrating social connections and social media. Participatory approaches are promising to better understand the needs of youth from minoritized backgrounds for digital mental health technologies, with the aim of equitable digital solutions.
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Introduction: Mental health issues among young people have surged post-COVID-19. Mental health apps can offer accessible preventive support on a large scale, yet the perspective of minoritized youth–such as those from low socioeconomic and ethnic/racial backgrounds–are underexplored. This risks low uptake and effectiveness, and exacerbating health inequities. This study aimed to understand the needs and concerns of minoritized youth in the Netherlands using a participatory approach. Methods: We conducted 3 co-creation sessions with 17 adolescents (16 females, majority Dutch Moroccan background) aged 11–22 years, recruited through community centers in lower-income neighborhoods in The Netherlands, with the help of community workers. We also organized a discussion session with 26 preventive youth workers to explore their perspectives regarding implementation. A subset of youth (n = 10) analyzed the data in 2 co-thematic analysis workshops. We compared youth and researcher themes. Results: Youth saw data-driven mental health apps as useful for short-term stress relief through motivational quotes, social activity suggestions, and homework support, but unable to solve more severe issues. In the co-analysis, youth analyzed based on emotion and functions, whereas researchers employed a more technical lens. Key themes included identity-based (such as religion, gender, and age) and contextual tailoring (to school/home schedules), compassionate communication as opposed to fake support (robots), safety, and the role of social media. Conclusion: These findings highlight the need to examine how app design for young people can prioritize authentic, compassionate communication, safety–including transparency about data–tailoring to identify aspects, adapting the timing and frequency of notifications, and integrating social connections and social media. Participatory approaches are promising to better understand the needs of youth from minoritized backgrounds for digital mental health technologies, with the aim of equitable digital solutions.
Toward Participatory Precision Health With Co-Designed Recommendations
Systematic Review of Just-in-Time Adaptive Interventions in Adolescents and Young Adults
Review
(2026)
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Kathleen W. Guan, Mohammed Amara, Eva Thalassinou, Eeske van Roekel, Loes Keijsers, Mark de Reuver, Caroline A. Figueroa, Viviana Cortiana, Imran Khan, Sıla Gürbüz, Carmine Iorio, Rayyan Ali, Christopher Adlung, Crystal R. Smit, Annabel Vreeker
Background: The transition from adolescence to young adulthood (age 10‐25 years) constitutes a sensitive developmental period marked by rapid biological, psychological, and social change, during which preventive health interventions can shape long-term outcomes. Mobile health tools offer accessible opportunities for tailored support for this population, but often adapt poorly to dynamic contexts, resulting in inconsistent engagement and effects. Just-in-time adaptive interventions (JITAIs), which tailor support in real time using ongoing data, are increasingly explored as precision health strategies. However, how these mechanisms are designed, implemented, and evaluated for adolescents and young adults (AYAs) has not been systematically reviewed. Objective: This review aimed to synthesize the evidence on JITAIs developed for AYAs, examine how their adaptive mechanisms have been designed to support specific health goals and changing AYA contexts, and assess methodological reporting quality to inform future precision health intervention development. Methods: We conducted a systematic review in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and SWiM (Synthesis Without Meta-Analysis) reporting guidelines. Twelve databases were searched for peer-reviewed studies published from 2013 to 2025. Eligible studies focused on participants aged 10 to 25 years and reported real-time adaptive mobile health interventions consistent with JITAI design principles. Two reviewers independently conducted screening, data extraction, and methodological quality appraisal using the Joanna Briggs Institute checklists. AYA coauthors contributed to all phases. Due to substantial heterogeneity in study populations, intervention content, adaptive mechanisms, comparators, and outcome measurements, findings were synthesized narratively, and no meta-analysis was conducted. Results: A total of 61 unique interventions were included. JITAIs for AYAs addressed substance use (n=24, 39.3%), mental health (n=23, 37.7%), and physical health or chronic conditions (n=14, 23%). JITAI tailoring mechanisms relied predominantly on self-reported behavioral data. Decision rules were typically symptom threshold–based, and decision points were commonly daily or event-triggered. Methodological concerns with reporting on intervention administration, participant selection, and outcome measurement reliability were pervasive across all studies, limiting the interpretability of observed effects and cross-study comparisons. Ethical considerations, including researcher positioning and reflexivity, alongside the depth of reporting around participatory AYA engagement in design and implementation, were also inconsistent. Conclusions: This review contributes a novel perspective to AYA digital health by moving beyond intervention outcomes to examine how core adaptive mechanisms are operationalized for AYAs across multiple health domains, while also integrating AYA perspectives into the interpretation of findings and recommendations. Unlike prior reviews focused primarily on adults or specific conditions, it identifies broader contextual, methodological, and ethical considerations relevant to AYA precision health. These findings highlight the need for more transparent, contextually responsive, and youth-centered adaptive interventions, alongside more rigorous designs for evaluating adaptive intervention components in daily life contexts.
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Background: The transition from adolescence to young adulthood (age 10‐25 years) constitutes a sensitive developmental period marked by rapid biological, psychological, and social change, during which preventive health interventions can shape long-term outcomes. Mobile health tools offer accessible opportunities for tailored support for this population, but often adapt poorly to dynamic contexts, resulting in inconsistent engagement and effects. Just-in-time adaptive interventions (JITAIs), which tailor support in real time using ongoing data, are increasingly explored as precision health strategies. However, how these mechanisms are designed, implemented, and evaluated for adolescents and young adults (AYAs) has not been systematically reviewed. Objective: This review aimed to synthesize the evidence on JITAIs developed for AYAs, examine how their adaptive mechanisms have been designed to support specific health goals and changing AYA contexts, and assess methodological reporting quality to inform future precision health intervention development. Methods: We conducted a systematic review in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and SWiM (Synthesis Without Meta-Analysis) reporting guidelines. Twelve databases were searched for peer-reviewed studies published from 2013 to 2025. Eligible studies focused on participants aged 10 to 25 years and reported real-time adaptive mobile health interventions consistent with JITAI design principles. Two reviewers independently conducted screening, data extraction, and methodological quality appraisal using the Joanna Briggs Institute checklists. AYA coauthors contributed to all phases. Due to substantial heterogeneity in study populations, intervention content, adaptive mechanisms, comparators, and outcome measurements, findings were synthesized narratively, and no meta-analysis was conducted. Results: A total of 61 unique interventions were included. JITAIs for AYAs addressed substance use (n=24, 39.3%), mental health (n=23, 37.7%), and physical health or chronic conditions (n=14, 23%). JITAI tailoring mechanisms relied predominantly on self-reported behavioral data. Decision rules were typically symptom threshold–based, and decision points were commonly daily or event-triggered. Methodological concerns with reporting on intervention administration, participant selection, and outcome measurement reliability were pervasive across all studies, limiting the interpretability of observed effects and cross-study comparisons. Ethical considerations, including researcher positioning and reflexivity, alongside the depth of reporting around participatory AYA engagement in design and implementation, were also inconsistent. Conclusions: This review contributes a novel perspective to AYA digital health by moving beyond intervention outcomes to examine how core adaptive mechanisms are operationalized for AYAs across multiple health domains, while also integrating AYA perspectives into the interpretation of findings and recommendations. Unlike prior reviews focused primarily on adults or specific conditions, it identifies broader contextual, methodological, and ethical considerations relevant to AYA precision health. These findings highlight the need for more transparent, contextually responsive, and youth-centered adaptive interventions, alongside more rigorous designs for evaluating adaptive intervention components in daily life contexts.
Children’s helplines train new counselors to adapt to children’s needs and values. This training typically involves roleplay, which can be resource-intensive. Interactive agents offer a promising alternative; yet, simulation-based training systems rarely model how personal values influence decision-making. We present a value-integrated belief–desire–intention (BDI) model that simulates virtual children whose behavior is guided by underlying values. The trainees’ task is to apply motivational interviewing to recognize and align with the child’s values. We conducted a between-subjects experiment (N = 193) comparing three conditions: a base BDI virtual child, a BDI virtual child with integrated values, and one with both integrated values and explanatory feedback on value-based reasoning. Results showed credible support that integrating values improves participants’ opportunities to align with a virtual child and enhances their situational awareness based on a child’s values. We also found some support that feedback improved value recognition and perceived usefulness. Additionally, integrating values improved believability and overall experience. These findings suggest that the proposed values-based model enables more targeted training, which we anticipate will better prepare counselors for value-sensitive conversations.
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Children’s helplines train new counselors to adapt to children’s needs and values. This training typically involves roleplay, which can be resource-intensive. Interactive agents offer a promising alternative; yet, simulation-based training systems rarely model how personal values influence decision-making. We present a value-integrated belief–desire–intention (BDI) model that simulates virtual children whose behavior is guided by underlying values. The trainees’ task is to apply motivational interviewing to recognize and align with the child’s values. We conducted a between-subjects experiment (N = 193) comparing three conditions: a base BDI virtual child, a BDI virtual child with integrated values, and one with both integrated values and explanatory feedback on value-based reasoning. Results showed credible support that integrating values improves participants’ opportunities to align with a virtual child and enhances their situational awareness based on a child’s values. We also found some support that feedback improved value recognition and perceived usefulness. Additionally, integrating values improved believability and overall experience. These findings suggest that the proposed values-based model enables more targeted training, which we anticipate will better prepare counselors for value-sensitive conversations.
Designing Health Recommender Systems to Promote Health Equity
A Socioecological Perspective
Journal article
(2025)
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C.A. Figueroa, H. Torkamaan, Ananya Bhattacharjee, Hanna Hauptmann, Kathleen Guan, Gayane Sedrakyan
Health recommender systems (HRS) have the capability to improve human-centered care and prevention by personalizing content, such as health interventions or health information. HRS, an emerging and developing field, can play a unique role in the digital health field as they can offer relevant recommendations, not only based on what users themselves prefer and may be receptive to, but also using data about wider spheres of influence over human behavior, including peers, families, communities, and societies. We identify and discuss how HRS could play a unique role in decreasing health inequities. We use the socioecological model, which provides representations of how multiple, nested levels of influence (eg, community, institutional, and policy factors) interact to shape individual health. This perspective helps illustrate how HRS could address not just individual health factors but also the structural barriers—such as access to health care, social support, and access to healthy food—that shape health outcomes at various levels. Based on this analysis, we then discuss the challenges and future research priorities. We find that despite the potential for targeting more complex systemic challenges to obtaining good health, current HRS are still focused on individual health behaviors, often do not integrate the lived experiences of users in the design, and have had limited reach and effectiveness for individuals from low socioeconomic status and racial or ethnic minoritized backgrounds. In this viewpoint, we argue that a new design paradigm is necessary in which HRS focus on incorporating structural barriers to good health in addition to user preferences. HRS should be designed with an emphasis on health systems, which also includes incorporating decolonial perspectives of well-being that challenge prevailing medical models. Furthermore, potential lies in evaluating the health equity effects of HRS and leveraging collected data to influence policy. With changes in practices and with an intentional equity focus, HRS could play a crucial role in health promotion and decreasing health inequities.
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Health recommender systems (HRS) have the capability to improve human-centered care and prevention by personalizing content, such as health interventions or health information. HRS, an emerging and developing field, can play a unique role in the digital health field as they can offer relevant recommendations, not only based on what users themselves prefer and may be receptive to, but also using data about wider spheres of influence over human behavior, including peers, families, communities, and societies. We identify and discuss how HRS could play a unique role in decreasing health inequities. We use the socioecological model, which provides representations of how multiple, nested levels of influence (eg, community, institutional, and policy factors) interact to shape individual health. This perspective helps illustrate how HRS could address not just individual health factors but also the structural barriers—such as access to health care, social support, and access to healthy food—that shape health outcomes at various levels. Based on this analysis, we then discuss the challenges and future research priorities. We find that despite the potential for targeting more complex systemic challenges to obtaining good health, current HRS are still focused on individual health behaviors, often do not integrate the lived experiences of users in the design, and have had limited reach and effectiveness for individuals from low socioeconomic status and racial or ethnic minoritized backgrounds. In this viewpoint, we argue that a new design paradigm is necessary in which HRS focus on incorporating structural barriers to good health in addition to user preferences. HRS should be designed with an emphasis on health systems, which also includes incorporating decolonial perspectives of well-being that challenge prevailing medical models. Furthermore, potential lies in evaluating the health equity effects of HRS and leveraging collected data to influence policy. With changes in practices and with an intentional equity focus, HRS could play a crucial role in health promotion and decreasing health inequities.
Journal article
(2024)
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Kathleen W Guan, Christopher Adlung, Loes Keijsers, Crystal R. Smit, Annabel Vreeker, Eva Thalassinou, Eeske van Roekel, Mark de Reuver, Caroline A Figueroa
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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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.
Diversity, equity and inclusion considerations in mental health apps for young people
Protocol for a scoping review
Journal article
(2024)
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Caroline A. Figueroa, Nancy J. Pérez-Flores, Kathleen W. Guan, Colleen Stiles-Shields
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 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.
Leveraging Personas for Social Impact
A Review of Their Applications to Social Good in Design
Journal article
(2023)
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Kathleen W. Guan, Joni Salminen, Soon Gyo Jung, Bernard J. Jansen
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.
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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.
Journal article
(2023)
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Francesca Penner, Kathryn M. Wall, Kathleen W. Guan, Helen J. Huang, Lietsel Richardson, Angel S. Dunbar, Ashley M. Groh, Helena J.V. Rutherford
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.
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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.
Book chapter
(2022)
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Christos Makridis, Kathleen Guan, Evan Ludington, Michael Hopkins, Soula Parassidis
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.
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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.
A Systematic Review of Gender-Based Violence Prevention and Response Interventions for HIV Key Populations
Female Sex Workers, Men Who Have Sex With Men, and People Who Inject Drugs
Journal article
(2022)
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Michele R. Decker, Carrie Lyons, Stefan Baral, Kathleen Guan, Vanessa Mosenge, Ghislane Fouda, Daniel Levitt, Anna Abelson, Gnilane Turpin Nunez, Iliassou Mfochive Njindam, Shaheen Kurani
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.
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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.
How to Create Personas
Three Persona Creation Methodologies with Implications for Practical Employment
Journal article
(2022)
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Bernard J. Jansen, Soon Gyo Jung, Lene Nielsen, Kathleen W. Guan, Joni Salminen
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.
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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.
Use Cases for Design Personas
A Systematic Review and New Frontiers
Conference paper
(2022)
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Joni Salminen, Kathleen Wenyun Guan, Soon Gyo Jung, Bernard Jansen
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.
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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.
Big Data, Small Personas
How Algorithms Shape the Demographic Representation of Data-Driven User Segments
Journal article
(2022)
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Joni Salminen, Kamal Chhirang, Soon Gyo Jung, Saravanan Thirumuruganathan, Kathleen W. Guan, Bernard J. Jansen
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.
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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.
Conference paper
(2021)
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Kathleen Wenyun Guan, Joni Salminen, Lene Nielsen, Soon Gyo Jung, Bernard J. Jansen
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.
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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.
Book
(2021)
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Bernard J. Jansen, Joni Salminen, Soon Gyo Jung, Kathleen Guan
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.
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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.
Strengths and weaknesses of persona creation methods
Guidelines and opportunities for digital innovations
Conference paper
(2021)
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Bernard J. Jansen, Soon Gyo Jung, Joni Salminen, Kathleen W. Guan, Lene Nielsen
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.
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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.
Journal article
(2021)
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Joni Salminen, Kathleen Guan, Soon Gyo Jung, Bernard J. Jansen
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.
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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.
Conference paper
(2020)
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Joni Salminen, Kathleen Guan, Soon Gyo Jung, Shammur A. Chowdhury, Bernard J. Jansen
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.
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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.
A template for data-driven personas
Analyzing 31 quantitatively oriented persona profiles
Conference paper
(2020)
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Joni Salminen, Kathleen Guan, Lene Nielsen, Soon gyo Jung, Bernard J. Jansen
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.
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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.