Stack Results - A Framework for Personalized Wellness
Stack Results - A Framework for Personalized Wellness
A peer-to-peer platform for sharing and discovering personalized health stacks.
A peer-to-peer platform for sharing and discovering personalized health stacks.
01 Overview
01 Overview
Stack Results is a platform for the peer-to-peer transfer of health and wellness knowledge in a systematic and individualized way. Its vision is to guide people toward healthier lifestyles and enable them to achieve their peak physical and mental states. The platform was born from the need to address the inherent problems of online health information, which is often dispersed, inconsistent, and lacks credibility or tailored advice. Stack Results aims to solve this by championing individualism, recognizing that no two people are alike, and creating a space where users can share and compare their health strategies and results over time to foster collective education and personal growth.
Stack Results is a platform for the peer-to-peer transfer of health and wellness knowledge in a systematic and individualized way. Its vision is to guide people toward healthier lifestyles and enable them to achieve their peak physical and mental states. The platform was born from the need to address the inherent problems of online health information, which is often dispersed, inconsistent, and lacks credibility or tailored advice. Stack Results aims to solve this by championing individualism, recognizing that no two people are alike, and creating a space where users can share and compare their health strategies and results over time to foster collective education and personal growth.
02 Core Idea
02 Core Idea
The core idea of Stack Results is built on the thesis that the individual is a complex system shaped by two primary factors: our body and our environment. It adopts a bottoms-up approach, starting at the granular level to understand the smallest components of health and working upwards to treat humanity as a whole system capable of achieving peak performance.
The core idea of Stack Results is built on the thesis that the individual is a complex system shaped by two primary factors: our body and our environment. It adopts a bottoms-up approach, starting at the granular level to understand the smallest components of health and working upwards to treat humanity as a whole system capable of achieving peak performance.
The scientific principle behind the platform is to create a digital, virtual representation of each user. By collecting detailed health data (vitals, macronutrients, environmental factors), the platform can analyze this information to identify profile matches between individuals. The higher the match percentage, the greater the probability that a solution or "stack" effective for one person will work for another. This data-driven individualism is centered on first achieving homeostasis—a stable internal environment which is the foundation for all health progress.
The scientific principle behind the platform is to create a digital, virtual representation of each user. By collecting detailed health data (vitals, macronutrients, environmental factors), the platform can analyze this information to identify profile matches between individuals. The higher the match percentage, the greater the probability that a solution or "stack" effective for one person will work for another. This data-driven individualism is centered on first achieving homeostasis—a stable internal environment which is the foundation for all health progress.
03 Research background & intellectual lineage
03 Research background & intellectual lineage
The conceptual framework of Stack Results is built upon an interdisciplinary synthesis of principles from biology, data science, and social ecology. Its intellectual lineage is rooted in three core concepts: the biological imperative of homeostasis, the analytical power of morphospaces, and the collaborative dynamic of collective mutualism.
The conceptual framework of Stack Results is built upon an interdisciplinary synthesis of principles from biology, data science, and social ecology. Its intellectual lineage is rooted in three core concepts: the biological imperative of homeostasis, the analytical power of morphospaces, and the collaborative dynamic of collective mutualism.
Personalized Homeostasis as the Foundational Goal — At its core, all health and wellness is a quest for homeostasis—the body's innate ability to maintain a stable, balanced internal environment. This equilibrium is the prerequisite for optimal physiological function, and its disruption is the basis for nearly every disease and chronic condition. The platform's primary objective is to help users achieve a state of "end homeostasis" tailored to their unique goals. However, modern science recognizes that the path to this balance is highly individual, as factors like genetics, lifestyle, and environment mean that a "one-size-fits-all" approach to health is ineffective. This has given rise to the field of precision wellness, which uses biomarkers, genomics, and lifestyle data to tailor interventions. Stack Results democratizes this concept by using accessible data points—such as biometrics, diet, activity levels, and environment—to create a practical, personalized roadmap to wellness for every user.
Personalized Homeostasis as the Foundational Goal — At its core, all health and wellness is a quest for homeostasis—the body's innate ability to maintain a stable, balanced internal environment. This equilibrium is the prerequisite for optimal physiological function, and its disruption is the basis for nearly every disease and chronic condition. The platform's primary objective is to help users achieve a state of "end homeostasis" tailored to their unique goals. However, modern science recognizes that the path to this balance is highly individual, as factors like genetics, lifestyle, and environment mean that a "one-size-fits-all" approach to health is ineffective. This has given rise to the field of precision wellness, which uses biomarkers, genomics, and lifestyle data to tailor interventions. Stack Results democratizes this concept by using accessible data points—such as biometrics, diet, activity levels, and environment—to create a practical, personalized roadmap to wellness for every user.
The Health Morphospace: Mapping Individual Wellness — To achieve data-driven individualism, Stack Results conceptualizes each user within a "health morphospace." Borrowed from evolutionary biology, a morphospace is a multidimensional representation of the possible forms or structures an organism can take, where each axis represents a specific variable. In this context, each user is a unique point within a complex health morphospace, defined by axes representing their biological, lifestyle, environmental, and behavioral data. The platform's personalization engine analyzes this space to identify users who are "neighbors"—individuals with closely clustered data points. The core hypothesis is that individuals who are proximate in the health morphospace have a higher probability of responding similarly to the same "stack" of interventions. This transforms health optimization from guesswork into a navigable, data-informed journey from one point in the morphospace (current state) to another (desired state).
The Health Morphospace: Mapping Individual Wellness — To achieve data-driven individualism, Stack Results conceptualizes each user within a "health morphospace." Borrowed from evolutionary biology, a morphospace is a multidimensional representation of the possible forms or structures an organism can take, where each axis represents a specific variable. In this context, each user is a unique point within a complex health morphospace, defined by axes representing their biological, lifestyle, environmental, and behavioral data. The platform's personalization engine analyzes this space to identify users who are "neighbors"—individuals with closely clustered data points. The core hypothesis is that individuals who are proximate in the health morphospace have a higher probability of responding similarly to the same "stack" of interventions. This transforms health optimization from guesswork into a navigable, data-informed journey from one point in the morphospace (current state) to another (desired state).
Collective Mutualism: A Self-Evolving Knowledge Ecosystem — The platform's social architecture is modeled on the ecological principle of mutualism, where different species "work together," each benefiting from the relationship. Stack Results creates a digital ecosystem where users engage in a form of collective mutualism. "Seekers" gain access to proven health strategies, while "Influencers" and "Elites" receive a platform to share their knowledge, build a following, and monetize their expertise. This structured, reciprocal exchange of value fosters a collaborative community that is more advanced than traditional online health forums, which are often unstructured and anecdotal.
Collective Mutualism: A Self-Evolving Knowledge Ecosystem — The platform's social architecture is modeled on the ecological principle of mutualism, where different species "work together," each benefiting from the relationship. Stack Results creates a digital ecosystem where users engage in a form of collective mutualism. "Seekers" gain access to proven health strategies, while "Influencers" and "Elites" receive a platform to share their knowledge, build a following, and monetize their expertise. This structured, reciprocal exchange of value fosters a collaborative community that is more advanced than traditional online health forums, which are often unstructured and anecdotal.
This ecosystem is designed to generate collective intelligence. The platform's user segmentation into "The Frontier" (innovators), "Elites" (early adopters/replicators), and "The Commoners" (mainstream users) creates a self-validating knowledge pipeline. New strategies are tested by the Frontier, validated by the Elites, and adopted by the Commoners once proven effective. This peer-to-peer process accelerates the discovery and dissemination of effective wellness strategies, allowing the community's collective knowledge to grow and evolve organically.
This ecosystem is designed to generate collective intelligence. The platform's user segmentation into "The Frontier" (innovators), "Elites" (early adopters/replicators), and "The Commoners" (mainstream users) creates a self-validating knowledge pipeline. New strategies are tested by the Frontier, validated by the Elites, and adopted by the Commoners once proven effective. This peer-to-peer process accelerates the discovery and dissemination of effective wellness strategies, allowing the community's collective knowledge to grow and evolve organically.
04 Process & methodology
04 Process & methodology
The platform's methodology follows a three-step process to transform user health:
The platform's methodology follows a three-step process to transform user health:
Research (Gathering Data)
Research (Gathering Data)
The process begins with in-depth research into each user's goals. The platform gathers granular data to quantify the end state of homeostasis a user wants to achieve. Based on their goals and risk tolerance, users are segmented into three distinct categories for tailored research and recommendations.
The process begins with in-depth research into each user's goals. The platform gathers granular data to quantify the end state of homeostasis a user wants to achieve. Based on their goals and risk tolerance, users are segmented into three distinct categories for tailored research and recommendations.
Experimentation (User Segmentation)
Experimentation (User Segmentation)
Users are categorized to match them with the right level of experimentation:
Users are categorized to match them with the right level of experimentation:
The Frontier: Individuals aiming to achieve unprecedented results who are willing to experiment to advance human health. They are connected with organizations that can fund their research.
The Frontier: Individuals aiming to achieve unprecedented results who are willing to experiment to advance human health. They are connected with organizations that can fund their research.
Elites: Those who wish to mimic the results of the top performers in a specific field. Stack Results helps them find and learn from these high-achievers.
Elites: Those who wish to mimic the results of the top performers in a specific field. Stack Results helps them find and learn from these high-achievers.
Evidence-first: Risk-averse individuals who seek methods that are scientifically proven or have stood the test of time. The platform provides them with evidence-backed stacks that have been validated by many others.
Evidence-first: Risk-averse individuals who seek methods that are scientifically proven or have stood the test of time. The platform provides them with evidence-backed stacks that have been validated by many others.
Application (Connecting & Tracking)
Application (Connecting & Tracking)
The platform applies its research by connecting users with individuals who have already achieved their desired results through a robust profile-matching system. The core application is tracking genuine outcomes. It allows users to log their health metrics, integrate wearable devices for seamless data flow, and based on their results, receive recommendations for better stacks to achieve their next milestone.
The platform applies its research by connecting users with individuals who have already achieved their desired results through a robust profile-matching system. The core application is tracking genuine outcomes. It allows users to log their health metrics, integrate wearable devices for seamless data flow, and based on their results, receive recommendations for better stacks to achieve their next milestone.
05 UI in practice
05 UI in practice
Home Screen
Home Screen
Keep up with your followed stacks, track your health, and explore what’s new in wellness and the store
Keep up with your followed stacks, track your health, and explore what’s new in wellness and the store
Explore Screen
Explore Screen
Discover stacks and posts across health categories, explore real results and updates
Discover stacks and posts across health categories, explore real results and updates
Stack Details
Stack Details
Get a detailed view of the stack, from results and product usage to every update made along the way
Get a detailed view of the stack, from results and product usage to every update made along the way
Store
Store
Explore products by category, compare across suppliers, and shop what works for your goals
Explore products by category, compare across suppliers, and shop what works for your goals
Track
Track
Track your biomarkers over time and share your progress with other
Track your biomarkers over time and share your progress with other
06 System architecture
06 System architecture
The architecture of Stack Results is built on a personalization engine that relies on a comprehensive data model. The objective is to build detailed health profiles for each user to enable personalized recommendations.
The architecture of Stack Results is built on a personalization engine that relies on a comprehensive data model. The objective is to build detailed health profiles for each user to enable personalized recommendations.
Biological Data
Vitals (heart rate, blood pressure), biometrics (age, weight, BMI), biomarkers, and known health conditions.
Biological Data
Vitals (heart rate, blood pressure), biometrics (age, weight, BMI), biomarkers, and known health conditions.
Lifestyle Data
Diet, physical activity habits, and sleep patterns.
Environmental Data
Geographic location data such as temperature, altitude, pollution levels, and sunlight exposure.
Environmental Data
Geographic location data such as temperature, altitude, pollution levels, and sunlight exposure.
Behavioral Data
Health product history, user-reported satisfaction levels, and stated goals (e.g. fat loss, muscle gain).
Behavioral Data
Health product history, user-reported satisfaction levels, and stated goals (e.g. fat loss, muscle gain).
Tracking Data
Real-time inputs from wearable devices and in-app logs
Tracking Data
Real-time inputs from wearable devices and in-app logs
The platform's engine uses this collected data to personalize recommendations:
The platform's engine uses this collected data to personalize recommendations:
Stack Recommendations
Personalized based on matches in user lifestyle, biomarkers, and environmental data.
Stack Recommendations
Personalized based on matches in user lifestyle, biomarkers, and environmental data.
User Recommendations
Connects users based on matching stack categories, commitments, and content engagement.
User Recommendations
Connects users based on matching stack categories, commitments, and content engagement.
Product Recommendations
Recommends health products based on stack interests, lifestyle choices (e.g., vegan), and products used by users with a high profile match.
Product Recommendations
Recommends health products based on stack interests, lifestyle choices (e.g., vegan), and products used by users with a high profile match.
07 Use cases & proposed pilots
07 Use cases & proposed pilots
The platform is designed to serve several key user groups:
The platform is designed to serve several key user groups:
For Influencers
A tool to create, share, and monetize their health stacks, attracting a larger audience and engaging with their followers. They can affiliate with product brands through a standard membership.
For Influencers
A tool to create, share, and monetize their health stacks, attracting a larger audience and engaging with their followers. They can affiliate with product brands through a standard membership.
For Seekers
The primary users who can find trusted stacks, receive recommendations based on their personal health data, commit to new routines, track their progress minutely, and contribute to the platform's trust by sharing their results.
For Seekers
The primary users who can find trusted stacks, receive recommendations based on their personal health data, commit to new routines, track their progress minutely, and contribute to the platform's trust by sharing their results.
For Brands
A targeted channel to reach engaged consumers who are actively seeking health and wellness products and solutions.
For Brands
A targeted channel to reach engaged consumers who are actively seeking health and wellness products and solutions.
A future version will include a dedicated "Phase Mode." This pilot program would create dedicated spaces within the app for users in a specific phase of life (e.g., new parents, injury recovery, pregnancy), providing highly specialized stacks and community support for those unique circumstances.
A future version will include a dedicated "Phase Mode." This pilot program would create dedicated spaces within the app for users in a specific phase of life (e.g., new parents, injury recovery, pregnancy), providing highly specialized stacks and community support for those unique circumstances.
08 Closing Insight
08 Closing Insight
Health and wellness are critical for longevity and personal growth. As people compare their results with others, there is a natural curiosity about the strategies that lead to success. While genetics play a role, a proactive, data-driven approach can make a drastic difference. By fostering a community where individuals can share and compare their health strategies, Stack Results aims to enhance collective knowledge and empower more people to find their unique path to wellness. This initiative not only addresses a growing interest in health optimization but also creates a robust business model centered around the evolving needs of the modern, health-conscious consumer.
Health and wellness are critical for longevity and personal growth. As people compare their results with others, there is a natural curiosity about the strategies that lead to success. While genetics play a role, a proactive, data-driven approach can make a drastic difference. By fostering a community where individuals can share and compare their health strategies, Stack Results aims to enhance collective knowledge and empower more people to find their unique path to wellness. This initiative not only addresses a growing interest in health optimization but also creates a robust business model centered around the evolving needs of the modern, health-conscious consumer.
× Asimakopoulos, S., De Moya, F., & Pallud, J. (2017). The role of self-efficacy in the use of wearables for health care. Proceedings of the 50th Hawaii International Conference on System Sciences.
× Chen, J., & Wang, Y. (2021). Social media use for health purposes: Systematic review. Journal of Medical Internet Research, 23(5), e17917.
× Chiu, C. M., Hsu, M. H., & Wang, E. T. (2006). Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories. Decision Support Systems, 42(3), 1872-1888.
× Ginsburg, G. S., & Phillips, K. A. (2018). Precision medicine: From science to value. Health Affairs, 37(5), 694-701.
× Kurvers, R. H. J. M., Nuzzolese, A. G., Russo, A., Barabucci, G., Herzog, S. M., & Trianni, V. (2023). A collective-intelligence approach for diagnosing medical conditions. Proceedings of the National Academy of Sciences, 120(44), e2305897120.
× Li, J., & Tang, L. (2022). Sharing health information across online platforms: A systematic review. Journal of Health Communication, 27(1), 1-12.
× Marks, D. F. (2023). The Homeostasis Theory of Well-being. Journal of Health Psychology, 28(1), 3-15.
× Mitteroecker, P., & Huttegger, S. M. (2009). The concept of morphospaces in evolutionary and developmental biology: Mathematics and metaphors. Biological Theory, 4(1), 54-67.
× Naslund, J. A., Aschbrenner, K. A., Marsch, L. A., & Bartels, S. J. (2016). The potential for online peer-to-peer support for individuals with serious mental illness. JMIR Mental Health, 3(2), e15.
× Patel, M. S., Asch, D. A., & Volpp, K. G. (2015). Wearable devices as facilitators, not drivers, of health behavior change. JAMA, 313(5), 459–460.
× Raup, D. M. (1966). Geometric analysis of shell coiling: general problems. Journal of Paleontology, 40(5), 1178-1190.
× Snyderman, R., & Yoediono, Z. (2014). Personalized health care: from theory to practice. Biotechnology Journal, 9(9), 1103-1109.
× Tang, M. S. S., Moore, K., & Ganesan, A. (2020). Effectiveness of wearable trackers on physical activity in healthy adults: Systematic review and meta-analysis of randomized controlled trials. JMIR mHealth and uHealth, 8(7), e15576.
× Wolf, G. (2010, June). The quantified self. [Video]. TED Conferences. https://www.ted.com/talks/gary_wolf_the_quantified_self
× Ziebland, S., & Wyke, S. (2012). Health and illness in a connected world: how might sharing experiences on the internet affect people's health? The Milbank Quarterly, 90(2), 219–249.
Stack Results - A Framework for Personalized Wellness
A peer-to-peer platform for sharing and discovering personalized health stacks.
01 Overview
Stack Results is a platform for the peer-to-peer transfer of health and wellness knowledge in a systematic and individualized way. Its vision is to guide people toward healthier lifestyles and enable them to achieve their peak physical and mental states. The platform was born from the need to address the inherent problems of online health information, which is often dispersed, inconsistent, and lacks credibility or tailored advice. Stack Results aims to solve this by championing individualism, recognizing that no two people are alike, and creating a space where users can share and compare their health strategies and results over time to foster collective education and personal growth.
02 Core Idea
The core idea of Stack Results is built on the thesis that the individual is a complex system shaped by two primary factors: our body and our environment. It adopts a bottoms-up approach, starting at the granular level to understand the smallest components of health and working upwards to treat humanity as a whole system capable of achieving peak performance.
The scientific principle behind the platform is to create a digital, virtual representation of each user. By collecting detailed health data (vitals, macronutrients, environmental factors), the platform can analyze this information to identify profile matches between individuals. The higher the match percentage, the greater the probability that a solution or "stack" effective for one person will work for another. This data-driven individualism is centered on first achieving homeostasis—a stable internal environment which is the foundation for all health progress.
03 Research background & intellectual lineage
The conceptual framework of Stack Results is built upon an interdisciplinary synthesis of principles from biology, data science, and social ecology. Its intellectual lineage is rooted in three core concepts: the biological imperative of homeostasis, the analytical power of morphospaces, and the collaborative dynamic of collective mutualism.
Personalized Homeostasis as the Foundational Goal — At its core, all health and wellness is a quest for homeostasis—the body's innate ability to maintain a stable, balanced internal environment. This equilibrium is the prerequisite for optimal physiological function, and its disruption is the basis for nearly every disease and chronic condition. The platform's primary objective is to help users achieve a state of "end homeostasis" tailored to their unique goals. However, modern science recognizes that the path to this balance is highly individual, as factors like genetics, lifestyle, and environment mean that a "one-size-fits-all" approach to health is ineffective. This has given rise to the field of precision wellness, which uses biomarkers, genomics, and lifestyle data to tailor interventions. Stack Results democratizes this concept by using accessible data points—such as biometrics, diet, activity levels, and environment—to create a practical, personalized roadmap to wellness for every user.
The Health Morphospace: Mapping Individual Wellness — To achieve data-driven individualism, Stack Results conceptualizes each user within a "health morphospace." Borrowed from evolutionary biology, a morphospace is a multidimensional representation of the possible forms or structures an organism can take, where each axis represents a specific variable. In this context, each user is a unique point within a complex health morphospace, defined by axes representing their biological, lifestyle, environmental, and behavioral data. The platform's personalization engine analyzes this space to identify users who are "neighbors"—individuals with closely clustered data points. The core hypothesis is that individuals who are proximate in the health morphospace have a higher probability of responding similarly to the same "stack" of interventions. This transforms health optimization from guesswork into a navigable, data-informed journey from one point in the morphospace (current state) to another (desired state).
Collective Mutualism: A Self-Evolving Knowledge Ecosystem — The platform's social architecture is modeled on the ecological principle of mutualism, where different species "work together," each benefiting from the relationship. Stack Results creates a digital ecosystem where users engage in a form of collective mutualism. "Seekers" gain access to proven health strategies, while "Influencers" and "Elites" receive a platform to share their knowledge, build a following, and monetize their expertise. This structured, reciprocal exchange of value fosters a collaborative community that is more advanced than traditional online health forums, which are often unstructured and anecdotal.
This ecosystem is designed to generate collective intelligence. The platform's user segmentation into "The Frontier" (innovators), "Elites" (early adopters/replicators), and "The Commoners" (mainstream users) creates a self-validating knowledge pipeline. New strategies are tested by the Frontier, validated by the Elites, and adopted by the Commoners once proven effective. This peer-to-peer process accelerates the discovery and dissemination of effective wellness strategies, allowing the community's collective knowledge to grow and evolve organically.
04 Process & methodology
The platform's methodology follows a three-step process to transform user health:
Research (Gathering Data)
The process begins with in-depth research into each user's goals. The platform gathers granular data to quantify the end state of homeostasis a user wants to achieve. Based on their goals and risk tolerance, users are segmented into three distinct categories for tailored research and recommendations.
Experimentation (User Segmentation)
Users are categorized to match them with the right level of experimentation:
The Frontier: Individuals aiming to achieve unprecedented results who are willing to experiment to advance human health. They are connected with organizations that can fund their research.
Elites: Those who wish to mimic the results of the top performers in a specific field. Stack Results helps them find and learn from these high-achievers.
Evidence-first: Risk-averse individuals who seek methods that are scientifically proven or have stood the test of time. The platform provides them with evidence-backed stacks that have been validated by many others.
Application (Connecting & Tracking)
The platform applies its research by connecting users with individuals who have already achieved their desired results through a robust profile-matching system. The core application is tracking genuine outcomes. It allows users to log their health metrics, integrate wearable devices for seamless data flow, and based on their results, receive recommendations for better stacks to achieve their next milestone.
05 UI in practice
Home Screen
Keep up with your followed stacks, track your health, and explore what’s new in wellness and the store
Explore Screen
Discover stacks and posts across health categories, explore real results and updates
Stack Details
Get a detailed view of the stack, from results and product usage to every update made along the way
Store
Explore products by category, compare across suppliers, and shop what works for your goals
Track
Track your biomarkers over time and share your progress with other
06 System architecture
The architecture of Stack Results is built on a personalization engine that relies on a comprehensive data model. The objective is to build detailed health profiles for each user to enable personalized recommendations.
Biological Data
Vitals (heart rate, blood pressure), biometrics (age, weight, BMI), biomarkers, and known health conditions.
Lifestyle Data
Diet, physical activity habits, and sleep patterns.
Environmental Data
Geographic location data such as temperature, altitude, pollution levels, and sunlight exposure.
Behavioral Data
Health product history, user-reported satisfaction levels, and stated goals (e.g. fat loss, muscle gain).
Tracking Data
Real-time inputs from wearable devices and in-app logs
The platform's engine uses this collected data to personalize recommendations:
Stack Recommendations
Personalized based on matches in user lifestyle, biomarkers, and environmental data.
User Recommendations
Connects users based on matching stack categories, commitments, and content engagement.
Product Recommendations
Recommends health products based on stack interests, lifestyle choices (e.g., vegan), and products used by users with a high profile match.
07 Use cases & proposed pilots
The platform is designed to serve several key user groups:
For Influencers
A tool to create, share, and monetize their health stacks, attracting a larger audience and engaging with their followers. They can affiliate with product brands through a standard membership.
For Seekers
The primary users who can find trusted stacks, receive recommendations based on their personal health data, commit to new routines, track their progress minutely, and contribute to the platform's trust by sharing their results.
For Brands
A targeted channel to reach engaged consumers who are actively seeking health and wellness products and solutions.
A future version will include a dedicated "Phase Mode." This pilot program would create dedicated spaces within the app for users in a specific phase of life (e.g., new parents, injury recovery, pregnancy), providing highly specialized stacks and community support for those unique circumstances.
08 Closing Insight
Health and wellness are critical for longevity and personal growth. As people compare their results with others, there is a natural curiosity about the strategies that lead to success. While genetics play a role, a proactive, data-driven approach can make a drastic difference. By fostering a community where individuals can share and compare their health strategies, Stack Results aims to enhance collective knowledge and empower more people to find their unique path to wellness. This initiative not only addresses a growing interest in health optimization but also creates a robust business model centered around the evolving needs of the modern, health-conscious consumer.
× Asimakopoulos, S., De Moya, F., & Pallud, J. (2017). The role of self-efficacy in the use of wearables for health care. Proceedings of the 50th Hawaii International Conference on System Sciences.
× Chen, J., & Wang, Y. (2021). Social media use for health purposes: Systematic review. Journal of Medical Internet Research, 23(5), e17917.
× Chiu, C. M., Hsu, M. H., & Wang, E. T. (2006). Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories. Decision Support Systems, 42(3), 1872-1888.
× Ginsburg, G. S., & Phillips, K. A. (2018). Precision medicine: From science to value. Health Affairs, 37(5), 694-701.
× Kurvers, R. H. J. M., Nuzzolese, A. G., Russo, A., Barabucci, G., Herzog, S. M., & Trianni, V. (2023). A collective-intelligence approach for diagnosing medical conditions. Proceedings of the National Academy of Sciences, 120(44), e2305897120.
× Li, J., & Tang, L. (2022). Sharing health information across online platforms: A systematic review. Journal of Health Communication, 27(1), 1-12.
× Marks, D. F. (2023). The Homeostasis Theory of Well-being. Journal of Health Psychology, 28(1), 3-15.
× Mitteroecker, P., & Huttegger, S. M. (2009). The concept of morphospaces in evolutionary and developmental biology: Mathematics and metaphors. Biological Theory, 4(1), 54-67.
× Naslund, J. A., Aschbrenner, K. A., Marsch, L. A., & Bartels, S. J. (2016). The potential for online peer-to-peer support for individuals with serious mental illness. JMIR Mental Health, 3(2), e15.
× Patel, M. S., Asch, D. A., & Volpp, K. G. (2015). Wearable devices as facilitators, not drivers, of health behavior change. JAMA, 313(5), 459–460.
× Raup, D. M. (1966). Geometric analysis of shell coiling: general problems. Journal of Paleontology, 40(5), 1178-1190.
× Snyderman, R., & Yoediono, Z. (2014). Personalized health care: from theory to practice. Biotechnology Journal, 9(9), 1103-1109.
× Tang, M. S. S., Moore, K., & Ganesan, A. (2020). Effectiveness of wearable trackers on physical activity in healthy adults: Systematic review and meta-analysis of randomized controlled trials. JMIR mHealth and uHealth, 8(7), e15576.
× Wolf, G. (2010, June). The quantified self. [Video]. TED Conferences. https://www.ted.com/talks/gary_wolf_the_quantified_self
× Ziebland, S., & Wyke, S. (2012). Health and illness in a connected world: how might sharing experiences on the internet affect people's health? The Milbank Quarterly, 90(2), 219–249.