Five icons representing the key concepts in the Socio-cognitive framework. They are aspirations, data exposure, stories, belongingess, and impediments.

The Socio-cognitive Framework consists of concepts and processes that facilitate social interactions and enhance users’ cognition toward improving their ability to manage their health. (Saksono and Parker, 2024)

Read the ToCHI paper

What is the framework for?

The Sociocognitive Framework explains how personal informatics can be improved by including protective social factors like family and community support. It is for designing personal informatics tools that facilitate social interactions. These interactions can enhance users’ cognition and improve their ability to manage their health

This framework argues that amplifying protective social factors is important for promoting health behavior and reducing health disparities, especially in communities that face the most challenges. By focusing on family, friends, and neighbors working together, these tools can help people in a community stay healthier.

This website is a summary of the Saksono and Parker (2024) paper. Please refer to the paper for details.

What is the theoretical foundation behind the framework?

The theoretical foundation is Social Cognitive Theory or SCT (Bandura, 1977, 1986, 1991, 1998, 1999, 2001). Read more about SCT here.

What is the research behind the framework?

The framework is built upon our multi-year Human-Computer Interaction and Health research (which involved 153 people over seven years). This research was focused on families in low-income neighborhoods who often faced more obstacles to staying healthy. Papers reporting this research have been published in ACM CHI and CSCW (Saksono et al., 2015, 2017, 2018, 2019, 2020, 2021, 2023). Read more about the research here.

What should I remember about this framework?

Five social and cognitive concepts are influencing the impact of personal informatics on users’ attitudes and behavior. These concepts are: Aspirations, Data exposure, Stories, Belongingness, and Impediments.

Aspirations

Personal informatics tools that match a person’s aspirations are more likely to make them feel positive about using the tool and act on the health behavior.

Data Exposure

Personal informatics tools that share peers’ data can help users set goals for their own behavior. Reaching or missing those goals can make people feel more or less confident in their ability to manage their health.

Stories

Personal informatics tools that share peers’ stories can help users build self-efficacy and outcome expectations in doing the health behavior.

Belongingness

Personal informatics tools that make users feel a sense of belonging can improve their outcome expectations about doing the health behaviors.

Impediments

Marginalization makes it harder for users to engage in healthy behaviors and weakens the effectiveness of personal informatics tools.

How do I use these concepts?

1. Use the concept’s hypothesis in your tech design

Each concept comes with a design hypothesis. This hypothesis is a new scientific idea in the form of theoretical statements that invites researchers and designers to test further (Shoemaker et al., 2004). By testing, we mean implementing the hypothesis in the technology design and evaluating the design.

2. Apply the design recommendations

Each concept also comes with a set of design recommendations. These are meant to make applying the concepts easier.

3. Evaluate the effect of the concept

We also added the process that links each concept with attitudes and behavior. The goal is to help evaluate your technology design. For example, if a concept is hypothesized to target self-efficacy, then the evaluation study should examine self-efficacy.

Incorporate impediments in the evaluation study because they could hinder the impact of the concept.

Why are social factors important for personal informatics?

Health behavior is shaped by both personal and social factors, but social factors often have a bigger impact. These social factors include the conditions people are born, live, and age in, which are influenced by inequalities in power, economy, and resources.

For example, lower education — a key social determinant of health — can lead to lower health literacy, low-paying jobs, unemployment, poor access to healthcare, and living in unsafe neighborhoods. All of these challenges increase the risk of chronic diseases. Another example is how people with lower socioeconomic status tend to be less physically active, not because of a lack of willpower, but because of public policies that create barriers like fewer exercise facilities and unsafe environments.

These social factors hinder the impact of personal informatics tools, especially those that are focused on individual efforts.

How can we address adverse social conditions?

Protective social factors can help offset negative social conditions (Braveman and Gottlieb, 2014). These factors include social support, in the form of informational, emotional, belongingness, and tangible supports (Uchino, 14).

For example, support from family and communities can boost physical activity, healthy eating, and mental health, while strong social capital can lower the risk of obesity and diabetes.

Because social factors have a big impact on health, we suggest that personal informatics research and design should focus on using technology to amplify protective social factors, such as social support.

Recommended citation?

Herman Saksono and Andrea G. Parker. 2024. Socio-Cognitive Framework for Personal Informatics: A Preliminary Framework for Socially-Enabled Health Technologies. ACM Trans. Comput.-Hum. Interact. 31, 3, Article 42 (August 2024), 41 pages. DOI: https://doi.org/10.1145/3674504

Is there a video explaining this framework?

Yes

Further Reading

  • H. Saksono, C. Castaneda-sceppa, J. Hoffman, M. S. El-Nasr, V. Morris, and A. G. Parker. 2018. Family health promotion in low-SES neighborhoods: A two-month study of wearable activity tracking. In Proceedings of the Conference on Human Factors in Computing Systems (CHI ’18). 1–13. DOI: https://doi.org/10.1145/3173574.3173883
  • H. Saksono, C. Castaneda-Sceppa, J. Hoffman, V. Morris, M. S. El-Nasr, and A. G. Parker. 2020. Storywell: Designing for family fitness app motivation by using social rewards and reflection. In Proceedings of the Conference on Human Factors in Computing Systems Proceedings (CHI ’20). 1–30. DOI: https://doi.org/10.1145/3313831.3376686
  • H. Saksono, C. Castaneda-Sceppa, J. Hoffman, M. Seif El-Nasr, V. Morris, and A. G. Parker. 2019. Social reflections on fitness tracking data: A study with families in low-SES neighborhoods. In Proceedings of the Conference on Human Factors in Computing Systems Proceedings (CHI ’19). 14. DOI: https://doi.org/10.1145/3290605.3300543
  • H. Saksono, C. Castaneda-Sceppa, J. A. Hoffman, V. Morris, M. S. El-Nasr, and A. G. Parker. 2021. StoryMap: Using social modeling and self-modeling to support physical activity among families of low-SES backgrounds. In Proceedings of the Conference on Human Factors in Computing Systems (CHI ’21). 14 pages. DOI: https://doi.org/10.1145/3411764. 3445087
  • H. Saksono and A. G. Parker. 2017. Reflective informatics through family storytelling: Self-discovering physical activity predictors. In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI ’17). 5232–5244. DOI: https://doi.org/10.1145/3025453.3025651
  • H. Saksono, V. Morris, A. G. Parker, V. Morris, and K. Z. Gajos. 2023. Evaluating similarity variables for peer matching in digital health storytelling. Proceedings of the ACM on Human-Computer Interaction 7, CSCW2 Article 269 (Oct. 2023), 25 pages, DOI: https://doi.org/10.1145/3610060. 1–25.
  • H. Saksono, A. Ranade, G. Kamarthi, C. Castaneda-Sceppa, J. A. Hoffman, C. Wirth, and A. G. Parker. 2015. Spaceship launch: Designing a collaborative exergame for families. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW ’15). 1776–1787. DOI: https://doi.org/10.1145/2675133.2675159

References

  1. A. Bandura. 1998. Health promotion from the perspective of social cognitive theory. Psychology and Health 13, 4 (1998), 623–649. DOI: https://doi.org/10.1080/08870449808407422
  2. A. Bandura. 1977. Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review 84, 2 (1977), 191–215. DOI: https://doi.org/10.1037/0033-295X.84.2.191
  3. A. Bandura. 1999. Social cognitive theory: An agentic perspective. Asian Journal of Social Psychology 2, (1999), 21–41. DOI: https://doi.org/10.1111/1467-839X.00024
  4. A. Bandura. 2001. Social cognitive theory of mass communication. Media Psychology 3, 3 (2001), 265–299. DOI: https://doi.org/10.1207/S1532785XMEP0303_03
  5. A. Bandura. 1991. Social cognitive theory of self-regulation. Organizational Behavior and Human Decision Processes 50, (1991), 248–287. DOI: https://doi.org/10.1016/0749-5978(91)90022-L
  6. A. Bandura. 1986. Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice Hall. DOI: http: //dx.doi.org/10.1037/13273-005P.
  7. P. Braveman and L. Gottlieb. 2014. The social determinants of health: It’s time to consider the causes of the causes. Public Health Reports 129, 1_suppl2 (Jan. 2014), 19–31. DOI: https://doi.org/10.1177/00333549141291S206
  8. J. Shoemaker, J. W. Tankard Jr., and D. L. Lasorsa. 2004. How to Build Social Science Theories. Sage Publications, Inc.
  9. Bert N. Uchino. 2014. Social Support and Physical Health. Social Support and Physical Health. 1–15. DOI: https://doi.org/10.12987/yale/9780300102185.001.0001.