MAHI: investigation of social scaffolding for reflective thinking in diabetes management

In the recent years, the number of individuals engaged in self-care of chronic diseases has grown exponentially. Advances in computing technologies help individuals with chronic diseases collect unprecedented volumes of health-related data. However, engaging in reflective analysis of the collected data may be challenging for the untrained individuals. We present MAHI, a health monitoring application that assists newly diagnosed individuals with diabetes in acquiring and developing reflective thinking skills through social interaction with diabetes educators. The deployment study with twenty five newly diagnosed individuals with diabetes demonstrated that MAHI significantly contributed to individuals' achievement of their diabetes management goals (changing diet). More importantly, MAHI inspired individuals to adopt Internal Locus of Control, which often leads to persistent engagement in self-care and positive health outcomes.

[1]  E. Langer,et al.  The effects of choice and enhanced personal responsibility for the aged: a field experiment in an institutional setting. , 1976, Journal of personality and social psychology.

[2]  K. Wallston,et al.  Development and validation of the health locus of control (HLC) scale. , 1976, Journal of consulting and clinical psychology.

[3]  J. Baron Thinking and Deciding , 2023 .

[4]  K. Wallston,et al.  The Relationship Between Health Beliefs, Adherence, and Metabolic Control of Diabetes , 1992, The Diabetes educator.

[5]  Vannevar Bush,et al.  As we may think , 1945, INTR.

[6]  K. Knorr Cetina Epistemic Cultures , 1999 .

[7]  Gregory D. Abowd,et al.  Charting past, present, and future research in ubiquitous computing , 2000, TCHI.

[8]  R. Hastie Problems for judgment and decision making. , 2001, Annual review of psychology.

[9]  Elizabeth D. Mynatt,et al.  Digital family portraits: supporting peace of mind for extended family members , 2001, CHI.

[10]  Vimla L. Patel,et al.  Emerging paradigms of cognition in medical decision-making , 2002, J. Biomed. Informatics.

[11]  T. Bodenheimer,et al.  Patient self-management of chronic disease in primary care. , 2002, JAMA.

[12]  E. Wagner,et al.  Care for chronic diseases , 2002, BMJ : British Medical Journal.

[13]  Allison Druin,et al.  Technology probes: inspiring design for and with families , 2003, CHI '03.

[14]  Daniel Fitton,et al.  Probing Technology with Technology Probes , 2004 .

[15]  K. Squire,et al.  Design-Based Research: Putting a Stake in the Ground , 2004 .

[16]  Sunny Consolvo,et al.  The CareNet Display: Lessons Learned from an In Home Evaluation of an Ambient Display , 2004, UbiComp.

[17]  J. McGill,et al.  Development and Validation of the Diabetes Quality of Life Brief Clinical Inventory , 2004 .

[18]  K. Weick,et al.  Organizing and the Process of Sensemaking , 2005 .

[19]  Paul Lukowicz,et al.  Analysis of Chewing Sounds for Dietary Monitoring , 2005, UbiComp.

[20]  Silvia Lindtner,et al.  Fish'n'Steps: Encouraging Physical Activity with an Interactive Computer Game , 2006, UbiComp.

[21]  James A. Landay,et al.  Design requirements for technologies that encourage physical activity , 2006, CHI.

[22]  Lena Mamykina,et al.  Investigating health management practices of individuals with diabetes , 2006, CHI.

[23]  Paul Lukowicz,et al.  Detecting and Interpreting Muscle Activity with Wearable Force Sensors , 2006, Pervasive.

[24]  Jane Yung-jen Hsu,et al.  The Diet-Aware Dining Table: Observing Dietary Behaviors over a Tabletop Surface , 2006, Pervasive.

[25]  Abigail Sellen,et al.  Do life-logging technologies support memory for the past?: an experimental study using sensecam , 2007, CHI.

[26]  Dorrit Billman,et al.  Medical sensemaking with entity workspace , 2007, CHI.