Toward Health Information Technology that Supports Overweight/Obese Women in Addressing Emotion- and Stress-Related Eating

Emotion- and stressed-related eating (ESRE) is associated with weight management difficulties and is more likely to affect women than men. Additionally, health information technology (HIT) for weight management tends to be less effective for women than it is for men, and less effective for people who engage in ESRE. Therefore, this study explores how HIT can support overweight/obese women curb ESRE behavior. Study participants, all adult overweight/obese women (BMI ' 25), logged dietary intake for 10 days with the Lose It! smartphone app as an elicitation exercise. Cross sectional, semi-structured interviews (N = 22) were then conducted to explore technology support needs concerning ESRE behavior. Findings revealed participants had the following needs: holistic health goal development, building motivation to achieve goals, and assistance with handling stress. Resulting HIT guidelines include supporting holistic health goals, developing and sustaining motivation, exchange of emotional support, understanding of behavior, and change in ESRE mindset.

[1]  M. M. Boggiano,et al.  Profiling motives behind hedonic eating. Preliminary validation of the Palatable Eating Motives Scale , 2014, Appetite.

[2]  Michelle Ortlipp Keeping and Using Reflective Journals in the Qualitative Research Process. , 2008 .

[3]  My Bui,et al.  When food is more than nutrition: Understanding emotional eating and overconsumption , 2013 .

[4]  Gregory D. Abowd,et al.  Barriers and Negative Nudges: Exploring Challenges in Food Journaling , 2015, CHI.

[5]  Krzysztof Z. Gajos,et al.  Platemate: crowdsourcing nutritional analysis from food photographs , 2011, UIST.

[6]  David A. Huffaker,et al.  Mobile health apps: adoption, adherence, and abandonment , 2015, UbiComp/ISWC Adjunct.

[7]  Clare E Collins,et al.  Behavioural factors related with successful weight loss 15 months post-enrolment in a commercial web-based weight-loss programme , 2011, Public Health Nutrition.

[8]  Ilkka Korhonen,et al.  Mobile Diary for Wellness Management—Results on Usage and Usability in Two User Studies , 2008, IEEE Transactions on Information Technology in Biomedicine.

[9]  Giuseppe Riva,et al.  Can relaxation training reduce emotional eating in women with obesity? An exploratory study with 3 months of follow-up. , 2009, Journal of the American Dietetic Association.

[10]  Costas A. Anastasiou,et al.  The role of social support in weight loss maintenance: results from the MedWeight study , 2016, Journal of Behavioral Medicine.

[11]  Jutta Mata,et al.  Mediators of Weight Loss and Weight Loss Maintenance in Middle‐aged Women , 2010, Obesity.

[12]  Sean A. Munson,et al.  Crumbs: Lightweight Daily Food Challenges to Promote Engagement and Mindfulness , 2016, CHI.

[13]  Predrag V. Klasnja,et al.  Good or bad, ups and downs, and getting better: Use of personal health data for temporal reflection in chronic illness , 2016, Int. J. Medical Informatics.

[14]  Christian Koehler,et al.  Why we use and abandon smart devices , 2015, UbiComp.

[15]  E. Gibson,et al.  The psychobiology of comfort eating: implications for neuropharmacological interventions , 2012, Behavioural pharmacology.

[16]  L. Canetti,et al.  Food and emotion , 2002, Behavioural Processes.

[17]  Andrea Grimes Parker,et al.  Reflection-through-performance: personal implications of documenting health behaviors for the collective , 2014, Personal and Ubiquitous Computing.

[18]  Anton J. Kuzel,et al.  Sampling in qualitative inquiry. , 1992 .

[19]  E. Deci,et al.  Self-Determination Theory Applied to Health Contexts , 2012, Perspectives on psychological science : a journal of the Association for Psychological Science.

[20]  Sean A. Munson,et al.  A framework for self-experimentation in personalized health , 2016, J. Am. Medical Informatics Assoc..

[21]  Margaret Volante Qualitative research. , 2008, Nurse researcher.

[22]  Andrea Z LaCroix,et al.  Long-Term Body Weight Maintenance among StrongWomen–Healthy Hearts Program Participants , 2017, Journal of environmental and public health.

[23]  Evan M. Forman,et al.  Perceptions of the feasibility and acceptability of a smartphone application for the treatment of binge eating disorders: Qualitative feedback from a user population and clinicians , 2015, Int. J. Medical Informatics.

[24]  H. Ellgring,et al.  Chocolate eating in healthy men during experimentally induced sadness and joy , 2002, Appetite.

[25]  Sandrine Péneau,et al.  The associations between emotional eating and consumption of energy-dense snack foods are modified by sex and depressive symptomatology. , 2014, The Journal of nutrition.

[26]  Paul Johns,et al.  Food and Mood: Just-in-Time Support for Emotional Eating , 2013, 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction.

[27]  James Fogarty,et al.  Rethinking the Mobile Food Journal: Exploring Opportunities for Lightweight Photo-Based Capture , 2015, CHI.

[28]  Matthew Chalmers,et al.  Personal tracking as lived informatics , 2014, CHI.

[29]  Marydee A. Spillett Peer Debriefing: Who, What, When, Why, How , 2003 .

[30]  Gaetano Borriello,et al.  2013 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops Design and Evaluation of a Food Index-based Nutrition Diary , 2022 .

[31]  Sean A. Munson,et al.  Beyond Abandonment to Next Steps: Understanding and Designing for Life after Personal Informatics Tool Use , 2016, CHI.

[32]  Sean A. Munson,et al.  TummyTrials: A Feasibility Study of Using Self-Experimentation to Detect Individualized Food Triggers , 2017, CHI.

[33]  Geir Egil Eide,et al.  Effective behaviour change techniques for physical activity and healthy eating in overweight and obese adults; systematic review and meta-regression analyses , 2017, International Journal of Behavioral Nutrition and Physical Activity.

[34]  G. Borriello,et al.  Simplifying Mobile Phone Food Diaries Design and Evaluation of a Food Index-Based Nutrition Diary , 2013 .

[35]  Sean A. Munson,et al.  When Personal Tracking Becomes Social: Examining the Use of Instagram for Healthy Eating , 2017, CHI.

[36]  C. Champagne,et al.  Weight loss during the intensive intervention phase of the weight-loss maintenance trial. , 2008, American journal of preventive medicine.

[37]  Jacqueline Bidgood,et al.  An exploration of obese adults’ experience of attempting to lose weight and to maintain a reduced weight , 2005 .

[38]  Lena Mamykina,et al.  MAHI: investigation of social scaffolding for reflective thinking in diabetes management , 2008, CHI.

[39]  I. Dey Qualitative Data Analysis: A User Friendly Guide for Social Scientists , 1993 .

[40]  Phoebe Sengers,et al.  Fit4life: the design of a persuasive technology promoting healthy behavior and ideal weight , 2011, CHI.

[41]  Sean A. Munson,et al.  Finding the Right Fit: Understanding Health Tracking in Workplace Wellness Programs , 2017, CHI.

[42]  A. Huberman,et al.  Qualitative Data Analysis: A Methods Sourcebook , 1994 .

[43]  Madhu C. Reddy,et al.  "It's Definitely Been a Journey": A Qualitative Study on How Women with Eating Disorders Use Weight Loss Apps , 2017, CHI.

[44]  R. Callister,et al.  eHealth interventions for the prevention and treatment of overweight and obesity in adults: a systematic review with meta‐analysis , 2015, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[45]  Jacquelynne S Eccles,et al.  Rebranding exercise: closing the gap between values and behavior , 2011, The international journal of behavioral nutrition and physical activity.

[46]  Valerie Swigart,et al.  Experiences of Self-Monitoring: Successes and Struggles During Treatment for Weight Loss , 2009, Qualitative health research.

[47]  J. Loewy,et al.  Identifying predictive variables for long-term weight change after participation in a weight loss program. , 1993, Journal of the American Dietetic Association.

[48]  Kevin D Hall,et al.  NIH working group report: Innovative research to improve maintenance of weight loss , 2015, Obesity.

[49]  Paul Johns,et al.  Predicting "About-to-Eat" Moments for Just-in-Time Eating Intervention , 2016, Digital Health.

[50]  G. Horgan,et al.  Weight outcomes audit in 1.3 million adults during their first 3 months’ attendance in a commercial weight management programme , 2015, BMC Public Health.

[51]  Klaus P. Ebmeier,et al.  Magnetic resonance imaging studies in unipolar depression: Systematic review and meta-regression analyses , 2012, European Neuropsychopharmacology.

[52]  Edith Talina Luhanga,et al.  Evaluating effectiveness of stimulus control, time management and self-reward for weight loss behavior change , 2015, UbiComp/ISWC Adjunct.

[53]  Barbara E Ainsworth,et al.  Use of nonprescription dietary supplements for weight loss is common among Americans. , 2007, Journal of the American Dietetic Association.

[54]  Stephan Rössner,et al.  The Change in Eating Behaviors in a Web-Based Weight Loss Program: A Longitudinal Analysis of Study Completers , 2014, Journal of medical Internet research.

[55]  Steven E. Stemler,et al.  An Overview of Content Analysis. , 2001 .

[56]  Jacquelynne S Eccles,et al.  Type of physical activity goal influences participation in healthy midlife women. , 2008, Women's health issues : official publication of the Jacobs Institute of Women's Health.

[57]  Johnny Saldaña,et al.  The Coding Manual for Qualitative Researchers , 2009 .

[58]  Jason Tang,et al.  How can weight-loss app designers' best engage and support users? A qualitative investigation. , 2015, British journal of health psychology.

[59]  Richard Harper,et al.  Celebratory technology: new directions for food research in HCI , 2008, CHI.