dyadic illness management; ambulatory assessment application; social support; experience sampling; MobileCoach; Type II diabetes; communal dyadic coping
Lüscher Janina, Kowatsch Tobias, Boateng George, Santhanam Prabhakaran, Bodenmann Guy, Scholz Urte (2019), Social Support and Common Dyadic Coping in Couples' Dyadic Management of Type II Diabetes: Protocol for an Ambulatory Assessment Application, in JMIR Research Protocols
, 8(10), e13685-e13685.
Boateng George, Santhanam Prabhakaran, Lüscher Janina, Scholz Urte, Kowatsch Tobias (2019), Poster: DyMand -- An Open-Source Mobile and Wearable System for Assessing Couples' Dyadic Management of Chronic Diseases, in MobiCom '19: The 25th Annual International Conference on Mobile Computing and Networking
, Los Cabos MexicoACM Digital Library, Los Cabos.
Boateng George, Santhanam Prabhakaran, Lüscher Janina, Scholz Urte, Kowatsch Tobias (2019), VADLitean open-source lightweight system for real-time voice activity detection on smartwatches, in the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2019 ACM I
, London, United KingdomACM Digital Library , London.
Theoretical background: Diabetes mellitus Type II is a common chronic disease. To manage blood glucose levels patients need to follow medical recommendations for healthy eating, physical activity, and medication adherence in their everyday life. Illness management is mainly shared with partners or spouses and may involve social support and common dyadic coping (CDC). Received social support and common dyadic coping have been identified as having implications for people’s health behavior and well-being. Visible received support, however, may also be negatively related to people’s well-being. Thus, the concept of invisible social support was introduced recently: that is, support provided that occurs outside of the awareness of the recipient or that is not encoded as support. So far, however, it is unknown which of these concepts (visible, invisible support, CDC) displays the most beneficial associations with health behavior and well-being when considered together in the context of illness management in couples. Furthermore, measurement of support and CDC in people’s everyday lives is usually by self-report only. Thus, more objective operationalisations of these constructs might solve common problems connected to self-report. Therefore, a mobile application that utilize objective sensor data in combination with self-reports need to be developed.Aim of the project: The aims of this proposed project are to systematically investigate the unique contributions of visible and invisible social support and CDC on health behaviors involved in diabetes management (e.g., physical activity, eating, medication adherence) and well-being of diabetes Type II patients and their partners. And to develop an ambulatory assessment application for smartphones for the open source behavioral intervention platform MobileCoach (AAMC) that allows the objective assessment of the core study constructs and outcomes in couples’ everyday lives.Design: In order to address these aims, the proposed study comprises two phases of data collection. The first phase is an experience sampling phase in daily life of N = 180 diabetes Type II patients and their partners. For this assessment phase, a novel ambulatory assessment application as an open source extension of the existing MobileCoach platform will be developed by applying design science research. The second phase is an observational study in the lab.Method: During the experience sampling phase participating couples will wear a mobile phone on their hip for seven consecutive days. The newly developed AAMC will capture couple’s conversations by random audio recordings of five minutes per hour using the smartphone’s microphones. Directly afterwards, participants will be prompted to answer very few questions on social support and CDC experienced in the past five minutes matching the audio recording. These data allow the (semi-)objective assessment of invisible support and CDC. At the same time, the newly developed AAMC will be able to recognize affect based on prosodic, spectral and sentiment analyses. This will help to deepen our understanding of when support and CDC is particularly effective. Finally, the AAMC will integrate the measurement of accelerometer data from the smartphone sensor. Dietary behavior and medication adherence will be assessed daily in end-of-day diaries. The observational study will examine visible and invisible support and CDC by analyzing couples’ videotaped discussions about diabetes-related concerns. The second phase complements the experience sampling sequence, in that the former will be an observation of naturalistic behavior in couples’ everyday lives and will thus not be able to capture a full discussion about diabetes-related concerns.Significance of the planned research: For further research and practice, it is crucial to identify the impact of social support and CDC on couple’s dyadic management of diabetes Type II in daily life. So far, visible and invisible support and CDC have not been analyzed together in daily life of couples coping with a chronic illness. It is thus unknown which of these concepts displays the most beneficial associations with health behaviors and well-being. Furthermore, the newly developed AAMC will make a key contribution with regard to the objective operationalisations of invisible support, CDC and physical activity. The automatic recognition of affect in speech will further our understanding of the conditions in which support and CDC are most effective. The results of the proposed project will provide a sound basis for the theory- and evidence-based development of dyadic interventions to change health behavior in the context of couple’s dyadic illness management.