Social Support and Common Dyadic Coping in Couples' Dyadic Management of Type II Diabetes: Protocol for an Ambulatory Assessment Application

Lüscher, Janina; Kowatsch, Tobias; Boateng, George; Santhanam, Prabhakaran; Bodenmann, Guy; Scholz, Urte

doi:10.2196/13685

Cited by 14 publications

(11 citation statements)

References 111 publications

(177 reference statements)

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“…While observations in the lab have been conducted in previous studies on support provision and relationship health (e.g., Lawrence et al, 2008 ; Jensen et al, 2013 ), a future way to go could lie in naturalistic observations of support instances in daily life via audio recordings (cf. Lüscher et al, 2019 ), using an electronically activated recorder (EAR; Mehl et al, 2001 ).…”

Section: Discussionmentioning

confidence: 99%

“We Feel Good”: Daily Support Provision, Health Behavior, and Well-Being in Romantic Couples

2021

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Intimate partners are an important source of support when pursuing health goals. A vast amount of literature documents the role of social support in alleviating recipients’ distress and facilitating health behaviors. Less studied is the phenomenon that providing support may entail a benefit for the provider, particularly in the context of health behavior change. In the present study, we investigated whether providing social support in daily life would be associated with more health behavior, and emotional and relational well-being that same day, using a sample of romantic couples aiming to become more physically active. Ninety-nine inactive and overweight heterosexual romantic couples (=198 individuals) participated in this dyadic daily diary study. Both partners reported on the provision of social support, positive and negative affect, and relationship satisfaction in electronic end-of-day diaries across 14 consecutive days. Moderate-to-vigorous physical activity (MVPA) was objectively assessed via triaxial accelerometers (Actigraph GT3X+). Using the Actor-Partner Interdependence Model (APIM), dyadic data analyses indicated that providing support to the partner was associated with higher own MVPA, more own positive affect, less own negative affect, and more own relationship satisfaction (actor effects), over and above the effect of support provision on outcomes in the other partner (partner effects). The present findings suggest that the provision of daily social support in couples is strongly associated with enhanced well-being not only at a personal level but also at a relational level. Providing social support may also serve the function of relationship maintenance. Thus, shifting the focus away from the recipient to examine beneficial effects of social support in providers is highly relevant. Future research should address the question of when, why, and how giving support is beneficial.

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“…Furthermore, social support from partners in chronic disease management has been shown to either have positive or negative effects on the emotional well-being of patients [15,50,76]. Because of the importance of emotions among couples, researchers are working towards understanding the emotional processes that take place in intimate relationships (e.g., [34,90]) and the link between emotions and social support in couples' dyadic management of chronic diseases [64]. Consequently, being able to automatically recognize each partner's emotions could enable the research of social and health psychologists, and also inform the development of dyadic interventions (where partners are both involved e.g., [54]) to improve the emotional well-being, relationship quality, and chronic disease management of couples.…”

Section: Introductionmentioning

confidence: 99%

Emotion Recognition among Couples: A Survey

Boateng¹,

Fleisch²,

Kowatsch³

2022

Preprint

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Couples' relationships affect the physical health and emotional well-being of partners. Automatically recognizing each partner's emotions could give a better understanding of their individual emotional well-being, enable interventions and provide clinical benefits.In the paper, we summarize and synthesize works that have focused on developing and evaluating systems to automatically recognize the emotions of each partner based on couples' interaction or conversation contexts. We identified 28 articles from IEEE, ACM, Web of Science, and Google Scholar that were published between 2010 and 2021. We detail the datasets, features, algorithms, evaluation, and results of each work as well as present main themes. We also discuss current challenges, research gaps and propose future research directions. In summary, most works have used audio data collected from the lab with annotations done by external experts and used supervised machine learning approaches for binary classification of positive and negative affect. Performance results leave room for improvement with significant research gaps such as no recognition using data from daily life. This survey will enable new researchers to get an overview of this field and eventually enable the development of emotion recognition systems to inform interventions to improve the emotional well-being of couples.CCS Concepts: • General and reference → Surveys and overviews; • Human-centered computing → Human computer interaction (HCI); • Applied computing → Psychology.

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“…This review provides only a snapshot of a rapidly evolving research area. The studies identified included, for instance, some study protocols for intervention studies that seem to be currently underway (Wittmann et al, 2017 ; Lüscher et al, 2019 ). Future reviews should also overcome the distinction between DC and spousal support literature.…”

Section: Discussionmentioning

confidence: 99%

Dyadic Coping in Couples Facing Chronic Physical Illness: A Systematic Review

et al. 2021

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Objective: Chronic physical illness affects not only patients but also their partners. Dyadic coping (DC)—the ways couples cope in dealing with a stressor such as chronic illness—has received increased attention over the last three decades. The aim of the current study was to summarize the state of research on DC in couples with chronic physical illnesses.Methods: We conducted a systematic review of qualitative, quantitative, and mixed-methods studies published between 1990 and 2020, assessing DC in couples affected by severe physical illnesses. We used DC and related search terms for the literature search in Psycinfo, Psyndex, and Medline. Five thousand three hundred thirty studies were identified in three electronic databases and 49 of these were included in the review (5,440 individuals reported on 2,820 dyads). We excluded studies on cancer, cardiovascular disease, and multiple sclerosis because of existing reviews in the respective fields. Half of the studies included were on diabetes. Other studies were on arthritis, chronic obstructive pulmonary disease (COPD), cystic fibrosis, human immunodeficiency virus (HIV), Huntington's disease, lupus erythematosus, Parkinson's disease, renal diseases, stroke, and endometriosis. Two raters extracted data using a predefined protocol, including study quality. Results were collated in a narrative synthesis organized by illness and DC operationalization.Results: Overall, DC was associated with beneficial outcomes in physical health, well-being, and relationship satisfaction. Differential effects became apparent for certain chronic conditions potentially depending on certain disease characteristics, such as early-onset, sudden-onset, or life-threatening conditions.Conclusion: Facing challenges together as a couple seemed indispensable for adapting to a diverse range of demands related to chronic illnesses with some specific demands of particular chronic diseases. There is a need for the development of truly dyadic interventions with an eye on the specific challenges of the various chronic conditions.

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“…In developing DyMand, experts from the field of computer science, information systems, and health psychology used justificatory knowledge from prior work [19,32,42,46,58] about social support, CDC, health behavior, and emotional well-being to derive a list of design specifications that are important for collecting corresponding data in-situ, in the context of chronic disease management. We describe the specifications.…”

Section: Development: System Designmentioning

confidence: 99%

“…Furthermore, the requirement for collecting this data when partners are interacting ensures there is a high likelihood of capturing conversations between partners as compared to collecting data at a random or scheduled time. Sensor data such as audio, heart rate, gestures, physical activity, and step count could be used to manually and automatically infer behavioral information such as social support, CDC, emotional well-being, and health behavior, which are relevant for chronic disease management [42]. Audio for example can be used to code constructs such as emotions, social support, and CDC.…”

Section: Multimodal Sensor Data Collectionmentioning

confidence: 99%

Development, Deployment, and Evaluation of DyMand -- An Open-Source Smartwatch and Smartphone System for Capturing Couples' Dyadic Interactions in Chronic Disease Management in Daily Life

Boateng¹,

Santhanam²,

Fleisch³

et al. 2022

Preprint

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Dyadic interactions of couples are of interest as they provide insight into relationship quality and chronic disease management.Currently, ambulatory assessment of couples' interactions entails collecting data at random or scheduled times which could miss significant couples' interaction/conversation moments. In this work, we developed, deployed and evaluated DyMand, a novel opensource smartwatch and smartphone system for collecting self-report and sensor data from couples based on partners' interaction moments. Our smartwatch-based algorithm uses the Bluetooth signal strength between two smartwatches each worn by one partner, and a voice activity detection machine-learning algorithm to infer that the partners are interacting, and then to trigger data collection.We deployed the DyMand system in a 7-day field study and collected data about social support, emotional well-being, and health behavior from 13 (N=26) Swiss-based heterosexual couples managing diabetes mellitus type 2 of one partner. Our system triggered 99.1% of the expected number of sensor and self-report data when the app was running, and 77.6% of algorithm-triggered recordings contained partners' conversation moments compared to 43.8% for scheduled triggers. The usability evaluation showed that DyMand was easy to use. DyMand can be used by social, clinical, or health psychology researchers to understand the social dynamics of couples in everyday life, and for developing and delivering behavioral interventions for couples who are managing chronic diseases. CCS Concepts: • Human-centered computing → Ubiquitous and mobile computing; • Applied computing → Consumer health; Psychology.

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Social Support and Common Dyadic Coping in Couples' Dyadic Management of Type II Diabetes: Protocol for an Ambulatory Assessment Application

Cited by 14 publications

References 111 publications

“We Feel Good”: Daily Support Provision, Health Behavior, and Well-Being in Romantic Couples

Emotion Recognition among Couples: A Survey

Dyadic Coping in Couples Facing Chronic Physical Illness: A Systematic Review

Development, Deployment, and Evaluation of DyMand -- An Open-Source Smartwatch and Smartphone System for Capturing Couples' Dyadic Interactions in Chronic Disease Management in Daily Life

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