Design and Evaluation of a Device for Ecological Momentary Assessment with Workers in a Garment Factory (original) (raw)
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The Design of Ecological Momentary Assessment Technologies
Interacting with Computers, 2020
Ecological Momentary Assessment (EMA) methods and technologies, designed to support the self-report of experience in the moment of daily life, have long been considered poised to revolutionize human-centred research, the practice of design and mental healthcare. The history of EMA is inextricably linked to technology, and mobile devices embody many of the characteristics required to support these methods. However, significant barriers to the design and adoption of these systems remain, including challenges of user engagement, reporting burden, data validity and honest disclosure. While prior research has examined the feasibility of a variety of EMA systems, few reviews have attended to their design. Through inter-disciplinary narrative literature review (n = 342), this paper presents a characterization of the EMA technology design space, drawing upon a diverse set of literatures, contexts, applications and demographic groups. This paper describes the options and strategies available...
Ecological Momentary Assessment
Annual Review of Clinical Psychology, 2008
Assessment in clinical psychology typically relies on global retrospective self-reports collected at research or clinic visits, which are limited by recall bias and are not well suited to address how behavior changes over time and across contexts. Ecological momentary assessment (EMA) involves repeated sampling of subjects' current behaviors and experiences in real time, in subjects' natural environments. EMA aims to minimize recall bias, maximize ecological validity, and allow study of microprocesses that influence behavior in real-world contexts. EMA studies assess particular events in subjects' lives or assess subjects at periodic intervals, often by random time sampling, using technologies ranging from written diaries and telephones to electronic diaries and physiological sensors. We discuss the rationale for EMA, EMA designs, methodological and practical issues, and comparisons of EMA and recall data. EMA holds unique promise to advance the science and practice of clinical psychology by shedding light on the dynamics of behavior in real-world settings.
User profiles of an electronic mental health tool for ecological momentary assessment: MEmind
International journal of methods in psychiatric research, 2017
Ecological momentary assessment (EMA) is gaining importance in psychiatry. This article assesses the characteristics of patients who used a new electronic EMA tool: the MEmind Wellness Tracker. Over one year, 13811 adult outpatients in our Psychiatry Department were asked to use MEmind. We collected information about socio-demographic data, psychiatric diagnoses, illness severity, stressful life events and suicidal thoughts/behavior. We compared active users (N = 2838) and non-active users (N = 10,973) of MEmind and performed a Random Forest analysis to assess which variables could predict its use. Univariate analyses revealed that MEmind-users were younger (42.2 ± 13.5 years versus 48.5 ± 16.3 years; χ(2) = 18.85; P < 0.001) and more frequently diagnosed with anxiety related disorders (57.9% versus 46.7%; χ(2) = 105.92; P = 0.000) than non-active users. They were more likely to report thoughts about death and suicide (up to 24% of active users expressed wish for death) and had...
2020
The COVID-19 pandemic continues to affect work life and the mental health burden globally. Asking millions of workers to work from home or go back to work with the risk of being infected is a problematic aspect of the pandemic increasing stress and negatively impacting productivity. The objective of occupational and precision health research and practice is to precisely measure and sustain workers' mental health and productivity. Best practices for the workplace propose the need to identify the early effects of factors such as psychological distress and develop interventions for the proactive treatment of pre-disease stages of mental disorders. In this position paper, we propose the development of a novel platform for workers that integrates continuous sensing and long-term self-regulation interventions. The Stanford Wellbeing and Emotional Education Technology Platform (SWEET) is a digital wellbeing and occupational health platform designed as a compendium of ubiquitous technology modules to help manage stress and productivity, during and post-pandemic, while amplifying research on occupational precision mental health. Here, we discuss adapting our system in the wake of COVID-19.
Ecological Momentary Assessment Tools: Lessons Learned from an HCI Perspective
Human-Computer Interaction. Design and User Experience, 2020
Ecological Momentary Assessment (EMA) is a popular family of tools in behavioural research that is known for its ability to capture in detail fluctuating phenomena while minimizing bias. They consist of short questions to be answered many times per day. Still, participants often perceive EMA-based studies as burdening, resulting in a low compliance rate. A good design of the EMA study-in terms of what to measure, how to put questions to the users, and when-is fundamental to minimize the above drawback and improve participants' compliance. Our research focuses on the "how" dimension of EMA design, looking at it through the lens of HCI. We performed an empirical study devoted to explore this specific design aspect, exposing 20 users to different formulations of EMA questions in the same domain for 2 weeks. From the study results, we distilled some lessons learned related to the design of the EMA User Experience, which can benefit future designers of this assessment tool.
Ecological momentary interventions for mental health: A scoping review
PLOS ONE, 2021
Background The development of mobile computing technology has enabled the delivery of psychological interventions while people go about their everyday lives. The original visions of the potential of these “ecological momentary interventions” were presented over a decade ago, and the widespread adoption of smartphones in the intervening years has led to a variety of research studies exploring the feasibility of these aspirations. However, there is a dearth of research describing the different dimensions, characteristics, and features of these interventions, as constructed. Objective To provide an overview of the definitions given for “ecological momentary interventions” in the treatment of common mental health disorders, and describe the set of technological and interaction possibilities which have been used in the design of these interventions. Methods A systematic search identified relevant literature published between 2009 and 2020 in the PubMed, PsycInfo, and ACM Guide to the Com...
Journal of Medical Internet Research, 2017
Background: Ecological momentary assessment (EMA) assesses individuals' current experiences, behaviors, and moods as they occur in real time and in their natural environment. EMA studies, particularly those of longer duration, are complex and require an infrastructure to support the data flow and monitoring of EMA completion. Objective: Our objective is to provide a practical guide to developing and implementing an EMA study, with a focus on the methods and logistics of conducting such a study. Methods: The EMPOWER study was a 12-month study that used EMA to examine the triggers of lapses and relapse following intentional weight loss. We report on several studies that informed the implementation of the EMPOWER study: (1) a series of pilot studies, (2) the EMPOWER study's infrastructure, (3) training of study participants in use of smartphones and the EMA protocol and, (4) strategies used to enhance adherence to completing EMA surveys. Results: The study enrolled 151 adults and had 87.4% (132/151) retention rate at 12 months. Our learning experiences in the development of the infrastructure to support EMA assessments for the 12-month study spanned several topic areas. Included were the optimal frequency of EMA prompts to maximize data collection without overburdening participants; the timing and scheduling of EMA prompts; technological lessons to support a longitudinal study, such as proper communication between the Android smartphone, the Web server, and the database server; and use of a phone that provided access to the system's functionality for EMA data collection to avoid loss of data and minimize the impact of loss of network connectivity. These were especially important in a 1-year study with participants who might travel. It also protected the data collection from any server-side failure. Regular monitoring of participants' response to EMA prompts was critical, so we built in incentives to enhance completion of EMA surveys. During the first 6 months of the 12-month study interval, adherence to completing EMA surveys was high, with 88.3% (66,978/75,888) completion of random assessments and around 90% (23,411/25,929 and 23,343/26,010) completion of time-contingent assessments, despite the duration of EMA data collection and challenges with implementation. Conclusions: This work informed us of the necessary preliminary steps to plan and prepare a longitudinal study using smartphone technology and the critical elements to ensure participant engagement in the potentially burdensome protocol, which spanned 12
Personalized support for well-being at work: an overview of the SWELL project
User Modeling and User-adapted Interaction, 2019
Recent advances in wearable sensor technology and smartphones enable simple and affordable collection of personal analytics. This paper reflects on the lessons learned in the SWELL project that addressed the design of user-centered ICT applications for self-management of vitality in the domain of knowledge workers. These workers often have a sedentary lifestyle and are susceptible to mental health effects due to a high workload. We present the sense-reason-act framework that is the basis of the SWELL approach and we provide an overview of the individual studies carried out in SWELL. In this paper, we revisit our work on reasoning: interpreting raw heterogeneous sensor data, and acting: providing personalized feedback to support behavioural change. We conclude that simple affordable sensors can be used to classify user behaviour and heath status in a physically non-intrusive way. The interpreted data can be used to inform personalized feedback strategies. Further longitudinal studies can now be initiated to assess the effectiveness of m-Health interventions using the SWELL methods.
Journal of Biomedical Informatics, 2016
The emergence of wearables and smartwatches is making sensors a ubiquitous technology to measure daily rhythms in physiological measures, such as movement and heart rate. An integration of sensor data from wearables and self-report questionnaire data about cognition, behaviors, and emotions can provide new insights into the interaction of mental and physiological processes in daily life. Hitherto no method existed that enables an easy-to-use integration of sensor and self-report data. To fill this gap, we present 'Physiqual', a platform for researchers that gathers and integrates data from commercially available sensors and service providers into one unified format for use in Ecological Momentary Assessments (EMA) or Experience Sampling Methods (ESM), and Quantified Self (QS). Physiqual currently supports sensor data provided by two well-known service providers and therewith a wide range of smartwatches and wearables. To demonstrate the features of Physiqual, we conducted a case study in which we assessed two subjects by means of data from an EMA study combined with sensor data as aggregated and exported by Physiqual. To the best of our knowledge, the Physiqual platform is the first platform that allows researchers to conveniently aggregate and integrate physiological sensor data with EMA studies.
Ecological Momentary Assessment Using a Mobile Phone
2013
The mobile phone has become a popular tool for providing information and capturing responses from different groups of people because of its technological features and portability. EMA (Ecological Momentary Assessment) is commonly used by health researchers to contemporaneously capture information regarding human experience. The authors proposed the use of a mobile EMA system as a supportive intervention to collect real-time patient data and to give back real-time advice. In this study, a mobile EMA system has been utilized by patients with a variety of conditions, including mood disorders, behavior disorders, and physical disorders. The real-time data collection included one or more pieces of information at each moment to improve understanding the causal mechanisms of disease. The effectiveness of real-time advice has been examined by comparing a mobile EMA system with and without this function. Patient compliance was high on average, at approximately 89%, and was higher, at approximately 93%, when advice was given. In several cases, the supportive intervention was shown to help patients improve their health conditions. However, the results were dependent on the patients' motivation, environment, and relationship with their doctor. The EMA data regarding advice given showed that symptoms tended to improve in most cases.