COVID-BEHAVE dataset: measuring human behaviour during the COVID-19 pandemic

Aiming to illuminate the effects of enforced confinements on people's lives, this paper presents a novel dataset that measures human behaviour holistically and longitudinally during the COVID-19 outbreak. In particular, we conducted a study during the first wave of the lockdown, where 21 healthy subjects from the Netherlands and Greece participated, collecting multimodal raw and processed data from smartphone sensors, activity trackers, and users' responses to digital questionnaires. The study lasted more than two months, although the duration of the data collection varies per participant. The data are publicly available and can be used to model human behaviour in a broad sense as the dataset explores physical, social, emotional, and cognitive domains. The dataset offers an exemplary perspective on a given group of people that could be considered to build new models for investigating behaviour changes as a consequence of the lockdown. Importantly, to our knowledge, this is the first dataset combining passive sensing, experience sampling, and virtual assistants to study human behaviour dynamics in a prolonged lockdown situation.

Consulting the Oracle: A Delphi study for determining parameters for a mental health user profile and personalization strategy for an online service to aid grieving older adults

While much effort has been devoted to the development of mental e-health interventions, the tailoring of these applications to user characteristics and needs is a comparatively novel field of research. The premise of personalizing mental e-health interventions is that personalization increases user motivation and (thereby) mitigates intervention dropout and enhances clinical effectiveness. In this study, we selected user profile parameters for personalizing a mental e-health intervention for older adults who lost their spouse. We conducted a three-round Delphi study involving an international and interdisciplinary expert panel (N = 16) with two objectives. The first aim was to elicit adaptation strategies that can be used to dynamically readjust the intervention to the user's needs. The second aim was to identify a set of meaningful indicators for monitoring the user from within the grief intervention to escalate from self-help to blended care, whenever advisable. This Delphi study used as starting point an evaluated, text-based grief intervention composed of ten modules, including psychoeducation about grief and cognitive-behavioral exercises to support the user in adjusting their lives after bereavement. Every user follows this grief intervention in a linear fashion from beginning to end. The resulting conceptual adaptation model encompasses dynamic adjustments, as well as one-time adjustments performed at the initialization of the service. On the level of the application structure, the adaptations affect when which topic module is presented to the user. The adaptations further provide strategies for adjusting the text-based content of individual intervention modules dependent on user characteristics and for selecting appropriate reactions to user input. Eighteen monitoring parameters were elicited and grouped into four categories: clinical, behavioral/emotional, interactive, and external. Parameters that were perceived as most urgent to attend to for escalation were Suicidality, Self-destructive behavior, Client-initiated escalation, Unresponsiveness and (Complicated) Grief symptoms.

Digital Therapeutics: Virtual Coaching Powered by Artificial Intelligence on Real-World Data

An ever-increasing number of people need to cope with one or more chronic conditions for a significant portion of their life. Digital Therapeutics (DTx) focused on the prevention, management, or treatment of chronic diseases are promising in alleviating the personal socio-economic burden caused. In this paper we describe a proposed DTx methodology covering three main components: observation (which data is collected), understanding (how to acquire knowledge based on the data collected), and coaching (how to communicate the acquired knowledge to the user). We focus on an emerging form of automated virtual coaching, delivered through conversational agents allowing interaction with end-users using natural language. Our methodology will be applied in the new generation of the Healthentia platform, an eClinical solution that captures clinical outcomes from mobile, medical and Internet of Things (IoT) devices, using a patient-centric mobile application and offers Artificial Intelligence (AI) driven smart services. While we are unable to provide data to prove its effectiveness, we illustrate the potential of the proposed architecture to deliver DTx by describing how the methodology can be applied to a use-case consisting of a clinical trial for treatment of a chronic condition, combining testing of a new medication and a lifestyle intervention, which will be partly implemented and evaluated in the context of the European research project RE-SAMPLE (REal-time data monitoring for Shared, Adaptive, Multi-domain and Personalised prediction, and decision making for Long-term Pulmonary care Ecosystems).

Clinician acceptance of complex clinical decision support systems for treatment allocation of patients with chronic low back pain

Background

The uptake of complex clinical decision support systems (CDSS) in daily practice remains low, despite the proven potential to reduce medical errors and to improve the quality of care. To improve successful implementation of a complex CDSS this study aims to identify the factors that hinder, or alleviate the acceptance of, clinicians toward the use of a complex CDSS for treatment allocation of patients with chronic low back pain.

Methods

We tested a research model in which the intention to use a CDSS by clinicians is influenced by the perceived usefulness; this usefulness, in turn is influenced by the perceived service benefits and perceived service risks. An online survey was created to test our research model and the data was analysed using Partial Least Squares Structural Equation Modelling. The study population consisted of clinicians. The online questionnaire started with demographic questions and continued with a video animation of the complex CDSS followed by the set of measurement items. The online questionnaire ended with two open questions enquiring the reasons to use and not use, a complex CDSS.

Results

Ninety-eight participants (46% general practitioners, 25% primary care physical therapists, and 29% clinicians at a rehabilitation centre) fully completed the questionnaire. Fifty-two percent of the respondents were male. The average age was 48 years (SD ± 12.2). The causal model suggests that perceived usefulness is the main factor contributing to the intention to use a complex CDSS. Perceived service benefits and risks are both significant antecedents of perceived usefulness and perceived service risks are affected by the perceived threat to autonomy and trusting beliefs, particularly benevolence and competence.

Conclusions

To improve the acceptance of complex CDSSs it is important to address the risks, but the main focus during the implementation phase should be on the expected improvements in patient outcomes and the overall gain for clinicians. Our results will help the development of complex CDSSs that fit more into the daily clinical practice of clinicians.

LEAVES (optimizing the mentaL health and resiliencE of older Adults that haVe lost thEir spouSe via blended, online therapy): Proposal for an Online Service Development and Evaluation

Background

Loss of a spouse is a frequent occurrence in later life. While most older adults successfully process this loss and will return to a normal life, about 10% of the individuals are unable to cope, and progress to prolonged grief (PG). PG, in turn, can result in mental and physical problems including poor sleep, cardiovascular problems, depression, and suicidal tendencies.

Objective

LEAVES (optimizing the mentaL health and resiliencE of older Adults that haVe lost thEir spouSe via blended, online therapy) is an online bereavement program that will support the prevention and treatment of PG, so that elderly mourners can continue to lead an active, meaningful, and dignified life. LEAVES will cater to secondary end users (eg, family, informal caregivers) by reducing stress.

Methods

LEAVES will help older adults to process the loss of a spouse in an online environment, which consists of (1) an existing online grief self-help program LIVIA, (2) the Before You Leave program that allows for storing personal memories, (3) a virtual agent platform, and (4) an accessible front-end design. LEAVES can detect persons at risk for complications, reveal negative trends in their emotional life, and act to counter such trends. The service relies on online support whenever possible but is blended with telephone or face-to-face counseling when necessary.

Results

The project will take place between February 2020 and January 2023 and includes a real-life evaluation in which 315 end users will use the service across 3 countries (the Netherlands, Portugal, and Switzerland). The evaluation of LEAVES will focus on clinical effect, its business case, and technology acceptance. The results will pave the way for smooth integration into existing care paths and reimbursement schemes.

Conclusions

The LEAVES service aims to soften the mourning process, prevents depression or social isolation, strengthens widow(er)s resilience and well-being, and quickens one’s return to societal participation.

International Registered Report Identifier (IRRID)

DERR1-10.2196/19344

The acceptance of clinical decision support systems among clinicians in the treatment of neck and/or back pain

Background

Clinical Decision Support Systems (CDSSs) are computerized systems using case-based reasoning to assist clinicians in making clinical decisions. Despite the proven added value to public health, the implementation of CDSS clinical practice is scarce. Particularly, little is known about the acceptance of CDSS among clinicians. Within the Back-UP project (Project Number: H2020-SC1-2017-CNECT-2-777090) a CDSS is developed with prognostic models to improve the management of Neck and/or Low Back Pain (NLBP). Therefore, the aim of this study is to present the factors involved in the acceptance of CDSSs among clinicians.

Methods

To assess the acceptance of CDSSs among clinicians we conducted a mixed method analysis of questionnaires and focus groups. An online questionnaire with a low-fidelity prototype of a CDSS (TRL3) was sent to Dutch clinicians aimed to identify the factors influencing the acceptance of CDSSs (intention to use, perceived threat to professional autonomy, trusting believes and perceived usefulness). Next to this, two focus groups were conducted with clinicians addressing the general attitudes towards CDSSs, the factors determining the level of acceptance, and the conditions to facilitate use of CDSSs.

Results

A pilot-study of the online questionnaire is completed and the results of the large evaluation are expected spring 2020. Eight clinicians participated in two focus groups. After being introduced to various types of CDSSs, participants were positive about the value of CDSS in the care of NLBP. The clinicians agreed that the human touch in NLBP care must be preserved and that CDSSs must remain a supporting tool, and not a replacement of their role as professionals.

Conclusions

By identifying the factors hindering the acceptance of CDSSs we can draw implications for implementation of CDSSs in the treatment of NLBP.

Association between objectively measured physical behaviour and neck- and/or low back pain: A systematic review

BACKGROUND AND OBJECTIVE

Clinical guidelines recommend physical activity to manage neck pain (NP) and low back pain (LBP). However, studies used to support these guidelines are based on self-reports of physical behaviour, which are prone to bias and misclassification. This systematic review aimed to investigate associations between objectively measured physical behaviour and the risk or prognosis of NP and/or LBP.

DATABASES AND DATA TREATMENT

Literature searches were performed in MEDLINE, Embase and Scopus from their inception until 18 January 2019. We considered prospective cohort studies for eligibility. Article selection, data extraction and critical appraisal were carried out by independent reviewers. Results were stratified on activity/sedentariness.

RESULTS

Ten articles out of 897 unique records identified met the inclusion criteria, of which eight studied working populations with mainly blue-collar workers. The overall results indicate that increased sitting time at work reduces the risk of NP and LBP while increased physical activity during work and/or leisure increases the risk of these conditions among blue-collar workers; however, associations were weak. Physical activity was not associated with prognosis of LBP (no studies investigated prognosis of NP). Most of the included articles have methodological shortcomings.

CONCLUSIONS

This review indicates that, among blue-collar workers, increased sitting at work may protect against NP and LBP while increased physical activity during work and/or leisure may increase this risk. There was no evidence supporting physical activity as a prognostic factor for LBP. Findings should be interpreted with caution due to the weak associations and few available studies with methodological shortcomings.

SIGNIFICANCE

Based on prospective cohort studies with objectively measured physical behaviour, this review questions the common notion that increased physical activity is associated with reduced risk or better prognosis of NP and/or LBP. We found that, among blue-collar workers, increased sitting time at work reduces the risk of NP and LBP, whereas physical activity somewhat increases the risk. Despite methodological shortcomings, there was consistency in the direction of the results, although high-quality articles reported the weakest associations. Systematic review registration: PROSPERO CRD42018100765.

Older Adults' Attitudes Toward Ambulatory Technology to Support Monitoring and Coaching of Healthy Behaviors: Qualitative Study

Background

Prevention of functional decline demands a holistic perspective of health management. Older adults are becoming avid users of technology; however, technology is not yet largely used in supporting self-management of health in daily life. Previous research suggests that the low adherence to these technologies is likely to be associated with the fact that opinions and wishes of the older population are not always taken into consideration when designing new technology.

Objective

The aim of this study was to investigate the attitudes of older adults living independently regarding technology to support healthy behaviors, addressing nutrition, physical and cognitive function, and well-being.

Methods

In-depth semistructured interviews were performed with 12 older adults addressing 4 themes: (1) current practices in health management, (2) attitudes toward using technology to support health management, (3) wishes from technology, and (4) change in attitudes after actual use of technology. The fourth theme was investigated with a follow-up interview after participants had used a step counter, a smart scale, and a mobile app for 1 month. Data collected were analyzed using inductive thematic analysis.

Results

Participants were active in self-managing their health and foresaw an added value on using technology to support them in adopting healthier behaviors in everyday life. Attitudes and wishes differed considerably per health domain, with cognitive function being the most sensitive topic. Fears from technology mentioned were attention theft, replacement of human touch, and disuse of existing abilities. Poststudy interviews suggest that attitudes toward technology improve after a short period of use.

Conclusions

Technology to support aging in place must target health literacy, allow personalization in the design but also in the use of the technology, and tackle existing fears concerning technology. Further research should investigate the effect of these strategies on the adherence to technology to be used in daily life. We outline a set of recommendations of interest to those involved in developing and implementing technology to support aging in place, focusing on acceptance, barriers, and ethical concerns.

Persuasive technology to support active and healthy ageing: An exploration of past, present, and future

The age of the population worldwide is rapidly increasing, bringing social and economic challenges. Persuasive technology can alleviate the burden on traditional healthcare services when used to support healthy behaviors, for instance in the prevention and treatment of chronic diseases. Additionally, healthy behaviors are key factors for active and healthy ageing by delaying or even reversing functional decline. In this manuscript, we present a multi-perspective analysis of technologies that can be used in the support of active and healthy ageing in the daily life. First, we take the perspective of physical and mental health, by focusing on the promotion of physical activity and emotional wellbeing. From a temporal perspective, we look at how technology evolved from past, present and future. The overview of the literature is structured in four main sections: (1) measurement of current behavior (monitoring), (2) analysis of the data gathered to derive meaningful information (analyzing & reasoning), (3) support the individual in the adoption or maintenance of a behavior (coaching), and (4) tools or interfaces that provide the information to the individual to stimulate the desired behavior (applications). Finally, we provide recommendations for the design, development and implementation of future technological innovations to support Active and Healthy Ageing in daily life.

Exploring the relation between positive emotions and the functional status of older adults living independently: a systematic review

OBJECTIVES

Literature suggests that positive emotions positively influence physiological parameters but their relation to functioning in the daily life of older adults living independently remains unclear. The present work aims to investigate the relation between positive emotions and functional status in daily life of older people living independently.

METHOD

A systematic literature review was conducted using the PubMed, PsycINFO and Scopus electronic databases. Included works were peer-reviewed empirical studies that analysed the relation between positive emotions and ability to perform activities of daily living with older adults living independently.

RESULTS

After removal of duplicates, 10 out of 963 papers met the inclusion criteria. Cross-sectional studies (n = 6) provided limited evidence about a relation between positive emotions and functioning in daily life. However, longitudinal studies (n = 4) provide significant evidence for an interaction between the two factors, suggesting that time influences this interaction.

CONCLUSION

The variety on the design and samples of the studies included in this review does not allow a cohesive conclusion of the results. Nevertheless, limited evidence suggests that higher frequency in the experience of positive emotions might be associated with lower functional limitations. The issue of causality in emotions-functioning remains unclear from the review. Further observational studies are highly recommended, supported by innovative technologies.

An exploratory study on the impact of daily activities on the pleasure and physical activity of older adults

Background

Pleasure is one determinant of intrinsic motivation and yet a dimension often forgotten when promoting physical activity among the older population. In this study we investigate the relation between daily activities and physical activity, experience of pleasure, and the interaction between pleasure and physical activity in the daily lives of community-dwelling older adults.

Methods

Participants carried a hip-worn accelerometer during 30 consecutive days resulting in a total of 320 days of data collection. Current activity, location, companion and experience of pleasure during each activity were assessed through experience sampling on a smartphone every 1–2 h. Between- and within-individual differences were analysed with multi-level models and 10xN = 1 regression analysis.

Results

Outdoor activities were associated with higher physical activity than indoor activities (p < 0.001). Performing leisure activities, outdoors and not alone significantly predicted pleasure in daily life (all p’s < 0.05). Being more active while performing leisure activities resulted in higher experiences of pleasure (p < 0.001). However, when performing basic activities of daily living (e.g. commuting or households) this relation was inverted. Results provide meaningful indication for individual variance. The 30 days of data collected from each participant allow for identification of individual differences.

Conclusions

Daily activities and their contexts do influence the experience of pleasure and physical activity of older adults in daily life of older adults, although similar research with larger population is recommended. Results are in accordance with the literature, indicating that the method adopted (accelerometry combined with experience sampling) provides reliable representation of daily life. Identification of individual differences can eventually be automatically performed through data mining techniques. Further research could look at innovative approaches to promote Active Ageing using mobile technology in the daily life, by promoting physical activity through recommendation of pleasurable activities, and thus likely to increase the intrinsic motivation to become physically active.

Tailored motivational message generation: A model and practical framework for real-time physical activity coaching

This paper presents a comprehensive and practical framework for automatic generation of real-time tailored messages in behavior change applications. Basic aspects of motivational messages are time, intention, content and presentation. Tailoring of messages to the individual user may involve all aspects of communication. A linear modular system is presented for generating such messages. It is explained how properties of user and context are taken into account in each of the modules of the system and how they affect the linguistic presentation of the generated messages. The model of motivational messages presented is based on an analysis of existing literature as well as the analysis of a corpus of motivational messages used in previous studies. The model extends existing 'ontology-based' approaches to message generation for real-time coaching systems found in the literature. Practical examples are given on how simple tailoring rules can be implemented throughout the various stages of the framework. Such examples can guide further research by clarifying what it means to use e.g. user targeting to tailor a message. As primary example we look at the issue of promoting daily physical activity. Future work is pointed out in applying the present model and framework, defining efficient ways of evaluating individual tailoring components, and improving effectiveness through the creation of accurate and complete user- and context models.