Creating value with eHealth: identification of the value proposition with key stakeholders for the resilience navigator app.

BACKGROUND: For a stress-management app to be persuasive and impactful, designers and developers should obtain a clear perspective of the value proposition according to key stakeholders before development. However, this is often not the case. In order to increase the chance of creating an impact by means of the Resilience Navigator app, this study aims to identify key stakeholders and work with them to gain an in-depth understanding of the value proposition of this stress-management app. METHODS: The approach used in this study builds on the approaches taken by Van Limburg et al. and Van Woezik et al. An initial list of stakeholders was identified by means of a literature scan. Stakeholders on this initial list took an online survey to identify key stakeholders with a ranking system. Semi-structured interviews were conducted with a subset of key stakeholders to identify the value proposition using the value proposition canvas as a framework for data collection. Finally, the value proposition was validated by key stakeholders during focus groups. RESULTS: The key stakeholders identified included employees, employers, participation councils within organisations, HR advisors, product owners, company doctors, and business analysts. The interviews produced a list of approximately one hundred values from which fifteen core values were distilled. One example is to take into account time constraints experienced by users during stress periods. In general, the Resilience Navigator app's main goal is to increase awareness of personal stress levels and causes of stress. In addition, the sub-goal is to increase skills for effective stress management. The focus groups validated the idea that the most important values were reflected in the value proposition and had been appropriately translated into design elements, according to key stakeholders. CONCLUSIONS: A thorough, bottom-up identification and validation of the value proposition for the Resilience Navigator app was obtained, reflecting key stakeholders' varying ideas on this piece of eHealth technology. The results will facilitate the continued development of the Resilience Navigator app from the value specification phase to the design phase. In the design phase, the remaining assumptions regarding the app's value proposition should be tested using rapid prototyping.

Increase in the Acute:Chronic Workload Ratio relates to Injury Risk in Competitive Runners.

Injuries of runners reduce the ability to train and hinder competing. Literature shows that the relation between potential risk factors and injuries are not definitive, limited, and inconsistent. In team sports, workload derivatives were identified as risk factors. However, there is an absence of literature in running on workload derivatives. This study used the workload derivatives acute workload, chronic workload, and acute: chronic workload ratios to investigate the relation between workload and injury risk in running. Twenty-three competitive runners kept a daily training log for 24 months. The runners reported training duration, training intensity and injuries. One-week (acute) and 4-week (chronic) workloads were calculated as the average of training duration multiplied by training intensity. The acute:chronic workload ratio was determined dividing the acute and chronic workloads. Results show that a fortnightly low increase of the acute:chronic workload ratio (0.10-0.78) led to an increased risk of sustaining an injury (p<0.001). Besides, a low increase of the acute:chronic workload ratio (0.05-0.62) between the second week and third week before an injury showed an association with increased injury risk (p=0.013). These findings demonstrate that the acute:chronic workload ratio relates to injury risk.

Personalized Physical Activity Coaching: A Machine Learning Approach.

Living a sedentary lifestyle is one of the major causes of numerous health problems. To encourage employees to lead a less sedentary life, the Hanze University started a health promotion program. One of the interventions in the program was the use of an activity tracker to record participants' daily step count. The daily step count served as input for a fortnightly coaching session. In this paper, we investigate the possibility of automating part of the coaching procedure on physical activity by providing personalized feedback throughout the day on a participant's progress in achieving a personal step goal. The gathered step count data was used to train eight different machine learning algorithms to make hourly estimations of the probability of achieving a personalized, daily steps threshold. In 80% of the individual cases, the Random Forest algorithm was the best performing algorithm (mean accuracy = 0.93, range = 0.88-0.99, and mean F1-score = 0.90, range = 0.87-0.94). To demonstrate the practical usefulness of these models, we developed a proof-of-concept Web application that provides personalized feedback about whether a participant is expected to reach his or her daily threshold. We argue that the use of machine learning could become an invaluable asset in the process of automated personalized coaching. The individualized algorithms allow for predicting physical activity during the day and provides the possibility to intervene in time.

Key Components in eHealth Interventions Combining Self-Tracking and Persuasive eCoaching to Promote a Healthier Lifestyle: A Scoping Review.

BACKGROUND: The combination of self-tracking and persuasive eCoaching in automated interventions is a new and promising approach for healthy lifestyle management. OBJECTIVE: The aim of this study was to identify key components of self-tracking and persuasive eCoaching in automated healthy lifestyle interventions that contribute to their effectiveness on health outcomes, usability, and adherence. A secondary aim was to identify the way in which these key components should be designed to contribute to improved health outcomes, usability, and adherence. METHODS: The scoping review methodology proposed by Arskey and O'Malley was applied. Scopus, EMBASE, PsycINFO, and PubMed were searched for publications dated from January 1, 2013 to January 31, 2016 that included (1) self-tracking, (2) persuasive eCoaching, and (3) healthy lifestyle intervention. RESULTS: The search resulted in 32 publications, 17 of which provided results regarding the effect on health outcomes, 27 of which provided results regarding usability, and 13 of which provided results regarding adherence. Among the 32 publications, 27 described an intervention. The most commonly applied persuasive eCoaching components in the described interventions were personalization (n=24), suggestion (n=19), goal-setting (n=17), simulation (n=17), and reminders (n=15). As for self-tracking components, most interventions utilized an accelerometer to measure steps (n=11). Furthermore, the medium through which the user could access the intervention was usually a mobile phone (n=10). The following key components and their specific design seem to influence both health outcomes and usability in a positive way: reduction by setting short-term goals to eventually reach long-term goals, personalization of goals, praise messages, reminders to input self-tracking data into the technology, use of validity-tested devices, integration of self-tracking and persuasive eCoaching, and provision of face-to-face instructions during implementation. In addition, health outcomes or usability were not negatively affected when more effort was requested from participants to input data into the technology. The data extracted from the included publications provided limited ability to identify key components for adherence. However, one key component was identified for both usability and adherence, namely the provision of personalized content. CONCLUSIONS: This scoping review provides a first overview of the key components in automated healthy lifestyle interventions combining self-tracking and persuasive eCoaching that can be utilized during the development of such interventions. Future studies should focus on the identification of key components for effects on adherence, as adherence is a prerequisite for an intervention to be effective.

How Reflective Automated e-Coaching Can Help Employees Improve Their Capacity for Resilience: Mixed Methods Study.

BACKGROUND: An eHealth tool that coaches employees through the process of reflection has the potential to support employees with moderate levels of stress to increase their capacity for resilience. Most eHealth tools that include self-tracking summarize the collected data for the users. However, users need to gain a deeper understanding of the data and decide upon the next step to take through self-reflection. OBJECTIVE: In this study, we aimed to examine the perceived effectiveness of the guidance offered by an automated e-Coach during employees' self-reflection process in gaining insights into their situation and on their perceived stress and resilience capacities and the usefulness of the design elements of the e-Coach during this process. METHODS: Of the 28 participants, 14 (50%) completed the 6-week BringBalance program that allowed participants to perform reflection via four phases: identification, strategy generation, experimentation, and evaluation. Data collection consisted of log data, ecological momentary assessment (EMA) questionnaires for reflection provided by the e-Coach, in-depth interviews, and a pre- and posttest survey (including the Brief Resilience Scale and the Perceived Stress Scale). The posttest survey also asked about the utility of the elements of the e-Coach for reflection. A mixed methods approach was followed. RESULTS: Pre- and posttest scores on perceived stress and resilience were not much different among completers (no statistical test performed). The automated e-Coach did enable users to gain an understanding of factors that influenced their stress levels and capacity for resilience (identification phase) and to learn the principles of useful strategies to improve their capacity for resilience (strategy generation phase). Design elements of the e-Coach reduced the reflection process into smaller steps to re-evaluate situations and helped them to observe a trend (identification phase). However, users experienced difficulties integrating the chosen strategies into their daily life (experimentation phase). Moreover, the identified events related to stress and resilience were too specific through the guidance offered by the e-Coach (identification phase), and the events did not recur, which consequently left users unable to sufficiently practice (strategy generation phase), experiment (experimentation phase), and evaluate (evaluation phase) the techniques during meaningful events. CONCLUSIONS: Participants were able to perform self-reflection under the guidance of the automated e-Coach, which often led toward gaining new insights. To improve the reflection process, more guidance should be offered by the e-Coach that would aid employees to identify events that recur in daily life. Future research could study the effects of the suggested improvements on the quality of reflection via an automated e-Coach.

Exploring tailored virtual emotion regulation approaches for individuals with emotional eating.

BACKGROUND: Emotional eating is a complex problem fostering obesity and resulting from maladaptive emotion regulation. Traditional behavioural weight loss interventions have shown insignificant effect. They can be improved by targeting the specific needs of individuals with emotional eating. OBJECTIVE: The current study explored a tailored online approach with the aim to positively influence affect (positive and negative) and emotion regulation by applying one of three exercises: body scan, opposite action, and positive reappraisal. DESIGN: An embedded mixed-method design (questionnaire data (t0, t1, t2) and perceived usefulness of exercises in t2) was used to evaluate the effects of a two-week online quasi-experimental pilot study. SUBJECTS/SETTING: In total, 80 participants with self-reported emotional eating difficulties (DEBQ-E; Memo = 3.48, SD = .64, range 1.62-4.92) finished baseline measurements; 15 completed the intervention. The study sample was predominantly female (95%), from 18 till 66 (Mage = 38,0 ± SD = 14.25). RESULTS: Participants reported that the exercises helped them to pay attention to their physical sensations, and to see positive aspects in negative matters. The exercises were considered difficult by the participants, with too little explanation, and dull, due to minor variation. The observed changes revealed small, and moreover, not significant improvements of the three exercises on positive and negative affect and overall emotion dysregulation. Although the quantitative results did not reach significance, the qualitative data highlighted which aspects of the tailored exercises may have contributed to mood and emotion regulation outcomes. A notable observation in the present study is the substantial dropout rate, with the number of participants decreasing from 80 at baseline (T0) to 15 at the post-intervention stage (T2). CONCLUSIONS: Future studies should identify tailored online exercises in emotion regulation skills in more detail and explore the contexts in which they are most effective in a personalized virtual coach virtual coach to be developed for individuals with emotional eating. Given the high dropout rate, more emphasis should be given to a proper presentation of the exercises, as well as more explanation of their usefulness and how to perform them.

Emotional eating is eating in response to negative emotions, and is problematic because it may lead to overweight, depression, and low self-image. People with emotional eating behaviour have difficulty regulating emotions and need mental healthcare but may feel too ashamed to seek help. Moreover, healthcare is not always available at the time of need. Our goal in this research project is to develop a virtual coach application that is available 24/7. This study examined what users of such an application would think of a series of online exercises that can help you recognize and take control of your own negative emotions. We wanted participants to tell us what they thought of the exercises. We also measured whether performing the exercises had an effect on how a person felt (well-being) and whether their skills in handling their own emotions improved.The outcome was that participants found the exercises insightful, but that completion was dull. It also revealed that the measured effects were small.

Preferences for coaching strategies in a personalized virtual coach for emotional eaters: an explorative study.

Objectives: Emotional eating is recognized as a potential contributor to weight gain. Emotional eaters often hide their problems because of feelings of shame about their behavior, making it challenging to provide them with the necessary support. The introduction of a virtual coach might offer a potential solution in assisting them. To find out whether emotional eaters are receptive to online personalized coaching, we presented emotional eaters with two essential proto-typical problem situations for emotional eaters: "experiencing cravings" and "after giving in to cravings," and asked them whether they preferred one of the three coaching strategies presented: Validating, Focus-on-Change and Dialectical. Methods: An experimental vignette study (2 × 3 design) was carried out. The vignettes featured two distinct personas, each representing one of the two common problem scenarios experienced by emotional eaters, along with three distinct coaching strategies for each scenario. To identify potential predictors for recognition of problem situations, questionnaires on emotional eating (DEBQ), personality traits (Big-5), well-being (PANAS), and BMI were administrated. Results: A total of 62% of the respondents identified themselves with "after giving in to cravings" and 47% with "experiencing cravings." BMI, emotional eating and emotional stability appeared to be predictors in recognizing both the problem situations. In "experiencing cravings," the participating women preferred Dialectical and the Validation coaching strategies. In the "after giving in to cravings" condition, they revealed a preference for the Dialectical and the Focus-on-Change coaching strategies. Conclusion: Using vignettes allowed a less threatening way of bringing up sensitive topics for emotional eaters. The personas representing the problem situations were reasonably well recognized. To further enhance this recognition, it is important for the design and content of the personas to be even more closely related to the typical problem scenarios of emotional eaters, rather than focusing on physical characteristics or social backgrounds. This way, users may be less distracted by these factors. With the knowledge gained about the predictors that may influence recognition of the problem situations, design for coaching can be more customized. The participants represented individuals with high emotional eating levels, enhancing external validity.

Application of three different coaching strategies through a virtual coach for people with emotional eating: a vignette study.

BACKGROUND: Around 13% of the world's population suffers from obesity. More than 40% of people with obesity display emotional eating behaviour (eating in response to negative emotions or distress). It is an alternate to more effective coping strategies for negative emotions. Our study explored the opportunities for helping adults with emotional overeating using a virtual coach, aiming to identify preferences for tailored coaching strategies applicable in a personal virtual coach environment. Three different coaching strategies were tested: a validating, a focus-on-change, and a dialectical one - the latter being a synthesis of the first two strategies. METHODS: A qualitative study used vignettes reflecting the two most relevant situations for people with emotional eating: 1. experiencing negative emotions, with ensuing food cravings; and 2. after losing control to emotional eating, with ensuing feelings of low self-esteem. Applied design: 2 situations × 3 coaching strategies. PARTICIPANTS: 71 adult women (Mage 44.4/years, range 19-70, SD = 12.86) with high scores on the DEBQ-emotional eating scale (Memo 3.65, range 1.69-4.92, SD = .69) with mean BMI 30.1 (range 18-46, SD = 6.53). They were recruited via dieticians' practices, were randomly assigned to the conditions and asked how they would face and react to the presented coaching strategies. Data were transcribed and a thematic analysis was conducted. RESULTS: Qualitative results showed that participants valued both the validating coaching strategy and the focus-on-change strategy, but indicated that a combination of validation and focus-on-change provides both mental support and practical advice. Data showed that participants differed in their level of awareness of the role that emotions play in their overeating and the need for emotion-regulation skills. CONCLUSION: The design of the virtual coach should be based on dialectical coaching strategies as preferred by participants with emotional eating behaviour. It should be tailored to the different stages of awareness of their emotions and individual emotion-regulation skills.