A Technology-Assisted Telephone Intervention for Work-Related Stress Management: Pilot Randomized Controlled Trial.

BACKGROUND: Stress management interventions combining technology with human involvement have the potential to improve the cost-effectiveness of solely human-delivered interventions, but few randomized controlled trials exist for assessing the cost-effectiveness of technology-assisted human interventions. OBJECTIVE: The aim of this study was to investigate whether a technology-assisted telephone intervention for stress management is feasible for increasing mental well-being or decreasing the time use of coaches (as an approximation of intervention cost) while maintaining participants' adherence and satisfaction compared with traditional telephone coaching. METHODS: A 2-arm, pilot randomized controlled trial of 9 months for stress management (4-month intensive and 5-month maintenance phases) was conducted. Participants were recruited on the web through a regional occupational health care provider and randomized equally to a research (technology-assisted telephone intervention) and a control (traditional telephone intervention) group. The coaching methodology was based on habit formation, motivational interviewing, and the transtheoretical model. For the research group, technology supported both coaches and participants in identifying behavior change targets, setting the initial coaching plan, monitoring progress, and communication. The pilot outcome was intervention feasibility, measured primarily by self-assessed mental well-being (WorkOptimum index) and self-reported time use of coaches and secondarily by participants' adherence and satisfaction. RESULTS: A total of 49 eligible participants were randomized to the research (n=24) and control (n=25) groups. Most participants were middle-aged (mean 46.26, SD 9.74 years) and female (47/49, 96%). Mental well-being improved significantly in both groups (WorkOptimum from "at risk" to "good" Â>0.85; P<.001), and no between-group differences were observed in the end (Â=0.56, 95% CI 0.37-0.74; P=.56). The total time use of coaches did not differ significantly between the groups (366.0 vs 343.0 minutes, Â=0.60, 95% CI 0.33-0.85; P=.48). Regarding adherence, the dropout rate was 13% (3/24) and 24% (6/25), and the mean adherence rate to coaching calls was 92% and 86% for the research and control groups, respectively; the frequency of performing coaching tasks was similar for both groups after both phases; and the diligence in performing the tasks during the intensive phase was better for the research group (5.0 vs 4.0, Â=0.58, 95% CI 0.51-0.65; P=.03), but no difference was observed during the maintenance phase. Satisfaction was higher in the research group during the intensive phase (5.0 vs 4.0, Â=0.66, 95% CI 0.58-0.73; P<.001) but not during the maintenance phase. CONCLUSIONS: The technology-assisted telephone intervention is feasible with some modifications, as it had similar preliminary effectiveness as the traditional telephone intervention, and the participants had better satisfaction with and similar or better adherence to the intervention, but it did not reduce the time use of coaches. The technology should be improved to provide more digested information for action planning and templates for messaging. TRIAL REGISTRATION: ClinicalTrials.gov NCT02445950; https://www.clinicaltrials.gov/ct2/show/study/NCT02445950.

Associations Between Engagement with the BitHabit Digital Lifestyle Intervention and Changes in Type 2 Diabetes Risk Factors.

Type 2 diabetes (T2D) can be prevented or delayed through a healthy lifestyle. Digital behavior change interventions (DBCIs) may offer cost-effective and scalable means to support lifestyle changes. This study investigated associations between user engagement with a habit-formation-based DBCI, the BitHabit app, and changes in T2D risk factors over 12 months in 963 participants at risk of T2D. User engagement was characterized by calculating use metrics from the BitHabit log data. User ratings were used as a subjective measure of engagement. The use metrics and user ratings were the strongest associated with improvements in diet quality. Weak positive associations were observed between the use metrics and changes in waist circumference and body mass index. No associations were found with changes in physical activity, fasting plasma glucose, or plasma glucose two hours after an oral glucose tolerance test. To conclude, increased use of the BitHabit app can have beneficial impacts on T2D risk factors, especially on diet quality.

A measure for assessment of beneficial and harmful fortitude: development and initial validation of the Sisu Scale.

Sisu is a Finnish cultural concept that denotes determination and resoluteness in the face of adversity. We propose that sisu will supplement the English-language based research on mental fortitude traits. Sisu has not been the focus of systematic research until very recently. We created a new questionnaire measuring sisu (the Sisu Scale), sought to validate the sisu construct and its sub-factor structure as postulated in a recent qualitative study. We investigated associations of sisu with other measures of mental fortitude and well-being. More generally we aimed to enrichen the cross-cultural understanding of human experience of overcoming adversity across life's challenges. We describe and validate a questionnaire that effectively measures both beneficial and harmful sisu, each comprising three sub-factors. Beneficial sisu was associated with other measures of fortitude, but less with personality dimensions. We also confirmed the existence of an independent harmful sisu factor. Beneficial sisu was associated with higher well-being and lower depressive symptoms, and harmful sisu with lower well-being and higher levels of general stress, work stress and depressive symptoms. Together the two factors were superior compared to pre-existing measures when predicting well-being-related variables. Results suggest that the new Sisu Scale we developed may provide a valuable addition to research on mental fortitude, resilience and their consequences for well-being.

Exploring Associations Between the Self-Reported Values, Well-Being, and Health Behaviors of Finnish Citizens: Cross-Sectional Analysis of More Than 100,000 Web-Survey Responses.

BACKGROUND: Understanding the relationship between personal values, well-being, and health-related behavior could facilitate the development of engaging, effective digital interventions for promoting well-being and the healthy lifestyles of citizens. Although the associations between well-being and values have been quite extensively studied, the knowledge about the relationship between health behaviors and values is less comprehensive. OBJECTIVE: The aim of this study was to assess retrospectively the associations between self-reported values and commitment to values combined with self-reported well-being and health behaviors from a large cross-sectional dataset. METHODS: We analyzed 101,130 anonymous responses (mean age 44.78 years [SD 13.82]; 78.88%, 79,770/101,130 women) to a Finnish Web survey, which were collected as part of a national health promotion campaign. The data regarding personal values were unstructured, and the self-reported value items were classified into value types based on the Schwartz value theory and by applying principal component analysis. Logistic and multiple linear regression were used to explore the associations of value types and commitment to values with well-being factors (happiness, communal social activity, work, and family-related distress) and health behaviors (exercise, eating, smoking, alcohol consumption, and sleep). RESULTS: Commitment to personal values was positively related to happiness (part r2=0.28), communal social activity (part r2=0.09), and regular exercise (part r2=0.06; P<.001 for all). Health, Power (social status and dominance), and Mental balance (self-acceptance) values had the most extensive associations with health behaviors. Regular exercise, healthy eating, and nonsmoking increased the odds of valuing Health by 71.7%, 26.8%, and 40.0%, respectively (P<.001 for all). Smoking, unhealthy eating, irregular exercise, and increased alcohol consumption increased the odds of reporting Power values by 27.80%, 27.78%, 24.66%, and 17.35%, respectively (P<.001 for all). Smoking, unhealthy eating, and irregular exercise increased the odds of reporting Mental balance values by 20.79%, 16.67%, and 15.37%, respectively (P<.001 for all). In addition, lower happiness levels increased the odds of reporting Mental balance and Power values by 24.12% and 20.69%, respectively (P<.001 for all). CONCLUSIONS: The findings suggest that commitment to values is positively associated with happiness and highlight various, also previously unexplored, associations between values and health behaviors.

Citizen-Centric Web-Based Health Profiling Service: A Service Concept and a Profiling Method.

Personalization of health interventions has been shown to increase their effectiveness. In digital services, user profiles enable this personalization. We introduce a web-based user profiling service, where citizens can 1) create various personal profiles, specific to certain health topics, by providing their personal data, 2) get summarized feedback on their health and behavioral determinants regarding each profile, and 3) share their profiles with health service providers. As part of the service, we define a profiling method that identifies the health needs and behavioral determinants of citizens, and highlights their most potential behavior change targets. The novelty in the service arises from allowing citizens to govern their health data, quantifying automatically various behavioral determinants, and summarizing aggregated knowledge efficiently via simple visualizations. The service aims to evoke personal awareness about behavior change needs and the factors influencing behavior, enable health service providers to develop and offer highly personalized, automated interventions, and facilitate time-efficient and transparent decision-making of health professionals. According to a preliminary concept evaluation with citizens (N=29), the presented profile feedback was perceived as interesting and intuitive.

An m-Health system for education and motivation in cardiac rehabilitation: the experience of HeartCycle guided exercise.

Introduction Home-based programmes for cardiac rehabilitation play a key role in the recovery of patients with coronary artery disease. However, their necessary educational and motivational components have been rarely implemented with the help of modern mobile technologies. We developed a mobile health system designed for motivating patients to adhere to their rehabilitation programme by providing exercise monitoring, guidance, motivational feedback, and educational content. Methods Our multi-disciplinary approach is based on mapping "desired behaviours" into specific system's specifications, borrowing concepts from Fogg's Persuasive Systems Design principles. A randomised controlled trial was conducted to compare mobile-based rehabilitation (55 patients) versus standard care (63 patients). Results Some technical issues related to connectivity, usability and exercise sessions interrupted by safety algorithms affected the trial. For those who completed the rehabilitation (19 of 55), results show high levels of both user acceptance and perceived usefulness. Adherence in terms of started exercise sessions was high, but not in terms of total time of performed exercise or drop-outs. Educational level about heart-related health improved more in the intervention group than the control. Exercise habits at 6 months follow-up also improved, although without statistical significance. Discussion Results indicate that the adopted design methodology is promising for creating applications that help improve education and foster better exercise habits, but further studies would be needed to confirm these indications.

Personalized behavior change support for disease prevention.

Healthy lifestyle is essential in prevention of chronic diseases. However, people need motivation and support to achieve and to maintain behavior changes. Moreover, effective behavior change support should be personalized to individual's unique characteristics, needs and context. This paper presents a blueprint of an ICT system, which is able to provide holistic, dynamic support for healthy behaviors, engaging also various co-producers in the health journey of a person. Three main concepts in the system are Virtual Individual, which maintains the user's personal profile, PGS-Mall, which collects various health and well-being services into one place, and HealthGuides, which support healthy choices in everyday life and coordinate the interactions between the user, the system, and other co-producers of health.

Rethinking health: ICT-enabled services to empower people to manage their health.

Lifestyle is a key determinant in the prevention and management of chronic diseases. If we would exercise regularly, eat healthy, control our weight, sleep enough, manage stress, not smoke and use alcohol only moderately, 90% of type II diabetes, 80% of coronary heart disease, and 70% of stroke could be prevented. Health statistics show that lifestyle related diseases are increasing at an alarming rate. Public health promotion campaigns and healthcare together are not effective enough to stop this "tsunami". The solution that is offered is to empower people to manage their health with the assistance of ICT-enabled services. A lot of R&D and engineering effort is being invested in Personal Health Systems. Although some progress has been made, the market for such systems has not yet emerged. The aim of this critical review is to identify the barriers which are holding back the growth of the market. It looks into the theoretical foundations of behavior change support, the maturity of the technologies for behavior change support, and the business context in which behavior change support systems are used.

A personalized approach for predicting the effect of aerobic exercise on blood pressure using a Fuzzy Inference System.

Regular aerobic exercise is a recommended treatment for elevated blood pressure (BP). However, making permanent lifestyle changes is not easy. Having personally relevant information about the treatment, about its effects and importance, is a precondition for motivation. Thus, the first step towards a successful lifestyle change is appropriate education. This paper describes a Sugeno-type Fuzzy Inference System (FIS) that predicts the effect of regular aerobic exercise on blood pressure based on the exercise dose variables, exercise frequency and intensity, as well as demographics (age, gender, ethnicity), and the baseline BP of a person. Since BP response to exercise varies largely between individuals, the system takes an initial step towards personalized prediction. Hence, the system can be used to educate a person about the benefits of exercise on BP in a personally relevant way, providing more accurate information than traditional education materials. Furthermore, preliminary validation results of the performance of the FIS are promising. The predictions comply with the findings of medical research for populations, though the individual-level validation remains still to be done.