The Explanations People Give for Going to Bed Late: A Qualitative Study of the Varieties of Bedtime Procrastination.

Background/Objective: Bedtime procrastination is a prevalent cause of sleep deprivation, but little is known about why people delay their bedtimes. In the present research, we conducted a qualitative study with bedtime procrastinators to classify their self-reported reasons for later-than-intended bedtime. Participants: Participants (N = 17) were selected who frequently engaged in bedtime procrastination, but whose sleep was not otherwise affected by diagnosed sleep disorders or shift work. Method: We conducted in-depth, semistructured interviews and used thematic analysis to identify commonly recurring themes in the interviews. Results and conclusions: Three emerging themes were identified: deliberate procrastination, mindless procrastination, and strategic delay. For the form of procrastination we classified as deliberate procrastination, participants typically reported wilfully delaying their bedtime because they felt they deserved some time for themselves. For the category of mindless procrastination, a paradigmatic aspect was that participants lost track of the time due to being immersed in their evening activities. Finally, participants who engaged in strategic delay reported going to bed late because they felt they needed to in order to fall asleep (more quickly), which suggests that despite describing themselves as "procrastinating," their bedtime delay may actually be linked to undiagnosed insomnia. The conceptual distinctions drawn in this paper deepen our understanding of bedtime delay and may be helpful for designing effective interventions.

Do heart failure status and psychosocial variables moderate the relationship between leisure time physical activity and mortality risk among patients with a history of myocardial infarction?

BACKGROUND: Leisure time physical activity (LTPA) is inversely related to mortality risk among patients with a history of myocardial infarction (MI). The aims were to explore if heart failure (HF) status and psychosocial variables moderate the association. METHODS: Participants (n = 1169) were from a multi-center prospective cohort study. Information on LTPA (none, irregular,1-150, 151-300 and >300 weekly minutes), depression, social support and other prognostic indicators were collected 10-13 years after index MI. Cox regressions were conducted, adjusting for potential confounders. In case of significant moderation by HF-status or psychosocial variables, stratified analyses were performed. RESULTS: During follow-up (M = 8.4 years), 25.6 % of the sample had died. LTPA was inversely associated with mortality (p for trend < 0.01 in all models). HF did not, but psychosocial variables did, moderate the association. In the LTPA category 1-150 weekly minutes, patients with a high level of depression had a lower mortality risk in comparison to those with a low level (hazard ratios (95 % confidence intervals) were 0.43 (0.25, 0.75) versus 0.69 (0.36, 1.32)), and patients with a low level of social support had a lower mortality risk in comparison to those with a high level (0.40 (0.21, 0.77) versus 0.71 (0.39, 1.27)). In the category >300 min, patients with a high level of social support had a lower mortality risk than those with a low level (0.38 (0.19, 0.79) versus 0.51 (0.30, 0.87)). CONCLUSIONS: LTPA was inversely related to mortality risk of post-MI patients. HF did not moderate the relationship; depression and social support partially did.

MI-PACE Home-Based Cardiac Telerehabilitation Program for Heart Attack Survivors: Usability Study.

BACKGROUND: Cardiac rehabilitation programs, consisting of exercise training and disease management interventions, reduce morbidity and mortality after acute myocardial infarction. OBJECTIVE: In this pilot study, we aimed to developed and assess the feasibility of delivering a health watch-informed 12-week cardiac telerehabilitation program to acute myocardial infarction survivors who declined to participate in center-based cardiac rehabilitation. METHODS: We enrolled patients hospitalized after acute myocardial infarction at an academic medical center who were eligible for but declined to participate in center-based cardiac rehabilitation. Each participant underwent a baseline exercise stress test. Participants received a health watch, which monitored heart rate and physical activity, and a tablet computer with an app that displayed progress toward accomplishing weekly walking and exercise goals. Results were transmitted to a cardiac rehabilitation nurse via a secure connection. For 12 weeks, participants exercised at home and also participated in weekly phone counseling sessions with the nurse, who provided personalized cardiac rehabilitation solutions and standard cardiac rehabilitation education. We assessed usability of the system, adherence to weekly exercise and walking goals, counseling session attendance, and disease-specific quality of life. RESULTS: Of 18 participants (age: mean 59 years, SD 7) who completed the 12-week telerehabilitation program, 6 (33%) were women, and 6 (33%) had ST-elevation myocardial infarction. Participants wore the health watch for a median of 12.7 hours (IQR 11.1, 13.8) per day and completed a median of 86% of exercise goals. Participants, on average, walked 121 minutes per week (SD 175) and spent 189 minutes per week (SD 210) in their target exercise heart rate zone. Overall, participants found the system to be highly usable (System Usability Scale score: median 83, IQR 65, 100). CONCLUSIONS: This pilot study established the feasibility of delivering cardiac telerehabilitation at home to acute myocardial infarction survivors via a health watch-based program and telephone counseling sessions. Usability and adherence to health watch use, exercise recommendations, and counseling sessions were high. Further studies are warranted to compare patient outcomes and health care resource utilization between center-based rehabilitation and telerehabilitation.

Factors Influencing Walking and Exercise Adherence in Healthy Older Adults Using Monitoring and Interfacing Technology: Preliminary Evidence.

BACKGROUND: Monitoring and interfacing technologies may increase physical activity (PA) program adherence in older adults, but they should account for aspects influencing older adults' PA behavior. This study aimed at gathering preliminary wrist-based PA adherence data in free-living and relate these to the influencing factors. METHODS: Ten healthy older adults (4 females, aged 70-78 years) provided health, fatigue, activity levels, attitude towards pacing, and self-efficacy information and performed a 6 min-walk test to assess their fitness. After a baseline week they followed a two-week walking and exercise intervention. Participants saw their progress via a purposely designed mobile application. RESULTS: Walking and exercise adherence did not increase during the intervention (p = 0.38, p = 0.65). Self-efficacy decreased (p = 0.024). The baseline physical component of the Short Form Health Survey was the most predictive variable of walking adherence. Baseline perceived risk of over-activity and resting heart rate (HRrest) were the most predictive variables of exercise adherence. When the latter two were used to cluster participants according to their exercise adherence, the fitness gap between exercise-adherent and non-adherent increased after the intervention (p = 0.004). CONCLUSIONS: Risk of over-activity and HRrest profiled short-term exercise adherence in older adults. If confirmed in a larger and longer study, these could personalize interventions aimed at increasing adherence.

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.

Proof of concept of a 45-second cardiorespiratory fitness self-test for coronary artery disease patients based on accelerometry.

Cardiorespiratory fitness (CRF) provides important diagnostic and prognostic information. It is measured directly via laboratory maximal testing or indirectly via submaximal protocols making use of predictor parameters such as submaximal [Formula: see text], heart rate, workload, and perceived exertion. We have established an innovative methodology, which can provide CRF prediction based only on body motion during a periodic movement. Thirty healthy subjects (40% females, 31.3 ± 7.8 yrs, 25.1 ± 3.2 BMI) and eighteen male coronary artery disease (CAD) (56.6 ± 7.4 yrs, 28.7 ± 4.0 BMI) patients performed a [Formula: see text] test on a cycle ergometer as well as a 45 second squatting protocol at a fixed tempo (80 bpm). A tri-axial accelerometer was used to monitor movements during the squat exercise test. Three regression models were developed to predict CRF based on subject characteristics and a new accelerometer-derived feature describing motion decay. For each model, the Pearson correlation coefficient and the root mean squared error percentage were calculated using the leave-one-subject-out cross-validation method (rcv, RMSEcv). The model built with all healthy individuals' data showed an rcv = 0.68 and an RMSEcv = 16.7%. The CRF prediction improved when only healthy individuals with normal to lower fitness (CRF<40 ml/min/kg) were included, showing an rcv = 0.91 and RMSEcv = 8.7%. Finally, our accelerometry-based CRF prediction CAD patients, the majority of whom taking ß-blockers, still showed high accuracy (rcv = 0.91; RMSEcv = 9.6%). In conclusion, motion decay and subject characteristics could be used to predict CRF in healthy people as well as in CAD patients taking ß-blockers, accurately. This method could represent a valid alternative for patients taking ß-blockers, but needs to be further validated in a larger population.

Potential role for clinical calibration to increase engagement with and application of home telemonitoring: a report from the HeartCycle programme.

AIMS: There is a need for alternative strategies that might avoid recurrent admissions in patients with heart failure. home telemonitoring (HTM) to monitor patient's symptoms from a distance may be useful. This study attempts to assess changes in HTM vital signs in response to daily life activities (variations in medication, salt intake, exercise, and stress) and to establish which variations affect weight, blood pressure, and heart rate. METHODS AND RESULTS: We assessed 76 patients with heart failure (mean age 76 ± 10.8 years, 75% male, mainly in NYHA class II/III and from ischaemic aetiology cause). Patients were given a calendar of interventions scheduling activities approximately twice a week before measuring their vital signs. Eating salty food or a large meal were the activities that had a significant impact on weight gain (+0.3 kg; P < 0.001 and P = 0.006, respectively). Exercise and skipping a dose of medication other than diuretics increased heart rate (+3 bpm, P = 0.001 and almost +2 bpm, P = 0.016, respectively). CONCLUSIONS: Our HTM system was able to detect small changes in vital signs related to these activities. Further studies should assess if providing such a schedule of activities might be useful for patient education and could improve long-term adherence to recommended lifestyle changes.

Clinical and cost-effectiveness of home-based cardiac rehabilitation compared to conventional, centre-based cardiac rehabilitation: Results of the FIT@Home study.

Aim Although cardiac rehabilitation improves physical fitness after a cardiac event, many eligible patients do not participate in cardiac rehabilitation and the beneficial effects of cardiac rehabilitation are often not maintained over time. Home-based training with telemonitoring guidance could improve participation rates and enhance long-term effectiveness. Methods and results We randomised 90 low-to-moderate cardiac risk patients entering cardiac rehabilitation to three months of either home-based training with telemonitoring guidance or centre-based training. Although training adherence was similar between groups, satisfaction was higher in the home-based group ( p = 0.02). Physical fitness improved at discharge ( p < 0.01) and at one-year follow-up ( p < 0.01) in both groups, without differences between groups (home-based p = 0.31 and centre-based p = 0.87). Physical activity levels did not change during the one-year study period (centre-based p = 0.38, home-based p = 0.80). Healthcare costs were statistically non-significantly lower in the home-based group (€437 per patient, 95% confidence interval -562 to 1436, p = 0.39). From a societal perspective, a statistically non-significant difference of €3160 per patient in favour of the home-based group was found (95% confidence interval -460 to 6780, p = 0.09) and the probability that it was more cost-effective varied between 97% and 75% (willingness-to-pay of €0 and €100,000 per quality-adjusted life-years, respectively). Conclusion We found no differences between home-based training with telemonitoring guidance and centre-based training on physical fitness, physical activity level or health-related quality of life. However, home-based training was associated with a higher patient satisfaction and appears to be more cost-effective than centre-based training. We conclude that home-based training with telemonitoring guidance can be used as an alternative to centre-based training for low-to-moderate cardiac risk patients entering cardiac rehabilitation.

A distributed shared data space for personal health systems.

Ubiquitous computing is a promising paradigm to support health care outside traditional care institutes. Sensor-based systems may continuously collect data on a person's health status and context, and provide immediate feedback or contact a remote physician. This paper presents a novel programming model to facilitate the development of such systems. The model, which has been inspired by tuple spaces, offers robustness for ad hoc mobile environments and explicit support for data streams.

Energy expenditure estimation in beta-blocker-medicated cardiac patients by combining heart rate and body movement data.

BACKGROUND: Accurate assessment of energy expenditure provides an opportunity to monitor physical activity during cardiac rehabilitation. However, the available assessment methods, based on the combination of heart rate (HR) and body movement data, are not applicable for patients using beta-blocker medication. Therefore, we developed an energy expenditure prediction model for beta-blocker-medicated cardiac rehabilitation patients. METHODS: Sixteen male cardiac rehabilitation patients (age: 55.8 ± 7.3 years, weight: 93.1 ± 11.8 kg) underwent a physical activity protocol with 11 low- to moderate-intensity common daily life activities. Energy expenditure was assessed using a portable indirect calorimeter. HR and body movement data were recorded during the protocol using unobtrusive wearable devices. In addition, patients underwent a symptom-limited exercise test and resting metabolic rate assessment. Energy expenditure estimation models were developed using multivariate regression analyses based on HR and body movement data and/or patient characteristics. In addition, a HR-flex model was developed. RESULTS: The model combining HR and body movement data and patient characteristics showed the highest correlation and lowest error (r2 = 0.84, root mean squared error = 0.834 kcal/minute) with total energy expenditure. The method based on individual calibration data (HR-flex) showed lower accuracy (i2 = 0.83, root mean squared error = 0.992 kcal/minute). CONCLUSIONS: Our results show that combining HR and body movement data improves the accuracy of energy expenditure prediction models in cardiac patients, similar to methods that have been developed for healthy subjects. The proposed methodology does not require individual calibration and is based on the data that are available in clinical practice.

Adherence to self-care in patients with heart failure in the HeartCycle study.

PURPOSE: The purpose of this study was to evaluate a novel online education and coaching program to promote self-care among patients with heart failure. In this program, education and coaching content is automatically tailored to the knowledge and behavior of the patient. PATIENTS AND METHODS: The evaluation of the program took place within the scope of the HeartCycle study. This multi-center, observational study examined the ability of a third generation telehealth system to enhance the management of patients recently (<60 days) admitted to the hospital for worsening heart failure or outpatients with persistent New York Heart Association (NYHA) Functional Classification III/IV symptoms. Self-reported self-care behavior was assessed at baseline and study-end by means of the 9-item European Heart Failure Self-care Behavior scale. Adherence to daily weighing, blood pressure monitoring, and reporting of symptoms was determined by analyzing the system's database. RESULTS: Of 123 patients enrolled, the mean age was 66±12 years, 66% were in NYHA III and 79% were men. Self-reported self-care behavior scores (n=101) improved during the study for daily weighing, low-salt diet, physical activity (P<0.001), and fluid restriction (P<0.05). Average adherence (n=120) to measuring weight was 90%±16%, to measuring blood pressure was 89%±17% and to symptom reporting was 66%±32%. CONCLUSION: Self-reported self-care behavior scores improved significantly during the period of observation, and the objective evidence of adherence to daily weight and blood pressure measurements was high and remained stable over time. However, adherence to daily reporting of symptoms was lower and declined in the long-term.

Development of Motivate4Change Using the Intervention Mapping Protocol: An Interactive Technology Physical Activity and Medication Adherence Promotion Program for Hospitalized Heart Failure Patients.

BACKGROUND: It is important that heart failure (HF) patients adhere to their medication regimen and engage in physical activity. Evidence shows that adherence to these HF self-management behaviors can be improved with appropriate interventions. OBJECTIVE: To further promote medication adherence and physical activity among HF patients, we developed an intervention for hospitalized HF patients. METHODS: The intervention mapping protocol was applied in the development of the intervention. This entailed performing a needs assessment, defining change objectives, selecting determinants and strategies, and developing the materials. RESULTS: The resulting intervention, Motivate4Change, makes use of interactive technology and provides HF patients with personalized feedback and advice. Specific change objectives were defined. The relevant behavioral determinants for the physical activity program were practical knowledge on physical activity performance and self-efficacy for, and perceived benefits of, physical activity. For medication-taking, the selected determinants were practical knowledge on medication-taking, perceived barriers to medication-taking, beliefs about the necessity and harm regarding the medication prescribed, and beliefs about overprescribing and harm of medication in general. The change objectives and behavior change determinants were translated in feedback and advice strategies in an interactive technology program that included tailored feedback and advice, and role models in videos in which the behaviors and overcoming barriers were demonstrated. Relevant stakeholders were involved in the interventions development process. The intervention was pretested among HF patients and adjustments were made accordingly. CONCLUSIONS: The interactive technology physical activity and medication adherence promotion program for hospitalized HF patients was systematically developed using the intervention mapping protocol and was based on the available theory and evidence regarding HF self-management behavior change. The intervention's efficacy is yet to be determined in evaluation research.

Predicting energy expenditure from photo-plethysmographic measurements of heart rate under beta blocker therapy: Data driven personalization strategies based on mixed models.

Energy expenditure have been often estimated using computational models based on heart rate (HR) and appropriate personalization strategies to account for users cardio-respiratory characteristics. However, medications like beta blockers which are prescribed to treat several cardiac conditions have a direct influence on the cardiovascular system and may impact the relationship between HR and energy expenditure during physical activity (AEE). This study proposes to estimate AEE from HR using mixed models (MIX-REG) by introducing a novel method to personalize the prediction equation. We selected as features to represent the individual random effect in the MIX-REG model those subject characteristics which minimized both estimation error (RMSE) and between-subjects error bias variability. Data from 17 patients post-myocardial infarction were collected during a laboratory protocol. AEE was measured using indirect calorimetry and HR using an innovative wrist worn activity monitor equipped with the Philips Cardio and Motion Monitoring Module (CM3-Generation-1), which is an integrated module including a photo-plethysmographic and accelerometer sensor. The presented method showed large AEE estimation accuracy (RMSE = 1.35 kcal/min) which was comparable to that of models personalized using data from laboratory calibration protocols (HR-FLEX) and was superior to multi-linear regression and MIX-REG models trained using a stepwise features selection procedure.

Design and Usage of the HeartCycle Education and Coaching Program for Patients With Heart Failure.

BACKGROUND: Heart failure (HF) is common, and it is associated with high rates of hospital readmission and mortality. It is generally assumed that appropriate self-care can improve outcomes in patients with HF, but patient adherence to many self-care behaviors is poor. OBJECTIVE: The objective of our study was to develop and test an intervention to increase self-care in patients with HF using a novel, online, automated education and coaching program. METHODS: The online automated program was developed using a well-established, face-to-face, home-based cardiac rehabilitation approach. Education is tailored to the behaviors and knowledge of the individual patient, and the system supports patients in adopting self-care behaviors. Patients are guided through a goal-setting process that they conduct at their own pace through the support of the system, and they record their progress in an electronic diary such that the system can provide appropriate feedback. Only in challenging situations do HF nurses intervene to offer help. The program was evaluated in the HeartCycle study, a multicenter, observational trial with randomized components in which researchers investigated the ability of a third-generation telehealth system to enhance the management of patients with HF who had a recent (<60 days) admission to the hospital for symptoms or signs of HF (either new onset or recurrent) or were outpatients with persistent New York Heart Association (NYHA) functional class III/IV symptoms despite treatment with diuretic agents. The patients were enrolled from January 2012 through February 2013 at 3 hospital sites within the United Kingdom, Germany, and Spain. RESULTS: Of 123 patients enrolled (mean age 66 years (SD 12), 66% NYHA III, 79% men), 50 patients (41%) reported that they were not physically active, 56 patients (46%) did not follow a low-salt diet, 6 patients (5%) did not restrict their fluid intake, and 6 patients (5%) did not take their medication as prescribed. About 80% of the patients who started the coaching program for physical activity and low-salt diet became adherent by achieving their personal goals for 2 consecutive weeks. After becoming adherent, 61% continued physical activity coaching, but only 36% continued low-salt diet coaching. CONCLUSIONS: The HeartCycle education and coaching program helped most nonadherent patients with HF to adopt recommended self-care behaviors. Automated coaching worked well for most patients who started the coaching program, and many patients who achieved their goals continued to use the program. For many patients who did not engage in the automated coaching program, their choice was appropriate rather than a failure of the program.

An interactive-technology health behavior promotion program for heart failure patients: a pilot study of experiences and needs of patients and nurses in the hospital setting.

BACKGROUND: Heart failure (HF) is a chronic condition, prevalent especially among older people, characterized by acute episodes leading to hospitalization. To promote HF patients' engagement in physical activity (PA) and adherence to medication, we developed Motivate4Change: a new interactive, information and communication technology (ICT)-based health promotion program for delivery in the hospital. The development of this program was guided by the Intervention Mapping protocol for the planning of health promotion programs. The users of Motivate4Change were defined as hospitalized HF patients and hospital nurses involved in HF patient education. OBJECTIVE: Two aims were addressed. First, to explore the use of interactive technology in the hospital setting and second, to evaluate user needs in order to incorporate them in Motivate4Change. METHODS: Participant observations at a hospital in the United Kingdom and semistructured interviews were conducted with hospitalized HF patients and HF nurses following their completion of Motivate4Change. Interviews were recorded, transcribed, and analyzed according to a thematic coding approach. RESULTS: Seven patients and 3 nurses completed Motivate4Change and were interviewed. Results demonstrated that patient needs included empathic and contextual content, interactive learning, and support from others, including nurses and family members. The nurse needs included integration in current educational practices and finding opportunities for provision of the program. CONCLUSIONS: The current work provides insight into user needs regarding an interactive-technology health promotion program for implementation in the hospital setting, such as Motivate4Change.

HeartCycle: user interaction and patient education.

Cardiovascular Diseases are the most prevalent and serious chronic conditions existing nowadays. They are the primary cause of death in the world and generate enormous expenditures to the health systems. Tele-monitoring and personal health systems have proven to be good options for tackling this situation; however they are still lacking many functionalities. It is necessary to find solutions that allow health professionals to follow up patients more closely and efficiently, while reducing the non-adherence of patients to the treatment regime. HeartCycle research project (partially funded by the European Commission) has developed a personal health system for cardiovascular diseases management with the aim to address this problem. This paper describes the Patient Loop of this solution, including the different components, the adopted user interaction, and the implemented patients' education and coaching strategy.