The combination of self-tracking and persuasive eCoaching in healthy lifestyle interventions is a promising approach. The objective of this study is to map the key components of existing healthy lifestyle interventions combining self-tracking and persuasive eCoaching using the scoping review methodology in accordance with the York methodological framework by Arksey and O’Malley. Seven studies were included in this preliminary scoping review. Components related to persuasive eCoaching applied only in effective interventions were reduction of complex behavior into small steps, providing positive motivational feedback by praise and providing reliable information to show expertise. Concerning self-tracking, it did not seem to matter if more action was required by the participant to obtain personal data. The first results of this study indicate the necessity to identify the needs and problems of the specific target group of the interventions, due to differences found between various groups of users. In addition to objective data on lifestyle and health behavior, other factors need to be taken into account, such as the context of use, daily experiences, and feelings of the users.
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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.
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Self-tracking and automated persuasive eCoaching combined in a smartphone application may enhance stress management among employees at an early stage. For the application to be persuasive and create impact, we need to achieve a fit between the design and end-users’ and important stakeholders’ values. Semi-structured interviews were conducted among 8 employees and 8 human resource advisors to identify values of self-tracking, persuasive eCoaching, and preconditions (e.g., privacy and implementation) for a stress management application, using the value proposition design by Osterwalder et al. Results suggest essential features and functionalities that the application should possess. In general, respondents see potential in combining self-tracking and persuasive eCoaching for stress management via a smartphone application. Future design of the application should mainly focus on gaining awareness about the level of stress and causes of stress. In addition, the application should possess a positive approach besides solely the focus on negative aspects of stress.
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The purpose of this study was to determine the efficacy of an online self-tracking program on physical activity, glycated hemoglobin, and other health measures in patients with type 2 diabetes. Seventy-two patients with type 2 diabetes were randomly assigned to an intervention or control group. All participants received usual care. The intervention group received an activity tracker (Fitbit Zip) connected to an online lifestyle program. Physical activity was analyzed in average steps per day from week 0 until 12. Health outcome measurements occurred in both groups at baseline and after 13 weeks. Results indicated that the intervention group significantly increased physical activity with 1.5 ± 3 days per week of engagement in 30 minutes of moderate-vigorous physical activity versus no increase in the control group (P = .047). Intervention participants increased activity with 1255 ± 1500 steps per day compared to their baseline (P < .010). No significant differences were found in glycated hemoglobin A1c, with the intervention group decreasing -0.28% ± 1.03% and the control group showing -0.0% ± 0.69% (P = .206). Responders (56%, increasing minimally 1000 steps/d) had significantly decreased glycated hemoglobin compared with nonresponders (-0.69% ± 1.18% vs 0.22% ± 0.47%, respectively; P = .007). To improve effectiveness of eHealth programs, additional strategies are needed.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
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1e alinea column: De grote beweging via ketenomkering naar customer self care en bottom-up self assembled teaming is zich snel aan het voltrekken. De klant neemt het initiatief en Tofflers prosumership wordt zichtbaar. Het aantal business voorbeelden wordt snel groter, al gaat het om je auto zelf samenstellen, onderdelen bestellen, 3D printing, zelfroosteren, civil journalism, klanten die restaurants recenseren, tracking &tracing van de post, medische zorg. Neem Qlinx als open architectuur in combinatie met bijvoorbeeld Twitter, dat laat goed zien wat dit kan gaan betekenen voor de dynamiek op de arbeidsmarkt. Wolfram-alpha toont de potentie van het semantic web. In bijvoorbeeld Share2Start - power of the open mind zien we de kracht van crowdfunding en het begin van ‘financials 2.0’. Deze sites laten goed zien welke richting het uitgaat.
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ACHTERGROND EN DOELAspecifieke lage rug- en/of nekpijn is een veel voorkomende klacht en kan tot veel beperkingen in ADL leiden. De vraag is “wat is de toegevoegde waarde van een self-tracking systeem de LumoBack” voor de fysiotherapie.METHODEIn dit onderzoek is geobserveerd of patiënten met aspeci eke lage rug en/of nekklachten (ALRNK) na twee weken gebruik van de LumoBack en reguliere fysiotherapie (groep A) minder moeite in activiteiten hebben en minder pijn ervaren, dan patiënten die alleen twee weken reguliere fysiotherapie (groep B) kregen. Het onderzoek bestond uit een voor- en nameting waarbij de VAS, de PSK en de QBPDS werden afgenomen.RESULTATENUit de resultaten blijkt dat er na twee weken geen signi cant verschil is gevonden tussen beide groepen. Wel is de verbetering in VAS1 en PSK3 signi cant verschillend tussen beide groepen. Groep A laat grotere verbeteringen zien met een klinisch relevante vermindering in vas 1 en vas 2.
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On this website I blog about Quantified Self, health, statistics, wearables, self-tracking. Relevant experiments, issue's, thoughts, and idea's are discussed.
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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.
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