Samen met onderzoekers van het Lectoraat Healthy Ageing, Allied Health Care and Nursing van de Hanzehogeschool en het Centrum voor Beweging en Onderzoek (CBO Groningen) hebben we tien populaire activity trackers onder de loep genomen. In het kort bestond dit onderzoek eruit dat we een groep proefpersonen de verschillende trackers hebben laten testen, zowel in een laboratoriumsetting (waarbij de metingen werden vergeleken met de gouden standaard; een handteller die – leuk om te vermelden – na al die duizenden stappen is stukgegaan) als buiten, in het wild, op een gewone werkdag. Recent hebben we nog eens tien populaire activity trackers in het lab getest. De resultaten waren over het algemeen boven verwachting, met name op het vlak van de betrouwbaarheid. Wat betreft de validiteit kan gezegd worden dat die in het algemeen minder goed is bij activity trackers die om de pols worden gedragen. (En dat is in feite logisch: ‘polstrackers’ letten op armbewegingen. In het lab, op de loopband, gaat dit nog behoorlijk goed (1 armzwaai = 1 looppas ) maar in het echte leven zwaai je ook wel eens met een arm bij het koffiezetten.) Uit de twintig geteste trackers is de volgende top 5 naar voren gekomen.
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Aim: The aim of this study was to describe the experience with commercially available activity trackers embedded in the physiotherapy treatment of patients with a chronic disease. Methods: In a qualitative study, 29 participants with a chronic disease participated. They wore an activity tracker for two to eight weeks. Data were collected using 23 interviews and discussion with 6 participants. A framework analysis was used to analyze the data. Results: The framework analysis resulted in seven categories: purchase, instruction, characteristics, correct functioning, sharing data, privacy, use, and interest in feedback. The standard goal of the activity trackers was experienced as too high, however the tracker still motivated them to be more active. Participants would have liked more guidance from their physiotherapists because they experienced the trackers as complex. Participants experienced some technical failures, are willing to share data with their physiotherapist and, want to spend a maximum of €50,-. Conclusion: The developed framework gives insight into all important concepts from the experiences reported by patients with a chronic disease and can be used to guide further research and practice. Patients with a chronic disease were positive regarding activity trackers in general. When embedded in physiotherapy, more attention should be paid to the integration in treatment.
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Aim: The aim of this study was to describe the experience with commercially available activity trackers embedded in the physiotherapy treatment of patients with a chronic disease. Methods: In a qualitative study, 29 participants with a chronic disease participated. They wore an activity tracker for two to eight weeks. Data were collected using 23 interviews and discussion with 6 participants. A framework analysis was used to analyze the data. Results: The framework analysis resulted in seven categories: purchase, instruction, characteristics, correct functioning, sharing data, privacy, use, and interest in feedback. The standard goal of the activity trackers was experienced as too high, however the tracker still motivated them to be more active. Participants would have liked more guidance from their physiotherapists because they experienced the trackers as complex. Participants experienced some technical failures, are willing to share data with their physiotherapist and, want to spend a maximum of e50,-. Conclusion: The developed framework gives insight into all important concepts from the experiences reported by patients with a chronic disease and can be used to guide further research and practice. Patients with a chronic disease were positive regarding activity trackers in general. When embedded in physiotherapy, more attention should be paid to the integration in treatment.
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Background: Activity trackers can potentially stimulate users to increase their physical activity behavior. The aim of this study was to examine the reliability and validity of ten consumer activity trackers for measuring step count in both laboratory and free-living conditions.Method: Healthy adult volunteers (n = 33) walked twice on a treadmill (4.8 km/h) for 30 min while wearing ten different activity trackers (i.e. Lumoback, Fitbit Flex, Jawbone Up, Nike+ Fuelband SE, Misfit Shine, Withings Pulse, Fitbit Zip, Omron HJ-203, Yamax Digiwalker SW-200 and Moves mobile application). In free-living conditions, 56 volunteers wore the same activity trackers for one working day. Test-retest reliability was analyzed with the Intraclass Correlation Coefficient (ICC).Validity was evaluated by comparing each tracker with the gold standard (Optogait system for laboratory and ActivPAL for free-living conditions), using paired samples t-tests, mean absolute percentage errors, correlations and Bland-Altman plots.Results: Test-retest analysis revealed high reliability for most trackers except for the Omron (ICC .14), Moves app (ICC .37) and Nike+ Fuelband (ICC .53). The mean absolute percentage errors of the trackers in laboratory and free-living conditions respectively, were: Lumoback (−0.2, −0.4), Fibit Flex (−5.7, 3.7), Jawbone Up (−1.0, 1.4), Nike+ Fuelband (−18, −24), Misfit Shine (0.2, 1.1), Withings Pulse (−0.5, −7.9), Fitbit Zip (−0.3, 1.2), Omron (2.5, −0.4), Digiwalker (−1.2, −5.9), and Moves app (9.6, −37.6). Bland-Altman plots demonstrated that the limits of agreement varied from 46 steps (Fitbit Zip) to 2422 steps (Nike+ Fuelband) in the laboratory condition, and 866 steps (Fitbit Zip) to 5150 steps (Moves app) in the free-living condition.Conclusion: The reliability and validity of most trackers for measuring step count is good. The Fitbit Zip is the most valid whereas the reliability and validity of the Nike+ Fuelband is low.
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Despite the increased use of activity trackers, little is known about how they can be used in healthcare settings. This study aimed to support healthcare professionals and patients with embedding an activity tracker in the daily clinical practice of a specialized mental healthcare center and gaining knowledge about the implementation process. An action research design was used to let healthcare professionals and patients learn about how and when they can use an activity tracker. Data collection was performed in the specialized center with audio recordings of conversations during therapy, reflection sessions with the therapists, and semi-structured interviews with the patients. Analyses were performed by directed content analyses. Twenty-eight conversations during therapy, four reflection sessions, and eleven interviews were recorded. Both healthcare professionals and patients were positive about the use of activity trackers and experienced it as an added value. Therapists formulated exclusion criteria for patients, a flowchart on when to use the activity tracker, defined goals, and guidance on how to discuss (the data of) the activity tracker. The action research approach was helpful to allow therapists to learn and reflect with each other and embed the activity trackers into their clinical practice at a specialized mental healthcare center.
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In dit review wordt een overzicht gegeven van effect van mobiele applicaties en activity trackers op een gezonde leefstijl. 17 artikelen werden geïncludeerd. De effecten van apps op beweeggedrag lijken positief. Het effect van apps op voeding en gewicht was wisselend. Maar er leek een trend te zijn voor verbetering van het voedingspatroon. Er is nog weinig onderzoek gedaan naar effect van activity trackers op leefstijl, maar eerste resultaten laten een positieve invloed zien op beweeggedrag. Voor apps aanbevolen kunnen worden, is verder onderzoek nodig. Hiervoor is grootschalig onderzoek nodig met uitgebalanceerde controlegroepen en lange termijn follow-up testen.
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Purpose: To examine the test–retest reliability and validity of ten activity trackers for step counting at three different walking speeds. Methods:Thirty-one healthy participants walked twice on a treadmill for 30 min while wearing 10 activity trackers (Polar Loop, GarminVivosmart, Fitbit Charge HR, Apple Watch Sport, Pebble Smartwatch, Samsung Gear S, Misfit Flash, Jawbone Up Move, Flyfit, andMoves). Participants walked three walking speeds for 10 min each; slow (3.2 kmIhj1), average (4.8 kmIhj1), and vigorous (6.4 kmIhj1).To measure test–retest reliability, intraclass correlations (ICC) were determined between the first and second treadmill test. Validity wasdetermined by comparing the trackers with the gold standard (hand counting), using mean differences, mean absolute percentage errors,and ICC. Statistical differences were calculated by paired-sample t tests, Wilcoxon signed-rank tests, and by constructing Bland–Altmanplots. Results: Test–retest reliability varied with ICC ranging from j0.02 to 0.97. Validity varied between trackers and different walkingspeeds with mean differences between the gold standard and activity trackers ranging from 0.0 to 26.4%. Most trackers showed relativelylow ICC and broad limits of agreement of the Bland–Altman plots at the different speeds. For the slow walking speed, the GarminVivosmart and Fitbit Charge HR showed the most accurate results. The Garmin Vivosmart and Apple Watch Sport demonstrated the bestaccuracy at an average walking speed. For vigorous walking, the Apple Watch Sport, Pebble Smartwatch, and Samsung Gear S exhibitedthe most accurate results. Conclusion: Test–retest reliability and validity of activity trackers depends on walking speed. In general,consumer activity trackers perform better at an average and vigorous walking speed than at a slower walking speed.
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In dit review wordt een overzicht gegeven van effect van mobiele applicaties en activity trackers op een gezonde leefstijl. 17 artikelen werden geïncludeerd. De effecten van apps op beweeggedrag lijken positief. Het effect van apps op voeding en gewicht was wisselend. Maar er leek een trend te zijn voor verbetering van het voedingspatroon. Er is nog weinig onderzoek gedaan naar effect van activity trackers op leefstijl, maar eerste resultaten laten een positieve invloed zien op beweeggedrag. Voor apps aanbevolen kunnen worden, is verder onderzoek nodig. Hiervoor is grootschalig onderzoek nodig met uitgebalanceerde controlegroepen en lange termijn follow-up testen.
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Data collected from fitness trackers worn by employees could be very useful for businesses. The sharing of this data with employers is already a well-established practice in the United States, and companies in Europe are showing an interest in the introduction of such devices among their workforces. Our argument is that employers processing their employees’ fitness trackers data is unlikely to be lawful under the General Data Protection Regulation (GDPR). Wearable fitness trackers, such as Fitbit and AppleWatch devices, collate intimate data about the wearer’s location, sleep and heart rate. As a result, we consider that they not only represent a novel threat to the privacy and autonomy of the wearer, but that the data gathered constitutes ‘health data’ regulated by Article 9. Processing health data, including, in our view, fitness tracking data, is prohibited unless one of the specified conditions in the GDPR applies. After examining a number of legitimate bases which employers can rely on, we conclude that the data processing practices considered do not comply with the principle of lawfulness that is central to the GDPR regime. We suggest alternative schema by which wearable fitness trackers could be integrated into an organization to support healthy habits amongst employees, but in a manner that respects the data privacy of the individual wearer.
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Aim: Wearables technology plays an important role in supporting patients in self-management. This study aims to identify the functions and purposes of activity trackers that contribute to and assist in addressing the nursing diagnosis of Sedentary Lifestyle in patients with heart failure. Design: A scoping review was conducted. Depending on the type of study, critical appraisal took place using PRISMA, CONSORT, STROBE, or SRQR. Methods: A systematic search was performed in CINAHL, MEDLINE/PubMed, and the Cochrane library. Publications from January 2010 through May 2019 were included. The main subjects of the review were the functions and purposes of activity trackers that are used to support heart failure patients who live a sedentary lifestyle. Results: Thirteen articles were used for the analysis. The main feature of an activity tracker is the registration of steps, active/sedentary time, and calories burnt during the day. The following functions were mentioned in the articles: data collection, monitoring/self-monitoring, feedback, goal setting, awareness of own behaviour, motivation, and providing social support through the sharing of data.
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