Sedentary LifestyleNCT02717169
Promoting Health Knowledge Among University Students
A study testing Biometrical tracker in people with Sedentary Lifestyle and Insomnia, run by The University of Hong Kong at 1 site in Hong Kong.
Trial summary
Background: The interactions between human beings and wearable technology like activity trackers equipped with biometric sensors can be linked to health related new learning concepts/instructional methods supporting deep knowledge acquisition, situated, self-regulated and active learning. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Sedentary Lifestyle, Insomnia
- What is being tested?
- Biometrical tracker
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 35 participants
- Where
- 1 siteHong Kong
- Study dates
- Mar 2016to Dec 2016
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Age over 18 years
- University Students
Who cannot join
- none
Trial locations and contacts
1 site in 1 country.
Hong Kong1 site, 1 recruiting
- Recruiting
The University of Hong Kong
Hong Kong, 000
Tanja Sobko, +85251816160, tanja.sobko@gmail.com
About this study
Official title: Promoting Health Knowledge Among University Students by Using Personal Biometric Information
Background: The interactions between human beings and wearable technology like activity trackers equipped with biometric sensors can be linked to health related new learning concepts/instructional methods supporting deep knowledge acquisition, situated, self-regulated and active learning. This personalized, long term interactions where specific information is pushed to the learner contributes to deepen the personal understanding related to the concept of and knowledge about health and has an impact on long term health action process.
Design and methods: In order to understand the behavioural change process, a multiple case study including 35 higher education students in Hong Kong from an undergraduate course, BSc Exercise and Health is currently conducted. Each student uses a wearable device (activity tracker) over a period of five months, reflects weekly on emerging personal data, documents their thinking and action in the ePortfolio, and engages in an online forum. The participants enter their experiences with the biometric data, lifestyle adaptations (e.g. more steps), special situations (e.g. hike, heart rate changes during activity) and how these experiences lead to specific searches and actions on the web and/or in their real social network. The ePortfolio will allow the students to critically reflect on their progress and for the researchers to intervene at any time on the issues related to the participants' postings. EHealth literacy is used as indicator for the health action process of the participants. Evidence regarding change in eHealth at the beginning and end of the intervention will be collected with a standard questionnaire detecting eHealth their literacy scale.
Scope: By reflecting on the information from their personal activity tracker and documenting it in their own ePortfolio, the students will continuously learn to analyse, search and critically assess health related personal and available digital information, organize it, present and discuss it with peers/tutor. This in turn will enhance critical thinking, raise questions about health related topics, stimulate further inquiry deepen their knowledge about personal health, inducing a healthier lifestyle.
Read the detailed description
Introduction
Bridging the know-do gap is one of the most important challenges for public health in this century. It also poses the greatest opportunity for strengthening health systems.
Health knowledge, or education, refers to the knowledge and understanding individual have about health-related issues. It is important to understand benefits for health and the causes of ill-health and recognize the extent to which they are vulnerable to, or at risk from, a health threat. In other words, knowledge is a necessary component of behavioral change .
Health knowledge is an important but not sufficient factor in order to provoke a behavioral change toward a healthier life style. Knowing that something is beneficial or a risk to your health and perceiving it as a chance or threat are not the same. Schwarzer proposes the Health Action Process Approach for helping to bridge the know - do gap underlining the importance of adoption, initiation, and maintenance of health behaviors conceived of as a structured process including a motivation phase and a volition phase. The proposed study fosters acquisition and maintenance of health behaviors like activity in form of amount of steps performed during a day, sleeping behavior and monitoring of the heart rate.
The context in which the described interactions between human beings and the wearable technology takes place, can be linked to learning concepts and instructional methods like knowledge building, situated, self-regulated and active learning. In situated learning it is important to create a meaning from the real activities of daily living where learning can also occur in an informal setting and connects prior knowledge to new contexts. According to recent reserach researchers, a selfregulated student is a student who is metacognitively, motivationally, and behaviorally engaged in its own learning processes and in achieving its own goals. Active learning refers to any instructional method that engages students (actively) in the learning process. Active learning requires students to do meaningful learning activities and to reflect what they are doing. Reserachers describe Knowledge building by an activity resulting in the creation or modification of so called public knowledge, knowledge that lives 'in the world' and is available to be worked on.
Wearable technologies can also provide a vehicle and act as motivator for the effective use of IT tools and resources from the internet and other information and media channels. Students' learn to work with their own, real data delivered over a long period of time, and through these experiences they may become more critical about encountered information deriving from other sources and so develop literacies related to the use of digital information in order to enhance their health. This literacy is called eHealth literacy.
eHealth literacy is not well developed for students in higher education. Wearable technologies like wristwatch trackers open an opportunity for development of new literacies and especially eHealth literacy by delivering in real-time, situated, personal information. Having access to these data and critically using it will stimulate individuals' interests in health issues and mediate deployment of interacting new literacies while locating and engaging with health information resources.
Methodology:
Procedure and data collection
To understand the qualitative aspect of the changes in eHealth literacy semi-structured interviews pre and post intervention will be conducted on a sub-group of 35 students.
During one academic semester 35 students from the course: 'Physical Activity and health' will be recruited. Participants will be asked to sign ethic clearance and the consent to participate to the study including the permission to publish the results of the study after anonymizing provenience of the collected data. Students of a higher education institution in Hong Kong aged 18 years and above. To understand eHealth literacy development in higher education in Hong Kong an existing ePortfolio tool will be used. Each of the participants will use a wearable device over a period of five month (1 semester), reflect on emerging personal data, document their thinking and share and communicate to other participants (optional) in their ePortfolio. The ePortfolio will allow the researchers to intervene at any time and to ask questions related to the participants reflections. Evidence regarding change in eHealth literacy at the beginning and end of the intervention will be collected with a well-established questionnaire. The same questionnaire will be used for Pre and Post intervention. Interviews and data from reflections and forum posts will be analyzed and triangulated to understand emerging issues influencing the development of eHealth literacy. After establishing a case report for each of the participants a cross-case analysis will be performed.
The participants will be asked to reflect weekly about their use of the trackers. It will enable participants to enter their experiences with the biometric data, like relevance of difference sensor data, lifestyle adaptations (like e.g. more sleep), special situations (e.g. hike, changes in heart rate during activity) and how these experiences lead to specific searches and actions in the web and/or in their real social network. Students will be able to publish different formats of reflections as text, hyperlinks to health related web pages and images. The quality of the materials, collected and published within the ePortfolio tool, has been shown to improve during the previously conducted pilot work during the development of this tool. The created ePortfolio is expected to provide a fundamental platform for meaningful and sustainable interaction between the students and the teacher in the continuous construction of knowledge towards any undergraduate programmes' intended learning outcomes. It is expected to enhance the metacognition of own learning through repeated reflection. This will be assessed as suggested previously. Students have access to all their reflections and can retrieve past events of their reflective ePortfolio, described above.
Study design and methodology
The presented research will employ a multi case methodology study to explicate the affordances of wearable trackers, as they emerge from the ten students using this technology. The study will constitute an inductive, hypotheses generating naturalistic inquiry, whose aim is to accumulate an understanding and propose recommendations relevant to the study context. It will focus on the larger picture, the whole picture, and begin with a search for understanding of the whole. The research findings will provide a broad picture of the events taking place in particular contexts, allowing readers to draw their own conclusions. The sample size of the presented study, conducted over 5 months with an exemplary group of 35 students across the four key areas, is sufficiently large for a multi case methodology study. The interview data will be collected by a research assistant and by the principal investigator. The questionnaire data will be collected by the research assistants. The data from the tracker (individual reflections and biometric data) will automatically be recorded into a database. Interview and questionnaire will take place at the University, 30 minutes for each interview, 20 minutes for each questionnaire (1 hours and 40 minutes for each participant). A consistency technique will be applied across the 35 cases to allow comparability. The adopted case study methodology is adequate for retrieving a well rooted set of arguments and recommendations related to the learning process performed by the 35 students during the intervention related to eHealth literacy.
- Conditions
- Sedentary Lifestyle, Insomnia
- Being tested
- Biometrical tracker
- Keywords
- health promotion, health action process, activity tracker, sleep regulation
- Medical subject headings
- Sedentary Behavior, Sleep Initiation and Maintenance Disorders
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Biometrical trackerDevice
35 participants are wearing a activity, sleep and heart rate tracker day and night time over a period of 5 month. The wrist watch is equipped with accelerometer, heart rate monitor using oximetry sensor, 3 led lights and vibrating alarm. The tracker is connected over Bluetooth with a smartphone App displaying the measured values and permitting to show different statistics related to amount of steps, sleep duration and heart rate over days, weeks and months.
| Study group | Role | What they receive |
|---|---|---|
| Biometrical Tracker | Other | The participants are equipped with an wrist watch. The activity tracker measures biometrical information like, steps, sleep duration and heart rate. Receives: Device: Biometrical tracker |
What is being measured
The primary outcome is the main question the study is designed to answer.
Physical activity levels
Number of steps recorded from the Activity tracker
Measured: 5 months
light sleep length
Daily duration of light sleep in hours
Measured: 5 months
deep sleep length
- Daily duration of deep sleep in hours
Measured: 5 months
Secondary outcomes (1)
eHealth literacy quantity
validated questionnaire pre and post intervention
Measured: 5 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Mar 2016 (estimated)
- Study startMar 2016
- Primary completionJul 2016 (estimated)
- Study completionDec 2016 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (14)Papers the sponsor has linked to this study.
- Other trials for Sedentary LifestyleStudies of the same condition, open and under way.
- More trials run by The University of Hong KongThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 35 participants (estimated)
Sponsor and investigators
- Lead sponsor
- The University of Hong Kong
- Sponsor type
- University, hospital or other
- Collaborators
- PHBern, University of Teacher Education Bern, Switzerland
- Responsible party
- Principal investigator, Dr. Tanja Sobko, The University of Hong Kong
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02717169
- Sponsor's protocol ID
- AT-2016
- Status last verified
- Mar 2016
- First submitted
- 11 Mar 2016
- Last updated
- 23 Mar 2016
- Results posted
- No
- Data monitoring committee
- Yes
- Individual data sharing
- Undecided
Publications
Bonwell, C.& J. A. Eison,J. (1991). Active Learning: Creating Excitement in the Classroom. ASHEERIC Higher Education Report No. 1. George Washington University.
Brown, J., Collins, A, Dugid, P. (1998). Situated cognition and the culture of learning. Educational Researcher.18:32-42.
Creswell, W.J. (1998). Qualitative inquiry and research design: Choosing among five traditions. Thousand Oaks, CA: Sage Publications.
Flyvbjerg, B (2006). Five misunderstandings about case-study research. Qualitative Inquiry 12(2): 219-45.
Janesick, V.J. (2000). The choreography of qualitative research design. In N.K. Denzin & Y.S. Lincoln (Eds.), Handbook of qualitative research (2nd ed., pp. 379-399). Thousand Oaks, CA: Sage Publications.
Savolainen, J. (1994). The rationality of drawing big conclusions based on small samples. Social Forces 72: 1217-24.
Scardamalia, M. & Bereiter, C. (2003). Knowledge Building. In Encyclopedia of Education. (2nd ed., pp. 1370-1373). New York: Macmillan Reference, USA.
Schwarzer, R. (2008). Modeling health behavior change: How to predict and modify the adoption and maintenance of health behaviors. Applied Psychology: An International Review, 57(1), 1-29.
Small, M. (2009). How many cases do I need? On science and the logic of case selection in field-based research. Ethnography 10(1): 5-38.
Stake, R. (2003). Case studies. In N. K. Denzin & Y. S. Lincoln (Eds.), Strategies of qualitative inquiry (2nd Ed., pp. 134-164). Thousand Oaks, CA: Sage.
Stellefson M, Hanik B, Chaney B, Chaney D, Tennant B, Chavarria EA. eHealth literacy among college students: a systematic review with implications for eHealth education. J Med Internet Res. 2011 Dec 1;13(4):e102. doi: 10.2196/jmir.1703.
PubMed 22155629Yin, R.K. (1989). Case study research: design and methods. Newbury Park, CA: Sage.
WHO (2006). Bridging the "Know-Do" Gap Meeting on Knowledge Translation in Global Health. Organized by the Departments of: Knowledge Management and Sharing (KMS) Research Policy and Cooperation (RPC). http://www.who.int/kms/WHO_EIP_KMS_2006_2.pdf .
Zimmerman, B., & Schunk, D. (2001). Self-regulated learning and academic achievement: Theoretical perspectives. Mahwah, NJ: Lawrence Erlbaum Associates.
Study at a glance
From the registry record, last updated by the sponsor on 23 Mar 2016. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Promoting Health Knowledge Among University Students by Using Personal Biometric Information
- ClinicalTrials.gov ID
- NCT02717169
- Acronym / sponsor ID
- AT-2016
- Conditions
- Sedentary Lifestyle, Insomnia
- Keywords
- health promotion, health action process, activity tracker, sleep regulation
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 35 participants (estimated)
- Lead sponsor
- The University of Hong KongUniversity, hospital or other
- Collaborators
- PHBern, University of Teacher Education Bern, Switzerland
- Study start
- Mar 2016
- Primary completion
- Jul 2016 (estimated)
- Study completion
- Dec 2016 (estimated)
- First posted
- 23 Mar 2016 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Background: The interactions between human beings and wearable technology like activity trackers equipped with biometric sensors can be linked to health related new learning concepts/instructional methods supporting deep knowledge acquisition, situated, self-regulated and active learning. This personalized, long term interactions where specific information is pushed to the learner contributes to deepen the personal understanding related to the concept of and knowledge about health and has an impact on long term health action process.
Design and methods: In order to understand the behavioural change process, a multiple case study including 35 higher education students in Hong Kong from an undergraduate course, BSc Exercise and Health is currently conducted. Each student uses a wearable device (activity tracker) over a period of five months, reflects weekly on emerging personal data, documents their thinking and action in the ePortfolio, and engages in an online forum. The participants enter their experiences with the biometric data, lifestyle adaptations (e.g. more steps), special situations (e.g. hike, heart rate changes during activity) and how these experiences lead to specific searches and actions on the web and/or in their real social network. The ePortfolio will allow the students to critically reflect on their progress and for the researchers to intervene at any time on the issues related to the participants' postings. EHealth literacy is used as indicator for the health action process of the participants. Evidence regarding change in eHealth at the beginning and end of the intervention will be collected with a standard questionnaire detecting eHealth their literacy scale.
Scope: By reflecting on the information from their personal activity tracker and documenting it in their own ePortfolio, the students will continuously learn to analyse, search and critically assess health related personal and available digital information, organize it, present and discuss it with peers/tutor. This in turn will enhance critical thinking, raise questions about health related topics, stimulate further inquiry deepen their knowledge about personal health, inducing a healthier lifestyle.
Detailed description
Introduction
Bridging the know-do gap is one of the most important challenges for public health in this century. It also poses the greatest opportunity for strengthening health systems.
Health knowledge, or education, refers to the knowledge and understanding individual have about health-related issues. It is important to understand benefits for health and the causes of ill-health and recognize the extent to which they are vulnerable to, or at risk from, a health threat. In other words, knowledge is a necessary component of behavioral change .
Health knowledge is an important but not sufficient factor in order to provoke a behavioral change toward a healthier life style. Knowing that something is beneficial or a risk to your health and perceiving it as a chance or threat are not the same. Schwarzer proposes the Health Action Process Approach for helping to bridge the know - do gap underlining the importance of adoption, initiation, and maintenance of health behaviors conceived of as a structured process including a motivation phase and a volition phase. The proposed study fosters acquisition and maintenance of health behaviors like activity in form of amount of steps performed during a day, sleeping behavior and monitoring of the heart rate.
The context in which the described interactions between human beings and the wearable technology takes place, can be linked to learning concepts and instructional methods like knowledge building, situated, self-regulated and active learning. In situated learning it is important to create a meaning from the real activities of daily living where learning can also occur in an informal setting and connects prior knowledge to new contexts. According to recent reserach researchers, a selfregulated student is a student who is metacognitively, motivationally, and behaviorally engaged in its own learning processes and in achieving its own goals. Active learning refers to any instructional method that engages students (actively) in the learning process. Active learning requires students to do meaningful learning activities and to reflect what they are doing. Reserachers describe Knowledge building by an activity resulting in the creation or modification of so called public knowledge, knowledge that lives 'in the world' and is available to be worked on.
Wearable technologies can also provide a vehicle and act as motivator for the effective use of IT tools and resources from the internet and other information and media channels. Students' learn to work with their own, real data delivered over a long period of time, and through these experiences they may become more critical about encountered information deriving from other sources and so develop literacies related to the use of digital information in order to enhance their health. This literacy is called eHealth literacy.
eHealth literacy is not well developed for students in higher education. Wearable technologies like wristwatch trackers open an opportunity for development of new literacies and especially eHealth literacy by delivering in real-time, situated, personal information. Having access to these data and critically using it will stimulate individuals' interests in health issues and mediate deployment of interacting new literacies while locating and engaging with health information resources.
Methodology:
Procedure and data collection
To understand the qualitative aspect of the changes in eHealth literacy semi-structured interviews pre and post intervention will be conducted on a sub-group of 35 students.
During one academic semester 35 students from the course: 'Physical Activity and health' will be recruited. Participants will be asked to sign ethic clearance and the consent to participate to the study including the permission to publish the results of the study after anonymizing provenience of the collected data. Students of a higher education institution in Hong Kong aged 18 years and above. To understand eHealth literacy development in higher education in Hong Kong an existing ePortfolio tool will be used. Each of the participants will use a wearable device over a period of five month (1 semester), reflect on emerging personal data, document their thinking and share and communicate to other participants (optional) in their ePortfolio. The ePortfolio will allow the researchers to intervene at any time and to ask questions related to the participants reflections. Evidence regarding change in eHealth literacy at the beginning and end of the intervention will be collected with a well-established questionnaire. The same questionnaire will be used for Pre and Post intervention. Interviews and data from reflections and forum posts will be analyzed and triangulated to understand emerging issues influencing the development of eHealth literacy. After establishing a case report for each of the participants a cross-case analysis will be performed.
The participants will be asked to reflect weekly about their use of the trackers. It will enable participants to enter their experiences with the biometric data, like relevance of difference sensor data, lifestyle adaptations (like e.g. more sleep), special situations (e.g. hike, changes in heart rate during activity) and how these experiences lead to specific searches and actions in the web and/or in their real social network. Students will be able to publish different formats of reflections as text, hyperlinks to health related web pages and images. The quality of the materials, collected and published within the ePortfolio tool, has been shown to improve during the previously conducted pilot work during the development of this tool. The created ePortfolio is expected to provide a fundamental platform for meaningful and sustainable interaction between the students and the teacher in the continuous construction of knowledge towards any undergraduate programmes' intended learning outcomes. It is expected to enhance the metacognition of own learning through repeated reflection. This will be assessed as suggested previously. Students have access to all their reflections and can retrieve past events of their reflective ePortfolio, described above.
Study design and methodology
The presented research will employ a multi case methodology study to explicate the affordances of wearable trackers, as they emerge from the ten students using this technology. The study will constitute an inductive, hypotheses generating naturalistic inquiry, whose aim is to accumulate an understanding and propose recommendations relevant to the study context. It will focus on the larger picture, the whole picture, and begin with a search for understanding of the whole. The research findings will provide a broad picture of the events taking place in particular contexts, allowing readers to draw their own conclusions. The sample size of the presented study, conducted over 5 months with an exemplary group of 35 students across the four key areas, is sufficiently large for a multi case methodology study. The interview data will be collected by a research assistant and by the principal investigator. The questionnaire data will be collected by the research assistants. The data from the tracker (individual reflections and biometric data) will automatically be recorded into a database. Interview and questionnaire will take place at the University, 30 minutes for each interview, 20 minutes for each questionnaire (1 hours and 40 minutes for each participant). A consistency technique will be applied across the 35 cases to allow comparability. The adopted case study methodology is adequate for retrieving a well rooted set of arguments and recommendations related to the learning process performed by the 35 students during the intervention related to eHealth literacy.
Study design
- Primary purpose
- Prevention
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Biometrical Tracker | Other | Device: Biometrical trackerThe participants are equipped with an wrist watch. The activity tracker measures biometrical information like, steps, sleep duration and heart rate. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- Age over 18 years
- University Students
Key exclusion criteria (1 listed)
- none
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Biometrical tracker35 participants are wearing a activity, sleep and heart rate tracker day and night time over a period of 5 month. The wrist watch is equipped with accelerometer, heart rate monitor using oximetry sensor, 3 led lights and vibrating alarm. The tracker is connected over Bluetooth with a smartphone App displaying the measured values and permitting to show different statistics related to amount of steps, sleep duration and heart rate over days, weeks and months. | Device | Biometrical Tracker |
Primary outcome
Physical activity levels
Time frame: 5 months
Number of steps recorded from the Activity tracker
light sleep length
Time frame: 5 months
Daily duration of light sleep in hours
deep sleep length
Time frame: 5 months
- Daily duration of deep sleep in hours
1 secondary outcome
eHealth literacy quantity
Time frame: 5 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Mar 2016.
- BackgroundBonwell, C.& J. A. Eison,J. (1991). Active Learning: Creating Excitement in the Classroom. ASHEERIC Higher Education Report No. 1. George Washington University.
- BackgroundBrown, J., Collins, A, Dugid, P. (1998). Situated cognition and the culture of learning. Educational Researcher.18:32-42.
- BackgroundCreswell, W.J. (1998). Qualitative inquiry and research design: Choosing among five traditions. Thousand Oaks, CA: Sage Publications.
- BackgroundFlyvbjerg, B (2006). Five misunderstandings about case-study research. Qualitative Inquiry 12(2): 219-45.
- BackgroundJanesick, V.J. (2000). The choreography of qualitative research design. In N.K. Denzin & Y.S. Lincoln (Eds.), Handbook of qualitative research (2nd ed., pp. 379-399). Thousand Oaks, CA: Sage Publications.
- BackgroundSavolainen, J. (1994). The rationality of drawing big conclusions based on small samples. Social Forces 72: 1217-24.
- BackgroundScardamalia, M. & Bereiter, C. (2003). Knowledge Building. In Encyclopedia of Education. (2nd ed., pp. 1370-1373). New York: Macmillan Reference, USA.
- BackgroundSchwarzer, R. (2008). Modeling health behavior change: How to predict and modify the adoption and maintenance of health behaviors. Applied Psychology: An International Review, 57(1), 1-29.
- BackgroundSmall, M. (2009). How many cases do I need? On science and the logic of case selection in field-based research. Ethnography 10(1): 5-38.
- BackgroundStake, R. (2003). Case studies. In N. K. Denzin & Y. S. Lincoln (Eds.), Strategies of qualitative inquiry (2nd Ed., pp. 134-164). Thousand Oaks, CA: Sage.
- Background: PubMed 22155629Stellefson M, Hanik B, Chaney B, Chaney D, Tennant B, Chavarria EA. eHealth literacy among college students: a systematic review with implications for eHealth education. J Med Internet Res. 2011 Dec 1;13(4):e102. doi: 10.2196/jmir.1703.
- BackgroundYin, R.K. (1989). Case study research: design and methods. Newbury Park, CA: Sage.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Biometrical tracker in people with Sedentary Lifestyle and Insomnia, run by The University of Hong Kong at 1 site in Hong Kong.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 23 Mar 2016. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Hong Kong. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Tanja Sobko, PhD (+85251816160, tsobko@hku.hk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Physical activity levels (time frame: 5 months). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT02717169, which also lists 14 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Mar 2016.