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Twente Panel is available for use!

Twente Intervention and Interaction Machine (TIIM)

Twente Intervention and Interaction Machine (TIIM) is a software created by the BMS Lab. Researchers, teachers, and students at the University of Twente can use the dashboard’s web application to create interventions, longitudinal studies, experience sampling method (ESM) or ecological momentary assessment (EMA) studies and questionnaires. Subsequently, through the TIIM’s mobile application, the researcher/teacher/student can gather data and/or distribute information/content to participants about different topics. It allows researchers to create sets of questionnaires and present them to participants based on a schedule or conditions. In addition, the studies can be adapted to individual participants due to the option to add item routing and questionnaire conditions. TIIM allows for interactive feedback, notifications and calculations, while giving you a better picture of your participants or patients by collecting wearable data when desired. The Twente Panel, a group of prospective participants, is created to aid the search for participants to join TIIM studies. 

TIIM is ISO/NEN 7510/7512/7513 and GDPR compliant and it operates on ISO/IEC27001 certified infrastructure. 

Contact

If you have any requests, questions or concerns regarding TIIM, please get in touch with our team by sending an email to dashboard-bms@utwente.nl

If you have questions or concerns regarding your study, please include your study ID (the four numbers in the URL when your study is open) in the email.

Useful links

Useful links
Researchers
Manual Best practices Twente Panel


Referring TIIM in your research

To the article
When using TIIM, please read and cite the following article: Van 't Klooster JWJR, Rabago Mayer LM, Klaassen B and Kelders SM (2024). Challenges and opportunities in mobile e-coaching. Front. Digit. Health 5:1304089. doi: 10.3389/fdgth.2023.1304089.


IsolatieCoach home screen.
TIIM For Research And Education

TIIM can be used for cohort studies, eCoaching, interventions, experience sampling, EMA/EMI, pilot testing, clinimetrics, wearable data, clinical trials and education & eLearning.

The IsolatieCoach research used TIIM as an interactive and personalised eCoach to support people during their process of isolation. Participants engaged in an interactive questionnaire where based on their answers, the app provided feedback. 

Another example is the project: Using motivational interviewing combined with digital shoe-fitting to improve adherence to wearing orthopaedic shoes in people with diabetes at risk of foot ulceration: study protocol for a cluster-randomized controlled trial. TIIM was used to collect participants biometric data (steps and heart rate) and sleep, through their wearables. The full article is available on this link. 

Further support

Manual and tutorials

User manual Video tutorials Illustrations

Best practices for researchers

To reduce potential issues and challenges, keep the following points in mind before using TIIM for your research:

Planning Your Research Design
  1. Think about what you would like to measure. When? What will it deliver afterwards? And how does TIIM fit within your research? This helps you realize what you need to build, when and how much time it will likely take.
  2. Take practical aspects into account: is there an easier way to do it? Uncertain? Ask the BMS Lab.
  3. Consider the limitations of the software to your study. Keep in mind that TIIM is in continuous development which means that bugs might be introduced as a result.
  4. Please note that in all cases users of TIIM are fully responsible for their own study design, data collection and the resulting data. Collecting data that may be deemed sensitive or medical in nature in TIIM is possible. In these cases, researchers should always go through the required procedures (e.g.: ethical approval from a central ethical commission, MDR approval (contact person: p.oosterhoff@utwente.nl) or AVG registration) for their individual studies.
  5. Be mindful of the size of the study! The more participants interventions, modules and module items you have, the longer it will take for the studies to load and download.
Developing Your Research
  1. Ensure that you have approximately 2 – 3 weeks to build your research. You might need to adapt your methodology based on TIIM’s functionalities (see “Further Support” section) or you might need time to get an answer from the BMS Lab.
  2. Your introduction screen should adequately inform your participants and meet the BMS faculty’s ethical standard on informed consent.
  3. Any time you make new additions, make sure to regularly test your research from the participant’s perspective.
  4. Duplicate your research to have a clean backup version.
  5. Test your final version as a participant.
  6. Download your data metrics to ensure that the data output fits with your research.
  7. Found a bug or issue? Please inform us.
Onboarding participants

Longitudinal studies often require a large time investment from participants and complinace sometimes may decline over time. As such, we suggest that reserachers sufficiently inform the participants about the study in which they will participant and what will be expected of them, but also, instruct the participants about how to use TIIM itself. For that purpose, we have created the list below. 

Instructions for onboarding participants

Designing ESM studies

You can conduct ESM (Experience Sampling Method) studies using the ESM timing rules. You can choose whether participants receive questionnaires on fixed dates or based on their individual enrollment date.

You can schedule questionnaires in bulk for the full intervention, and you can also add reminders and notifications for participants. You can set how long a questionnaire remains open and decide whether it is sent at random moments (by specifying the minimum time between instances) or iteratively, at the start of each period.

In addition, it is possible to schedule single instances.

Designing e-learning and diarisation studies

Here are few tips and tricks on how to do an E-diarisation study in TIIM.

Working with ‘goals’

Oftentimes when TIIM is used as a tool to facilitate learning, participants are asked to specify their learning goals or objectives. Using the dynamic text function can be used to call back to the goals or objectives specified by the participants.  

Keep in mind that the module(s) that specify the goals and graphs should be part of the same intervention.  

Using graphs in TIIM

The item type graphs allows for visualisation of the progress of the participants.  

You can use a different item type (for example, number slider) to ask participants to assess their knowledge or familiarity with a chosen goal. Then, using dynamic text option in the graph item type, you can create a graph showing their progress over time by dates. You can select the modules and the items from which the values in the graph will be shown. 

Using the e-portfolio

You can enable the e-porfolio so that your participants are able to view and follow their results over time upon request. 

On-demand module

You can invite participants to complete a questionnaire after each learning activity by using the on-demand module timing rule. This timing rule ensures that participants always have a questionnaire available to reflect on their learning activity and progress.

Minimising missing data

We advise you to carefully consider the starting moment of the study, choosing it to be close to a real life case or trigger that will start the process (such as lecture that is held on a specific day). Then, all of the participants can be automatically receive the intervention once it is available to them, by either scheduling the intervention to start at a specific date and time. 

It is also possible to send reminders (both to all participants or individually) to ensure their retention. 

Dealing with missing data

Missing data can happen in the instances when participants have not answered specific modules. We advise you to consider the data as if it is liked, and not fixed (for example, in time). If linear processes are used, the missing points can be interpolated. It is also advisable to consider whether carefully examine whether you want within person or between person results, i.e. with high inconsistency of some individuals between person results analysis can still be done if the group is large enough. 

For the participants it may be motivating and useful to use the graph item type, as it allows them to visualise their progress. You can also download the data per participant and individually send it to them to increase engagement or adherence.  

Lastly, having enough data points may minimise the impact of the missing data and currently in TIIM all items in a module are mandatory to be answered.  

E-learning vs ESM
Collecting health data

How to enable health data collection

After creating a study, researchers can enable health data gathering by navigating to the study detail page. At the bottom of this page, there is an option to enable health data collection. Once this option is enabled, the change must be saved. The researcher can then go to the modules page. After creating a module, several health sensor types will become available, including heart, steps, and sleep. The researcher can select which health data types they would like to collect. After selecting the data types, there is one shared time period setting that can be configured for all selected data types together. This can range from the last 30 minutes up to the last month, or a specific custom date range, for example from March 10 to March 20. The selected health data will be gathered when the participant finishes the module.

Health data on iOS

For iOS, the participant needs to connect their Apple Watch to their iPhone and allow the TIIM app to access health data through Apple HealthKit. Once permission is granted, the app can collect the selected health data based on the time period configured by the researcher. Heart data will return the participant’s beats per minute within the selected time period. Steps data will return the number of steps within each hour of the selected period. Sleep data will return the sleep states recorded during that period, such as In Bed, Awake, Asleep Core, Asleep Deep, and Asleep.

Health data on Android

For Android, the participant needs to connect their smartwatch to their phone and allow Samsung Health to access the data and share it with other apps. After this is set up, the participant must also allow the TIIM app to connect with Samsung Health. The health data collection works similarly to iOS. Heart data returns the beats per minute within the selected time period and sleep data returns the recorded sleep states during that period. The main difference is steps data: on Android, steps will return the total amount of steps for that day, instead of the steps within the selected time period.

TWENTE PANEL: Best practices & criteria

For UT researchers, we have a participant pool available upon request to supplement your data collection. However, to use the panel, you need to adhere to our best practices. Please keep in mind that the panel is a supporting resourse to your participant recruitment. 

Researchers interested in using the Twente Panel must indicate their interest in their request registration. Each request will be evaluated to ensure it meets the necessary criteria before approval. To maintain the integrity and availability of the panel, studies can only be conducted using this resource once every few months.

Accessing the panel

To access the panel you must ensure that you have requested it via the BMS Lab request system when registering your study. 

As such, you must show ethical approval, relevance, as well as methodological soundness. Your study will be checked by the panel’s administrator. If several requests are made for similar studies, it might be that you will be invited to collaborate.

Keep in mind that the panel can be accessed once every few months.

Preparing the study

We recommend keeping your study short and focused to encourage high-quality responses.
Use a single default intervention so participants can begin immediately. Alternatively, coordinate with the panel administrator to ensure that participants receive the study questions as soon as they join.

You can include your informed consent form as a page under the subscription section of your study.

Templates & communication to the panel

The panel is informed about the study with a notification and an email. Both use standard templates: only the study name, description, and unique voucher code will be customized based on your input.

Your study description must fit naturally within these templates, as the wording cannot be changed per study.

 

Template email:

Dear [Participant name],

We are excited to announce a new study, [study name], focused on [study decsription]. We invite you to participate and share your insights.

To join, please use the voucher code: [unique voucher code].

 

Template notification:

 New study: [study name] is available for you to join. You can find the details in your email.

Maximizing participation

Some useful pointers when using the panel to maximise participation:

  • Think about the moment sending around: when should the invite be sent?
  • Use a raffle, giveaway or similar as token of appreciation for participating.
  • Use short questionnaire, clear languages in Dutch and English (A2 level).
  • Carefully craft a clear and short email, showing appreciation, explaining the topic,vwhy participation is important, and what it brings participants. 
  • Make sure that the topic is of broad relevance or general interest, since anyone can join the panel.
  • Carefully read the instructions on using the title study and description’s usage in the invitation email.
  • Don’t underestimate the time needed for filling out.
  • Consider that the panel can also be used to just enquire participation in a different (either digital or physical) follow-up study.

Be aware no reminders about your study are sent and responses may vary and depend on many factors, including above.

Sending the study to the panel

To send your study to the panel, the study and all communication in the app and all messages to participants must be fully set up. 

This includes finalisation of questions, scheduling, notifications, reminders and emails. The study must be thoroughly tested as well. Once complete, you will need to contact the administrator who will then share it to the panel. 

When contacting the administrator who will distribute the study to the panel, please indicate the study ID (4 numbers in the study URL) and indicate the desired time of the week when you would like the participants to receive the study. 

Publications

Articles

van 't Klooster JWJR, Rabago Mayer LM, Klaassen B and Kelders SM (2024) Challenges and opportunities in mobile e-coaching. Front. Digit. Health 5:1304089. doi: 10.3389/fdgth.2023.1304089

Kip, H., Da Silva, M., Bouman, Y. H. A., van Gemert-Pijnen, L. J. E. W. C., & Kelders, S. M. (2021). A self-control training app to increase self-control and reduce aggression – A full factorial design. Internet interventions, 25, [100392]. https://doi.org/10.1016/j.invent.2021.100392

Kip, H. (2021). The added value of eHealth: Improving the development, implementation and evaluation of technology in treatment of offenders. University of Twente. https://doi.org/10.3990/1.9789036551311

Lentferink, A. J. (2021). Quantified eCoaching for Resilience Training: Combining self-tracking and persuasive eCoaching to train employees' capacity for resilience: identification of values and requirements with stakeholders. University of Twente. https://doi.org/10.3990/1.9789036552783

van 't Klooster, J. W. J. R., van Gend, J. E., Schreijer, M. A., de Witte, E. R., & van Gemert-Pijnen, L. J. E. W. C. (2021). Isolatiecoach: Een app als interventie ter bevordering van adherentie aan isolatie en quarantaine.

Lentferink, A., Noordzij, M. L., Burgler, A., Klaassen, R., Derks, Y., Oldenhuis, H., Velthuijsen, H., & Gemert-Pijnen, L. V. (2021). On the receptivity of employees to just-in-time self-tracking and eCoaching for stress management: a mixed-methods approach. Behaviour & information technology. https://doi.org/10.1080/0144929X.2021.1876764

Jongebloed-Westra, M., Bode, C., van Netten, J. J., ten Klooster, P. M., Exterkate, S. H., Koffijberg, H., & van Gemert-Pijnen, J. E. W. C. (2021). Using motivational interviewing combined with digital shoe-fitting to improve adherence to wearing orthopedic shoes in people with diabetes at risk of foot ulceration: study protocol for a cluster-randomized controlled trial. Trials, 22(1), [750]. https://doi.org/10.1186/s13063-021-05680-0

van der Zeeuw, A. (2021). IoT as simple as Do Re Mi: A micro-figurational approach to the social context of Internet of Things skills and digital inequalities. University of Twente. https://doi.org/10.3990/1.9789036552844

van 't Klooster, J. W. J. R., van Gend, J. E., Schreijer, M. A., de Witte, E. R., & van Gemert-Pijnen, L. J. E. W. C. (2022). The Value of eCoaching in the COVID-19 Pandemic to Promote Adherence to Self-isolation and Quarantine. In J-H. Kim, J. Khan, M. Singh, U. S. Tiwary, M. Sur, & D. Singh (Eds.), IHCI 2021 (pp. 417-422). (Lecture notes in computer science; Vol. 13184). Springer. https://doi.org/10.1007/978-3-030-98404-5_39

Student Theses

Dewi, Ni Made Gita Anandita (2025) Exploring Physiological and Psychological Stress Responses in Lean and Non-Lean Individuals Using Ambulatory Monitoring and the VR Trier Social Stress Test.

Huntjens, I.C.W. (2024) Exploring the Dynamics of Emotions: Combining the Experience Sampling Method With Continuous Physiological Data.

Hohlfeld, Nico M. (2024) Examining the Influence of Informative Podcasts About Sleep Health on the Development of Sleep Hygiene Behaviour in Young Adults: A Randomised Controlled Trial.

Uhlke, V.C. (2024) Exploring How Self-Monitoring Influences the Effects of Listening to Sleep Meditations to Improve Sleep Quality and Adherence.

Behrens, Jan (2024) Queer Minority Stress and Resilience in everyday life: An ecological momentary assessment study.

Wischmann, Mara (2022) An Experience Sampling Study on Self-Compassion and Loneliness in Daily Life.

Oomen, Iris (2021) Supporting Nurses' Regulatory Readiness at the Workplace via an Online Micro-Intervention.

Kattenberg, K.B. (2021) Supporting nurses’ daily self-regulated learning behaviour via an online micro-intervention.

Docter, M.S. (2021) Feeling Home Already? A Diary Study among Newcomers in STEM about the Effects of Interactions on Organisational Belonging, and how this Differs for Gender.

Dittrich, Samuel Marten (2021) Understanding the Association between Gratitude and Loneliness in Daily Life: An Experience Sampling Study.

Zorc, Elena (2021) The Association between daily affect and trait anxiety, depression, and alexithymia within individuals.

Gütges, I.D. (2020) Loneliness in the daily lives of university students : an experience sampling study exploring the role of social context and trait measures of loneliness and self-compassion.

Böggemann, Max (2020) The Association between Self-Compassion and Perceived Stress on the Within-Person and Between-Person Level.

Tiede, T. (2020) How did I feel? Recalling reported core affect in light of its fluctuation, the present state, and individual degrees of neuroticism.

Friedrichs, P.A.M. (2020) An experience sampling study into stress and the presence of friends.

Wellinger, Felizia Leonie (2020) The association between gratitude and stress in a daily context : an experience sampling study.

Watermann, Lara (2020) How the social context affects self-compassion and its association with stress - an experience sampling study.

Wallisch-Prinz, L. (2020) Measuring feelings of self-compassion and stress in daily life : an experience sampling study.

Berg, S.H.M.P. van den (2020) Co-designing a self-compassion application for newly diagnosed cancer patients with a focus on sustained use.

Adam, J.T. (2020) How the company of others and being alone affect feelings of loneliness and gratitude : an experience sampling study.

da Silva, Marcia Cristina (2019) A mobile app-based intervention for self-control(Hands-ON): usability and feasibility evaluations.

Ahlemeyer, Jan-Luca (2019) An experience sampling study into intra-individual correlations between bodily signals and experienced feelings.

Cordts, Florian (2019) Exploration of Video-On-Demand Watching Behaviour on YouTube and PS-ODVSP : an experience sampling study with regard to intentionality.

Hoppe, Wiebke (2019) Measuring Feelings of Anxiety and Depression in Daily Life – An Experience Sampling Study.

Sundermann, Josefine (2019) Assessing Predictors and Consequences of Video-on-Demand Streaming Behaviour : An Experience Sampling Study.

Frequently asked questions (FAQ)

General
How can I start using TIIM in my study?

Sign-up for your new project or Reserve for an Existing one following the project registration process. Afterwards, fill in the form and then reserve TIIM as software.

After signing up my study and reserving the TIIM software, how can I start a study?

Browse to https://dashboard.tech4people-apps.bms.utwente.nl, log in with your account. This will open the dashboard page. On the right click on ‘start a new study’, select the TIIM survey button and click on create new study.

How do I extend the duration of my study if it is not (yet) closed?

It is not possible to re-open the study after the end date. In the study details you can change when the study begins and ends and under the subscription page you can decide when to open and end the subscription. These two data don’t have to overlap.

TIIM Participants
How can I register participants?

Participants can subscribe via the subscription URL. This can be found on the study home page and/or the subscription page.

My participant is not able to fill in their information on the subscription page. What can I, as a Researcher, do?

When the participant wants to fill in their details, it is not possible to click on the grey word that details which information they have to fill in. They should either click on the right of the word or on the grey bar underneath it.

What happens when I send participants an email?

The email is sent by the BMS Lab email account, yet the participant will see it as if the e-mail had been sent by the researcher who created the study. This will allow the participant to reply to the researcher.

My participant does not receive notifications. What can I, as a Researcher, suggest them to do?

In the app under settings, the participant should see if the push notifications and email notifications have been checked.

Are the participants anonymous?

Each participant is assigned an ID and the metrics and data export, you are able only to view them by the ID. However, in the participants tab, you are able to match the participant to their ID. The participants are pseudonymised, but not anonymised.

Why are notifications and modules being sent at incorrect times for participants in different time zones?

notifications and module scheduling are currently based on European time. This may cause participants in other time zones to receive content at unintended times.

Workaround:
At this time, there is no direct way to assign different time zones within a single intervention. As a workaround, you can:

  • Remove the affected participant(s) from the study
  • Duplicate the intervention
  • Adjust the timing rules in the duplicated intervention to match the relevant time zone
  • Assign participants from that time zone to the new intervention

This will result in two otherwise identical interventions running in parallel, each configured for a different time zone. These can be combined later if needed.

TIIM Calculated Variables
What operations can be done on the calculated variables?

You can create an equation based on basic logical operators (+, -, /, (), * or 2^2) and so on.

Can I use the Likert Scale for calculated variables?

Yes. Calculated variables can also be made with the numerical item types: Number Input, Number Slider, Number Dropdown and Number Choice.

TIIM Time Rule Interventions
The timing of modules within my intervention is incorrect. What can I, as a Researcher, do?

Check if the dates of the time rule is set after the subscription date and the study start date.

TIIM Data Metrics and Export
How can I download data?

The procedure to download data is the following:

  1. On the left menu of your study, click on the “metrics” tab.
  2. At the top of the screen, click on the “Download” button.
  3. Click the “Download” blue button next to the intervention or module.

It will automatically download the data as a CSV file on your device.

How can I import my data in Excel?

After you have downloaded your data from the TIIM’s dashboard:

  1. Open Excel.
  2. Click “Data tab”.
  3. Click “from Text/CSV”.
  4. This will open a preview screen.
  5. Select the file.
  6. Click on “get data”.
  7. A pop-up screen will appear.
  8. In step 1, there are no changes needed. Click on “next”.
  9. In step 2, set the delimiter as a comma.
  10. Click on “next” again.
  11. In step 3, there are no changes needed. So, you can click on “finish”.
  12. Lastly, select where you would like your data to be placed.
  13. Then, click on “ok”.

You can now see your data in excel.

How can I import data in SPSS?

After you have downloaded your data from the TIIM’s dashboard:

  1. Open SPSS.
  2. Click “File”.
  3. Click “Open”.
  4. Click “data”.
  5. This will open a new window.
  6. Make sure your file type is set to CSV.
  7. Find the document you would like to open.
  8. Select it.
  9. And, click on “open”.
  10. The text import wizard window will open.
  11. In step 1, there are no changes needed. So, click on “next”.
  12. In step 2, under the question “Are variable names included at the top of your file?” click yes.
  13. Then, click “next”.
  14. In step 3, there are no changes needed. So, click on “next”.
  15. In step 4, under the question “which delimiters appear between variables?” tick the box next to “comma”.
  16. Then, click on “next”.
  17. In step 5, there are no changes needed. So, click on “next”.
  18. Then, in step 6, the last step, there are also no changes needed.
  19. Click on “finish”.

You can now see your data in SPSS.

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