Many tools built to help Researchers are made with legacy systems and old models of internet delivery. The problems with this model are many and varied:
- not an engaging method of learning
- often not a “mobile first” methodology
- difficult to maintain and upgrade
- only use email as a method to notify or provide feedback to the user
- models of self reported data are often unreliable
Definitely. All word-clouds(contexts), predefined thoughts, emotions and behaviours can be customized. The notifications which the participants receive based on their tracking can also be customized by study. There are any other customizations which any specific research study can make. Just ask!
lmtls™ provides a systematic and portable means of rating mood symptoms, energy levels or product/service satisfaction over time, depending on what application it is used for when collecting data.
Having a snapshot of metadata collected over time can help overcome some of the limitations of self reported content data. This also allows the Platform to tag specified items or combination of items for automatic responses.
Receive customized reporting of user data over required periods and compared to various study/project metrics.
Lmtls has partnered with the University of Calgary on an ongoing Randomized Control Trial. The results have yet to be published.
- The content of someone’s “self-reported” data is often unreliable because the person themselves is often not aware of the extent to which unconscious processes control their thoughts, emotions and behaviours.
- Complex & intelligent design in living things is not assumed to be driven by conscious processes.
- Unconscious processes are smart & adaptive throughout the living world.
- Lmtls is based on a successful psychological method of treating the cause of problematic thought, emotion and behaviour.
Interested in using lmtls for a research study?
We are looking for research teams who are interested in using the app in their work.
Please contact us and we can discuss whether lmtls would be a good fit.