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CogniFit: Cognitive Assessment Tool for Holistic Assessments

Scientific publication on the importance of conducting holistic assessments in seniors

  • Conveniently manage research patients from the platform for researchers

  • Evaluate and train up to 23 cognitive skills for your study participants

  • Check and compare participants' cognitive development for your study data

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Original Name: A Holistic approach to assess older adults’ wellness using e-health technologies.

Autores: Hilaire J. Thompson1, George Demiris1,2, Tessa Rue3, Evelyn Shatil4,5, Katarzyna Wilamowska2,Oleg Zaslavsky1 y Blaine Reeder1.

  • 1. Biobehavioral Nursing and Health Systems, School of Nursing, University of Washington, Seattle, Washington.
  • 2. Department of Medical Education and Biomedical Informatics, School of Medicine, University, University of Washington, Seattle, Washington.
  • 3. Center for Biomedical Statistics, Institute for Translational Health Sciences, University of Washington, Seattle, Washington.
  • 4. Department of Psychology and the Center for Psychobiological Research, Max Stern Academic College of Emek Yezreel, Yoqneam Ilit, Israel.
  • 5. CogniFit Ltd., Yoqneam Ilit, Israel.

Journal: Telemedicine and e-health (2011), vol. 17 (10): 794-800.

References to this article (APA style)::

  • Thompson, H., Demiris, G., Rue, T., Shatil, E., Wilamowska, K., Zaslavsky, O., Reeder, B. (2011). A Holistic approach to assess older adults’ wellness using e-health technologies. Telemedicine and e-health, vol. 17 (10), pp.794-800.

Study Conclusion

The different areas of well-being correlate with each other, especially the cognitive and physiological areas. The data shows the importance of holistically assessing the health and well-being of seniors. CogniFit can be an excellent tool for evaluating cognitive health. Negative correlation between age and divided attention (r=-0.48, p=0.029), planning (r=-0,53, p=0.013) and spatial perception (r=-0.718, p<0.0005). The negative correlation between some chronic diseases and planning (r=-0.52, p=0.016).

Study Summary

The prediction and slowing of the progression of chronic diseases in seniors help maintain functional autonomy. Therefore, we can use holistic assessments in order to get a more concrete and adapted the idea of the state of this population. Currently, there are few methodologies that holistically assess the well-being of our seniors. Fortunately, e-health (health technologies), such as CogniFit, can be a good tool for performing these assessments.

Participants were shown how to use different e-health technologies to assess their cognitive, physiological and functional variables of well-being. The correlations between the different parameters were evaluated and a hierarchical cluster analysis was used to determine the validity of the model.

There were strong associations between different wellness parameters, such as cognitive, physical. However, spirituality did not correlate with any other parameter studied. Participants also welcomed e-health technologies.

The parameters correlated strongly across the different areas of well-being. A highlighted strong link between cognitive and physiological areas was discovered, which makes the need for a holistic approach to assessing wellness relevant.

Context

To be able to measure, predict, prevent or slow down chronic diseases and seniors general health problems, it is necessary to address the problem with a holistic and interdisciplinary vision. To this end, e-health can be a good tool. If we want to assess the real degree a person's well-being, we must take into account different parameters of their everyday environment:

  • Physical health and fitness.
  • Mental and cognitive health.
  • Social well-being.
  • Spiritual well-being

This study attempted to assess well-being in a holistic way to learn how these four parameters interact. The technology helps collect, store and analyze a large amount of data in a convenient and non-invasive way. With e-health, we will be able to measure the parameters relevant to the well-being of the elderly.

Methodology

Participants

Twenty-seven people aged 78 to 94 from a retirement community in Seattle, Washington participated. Participants meeting the criteria underwent a detailed eligibility assessment and informed consent was obtained.

Procedure

Participants were taught how to use equipment, study procedures, and pre-test evaluations were conducted. For 8 weeks, participants provided cognitive, physiological and functional data three times a week. All this took about 1 hour. Participants could obtain feedback by accessing their own data. From the first week onwards, most users were able to manage the e-health tools without any help. The e-health tools used were

  • Telehealth kiosk,which evaluates physiological patterns.
  • WebQ, which evaluates functional, social and spiritual well-being.
  • CogniFit, neuropsychological tool that evaluates cognitive parameters.

CogniFit Evaluation: Platform for Researchers.

Older people in this study were assessed with CogniFit at the beginning and end of the 8-week study. Participants conducted the General Cognitive Assessment. CogniFit is a cognitive assessment and training tool with features that make it ideal both for conducting research and for assessing participants' cognitive abilities.

  • In addition to the training, CogniFit also has evaluations that will allow us to know the user's complete profile in a single session. These assessments help measure the baseline level of each participant so that the intervention can begin to adjust to the user from the start. By applying the evaluation after the intervention, we will also be able to measure the changes that it has generated as a result of the training.
  • It is a highly accessible online tool since it is available in 18 languages and only requires a device with Internet access. The CogniFit tool has been validated by scientific studies from a number of countries. This makes it a robust and reliable tool for training our participants' cognitive status.
  • CogniFit currently has 18 different assessment tasks that measure over 20 cognitive skills. Thus, participants and researchers will be able to know the status of their cognitive profile.
  • CogniFit generates a report after each assessment, so that researchers can explain their strengths and weaknesses to their participants and focus on them.
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CogniFitresearcher's platform makes it possible to conveniently handle research conducted with this tool. In order to create a free account all you have to do is follow the steps below. This investigator account allows:

  • Invite and regulate the activities of the participants, as well as the tests that will be applied to measure and/or train their cognitive functions.
  • Collect participant data and being able to see the state and cognitive evolution.
  • To carry out experimental studies on the effects of cognitive stimulation through computer programs.
  • Design the investigation training for general or specific cognitive areas.
CogniFit – Image Sign up

When we are logged in, we may buy licenses for evaluations, trainings or both. The CogniFit tool has 9 different evaluations and 15 different training programs.

CogniFit – Image Main screen

CogniFit's two main products help measure and train all the cognitive skills we work with scientific validity:

  • Assessments: Through 18 different tasks we can accurately evaluate more than 20 cognitive abilities. This allows us to create a complete profile of the participant's current cognitive status. The most complete assessment is the General Assessment Battery (CAB), but CogniFit also offers more specific assessment batteries: for Parkinson, Depression, Dyslexia, ADHD and others. At the beginning of each task, the participant will be interactively explained what to do.
  • Training: With more than 30 training games, it is possible to stimulate all cognitive skillstrained in CogniFit. Personalized brain training allows us to strengthen the cognitive abilities of our participants in an entertaining and comfortable way. CogniFit also offers training for specific pathologies. The games include an interactive explanation so that participants can easily understand how they work. Each training session lasts approximately 15 to 20 minutes. During this time, our participants will carry out three activities (two games and one evaluation task). In addition, the tool automatically adapts the difficulty of the activities to the participants' level. We will also have the option to indicate the number of hours we want each participant to rest between training sessions.

When we have chosen the evaluations and training that interest us, we can invite the participants, assign them a group and the activities they will have to do. Participants will receive an email invitation and will only need to create an account as a normal user and accept that researchers can view their results.

CogniFit – Image Invite participant

From our researcher's account, we will be able to observe participant activity view their profiles or cognitive evolution and export the study data. We will also have access to different data:

  • The status of the five cognitive areas in which the other cognitive skills are included.
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CogniFit – Image Cognitive areas
  • An individual status of each of the cognitive abilities.
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CogniFit – Image Cognitive skills
  • A graphic with the general evolution of the participant's cognitive state, or each of the cognitive abilities independently.
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CogniFit – Image Cognitive evolution

Once we have completed the data collection from the study, we will be able to download the results of each participant to our computer for analysis.

Statistical Analysis

To analyze the data, SPSS 15.0 descriptive statistics were used, correlations of the parameters and a hierarchical cluster analysis with Hoeffding's statistic D was performed.

Results and Conclusions

Overall, participants indicated that they had 0-9 health problems. 17% said their health was excellent and 67% said they were very good. As for their physical health, they tended to say that in the last 30 days it had not been good. On the other hand, social support was perceived as very good. The importance they gave to spirituality was very different from one participant to another. Age correlated negatively with the score in cognitive tasks requiring divided attention (r=-0.48, p=0.029), planning (r=-0,53, p=0.013) and spatial perception (r=-0.718, p<0.0005).

It is striking that social support and spirituality did not correlate with other well-being parameters, which clashes with some previous studies. In the cognitive, physical and functional areas, there were a number of chronic diseases that correlated negatively with the scoring in tasks requiring planning (r=-0.52, p=0.016) , while the difficulties in daily living activities correlated with inhibition (r=0).46, p=0.03) . The subjective perception of having better health correlated positively with the score in inhibition tasks (r=0.493, p=0.0027) and planning tasks (r=0.47, p=0.037). The hierarchical cluster analysis showed two groups of data: physiological and other parameters.

In this study, large correlations between the different areas of well-being are observed, especially cognitive and physiological. These data speak to the importance of holistically assessing the health and well-being of seniors. CogniFit has proven to be a tool capable of effectively and truthfully measuring cognitive health.

Patient #141

Cate Brown

catebrown@mail.com

59 years old

Last activity: 02/01/2016 | 4:09 min

Registration date: 01/01/2013

Total number of logins: 23

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598

Focused Attention

608

Auditory Short-term Memory

468

Spatial Perception

405

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