Planning and Incentives for Traumatic Brain Injury

Age: 18+

Sex: Any

Travel: May Be Covered

Time Reimbursement: Varies

Trial Phase: Academic

Recruiting

Sponsor: Northeastern University

Must not be taking: CNS medications

Disqualifiers: Severe TBI, Neurological condition, others

No Placebo Group

Trial Summary

What is the purpose of this trial?

The purpose of this research is to learn if different behavioral interventions can change walking behaviors over 12-weeks, in older adults who have previously suffered a non-penetrating mild or moderate TBI. Participants will provide information and be screened for eligibility via phone screening call (verification of age, confirmation that the participant is not currently on any medication that affects the central nervous system, and verification that the subject can participate in exercise, brief TBI history). Baseline testing will take place at the Center for Cognitive and Brain Health and Northeastern University Biomedical Imaging Center, for the baseline magnetic resonance imaging, in the interdisciplinary science and engineering complex on Northeastern University's campus. In person testing will take place over one session. The study period lasts 12 weeks, during which all participants will 1. Receive a weekly phone call with study staff and 2. Wear a wrist-worn Fit Bit tracker. A remote participation option is available for those who cannot travel to Northeastern University.

Will I have to stop taking my current medications?

The trial requires that participants are not currently on any medication that affects the central nervous system. If you are taking such medications, you may need to stop them to participate.

What data supports the effectiveness of the treatment Planning and Incentives for Traumatic Brain Injury?

Research shows that incentive-based interventions, which reward healthy behaviors, can effectively promote behavior change. Health education has also been proven to alter health behaviors, suggesting that combining these approaches could support rehabilitation after traumatic brain injury. ^{1 2 3 4 5}

Is the treatment generally safe for humans?

The research does not provide specific safety data for the treatment, but it discusses the effectiveness of health education and incentive-based interventions, which are generally considered safe when applied correctly. ^{2 4 6 7 8}

How is the treatment 'Planning and Incentives for Traumatic Brain Injury' different from other treatments for TBI?

This treatment is unique because it combines health education, planning, reminders, and micro-incentives to encourage rehabilitation after a traumatic brain injury. Unlike traditional treatments, it uses small rewards to boost motivation and participation in rehabilitation activities, which can be particularly effective for individuals with memory challenges. ^{9 10 11 12 13}

Research Team

Eligibility Criteria

This trial is for older adults who have had a mild or moderate non-penetrating traumatic brain injury (TBI). They must be able to exercise, not on central nervous system medications, and willing to attend baseline testing at Northeastern University. Specific inclusion and exclusion criteria details were not provided.

Inclusion Criteria

Signed Informed consent

Men and women of all ethnicities/races and socio-economic status

Physically fit enough to undergo exercise as screened using the Physical Activity Readiness Questionnaire (PAR-Q) and the cardiovascular section of the Health History & Demographics Questionnaire

Exclusion Criteria

Not MRI compatible

Not medically cleared for exercise

I am not fluent in English.

Trial Timeline

Screening

Participants are screened for eligibility to participate in the trial

1 week

1 visit (phone call)

Baseline Assessment

Participants undergo baseline testing including MRI and cognitive assessments

1 session

1 visit (in-person)

Treatment

Participants receive behavioral interventions over 12 weeks, including weekly phone calls and wearing a Fit Bit

12 weeks

12 visits (phone calls)

Follow-up

Participants complete post-testing remotely, including cognitive tasks and questionnaires

1 week

Remote participation

Treatment Details

Interventions

• Health Education (Behavioural Intervention)
• Planning, Reminders, and Micro-Incentives (Behavioural Intervention)

Trial Overview The study compares the effectiveness of a special program with planning, reminders, and small rewards against standard health education in increasing physical activity over 12 weeks. Participants will use FitBit trackers and record their walking activities.

Participant Groups

Group I: Planning, Reminders, and Micro-Incentives Experimental Treatment 1 Intervention

Group II: Health Education Active Control 1 Intervention

Who Is Running the Clinical Trial?

Northeastern University

Lead Sponsor

Trials

103

Recruited

72,600+

Jared Auclair

Northeastern University

Chief Executive Officer

PhD in Biomedical Science from the University of Massachusetts Medical School

Anantdeep Kaur

Northeastern University

Chief Medical Officer since 2023

Master’s and Doctorate in Biotechnology from the University of Technology Sydney

Timothy Morris

Lead Sponsor

Trials

1

Recruited

60+

Brandeis University

Collaborator

Trials

22

Recruited

14,000+

National Institute on Aging (NIA)

Collaborator

Trials

1,841

Recruited

28,150,000+

Dr. Richard J. Hodes

National Institute on Aging (NIA)

Chief Executive Officer since 1993

MD from Harvard Medical School

Dr. Marie Bernard

National Institute on Aging (NIA)

Chief Medical Officer

MD from Harvard Medical School

Findings from Research

Many incentive programs aimed at improving patient self-care are unlikely to be effective because they rely on patients having the necessary information, expertise, and self-control, which many do not possess.

Incorporating behavioral economics insights, such as providing small, frequent payments for positive health behaviors like medication adherence, can enhance the effectiveness of these programs and improve patient engagement, benefiting both patients and insurers.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Behavioral economics holds potential to deliver better results for patients, insurers, and employers. Loewenstein, G., Asch, DA., Volpp, KG.[2022]

Incentive-based interventions that promote healthy behaviors, such as exercise and smoking cessation, are becoming more common in healthcare settings and can significantly impact health outcomes.

Behavior analytic research provides valuable insights that can help healthcare providers design effective incentive-based interventions tailored to encourage specific healthy behaviors.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The ABCs of incentive-based treatment in health care: a behavior analytic framework to inform research and practice. Meredith, SE., Jarvis, BP., Raiff, BR., et al.[2021]

The Dynamic Computer Interactive Decision Application (DCIDA) was developed to help patients make better health decisions by addressing common cognitive errors, and preliminary testing with 20 participants showed it was reasonably usable and useful.

Participants using DCIDA spent 21% more time focusing on the most important features of their decisions, and 25% changed their preferred option, indicating that the application may enhance the quality of decision-making in healthcare.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Development and preliminary user testing of the DCIDA (Dynamic computer interactive decision application) for 'nudging' patients towards high quality decisions. Bansback, N., Li, LC., Lynd, L., et al.[2022]

Behaviour Change Interventions (BCIs) and Patient Decision Aids (PtDAs) have distinct goals and methods but can be integrated to enhance health-related decision-making and behavior change for individuals.

The integration of insights from both BCIs and PtDAs could improve patient engagement and help individuals set and achieve health goals that align with their personal values and preferences.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Integrating behaviour change interventions and patient decision aids: How to accomplish synergistic effects? Gültzow, T., Hoving, C., Smit, ES., et al.[2023]

Health education initiatives have been shown to effectively change health behaviors, contributing to improved health outcomes, although the specific mechanisms behind this success are not fully understood.

Incorporating preventive services into patient care, especially for high-risk individuals, can enhance the effectiveness of health education efforts, highlighting the growing focus on preventive care in primary healthcare settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Education for health. A role for physicians and the efficacy of health education efforts. Council on Scientific Affairs. [2016]

Health interventions developed over the last 20 years show substantial effectiveness, with average effect sizes of 0.46 for primary prevention and 0.49 for secondary prevention and patient education, based on meta-analyses of various studies.

The effectiveness of these interventions can be enhanced by systematically applying social science theories in their development and incorporating learning principles like rewards and feedback, as well as strategies to facilitate behavior change, such as reminders and financial incentives.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Effectiveness of health education and health promotion: meta-analyses of effect studies and determinants of effectiveness. Kok, G., van den Borne, B., Mullen, PD.[2019]

Health care interventions, like computerized order entry systems, can lead to new types of errors, as providers may depend too much on default information instead of consulting proper guidelines.

To improve the effectiveness of health care interventions, it's important to measure how patients and physicians behave in response to these interventions, as this can help explain why some logical solutions don't work as well in real-world settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The Peltzman effect and compensatory markers in medicine. Prasad, V., Jena, AB.[2019]

A systematic review of six studies on cue-reminders in health-risk behavior interventions showed mixed results, with one study indicating a small positive effect and another a medium negative effect.

Overall, the evidence is inconclusive regarding the effectiveness of cue-reminders in enhancing health-risk behavior interventions, suggesting that more research is needed to determine their true impact.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Cue-Reminders to Prevent Health-Risk Behaviors: A Systematic Review. van Leeuwen, L., Onrust, S., van den Putte, B., et al.[2020]

A collaborative process involving researchers, individuals with traumatic brain injury, and health professionals led to the development of a survey that identifies physical activity preferences for people with moderate-to-severe traumatic brain injury, refining 17 initial attributes down to six key factors.

The co-development process enhanced the survey's relevance and clarity, addressing challenges in recruitment and communication, which could be beneficial for similar studies in the future.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Physical Activity Preferences of People Living with Brain Injury: Formative Qualitative Research to Develop a Discrete Choice Experiment. Haynes, A., Howard, K., Johnson, L., et al.[2023]

Participants with traumatic brain injury (TBI) reported an average of 2.25 barriers to physical activity (PA) and completed about 46 minutes of PA weekly, indicating that while barriers exist, some level of activity is achievable.

Those in the 'action' and 'maintenance' stages of PA participation engaged in significantly more activity compared to those in earlier stages, highlighting the importance of readiness to change in promoting physical activity among TBI patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

What barriers to physical activity do individuals with a recent brain injury face? Driver, S., Ede, A., Dodd, Z., et al.[2016]

Understanding non-compliance in individuals with traumatic brain injury (TBI) involves considering factors like memory deficits, cultural background, and personal interests, which can influence their participation in treatment.

Using techniques like consequence management and antecedent control can effectively promote engagement in therapy, highlighting the importance of recognizing each individual's unique preferences and pre-injury lifestyle.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Assessing and treating non-compliance in brain-injured clients. Zencius, AH., Lane, I., Wesolowski, MD.[2019]

A study involving 116 participants with mild-to-moderate traumatic brain injury found that a combined cognitive and vocational intervention (CCT-SE) was more cost-effective from a societal perspective compared to treatment as usual (TAU), primarily due to lower productivity loss costs.

While the CCT-SE intervention resulted in higher healthcare costs, it led to a quicker return to work, with an incremental cost-effectiveness ratio of €56 per day earlier back to work, indicating its potential benefits in reducing overall societal costs associated with TBI.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Cost-effectiveness analysis of combined cognitive and vocational rehabilitation in patients with mild-to-moderate TBI: results from a randomized controlled trial. Howe, EI., Andelic, N., Fure, SCR., et al.[2022]

In a study involving 24 clients with traumatic brain injury (TBI), the introduction of monetary incentives significantly improved memory performance across three different memory tasks compared to conditions without rewards.

These findings support the author's incentive-based model of cognitive retraining, suggesting that rewards can enhance cognitive function in individuals with TBI.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Effect of monetary incentives on performance after traumatic brain injury. Parenté, R.[2014]

References

1. United States pubmed.ncbi.nlm.nih.gov

Behavioral economics holds potential to deliver better results for patients, insurers, and employers. [2022]

2. New Zealand pubmed.ncbi.nlm.nih.gov

The ABCs of incentive-based treatment in health care: a behavior analytic framework to inform research and practice. [2021]

3. England pubmed.ncbi.nlm.nih.gov

Development and preliminary user testing of the DCIDA (Dynamic computer interactive decision application) for 'nudging' patients towards high quality decisions. [2022]

4. Ireland pubmed.ncbi.nlm.nih.gov

Integrating behaviour change interventions and patient decision aids: How to accomplish synergistic effects? [2023]

5. United States pubmed.ncbi.nlm.nih.gov

Education for health. A role for physicians and the efficacy of health education efforts. Council on Scientific Affairs. [2016]

6. Ireland pubmed.ncbi.nlm.nih.gov

Effectiveness of health education and health promotion: meta-analyses of effect studies and determinants of effectiveness. [2019]

7. Netherlands pubmed.ncbi.nlm.nih.gov

The Peltzman effect and compensatory markers in medicine. [2019]

8. Switzerland pubmed.ncbi.nlm.nih.gov

Cue-Reminders to Prevent Health-Risk Behaviors: A Systematic Review. [2020]

9. New Zealand pubmed.ncbi.nlm.nih.gov

Physical Activity Preferences of People Living with Brain Injury: Formative Qualitative Research to Develop a Discrete Choice Experiment. [2023]

10. United States pubmed.ncbi.nlm.nih.gov

What barriers to physical activity do individuals with a recent brain injury face? [2016]

11. England pubmed.ncbi.nlm.nih.gov

Assessing and treating non-compliance in brain-injured clients. [2019]

12. England pubmed.ncbi.nlm.nih.gov

Cost-effectiveness analysis of combined cognitive and vocational rehabilitation in patients with mild-to-moderate TBI: results from a randomized controlled trial. [2022]

13. Netherlands pubmed.ncbi.nlm.nih.gov

Effect of monetary incentives on performance after traumatic brain injury. [2014]