Frontiers | Increasing physical activity in moderate-severe traumatic brain injury: protocol for a two-stage randomized controll

Frontiers | Increasing physical activity in moderate-severe traumatic brain injury: protocol for a two-stage randomized controlled trial of a remote, mHealth-enhanced intervention
METHODS article
Front. Rehabil. Sci.
, 02 February 2026
Sec. Interventions for Rehabilitation
Volume 7 - 2026 |
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Advancing Physical Activity Behavior Change: The Potential of Serious Digital Health Technologies
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METHODS article
Front. Rehabil. Sci.
, 02 February 2026
Sec. Interventions for Rehabilitation
Volume 7 - 2026 |
Increasing physical activity in moderate-severe traumatic brain injury: protocol for a two-stage randomized controlled trial of a remote, mHealth-enhanced intervention
Tessa Hart
Monica Vaccaro
Lauren Krasucki
Inna Chervoneva
Amanda Rabinowitz
1.
Jefferson Moss Rehabilitation Research Institute, Elkins Park, PA, United States
2.
Division of Biostatistics, Thomas Jefferson University Sidney Kimmel Medical College, Philadelphia, PA, United States
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Abstract
Objective:
Protocol for randomized controlled trial (RCT) examining effects of novel, remotely delivered intervention (called GetUp&Go) to increase physical activity (PA) in chronic, moderate-severe traumatic brain injury (msTBI), including a mobile health (mHealth) component.
Design:
RCT (Clinicaltrials.gov NCT06028334) with 1:1 randomization to 10 weeks of immediate treatment (IT) or waitlist (WL), with primary outcome measured at 10 weeks. A second randomization to 10 weeks of continued mHealth support vs. no treatment will allow for examination of effects of mHealth on maintenance of treatment gains.
Participants:
70 community-dwelling adults ≥6 months post msTBI; medically cleared and physically/ cognitively able to participate; physically inactive (≤23 weekly moderate/ vigorous activity units on Godin Leisure-Time Exercise Questionnaire).
Interventions:
10-week GetUp&Go program: manualized, remotely delivered intervention with ingredients based on theoretical model of behavior change, in which participants set individual goals and programs for increasing PA; mHealth support via chatbot that delivers personalized messages, reminders, and reinforcement to participant phone.
Main outcome measures:
Primary outcome is activity count measured by accelerometer worn on wrist for 7 days at all assessment intervals. Secondary outcomes include emotional function, fatigue, sleep, pain, health-related quality of life.
Discussion:
While conclusions await the results of the trial, we consider PA enhancement to be a valuable and under-studied direction for treatment of msTBI. The advantages of the described treatment include strong theoretical and empirical basis for the treatment protocol, which has been designed to help to circumvent difficulties with initiation, persistence, and memory that interfere with the ability to develop healthful habits and routines following msTBI.
1 Introduction
The importance of physical activity (PA) for human health and well-being is incontrovertible. Widely cited guidelines state that adults aged 18+ should engage weekly in at least 150 min of moderate-to-vigorous PA (MVPA) or 75 min of vigorous-intensity PA, plus ≥2 bouts of strengthening activities involving all major muscle groups (
). PA at this level is associated with many health benefits including lower risk of all-cause mortality, reduced risk of depression and anxiety, improved sleep, and better quality of life (
). In the general population there is also a strong association between PA and emotional well-being (
).
Moderate to severe traumatic brain injury (msTBI) is a significant public health problem. It is estimated that in the US alone, almost 20% of the population has experienced TBI with loss of consciousness (
). Although many TBIs lead to transient symptoms, msTBI can cause potentially lifelong difficulties with physical, cognitive, and emotional function, leading to the recent conceptualization of TBI as a chronic health condition (
). A growing body of research shows that people with msTBI have decreased PA levels after msTBI compared to preinjury (
), as well as increased propensity for sedentary behavior and weight gain (
) and significantly elevated risk of cardiovascular disease (
10
). Among the many barriers to PA reported by those with msTBI are potential for pain, discomfort, or embarrassment; safety concerns; insufficient knowledge about PA or lack of access to PA-friendly spaces; limitations in time, transportation and other resources; fatigue; and poor motivation (
11
13
).
Despite these barriers, people with msTBI have expressed the view that PA is very important and report a high level of interest in programs promoting PA (
12
14
), particularly those adapted to the specific needs of people with brain injury (
15
). PA programs delivered remotely are also acceptable to this population (
16
). Studies show that even those with mobility limitations due to msTBI are able to attain cardiovascular fitness equivalent to their uninjured counterparts (
17
). Several reports suggest that PA also improves cognitive function following msTBI (
18
19
). An intriguing observational study (
20
) revealed that in persons with a history of TBI, there were significantly stronger correlations between PA and self-reported measures of cognitive function and global health, compared to the same correlations in uninjured controls. Although causality cannot be assumed, one implication of this finding is that people with TBI could experience a particularly high degree of health benefit from increased PA.
There is a modest literature describing efforts to increase PA for people with msTBI; most have tested short-term aerobic exercise programs, using a variety of outcome measures. A 2020 systematic review included 9 studies that used reduction in depression symptoms as a primary outcome (
21
). Small to medium positive effects on mood were noted overall; however, the effects on sustained PA were largely unexamined. Another group of studies examined cardiovascular endurance and/ or resistance training. A 2010 narrative review (
22
) and a 2017 Cochrane review (
23
) concluded that exercise training is safe in msTBI and mostly effective in improving fitness, but that the clinical value remained unclear. That is, the impact on metabolic measures of fitness was confirmed, but not the effect of increased PA in daily life or health and well-being. A more flexible approach, using individually tailored PA plans rather than prescribed exercise regimens, has been used by a few investigators. For example, Clanchy and colleagues (
24
25
) delivered 10 sessions of PA promotion to persons with msTBI and other forms of acquired brain injury, both in-person and by phone, with the frequency of contact diminishing over time. The program emphasized safe, sustainable, and enjoyable activities, and included individualized relapse-prevention strategies as a final step. Therapist contact was withdrawn so that self-maintained PA could be measured 12 weeks after treatment cessation. While robust effects were found for increased PA after treatment, there was limited maintenance of gains at follow-up (
24
). The authors emphasized the importance of continued support to maintain gains in PA. Similarly, the most recent systematic review of PA interventions for msTBI (
26
) echoed the need for follow-up. This review also noted that the majority of studies to date are of poor methodologic quality, limiting conclusions about the impact of PA on function and quality of life in this population. The authors also urged the use of a broader range of outcome measures, including health and participation measures; more attention to study power; and more rigorous study design.
As detailed below, we have attended to all of these recommendations in developing the current trial. We designed an intervention for promoting PA in people with msTBI that has the following characteristics.
1.1 Theoretical basis
Few efforts to increase PA in this population have been grounded in theory, yet the literature on PA promotion in the general population has yielded rich insights from theoretical models of health-related behavior change. The ingredients used in the current intervention were derived from a highly influential model: the COM-B framework of Michie and colleagues (
27
). This framework, which has been called a “meta-theory (
28
),” has been rigorously developed and validated in extensive research on health behavior (
29
33
) and was strongly supported in a review of major theoretical approaches to PA promotion (
34
). According to this model, voluntary behavior and changes in behavior are a function of three factors:
apability,
pportunity, and
otivation. Capability refers to both cognitive/ psychological capacity, e.g., knowledge about why and how to perform a desired behavior and remembering to do it, and the physical ability to perform it. Opportunity means access to necessary social and physical/ logistic resources, including space, time, and social support. Motivation refers both to conscious/ reflective factors affecting drive and reward, and reflexive/ automatic motivation (e.g., priming) that may enhance habit formation (
27
).
1.2 Individual tailoring
Within this theoretical framework, we designed the intervention to accommodate a wide range of individual choices and physical capabilities. In this regard we were guided by the work of Clanchy et al. (
24
25
) as well as research showing a
dose-response
relationship between PA increase and health benefit—meaning that it is not necessary to meet the standard recommendations for PA levels to experience improvements in mood, energy, and quality of life, as well as health risk reduction (
35
).
1.3 Remote delivery and mobile health support
Studies have revealed that personalized PA programs can successfully be delivered via remote means including phone, web, and text messages (
36
37
). A recent review focused on smartphone-delivered PA promotion for mental health emphasized the importance of including education about the value of PA and personalized coaching within the intervention (
38
). There is a burgeoning literature showing that persons with msTBI, even those with significant neurocognitive impairment, can successfully engage in, and benefit from, interventions delivered via phone (
39
41
) and other remote methods. Mobile health (mHealth) interventions, such as smartphone apps and interventions delivered by text, are increasingly being used in TBI rehabilitation and research (
42
43
). As described below, the current study provides both remote therapist contact and mHealth support from a chatbot called RehaBot, which was developed in our laboratory specifically for the needs of participants with TBI. In a feasibility study, participants with msTBI found RehaBot both easy to use and enjoyable (
44
).
1.4 Objective measurement of PA
There is considerable evidence that self-report measures of PA are less reliable than objective measurement using accelerometers worn on the body (
45
); the latter method has been shown to be reliable in persons with TBI (
46
). In this study, our primary outcome is increase in PA from pre- to post-treatment, measured with a wrist-worn accelerometer that has been successfully used with the msTBI population (
47
).
1.5 Attention to long-term impact
As described below, we include a follow-through phase to assess the effects of the intervention after therapist support is withdrawn, with randomization either to no continued support, or continued use of RehaBot (without therapist intervention). We also include treatment ingredients that have been shown to help sustain new PA habits, and less sedentary behavior, as part of daily life (
36
48
).
1.6 Consumer input
Throughout intervention development, consumer input was obtained through multiple structured methods. Two paid consumer consultants with lived experience of msTBI and self-reported difficulties with PA were engaged in this process. Input was collected through facilitated focus group sessions where consultants reviewed and provided feedback on the treatment rationale and session structure; visual materials and participant handouts; and the use of RehaBot to deliver just-in-time support for PA in participants' daily environments. Additionally, consumer consultants participated in pilot testing of treatment sessions, providing feedback on feasibility, acceptability, and comprehensibility of intervention components. This iterative feedback was incorporated into the final treatment manual. Consultants also selected the name of the intervention:
GetUp&Go
1.7 Aims and hypotheses
The aim of this study is to examine the efficacy of the GetUp&Go intervention for increasing PA and enhancing associated functional outcomes in msTBI. We propose the following hypotheses:
1a. Participants who receive the GetUp&Go intervention directly after randomization will show significantly more increase in PA, as assessed by average accelerometer activity counts/ day, from pre-randomization baseline to post-treatment 10 weeks later, compared to those waitlisted for 10 weeks.
1b. Participants randomized to immediate treatment (IT) will also show significantly more improvement compared to waitlisted participants (WL) on secondary outcome measures including intensity of PA (derived from accelerometer readings), self-reported PA, emotional function, fatigue, sleep, pain, and health-related quality of life.
2a. Participants randomized to continued use of RehaBot for 10 weeks after treatment (RB) will demonstrate significantly less diminution in accelerometer-based activity counts from post-treatment to 10-week follow-up compared to those for whom RehaBot is withdrawn (No Tx), adjusted for the degree of change in the initial treatment phase.
2b. Participants randomized to RB in the follow-through phase will demonstrate significantly less diminution/ worsening in other outcome domains listed under Hypothesis 1b, compared to No Tx participants.
In addition to testing these hypotheses, we will explore the predictors of treatment response, using pooled data from all participants from pre- to post-treatment. We will analyze in exploratory fashion the predictive effects of demographic and injury characteristics; baseline cognitive, physical, social, emotional, and personality factors; objective and perceived neighborhood characteristics; intrapersonal variables such as motivation, self-efficacy, outcome expectancies, and identity/ values as related to PA; and process variables such as the amount of interaction with RehaBot during treatment.
2 Methods
2.1 Overview of design
This is a randomized waitlist-controlled trial, registered prior to participant recruitment at
(NCT06028334). As shown in
Figure 1
, after a baseline assessment, participants are randomized 1:1 into IT (10 weeks of GetUp&Go intervention) or WL (10 weeks on waitlist), after which the primary outcome is measured. WL participants then receive 10 weeks of GetUp&Go. The 10-week treatment period (for all participants) is termed the Acquisition or A phase. Directly after the A phase, participants are re-randomized 1:1 into the Follow-Through (FT) phase: 10 additional weeks, of either RB or No Tx. A final outcome assessment and a debriefing interview are conducted at the end of the FT phase.
Figure 1
2.2 Participants
Participants will be 70 persons who meet the following inclusion criteria: (1) age ≥18; (2) TBI (open or closed), sustained at least 6 months prior to enrollment, of at least moderate severity as evidenced by: (a) loss or alteration of consciousness ≥30 min and/ or post-traumatic amnesia (PTA) ≥ 24 h, not due to intoxication/ sedation
and
documented prospectively from the injury (i.e., not retrospectively self-reported); and/ or (b) positive neuroimaging findings consistent with TBI; (3) fully weight bearing on lower limbs and able to walk indoors and outdoors without the assistance of another person (independent use of an assistive device such as a cane is acceptable); (4) cognitively able to participate in treatment, using selected items from the Glasgow Outcome Scale-Extended (
49
); (5) able to communicate adequately in English for participation in the treatment protocols; (6) informed consent given by participant. Participants are excluded for (1) contraindications to increasing PA as judged by a study physician and/ or study Physical Therapist, using an exam adapted from published screening tools (
50
); (2) medical or psychiatric instability, including current psychosis or severe uncontrolled substance misuse, as assessed using items from the Mini-International Neuropsychiatric Interview (
51
), or suicidal ideation with intent or plan, as assessed by the Columbia-Suicide Severity Rating Scale, screening version (
52
); (3) significant physical or intellectual disability predating the TBI; (4) neurodegenerative disorder, e.g., Parkinson's disease, dementia; (5) insufficiently inactive, i.e., reporting >23 weekly moderate/ vigorous activity units on the Godin Leisure-Time Exercise Questionnaire (
53
); (6) planned surgery or other hospitalization during the succeeding 9 months; (7) physical or sensory disability (e.g., blindness; severe bimanual incoordination) that prevents use of a smartphone.
2.3 Measures
The measures collected at each time point are displayed in
Table 1
. The baseline evaluation (T1) includes psychometric measures and questionnaires as well as demographic and injury-related information collected from medical records and participant interview. Because we have found that primary medical chart information is variable for people with chronic TBI, we measure PTA duration with a structured interview that has been used in other studies and that correlates well with prospectively measured PTA (
54
). The primary outcome (average activity counts/ minute) and other objective PA outcomes are measured using the wrist-worn Actigraph GT3XP. Activity counts using the GT3XP correlate well with biometric measures of energy expenditure (
55
). Following a practice prevalent in the PA measurement literature (
56
57
), daily activity counts are averaged only from a minimum of 4 full wear days out of each 7-day wear period; if 4 days of data are not recorded, the wear period is repeated or discarded.
Table 1
Type and name of measure
T1
T2/T2b
T3
Demographics: Age, race/ ethnicity, education
Injury severity (estimated days of PTA), time post injury
Episodic memory: Rey Auditory Verbal Learning Test (
58
) z-scores
Executive function: Trail Making Test (
59
), Brixton Spatial Anticipation Test (
60
Speed of processing: Symbol Digit Modalities Test (
61
Conscientiousness/ other personality factors: NEO Personality Inventory-Revised (
62
Living situation; use of walking aid; Body Mass Index
Neighborhood characteristics: Safety, walkability
Social support for PA (
63
64
Type and level of motivation for PA: Exercise Regulations Questionnaire (BREQ-3) (
65
Self-efficacy, outcome expectancies, and identity/ values related to PA (
64
66
68
Outcome measures
Accelerometer: average counts/ minute from 4 + days over 7-day wearing period (primary outcome)
Accelerometer: % time sedentary, % time engaged in MVPA, avg daily step count
Self-reported PA: Godin Leisure-Time Exercise Questionnaire (
53
Emotional function: Brief Symptom Inventory-18 (
69
Fatigue: Fatigue Severity Scale, short form (
70
Sleep quality: Pittsburgh Sleep Quality Index (
71
Pain: PROMIS Pain Interference Scale, short form 6b (
72
Health-related quality of life: Quality of Life After Brain Injury (
73
Measures administered at each data collection point.
2.4 Procedure
This study is approved and overseen by an Institutional Review Board (iRISID-2023-1533) and complies in full with the Helsinki Declaration for the protection of human subjects.
Participants are recruited from a variety of sources including two research registries at the study site, as well as clinical programs at the site and others in the geographical vicinity. Recruitment began in December, 2023 and is expected to continue until December, 2026. Prospective participants are screened for eligibility over the phone after expressing interest in the study and assenting to screening. Eligible participants are invited to an in-person session that includes written consent, administration of T1 measures listed in
Table 1
, and screening by both the study physician and the study Physical Therapist. These screenings include a review of systems and assessment of vital signs, lower extremity range of motion, and mobility. Exercise tolerance is evaluated using the modified Bruce protocol (
74
). Following the physical/ medical screening and the T1 evaluation, participants are given the Actigraph and instructed to wear it continuously for 7 days as they go about their normal routines in the home and community. Participants are given postage-paid padded envelopes for returning the devices.
After all baseline data including the Actigraph data are collected, participants are randomized 1:1 to IT or WL. Randomization uses a sequence of permuted blocks randomly selected from sizes 6, 9, and 12. The randomization sequence was created by the study statistician and is kept in a securely housed spreadsheet which kept all but the current treatment assignment obscured from view. To maximize equipoise and minimize attrition, participants are informed that the randomization is to “one baseline evaluation” or “two baseline evaluations 10 weeks apart.” WL participants receive periodic contacts from research staff reminding them of their upcoming activities in the program. After this initial 10-week period, the primary outcome is measured with another 7-day Actigraph wear period, followed by telephone administration of the outcome measures listed in
Table 1
When all post-treatment data are collected (at T2 for IT and T2b for WL), participants are re-randomized 1:1 to 10 weeks of RB or No Tx (see
Figure 1
). T3 data are collected after that interval and as a final step, the participant receives a 15-minute debriefing interview by phone. This interview includes the Patient Global Impression of Change scale (
75
), worded as follows: “Since your participation in this study, how would you describe the change (if any) in areas of your life that could be related to physical activity and fitness, such as physical and mental well-being, mood, and overall quality of life?” Responses are on a 7-point scale from “No change (or condition has gotten worse)” to “A great deal better and a considerable improvement that has made all the difference.” Other questions are concerned with features of the treatment and the RehaBot app that the participant particularly liked or disliked.
This trial uses masked outcome assessment, with special precautions taken to prevent inadvertent unmasking. These include making treatment information completely inaccessible to data collection staff, and using a “script” reminding participants not to discuss any of their experiences in the program when contacted by a data collector. Any instances of inadvertent unmasking are recorded for later analysis of their influence, and data collectors are asked to guess the participant's treatment allocation following each assessment.
Adverse events (AEs) are documented systematically throughout the trial. AEs are defined as any of the following: 1) Events that initiate the risk management protocol (i.e., expression of suicidal ideation or intent), 2) Events prompting an unscheduled emergency department visit not resulting in hospitalization, 3) Any unanticipated event that is unexpected and related to the study treatment. Serious Adverse Events (SAEs) are defined as outcomes resulting in death, hospitalization, life-threatening circumstances, person at risk of death at the time of the event, disability and/or incapacity, or events requiring intervention to prevent these outcomes. All hospitalizations are considered SAEs, with the exception of planned hospitalizations for elective procedures unrelated to the study intervention. AEs and SAEs are tracked through multiple surveillance mechanisms: spontaneous reporting by participants, discovery by study staff, identification by clinicians during therapy sessions, or detection during study assessments. When an AE is identified or reported, the therapist/data collector completes an Adverse Event Form immediately. This form documents the adverse event type, duration and timing, event details, and resolution status. AEs are reviewed periodically by a Data Safety Monitoring (DSM) team consisting of a physiatrist with extensive experience in msTBI research, and a statistician with expertise in clinical trials methodology. The DSM team also reviews and makes recommendations on recruitment, attrition, and other data relevant to the conduct of the trial and human subjects protections.
2.5 Intervention
The overall goal of the intervention is to develop and support a personalized plan to increase physical activity and decrease sedentary behavior, using treatment ingredients consonant with the COM-B model (
27
). The ingredients in each COM-B domain (Capability, Opportunity, Motivation) that are supplied by the therapist and by RehaBot are summarized in
Table 2
Table 2
COM-B domain
Treatment Ingredients
Capability: Physical
-Elicit past skills/ experiences and current preferences re: PA
-Steer P toward safe/ appropriate activities as per MD/ PT screening; provide instruction for safe/ effective PA as needed
Capability: Psychological/ Cognitive
-Education about PA: benefits, types, dose-response relationship
-Provide menus and ideas for PA at all levels of intensity; indoors and outdoors; scheduled bouts and incidental activity
-Teach how to monitor exertion level, as needed
-Provide structure and prompts for action planning (where, when, how, how often, with whom PA will be performed) and coping planning (how to deal with anticipated obstacles to PA)
Provide reminders of planned activities in P's daily environment
Provide on-demand support by reminding P of daily plans and coping plans
Opportunity: Social
-Elicit information about familial and sociocultural norms/ factors that may affect P's pursuit of PA
-Encourage P to solicit support and/ or co-participation in PA from family and friends
Opportunity: Physical
-Assess/ discuss perceived neighborhood characteristics (walkability, aesthetics, safety, amenities)
-Assess/ discuss home/ lifestyle affordances (space, time); assist with time management as needed
-Elicit information, problem-solve, and provide tips regarding equipment/ clothing, facilities, transportation, costs, other resources
-Encourage PA in varied contexts to promote generalization
Motivation: Reflective
-Assist P in formulating/ stating macro goals and intentions regarding PA; prompt/ discuss self-assessment of commitment level
-Assess self-efficacy regarding chosen PA, ability to cope with obstacles, and ability to schedule PA in daily life; provide feedback and information to enhance self-efficacy; remind P of past and current successes
-Assess for, encourage, and reinforce autonomous motivation for PA
-Elicit expected positive outcomes; elicit and educate re: negative beliefs
-Teach/ encourage motivational self-talk, including implementation intentions
-Provide verbal reinforcement and feedback on gains
Support self-monitoring by prompting P to report on progress towards goals and positive outcomes/ satisfaction with increased PA in their daily environment as they complete activities
Provide reinforcing messages in the moment as P completes activities
Provide on-demand feedback on accomplishments and progress towards goals
Provide on-demand support by reminding P of macro goal intentions regarding PA
Motivation: Automatic
-Explore P's implicit associations with PA as pleasant/ unpleasant
-Steer P toward activities that evoke pleasure, enjoyment
-Explore and encourage P's values related to PA and self-identification as an (e.g.) active person/ fit person/ role model to others
-Prompt P to use habit formation strategies such as distinctive activity-initiation cues in environment, time-of-day cues
Assist in habit formation by cuing P's activities in daily environment
Treatment ingredients in theoretically defined domains in the GetUp&Go program. Ingredients delivered via RehaBot are
italicized.
P, participant; MD, medical doctor; PT, Physical Therapist; PA, physical activity.
The 10-week GetUp&Go intervention is delivered entirely remotely. The first 2 sessions last 60–90 min each and are delivered within the first week over Zoom for Healthcare (or smartphone if needed). The following 3 sessions (in weeks 3, 5, and 8) are delivered by phone and last 30–45 min. The RehaBot app is installed on the participant's phone in Session 2 followed by a guided overview and brief training that includes hands-on practice, troubleshooting, and opportunities to ask questions, until the participant expresses confidence in using the app. Participants who do not own a smartphone or do not have access to a computer/ tablet are issued a phone with unlimited texting and/ or an iPad for the duration of the trial. To maximize scheduling flexibility, participants are assigned to one of 4 therapists: Two doctoral level neuropsychologists, one Masters-trained clinician with extensive experience in neuropsychological approaches to the treatment of msTBI, and one doctoral-level Physical Therapist. All therapists are experienced clinicians with specific expertise in treating persons with msTBI. To ensure fidelity, a detailed manual is used for all treatment sessions. In addition, two therapists were present during treatment sessions for the first four participants in the trial in order to achieve proficiency and consistency in delivering the intervention. All therapists continue to meet weekly to review cases to ensure that their approaches and procedures are comparable.
In Session 1, the therapist provides education on the benefits of PA, emphasizing the dose-response relationship (i.e., the fact that
any
degree of PA increase is potentially beneficial). In discussion with the participant, the therapist explores in more depth the factors revealed in screening, and they begin to brainstorm a list of possible activities and routines to increase PA/ decrease sedentary behavior within the participant's preferences and opportunities in the home and community environment. The therapist promotes consideration of new activities, existing activities that might be modified or increased, and ways to “sneak in” PA, such as taking extra steps to reach a destination. The therapist also elicits overall goals and specific intentions regarding increased PA and reduction of sedentary time (
64
76
), expected outcomes (
64
), and other statements for later use as personalized motivational reminders, delivered by RehaBot. The capabilities of RehaBot are explained and demonstrated in Session 1 using sample screen shots, to help participants begin to consider how they might benefit from using the app. See
Figure 2
for sample screenshots.
Figure 2
As the list of planned activities takes shape, the therapist engages the participant in action planning, i.e., specific plans for when, where, how often, and (if applicable) with whom activities will occur during the week (
64
76
78
). Additional discussion involves potential barriers to activity completion, and possible ways of overcoming them. Obstacles may be overcome with various types of coping plans for one-time solutions (e.g., buying suitable shoes for walking or jogging; joining the nearby fitness center), or via just-in-time reminders framed as implementation intentions (
76
79
80
) (e.g., “If I don't feel like taking my walk, I’ll remind myself that….”) that may be accessed through RehaBot.
In Session 2, RehaBot is installed on the participant's phone, the participant is trained on all of its features, and the therapist and participant collaborate on personalizing the app. RehaBot is accessed via regular text-messaging, and engages in bi-directional communication with the user (see
Figure 2
). Therapists use a portal to enter participants' action plans, coping plans, goals, and other relevant data into the RehaBot app. Message timing is fully customizable. Participants select their preferred times for daily “good morning” and “good evening” check-in messages. They also determine how many activity reminder messages they wish to receive throughout the day and when those reminders should be delivered. Scheduled contacts come in the form of text message reminders to check your plan for the day, carry out a planned activity at a scheduled time, and report on your accomplishments. However, RehaBot is also available on-demand to serve as a “coach” to provide reminders, suggestions, feedback, reinforcement, coping plans, and personalized motivational messages. Activity reminder messages are worded using the participant's own language and selected activities. Participants also personalize the content of activity suggestions and the language and content of their coping plans. When an activity is logged as complete, RehaBot sends encouraging messages that reinforce the effort and tie the participant's accomplishments to progress towards a specific personal goal. Self-efficacy, thought to be a strong mediator of positive behavior change, is a particular target of intervention via specific positive feedback from both therapist and chatbot, and reminders of task mastery and overall progress (
81
).
In the phone sessions in weeks 3, 5, and 8, the participant's plan and their reactions to it are reviewed. Progress is reinforced, problems and obstacles are addressed, and any desired changes to the plan are instituted in the RehaBot portal. In the final telephone session, the therapist guides the participant in reflecting on their overall progress and their ability to overcome barriers to physical activity, while offering feedback on positive changes observed throughout the intervention. The participant continues to use RehaBot independently until Week 10, when they receive a letter reminding them of the upcoming telephone data collection and Actigraph wear period.
Participants randomized to RB for the FT phase receive a call notifying them that their RehaBot plan will remain in place for another 10 weeks. These participants are encouraged to use RehaBot to continue with their activity plans until the next evaluation period. Those randomized to No Tx are reminded of the final evaluation in 10 weeks and encouraged to keep up their PA plans. Neither FT condition includes any further contact from the therapist, although we would respond to participants who contacted us regarding a technical problem with the app.
2.6 Data analysis
For the primary endpoint (
Hypothesis 1a
primary hypothesis
) and each of the secondary endpoints (
Hypothesis 1b
), the mean change from T1 to T2 in the IT group will be compared to the mean change from T1 to T2 in the WL group using the two-sided two-sample t-test with alpha = 0.05. The mean change in each group and the mean difference between changes in IT vs. WL group will be estimated with the corresponding 95% confidence interval. If the normal distribution assumption is not appropriate for patient-specific changes in one or both groups, then the two-sided two-sample Wilcoxon test will be used instead of the t-test. We will employ intent-to-treat for the
primary analysis
, and as such, we will make every attempt to collect T2 outcome data on all randomized participants regardless of treatment received. Per current recommendations (
82
84
), we will use multiple imputation to account for missing T2 data, and evaluate missingness assumptions (by comparing available data for participants with complete vs. missing T2). If the assumption of the data being
missing at random
is not appropriate, the imputations will be performed using the methods specifically developed for data
missing not at random
85
). As a
secondary analysis
we will perform a complete-case analysis with dropouts excluded. With the proposed sample size of 35 subjects per arm and assuming up to 15% loss to follow-up, we expect to have at least 30 subjects per arm available for analysis. The sample size of 30 subjects per arm provides 81% power to detect the mean difference between changes in IT vs. WL arms corresponding to the effect size of 0.75 (effect size for the primary endpoint as reported in Clanchy et al. (
24
) using the two-sided two-sample t-test with alpha 0.05.
For
Hypothesis 2a
, the primary endpoint is the change in average accelerometer activity counts/ day from post-intervention timepoint (T2 for IT participants, T2b for WL) to the follow-up endpoint, T3, 10 weeks later. The subject-specific T2/T2b-T3 changes will be modeled in an ANCOVA model as dependent on group (RB vs. No Tx) and the average accelerometer activity counts/day during the A phase (from timepoint T1 to post-intervention timepoint T2/T2b). The interaction between group and T1-T2(b) changes will be considered and retained in the model, if significant. If the interaction is not significant, Hypothesis 2a will be tested by comparing the mean change in RB vs. No Tx group using the model-based two-sided two-sample t-test with alpha 0.05. In the case of the main effects model (no significant interaction), this is equivalent to testing the main effect of RB (vs. No Tx) as the difference between intercepts of the regression lines with T1-T2(b) change as a predictor. A significant interaction would imply that the effect of RB (vs. No Tx) depends on the amount of change achieved during the A phase, and the test of interaction corresponds to comparing the slopes of the T1-T2(b) change regression lines between RB and No Tx groups. In the case of a significant interaction, the difference between RB and No Tx groups will be quantified in terms of the difference between the T1-T2(b) change regression slopes, and the significance (
-value) for that difference is the same as the significance (
-value) of the interaction. It is not expected that this interaction is important, and the study is not powered to detect such interaction. The secondary outcome measures (
Hypothesis 2b)
will be analyzed using the same approach.
We will report AEs and SAEs descriptively by treatment arm, including the number and percentage of participants experiencing at least one AE/SAE, as well as the total number of events by category. All AEs will be categorized by severity, relatedness to the intervention, and resolution status.
With regard to power, in the study of Clanchy et al. (
24
), participants in the active intervention group lost a mean of 1.7 standard deviations in average activity counts per day between their post-treatment and follow-up assessments, without any treatment during this time (comparable to our No Tx condition). We hypothesize that the loss in activity in the RB (treated) group in our study will be reduced by at least 50% of this value, an expected difference in effect size between RB and No Tx groups of 0.85. We make the conservative assumption of up to 15% additional attrition during the FT phase, leaving
= 46. With this sample size we will have 80% power to detect a difference in effect size of at least.85 between groups, using the two-sided two-sample t-test with alpha 0.05.
The analyses of predictors of treatment response will be exploratory, as the large number of predictors of possible interest will preclude hypothesis-driven methods. We will consider the use of analysis techniques such as model averaging (
86
87
a method that allows for more robust conclusions about important candidate predictors when the possible predictors are numerous and the sample is relatively small, and when different variable selection methods may result in different and possibly suboptimal models.
3 Anticipated results
In this manuscript we describe a randomized controlled trial of a novel intervention intended to promote PA in individuals with chronic msTBI, a population at risk for reduced PA and increased sedentary behavior. The GetUp&Go intervention includes a combination of features that are unique in the msTBI literature to date: Treatment ingredients that are based in a strong theoretical model and vetted by people with lived experience of msTBI; a standardized treatment manual that also allows for individualized PA plans; remote treatment delivery, with a chatbot to supplement and support increased PA; and objectively measured PA as a primary outcome, with a wide variety of secondary outcome measures for assessment of the broader impact of the intervention. In addition, the post-treatment follow-up phase is designed to evaluate the impact of continued chatbot support on maintenance of treatment gains. If use of the chatbot results in less diminution of gains, as we have hypothesized, this could offer one type of solution to the problem noted in prior studies: that participants with msTBI tend not to persist with successful PA programs once therapeutic support is withdrawn.
Whether or not the improvements in PA and the secondary outcomes occur as hypothesized, we anticipate that our exploratory analyses will provide valuable information on the predictive factors of treatment success. This information, enhanced with the qualitative data supplied in debriefing interviews of study participants, will help enable the refinement of the protocol for future research.
3.1 Limitations
The sample population for this trial is limited to persons with chronic msTBI who are living in the community, and who are able to walk without the assistance of another person. Our findings may not generalize to those with mild or acute TBI, institutionalized people, or those who are non-ambulatory.
4 Discussion
The conclusions from this trial must, of course, await the completion of data collection and analysis. However, we believe that PA enhancement provides a valuable and under-studied direction for msTBI. People with chronic msTBI experience a variety of challenges to both mental and physical well-being; and there is unassailable evidence that increasing PA leads to a broad array of improvements in both physical and mental health. The dose-response relationship between PA increase and health benefit suggests that people who are unable to achieve published guidelines for moderate-vigorous PA may still enjoy the fruits of more modest efforts. It is known that PA is valued by people with msTBI and that they are interested in finding ways to become more active; and PA programs may readily be tailored to individual abilities, preferences, and social/ environmental circumstances. Moreover, treatment programs that incorporate theoretically motivated and empirically validated behavior change ingredients may help to circumvent difficulties with initiation, persistence, and memory that can interfere with the ability to develop and maintain enhanced PA habits and routines following msTBI.
Regardless of outcome, this trial will advance the field of neurorehabilitation by addressing a critical gap identified in prior research: the lack of RCTs of theoretically motivated interventions to promote PA for those with msTBI. The GetUp&Go intervention incorporates evidence-based behavior change techniques shown to be effective in other populations, while systematically adapting them to address the specific cognitive, emotional, and physical challenges faced by people with chronic msTBI. In addition, this trial will generate critical feasibility data for delivering behavioral interventions remotely to people with msTBI—a population that faces significant barriers to accessing in-person rehabilitation services due to transportation limitations, cognitive and physical problems, and geographic distance from specialized providers. The integration of mobile health technology represents an innovative approach to overcoming these barriers. Our findings relevant to feasibility, adherence, and user experience will provide valuable insights for refining remote delivery approaches, further adding to the evidence for telehealth interventions for people with chronic msTBI (
88
).
5 Recommendations
The design of this trial illustrates several features that are empirically supported yet too little employed in studies of msTBI rehabilitation. For future trials, we encourage the use of well-studied treatment ingredients that are known to enhance behavior change in the domain of physical activity. We also recommend continued exploration of remote interventions, particularly those capitalizing on SMS and mobile apps with demonstrated feasibility and acceptability in this population. Finally, we strongly recommend the inclusion of persons with lived experience of msTBI in the design and implementation of all treatment studies.
Statements
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
Author contributions
TH: Writing – review & editing, Conceptualization, Methodology, Writing – original draft. MV: Resources, Data curation, Supervision, Methodology, Writing – review & editing, Conceptualization. LK: Methodology, Supervision, Conceptualization, Project administration, Writing – review & editing. IC: Writing – original draft, Data curation, Conceptualization, Methodology, Writing – review & editing. AR: Supervision, Funding acquisition, Conceptualization, Writing – review & editing, Methodology, Writing – original draft.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This work was funded by the National Institute on Disability, Independent Living, and Rehabilitation Research (Grant #90DPTB0001). The sponsor had no role in the preparation of this manuscript.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher’s note
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References
1.
Bull
FC
Al-Ansari
SS
Biddle
Borodulin
Buman
MP
Cardon
et al
World health organization 2020 guidelines on physical activity and sedentary behaviour
Br J Sports Med
. (
2020
54
24
):
1451
62
10.1136/bjsports-2020-102955
Pubmed Abstract
CrossRef
Google Scholar
2.
Piercy
KL
Troiano
RP
Ballard
RM
Carlson
SA
Fulton
JE
Galuska
DA
et al
The physical activity guidelines for Americans
JAMA
. (
2018
320
19
):
2020
10.1001/jama.2018.14854
Pubmed Abstract
CrossRef
Google Scholar
3.
Chan
JSY
Liu
Liang
Deng
Wu
Yan
JH
Special issue - therapeutic benefits of physical activity for mood: a systematic review on the effects of exercise intensity, duration, and modality
J Psychol
. (
2019
153
):
102
25
10.1080/00223980.2018.1470487
Pubmed Abstract
CrossRef
Google Scholar
4.
Karamian
Lucke-Wold
Seifi
Prevalence of traumatic brain injury in the general adult population of the USA: a meta-analysis
Neuroepidemiology
. (
2025
59
):
558
67
10.1159/000540676
Pubmed Abstract
CrossRef
Google Scholar
5.
Corrigan
JD
Hammond
FM
Traumatic brain injury as a chronic health condition
Arch Phys Med Rehabil
. (
2013
94
):
1199
201
10.1016/j.apmr.2013.01.023
Pubmed Abstract
CrossRef
Google Scholar
6.
Fleming
Braithwaite
Gustafsson
Griffin
Collier
AM
Fletcher
Participation in leisure activities during brain injury rehabilitation
Brain Inj
. (
2011
25
):
806
18
10.3109/02699052.2011.585508
Pubmed Abstract
CrossRef
Google Scholar
7.
Goverover
Genova
Smith
Chiaravalloti
Lengenfelder
Changes in activity participation following traumatic brain injury
Neuropsychol Rehabil
. (
2017
27
):
472
85
10.1080/09602011.2016.1168746
Pubmed Abstract
CrossRef
Google Scholar
8.
Wise
EK
Mathews-Dalton
Dikmen
Temkin
Machamer
Bell
et al
Impact of traumatic brain injury on participation in leisure activities
Arch Phys Med Rehabil
. (
2010
91
):
1357
62
10.1016/j.apmr.2010.06.009
Pubmed Abstract
CrossRef
Google Scholar
9.
Crenn
Hamchaoui
Bourget-Massari
Hanachi
Melchior
JC
Azouvi
Changes in weight after traumatic brain injury in adult patients: a longitudinal study
Clin Nutr
. (
2014
33
):
348
53
10.1016/j.clnu.2013.06.003
Pubmed Abstract
CrossRef
Google Scholar
10.
Izzy
Chen
PM
Tahir
Grashow
Radmanesh
Cote
DJ
et al
Association of traumatic brain injury with the risk of developing chronic cardiovascular, endocrine, neurological, and psychiatric disorders
JAMA Netw Open
. (
2022
):
e229478
10.1001/jamanetworkopen.2022.9478
Pubmed Abstract
CrossRef
Google Scholar
11.
Self
Driver
Stevens
Warren
AM
Physical activity experiences of individuals living with a traumatic brain injury: a qualitative research exploration
Adapt Phys Act Q
. (
2013
30
):
20
39
10.1123/apaq.30.1.20
CrossRef
Google Scholar
12.
Törnbom
Sunnerhagen
KS
Danielsson
Perceptions of physical activity and walking in an early stage after stroke or acquired brain injury
PLoS One
. (
2017
12
):
e0173463
10.1371/journal.pone.0173463
CrossRef
Google Scholar
13.
Reavenall
Blake
Determinants of physical activity participation following traumatic brain injury
Int J Ther Rehabil
. (
2010
17
360
10.12968/ijtr.2010.17.7.48893
CrossRef
Google Scholar
14.
Driver
Ede
Dodd
Stevens
Warren
AM
What barriers to physical activity do individuals with a recent brain injury face?
Disabil Health J
. (
2012
):
117
25
10.1016/j.dhjo.2011.11.002
Pubmed Abstract
CrossRef
Google Scholar
15.
Quilico
EL
Wilkinson
Bédard
Duncan
LR
Sweet
SN
Swaine
BR
et al
COVID-19’s impact on a community-based physical activity program for adults with moderate-to-severe TBI
Dis Rehabil
. (
2024
46
10
):
2014
22
10.1080/09638288.2023.2212180
CrossRef
Google Scholar
16.
Jones
TM
Dean
CM
Dear
BF
Hush
JM
Titov
An internet survey of the characteristics and physical activity of community-dwelling Australian adults with acquired brain injury: exploring interest in an internet-delivered self-management program focused on physical activity
Disabil Health J
. (
2016
):
54
63
10.1016/j.dhjo.2015.08.004
Pubmed Abstract
CrossRef
Google Scholar
17.
Williams
Weragoda
Paterson
Clark
Cardiovascular fitness is unrelated to mobility limitations in ambulant people with traumatic brain injury
J Head Trauma Rehabil
. (
2013
28
):
E1
10.1097/HTR.0b013e318279536d
Pubmed Abstract
CrossRef
Google Scholar
18.
Devine
JM
Zafonte
RD
Physical exercise and cognitive recovery in acquired brain injury: a review of the literature
PM&R
. (
2009
):
560
75
10.1016/j.pmrj.2009.03.015
CrossRef
Google Scholar
19.
Chin
LM
Keyser
RE
Dsurney
Chan
Improved cognitive performance following aerobic exercise training in people with traumatic brain injury
Arch Phys Med Rehabil
. (
2015
96
):
754
10.1016/j.apmr.2014.11.009
Pubmed Abstract
CrossRef
Google Scholar
20.
Morris
TP
Tormos Muñoz
JM
Cattaneo
Solana-Sánchez
Bartrés-Faz
Pascual-Leone
Traumatic brain injury modifies the relationship between physical activity and global and cognitive health: results from the Barcelona brain health initiative
Front Behav Neurosci
. (
2019
13
135
10.3389/fnbeh.2019.00135
Pubmed Abstract
CrossRef
Google Scholar
21.
Perry
SA
Coetzer
Saville
CWN
The effectiveness of physical exercise as an intervention to reduce depressive symptoms following traumatic brain injury: a meta-analysis and systematic review
Neuropsychol Rehabil
. (
2020
30
):
564
78
10.1080/09602011.2018.1469417
Pubmed Abstract
CrossRef
Google Scholar
22.
Mossberg
KA
Amonette
WE
Masel
BE
Endurance training and cardiorespiratory conditioning after traumatic brain injury
J Head Trauma Rehabil
. (
2010
25
):
173
83
10.1097/HTR.0b013e3181dc98ff
Pubmed Abstract
CrossRef
Google Scholar
23.
Hassett
Moseley
AM
Harmer
AR
Fitness training for cardiorespiratory conditioning after traumatic brain injury
Cochrane Database Syst Rev
. (
2017
12
12
):
CD006123
(pages
64
).
10.1002/14651858.CD006123.pub3
CrossRef
Google Scholar
24.
Clanchy
KM
Tweedy
SM
Trost
SG
Evaluation of a physical activity intervention for adults with brain impairment: a controlled clinical trial
Neurorehabil Neural Repair
. (
2016
30
):
854
65
10.1177/1545968316632059
Pubmed Abstract
CrossRef
Google Scholar
25.
Clanchy
KM
Tweedy
SM
Trost
SG
The adapted physical activity program: a theory-driven, evidence-based physical activity intervention for people with brain impairment
Brain Impair
. (
2019
20
):
81
95
10.1017/BrImp.2018.16
CrossRef
Google Scholar
26.
Johnson
Williams
Sherrington
Pilli
Chagpar
Auchettl
et al
The effect of physical activity on health outcomes in people with moderate-to-severe traumatic brain injury: a rapid systematic review with meta-analysis
BMC Public Health
. (
2023
23
):
63
10.1186/s12889-022-14935-7
Pubmed Abstract
CrossRef
Google Scholar
27.
Michie
van Stralen
MM
West
The behaviour change wheel: a new method for characterising and designing behaviour change interventions
Implement Sci iS
. (
2011
42
10.1186/1748-5908-6-42
Pubmed Abstract
CrossRef
Google Scholar
28.
Rhodes
RE
Cox
Sayar
What predicts the physical activity intention–behavior gap? A systematic review
Ann Behav Med
. (
2022
56
):
20
10.1093/abm/kaab044
Pubmed Abstract
CrossRef
Google Scholar
29.
Bohlen
LC
Michie
de Bruin
Rothman
AJ
Kelly
MP
Groarke
HNK
et al
Do combinations of behavior change techniques that occur frequently in interventions reflect underlying theory?
Ann Behav Med
. (
2020
54
11
):
827
42
10.1093/abm/kaaa078
Pubmed Abstract
CrossRef
Google Scholar
30.
Connell
LE
Carey
RN
de Bruin
Rothman
AJ
Johnston
Kelly
MP
et al
Links between behavior change techniques and mechanisms of action: an expert consensus study
Ann Behav Med
. (
2019
53
):
708
20
10.1093/abm/kay082
Pubmed Abstract
CrossRef
Google Scholar
31.
Johnston
Carey
RN
Bohlen
LEC
Johnston
DW
Rothman
AJ
de Bruin
et al
Development of an online tool for linking behavior change techniques and mechanisms of action based on triangulation of findings from literature synthesis and expert consensus
Transl Behav Med
. (
2021
11
):
1049
65
10.1093/tbm/ibaa050
Pubmed Abstract
CrossRef
Google Scholar
32.
Michie
Carey
RN
Johnston
Rothman
AJ
de Bruin
Kelly
MP
et al
From theory-inspired to theory-based interventions: a protocol for developing and testing a methodology for linking behaviour change techniques to theoretical mechanisms of action
Ann Behav Med
. (
2018
52
):
501
12
10.1007/s12160-016-9816-6
Pubmed Abstract
CrossRef
Google Scholar
33.
Michie
Wood
CE
Johnston
Abraham
Francis
JJ
Hardeman
Behaviour change techniques: the development and evaluation of a taxonomic method for reporting and describing behaviour change interventions (a suite of five studies involving consensus methods, randomised controlled trials and analysis of qualitative data)
Health Technol Assess
. (
2015
19
99
):
10.3310/hta19990
CrossRef
Google Scholar
34.
Ntoumanis
Thørgersen-Ntoumani
Quested
Chatzisarantis
Theoretical approaches to physical activity promotion.
In
Oxford Research Encyclopedia of Psychology.
Oxford University Press
2018
).
Available online at:
Google Scholar
35.
Warburton
DER
Bredin
SSD
Health benefits of physical activity: a systematic review of current systematic reviews
Curr Opin Cardiol
. (
2017
32
):
541
56
10.1097/HCO.0000000000000437
Pubmed Abstract
CrossRef
Google Scholar
36.
King
AC
Whitt-Glover
MC
Marquez
DX
Buman
MP
Napolitano
MA
Jakicic
et al
Physical activity promotion: highlights from the 2018 physical activity guidelines advisory committee systematic review
Med Sci Sports Exerc
. (
2019
51
):
1340
53
10.1249/MSS.0000000000001945
Pubmed Abstract
CrossRef
Google Scholar
37.
Smith
DM
Duque
Huffman
JC
Healy
BC
Celano
CM
Text message interventions for physical activity: a systematic review and meta-analysis
Am J Prev Med
. (
2020
58
):
142
51
10.1016/j.amepre.2019.08.014
Pubmed Abstract
CrossRef
Google Scholar
38.
Bernstein
EE
Wolfe
EC
Huguenel
BM
Wilhelm
Lessons and untapped potential of smartphone-based physical activity interventions for mental health: narrative review
JMIR Mhealth Uhealth
. (
2024
12
e45860
10.2196/45860
Pubmed Abstract
CrossRef
Google Scholar
39.
Bell
KR
Temkin
NR
Esselman
PC
Doctor
JN
Bombardier
CH
Fraser
RT
et al
The effect of a scheduled telephone intervention on outcome after moderate to severe traumatic brain injury: a randomized trial
Arch Phys Med Rehabil
. (
2005
86
):
851
10.1016/j.apmr.2004.09.015
Pubmed Abstract
CrossRef
Google Scholar
40.
Fann
JR
Bombardier
CH
Vannoy
Dyer
Ludman
Dikmen
et al
Telephone and in-person cognitive behavioral therapy for Major depression after traumatic brain injury: a randomized controlled trial
J Neurotrauma
. (
2015
32
):
45
57
10.1089/neu.2014.3423
Pubmed Abstract
CrossRef
Google Scholar
41.
Ownsworth
Arnautovska
Beadle
Shum
DHK
Moyle
Efficacy of telerehabilitation for adults with traumatic brain injury: a systematic review
J Head Trauma Rehabil
. (
2018
33
):
E33
10.1097/HTR.0000000000000350
Pubmed Abstract
CrossRef
Google Scholar
42.
Juengst
SB
Hart
Sander
AM
Nalder
EJ
Pappadis
MR
Mobile health interventions for traumatic brain injuries
Curr Phys Med Rehabil Rep
. (
2019
):
341
56
10.1007/s40141-019-00240-9
CrossRef
Google Scholar
43.
Juengst
SB
Terhorst
Nabasny
Wallace
Weaver
JA
Osborne
CL
et al
Use of mHealth technology for patient-reported outcomes in community-dwelling adults with acquired brain injuries: a scoping review
Int J Environ Res Public Health
. (
2021
18
):
2173
10.3390/ijerph18042173
Pubmed Abstract
CrossRef
Google Scholar
44.
Rabinowitz
AR
Collier
Vaccaro
Wingfield
Development of RehaBot-A conversational agent for promoting rewarding activities in users with traumatic brain injury
J Head Trauma Rehabil
. (
2022
37
):
144
51
10.1097/HTR.0000000000000770
Pubmed Abstract
CrossRef
Google Scholar
45.
Prince
SA
Adamo
KB
Hamel
ME
Hardt
Connor Gorber
Tremblay
M.
A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review
Int J Behav Nutr Phys Act
2008
56
10.1186/1479-5868-5-56
Pubmed Abstract
CrossRef
Google Scholar
46.
Pawlowski
Dixon-Ibarra
Driver
Review of the Status of physical activity research for individuals with traumatic brain injury
Arch Phys Med Rehabil
. (
2013
94
):
1184
10.1016/j.apmr.2013.01.005
Pubmed Abstract
CrossRef
Google Scholar
47.
Pradhan
Esterov
Driver
Whyte
Bell
KR
Barber
et al
Predictors of physical activity one year after moderate to severe traumatic brain injury
J Head Trauma Rehabil
. (
2025
40
):
E54
65
10.1097/HTR.0000000000000966
Pubmed Abstract
CrossRef
Google Scholar
48.
Rothman
AJ
Toward a theory-based analysis of behavioral maintenance
Health Psychol
. (
2000
19
1S
):
64
10.1037/0278-6133.19.suppl1.64
Pubmed Abstract
CrossRef
Google Scholar
49.
Wilson
JT
Pettigrew
LE
Teasdale
GM
Structured interviews for the Glasgow outcome scale and the extended Glasgow outcome scale: guidelines for their use
J Neurotrauma
. (
1998
15
):
573
85
10.1089/neu.1998.15.573
Pubmed Abstract
CrossRef
Google Scholar
50.
Kaushal
Rhodes
RE
Spence
JC
Meldrum
JT
Increasing physical activity through principles of habit formation in new gym members: a randomized controlled trial
Ann Behav Med Publ Soc Behav Med
. (
2017
51
):
578
86
10.1007/s12160-017-9881-5
CrossRef
Google Scholar
51.
Sheehan
DV
Lecrubier
Sheehan
KH
Amorim
Janavs
Weiller
et al
The mini-international neuropsychiatric interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10
J Clin Psychiatry
. (
1998
59
Suppl 20
):
22
33
quiz 34–57
Pubmed Abstract
Google Scholar
52.
Bjureberg
Dahlin
Carlborg
Edberg
Haglund
Runeson
Columbia-Suicide Severity rating scale screen version: initial screening for suicide risk in a psychiatric emergency department
Psychol Med
. (
2021
52
16
):
10.1017/S0033291721000751
Pubmed Abstract
CrossRef
Google Scholar
53.
Godin
The Godin-Shephard leisure-time physical activity questionnaire
Health Fit J Can
. (
2011
):
18
22
10.14288/hfjc.v4i1.82
CrossRef
Google Scholar
54.
Hart
Dijkers
Whyte
Braden
Trott
Fraser
Vocational interventions and supports following job placement for persons with traumatic brain injury
J Vocat Rehabil
. (
2010
32
):
135
50
10.3233/JVR-2010-0505
CrossRef
Google Scholar
55.
Chomistek
AK
Yuan
Matthews
CE
Troiano
RP
Bowles
HR
Rood
et al
Physical activity assessment with the ActiGraph GT3X and doubly labeled water
Med Sci Sports Exerc
. (
2017
49
):
1935
44
10.1249/MSS.0000000000001299
Pubmed Abstract
CrossRef
Google Scholar
56.
Jones
TM
Dear
BF
Hush
JM
Titov
Dean
CM
Mymoves program: feasibility and acceptability study of a remotely delivered self-management program for increasing physical activity among adults with acquired brain injury living in the community
Phys Ther
. (
2016
96
12
):
1982
93
10.2522/ptj.20160028
Pubmed Abstract
CrossRef
Google Scholar
57.
Loprinzi
PD
Sheffield
Tyo
BM
Fittipaldi-Wert
Accelerometer-determined physical activity, mobility disability, and health
Disabil Health J
. (
2014
):
419
25
10.1016/j.dhjo.2014.05.005
Pubmed Abstract
CrossRef
Google Scholar
58.
Rey
L’examen Clinique En Psychologie
Paris
Presses Universitairies de France
1964
).
Google Scholar
59.
Reitan
RM
Wolfson
The Halstead-Reitan Neuropsychological Test Battery
Bloomington, IN
Neuropsychology Press
1988
).
Google Scholar
60.
Burgess
PW
Shallice
The Hayling and Brixton Tests.
Thurston, UK
Thames Valley Test Company
1997
). Available online at:
(Accessed January 15, 2026)
Google Scholar
61.
Smith
Symbol digit modalities test (SDMT). Manual (Revised). Western Psychological Services
. (
1982
).
Google Scholar
62.
Costa
PT
Jr
McCrae
RR
The revised NEO personality inventory (NEO-PI-R)
. In:
Boyle
GJ
Matthews
Saklofske
DH
, editors.
The SAGE Handbook of Personality Theory and Assessment, Vol 2: Personality Measurement and Testing
London
Sage Publications, Inc
2008
). p.
179
98
10.4135/9781849200479.n9
CrossRef
Google Scholar
63.
Driver
Social support and the physical activity behaviours of people with a brain injury
Brain Inj
. (
2005
19
13
):
1067
75
10.1080/02699050500149338
Pubmed Abstract
CrossRef
Google Scholar
64.
Schwarzer
Lippke
Luszczynska
Mechanisms of health behavior change in persons with chronic illness or disability: the health action process approach (HAPA)
Rehabil Psychol
. (
2011
56
):
161
70
10.1037/a0024509
Pubmed Abstract
CrossRef
Google Scholar
65.
Wilson
PM
Rodgers
WM
Fraser
SN
Examining the psychometric properties of the behavioral regulation in exercise questionnaire
Meas Phys Educ Exerc Sci
. (
2002
):
21
10.1207/S15327841MPEE0601_1
CrossRef
Google Scholar
66.
Sheeran
Maki
Montanaro
Avishai-Yitshak
Bryan
Klein
WMP
et al
The impact of changing attitudes, norms, and self-efficacy on health-related intentions and behavior: a meta-analysis
Health Psychol
. (
2016
35
11
):
1178
88
10.1037/hea0000387
Pubmed Abstract
CrossRef
Google Scholar
67.
Ezeugwu
VE
Manns
PJ
Using intervention mapping to develop and implement a home-based sedentary behavior change intervention after stroke
Transl Behav Med
. (
2020
10
):
87
95
10.1093/tbm/iby128
Pubmed Abstract
CrossRef
Google Scholar
68.
Buchan
DS
Ollis
Thomas
NE
Baker
JS
Physical activity behaviour: an overview of current and emergent theoretical practices
J Obes
. (
2012
2012
546459
10.1155/2012/546459
Pubmed Abstract
CrossRef
Google Scholar
69.
Derogatis
LR
Brief Symptom Inventory 18
Minneapolis, MN
National Computer Systems
2000
).
Google Scholar
70.
Learmonth
YC
Dlugonski
Pilutti
LA
Sandroff
BM
Klaren
Motl
RW
Psychometric properties of the fatigue severity scale and the modified fatigue impact scale
J Neurol Sci
. (
2013
331
):
102
10.1016/j.jns.2013.05.023
Pubmed Abstract
CrossRef
Google Scholar
71.
Buysse
Reynolds
Monk
Berman
Kupfer
The Pittsburgh sleep quality Index (PSQI): a new instrument for psychiatric research and practice
Psychiatry Res
. (
1989
28
):
193
213
10.1016/0165-1781(89)90047-4
Pubmed Abstract
CrossRef
Google Scholar
72.
dela Cruz
AM
Bernstein
IH
Greer
TL
Walker
Rethorst
CD
Grannemann
et al
Self-rated measure of pain frequency, intensity, and burden: psychometric properties of a new instrument for the assessment of pain
J Psychiatr Res
. (
2014
59
155
60
10.1016/j.jpsychires.2014.08.003
Pubmed Abstract
CrossRef
Google Scholar
73.
von Steinbüchel
Wilson
Gibbons
Hawthorne
Höfer
Schmidt
et al
Quality of life after brain injury (QOLIBRI): scale development and metric properties
J Neurotrauma
. (
2010
27
):
1167
85
10.1089/neu.2009.1076
CrossRef
Google Scholar
74.
Stefani
Mascherini
Galanti
Aerobic threshold for exercise prescription
Int J Clin Med
. (
2010
01
01
):
10.4236/ijcm.2010.11002
CrossRef
Google Scholar
75.
Farrar
JT
Young
JP
LaMoreaux
Werth
JL
Poole
MR
Clinical importance of changes in chronic pain intensity measured on an 11-point numerical pain rating scale
Pain
. (
2001
94
):
149
58
10.1016/S0304-3959(01)00349-9
Pubmed Abstract
CrossRef
Google Scholar
76.
Reuter
Ziegelmann
JP
Lippke
Schwarzer
Long-term relations between intentions, planning, and exercise: a 3-year longitudinal study after orthopedic rehabilitation
Rehabil Psychol
. (
2009
54
):
363
71
10.1037/a0017830
Pubmed Abstract
CrossRef
Google Scholar
77.
Lally
Gardner
Promoting habit formation
Health Psychol Rev
. (
2013
sup1
):
S137
58
10.1080/17437199.2011.603640
CrossRef
Google Scholar
78.
Sniehotta
FF
Scholz
Schwarzer
Action plans and coping plans for physical exercise: a longitudinal intervention study in cardiac rehabilitation
Br J Health Psychol
. (
2006
11
):
23
37
10.1348/135910705X43804
Pubmed Abstract
CrossRef
Google Scholar
79.
Sheeran
Gollwitzer
PM
Bargh
JA
Nonconscious processes and health
Health Psychol
. (
2013
32
):
460
73
10.1037/a0029203
Pubmed Abstract
CrossRef
Google Scholar
80.
Luszczynska
An implementation intentions intervention, the use of a planning strategy, and physical activity after myocardial infarction
Soc Sci Med
. (
2006
62
):
900
10.1016/j.socscimed.2005.06.043
Pubmed Abstract
CrossRef
Google Scholar
81.
Ashford
Edmunds
French
DP
What is the best way to change self-efficacy to promote lifestyle and recreational physical activity? A systematic review with meta-analysis
Br J Health Psychol
. (
2010
15
Pt 2
):
265
88
10.1348/135910709X461752
Pubmed Abstract
CrossRef
Google Scholar
82.
White
IR
Carpenter
Horton
NJ
Including all individuals is not enough: lessons for intention-to-treat analysis
Clin Trials Lond Engl
. (
2012
):
396
407
10.1177/1740774512450098
CrossRef
Google Scholar
83.
Chakraborty
Gu
A Mixed Model Approach for Intent-to-Treat Analysis in Longitudinal Clinical Trials with Missing Values. Published online 2009
Available online at:
(Accessed January 15, 2026)
Google Scholar
84.
Sidi
Harel
The treatment of incomplete data: reporting, analysis, reproducibility, and replicability
Soc Sci Med
. (
2018
209
169
73
10.1016/j.socscimed.2018.05.037
Pubmed Abstract
CrossRef
Google Scholar
85.
van Buuren
Flexible Imputation of Missing Data, Second Edition
Boca Raton, FL
CRC Press
2018
).
Google Scholar
86.
Buckland
ST
Burnham
KP
Augustin
NH
Model selection: an integral part of inference
Biometrics
1997
53
):
603
18
10.2307/2533961
CrossRef
Google Scholar
87.
Burnham
Anderson
Model Selection and Multimodel Inference
New York
Springer Verlag
Published online
2002
).
Google Scholar
88.
Suarilah
Zulkarnain
Saragih
ID
Lee
BO
Effectiveness of telehealth interventions among traumatic brain injury survivors: a systematic review and meta-analysis
J Telemed Telecare
. (
2024
30
):
781
94
10.1177/1357633X221102264
Pubmed Abstract
CrossRef
Google Scholar
Summary
Keywords
intervention
mobile health
physical activity
randomized controlled trial
traumatic brain injuries
Citation
Hart T, Vaccaro M, Krasucki L, Chervoneva I and Rabinowitz A (2026)
Increasing physical activity in moderate-severe traumatic brain injury: protocol for a two-stage randomized controlled trial of a remote, mHealth-enhanced intervention
Front. Rehabil. Sci.
7:1656326. doi:
10.3389/fresc.2026.1656326
Received
29 June 2025
Revised
22 December 2025
Accepted
08 January 2026
Published
02 February 2026
Volume
7 - 2026
Edited by
Eveline Graf
, ZHAW Zurich University of Applied Sciences, Switzerland
Reviewed by
Rui Viana
, Fernando Pessoa Foundation, Portugal
Anne-Kathrin Rausch
, Zurich University of Applied Sciences, Switzerland
Updates
© 2026 Hart, Vaccaro, Krasucki, Chervoneva and Rabinowitz.
This is an open-access article distributed under the terms of the
Creative Commons Attribution License (CC BY)
. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Correspondence:
Tessa Hart
tessa.hart@jefferson.edu
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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