Tied by tiredness, a blended care intervention for fatigue after acquired brain injury: study protocol for a multicentre prospective non-randomized patient-preference trial into patient-related outcomes and costs

Abstract

Background

Despite the high prevalence of fatigue after acquired brain injury and the major impact of fatigue on people’s lives, evidence-based interventions are scarce. We developed a new personalized blended care intervention, Tied by Tiredness, which was found to be feasible in a pilot study. In this paper, we present the design of a study of patient-related outcomes and the societal costs of the intervention.

Methods

This study is a multicentre prospective nonrandomized patient preference trial with baseline (T0), posttreatment (T1), 3-month (T2) and 6-month (T3) follow-up data. The participants will be 45 adults who have experienced brain injury (stroke or traumatic brain injury) and are seeking treatment for fatigue symptoms. The participants will choose whether to receive Tied by Tiredness or treatment as usual. The Tied by Tiredness intervention consists of a 6-week blended care treatment, which combines experience sampling methodology (participants answer momentary questions about fatigue and their daily lives sent via a phone application) with personalized face-to-face feedback by a health care professional. Treatment as usual entails occupational therapy sessions once a week for 6–8 weeks. Measures of fatigue and secondary outcomes (mood, cognitive complaints, participation, and quality of life) will be collected via questionnaires at each time point. To investigate the changes in fatigue severity from pre- to postintervention and follow-up, a linear mixed-effects model with fatigue severity score (FSS) as the dependent variable and time point (T0, T1, T2, T3) as a within-subject factor will be used.

In addition, a cost analysis will be performed from a societal perspective, including both direct medical costs (e.g., intervention costs) and societal costs (e.g., informal care, productivity losses).

Discussion

Fatigue after brain injury is multifactorial with high individual variability. We hypothesize that the personalized blended care intervention Tied by Tiredness may be an efficient and effective intervention to reduce fatigue and related problems

Trial registration

Clinical trial number: ID: NL-OMON21265; Overview of Medical Research in the Netherlands (OMON).

The trial was first registered in the Overview of Medical Research in the Netherlands (ID: NL-OMON21265) on May 31st, 2021, before recruitment started.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-026-05062-6.

Background

Fatigue ranks among the most prevalent consequences of acquired brain injury (ABI) (e.g., stroke or traumatic brain injury (TBI)) and has been associated with lower quality of life, poorer neurological recovery and a higher risk of mortality than without fatigue [1, 2]. For some individuals, fatigue is transient in nature, but for many others, it becomes a chronic health complaint, with the prevalence of fatigue after TBI and stroke decreasing from 47% after 2 days to 32% at 6 months post-injury [2, 3]. This is particularly problematic, as long-term fatigue symptoms can lead to difficulties in societal participation and increased medical and economic costs [4, 5].

To treat fatigue after ABI, there is no preferred evidence-based treatment. On the one hand, evidence supporting the effectiveness of interventions for treating or preventing fatigue is frequently inadequate or insufficient [6, 7]. On the other hand, fatigue after ABI is a complex symptom because many factors, such as premorbid vulnerability, injury-specific factors, and psychological, motivational, and context-specific factors, can influence the development and maintenance of fatigue after ABI (7). As such, the causes of fatigue after ABI are diverse and highly person specific, which calls for personalized fatigue treatment [8].

To this end, personalized feedback based on momentary (here-and-now) questions about fatigue and personal and environmental factors can be applied [9]. This can be accomplished via experience sampling methodology (ESM). ESM is a highly reliable momentary assessment method that provides insight into how people function in the flow of daily life [10, 11]. The three basic components of the ESM are (a) repeated (b) real-time measurements and (c) daily life contexts. Through an application installed on a smartphone, participants are asked to report their current symptoms, experiences, behaviour and context (activity, company, location) at different times throughout the day. Owing to the momentary nature of ESM assessments, revealing subtle patterns of symptoms unique to each individual who could otherwise be influenced by recall bias in standard retrospective questionnaires or traditional clinical interviews is possible [12, 13]. Preparatory work from our research team has shown that ESM is a feasible method for identifying brain injury in participants and that it is highly effective in identifying personalized symptom patterns in these populations [14, 15].

In the present study, we will investigate patient-related outcomes and the societal costs of the Tied by Tiredness intervention. The concept of the protocol was tested in a pilot study. The Tied by Tiredness intervention was shown to be feasible and usable for the treatment of fatigue after ABI [16]. In this blended care intervention, participants engage in six weeks of ESM data collection about fatigue and related factors, followed by a weekly face-to-face session with a therapist. The goal of these weekly sessions is to gain insight into daily fatigue patterns and factors related to fatigue and to implement cognitive and behavioural interventions in daily life targeted at the alleviation of fatigue and other symptoms.

We hypothesize that the Tied by Tiredness intervention will be associated with a clinically relevant improvement in fatigue symptoms from pre- to post-intervention. We will also assess whether the intervention is associated with a reduction in cognitive and emotional complaints and potential improvements in societal participation and quality of life. Furthermore, we will explore whether the blended care format is associated with lower intervention costs than is face-to-face care alone, and whether it is associated with a reduction in societal costs.

Objectives

Primary objective

To investigate the changes in fatigue severity of the combined ESM with personalised feedback intervention ‘Tied by Tiredness’ from pre to postintervention and follow-up.

Secondary objectives

To investigate whether Tied by Tiredness may be associated with improvements in fatigue symptoms, in fatigue subtypes, daily fatigue experiences, and cognitive and emotional complaints, as well as improvements in societal participation and quality of life from pre- to postintervention and follow-up.

To explore fatigue outcomes as measured by the Fatigue Severity Scale (FSS) of the Tied by Tiredness intervention in comparison to treatment as usual (TAU).

To explore the costs of the intervention in comparison to those of the TAU.

Methods/design

Design

This is a multicentre prospective nonrandomized patient preference trial. The participants will choose between the Tied by Tiredness and the TAU after the baseline assessment.

The TAU arm is included solely to capture patient treatment preference and to allow exploratory, descriptive comparisons of outcomes between patients who prefer the blended care intervention and those who prefer treatment as usual. The study is not powered for confirmatory between-group comparisons; such analyses are strictly exploratory and hypothesis-generating in nature.

The participants will be assessed at four different time points: baseline (T0), postintervention (T1), 3 months (T2) and 6 months post-intervention (T3). The study was approved by the Ethics Review Committee Psychology and Neuroscience (ERCPN) of Maastricht University (registration number ERCPN-256_104_08_2022) and the local ethics committees of the participating centres. The trial was first registered in the Overview of Medical Research in the Netherlands (ID: NL-OMON21265) on May 31st, 2021, before recruitment started.

The design of this study allows participants to choose their preferred treatment rather than being randomly assigned while still maintaining a prospective approach to data collection and analysis. This design is particularly useful in situations where patient preferences might influence the outcomes or adherence to the treatment protocol. It aims to enhance the external validity of a trial by reflecting real-world scenarios where participants have treatment preferences [17].

Participants

This study will include adults with ABI who are seeking treatment for fatigue in outpatient rehabilitation centers or occupational therapy practices. The goal of this study is to recruit 45 participants who will choose the Tied by Tiredness intervention from various medical and rehabilitation centers and private occupational therapist practices in the Netherlands. Participants may continue to receive usual care during the trial; however, concurrent psychological or behavioral treatments specifically targeting fatigue symptoms are not permitted. This restriction is necessary to ensure that any observed effects can be attributed to the study intervention rather than to parallel treatments addressing the same symptom domain.

Following power analysis, recruitment will be stopped when 45 participants will have chosen to follow the Tied by Tiredness intervention. The first participant was recruited in May 2023, and approximately 45% of the participants were recruited at the time of submission of this article. Table 1 displays the inclusion and exclusion criteria for the participants.

Table 1.

Participant inclusion and exclusion criteria

Inclusion Criteria	Exclusion Criteria
Stroke or TBI (ABI)	< 18 years old
Objectified by a physician/neurologist and/or neuropsychologist	Current diagnosis of depression or chronic fatigue syndrome
Starting outpatient rehabilitation or occupational therapy	Currently receiving cancer treatment
Referred for treatment of fatigue and score 4 or higher on the statement “I am easily fatigued and I am hindered by fatigue in daily life.” where 1 is ‘strongly disagree’, and 7 is ‘strongly agree’; The statement is asked by the clinician.
Good comprehension of Dutch, based on clinical judgment.
Capable of handling smartphone (intervention condition), based on clinical judgment and report of the participant.
Willing and be able to give informed consent

Power analysis for the primary outcome measure (Fatigue Severity Scale; FSS) was based on the expected within-subject change in fatigue from baseline (T0) to post-intervention (T1) within the intervention group. Assuming α = 0.05, power = 0.80, a small effect size (Cohen’s d = 0.29), four repeated measurements, and a within-subject correlation of 0.70, approximately 41 participants are required for analysis using a linear mixed-effects model. Assuming drop-outs, we will recruit 45 participants for the Tied by Tiredness intervention group. Since the trial is a patient-preference trial, some of our participants will receive TAU. Data from both groups were collected.

The sample size calculation was based on the primary confirmatory analysis: within-group changes in fatigue symptoms in the intervention arm. The TAU arm is not included in this calculation, as confirmatory between-group comparisons are not an aim of this study. Any between-group analyses will be exploratory.

Procedure

Eligible participants will be notified of the study by their therapist at the participating centers. They will then be asked if a member of the research team may contact them to ask if they want to participate. Researchers will send potential participants the information letter and schedule a baseline session with the participant at least 4 days later at either the participant’s home or the treating center (on the basis of participant preference). During the baseline session, a participants will first be asked to provide their informed consent, and will then complete a series of questionnaires. Subsequently, participants will inform the researcher of their choice of treatment. For participants who choose TAU, the baseline session will end at that point. In the Tied by Tiredness intervention group, the ESM question list will be presented in an app (M-path;https://m-path.io). During the baseline session, this app will be installed by the researcher on the participant’s smartphone followed by a practice session. Participants will then follow their chosen treatment (6 weeks for Tied by Tiredness versus 6–8 weeks for TAU). All questionnaires will be presented to participants at each time point. At baseline, demographic data and injury characteristics will be collected. No financial incentives will be given during the intervention phase. At the T2 and T3 follow-ups, participants will receive a shopping voucher worth 7.50 euros for their participation in each of the follow-up measurements. Figure 1 illustrates the study timeline and the measurements taken at each assessment point.

Fig. 1.

Flow diagram of the Tied by Tiredness study timeline

Interventions

Tied by tiredness intervention

The feasibility of the Tied by Tiredness intervention protocol has been piloted in a small sample of individuals with TBI or stroke treated by clinicians involved in multidisciplinary rehabilitation [16]. The results and participant feedback from this pilot study revealed that the 6-week intervention protocol is feasible and well received by end-users, including individuals with brain injury and therapists. During the intervention, participants will monitor their symptoms, behaviour and contextual information (e.g., location) in daily life via the m-Path app (https://m-path.io) installed on participants’ phones. The use of Experience Sampling Methodology (ESM) via apps has been used and validated in various clinical populations, including individuals with brain injury [18, 19]. During the intervention period, participants will collect ESM data for 3 days per week, receiving 10 notifications (beeps) to fill in the ESM questions on each of those days (this was increased from the eight notifications used in the pilot study to increase the potential for more responses). This number of data points allows detailed insight into diurnal symptom patterns even in the presence of missing data. The feasibility study revealed a 71% average response rate [19]. The minimum required response rate for ESM data has been estimated to be approximately 33% for the method to be reliable [20]. The beeps will be sent by default between 08:30 and 22:30, but the timings of this 14-hour period can be adjusted to suit the habitual sleep‒wake rhythm of individual participants. Notifications will be sent semi-randomly within time blocks of 90 min to guarantee a spread of responses throughout the day. The semi-random beep design is also used to prevent anticipatory behavior, which is likely when the timing of beeps is fixed. The 3 ESM days per week will include 2 weekdays and 1 weekend day. This will be Thursday, Friday and Saturday, or Sunday, Monday and Tuesday, on the basis of participant preference. The participants will be encouraged to select the group of days in which they most commonly experience fatigue. A weekend day is added to both options, on the basis of the pilot study, to capture more variation in daily activities.

With each notification, participants will be asked to complete a short self-report questionnaire (approximately 2 min). This questionnaire consists of 26 questions. The first eight questions measure positive and negative affect, e.g., “I feel cheerful” and “I feel anxious”. The subsequent questions cover current (general) fatigue, physical and mental fatigue, mood, physical well-being, location, and current activities. Participants will have 15 min to respond after each beep before the questionnaire is skipped. Most questions are statements that can be answered on a 7-point Likert scale, e.g., “I feel tired”; however, items such as current activity, e.g., “What are you doing?”, are presented in a multiple-choice format. An overview of the questions and answer options is shown in Appendix 1.

At the end of each intervention week, participants will meet with their therapist (i.e., occupational therapist, psychologist, or rehabilitation doctor) for a face-to-face feedback session. Feedback will be assisted by the m-Path website that accompanies the app. The website allows therapists to visually plot diurnal and weekly patterns within the ESM data, look at the average scores for different items, and determine whether there are any correlations between items (e.g., fatigue and pain). The website also allows gaining insight in behavior and its consequences. For example, for some people, physical activity may be followed by higher levels of fatigue, whereas for others, physical activity may be more relaxing and may therefore relieve fatigue, which may also differ within individuals over time. Therefore, the ESM data collected by participants themselves allows highly personalized insights that offer concrete entry points for treatment approaches. Sessions will consist of 3 modules. Sessions 1&2 will focus on diurnal variation in fatigue and mood, sessions 3&4 will focus on fatigue in relation to physical activity and type of activity, and sessions 5&6 will focus on fatigue in relation to social interactions and location. The central aim is to provide insight into everyday functioning, fatigue and related factors and to initiate behavioral/contextual changes to improve fatigue, other symptoms, and (eventually) participation in meaningful activities. A detailed treatment protocol will be provided to healthcare professionals who will deliver the Tied by Tiredness intervention.

Intervention fidelity monitoring is described in full in the treatment protocol paper [21]. In brief, the Tied by Tiredness intervention will be delivered by occupational therapists or psychologists with relevant knowledge and clinical experience in acquired brain injury and fatigue. Prior to study commencement, research team members will train therapists involved in fatigue rehabilitation in the Tied by Tiredness treatment protocol at each study location. More precisely, these professionals will be trained in interpreting the ESM data and providing personalized feedback on the ESM data accessed via the m-Path website. Adherence and fidelity will be monitored continuously throughout the trial via app-generated data and structured session reports, enabling real-time and post-intervention evaluations of participant engagement and consistency of intervention delivery across sessions and sites. The therapists will follow a standardized protocol when reviewing m-Path output with participants.

TAU group

Treatment as usual (TAU) for fatigue will be delivered by occupational therapists and comprises two minimum expected components for all participants: (1) psychoeducation about fatigue following acquired brain injury (ABI) and (2) elements of Niet-Rennen-Maar-Plannen (“Do not Run, But Plan”), a treatment program for individuals with ABI who experience cognitive problems, which is widely used in the Netherlands and includes a fatigue module [22]. Sessions will be delivered individually and will last either 30–45 min at a frequency of once or twice per week, depending on the clinical setting. To account for this variability and to support reproducibility, the number of sessions, session duration, session frequency, and treatment content delivered will be recorded for each participant throughout the trial. The treating therapist will provide this information at the end of treatment.

Allocation and blinding

After providing written informed consent and completing the baseline assessment, the participants will inform the researcher of their choice for either TAU or the new intervention. The participants will be able to discuss both options with their treating therapist beforehand, but the researcher will remain blinded until after the baseline measurements are completed. Hereafter, assessments will consist of self-report questionnaires for which blinding is not applicable, and for the ESM intervention, blinding is not possible

Adverse events and unintended effects

Although the Tied by Tiredness intervention is considered low risk, monitoring adverse events and unintended effects is an integral part of the study protocol. Healthcare professionals will be instructed to report any adverse events or unexpected deterioration in participant well-being to the principal investigator. Participant burden and fatigue exacerbation will be specifically monitored through the app-generated ESM data and session reports, which allow for early identification of any increase in symptom severity or disengagement. If a participant reports or displays significant distress or worsening of fatigue during the intervention, the treating professional will discuss this with the participant and, where necessary, adapt the intervention pace or intensity or refer the participant to their treating physician. Participants will also be informed at enrolment that they may withdraw from the study at any time without consequences for their care.

Measures

Demographics and injury characteristics

This information includes age, sex, employment status (current and before brain injury), and education on the basis of self-reports. Injury characteristics: date most recent brain injury, type of most recent brain injury, date and type of previous brain injury/injuries, hospital admission (yes/no), and length of hospital stay (proxy of severity) of most recent brain injury.

Primary outcome measure

Fatigue Severity

The Fatigue Severity Scale (FSS) assesses fatigue severity in daily life [23]. The FSS consists of nine statements (e.g., ‘I am easily fatigued’) rated on a 7-point Likert scale (1-7). The total score is calculated as the mean score per item, with higher values indicating greater fatigue severity. A score of ≥ 4 is considered to be indicative of clinically significant fatigue. More recently, Lerdal and Kottorp [24] reported that the FSS has more robust psychometric properties for poststroke fatigue when the first two items are removed. Therefore, we calculate the total mean score per item using only questions 3–9.

Secondary outcome measures

Multifactor Fatigue

The Dutch Multifactor Fatigue Scale (DMFS) [25] was recently developed specifically to measure fatigue after brain injury. The DMFS consists of five factors: impact of fatigue, mental fatigue, signs and direct consequences of fatigue, physical fatigue, and coping with fatigue. The total score per factor is calculated as the sum score of all the items from that factor. All the subscales of the DMFS show sufficient to good reliability, good convergent validity with an existing fatigue scale, and good divergent validity with measures of mood and self-esteem. The average scores of each of the five factors were used in the analyses.

Fatigue (ESM)

Changes in ESM-reported fatigue in the intervention group over the intervention period will also be measured. This analysis is used to identify within-group, person-level variables that moderate the effect of the intervention.

Subjective cognitive symptoms

The Checklist for Cognitive and Emotional Consequences of Stroke (CLCE-24) [26] consists of 24 items and covers two subscales assessing cognitive and emotional complaints separately. The CLCE-24 is used to identify the number of cognitive and emotional problems after brain injury, with each problem being marked as present or not present (1–0). Higher scores indicate more problems. The scale has been validated in brain injury populations and has good internal consistency.

Anxiety and depression

The Hospital Anxiety and Depression Scale (HADS) [27] will be used to measure self-reported anxiety and depression symptoms. The scores for the subscales, with 7 items each, range from 0 to 21, with higher scores indicating higher levels of depression or anxiety. The questionnaire has been validated in a TBI population [28, 29]. Furthermore, good internal consistency for both subscales (Cronbach’s α depression scale: 0.81; anxiety scale: 0.84) was found in a stroke population [30].

Participation

The Utrecht Scale for Evaluation of Rehabilitation-Participation (USER-P) [31] measures aspects of participation on three subscales: frequency of participation in social activities, restrictions to participation due to health conditions, and satisfaction with participation. The questionnaire consists of 31 items. For each subscale, a score ranging from 0 to 100 is calculated. Higher scores indicate more participation, less restriction, and more satisfaction. It is a valid and reliable measure for participants with ABI with good internal consistency (Cronbach’s α = 0.70– 0.91).

Health status

The SF-12 [32] will be used to measure the health status of the participants. The 12 items, which are a subset of the SF-36, provide scores for the physical and mental health of the participants. The total score ranges from 0 to 100, with a higher score indicating a better health status. The SF-12 has been validated for use in TBI research [33].

Quality of life

The EQ-5D-5 L [34] consists of five questions measuring health status. The scale covers the dimensions of mobility, self-care, daily activities, pain or discomfort, and anxiety or depression. Each domain is scored on a five-point scale ranging from “no problems” to “extreme problems”. Scores were calculated with Dutch tariffs, which range from − 0.446 (worst health state) to 1 (full health) [35] VAS.

Intervention costs

The costs of Tied by Tiredness and TAU will be calculated by multiplying the number of sessions by the Dutch unit price of the corresponding type of care professional that delivered the sessions.

Study-specific cost questionnaire

This questionnaire was constructed to collect cost data from a societal perspective. It is based on the steps described by Thorn et al. [36] and on the questionnaire used in Kootker et al. [37]. Several questions were altered on the basis of response patterns and analyses in Kootker et al.’s study. The questions concern the usage frequency of healthcare resources, informal care, medication use and loss of productivity at work over the past 3 months. For example, participants record the number of visits to the GP, specialists or hospital services as well as the number of hours per week they receive help from home from healthcare workers, friends and family.

Data management

The participants will be assigned a unique code upon completion of the consent form. This code will be used for all questionnaires and data documents. The questionnaires will be completed online via Qualtrics or on paper (on the basis of participant preference). Baseline questionnaires will be completed in the presence of a researcher, but all subsequent questionnaires will be e-mailed or mailed to participants. Participants who withdraw from the study will be asked if they are still willing to complete the T1, T2, and T3 study measurements. If they decline (no reason needs to be given for this), participants will be no longer approached for the study assessments. If they agree, participants will still receive T1, T2, and T3 study measurements. The intention-to-treat (ITT) principle will be applied to all analyses to take into account potential bias due to non-random attrition.

Data will be handled confidentially, and reporting will be coded. Each participant is given a personal code that is only convertible to a person when the coding key is known. The personal and anonymous code will be numerical, and the order will be based on the moment of inclusion (e.g., 001, 002, 003). The collected data and personal information will be stored separately in locked cabinets at Maastricht University. Only members of the research team will have access to participant data. The handling of personal data will comply with the Dutch Act on Implementation of the General Data Protection Rule (GDPR) and the Research Data Management Code of Conduct of Maastricht University. The data will be stored for 15 years after the end of the study. The participants will be informed that their data may be important for future research on rehabilitation after brain injury and may therefore be reused in the future. This will be described in the information letter. Participants will be explicitly informed that they can agree or disagree with this on the informed consent form and that this will have no impact on their current treatment.

Data monitoring

The ethics committee decided that this study does not fall under the Dutch Medical Research Involving Human Subjects Act (WMO); therefore, data monitoring is not necessary.

Statistical analysis

For the primary research objective, we will use a linear mixed-effects model with fatigue severity score (FSS) as the dependent variable and time points (T0, T1, T2, and T3) as within-subject factors. Participants will be included as a random effect. Planned contrasts will be conducted to assess pre- to postintervention changes. Our primary comparison of interest is the change from pre-intervention (T0) to post-intervention (T1) in the Tied by Tiredness group. For all reported linear mixed-effects models, age and sex will be included as covariates. In all analyses examining within-group changes over time, time since injury will additionally be included as a covariate, given its potential association with spontaneous recovery and fatigue trajectories following brain injury. For the secondary research objectives related to reductions in fatigue subtypes (DMFS) and cognitive and emotional complaints and improvements in societal participation and quality of life, similar linear mixed-effects models will be conducted with the respective secondary outcomes as the dependent variable. To assess changes in daily fatigue (ESM) over the course of the intervention, linear mixed models will be used, with ESM-reported fatigue as the dependent variable and with time (weeks 1–6) included as a fixed factor. Random intercepts and slopes will be included where appropriate to account for individual variability in fatigue severity and the course of fatigue. This analysis will be complemented with a paired samples t-test to compare the average of the first week of ESM-reported fatigue to that of the final week of ESM-reported fatigue.

Baseline characteristics will be compared descriptively between groups using appropriate summary statistics (means and standard deviations for continuous variables; frequencies and percentages for categorical variables). These comparisons are intended to inform the interpretation of outcomes rather than to serve as formal hypothesis tests. As this is a non-randomized study, self-selection into groups cannot be fully accounted for by statistical methods, and residual confounding should be considered when interpreting the results.

The secondary research objective exploring the outcomes of the Tied by Tiredness intervention in comparison to treatment as usual (TAU) will be tested via linear mixed-effects models with fatigue severity scores (FSS) as the dependent variable and time points (T0, T1, T2, T3) as the within-subjects factor and with group (Tied by Tiredness versus TAU) as the between-subjects factor. We will test for a main effect of group, time, and group*time interaction.

Finally, the intervention costs of Tied by Tiredness and TAU will be explored via t-tests. The cost data will be valued via the most recent Dutch costing guidelines and reference prices available at the time of analysis, with the final year of data collection (i.e., 2026) as the reference costing year. Productivity losses and informal care will be valued in accordance with Dutch guidelines for economic evaluations in healthcare. Health-related quality of life will be assessed via the EQ-5D-5 L, from which utility scores and quality-adjusted life years (QALYs) will be derived via the Dutch tariff and area-under the-curve methods. Given the expected skewness of cost data, appropriate regression-based methods and bootstrapping will be used to estimate differences in costs and assess uncertainty. The changes in other costs related to the Tied by Tiredness intervention (study-specific cost questionnaire) over time will be analyzed via linear mixed-effects models per cost category (health-care and nonhealthcare costs). Cost analyses will be exploratory and are not prespecified as secondary outcomes. Results of this and any other between-group comparison should therefore be interpreted with caution and considered exploratory rather than confirmatory in nature.

Analyses will follow the intention-to-treat (ITT) principle to minimize potential bias due to non-random attrition. Intervention fidelity and participant adherence will be quantified and reported descriptively to characterize implementation quality. These variables will not be incorporated as covariates or moderators in the primary outcome analyses. Analyses will be conducted via SPSS version 31, with an alpha level of 0.05. All linear mixed-effects models will be fitted using all available data. Model parameters are estimated via maximum likelihood estimation under the missing-at-random (MAR) assumption. Missing outcome data will not be imputed.

Discussion

Despite the high prevalence of fatigue after brain injury [2], evidence-based and efficient treatments are scarce. This study will investigate a new treatment for fatigue after ABI based on the Experience Sampling Method (ESM). To the extent that the Tied by Tiredness intervention is associated with improvements in fatigue, this treatment could be implemented in clinical practice with few additional resources needed.

The design of this study is a multicentre prospective non-randomized patient preference trial. Non-randomized studies, also known as quasi-experiments, play a significant role in the scientific literature, particularly in fields where conducting randomized controlled trials (RCTs) may be impractical or unethical [38]. This method has been chosen to better reflect real-world clinical practice, providing insights into how the intervention influences outcomes in natural settings. Real-world clinical practice involves treating participants with a wide range of characteristics, needs and symptoms [39]. This diversity can impact treatment choices and outcomes and requires healthcare providers to tailor their approach to individual patient needs. Real-world clinical practice often involves variability in treatment decisions on the basis of factors such as patient preferences, clinician expertise, resource availability, and local guidelines. This variability reflects the complexity of healthcare delivery and the need for personalized medicine [40]. Furthermore, non-randomized studies are often less expensive and time-consuming than RCTs are. Finally, translating the evidence of randomized controlled trials into real-world practice can be challenging. Factors such as patient adherence, healthcare infrastructure, and reimbursement policies can influence the adoption and implementation of evidence-based practices [41].

We acknowledge that there are several weaknesses associated with non-randomized studies, such as confounding variables. Since participants are not randomly assigned to groups, there is a greater risk of confounding variables influencing the results. The non-randomized design also precludes making causal inferences [42]. Furthermore, the results that will emerge from the current study warrant careful consideration. As a non-randomized patient-preference trial, participants will self-select into treatment arms following baseline assessment, which introduces a substantial risk of selection bias. Individuals who will choose the Tied by Tiredness intervention may differ systematically from those who will choose TAU in characteristics that are themselves predictive of outcomes, such as motivation, fatigue severity, treatment expectations, or digital literacy. Although baseline characteristics will be reported and compared between groups, these differences cannot be fully controlled for, and residual confounding from unmeasured variables remains a fundamental limitation of this design. Consequently, the study does not permit making causal inference about the effectiveness of the Tied by Tiredness intervention relative to TAU. Between-group comparisons will therefore be exploratory in nature and should be interpreted as associations between treatment preference and outcome rather than as estimates of treatment efficacy. This distinction is further underscored by the fact that the TAU arm will be included primarily to capture patient treatment preference and to enable exploratory analyses, and the study is not powered for formal comparative effectiveness testing. A further consideration specific to patient-preference designs is the preference effect: participants receiving their chosen treatment may experience better outcomes in part because of the act of receiving a preferred treatment, independent of its specific therapeutic components. This limits the extent to which outcomes in the Tied by Tiredness arm can be attributed solely to the intervention content.

However, studies have shown that incorporating patient preferences into trial designs can further improve the representativeness of study populations and the relevance of trial results to everyday clinical practice without compromising the integrity of the data collected [43], as the rates of loss to follow-up and treatment crossovers were significantly higher in the randomized cohorts than in the preference cohorts. This finding indicates that participants who are allowed to choose their treatment are more likely to adhere to the study protocol [38].

A positive outcome from this trial could lead to implementation of the Tied by Tiredness intervention on a broader scale. This may foster multi-domain improvements in individuals experiencing fatigue after brain injury, leading to an overall improvement in quality of life while potentially being more cost-effective for the health care system.

Abbreviations

TBI

Traumatic brain injury

TAU

Treatment as usual

COGRAT

Cognitive and graded activity training

NRMP

Niet Rennen Maar Plannen (English: Don’t Run, But Plan)

ESM

Experience sampling methodology

FSS

Fatigue severity scale

USER-P

Utrecht scale for evaluation of rehabilitation-participation

CLCE-24

Checklist for cognitive and emotional consequences of stroke

HADS

Hospital anxiety and depression scale

DMFS

Dutch multifactor fatigue scale

SF-12

Short form survey

EQ-5D-5 L

European quality of life 5 dimensions 5 level version

ITT

Intention to treat

GDPR

General Data Protection Rule

Authors’ contributions

BL, CvH and RP conceived the original idea, developed the overall study design, and obtained funding for the study. ES, CW, VS, JD and TS were added to the project team after funding had been received and were involved in refining the design of the study. TS drafted the manuscript. ES and BL prepared the final version. All the authors reviewed and approved the final manuscript.

Funding

Hersenstichting (Brain Foundation); founding nr. ONI − 2019-09.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

This study was granted ethical approval by the Ethics Review Committee Psychology and Neuroscience at Maastricht University (Ethics code: ERCPN- 256_104_08_2022).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.