Search

Purpose: Brain injuries (traumatic-/nontraumatic, TBI/nTBI) in young patients may lead to problems e.g., decreased health-related quality of life (HRQoL), and causes family impact. Knowledge regarding the family impact and the relationship with patients' HRQoL over time is scarce. This follow-up study describes family impact/HRQoL and their mutual relationship in young patients (5-24 years) after TBI/nTBI., Materials and Methods: Parents of patients that were referred to outpatient rehabilitation completed the PedsQL™Family-Impact-Module questionnaire to assess the family impact and the parent-reported PedsQL™Generic-core-set-4.0 to assess patients' HRQoL (lower scores: more family impact/worse HRQoL). Questionnaires were completed at the time of referral to rehabilitation (baseline) and one/two years later (T1/T2). Linear-mixed models were used to examine family impact/HRQoL change scores, and repeated-measure correlations (r) to determine longitudinal relationships., Results: Two-hundred-forty-six parents participated at baseline, 72 (at T2), median patient's age at baseline was 14 years (IQR:11-16), and 181 (74%) had TBI. Mean (SD) PedsQL™Family-Impact-Module score at baseline was 71.7 (SD:16.4) and PedsQL™Generic-core-set-4.0: 61.4 (SD:17.0). Over time, PedsQL™Family-Impact-Module scores remained stable, while PedsQL™Generic-core-set-4.0 scores improved significantly( p  < 0.05). A moderately strong longitudinal correlation was found between family impact&HRQoL ( r  = 0.51)., Conclusions: Family impact does not tend to decrease over time but remained a considerable problem, although patients' HRQoL improved. Next to focusing on patients' HRQoL, it remains important to consider family impact and offer family support throughout rehabilitation.IMPLICATIONS FOR REHABILITATIONThis longitudinal study found that in young patients with traumatic brain injury (TBI) or non-traumatic brain injury (nTBI) referred for rehabilitation there is a considerable impact on the family until two years after referral, whereas the patients' health-related quality of life (HRQoL) improved significantly.Improvements in patients' quality of life status may not automatically lead to a decrease of family impact.Rehabilitation clinicians should monitor the impact on the family over time and provide long-term family support with special attention to parental worrying when needed.Clinicians should be aware that, despite significant differences between the clinical characteristics of patients with TBI and nTBI, the courses of family impact are very similar.

Background: Implementation of an eRehabilitation intervention named Fit After Stroke @Home (Fast@home) - including cognitive/physical exercise applications, activity-tracking, psycho-education - after stroke resulted in health-related improvements. This study investigated what worked and why in the implementation., Methods: Implementation activities (information provision, integration of Fast@home, instruction and motivation) were performed for 14 months and evaluated, using the Medical Research Council framework for process evaluations which consists of three evaluation domains (implementation, mechanisms of impact and contextual factors). Implementation activities were evaluated by field notes/surveys/user data, it's mechanisms of impact by surveys and contextual factors by field notes/interviews among 11 professionals. Surveys were conducted among 51 professionals and 73 patients. User data ( n  = 165 patients) were extracted from the eRehabilitation applications., Results: Implementation activities were executed as planned. Of the professionals trained to deliver the intervention (33 of 51), 25 (75.8%) delivered it. Of the 165 patients, 82 (49.7%) were registered for Fast@home, with 54 patient (65.8%) using it. Mechanisms of impact showed that professionals and patients were equally satisfied with implementation activities (median score 7.0 [IQR 6.0-7.75] versus 7.0 [6.0-7.5]), but patients were more satisfied with the intervention (8.0 [IQR 7.0-8.0] versus 5.5 [4.0-7.0]). Guidance by professionals was seen as most impactful for implementation by patients and support of clinical champions and time given for training by professionals. Professionals rated the integration of Fast@home as insufficient. Contextual factors (financial cutbacks and technical setbacks) hampered the implementation., Conclusion: Main improvements of the implementation of eRehabilitation are related to professionals' perceptions of the intervention, integration of eRehabilitation and contextual factors.Implication for rehabilitationTo increase the use of eRehabilitation by patients, patients should be supported by their healthcare professional in their first time use and during the rehabilitation process.To increase the use of eRehabilitation by healthcare professionals, healthcare professionals should be (1) supported by a clinical champion and (2) provided with sufficient time for learning to work and getting familiar with the eRehabilitation program.Integration of eRehabilitation in conventional stroke rehabilitation (optimal blended care) is an important challenge and a prerequisite for the implementation of eRehabilitation in the clinical setting.

Background: Knowledge on long-term participation is scarce for patients with paid employment at the time of stroke., Objective: Describe the characteristics and the course of participation (paid employment and overall participation) in patients who did and did not remain in paid employment., Methods: Patients with paid employment at the time of stroke completed questions on work up to 30 months after starting rehabilitation, and the Utrecht Scale for Evaluation of Rehabilitation-Participation (USER-P, Frequency, Restrictions and Satisfaction scales) up to 24 months. Baseline characteristics of patients with and without paid employment at 30 months were compared using Fisher's Exact Tests and Mann-Whitney U Tests. USER-P scores over time were analysed using Linear Mixed Models., Results: Of the 170 included patients (median age 54.2 interquartile range 11.2 years; 40% women) 50.6% reported paid employment at 30 months. Those returning to work reported at baseline more working hours, better quality of life and communication, were more often self-employed and in an office job. The USER-P scores did not change statistically significantly over time., Conclusion: About half of the stroke patients remained in paid employment. Optimizing interventions for returning to work and achieving meaningful participation outside of employment seem desirable.

Background: Persons with disabilities are at risk for unemployment with negative long-term consequences., Objective: This study aimed to explore the process and outcomes of a novel vocational rehabilitation (VR) program based on the concept of mentorship., Methods: Observational, retrospective study including unemployed young adults with acquired brain injury (ABI) taking part in a VR program including assessment, training, individual counselling and mentor support from volunteering professionals. Adherence to the program and work status were registered and at follow-up all patients were invited to complete a general questionnaire and EuroQol 5D., Results: 49 patients started the program, with 41 completing the follow-up. Median age was 31 years and 19 were male. Median duration of the program was 8 months. At follow-up, 9 patients had acquired paid employment, 7 with the support of a mentor; 6 of whom were bothered by health problems at work. Nine patients left the program prematurely, with insufficient financial support for continuation being the primary reason for withdrawal (n = 6)., Conclusions: A VR program including a mentor may be a promising program for patients who are unemployed at onset of ABI. Lack of financial support to complete the program and concurrent health problems were found to hamper the process and outcomes of the program, respectively.

Purpose: To increase knowledge/awareness on family impact (FI) after acquired brain injury (ABI) in rehabilitation settings, it is essential to investigate the associations between patient-functioning and impact on families. This has been explored in hospital-based cohorts, but not in rehabilitation settings. Methods: A cross-sectional, multi-center study among parents of children/young adults (aged 5-24 years) with ABI referred to rehabilitation was performed. Patient/injury/family-characteristics were noted, and parents completed the PedsQL™Family-Impact-Module and PedsQL™generic-core-4.0 to assess FI and health-related quality of life (HRQoL). Univariate- and multivariable-regression analyses were performed to investigate associations between HRQoL/patient/injury/family-related factors and FI. Results: 246 families participated; patients' median age was 14 year (IQR 11-16), 65 had non-traumatic-brain-injury (nTBI) (26%), 127 were female. FI was found to be considerable (median FIM-score 71.9, IQR:60-85). Especially referral to rehabilitation >6 months after onset, diminished patients' mental/emotional health and HRQoL (child/family factors), and premorbid problems were associated with higher FI. Conclusions: In this rehabilitation cohort, pediatric ABI caused considerably higher FI than in hospital-based studies with referral to rehabilitation >6 months, diminished child/family factors and presence of premorbid problems increasing FI. Assessing and monitoring FI and its associated factors enables professionals to individualize treatment, psychoeducation, support and follow-up.

Objective: To compare the effect on disability and quality of life, of conventional rehabilitation (control group) with individualized, tailored eRehabilitation intervention alongside conventional rehabilitation (Fast@home; intervention group), for people with stroke., Methods: Pre-post design. The intervention comprised cognitive (Braingymmer®) and physical (Telerevalidatie®/Physitrack®) exercises, activity-tracking (Activ8®) and psycho-education. Assessments were made at admission (T0) and after 3 (T3) and 6 months (T6). The primary outcome concerned disability (Stroke Impact Scale; SIS). Secondary outcomes were: health-related quality of life, fatigue, self-management, participation and physical activity. Changes in scores between T0-T3, T3-T6, and T0-T6 were compared by analysis of variance and linear mixed models., Results: The study included 153 and 165 people with stroke in the control and intervention groups, respectively. In the intervention group, 82 (50%) people received the intervention, of whom 54 (66%) used it. Between T3 and T6, the change in scores for the SIS subscales Communication (control group/intervention group -1.7/-0.3) and Physical strength (-5.7/3.3) were significantly greater in the total intervention group (all mean differences< minimally clinically important differences). No significant differences were found for other SIS subscales or secondary outcomes, or between T0-T3 and T0-T6., Conclusion: eRehabilitation alongside conventional stroke rehabilitation had a small positive effect on communication and physical strength on the longer term, compared to conventional rehabilitation only.

An amendment to this paper has been published and can be accessed via the original article.

Purpose: To study the association between fatigue and participation and QoL after acquired brain injury (ABI) in adolescents and young adults (AYAs)., Materials & Methods: Cross-sectional study with AYAs aged 14-25 years, diagnosed with ABI. The PedsQL™ Multidimensional Fatigue Scale, Child & Adolescent Scale of Participation, and PedsQL™4.0 Generic Core Scales were administered., Results: Sixty-four AYAs participated in the study, 47 with traumatic brain injury (TBI). Median age at admission was 17.6 yrs, 0.8 yrs since injury. High levels of fatigue (median 44.4 (IQR 34.7, 59.7)), limited participation (median 82.5 (IQR 68.8, 92.3)), and diminished QoL (median 63.0 (IQR 47.8, 78.3)) were reported. More fatigue was significantly associated with more participation restrictions (β 0.64, 95%CI 0.44, 0.85) and diminished QoL (β 0.87, 95%CI 0.72, 1.02)., Conclusions: AYAs with ABI reported high levels of fatigue, limited participation and diminished quality of life with a significant association between fatigue and both participation and QoL. Targeting fatigue in rehabilitation treatment could potentially improve participation and QoL.

Background: To improve the use of eRehabilitation after stroke, the identification of barriers and facilitators influencing this use in different healthcare contexts around the world is needed. Therefore, this study aims to investigate differences and similarities in factors influencing the use of eRehabilitation after stroke among Brazilian Healthcare Professionals (BHP) and Dutch Healthcare Professionals (DHP)., Method: A cross-sectional survey study including 88 statements about factors related to the use of eRehabilitation (4-point Likert scale; 1-4; unimportant-important/disagree-agree). The survey was conducted among BHP and DHP (physical therapists, rehabilitating physicians and psychologists). Descriptive statistics were used to analyse differences and similarities in factors influencing the use of eRehabilitation., Results: ninety-nine (response rate 30%) BHP and 105 (response rate 37%) DHP participated. Differences were found in the top-10 most influencing statements between BHP and DHP BHP rated the following factors as most important: sufficient support from the organisation (e.g. the rehabilitation centre) concerning resources and time, and potential benefits of the use of eRehabilitation for the patient. DHP rated the feasibility of the use of eRehabilitation for the patient (e.g. a helpdesk and good instructions) as most important for effective uptake. Top-10 least important statements were mostly similar; both BHP and DHP rated problems caused by stroke (e.g. aphasia or cognitive problems) or problems with resources (e.g. hardware and software) as least important for the uptake of eRehabilitation., Conclusion: The results indicate that the use of eRehabilitation after stroke by BHP and DHP is influenced by different factors. A tailored implementation strategy for both countries needs to be developed.

Objective: Despite the increasing availability of eRehabilitation, its use remains limited. The aim of this study was to assess factors associated with willingness to use eRehabilitation., Design: Cross-sectional survey., Subjects: Stroke patients, informal caregivers, health-care professionals., Methods: The survey included personal characteristics, willingness to use eRehabilitation (yes/no) and barri-ers/facilitators influencing this willingness (4-point scale). Barriers/facilitators were merged into factors. The association between these factors and willingness to use eRehabilitation was assessed using logistic regression analyses., Results: Overall, 125 patients, 43 informal caregivers and 105 healthcare professionals participated in the study. Willingness to use eRehabilitation was positively influenced by perceived patient benefits (e.g. reduced travel time, increased motivation, better outcomes), among patients (odds ratio (OR) 2.68; 95% confidence interval (95% CI) 1.34-5.33), informal caregivers (OR 8.98; 95% CI 1.70-47.33) and healthcare professionals (OR 6.25; 95% CI 1.17-10.48). Insufficient knowledge decreased willingness to use eRehabilitation among pa-tients (OR 0.36, 95% CI 0.17-0.74). Limitations of the study include low response rates and possible response bias., Conclusion: Differences were found between patients/informal caregivers and healthcare professionals. Ho-wever, for both groups, perceived benefits of the use of eRehabilitation facilitated willingness to use eRehabili-tation. Further research is needed to determine the benefits of such programs, and inform all users about the potential benefits, and how to use eRehabilitation.

Background: Despite the growing importance of eHealth it is not consistently embedded in the curricula of functional exercise and physical therapy education. Insight in barriers and facilitators for embedding eHealth in education is required for the development of tailored strategies to implement eHealth in curricula. This study aims to identify barriers/facilitators perceived by teachers and students of functional exercise/physical therapy for uptake of eHealth in education., Methods: A qualitative study including six focus groups (two with teachers/four with students) was conducted to identify barriers/facilitators. Focus groups were audiotaped and transcribed in full. Reported barriers and facilitators were identified, grouped and classified using a generally accepted framework for implementation including the following categories: innovation, individual teacher/student, social context, organizational context and political and economic factors., Results: Teachers (n = 11) and students (n = 24) of functional exercise/physical therapy faculties of two universities of applied sciences in the Netherlands participated in the focus groups. A total of 109 barriers/facilitators were identified during the focus groups. Most related to the Innovation category (n = 26), followed by the individual teacher (n = 22) and the organization (n = 20). Teachers and students identified similar barriers/facilitators for uptake of eHealth in curricula: e.g. unclear concept of eHealth, lack of quality and evidence for eHealth, (lack of) capabilities of students/teachers on how to use eHealth, negative/positive attitude of students/teachers towards eHealth., Conclusion: The successful uptake of eHealth in the curriculum of functional exercise/physical therapists needs a systematic multi-facetted approach considering the barriers and facilitators for uptake identified from the perspective of teachers and students. A relatively large amount of the identified barriers and facilitators were overlapping between teachers and students. Starting points for developing effective implementation strategies can potentially be found in those overlapping barriers and facilitators., Registration: The study protocol was a non-medical research and no registration was required. Participants gave written informed consent.

Background: The uptake of eRehabilitation programs in stroke care is insufficient, despite the growing availability. The aim of this study was to explore which factors influence the uptake of eRehabilitation in stroke rehabilitation, among stroke patients, informal caregivers, and healthcare professionals., Methods: A qualitative focus group study with eight focus groups (6-8 participants per group) was conducted: six with stroke patients/informal caregivers and two with healthcare professionals involved in stroke rehabilitation (rehabilitation physicians, physical therapists, occupational therapists, psychologists, managers). Focus group interviews were audiotaped, transcribed in full, and analyzed by direct content analysis using the implementation model of Grol., Results: Thirty-two patients, 15 informal caregivers, and 13 healthcare professionals were included. A total of 14 influencing factors were found, grouped to 5 of the 6 levels of the implementation model of Grol (Innovation, Organizational context, Individual patient, Individual professional, and Economic and political context). Most quotes of patients, informal caregivers, and healthcare professionals were classified to factors at the level of the Innovation (e.g., content, attractiveness, and feasibility of eRehabilitation programs). In addition, for patients, relatively many quotes were classified to factors at the level of the individual patient (e.g., patients characteristics as fatigue and the inability to understand ICT-devices), and for healthcare professionals at the level of the organizational context (e.g., having sufficient time and the fit with existing processes of care)., Conclusion: Although there was a considerable overlap in reported factors between patients/informal caregivers and healthcare professionals when it concerns eRehabilitation as innovation, its seems that patients/informal caregivers give more emphasis to factors related to the individual patient, whereas healthcare professionals emphasize the importance of factors related to the organizational context. This difference should be considered when developing an implementation strategy for patients and healthcare professionals separately.

Objective: To determine neurological outcome in children and youth with acquired brain injury (ABI) and explore associated factors., Design: Cross-sectional study, two-years post-injury., Patients: Hospital-based sample (n=112) aged 6-22 years., Methods: Neurological outcome and participation were assessed with a multidimensional neurological examination and the Child and Adolescent Scale of Participation. Logistic regression analyses were used to explore the relationships., Results: Both sensorimotor and cognitive deficits were found in 30-31%, language deficits and behavioural deficits in 10-17%. Non-traumatic injury had a negative impact on neurological outcome, specifically regarding sensorimotor and language deficits. Lower education level showed a significantly poorer neurological outcome. High levels of age-expected participation were reported, with a significant relation between deficits and participation restrictions, especially at school., Conclusion: One out of three have a poor neurological outcome, related to type of injury and lower level of education. The amount of deficits is associated with participation restrictions.

Introduction: Success of e-health relies on the extent to which the related technology, such as the electronic device, is accepted by its users. However, there has been limited research on the patients' perspective on use of e-health-related technology in rehabilitation care., Objective: To explore the usage of common electronic devices among rehabilitation patients with access to email and investigate their preferences regarding their usage in rehabilitation., Methods: Adult patients who were admitted for inpatient and/or outpatient rehabilitation and were registered with an email address were invited to complete an electronic questionnaire regarding current and preferred use of information and communication technologies in rehabilitation care., Results: 190 out of 714 invited patients completed the questionnaire, 94 (49%) female, mean age 49 years (SD 16). 149 patients (78%) used one or more devices every day, with the most frequently used devices were: PC/laptop (93%), smartphone (57%) and tablet (47%). Patients mostly preferred to use technology for contact with health professionals (mean 3.15, SD 0.79), followed by access to their personal record (mean 3.09, SD 0.78) and scheduling appointments with health professionals (mean 3.07, SD 0.85)., Conclusion: Most patients in rehabilitation used one or more devices almost every day and wish to use these devices in rehabilitation. Implications for Rehabilitation In a sample of 190 patients in rehabilitation with access to email, almost all patients used one or more electronic devices almost every day of the week, with the most frequently used devices were: a PC/laptop, smartphone and tablet. Most of the patients wish to incorporate electronic devices in their rehabilitation process and prefer to use those devices to have insight in their health record, communication with peers and scheduling appointments with health professionals. To better assist patients with e-health in rehabilitation care in the future, preferences could be implemented in rehabilitation care by using the most commonly used devices.

Incorporating user requirements in the design of e-rehabilitation interventions facilitates their implementation. However, insight into requirements for e-rehabilitation after stroke is lacking. This study investigated which user requirements for stroke e-rehabilitation are important to stroke patients, informal caregivers, and health professionals. The methodology consisted of a survey study amongst stroke patients, informal caregivers, and health professionals (physicians, physical therapists and occupational therapists). The survey consisted of statements about requirements regarding accessibility, usability and content of a comprehensive stroke e-health intervention (4-point Likert scale, 1=unimportant/4=important). The mean with standard deviation was the metric used to determine the importance of requirements. Patients (N=125), informal caregivers (N=43), and health professionals (N=105) completed the survey. The mean score of user requirements regarding accessibility, usability and content for stroke e-rehabilitation was 3.1 for patients, 3.4 for informal caregivers and 3.4 for health professionals. Data showed that a large number of user requirements are important and should be incorporated into the design of stroke e-rehabilitation to facilitate their implementation.

Background Computer-based cognitive rehabilitation is used to improve cognitive functioning after stroke. However, knowledge on adherence rates of stroke patients is limited. Objective To describe stroke patients' adherence with a brain training program using two frequencies of health professionals' supervision. Methods This study is part of a randomized controlled trial comparing the effect of the brain training program (600 min playtime with weekly supervision) with a passive intervention in patients with self-perceived cognitive impairments after stroke. Patients randomized to the control condition were offered the brain training after the trial and received supervision twice (vs weekly in intervention group). Adherence was determined using data from the study website. Logistic regression analyses were used to examine the impact of supervision on adherence. Results 53 patients allocated to the intervention group (group S8; 64% male, mean age 59) and 52 patients who were offered the intervention after the trial (group S2; 59% male, mean age 59) started the brain training. The median playtime was 562 min (range 63-1264) in group S8 vs. 193 min (range 27-2162) in group S2 (p < 0.001, Mann Whitney U). Conclusions The overall adherence of stroke patients with a brain training was low and there are some implications that systematic, regular interaction with a supervisor can increase training adherence of stroke patients with a restitution-focused intervention performed at home.

Background: 10-20% of children and youth with mild traumatic brain injury (mTBI) suffer from long-term cognitive impairments with, supposedly, a negative impact on most domains of functioning., Objectives: To describe cognitive functioning and participation in children and youth two-years post-mTBI and to determine associated risk factors., Methods: Cross-sectional study among 73 patients (aged 6-22 years), hospital diagnosed with mTBI. Linear regression modelling was used to investigate the effect of potential predictors on cognitive functioning as measured with a neuropsychological assessment (NPA), two-years post-injury. Extent of participation was assessed using the Child and Adolescent Scale of Participation and correlation analysis was conducted to examine its association with level of cognitive functioning., Results: 7-15% of all participants had impaired cognitive functions, especially in the domains of processing speed, inhibitory control, cognitive flexibility, visuospatial constructional ability and visuospatial memory. Lower level of education and pre-injury cognitive problems were predictive for a lower level of long-term cognitive functioning. Slower inhibition speed, impaired visuospatial and verbal working memory were associated with reduced participation., Discussion and Conclusions: Persisting cognitive problems two years after mTBI were mostly related to the lower level of education and to pre-injury cognitive problems. Although participation of the patients was reported by parents to be relatively high, slower inhibition speed, impaired visuospatial and verbal working memory were associated with reduced participation.

Cognitive impairment after stroke has a direct impact on daily functioning and quality of life (QoL) of patients and is associated with higher mortality and healthcare costs. The aim of this study was to determine the effect of a computer-based brain training programme on cognitive functioning, QoL and self-efficacy compared to a control condition in stroke patients. Stroke patients with self-perceived cognitive impairment were randomly allocated to the intervention or control group. The intervention consisted of an 8-week brain training programme (Lumosity Inc.®). The control group received general information about the brain weekly. Assessments consisted of a set of neuropsychological tests and questionnaires. In addition, adherence with trained computer tasks was recorded. No effect of the training was found on cognitive functioning, QoL or self-efficacy when compared to the control condition, except for very limited effects on working memory and speed. This study found very limited effects on neuropsychological tests that were closely related to trained computer tasks, but no transfers to other tests or self-perceived cognitive failures, QoL or self-efficacy. These findings warrant the need for further research into the value of computer-based brain training to improve cognitive functioning in the chronic phase after stroke.

Background: Approximately 20 % of children and adolescents who have sustained mild traumatic brain injuries may experience long-term consequences, including cognitive problems, post-traumatic stress symptoms and reduced load-bearing capacity. The underestimation and belated recognition of these long-term consequences may lead to chronic and disruptive problems, such as participation problems in school and in social relationships. The aim of this study is to examine the level of activities and participation of children and adolescents up to 6 months after a mild traumatic brain injury and to identify possible outcome predictors. Another aim is to investigate the effectiveness of an early psychoeducational intervention and compare the results with those obtained with usual care., Methods/design: This paper presents the Brains Ahead! study design, a randomised controlled trial nested within a multicentre, longitudinal, prospective cohort study. The eligible participants include children and adolescents between 6 and 18 years of age who have experienced a mild traumatic brain injury within the last 2 weeks. The cohort study will include 500 children and adolescents with a mild traumatic brain injury and their caregivers. A subset of 140 participants and their caregivers will be included in the randomised controlled trial. Participants in the randomised controlled trial will be randomly assigned to either the psychoeducational intervention group or the usual care control group. The psychoeducational intervention involves one face-to-face contact and one phone contact with the interventionist, during which the consequences of mild traumatic brain injury and advice for coping with these consequences to prevent long-term problems will be discussed. Information will be provided both verbally and in a booklet. The primary outcome domain is activities and participation, which will be evaluated using the Child and Adolescent Scale of Participation. Participants are evaluated 2 weeks, 3 months and 6 months after the mild traumatic brain injury., Discussion: The results of this study will provide insight into which children with mild traumatic brain injury are at risk for long-term participation problems and may benefit from a psychoeducational intervention., Trial Registration: Netherlands Trial Register identifier NTR5153 . Registered on 17 Apr 2015.

Objective: To assess the degree of fatigue in children and youth after traumatic and non-traumatic brain injury (TBI and NTBI) and related factors., Method: Follow-up study including patients with a hospital-based diagnosis of acquired brain injury (ABI), aged 4-20 years at onset and their parents. Parents and children (dependent on age) completed the Paediatric Quality of Life Inventory™ Multidimensional Fatigue Scale (PedsQL™ MFS), which measures general fatigue (GF), sleep/rest fatigue (SRF) and cognitive fatigue (CF). Additional assessments included the Child & Family Follow-up Survey (CFFS) and PedsQL™ 4.0 General Core Scales and sociodemographic and disease characteristics., Results: Eighty-eight parents completed the PedsQL™ MFS 24-30 months after diagnosis, with 49/88 patients (56%) completing the child version. The median age of the patients was 11 years (interquartile range [IQR] = 7). There were 69 patients with TBI (16% moderate/severe TBI) and 19 patients with NTBI (16% moderate/severe NTBI). The median parent-reported and child-reported PedsQL™ MFS Total Scale Scores were 76.5 (SD = 16.4) and 78.5 (12.9), respectively (Spearman r = 0.450, p = 0.001). Apart from NTBI, increasing age and a single-parent household were significantly associated with more fatigue according to the parent-reported PedsQL™ MFS Total Score (and/or one or more sub-scale scores)., Conclusion: Two years after onset, in particular, the parent-reported fatigue after NTBI was considerable. Moreover, older children and children from a single-parent household were found to have higher fatigue levels.

Objective: To determine health-related quality of life (HRQoL) in children and youth with acquired brain injury (ABI) two years post-injury and explore associated factors., Design: Cross-sectional., Subjects: Children and youth (n = 72; aged 6-22 years) with mild to severe ABI (87% mild)., Methods: The primary outcome measures self-reported and parent-reported HRQoL were assessed with the Paediatric Quality of Life Inventory (PedsQL) and compared with age-appropriate reference values of the Dutch population. Spearman correlation coefficients (Rs) were used to explore relationships between HRQoL and sociodemographic and ABI characteristics, severity of impairments and presence of post-injury problems., Results: Children and youth with ABI and the reference population had similar self-reported HRQoL. However, as reported by parents, children with ABI aged 6-7 years and youth aged 13-18 years had poorer HRQoL regarding psychosocial health. Children's post-injury cognitive, behavioural and social problems were moderately associated with poorer HRQoL, especially psychosocial health (Rs ≥ 0.40). Severity nor type of injury were associated with children's HRQoL., Conclusion: Two years post-injury, in children and youth with mild to severe ABI, reported HRQoL is similar to that in the general population, whereas parents reported less favourable outcomes. Post-injury cognitive, behavioural and social problems require ongoing attention during long-term follow-up., (Copyright © 2015 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.)

Objectives: Participation is considerably restricted in children and adolescents with acquired brain injury (ABI) as compared to their healthy peers. This systematic review aims to identify which factors are associated with participation in children and adolescents with ABI., Methods: A systematic search in Medline and various other electronic databases from January 2001-November 2014 was performed. All clinical studies describing determinants of participation at least 1 year after the diagnosis of ABI by means of one or more pre-defined instruments in patients up to 18 years of age were included. Extracted data included study characteristics, patient characteristics, participation outcome and determinants of participation (categorized into: health conditions (including characteristics of ABI), body functions and structures, activities, personal factors and environmental factors). The methodological quality of the studies was evaluated based on three quality aspects (selection, information and statistical analysis bias) and scored as low, moderate or high., Results: Eight studies using an explicit participation outcome measure were selected after review, including a total of 1863 patients, with a follow-up ranging from 1 up to 288 months. Three studies included patients with a traumatic or a non-traumatic brain injury (TBI or NTBI) and five studies with only TBI patients. Factors consistently found to be associated with more participation restrictions were: greater severity of ABI, impaired motor, cognitive, behavioural and/or sensory functioning, limited accessibility of the physical environmentand worse family functioning. Fewer participation problems were associated with a supportive/nurturing parenting style, higher household income, acceptance and support in the community and availability of special programmes. The overall methodological quality of the included studies was high in two and moderate in six studies., Conclusion: This systematic review shows that only a few, moderate quality, studies on the determinants of participation after paediatric ABI using recommended explicit measurement instruments are available. Various components of the ICF model: health condition, body functions and structures and environmental factors were consistently found to be associated with participation. More methodologically sound studies, using the recommended explicit outcome measures, a standardized set of potential determinants and long-term follow-up are suggested to increase the knowledge on participation in children and youth with ABI.

Objective: To assess the parental view on the impact of pediatric traumatic brain injury (TBI) and nontraumatic brain injury (NTBI) on the family and its determinants., Methods: Follow-up study including parents of children with a hospital-based diagnosis of acquired brain injury (ABI) aged 4-20 years at onset of ABI. Parents completed the Pediatric Quality of Life Inventory Family Impact Module (PedsQL FIM), which measures Parent Health-Related Quality of Life, Family Functioning, Communication, and Worry. Additional assessments included the Pediatric Stroke Outcome Measure (PSOM), the Child & Family Follow-up Survey (CFFS), PedsQL General Core and Multiple Fatigue Scales, and sociodemographic and disease characteristics., Results: Parents of 108 patients, median age 13 years (range 5-22), completed the questionnaires 24-30 months after diagnosis. There were 81 patients with TBI of whom 11 (14%) with moderate/severe TBI and 27 patients with NTBI of whom 5 (19%) with moderate/severe NTBI. The median PedsQL FIM Total Scale was 80.4 (SD 16.1). The PedsQL FIM Total Scale and 4 out of 5 Subscale Scores were statistically significantly better in the TBI group than in the NTBI group and in patients with severe NTBI than with mild/moderate NTBI. Moreover, in the total group, there were significant univariate associations between the FIM Total Scale and/or one or more Subscale Scores and age, preinjury patient health problems, and the PSOM, CFFS, PedsQL General Core, and Multiple Fatigue Scales. In the multivariable analysis, the FIM Total Scale was significantly associated with type and severity of injury and preinjury patient health problems., Conclusions: Two years after onset, the parent-reported that impact of ABI on the family as measured by the PedsQL FIM was considerable especially in patients with moderate/severe NTBI.

Aim: The Child and Family Follow-up Survey (CFFS) is developed to monitor long-term outcomes of children and youth with acquired brain injury (ABI). The aim of this study was to translate and adapt it into the Dutch language and to evaluate its reliability and validity., Methods: The CFFS includes the Child and Adolescent Scale of Participation (CASP), the Child and Adolescent Factors Inventory (CAFI) and the Child and Adolescent Scale of Environment (CASE). The CFFS was translated into Dutch following international guidelines and adapted. The internal consistency, validity and test-retest reliability were examined among two groups of patients (n = 140 and n = 27) in the age of 5-22 years with ABI and their parents., Results: The translation and adaptation resulted in the CFFS-DLV, Dutch language version. The CASP-DLV, CAFI-DLV and CASE-DLV had a good internal consistency, with Cronbach's alpha being 0.95, 0.89 and 0.83, respectively. There were statistically significant correlations among the three CFFS subscale scores. These scores were also significantly correlated with the total scores of the Pediatric Quality of Life Inventory (PedsQL, parent) and the Pediatric Stroke Outcome Measure, but not with the domain scores of the Children's Assessment of Participation and Enjoyment (CAPE). The test-retest reliability was good to moderate, with the intra-class correlation coefficients being 0.90 for the CASP-DLV, 0.95 for the CAFI-DLV and 0.81 for the CASE-DLV., Conclusions: The CFFS-DLV, as translation and adaptation of the CFFS into Dutch, proved to be a promising instrument to measure long-term outcomes of children and youth with ABI. Further research is needed to examine its responsiveness to change and potential in other patient groups.