Psychometric Rigor and Gaps in Transition Readiness Assessment Tools for Youth with Neurosurgical Conditions: A Systematic Mapping Review

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Nguyen, Amber Q. Nguyen, Jonathan D. Bui This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7359414/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background: Health care transition (HCT) is a critical process where adolescents and young adults with chronic medical conditions shift from pediatric to adult-oriented health systems. Despite its importance, youth with neurological and neurosurgical conditions face heightened barriers due to cognitive, psychosocial, and functional complexities. Objective: To systematically identify, categorize, and evaluate transition readiness assessment tools for youth with chronic illnesses, with a focus on those relevant to neurological and neurosurgical populations. Methods: A systematic mapping review was conducted across PubMed, Embase, Scopus, and Web of Science using predefined search terms and eligibility criteria. Included studies reported on the development or validation of tools assessing transition readiness in individuals with chronic conditions. Tools were classified as generic or condition-specific, evaluated using Terwee et al.’s psychometric quality framework. Results: 24 tools were identified: 13 generic and 11 condition-specific. Generic tools like (Transition Readiness Assessment Questionnaire) TRAQ, (Adolescent Assessment of Preparation for Transition) ADAPT, and TRANSITION-Q demonstrated strong internal consistency and construct validity but rarely assessed responsiveness or ecological validity. Disease-specific tools—particularly for spina bifida and epilepsy—showed high content relevance but limited generalizability and psychometric depth. Hydrocephalus and pediatric brain tumor survivor tools were underdeveloped. Responsiveness and test–retest reliability were evaluated in only 33% of tools; ecological validity was addressed in just two. Conclusion: While multiple tools measure transition readiness, most lack comprehensive psychometric validation, especially longitudinal and real-world application. Urgent need exists for condition-specific tools for neurosurgical populations, emphasizing responsiveness, ecological validity, and implementation science in future development. health care transition transition readiness adolescents neurological conditions neurosurgery psychometric evaluation Figures Figure 1 Figure 2 Introduction Health care transition (HCT) refers to the deliberate and coordinated process by which adolescents and young adults with chronic medical conditions move from child-centered to adult-oriented health care systems. Far from being a singular event, this transition encompasses a broader developmental process that aims to empower patients to independently manage their health care while maintaining continuity of medical support. [1] According to the American Academy of Pediatrics (AAP), the American Academy of Family Physicians, and the American College of Physicians, a well-executed transition is defined by six core elements: policy, tracking and monitoring, readiness assessment, planning, transfer of care, and transfer completion. [2] Adolescents with chronic diseases are at heightened risk for deterioration in health outcomes throughout the transition to adult care, mostly due to discontinuities in follow-up, gaps in self-management skills, and lack of support in adult services. Data from the 2016 National Survey of Children's Health in the United States found that just 17% of kids with special health care needs accomplished the main transition objectives recommended by national guidelines. [3] Poorly executed transitions have been linked to increased emergency room visits, hospitalizations, medication errors, non-adherence to treatment, diminished satisfaction with care, and even mortality. [4], [5] Neurological and neurosurgical conditions, such as spina bifida, epilepsy, hydrocephalus, and pediatric brain tumors, typically begin in early childhood and last into adulthood, necessitating lifelong monitoring, multiple surgical interventions, and multidisciplinary care. [6], [7] Youth with such conditions face a complex interplay of medical, cognitive, psychological, and social challenges that uniquely complicate the transition process. For instance, individuals with spina bifida often contend with neurogenic bladder and bowel dysfunction, mobility impairment, skin integrity concerns, and frequent need for urological and neurosurgical oversight. [8], [9] Those with epilepsy may experience episodic loss of consciousness, medication side effects, and stigma, while survivors of brain tumors often present with significant neurocognitive impairment due to tumor location or radiation therapy. [10] Many of these patients also experience deficits in executive function, adaptive behavior, or verbal communication that may interfere with their ability to engage with adult health systems independently. Adult health care providers—particularly those outside of tertiary care centers—are often ill-prepared to manage patients with ongoing neurosurgical needs, resulting in fragmentation of care and loss to follow-up. Compounding this is the absence of structured transition programs in many neurosurgical services, particularly outside North America. [7], [11] Given these complexities, transition readiness assessments have become a cornerstone of transition planning. These tools aim to evaluate an adolescent’s knowledge, skills, behaviors, and psychosocial attributes relevant to managing their condition and navigating the adult health care system. A valid transition readiness assessment allows clinicians to tailor transition education, identify at-risk youth, and monitor progress over time. [2], [12] This review therefore aims to systematically catalog and evaluate the available tools for assessing transition readiness in youth to synthesize the existing psychometric evidence supporting each tool. Methods Study Design This study was conducted as a systematic mapping review with the aim of identifying, classifying, and evaluating assessment tools used to measure transition readiness in adolescents and young adults with chronic medical conditions, particularly those with neurological and neurosurgical disorders. This approach was chosen to clarify gaps in current assessment practices and inform future tool development in the context of complex conditions that require life-long multidisciplinary management. Search Strategy A comprehensive literature search was performed using four major electronic databases: PubMed, Scopus, Embase, and Web of Science (WOS). The search covered the period from January 1966 to April 2025, ensuring inclusion of foundational instruments as well as recent innovations. The search strategy combined Medical Subject Headings (MeSH) and keyword terms with Boolean operators to capture a wide range of relevant studies. The core search string included combinations of the following terminology: “transition” OR “health care transition” OR “pediatric to adult care” AND “assessment” OR “questionnaire” OR “tool” OR “scale” OR “instrument” AND “chronic illness” OR “neurological condition” OR “neurosurgery” OR “spina bifida” OR “epilepsy” OR “hydrocephalus” OR “brain tumor” AND “psychometric” OR “validation” OR “reliability” OR “validity” OR “internal consistency” OR “construct validity”. Search filters were applied to limit the results to human studies published in English. Reference lists of eligible articles and relevant narrative reviews were also hand-searched to identify additional tools not captured by the electronic database queries. Eligibility Criteria To be included in this review, studies had to meet the following criteria. First, articles must have been published in English in a peer-reviewed journal. Second, the study must describe the development, application, or psychometric evaluation of an instrument intended to assess transition readiness, self-management, or independent functioning in adolescents or young adults aged 10 to 25 years. Third, the tools must be applicable to individuals with chronic health conditions, with particular emphasis on neurological or neurosurgical conditions, including but not limited to spina bifida, epilepsy, hydrocephalus, traumatic brain injury, and pediatric brain tumors. Fourth, studies were required to report at least one psychometric property, such as internal consistency, test-retest reliability, construct validity, or responsiveness. Studies were excluded if they focused exclusively on adult populations, did not evaluate any psychometric property, described tools unrelated to health care transition (e.g., purely clinical severity indices), or were limited to conference abstracts, editorials, letters, or grey literature. Data Extraction Data extraction was conducted systematically using a predefined coding framework. Each article was reviewed in full, and the following variables were extracted and entered into a structured matrix: the name of the assessment tool, its intended purpose, the target population or diagnostic group, the health domains or competencies assessed (e.g., appointment management, medication use, communication, adaptive functioning), and the method of administration (e.g., youth self-report, parent proxy-report, clinician-administered interview). Psychometric data were extracted in detail, including all reported metrics of reliability and validity. Where available, Cronbach’s alpha values, inter-rater reliability coefficients, test-retest results, and statistical indicators of construct or criterion validity were recorded. Sample size, population demographics, and clinical setting (e.g., outpatient clinic, rehabilitation center, school-based program) were also captured for each validation study. To organize the results, tools were categorized into two major types: Generic tools that were developed for use in broad populations of youth with chronic illnesses. Condition-specific tools designed for youth with particular neurological or neurosurgical conditions, such as spina bifida or epilepsy. Tools were further differentiated based on whether they were used in clinical practice, research settings, or educational settings, and whether they allowed youth-only, parent-only, or multi-informant reporting. Psychometric Evaluation Framework The psychometric properties of each identified tool were evaluated based on the quality criteria proposed by Terwee et al. (2007), a widely accepted framework for appraising health measurement instruments. [13] This framework includes eight core measurement properties that together reflect the overall validity, reliability, and usability of a tool. These properties are: Content Validity : Whether the instrument fully reflects the construct of interest, often based on expert consensus and involvement of the target population during development. Internal Consistency : The degree of interrelatedness among items, typically assessed using Cronbach’s alpha (acceptable threshold ≥ 0.70). Criterion Validity : The extent to which scores on the instrument correlate with an established gold standard. Construct Validity : Evidence that the tool measures the intended theoretical construct, often demonstrated through factor analysis or hypothesis testing. Test–Retest Reliability : The stability of responses over time in the absence of change in the underlying construct. Reproducibility/Agreement : The extent to which scores remain consistent across different raters or occasions. Responsiveness : The ability of the tool to detect meaningful changes over time in response to clinical interventions or maturation. Floor and Ceiling Effects : Whether a substantial proportion of respondents score at the extremes of the scale, limiting the tool’s sensitivity. Each tool was examined for the presence or absence of these eight properties, and a matrix was created to visually represent the completeness of psychometric validation. Tools with greater coverage of these criteria were considered to be more robust and clinically applicable. Results A total of 24 unique assessment tools were identified and analyzed, encompassing both generic instruments (n = 13) and disease-specific tools (n = 11). Figure 1 These tools demonstrated variable psychometric quality, population coverage, and clinical applicability. Across the tools, thematic trends in content domains and validation rigor emerged, informing the state of readiness assessment in pediatric-to-adult transition care. Generic Transition Tools Tools such as TRAQ, ADAPT, and TRANSITION-Q were extensively used and validated. TRAQ, one of the most widely adopted instruments, demonstrated strong internal consistency (α = 0.93–0.94) and was used in diverse clinical and community settings. ADAPT, derived from national Medicaid datasets, showed strong ordinal reliability (α ≥ 0.7) and supported construct validity. TRANSITION-Q was notable for its Rasch scaling, test-retest reliability (r = 0.90), and age-appropriate content. These tools typically assessed self-management, medication knowledge, appointment keeping, and provider communication. However, not all generic tools were psychometrically robust. TPT and CLSS lacked formal validation, functioning more as process checklists than assessment scales. CA HRTW THCA and Self-Management Skills Guide were guided by conceptual frameworks but lacked large-scale psychometric testing. ABAS-II and BRIEF, while not designed for transition readiness, provided valuable insights into adaptive and executive functioning, especially for youth with developmental or cognitive impairments. Other tools such as Mind the Gap, STARx, and UNC TRxANSITION Scale demonstrated multidomain strength but were often condition- or setting-specific. Meanwhile, tools such as the Six Core Elements of HCT 3.0 served more as structured frameworks than validated assessments. Table 1 Disease-Specific Transition Tools The 11 disease-specific tools targeted key clinical populations: spina bifida, epilepsy, and pediatric brain tumor survivors (PBTS). Spina bifida tools included TRAQ-SB, AMIS-II, KKIS-SB, and KIS-SB. TRAQ-SB, an adaptation of the original TRAQ, was validated in a cohort of 90 youth and demonstrated high internal consistency (α = 0.90), although a unidimensional factor structure was observed. AMIS-II, developed over a six-year longitudinal study, demonstrated excellent internal consistency (α = 0.95) and moderate-to-strong construct validity (r = 0.38–0.78). KKIS-SB, a parent-reporte d tool, focused on executive aspects of self-management and showed good reliability (α = 0.89) and four validated subscales. KIS-SB emphasized independence and adaptive behavior but has limited published validation. EpiTRAQ, adapted for epilepsy management, retained the TRAQ structure while incorporating seizure safety and medication tracking. It was validated in two separate neurology clinic cohorts totaling 683 participants and demonstrated consistency across time points. Notably, it excluded youth with intellectual disabilities. Two tools targeted PBTS populations. One utilized TRAQ in the context of workshop-based interventions and showed moderate improvements in readiness scores (Cohen’s d = 0.36). The other synthesized readiness outcomes within a neuro-oncology framework. Both efforts lacked formal psychometric testing and were considered developmental or pilot stage. Additionally, studies like Self-Management Experiences (Sawin et al., 2012) provided thematic insights but were qualitative and not designed as assessment instruments. Table 2 Psychometric Coverage Across Tools Psychometric coverage varied widely, Among the 24 tools: Internal consistency was reported in 21 tools (88%), typically using Cronbach’s alpha. Construct validity was demonstrated in 20 tools, supported by factor analysis or convergent correlation. Reliability (e.g., test-retest or interrater) was evaluated in only 8 tools (33%). Responsiveness, essential for intervention assessment, was almost entirely absent—reported in only two tools. Ecological validity, representing real-world applicability, was explicitly addressed in only two tools (ABAS-II, BRIEF). Overall, the generic tools tended to outperform disease-specific tools in terms of breadth of validation, though disease-specific tools were stronger in condition-tailored content. No tools were both fully validated and highly responsive, indicating a significant methodological and developmental gap in the current assessment landscape. Figure 2 Discussion This systematic mapping review presents the most comprehensive psychometric synthesis to date of transition readiness assessment tools applicable to youth with chronic medical conditions, including those with neurological and neurosurgical diagnoses. We identified 24 tools—13 generic and 11 disease-specific—and systematically evaluated their scope, validation status, and relevance for adolescents navigating complex medical transitions. The findings highlight both advancements in the field and substantial gaps in the development, validation, and implementation of these tools, particularly for youth with conditions such as hydrocephalus and pediatric brain tumors. Principal Findings The majority of transition readiness tools focus on domains such as appointment keeping, medication adherence, self-advocacy, and understanding of one’s medical condition. Tools like TRAQ, ADAPT, and TRANSITION-Q have emerged as leading instruments due to their psychometric robustness and widespread clinical use. [12], [14], [15] TRAQ, in particular, has served as a foundation for multiple disease-specific adaptations, including EpiTRAQ and TRAQ-SB. [14] These tools consistently report strong internal consistency and construct validity and have been translated across settings, from outpatient clinics to school-based programs. Nevertheless, a significant proportion of the tools, including TPT, CLSS, and CA HRTW THCA, lack psychometric rigor. These instruments tend to function as structured checklists rather than validated measurement tools, raising concerns about their use in guiding clinical decisions. Even among validated tools, very few reported test–retest reliability or responsiveness to clinical interventions, underscoring a key limitation in their use for outcome monitoring. This is particularly problematic given that one of the central goals of transition planning is to track progress over time and assess readiness to shift to adult care. [16], [17], [18] Disease-specific tools—such as AMIS-II, KKIS-SB, and EpiTRAQ—offer an important layer of specificity, especially for conditions like spina bifida and epilepsy where transition planning must be tailored to individual medical and functional challenges. These tools demonstrated strong internal consistency and clear domain relevance, with some evidence for construct validity. However, they are often developed in single-site studies with small sample sizes, limiting their generalizability. [19], [20], [21] Tools developed for pediatric brain tumor survivors (PBTS) and individuals with neuro-oncology or hydrocephalus remain underdeveloped, and the few pilot applications show limited psychometric grounding. Psychometric Limitations and Conceptual Gaps The evaluation matrix revealed that internal consistency and construct validity are the most commonly reported psychometric properties, consistent with trends in broader health measurement literature. [22] However, responsiveness, test–retest reliability, and ecological validity were either absent or underreported in the majority of tools. This absence is critical, as transition readiness is a dynamic construct that should ideally evolve with patient education, psychosocial development, and clinical maturity. Without these properties, the tools cannot be effectively used to evaluate the impact of transition interventions or detect changes in readiness over time. Ecological validity—defined as the extent to which a tool’s outcomes translate into real-world functioning—was explicitly addressed in only a minority of tools (ABAS-II, BRIEF, and PedsQL 4.0), which were not originally designed for transition assessment. This gap reflects a broader disconnection between psychometric design and implementation science. Tools developed without attention to real-world usability, integration into clinical workflows, or end-user feedback may have limited uptake even if they are psychometrically sound. There is a fundamental lack of instruments tailored to neurosurgical populations, including youth with hydrocephalus, traumatic brain injury, or neuro-oncological conditions. These populations often experience a combination of cognitive impairment, executive dysfunction, and social dependency that make traditional self-report transition tools insufficient. Most existing instruments presume a baseline level of health literacy, communication capacity, and behavioral insight that may not be present in these groups. Comparison With Prior Literature The findings of this review are largely consistent with earlier narrative reviews and systematic appraisals of transition assessment tools. Similar to the scoping review by Schmidt et al. (2020), we found that TRAQ remains the most widely adopted tool, with several adaptations for condition-specific use but minimal innovations beyond its core structure. [23] In contrast to the review by Jensen et al. (2018), which emphasized tool proliferation without addressing validation, our study focused specifically on psychometric robustness and found that many tools commonly cited in literature lack sufficient empirical support. [24] In opposition to findings from earlier work by Reiss et al., who noted that transition tools were rarely tailored for cognitive impairment, our review identifies a modest but growing interest in applying adaptive functioning and executive skill tools such as BRIEF, ABAS-II, and now PedsQL 4.0. [25] Nonetheless, these tools are still underutilized in transition contexts. Implications for Research and Practice From a clinical standpoint, the findings suggest that while existing tools may be appropriate for initial screening, they should be used cautiously for program evaluation or high-stakes decision-making unless longitudinal responsiveness and ecological validity have been established. The adaptation of tools like TRAQ for specific conditions is a promising direction but must be accompanied by rigorous psychometric testing across diverse settings. This review highlights three actionable priorities: Development of Neurosurgical-Specific Instruments: Novel tools are needed for underrepresented conditions such as hydrocephalus and pediatric brain tumors. These tools should account for the medical complexity, cognitive impairments, and social vulnerability common in these populations., Expansion of Psychometric Frameworks: Future studies must go beyond internal consistency and construct validity to include test–retest reliability, responsiveness, and ecological validity. Incorporating these properties will enable tools to be used not only for diagnosis but also for monitoring and quality improvement, and Implementation Research: More work is needed to understand how validated tools are adopted and used in practice. This includes integration into electronic health records, clinician training, and feedback mechanisms to improve youth engagement in transition planning. Strengths and Limitations The strengths of this review include a comprehensive search strategy across multiple databases, the application of a rigorous psychometric evaluation framework, and inclusion of both generic and condition-specific tools. The synthesis offers granular insight into validation gaps and tool applicability across clinical settings. Limitations include potential publication bias, exclusion of non-English studies, and underreporting of psychometric properties in some included articles. Additionally, given the mapping nature of the review, we did not perform meta-analysis or quality scoring using tools like COSMIN. Conclusion This mapping review identifies 24 tools designed to measure transition readiness in youth with chronic and complex conditions. While several validated instruments exist for general use, there remains a critical need for responsive, ecologically valid tools tailored to the unique needs of youth with neurological and neurosurgical conditions. A paradigm shift is needed in how transition readiness is conceptualized, measured, and implemented—one that prioritizes inclusivity, longitudinal sensitivity, and real-world usability. Such efforts will be essential to optimizing health trajectories for this medically vulnerable population. Declarations Author contributions: All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Joshua Hien Nguyen, Amber Nguyen, and Jonathan D. Bui. The first draft of the manuscript was written by Joshua Hien Nguyen and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Competing Interests: The authors declare they have no competing financial or non-financial interests relevant to the content of this article. Funding: No funds, grants, or other support were received for the preparation of this manuscript. Ethics Approval : This article is a review of existing literature and does not involve new studies with human participants, their data, or biological material. Therefore, ethical approval is not applicable. Consent to Participate This article is a review of existing literature and does not involve new studies with human participants. Therefore, informed consent to participate is not applicable. Consent to Publish: This review article does not contain any new identifiable individual data or images from human participants. Data Availability Statement: All data reviewed and analyzed in this manuscript are publicly available through the cited original publications. No new datasets were generated or analyzed for this review. 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(2019) The reliability and validity of a newly developed spina bifida-specific Transition Readiness Assessment Questionnaire: Transition Readiness Assessment Questionnaire-supplement (TRAQ-SB). J Pediatr Rehabil Med 12:415-422. https://doi.org/10.3233/PRM-180599 Carrier J. et al. (2025) Targeted Transition Readiness Workshops for Pediatric Brain Tumor Survivors: Feasibility, Acceptability, and Preliminary Effects. Curr Oncol 32:34. https://doi.org/10.3390/curroncol32010034 Wood D., Rocque B., Hopson B., Barnes K., Johnson K.R. (2019) Transition Readiness Assessment Questionnaire Spina Bifida (TRAQ-SB) specific module and its association with clinical outcomes among youth and young adults with spina bifida. J Pediatr Rehabil Med 12:405-413. https://doi.org/10.3233/PRM-180595 Bellin M.H. et al. (2011) Interrelationships of sex, level of lesion, and transition outcomes among young adults with myelomeningocele: Young Adults with Myelomeningocele. Dev Med Child Neurol 53:647-652. https://doi.org/10.1111/j.1469-8749.2011.03938.x Hopson B., Msha, Alford E.N., Zimmerman K., Blount J.P., Rocque B.G. (2019) Development of an evidence-based individualized transition plan for spina bifida. Neurosurg Focus 47:E17. https://doi.org/10.3171/2019.7.FOCUS19425 Sawin K.J., Bellin M.H., Roux G., Buran C.F., Brei T.J. (2009) The Experience of Self-Management in Adolescent Women with Spina Bifida. Rehabil Nurs 34:26-38. https://doi.org/10.1002/j.2048-7940.2009.tb00245.x Zabel T.A., Ries J., Mahone E.M., Demetrides S., Levey E., Kinsman S.L. (2003) The Kennedy Independence Scales - Spina Bifida Version: A Parent Report Rating Scale of Adaptive Functioning in Adolescents with Spina Bifida. Eur J Pediatr Surg Suppl 13:S37-S39. Tables Table 1. The key characteristics of Generic Transition Readiness Assessment Tools. Tool name Authors/Year Purpose/Population Domains Assessed Sample/Group Validation Results Limitations ADAPT Sawicki et al., 2015 [12] Adolescent-reported measure of HCT preparation Self-management, prescription counseling, transfer planning 3 large samples (2 Medicaid ~3000 each, 1 hospital n=623) Ordinal ± 0.7; Confirmatory factor analysis validated structure One domain lower consistency; early validation stage STARx and STARx-P Nazareth et al., 2018 [26] Youth and parent assessment of transition readiness Disease knowledge, self-management, communication 455 youth, 341 parents (various chronic diseases) α = 0.545 ± 0.759; PCA supported 3-factor structure Moderate reliability; more testing needed for parent version Mind the Gap Shaw et al., 2007 [27] Satisfaction with transitional healthcare in JIA Environment, provider, process 308 adolescents, 303 parents from 10 UK centers α = 0.91 ± 0.94; three-factor model validated Developed for JIA; limited generalizability BRIEF Isquith et al., 2013 [28] Behavioral measure of executive function Inhibition, shift, working memory, etc. Children in neuropsychological settings Extensively validated; high internal consistency Not transition-specific; for broader EF CLSS Barnard et al., 1991 [16] Assess life and self-care skills in community Independence, hygiene, tasks, communication Adolescents with developmental conditions Research supported; psychometrics not extensively reported Limited current validation and publications Six Core Elements of HCT 3.0 Got Transition, 2020 [29] Guide transition practices in clinics Policy, tracking, readiness, planning, transfer, feedback Youth/Young adults in medical systems Framework-based; implementation evidence only Not a psychometric tool; qualitative evaluation UNC TRxANSITION Scale Ferris et al., 2012 [30] Clinician-rated multidomain transition tool 10 domains: Rx, Adherence, Nutrition, etc. 185 youth with chronic illnesses r = 0.71; strong construct/content validity Requires interviewer; longer administration TRANSITION-Q Klassen et al., 2015 [15] Youth self-report transition skills readiness Self-management behaviors 337 youth with chronic illness ± 0.85; test-retest r = 0.90; Rasch modeled Narrow scope; no planning/transfer content CA HRTW THCA Betz et al., 2000 & 2003 [18] Developmental health care skill guidelines Self-care by developmental stage Children and teens with special health needs Developmentally grounded; qualitative framework Not a formal psychometric scale TRAQ Cleverley et al., 2022 [14] Youth transition readiness (mental health) Appointments, tracking health, Rx, daily tasks 237 youth in mental health outpatient clinics ± 0.86; CFA supported 5-factor model Some subscales weaker; moderate convergent validity ABAS-II Richardson et al. 2005 [31] Norm-referenced adaptive behavior assessment (ages =89) Communication, functional academics, self-direction, leisure, work, social Standardization sample of 7,370 individuals Cronbach ± 0.90 (GAC); strong test-retest and interrater reliability Not HCT-specific; may require clinical interpretation Self-Management Skills Assessment Guide Williams et al., 2010 [32] Evaluate readiness among Canadian youth with chronic illness Medical understanding, independence, care participation 49 youth (11 ± 18 yrs) and parents at Alberta Children’s Hospital Moderate youth-parent agreement; correlated with adaptive skills Preliminary validation; limited demographic variance Transition Planning Tool (TPT) Wiemann et al., 2015 [17] EMR-based tool for transition planning in youth with special health care needs aged 16 ± 25 Condition knowledge, medication management, self-advocacy, planning, independence, family support 182 youth (303 encounters), 25 providers in 4 subspecialty clinics No formal psychometric testing; usability and provider satisfaction via PDSA cycles No reliability/validity data; limited generalizability; underuse in busy settings Table 2. The key characteristics of Disease-Specific Transition Readiness Assessment Tools. Tool name Authors/Year Purpose/Population Domains Assessed Sample/Group Validation Results Limitations TRAQ-SB Johnson et al., 2019 [33] Measure transition readiness in adolescents with spina bifida Self-management, continence, shunt awareness, skin care N = 90, youth aged 12 ±25 at a spina bifida clinic Cronbach’s α = 0.90; strong correlation with TRAQ and age Single-center; only one factor retained AMIS-II Ridosh et al., 2021 [19] Evaluate self-management and independence in AYA with spina bifida Condition self-management and independent living N = 64 AYA (18 ± 25 yrs); parent-report comparison from 6 years earlier Excellent internal consistency (α = 0.95); strong construct validity (r = 0.378 ± 0.777) Primarily descriptive; limited diversity in prior studies KKIS-SB Jacobson et al., 2013 [20] Measure executive components of self-management for SB Routine initiation, prospective memory, self-care N = 100 youth with SB (ages 10 ± 29), parent-reported Cronbach ± 0.89; 4-factor model, strong construct validity No youth self-report; U.S.-only validation EpiTRAQ Clark et al., 2020 [21] Assess epilepsy-specific transition readiness for AYA without intellectual disability Medication management, seizure safety, healthcare navigation N = 683 (302 + 381), ages 16 ± 26; tested in neurology clinics High internal consistency; stability across two waves; strong adaptation from TRAQ Limited applicability to those with cognitive impairment TRAQ + PBTS Workshops Carrier et al., 2025 [34] Workshop-based transition readiness program for pediatric brain tumor survivors Social, cognitive, disease self-management N = 12 dyads (PBTS + parents), age 14+, pre/post pilot design Clinically meaningful improvements; moderate effect size (d = 0.36) Pilot; low recruitment; small sample TRAQ-SB Wood et al., 2019 [35] To assess spina bifida-specific self-management skills among youth and young adults aged 12–25 Urine/stool continence, skin care, shunt awareness N = 90 youth with spina bifida in NSBPR clinics Internal consistency (α = 0.91); predictive validity for urinary incontinence No association with stool or skin outcomes; small sample; requires broader validation AMIS-II Bellin et al., 2011 [36] To evaluate self-management and independence among young adults with myelomeningocele Condition management, daily living skills, autonomy N = 50, ages 18–25 from 5 US specialty clinics Clinical interview tool; mean AMIS-II scores reflect deficits in condition management Descriptive, limited psychometric analysis reported Individualized Transition Plan (ITP) Hopson et al., 2019 [37] To individualize transition plans for adolescents with spina bifida Education, bowel management, patient/family goals N = 32 patients (mean age 16.4), interdisciplinary clinic Not psychometrically validated; descriptive goal tracking Limited sample; retrospective review; no standardized outcome evaluation AMIS-II (extended study) Mahmood et al., 2011 [9] To correlate self-management with preventable conditions and health service use in young adults with myelomeningocele Skin and bladder care, condition knowledge, ADLs N = 38, aged 18–25, 5 SB clinics Lower AMIS-II scores associated with more UTIs and hospitalizations Small sample; cross-sectional design; limited generalizability Self-Management Experiences (Qualitative Framework) Sawin et al., 2012 [38] To explore the lived experience of self-management in adolescent women with spina bifida Specialized knowledge, general independence tasks, parental influence, advocacy 31 adolescent women with SB, aged 12–21 years Qualitative thematic analysis; not a psychometric tool; themes triangulated using content coding and expert review Not a standardized instrument; small, homogeneous sample; qualitative outcomes not generalizable Kennedy Independence Scales - Spina Bifida (KIS-SB) Zabel et al., 2003 [39] Parent-reported measure of executive function and independence in youth with spina bifida Medical, educational/pre-vocational, community functioning Adolescents with SB; exact sample not specified in the summary Psychometric analysis ongoing; structured scoring format Limited published validation results; based on parental perception Additional Declarations No competing interests reported. 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13:05:21","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":123424,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7359414/v1/9b107ad297f3e2c61960738e.html"},{"id":92088881,"identity":"6f1d015b-532e-455c-99b2-d05e0c20fb03","added_by":"auto","created_at":"2025-09-24 13:21:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51118,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA Flow Diagram of Study Selection Process.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7359414/v1/b75b2b45e810d68ecf606730.png"},{"id":92090011,"identity":"b4ecac48-0521-4d01-836e-c75cd56ef548","added_by":"auto","created_at":"2025-09-24 13:29:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":80398,"visible":true,"origin":"","legend":"\u003cp\u003ePsychometric Property Coverage Across Identified Tools.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7359414/v1/36049a3e2f8fc431e79c318e.png"},{"id":92090012,"identity":"9f71aaaf-8b35-4e03-8472-2377a53f6152","added_by":"auto","created_at":"2025-09-24 13:29:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":878824,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7359414/v1/23ce9ae4-4309-4e5e-a597-680c1a290cc7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Psychometric Rigor and Gaps in Transition Readiness Assessment Tools for Youth with Neurosurgical Conditions: A Systematic Mapping Review","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHealth care transition (HCT) refers to the deliberate and coordinated process by which adolescents and young adults with chronic medical conditions move from child-centered to adult-oriented health care systems. Far from being a singular event, this transition encompasses a broader developmental process that aims to empower patients to independently manage their health care while maintaining continuity of medical support. [1] According to the American Academy of Pediatrics (AAP), the American Academy of Family Physicians, and the American College of Physicians, a well-executed transition is defined by six core elements: policy, tracking and monitoring, readiness assessment, planning, transfer of care, and transfer completion. [2]\u003c/p\u003e\n\u003cp\u003eAdolescents with chronic diseases are at heightened risk for deterioration in health outcomes throughout the transition to adult care, mostly due to discontinuities in follow-up, gaps in self-management skills, and lack of support in adult services. \u0026nbsp;Data from the 2016 National Survey of Children\u0026apos;s Health in the United States found that just 17% of kids with special health care needs accomplished the main transition objectives recommended by national guidelines. [3] Poorly executed transitions have been linked to increased emergency room visits, hospitalizations, medication errors, non-adherence to treatment, diminished satisfaction with care, and even mortality. [4], [5] \u0026nbsp;Neurological and neurosurgical conditions, such as spina bifida, epilepsy, hydrocephalus, and pediatric brain tumors, typically begin in early childhood and last into adulthood, necessitating lifelong monitoring, multiple surgical interventions, and multidisciplinary care. [6], [7] Youth with such conditions face a complex interplay of medical, cognitive, psychological, and social challenges that uniquely complicate the transition process. For instance, individuals with spina bifida often contend with neurogenic bladder and bowel dysfunction, mobility impairment, skin integrity concerns, and frequent need for urological and neurosurgical oversight. [8], [9] Those with epilepsy may experience episodic loss of consciousness, medication side effects, and stigma, while survivors of brain tumors often present with significant neurocognitive impairment due to tumor location or radiation therapy. [10]\u003c/p\u003e\n\u003cp\u003eMany of these patients also experience deficits in executive function, adaptive behavior, or verbal communication that may interfere with their ability to engage with adult health systems independently. Adult health care providers\u0026mdash;particularly those outside of tertiary care centers\u0026mdash;are often ill-prepared to manage patients with ongoing neurosurgical needs, resulting in fragmentation of care and loss to follow-up. Compounding this is the absence of structured transition programs in many neurosurgical services, particularly outside North America. [7], [11] Given these complexities, transition readiness assessments have become a cornerstone of transition planning. These tools aim to evaluate an adolescent\u0026rsquo;s knowledge, skills, behaviors, and psychosocial attributes relevant to managing their condition and navigating the adult health care system. A valid transition readiness assessment allows clinicians to tailor transition education, identify at-risk youth, and monitor progress over time. [2], [12] This review therefore aims to systematically catalog and evaluate the available tools for assessing transition readiness in youth to synthesize the existing psychometric evidence supporting each tool.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eStudy Design\u003c/h2\u003e\n\u003cp\u003eThis study was conducted as a systematic mapping review with the aim of identifying, classifying, and evaluating assessment tools used to measure transition readiness in adolescents and young adults with chronic medical conditions, particularly those with neurological and neurosurgical disorders. This approach was chosen to clarify gaps in current assessment practices and inform future tool development in the context of complex conditions that require life-long multidisciplinary management.\u003c/p\u003e\n\u003ch2 id=\"_Toc198460779\"\u003eSearch Strategy\u003c/h2\u003e\n\u003cp\u003eA comprehensive literature search was performed using four major electronic databases: PubMed, Scopus, Embase, and Web of Science (WOS). The search covered the period from January 1966 to April 2025, ensuring inclusion of foundational instruments as well as recent innovations. The search strategy combined Medical Subject Headings (MeSH) and keyword terms with Boolean operators to capture a wide range of relevant studies. The core search string included combinations of the following terminology: \u0026ldquo;transition\u0026rdquo; OR \u0026ldquo;health care transition\u0026rdquo; OR \u0026ldquo;pediatric to adult care\u0026rdquo; AND \u0026ldquo;assessment\u0026rdquo; OR \u0026ldquo;questionnaire\u0026rdquo; OR \u0026ldquo;tool\u0026rdquo; OR \u0026ldquo;scale\u0026rdquo; OR \u0026ldquo;instrument\u0026rdquo; AND \u0026ldquo;chronic illness\u0026rdquo; OR \u0026ldquo;neurological condition\u0026rdquo; OR \u0026ldquo;neurosurgery\u0026rdquo; OR \u0026ldquo;spina bifida\u0026rdquo; OR \u0026ldquo;epilepsy\u0026rdquo; OR \u0026ldquo;hydrocephalus\u0026rdquo; OR \u0026ldquo;brain tumor\u0026rdquo; AND \u0026ldquo;psychometric\u0026rdquo; OR \u0026ldquo;validation\u0026rdquo; OR \u0026ldquo;reliability\u0026rdquo; OR \u0026ldquo;validity\u0026rdquo; OR \u0026ldquo;internal consistency\u0026rdquo; OR \u0026ldquo;construct validity\u0026rdquo;. Search filters were applied to limit the results to human studies published in English. Reference lists of eligible articles and relevant narrative reviews were also hand-searched to identify additional tools not captured by the electronic database queries.\u003c/p\u003e\n\u003ch2 id=\"_Toc198460780\"\u003eEligibility Criteria\u003c/h2\u003e\n\u003cp\u003eTo be included in this review, studies had to meet the following criteria. First, articles must have been published in English in a peer-reviewed journal. Second, the study must describe the development, application, or psychometric evaluation of an instrument intended to assess transition readiness, self-management, or independent functioning in adolescents or young adults aged 10 to 25 years. Third, the tools must be applicable to individuals with chronic health conditions, with particular emphasis on neurological or neurosurgical conditions, including but not limited to spina bifida, epilepsy, hydrocephalus, traumatic brain injury, and pediatric brain tumors. Fourth, studies were required to report at least one psychometric property, such as internal consistency, test-retest reliability, construct validity, or responsiveness.\u003c/p\u003e\n\u003cp\u003eStudies were excluded if they focused exclusively on adult populations, did not evaluate any psychometric property, described tools unrelated to health care transition (e.g., purely clinical severity indices), or were limited to conference abstracts, editorials, letters, or grey literature.\u003c/p\u003e\n\u003ch2 id=\"_Toc198460781\"\u003eData Extraction\u003c/h2\u003e\n\u003cp\u003eData extraction was conducted systematically using a predefined coding framework. Each article was reviewed in full, and the following variables were extracted and entered into a structured matrix: the name of the assessment tool, its intended purpose, the target population or diagnostic group, the health domains or competencies assessed (e.g., appointment management, medication use, communication, adaptive functioning), and the method of administration (e.g., youth self-report, parent proxy-report, clinician-administered interview).\u003c/p\u003e\n\u003cp\u003ePsychometric data were extracted in detail, including all reported metrics of reliability and validity. Where available, Cronbach\u0026rsquo;s alpha values, inter-rater reliability coefficients, test-retest results, and statistical indicators of construct or criterion validity were recorded. Sample size, population demographics, and clinical setting (e.g., outpatient clinic, rehabilitation center, school-based program) were also captured for each validation study. To organize the results, tools were categorized into two major types:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eGeneric tools that were developed for use in broad populations of youth with chronic illnesses.\u003c/li\u003e\n \u003cli\u003eCondition-specific tools designed for youth with particular neurological or neurosurgical conditions, such as spina bifida or epilepsy.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eTools were further differentiated based on whether they were used in clinical practice, research settings, or educational settings, and whether they allowed youth-only, parent-only, or multi-informant reporting.\u003c/p\u003e\n\u003ch2 id=\"_Toc198460782\"\u003ePsychometric Evaluation Framework\u003c/h2\u003e\n\u003cp\u003eThe psychometric properties of each identified tool were evaluated based on the quality criteria proposed by Terwee et al. (2007), a widely accepted framework for appraising health measurement instruments. [13] This framework includes eight core measurement properties that together reflect the overall validity, reliability, and usability of a tool.\u003c/p\u003e\n\u003cp\u003eThese properties are:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eContent Validity\u003c/strong\u003e: Whether the instrument fully reflects the construct of interest, often based on expert consensus and involvement of the target population during development.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eInternal Consistency\u003c/strong\u003e: The degree of interrelatedness among items, typically assessed using Cronbach\u0026rsquo;s alpha (acceptable threshold \u0026ge; 0.70).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eCriterion Validity\u003c/strong\u003e: The extent to which scores on the instrument correlate with an established gold standard.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eConstruct Validity\u003c/strong\u003e: Evidence that the tool measures the intended theoretical construct, often demonstrated through factor analysis or hypothesis testing.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eTest\u0026ndash;Retest Reliability\u003c/strong\u003e: The stability of responses over time in the absence of change in the underlying construct.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eReproducibility/Agreement\u003c/strong\u003e: The extent to which scores remain consistent across different raters or occasions.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eResponsiveness\u003c/strong\u003e: The ability of the tool to detect meaningful changes over time in response to clinical interventions or maturation.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eFloor and Ceiling Effects\u003c/strong\u003e: Whether a substantial proportion of respondents score at the extremes of the scale, limiting the tool\u0026rsquo;s sensitivity.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eEach tool was examined for the presence or absence of these eight properties, and a matrix was created to visually represent the completeness of psychometric validation. Tools with greater coverage of these criteria were considered to be more robust and clinically applicable.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 24 unique assessment tools were identified and analyzed, encompassing both generic\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003einstruments (n = 13) and disease-specific tools (n = 11). Figure 1\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese tools demonstrated variable psychometric quality, population coverage, and clinical applicability. Across the tools, thematic trends in content domains and validation rigor emerged, informing the state of readiness assessment in pediatric-to-adult transition care.\u003c/p\u003e\n\u003ch2 id=\"_Toc198460784\"\u003eGeneric Transition Tools\u003c/h2\u003e\n\u003cp\u003eTools such as TRAQ, ADAPT, and TRANSITION-Q were extensively used and validated. TRAQ, one of the most widely adopted instruments, demonstrated strong internal consistency (\u0026alpha; = 0.93\u0026ndash;0.94) and was used in diverse clinical and community settings. ADAPT, derived from national Medicaid datasets, showed strong ordinal reliability (\u0026alpha; \u0026ge; 0.7) and supported construct validity. TRANSITION-Q was notable for its Rasch scaling, test-retest reliability (r = 0.90), and age-appropriate content. These tools typically assessed self-management, medication knowledge, appointment keeping, and provider communication.\u003c/p\u003e\n\u003cp\u003eHowever, not all generic tools were psychometrically robust. TPT and CLSS lacked formal validation, functioning more as process checklists than assessment scales. CA HRTW THCA and Self-Management Skills Guide were guided by conceptual frameworks but lacked large-scale psychometric testing. ABAS-II and BRIEF, while not designed for transition readiness, provided valuable insights into adaptive and executive functioning, especially for youth with developmental or cognitive impairments. Other tools such as Mind the Gap, STARx, and UNC TRxANSITION Scale demonstrated multidomain strength but were often condition- or setting-specific. Meanwhile, tools such as the Six Core Elements of HCT 3.0 served more as structured frameworks than validated assessments. Table 1\u003c/p\u003e\n\u003ch2 id=\"_Toc198460785\"\u003eDisease-Specific Transition Tools\u003c/h2\u003e\n\u003cp\u003eThe 11 disease-specific tools targeted key clinical populations: spina bifida, epilepsy, and pediatric brain tumor survivors (PBTS). Spina bifida tools included TRAQ-SB, AMIS-II, KKIS-SB, and KIS-SB. TRAQ-SB, an adaptation of the original TRAQ, was validated in a cohort of 90 youth and demonstrated high internal consistency (\u0026alpha; = 0.90), although a unidimensional factor structure was observed. AMIS-II, developed over a six-year longitudinal study, demonstrated excellent internal consistency (\u0026alpha; = 0.95) and moderate-to-strong construct validity (r = 0.38\u0026ndash;0.78). KKIS-SB, a parent-reporte\u0026nbsp;d tool, focused on executive aspects of self-management and showed good reliability (\u0026alpha; = 0.89) and four validated subscales. KIS-SB emphasized independence and adaptive behavior but has limited published validation.\u003c/p\u003e\n\u003cp\u003eEpiTRAQ, adapted for epilepsy management, retained the TRAQ structure while incorporating seizure safety and medication tracking. It was validated in two separate neurology clinic cohorts totaling 683 participants and demonstrated consistency across time points. Notably, it excluded youth with intellectual disabilities.\u003c/p\u003e\n\u003cp\u003eTwo tools targeted PBTS populations. One utilized TRAQ in the context of workshop-based interventions and showed moderate improvements in readiness scores (Cohen\u0026rsquo;s d = 0.36). The other synthesized readiness outcomes within a neuro-oncology framework. Both efforts lacked formal psychometric testing and were considered developmental or pilot stage. Additionally, studies like Self-Management Experiences (Sawin et al., 2012) provided thematic insights but were qualitative and not designed as assessment instruments. Table 2\u003c/p\u003e\n\u003ch2 id=\"_Toc198460786\"\u003ePsychometric Coverage Across Tools\u003c/h2\u003e\n\u003cp\u003ePsychometric coverage varied widely, Among the 24 tools:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eInternal consistency was reported in 21 tools (88%), typically using Cronbach\u0026rsquo;s alpha.\u003c/li\u003e\n \u003cli\u003eConstruct validity was demonstrated in 20 tools, supported by factor analysis or convergent correlation.\u003c/li\u003e\n \u003cli\u003eReliability (e.g., test-retest or interrater) was evaluated in only 8 tools (33%).\u003c/li\u003e\n \u003cli\u003eResponsiveness, essential for intervention assessment, was almost entirely absent\u0026mdash;reported in only two tools.\u003c/li\u003e\n \u003cli\u003eEcological validity, representing real-world applicability, was explicitly addressed in only two tools (ABAS-II, BRIEF).\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eOverall, the generic tools tended to outperform disease-specific tools in terms of breadth of validation, though disease-specific tools were stronger in condition-tailored content. No tools were both fully validated and highly responsive, indicating a significant methodological and developmental gap in the current assessment landscape. Figure 2\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis systematic mapping review presents the most comprehensive psychometric synthesis to date of transition readiness assessment tools applicable to youth with chronic medical conditions, including those with neurological and neurosurgical diagnoses. We identified 24 tools\u0026mdash;13 generic and 11 disease-specific\u0026mdash;and systematically evaluated their scope, validation status, and relevance for adolescents navigating complex medical transitions. The findings highlight both advancements in the field and substantial gaps in the development, validation, and implementation of these tools, particularly for youth with conditions such as hydrocephalus and pediatric brain tumors.\u003c/p\u003e\n\u003ch2 id=\"_Toc198460788\"\u003ePrincipal Findings\u003c/h2\u003e\n\u003cp\u003eThe majority of transition readiness tools focus on domains such as appointment keeping, medication adherence, self-advocacy, and understanding of one\u0026rsquo;s medical condition. Tools like TRAQ, ADAPT, and TRANSITION-Q have emerged as leading instruments due to their psychometric robustness and widespread clinical use. [12], [14], [15] TRAQ, in particular, has served as a foundation for multiple disease-specific adaptations, including EpiTRAQ and TRAQ-SB. [14] These tools consistently report strong internal consistency and construct validity and have been translated across settings, from outpatient clinics to school-based programs.\u003c/p\u003e\n\u003cp\u003eNevertheless, a significant proportion of the tools, including TPT, CLSS, and CA HRTW THCA, lack psychometric rigor. These instruments tend to function as structured checklists rather than validated measurement tools, raising concerns about their use in guiding clinical decisions. Even among validated tools, very few reported test\u0026ndash;retest reliability or responsiveness to clinical interventions, underscoring a key limitation in their use for outcome monitoring. This is particularly problematic given that one of the central goals of transition planning is to track progress over time and assess readiness to shift to adult care. [16], [17], [18] Disease-specific tools\u0026mdash;such as AMIS-II, KKIS-SB, and EpiTRAQ\u0026mdash;offer an important layer of specificity, especially for conditions like spina bifida and epilepsy where transition planning must be tailored to individual medical and functional challenges. These tools demonstrated strong internal consistency and clear domain relevance, with some evidence for construct validity. However, they are often developed in single-site studies with small sample sizes, limiting their generalizability. [19], [20], [21] Tools developed for pediatric brain tumor survivors (PBTS) and individuals with neuro-oncology or hydrocephalus remain underdeveloped, and the few pilot applications show limited psychometric grounding.\u0026nbsp;\u003c/p\u003e\n\u003ch2 id=\"_Toc198460789\"\u003ePsychometric Limitations and Conceptual Gaps\u003c/h2\u003e\n\u003cp\u003eThe evaluation matrix revealed that internal consistency and construct validity are the most commonly reported psychometric properties, consistent with trends in broader health measurement literature. [22] However, responsiveness, test\u0026ndash;retest reliability, and ecological validity were either absent or underreported in the majority of tools. This absence is critical, as transition readiness is a dynamic construct that should ideally evolve with patient education, psychosocial development, and clinical maturity. Without these properties, the tools cannot be effectively used to evaluate the impact of transition interventions or detect changes in readiness over time.\u003c/p\u003e\n\u003cp\u003eEcological validity\u0026mdash;defined as the extent to which a tool\u0026rsquo;s outcomes translate into real-world functioning\u0026mdash;was explicitly addressed in only a minority of tools (ABAS-II, BRIEF, and PedsQL 4.0), which were not originally designed for transition assessment. This gap reflects a broader disconnection between psychometric design and implementation science. Tools developed without attention to real-world usability, integration into clinical workflows, or end-user feedback may have limited uptake even if they are psychometrically sound. There is a fundamental lack of instruments tailored to neurosurgical populations, including youth with hydrocephalus, traumatic brain injury, or neuro-oncological conditions. These populations often experience a combination of cognitive impairment, executive dysfunction, and social dependency that make traditional self-report transition tools insufficient. Most existing instruments presume a baseline level of health literacy, communication capacity, and behavioral insight that may not be present in these groups.\u0026nbsp;\u003c/p\u003e\n\u003ch2 id=\"_Toc198460790\"\u003eComparison With Prior Literature\u003c/h2\u003e\n\u003cp\u003eThe findings of this review are largely consistent with earlier narrative reviews and systematic appraisals of transition assessment tools. Similar to the scoping review by Schmidt et al. (2020), we found that TRAQ remains the most widely adopted tool, with several adaptations for condition-specific use but minimal innovations beyond its core structure. [23] In contrast to the review by Jensen et al. (2018), which emphasized tool proliferation without addressing validation, our study focused specifically on psychometric robustness and found that many tools commonly cited in literature lack sufficient empirical support. [24] In opposition to findings from earlier work by Reiss et al., who noted that transition tools were rarely tailored for cognitive impairment, our review identifies a modest but growing interest in applying adaptive functioning and executive skill tools such as BRIEF, ABAS-II, and now PedsQL 4.0. [25] Nonetheless, these tools are still underutilized in transition contexts.\u003c/p\u003e\n\u003ch2 id=\"_Toc198460791\"\u003eImplications for Research and Practice\u003c/h2\u003e\n\u003cp\u003eFrom a clinical standpoint, the findings suggest that while existing tools may be appropriate for initial screening, they should be used cautiously for program evaluation or high-stakes decision-making unless longitudinal responsiveness and ecological validity have been established. The adaptation of tools like TRAQ for specific conditions is a promising direction but must be accompanied by rigorous psychometric testing across diverse settings. This review highlights three actionable priorities: Development of Neurosurgical-Specific Instruments: Novel tools are needed for underrepresented conditions such as hydrocephalus and pediatric brain tumors. These tools should account for the medical complexity, cognitive impairments, and social vulnerability common in these populations., Expansion of Psychometric Frameworks: Future studies must go beyond internal consistency and construct validity to include test\u0026ndash;retest reliability, responsiveness, and ecological validity. Incorporating these properties will enable tools to be used not only for diagnosis but also for monitoring and quality improvement, and Implementation Research: More work is needed to understand how validated tools are adopted and used in practice. This includes integration into electronic health records, clinician training, and feedback mechanisms to improve youth engagement in transition planning.\u003c/p\u003e\n\u003ch2 id=\"_Toc198460792\"\u003eStrengths and Limitations\u003c/h2\u003e\n\u003cp\u003eThe strengths of this review include a comprehensive search strategy across multiple databases, the application of a rigorous psychometric evaluation framework, and inclusion of both generic and condition-specific tools. The synthesis offers granular insight into validation gaps and tool applicability across clinical settings.\u003c/p\u003e\n\u003cp\u003eLimitations include potential publication bias, exclusion of non-English studies, and underreporting of psychometric properties in some included articles. Additionally, given the mapping nature of the review, we did not perform meta-analysis or quality scoring using tools like COSMIN.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis mapping review identifies 24 tools designed to measure transition readiness in youth with chronic and complex conditions. While several validated instruments exist for general use, there remains a critical need for responsive, ecologically valid tools tailored to the unique needs of youth with neurological and neurosurgical conditions. A paradigm shift is needed in how transition readiness is conceptualized, measured, and implemented\u0026mdash;one that prioritizes inclusivity, longitudinal sensitivity, and real-world usability. Such efforts will be essential to optimizing health trajectories for this medically vulnerable population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Joshua Hien Nguyen, Amber Nguyen, and Jonathan D. Bui. The first draft of the manuscript was written by Joshua Hien Nguyen and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u0026nbsp;\u003c/strong\u003eThe authors declare they have no competing financial or non-financial interests relevant to the content of this article.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNo funds, grants, or other support were received for the preparation of this manuscript.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e: This article is a review of existing literature and does not involve new studies with human participants, their data, or biological material. Therefore, ethical approval is not applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e This article is a review of existing literature and does not involve new studies with human participants. Therefore, informed consent to participate is not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish:\u0026nbsp;\u003c/strong\u003eThis review article does not contain any new identifiable individual data or images from human participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eAll data reviewed and analyzed in this manuscript are publicly available through the cited original publications. No new datasets were generated or analyzed for this review.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and/or Code Availability:\u0026nbsp;\u003c/strong\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number:\u003c/strong\u003e Not applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBlum R.W. et al. (1993) Transition from child-centered to adult health-care systems for adolescents with chronic conditions. J Adolesc Health 14:570-576. https://doi.org/10.1016/1054-139X(93)90143-D\u003c/li\u003e\n\u003cli\u003eWhite P.H., Cooley W.C. et al. (2018) Supporting the Health Care Transition From Adolescence to Adulthood in the Medical Home. Pediatrics 142:e20182587. https://doi.org/10.1542/peds.2018-2587\u003c/li\u003e\n\u003cli\u003eLebrun-Harris L.A. et al. (2018) Transition Planning Among US Youth With and Without Special Health Care Needs. 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(2011) Measurement of medical self-management and transition readiness among Canadian adolescents with special health care needs. International Journal of Child and Adolescent Health 3:527-535.\u003c/li\u003e\n\u003cli\u003eJohnson K., Rocque B., Hopson B., Barnes K., Omoike O.E., Wood D. (2019) The reliability and validity of a newly developed spina bifida-specific Transition Readiness Assessment Questionnaire: Transition Readiness Assessment Questionnaire-supplement (TRAQ-SB). J Pediatr Rehabil Med 12:415-422. https://doi.org/10.3233/PRM-180599\u003c/li\u003e\n\u003cli\u003eCarrier J. et al. (2025) Targeted Transition Readiness Workshops for Pediatric Brain Tumor Survivors: Feasibility, Acceptability, and Preliminary Effects. Curr Oncol 32:34. https://doi.org/10.3390/curroncol32010034\u003c/li\u003e\n\u003cli\u003eWood D., Rocque B., Hopson B., Barnes K., Johnson K.R. (2019) Transition Readiness Assessment Questionnaire Spina Bifida (TRAQ-SB) specific module and its association with clinical outcomes among youth and young adults with spina bifida. J Pediatr Rehabil Med 12:405-413. https://doi.org/10.3233/PRM-180595\u003c/li\u003e\n\u003cli\u003eBellin M.H. et al. (2011) Interrelationships of sex, level of lesion, and transition outcomes among young adults with myelomeningocele: Young Adults with Myelomeningocele. Dev Med Child Neurol 53:647-652. https://doi.org/10.1111/j.1469-8749.2011.03938.x\u003c/li\u003e\n\u003cli\u003eHopson B., Msha, Alford E.N., Zimmerman K., Blount J.P., Rocque B.G. (2019) Development of an evidence-based individualized transition plan for spina bifida. Neurosurg Focus 47:E17. https://doi.org/10.3171/2019.7.FOCUS19425\u003c/li\u003e\n\u003cli\u003eSawin K.J., Bellin M.H., Roux G., Buran C.F., Brei T.J. (2009) The Experience of Self-Management in Adolescent Women with Spina Bifida. Rehabil Nurs 34:26-38. https://doi.org/10.1002/j.2048-7940.2009.tb00245.x\u003c/li\u003e\n\u003cli\u003eZabel T.A., Ries J., Mahone E.M., Demetrides S., Levey E., Kinsman S.L. (2003) The Kennedy Independence Scales - Spina Bifida Version: A Parent Report Rating Scale of Adaptive Functioning in Adolescents with Spina Bifida. Eur J Pediatr Surg Suppl 13:S37-S39.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. The key characteristics of Generic Transition Readiness Assessment Tools.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"754\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eTool name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eAuthors/Year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003ePurpose/Population\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003eDomains Assessed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eSample/Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003eValidation Results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eLimitations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eADAPT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eSawicki et al., 2015\u0026nbsp;[12]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eAdolescent-reported measure of HCT preparation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003eSelf-management, prescription counseling, transfer planning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003e3 large samples (2 Medicaid ~3000 each, 1 hospital n=623)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003eOrdinal \u0026plusmn; 0.7; Confirmatory factor analysis validated structure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eOne domain lower consistency; early validation stage\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eSTARx and STARx-P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eNazareth et al., 2018\u0026nbsp;[26]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eYouth and parent assessment of transition readiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003eDisease knowledge, self-management, communication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003e455 youth, 341 parents (various chronic diseases)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003e\u0026Icirc;\u0026plusmn; = 0.545 \u0026plusmn; 0.759; PCA supported 3-factor structure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eModerate reliability; more testing needed for parent version\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eMind the Gap\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eShaw et al., 2007\u0026nbsp;[27]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eSatisfaction with transitional healthcare in JIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003eEnvironment, provider, process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003e308 adolescents, 303 parents from 10 UK centers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003e\u0026Icirc;\u0026plusmn; = 0.91 \u0026plusmn; 0.94; three-factor model validated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eDeveloped for JIA; limited generalizability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eBRIEF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eIsquith et al., 2013\u0026nbsp;[28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eBehavioral measure of executive function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003eInhibition, shift, working memory, etc.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eChildren in neuropsychological settings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003eExtensively validated; high internal consistency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eNot transition-specific; for broader EF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eCLSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eBarnard et al., 1991\u0026nbsp;[16]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eAssess life and self-care skills in community\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003eIndependence, hygiene, tasks, communication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eAdolescents with developmental conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003eResearch supported; psychometrics not extensively reported\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eLimited current validation and publications\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eSix Core Elements of HCT 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eGot Transition, 2020\u0026nbsp;[29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eGuide transition practices in clinics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003ePolicy, tracking, readiness, planning, transfer, feedback\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eYouth/Young adults in medical systems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003eFramework-based; implementation evidence only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eNot a psychometric tool; qualitative evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eUNC TRxANSITION Scale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eFerris et al., 2012\u0026nbsp;[30]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eClinician-rated multidomain transition tool\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003e10 domains: Rx, Adherence, Nutrition, etc.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003e185 youth with chronic illnesses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003er = 0.71; strong construct/content validity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eRequires interviewer; longer administration\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eTRANSITION-Q\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eKlassen et al., 2015\u0026nbsp;[15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eYouth self-report transition skills readiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003eSelf-management behaviors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003e337 youth with chronic illness\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003e\u0026plusmn; 0.85; test-retest r = 0.90; Rasch modeled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eNarrow scope; no planning/transfer content\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eCA HRTW THCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eBetz et al., 2000 \u0026amp; 2003\u0026nbsp;[18]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eDevelopmental health care skill guidelines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003eSelf-care by developmental stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eChildren and teens with special health needs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003eDevelopmentally grounded; qualitative framework\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eNot a formal psychometric scale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eTRAQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eCleverley et al., 2022\u0026nbsp;[14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eYouth transition readiness (mental health)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003eAppointments, tracking health, Rx, daily tasks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003e237 youth in mental health outpatient clinics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003e\u0026plusmn; 0.86; CFA supported 5-factor model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eSome subscales weaker; moderate convergent validity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eABAS-II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eRichardson et al. 2005\u0026nbsp;[31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eNorm-referenced adaptive behavior assessment (ages =89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003eCommunication, functional academics, self-direction, leisure, work, social\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eStandardization sample of 7,370 individuals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003eCronbach \u0026plusmn; 0.90 (GAC); strong test-retest and interrater reliability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eNot HCT-specific; may require clinical interpretation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eSelf-Management Skills Assessment Guide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eWilliams et al., 2010\u0026nbsp;[32]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eEvaluate readiness among Canadian youth with chronic illness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003eMedical understanding, independence, care participation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003e49 youth (11 \u0026plusmn; 18 yrs) and parents at Alberta Children\u0026acirc;\u0026euro;\u0026trade;s Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003eModerate youth-parent agreement; correlated with adaptive skills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003ePreliminary validation; limited demographic variance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3775%;\"\u003e\n \u003cp\u003eTransition Planning Tool (TPT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.5232%;\"\u003e\n \u003cp\u003eWiemann et al., 2015\u0026nbsp;[17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003eEMR-based tool for transition planning in youth with special health care needs aged 16 \u0026plusmn; 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6291%;\"\u003e\n \u003cp\u003eCondition knowledge, medication management, self-advocacy, planning, independence, family support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7616%;\"\u003e\n \u003cp\u003e182 youth (303 encounters), 25 providers in 4 subspecialty clinics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.0397%;\"\u003e\n \u003cp\u003eNo formal psychometric testing; usability and provider satisfaction via PDSA cycles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.9073%;\"\u003e\n \u003cp\u003eNo reliability/validity data; limited generalizability; underuse in busy settings\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. The key characteristics of Disease-Specific Transition Readiness Assessment Tools.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"762\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.9423%;\"\u003e\n \u003cp\u003eTool name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4173%;\"\u003e\n \u003cp\u003eAuthors/Year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6168%;\"\u003e\n \u003cp\u003ePurpose/Population\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3543%;\"\u003e\n \u003cp\u003eDomains Assessed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3858%;\"\u003e\n \u003cp\u003eSample/Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.9606%;\"\u003e\n \u003cp\u003eValidation Results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3228%;\"\u003e\n \u003cp\u003eLimitations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.9423%;\"\u003e\n \u003cp\u003eTRAQ-SB\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4173%;\"\u003e\n \u003cp\u003eJohnson et al., 2019\u0026nbsp;[33]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6168%;\"\u003e\n \u003cp\u003eMeasure transition readiness in adolescents with spina bifida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3543%;\"\u003e\n \u003cp\u003eSelf-management, continence, shunt awareness, skin care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3858%;\"\u003e\n \u003cp\u003eN = 90, youth aged 12 \u0026plusmn;25 at a spina bifida clinic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.9606%;\"\u003e\n \u003cp\u003eCronbach\u0026acirc;\u0026euro;\u0026trade;s \u0026Icirc;\u0026plusmn; = 0.90; strong correlation with TRAQ and age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3228%;\"\u003e\n \u003cp\u003eSingle-center; only one factor retained\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.9423%;\"\u003e\n \u003cp\u003eAMIS-II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4173%;\"\u003e\n \u003cp\u003eRidosh et al., 2021\u0026nbsp;[19]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6168%;\"\u003e\n \u003cp\u003eEvaluate self-management and independence in AYA with spina bifida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3543%;\"\u003e\n \u003cp\u003eCondition self-management and independent living\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3858%;\"\u003e\n \u003cp\u003eN = 64 AYA (18 \u0026plusmn; 25 yrs); parent-report comparison from 6 years earlier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.9606%;\"\u003e\n \u003cp\u003eExcellent internal consistency (\u0026Icirc;\u0026plusmn; = 0.95); strong construct validity (r = 0.378 \u0026plusmn; 0.777)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3228%;\"\u003e\n \u003cp\u003ePrimarily descriptive; limited diversity in prior studies\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.9423%;\"\u003e\n \u003cp\u003eKKIS-SB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4173%;\"\u003e\n \u003cp\u003eJacobson et al., 2013\u0026nbsp;[20]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6168%;\"\u003e\n \u003cp\u003eMeasure executive components of self-management for SB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3543%;\"\u003e\n \u003cp\u003eRoutine initiation, prospective memory, self-care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3858%;\"\u003e\n \u003cp\u003eN = 100 youth with SB (ages 10 \u0026plusmn; 29), parent-reported\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.9606%;\"\u003e\n \u003cp\u003eCronbach \u0026plusmn; 0.89; 4-factor model, strong construct validity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3228%;\"\u003e\n \u003cp\u003eNo youth self-report; U.S.-only validation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.9423%;\"\u003e\n \u003cp\u003eEpiTRAQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4173%;\"\u003e\n \u003cp\u003eClark et al., 2020\u0026nbsp;[21]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6168%;\"\u003e\n \u003cp\u003eAssess epilepsy-specific transition readiness for AYA without intellectual disability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3543%;\"\u003e\n \u003cp\u003eMedication management, seizure safety, healthcare navigation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3858%;\"\u003e\n \u003cp\u003eN = 683 (302 + 381), ages 16 \u0026plusmn; 26; tested in neurology clinics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.9606%;\"\u003e\n \u003cp\u003eHigh internal consistency; stability across two waves; strong adaptation from TRAQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3228%;\"\u003e\n \u003cp\u003eLimited applicability to those with cognitive impairment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.9423%;\"\u003e\n \u003cp\u003eTRAQ + PBTS Workshops\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4173%;\"\u003e\n \u003cp\u003eCarrier et al., 2025\u0026nbsp;[34]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6168%;\"\u003e\n \u003cp\u003eWorkshop-based transition readiness program for pediatric brain tumor survivors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3543%;\"\u003e\n \u003cp\u003eSocial, cognitive, disease self-management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3858%;\"\u003e\n \u003cp\u003eN = 12 dyads (PBTS + parents), age 14+, pre/post pilot design\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.9606%;\"\u003e\n \u003cp\u003eClinically meaningful improvements; moderate effect size (d = 0.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3228%;\"\u003e\n \u003cp\u003ePilot; low recruitment; small sample\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.9423%;\"\u003e\n \u003cp\u003eTRAQ-SB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4173%;\"\u003e\n \u003cp\u003eWood et al., 2019\u0026nbsp;[35]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6168%;\"\u003e\n \u003cp\u003eTo assess spina bifida-specific self-management skills among youth and young adults aged 12\u0026ndash;25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3543%;\"\u003e\n \u003cp\u003eUrine/stool continence, skin care, shunt awareness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3858%;\"\u003e\n \u003cp\u003eN = 90 youth with spina bifida in NSBPR clinics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.9606%;\"\u003e\n \u003cp\u003eInternal consistency (\u0026alpha; = 0.91); predictive validity for urinary incontinence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3228%;\"\u003e\n \u003cp\u003eNo association with stool or skin outcomes; small sample; requires broader validation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.9423%;\"\u003e\n \u003cp\u003eAMIS-II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4173%;\"\u003e\n \u003cp\u003eBellin et al., 2011\u0026nbsp;[36]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6168%;\"\u003e\n \u003cp\u003eTo evaluate self-management and independence among young adults with myelomeningocele\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3543%;\"\u003e\n \u003cp\u003eCondition management, daily living skills, autonomy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3858%;\"\u003e\n \u003cp\u003eN = 50, ages 18\u0026ndash;25 from 5 US specialty clinics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.9606%;\"\u003e\n \u003cp\u003eClinical interview tool; mean AMIS-II scores reflect deficits in condition management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3228%;\"\u003e\n \u003cp\u003eDescriptive, limited psychometric analysis reported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.9423%;\"\u003e\n \u003cp\u003eIndividualized Transition Plan (ITP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4173%;\"\u003e\n \u003cp\u003eHopson et al., 2019\u0026nbsp;[37]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6168%;\"\u003e\n \u003cp\u003eTo individualize transition plans for adolescents with spina bifida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3543%;\"\u003e\n \u003cp\u003eEducation, bowel management, patient/family goals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3858%;\"\u003e\n \u003cp\u003eN = 32 patients (mean age 16.4), interdisciplinary clinic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.9606%;\"\u003e\n \u003cp\u003eNot psychometrically validated; descriptive goal tracking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3228%;\"\u003e\n \u003cp\u003eLimited sample; retrospective review; no standardized outcome evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.9423%;\"\u003e\n \u003cp\u003eAMIS-II (extended study)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4173%;\"\u003e\n \u003cp\u003eMahmood et al., 2011\u0026nbsp;[9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6168%;\"\u003e\n \u003cp\u003eTo correlate self-management with preventable conditions and health service use in young adults with myelomeningocele\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3543%;\"\u003e\n \u003cp\u003eSkin and bladder care, condition knowledge, ADLs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3858%;\"\u003e\n \u003cp\u003eN = 38, aged 18\u0026ndash;25, 5 SB clinics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.9606%;\"\u003e\n \u003cp\u003eLower AMIS-II scores associated with more UTIs and hospitalizations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3228%;\"\u003e\n \u003cp\u003eSmall sample; cross-sectional design; limited generalizability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.9423%;\"\u003e\n \u003cp\u003eSelf-Management Experiences (Qualitative Framework)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4173%;\"\u003e\n \u003cp\u003eSawin et al., 2012\u0026nbsp;[38]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6168%;\"\u003e\n \u003cp\u003eTo explore the lived experience of self-management in adolescent women with spina bifida\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3543%;\"\u003e\n \u003cp\u003eSpecialized knowledge, general independence tasks, parental influence, advocacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3858%;\"\u003e\n \u003cp\u003e31 adolescent women with SB, aged 12\u0026ndash;21 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.9606%;\"\u003e\n \u003cp\u003eQualitative thematic analysis; not a psychometric tool; themes triangulated using content coding and expert review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3228%;\"\u003e\n \u003cp\u003eNot a standardized instrument; small, homogeneous sample; qualitative outcomes not generalizable\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11.9423%;\"\u003e\n \u003cp\u003eKennedy Independence Scales - Spina Bifida (KIS-SB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.4173%;\"\u003e\n \u003cp\u003eZabel et al., 2003\u0026nbsp;[39]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6168%;\"\u003e\n \u003cp\u003eParent-reported measure of executive function and independence in youth with spina bifida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3543%;\"\u003e\n \u003cp\u003eMedical, educational/pre-vocational, community functioning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3858%;\"\u003e\n \u003cp\u003eAdolescents with SB; exact sample not specified in the summary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.9606%;\"\u003e\n \u003cp\u003ePsychometric analysis ongoing; structured scoring format\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3228%;\"\u003e\n \u003cp\u003eLimited published validation results; based on parental perception\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"health care transition, transition readiness, adolescents, neurological conditions, neurosurgery, psychometric evaluation","lastPublishedDoi":"10.21203/rs.3.rs-7359414/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7359414/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Health care transition (HCT) is a critical process where adolescents and young adults with chronic medical conditions shift from pediatric to adult-oriented health systems. Despite its importance, youth with neurological and neurosurgical conditions face heightened barriers due to cognitive, psychosocial, and functional complexities.\u003c/p\u003e\n\u003cp\u003eObjective: To systematically identify, categorize, and evaluate transition readiness assessment tools for youth with chronic illnesses, with a focus on those relevant to neurological and neurosurgical populations.\u003c/p\u003e\n\u003cp\u003eMethods: A systematic mapping review was conducted across PubMed, Embase, Scopus, and Web of Science using predefined search terms and eligibility criteria. Included studies reported on the development or validation of tools assessing transition readiness in individuals with chronic conditions. Tools were classified as generic or condition-specific, evaluated using Terwee et al.’s psychometric quality framework.\u003c/p\u003e\n\u003cp\u003eResults: 24 tools were identified: 13 generic and 11 condition-specific. Generic tools like (Transition Readiness Assessment Questionnaire) TRAQ, (Adolescent Assessment of Preparation for Transition) ADAPT, and TRANSITION-Q demonstrated strong internal consistency and construct validity but rarely assessed responsiveness or ecological validity. Disease-specific tools—particularly for spina bifida and epilepsy—showed high content relevance but limited generalizability and psychometric depth. Hydrocephalus and pediatric brain tumor survivor tools were underdeveloped. Responsiveness and test–retest reliability were evaluated in only 33% of tools; ecological validity was addressed in just two.\u003c/p\u003e\n\u003cp\u003eConclusion: While multiple tools measure transition readiness, most lack comprehensive psychometric validation, especially longitudinal and real-world application. Urgent need exists for condition-specific tools for neurosurgical populations, emphasizing responsiveness, ecological validity, and implementation science in future development.\u003c/p\u003e","manuscriptTitle":"Psychometric Rigor and Gaps in Transition Readiness Assessment Tools for Youth with Neurosurgical Conditions: A Systematic Mapping Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-24 13:05:17","doi":"10.21203/rs.3.rs-7359414/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"297225656651806572953434177935324203308","date":"2025-09-25T16:11:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-22T15:01:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"264291464659272602983859532955322233625","date":"2025-09-16T13:05:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-16T06:25:29+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-21T09:15:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-21T07:33:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-21T07:33:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-08-12T22:57:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bcfca12c-e3a4-4a84-8da1-a7836a3142d4","owner":[],"postedDate":"September 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-24T13:05:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-24 13:05:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7359414","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7359414","identity":"rs-7359414","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}