Candidate Items Research Articles

Development of a Rubric to Evaluate Implementation Quality of Simulation-Based Courses: A Consensus Study.

Simulation-based education is a recognized way of developing medical competencies, and there is overwhelming scientific evidence to support its efficacy. However, it is still underused, which can often be related to poor implementation process. In addition, best practices for implementation of simulation-based courses based on implementation science are not widely known nor applied. The purpose of this study was to develop a rubric, the Implementation Quality Rubric for Simulation (IQR-SIM), to evaluate the implementation quality of simulation-based courses. A 3-round, modified Delphi process involving international simulation and implementation experts was initiated to gather and converge opinions regarding criteria for evaluating the implementation quality of simulation-based courses. Candidate items for Round 1 were developed based on the Adapted Implementation Model for Simulation. Items were revised and expanded to include descriptive anchors for evaluation in Round 2. Criterion for inclusion was 70% of respondents selecting an importance rating of 4 or 5/5. Round 3 provided refinement and final approval of items and anchors. Thirty-three experts from 9 countries participated. The initial rubric of 32 items was reduced to 18 items after 3 Delphi rounds, resulting in the IQR-SIM: a 3-point rating scale, with nonscored options "Don't know/can't assess" and "Not applicable," and a comments section. The IQR-SIM is an operational tool that can be used to evaluate the implementation quality of simulation-based courses and aid in the implementation process to identify gaps, monitor the process, and promote the achievement of desired implementation and learning outcomes.

Remembering past and predicting future: a hybrid recurrent neural network based recommender system.

Traditional recommender systems (RS) assume users’ taste to be static (taste remains same over time) and reactive (a change in taste cannot be predicted and is observed only after it occurs). Further, traditional RS restricts the recommendation process to candidate items generation. This work aims to explore two phases of RS, i.e., Candidate Generation as well as Candidate Ranking. We propose a RS from a multi-objective (short-term prediction, long-term prediction, diversity, and popularity bias) perspective which was previously overlooked. The sequential and non-sequential behavior of users is exploited to predict future behavioral trajectories with the consideration of short-term and long-term prediction using recurrent neural networks and nearest neighbors approach. Further, a novel candidate ranking method is introduced to prevent users from being entangled in recommended items. On multiple datasets, largest being MovieLens (ML) 1M, our model shows excellent results achieving a hit rate and short-term prediction success of 58% and 71% respectively on ML 1M. Further, it implicitly handles two important parameters, i.e., diversity and item popularity with a success rate of 59.22% and 34.28% respectively.

“It cannot be boring!”: Developing a measure of function for young adults accessing integrated youth services

BackgroundIn Canada, the prevalence of mental health challenges is highest in young people aged 12–24. Mental health challenges frequently cause marked functional impairment. Despite this, we are unaware of any existing conceptualization and/or measures of function that has been developed from the perspective of young people. The objective of this paper is to develop a conceptual and measurement model, including a preliminary set of items, for an outcome measure of function for young adults accessing mental health services.MethodsWe conducted this study in three phases. In phase 1, we conducted three focus groups to conceptualize function as a construct from the perspective of young adults. In phase 2, we co-designed a set of items with youth (n = 4) to capture the construct. In phase 3, we invited young people (n = 12) accessing mental health services to complete workbooks and participate in one of two focus groups to evaluate whether items were clear, captured function comprehensively, and were relevant. We transcribed and compiled all data to eliminate, refine and generate new items.ResultsIn phase 1, a conceptual model of function was developed with three main themes: basic needs, roles and responsibilities, and social connections. In phase 2, 97 candidate items were developed, and in phase 3, a candidate pool of 50 items resulted for psychometric testing.ConclusionThis youth-centred conceptualization of function and preliminary item bank has the potential to advance person-centred care, outcomes, and experiences for youth seeking mental health services.

An international collaborative study to co-produce a patient-reported outcome measure of cardiac arrest survivorship and health-related quality of life (CASHQoL): A protocol for developing the long-form measure

BackgroundCurrent measures of health-related quality of life are neither sufficiently sensitive or specific to capture the complex and heterogenous nature of the recovery and survivorship associated with cardiac arrest. To address this critical practice gap, we plan a mixed-methods study to co-produce and evaluate a new cardiac arrest-specific patient/survivor-reported outcome measure (PROM). MethodsInternational guidelines have informed a two-stage, iterative, and interactive process.Stage one will establish what is important to measure following cardiac arrest. A meta-ethnography of published qualitative research and a qualitative exploration of the experiences of survivors and their key supporters will inform the development of a measurement framework. This will be supplemented by existing, extensive reviews describing concepts that have previously been measured in this population. Focus groups with survivors, key supporters, and healthcare professionals, followed by further interviews with survivors and key supporters, will inform the iterative refinement of the framework, candidate items, and PROM structure.Stage two will involve a psychometric evaluation following completion by a large cohort of survivors. Measurement theory will inform: the identification of items that best measure important outcomes; item reduction; and provide robust evidence of measurement and practical properties. DiscussionAn international, collaborative approach to PROM development will engage survivors, key supporters, researchers, and health professionals from study commencement. Successful co-production of the cardiac arrest survivorship and health-related quality of life (CASHQoL) measure will provide a robust, relevant, and internationally applicable measure, suitable for completion by adult survivors, and integration into research, registries, and routine care settings.Ethical approval: University of Warwick Biomedical & Scientific Research Ethics Committee (BSREC 22/20-21 granted 10/11/20).

Development and psychometric properties of the hospitalized elder abuse questionnaire (HEAQ): a mixed methods study

BackgroundOlder patients are more vulnerable and prone to abuse and neglect in hospitals and acute care settings. The present study aimed to develop and assess the psychometric properties of a questionnaire for screening abuse in hospitalized older adults.MethodsThis study was conducted from October 2017 to September 2019 using the exploratory sequential mixed-methods research design. The participants were selected among those admitted to various wards of six teaching hospitals affiliated with Shiraz University of Medical Sciences, Shiraz, Iran. In the qualitative phase of the study, using the inductive content analysis method, the concept of abuse in hospitalized older adults was extracted through individual in-depth semi-structured interviews with 16 older patients and 11 family caregivers. Based on qualitative findings and a review of existing literature, an initial version of the questionnaire was developed. In the quantitative phase of the study, the psychometric properties (face, content, construct, and convergent validity; internal consistency and stability) of the questionnaire were examined.ResultsBased on qualitative findings and literature review, a pool of 154 candidate items was defined. These items were reduced to 37 after initial refinement, qualitative and quantitative face and content validity, and item analysis. The outcome of principal component analysis further reduced the number of items to 27, which were grouped into 5 components, namely “Shortcomings in management and care facility”, “Neglect of professional commitments”, “Physical and psychological abuse”, “Protracted treatment process”, and “Invasion of privacy”. The explained variance of these 5 components was 50.09% of the overall variability of the questionnaire. The convergent validity of the questionnaire was acceptable (P < 0.00, r = − 0.44). Cronbach’s alpha coefficient and intraclass correlation coefficient for the entire questionnaire were 0.89 and 0.92, respectively; indicating high reliability and stability of the questionnaire.ConclusionThe hospitalized elder abuse questionnaire (HEAQ) has acceptable psychometric properties. It is recommended to use HEAQ to screen for suspected cases of abuse of hospitalized older adults.

A Data Mining Algorithm for Association Rules with Chronic Disease Constraints.

The Apriori algorithm in association rules is the main algorithm used in the treatment and prevention of chronic diseases in data mining, and the algorithm in the current stage of China's medical field of association between chronic diseases has some problems, such as the need to scan the transaction database of cases several times, producing a large data set and more redundant rules. To address the above problems, a data mining algorithm of association rules combining clustering matrix and pruning strategy is proposed, which improves the algorithm by using the clustering matrix method to compress the stored transaction database and introducing the prepruning and postpruning strategy methods on the basis of adding constraint conditions. The experimental results show that the optimization algorithm has unique advantages in reducing the number of database scans and the number of candidate item sets generated and ultimately greatly reduces the running time and I/O load of the algorithm, and the running efficiency of the algorithm is greatly improved.

Validity of intraoperative voice monitoring undergoing type 2 thyroplasty with titanium bridges for adductor spasmodic dysphonia.

ObjectivesThe success of type 2 thyroplasty (TP2) for adductor spasmodic dysphonia (AdSD) depends on the selection of optimally sized titanium bridges, which requires accurate assessment of intraoperative vocal changes. While this procedure has traditionally been performed according to the laryngologist's experience, the most appropriate method for voice monitoring and selection of titanium bridge size remains to be determined. This study aimed to investigate evaluation parameters useful for voice monitoring, as these may allow less experienced surgeons to perform TP2 properly.MethodsIn this prospective study, voice monitoring was performed in 18 patients with AdSD patients undergoing TP2. Evaluations were performed preoperatively, intraoperatively, 13 weeks postoperatively, and 52 weeks postoperatively using GRBAS (grade, roughness, breathiness, asthenia, and strain), as well as perceptual judgment and acoustic analyses.ResultsPreoperative and intraoperative assessments of the G, R, B, and S parameters, perceptual judgment, and harmonic‐to‐noise ratio (HNR) were in moderate or better agreement. Intraoperative and 13‐ or 52‐week postoperative measurements of the R, B, and G parameters and strangulation, tremor, and HNR were also in high agreement. When two different sizes of titanium bridges were compared (unselected vs. selected), ratings for G, R, S, strangulation, tremor, jitter, shimmer, HNR, standard deviation of F0, and degree of voice breaks were better for the selected width than the unselected width.ConclusionThe candidate items for intraoperative voice monitoring during TP2 for AdSD are G, R, strangulation, tremor, and HNR. The use of these items may help to ensure successful TP2 and contribute to the advancement of laryngeal framework surgery.Level of evidenceLevel 4.

Measuring a Patient's understanding of their prognosis: An exploratory analysis.

In patients with cancer across the illness trajectory, treatment decisions are often influenced by one's perception of their prognosis (i.e., curability of disease, life expectancy, quality of life). However, research on how patients understand their prognosis (i.e., prognostic understanding) has been limited by simplistic measurement tools that fail to capture the complexity of the construct. This study describes the initial development of a measure of prognostic understanding: the Prognostic Understanding Perceptions Scale (PUPS) for use in patients with advanced cancer. An initial pool of 16 candidate items were developed through semi-structured interviews with 15 experts (oncology, psycho-oncology and palliative care professionals) and 30 advanced cancer patients. We investigated the dimensionality, internal item structure, item difficulty and item discrimination of the item pool using exploratory factor analysis (EFA), classical test theory (CTT) and item response theory (IRT) analyses. Convergent and divergent validity were based on correlations between PUPS, terminal illness acknowledgement, and self-report measures of depression, anxiety, hopelessness, and death acceptance. The final measure was comprised of nine items encompassing three factors (perceived curability, illness trajectory, treatment options), yielding strong psychometric properties. These results provide preliminarily support for PUPS as a multifaceted measure of prognostic understanding developed for use in patients with advanced cancer. Preliminary findings also highlight the potential utility of the PUPS for clinical settings, as a means of enhancing communication between patients and physicians.

Tunnel Security Management Based on Association Rule Mining under Hadoop Platform

The problem of how to use large amounts of historical data for tunnel safety management has a greater practical application value. The association rule method in data mining technology can provide effective decision support for tunnel safety prevention by mining historical data. To address the problem of large data volume and sparse data items in tunnel safety management, an association rule method—Apriori algorithm—based on the Hadoop platform is proposed to improve the efficiency and accuracy of data mining in cloud environment. First, the parallel MapReduce implementation steps are analyzed on the basis of the distributed Hadoop framework. Then, the existing single-user data validation algorithm is improved by applying a multiuser parallel validation algorithm to Apriori in order to reduce the number of validations. Next, the traditional association rule Apriori algorithm is MapReduce optimized to generate a smaller set of useless candidate items. At the same time, Boolean ranking is used to optimize the way transactional data are stored in the database, reducing the number of redundant subsets and the number of times the database is connected, and shortening the task processing time. The experimental results show that the proposed method is able to mine the relationships between tunnel safety hazards and provide effective decision support for tunnel safety prevention. At the same time, the proposed method more efficiently operates than other association rule methods.

Development and evaluation of the patient-reported outcomes measurement information system (PROMIS) pediatric pain quality item bank and short form.

Pain is a common problem among children, particularly those with pediatric chronic diseases. Multifaceted assessment of pain can improve communication about pain and help clinicians characterize, differentiate, and treat a patient's unique experience of pain. Pain quality is an important domain of pain, describing the subjective sensory experiences associated with pain as well as the affective experiences of pain. The aim of the current study was to quantitatively evaluate the measurement properties of the 59 Patient-Reported Outcomes Measurement Information System pediatric pain quality candidate items developed as part of the National Institutes of Health's Patient-Reported Outcomes Measurement Information System initiative with input from children and adolescents with chronic pain. Participants included N = 448 pediatric patients between 8 and 18 years of age with chronic health conditions with a prominent component of chronic or recurrent pain, including juvenile fibromyalgia, juvenile idiopathic arthritis, and sickle cell disease. A confirmatory factor analysis revealed a unidimensional model fit the data best, with 56 of the 59 items demonstrating good psychometric properties for inclusion in the final measure. In addition, a consensus-building method was used to establish 2 versions of a short form measure-one with 8 items focused primarily on the sensory pain qualities and one with 8 items focused on affective pain qualities. The final measure shows good reliability and validity, and is recommended for use in research and clinical care with pediatric populations.

Knowledge Graph Recommendation Model Based on Adversarial Training

The recommendation model based on the knowledge graph (KG) alleviates the problem of data sparsity in the recommendation to a certain extent and further improves the accuracy, diversity, and interpretability of recommendations. Therefore, the knowledge graph recommendation model has become a major research topic, and the question of how to utilize the entity and relation information fully and effectively in KG has become the focus of research. This paper proposes a knowledge graph recommendation model based on adversarial training (ATKGRM), which can dynamically and adaptively adjust the knowledge graph aggregation weight based on adversarial training to learn the features of users and items more reasonably. First, the generator adopts a novel long- and short-term interest model to obtain user features and item features and generates a high-quality set of candidate items. Then, the discriminator discriminates candidate items by comparing the user’s scores of positive items, negative items, and candidate items. Finally, experimental studies on five real-world datasets with multiple knowledge graph recommendation models and multiple adversarial training recommendation models prove the effectiveness of our model.

China Health Related Outcomes Measures (CHROME): Development of a New Generic Preference-Based Measure for the Chinese Population.

Background and ObjectivesExisting generic preference-based measures were all developed in Western countries. Evidence shows that the Chinese population may have different perceptions about health and health-related quality of life. This study aimed at developing a descriptive system of a new generic preference-based measure under the initiative of China Health Related Outcomes Measures (CHROME).MethodsQualitative data were collected through semi-structured interviews conducted in-person or online. Respondents were recruited from both the general public and populations with chronic diseases. Open-ended questions about the respondent’s perception of general health and important aspects of health-related quality of life were asked. Probing questions based on a systematic review of existing generic preference-based measures were also used. The framework analysis was used to synthesize the qualitative data. Candidate items for the descriptive system were selected following the ISPOR and COSMIN guidelines. Expert panel review and cognitive debriefings were conducted for further revisions.ResultsQualitative interviews were conducted among 68 respondents, with 48.5% male and a mean age of 47.8 years (range 18–81 years). In total, 1558 codes were identified and then aggregated to 31 sub-themes and corresponding six themes to inform the development of the initial version of the descriptive system. Feedback from the expert panel survey and meeting (n = 15) and the cognitive debriefing interviews (n = 30) was incorporated into the revised version of the measure. Finally, the generic version of CHROME (CHROME-G) included 12 items across six domains, namely, pain, fatigue, appetite, mobility, vision, hearing, sleeping, daily activities, depression, worry, memory, and social interactions. The descriptive system used a mix of four-level and five-level response options and a 7-day recall period.ConclusionsThe CHROME-G is the first generic preference-based measure to be developed based on the inputs from the Chinese populations.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40273-022-01151-9.

The development and initial validation of the PROMIS®+HF-27 and PROMIS+HF-10 profiles.

Heart failure (HF) is a common and morbid condition impacting multiple health domains. We previously reported the development of the PROMIS®-Plus-HF (PROMIS+HF) profile measure, including universal and HF-specific items. To facilitate use, we developed shorter, PROMIS+HF profiles intended for research and clinical use. Candidate items were selected based on psychometric properties and symptom range coverage. HF clinicians (n=43) rated item importance and clinical actionability. Based on these results, we developed the PROMIS+HF-27 and PROMIS+HF-10 profiles with summary scores (0-100) for overall, physical, mental, and social health. In a cross-sectional sample (n=600), we measured internal consistency reliability (Cronbach's alpha and Spearman-Brown), test-retest reliability (intraclass coefficient; n=100), known-groups validity via New York Heart Association (NYHA) class, and convergent validity with Kansas City Cardiomyopathy Questionnaire (KCCQ) scores. In a longitudinal sample (n=75), we evaluated responsiveness of baseline/follow-up scores by calculating mean differences and Cohen's d and comparing with paired t-tests. Internal consistency was good to excellent (α 0.82-0.94) for all PROMIS+HF-27 scores and acceptable to good (α/Spearman-Brown 0.60-0.85) for PROMIS+HF-10 scores. Test-retest intraclass coefficients were acceptable to excellent (0.75-0.97). Both profiles demonstrated known-groups validity for the overall and physical health summary scores based on NYHA class, and convergent validity for nearly all scores compared with KCCQ scores. In the longitudinal sample, we demonstrated responsiveness for PROMIS+HF-27 and PROMIS+HF-10 overall and physical summary scores. For the PROMIS+HF overall summary scores, a group-based increase of 7.6-8.3 points represented a small to medium change (Cohen's d=0.40-0.42). For the PROMIS+HF physical summary scores, a group-based increase of 5.0-5.9 points represented a small to medium change (Cohen's d=0.29-0.35). The PROMIS+HF-27 and PROMIS+HF-10 profiles demonstrated good psychometric characteristics with evidence of responsiveness for overall and physical health. These new measures can facilitate patient-centred research and clinical care, such as improving care quality through symptom monitoring, facilitating shared decision-making, evaluating quality of care, assessing new interventions, and monitoring during the initiation and titration of guideline-directed medical therapy.

The Osteopaths’ Therapeutic Approaches Questionnaire (Osteo-TAQ) - A content validity study

BackgroundOsteopathy requires reliable and valid research tools to generate evidence on the different aspects of practice including how osteopaths approach the clinical care of patients. Such research will help the osteopathy profession understand its contribution to healthcare provision and communicate this to stakeholders. However, current quantitative tools to measure the different aspects of osteopathic practice are either focused on single pain conditions or developed from other health professional contexts. AimThe Osteopaths' Therapeutic Approaches Questionnaire (Osteo-TAQ) is a novel tool developed from qualitative research and aims to measure and describe multiple dimensions of osteopaths’ therapeutic approach to patient care. The aim of this study was to further develop the Osteo-TAQ to assess the content validity of the tool. MethodA modified nominal group technique (NGT) was employed to establish whether the Osteo-TAQ items were consistent with the underlying construct and to ascertain the prevalence and strength of agreement amongst the expert group panel members (N = 11). A content validity index (CVI) was performed to obtain the evidence for the content validity for a revised version of the Osteo-TAQ. ResultsTwo rounds of review and feedback by an expert panel as part of the NGT resulted in the revision of 13 of the 37 candidate items and refinement of the previously published Osteo-TAQ. Item CVI scores after phase 1 ranged from 0.44 to 1.0 and agreement was reached after two rounds. Data from the expert panel supports the content validity of the revised Osteo-TAQ items based on high levels of agreement with respect to coverage of the construct being measured. ConclusionThis preliminary work to revise and refine the Osteo-TAQ resulted in a measure that is suitable for further testing as part of a validation research program.

Identifying Potential Classification Criteria for Calcium Pyrophosphate Deposition Disease: Item Generation and Item Reduction.

Classification criteria for calcium pyrophosphate deposition (CPPD) disease will facilitate clinical research on this common crystalline arthritis. Our objective was to report on the first 2 phases of a 4-phase process for developing CPPD classification criteria. CPPD classification criteria development is overseen by a 12-member steering committee. Item generation (phase I) included a scoping literature review of 5 literature databases and contributions from a 35-member combined expert committee and 2 patient research partners. Item reduction and refinement (phase II) involved a combined expert committee meeting, discussions among clinical, imaging, and laboratory advisory groups, and an item-rating exercise to assess the influence of individual items toward classification. The steering committee reviewed the modal rating score for each item (range -3 [strongly pushes away from CPPD] to +3 [strongly pushes toward CPPD]) to determine items to retain for future phases of criteria development. Item generation yielded 420 items (312 from the literature, 108 from experts/patients). The advisory groups eliminated items that they agreed were unlikely to distinguish between CPPD and other forms of arthritis, yielding 127 items for the item-rating exercise. Fifty-six items, most of which had a modal rating of +/- 2 or 3, were retained for future phases. As numerous imaging items were rated +3, the steering committee recommended focusing on imaging of the knee and wrist and 1 additional affected joint for calcification suggestive of CPP crystal deposition. A data- and expert-driven process is underway to develop CPPD classification criteria. Candidate items comprise clinical, imaging, and laboratory features.

Anisotropic Additive Quantization for Fast Inner Product Search

Maximum Inner Product Search (MIPS) plays an important role in many applications ranging from information retrieval, recommender systems to natural language processing and machine learning. However, exhaustive MIPS is often expensive and impractical when there are a large number of candidate items. The state-of-the-art approximated MIPS is product quantization with a score-aware loss, which weighs more heavily on items with larger inner product scores. However, it is challenging to extend the score-aware loss for additive quantization due to parallel-orthogonal decomposition of residual error. Learning additive quantization with respect to this loss is important since additive quantization can achieve a lower approximation error than product quantization. To this end, we propose a quantization method called Anisotropic Additive Quantization to combine the score-aware anisotropic loss and additive quantization. To efficiently update the codebooks in this algorithm, we develop a new alternating optimization algorithm. The proposed algorithm is extensively evaluated on three real-world datasets. The experimental results show that it outperforms the state-of-the-art baselines with respect to approximate search accuracy while guaranteeing a similar retrieval efficiency.

AUGS-PERFORM: A New Patient-Reported Outcome Measure to Assess Quality of Prolapse Care.

ObjectivePatient-reported outcomes (PRO) are important for measuring quality of care, particularly for interventions aimed at improving symptom bother such as procedures for pelvic organ prolapse. We aimed to create a concise yet comprehensive PRO measurement tool to assess pelvic organ prolapse care in high-volume clinical environments.MethodsThe relevant concepts to measure prolapse treatment quality were first established through literature review, qualitative interviews, and a patient and provider-driven consensus-building process. Extant items mapping to these concepts, or domains, were identified from an existing pool of patient-reported symptoms and condition-specific and generic health-related quality of life measures. Item classification was performed to group items assessing similar concepts while eliminating items that were redundant, inconsistent with domains, or overly complex. A consensus meeting was held in March 2020 where patient and provider working groups ranked the remaining candidate items in order of relevance to measure prolapse treatment quality. After subsequent expert review, the revised candidate items underwent cognitive interview testing and were further refined.ResultsFifteen relevant PRO instruments were initially identified, and 358 items were considered for inclusion. After 2 iterative consensus reviews and 4 rounds of cognitive interviewing with 19 patients, 11 final candidate items were identified. These items map 5 consensus-based domains that include awareness and bother from prolapse, physical function, physical discomfort during sexual activity, pain, and urinary/defecatory symptoms.ConclusionsWe present a concise set of candidate items that were developed using rigorous patient-centered methodology and a national consensus process, including urogynecologic patients and providers.

Development and psychometric analysis of the Diabetes Device Confidence Scale for school nurses.

School nurses need to be equipped to help students with diabetes devices. No existing tools assess school nurse self-efficacy in using devices. To develop and evaluate the psychometric properties of a novel scale to measure school nurse confidence with diabetes devices. We generated a list of items with community partners and examined logical validity. We then revised and distributed the item set to school nurses in Pennsylvania to examine aspects of structural validity, convergent validity, and internal consistency reliability. We used item response theory to refine the scale. Facilitated discussion with collaborators generated an initial list of 50 potential items. Based upon the item-content validity index, we revised/eliminated 13 items. School nurses (n= 310) in Pennsylvania completed an updated 38-item scale; the majority had experience with insulin pumps or continuous glucose monitors. Exploratory factor analysis identified a one-factor solution, suggesting a unidimensional scale. We eliminated 13 additional items based upon significant inter-item correlation or skewed response patterns. Item response theory did not identify additional candidate items for removal. Despite a high degree of redundancy (Cronbach's alpha > 0.90), we retained all remaining items to maximize the future utility of the scale. The 25-item, unidimensional Diabetes Device Confidence Scale is a new tool to measure school nurse confidence with diabetes devices. This scale has future clinical, programmatic, and research applications. Combined with knowledge assessments, this scale can serve to evaluate school nurse device use readiness, assess training gaps, and tailor interventions.

Generating Items for a Novel Bedside Dysphagia Screening Tool Post Acute Pediatric Stroke.

Bedside dysphagia assessment protocols are not well developed in acute pediatric stroke unlike adults. The objective of this study was to identify items deemed relevant and feasible by expert consensus to inform the development of a bedside dysphagia screening tool for acute pediatric stroke. A two-phase study was conducted: (1) literature review and expert consultation generated a comprehensive list of dysphagia assessment items; (2) items were formatted in an online survey asking respondents opinion of relevance to acute pediatric stroke and feasibility for bedside administration by a trained health professional. The Dillman Tailored Design approach optimized response rate. Respondents were identified using the snowball method. Speech-language pathologists with > 2years in pediatric dysphagia were invited to complete the survey. Demographic and practice variables were compared using univariate statistics. Item relevance and feasibility were made using binary or ordinal responses, combined to derive item-content validity indices (I-CVI) to guide item reduction. Items with I-CVI > 0.78 (excellent content validity) were moved forward to tool development. Of the 71 invited respondents, 57(80.3%) responded, of which 34(59.6%) were from North America. Sixty-one items were generated of which 4(6.6%) items were rated 'to keep'. These were face symmetry (I-CVI:0.89), salivary control (I-CVI:0.95), alertness (I-CVI:0.89) and choking (I-CVI:0.84). Of all respondents, 31(54.4%) endorsed swallowing trials, of which 25(80.6%) endorsed thin liquid by teaspoon (n = 17, 68%) or open cup (n = 20, 80%). We identified candidate items for bedside dysphagia screening with excellent content validity for acute pediatric stroke patients. Next steps include assessment of the psychometric value of each item in identifying dysphagia in children in the acute stage of recovery from stroke.

Development of a Guideline to Enhance the Reporting of Concept Mapping Research: Study Protocol.

Reporting guidelines are intended to enhance the clarity and transparency of research publications. Concept mapping, a mixed-methods design, has been widely used in health research. Current reporting guidelines for mixed-methods studies are not relevant for concept mapping research. The aim of this study is to develop a reporting guideline for concept mapping research following the EQUATOR network toolkit. Guideline development is in three stages: 1. A systematic review to identify key components of reporting concept mapping research, 2. A concept mapping study involving the key stakeholder groups—researchers, methodologists, peer reviewers, journal editors, statisticians, and people who have participated in concept mapping research—to identify candidate items to include in a reporting guideline, and 3. Development of a draft reporting guideline for concept mapping research. The outcome of the research will be a reporting guideline for concept mapping research.