Objective Quality Measures Research Articles

Pediatric contrast-enhanced chest CT on a photon-counting detector CT: radiation dose and image quality compared to energy-integrated detector CT.

Photon counting detector (PCD) CT benefits from reduced noise compared with conventional energy-integrating detector (EID) CT, which should translate to improved image quality and reduced radiation exposure for pediatric patients undergoing chest CT with IV contrast. To determine the differences in radiation exposure and image quality of PCD CT and EID CT in pediatric chest CT with intravenous (IV) contrast. In this institutional review board-approved retrospective observational study, 20 scan pairs (20 PCD CT; 20 EID CT) for children who underwent chest CT with IV contrast on both a PCD CT (Siemens NAEOTOM Alpha) and an EID CT (Siemens SOMATOM Definition Edge or Force) within 12months were reviewed independently by three pediatric radiologists for three subjective quality features on 5-point Likert scales: overall quality, small structure delineation, and motion artifact. Objective measures of image quality (image noise, signal-to-noise ratio, and contrast-to-noise ratio) were assessed by a single radiologist in several locations in the chest through region of interest measurement of Hounsfield units (HU) and standard deviation. Patient-related and radiation exposure parameters were collected for each scan and summarized with median and interquartile range (IQR). The Wilcoxon rank-sum test was utilized to compare groups. A P < 0.05 indicated statistical significance. Inter-observer agreement of subjective image quality metrics was analyzed using weighted kappa. Age (14.2years vs 13.8years, P= 0.15), height (P= 0.13), weight (P= 0.21), and BMI (P = 0.24) did not significantly differ between groups. There were 10 male and 3 female patients. Compared to EID CT, PCD CT showed lower radiation exposure parameters including volumetric CT dose index, 1.7mGy (IQR 1.1-2.4mGy) vs 3.8mGy (IQR 2.0-4.7mGy) (P< 0.01), and size-specific dose estimate, 2.6mGy (IQR 1.8-3.1mGy) vs 5.0mGy (IQR 3.3-6.2mGy) (P< 0.01). Objective image quality of lung parenchyma was improved on the PCD CT scanner, including image noise 119.5 HU (IQR 95.4-135.7 HU) vs 143.1 HU (IQR 125.4-169.8 HU) (P < 0.01), signal-to-noise ratio (SNR) -6.1 (IQR -8.4 to -4.8) vs -4.9 (IQR -5.6 to -3.8) (P= 0.01), and contrast-to-noise ratio -63.9 (-84.1 to -57.5) vs -60.5 (-76.3 to -52.5) (P = 0.01). Motion artifact was improved on the PCD CT scanner (P< 0.01). No significant differences in overall image quality or small structure delineation were identified (P= 0.06 and P= 0.31). PCD CT pediatric chest CT had significantly reduced radiation exposure, improved image quality, and reduced motion artifact compared with EID CT.

IEHT vs. Regular Treatment - Are there Differences between the Two forms of Treatment in the Retrospective Course with regard to Individual Objective and Subjective Outcome Variables?

This retrospective follow-up study over one year (after discharge from the index treatment), compares the effects of inpatient-equivalent home treatment (IEHT) and regular psychiatric treatment using subjective and objective quality indicators. Using a 1:1 matching of cohorts (diagnosis, age, gender, number of previous treatments and severity of illness), 732 IEHT patients were assigned to a comparison group. Outcome data was taken from the routine data of the clinic database and the in-house basic documentation. In the subjective quality measure, patients and practitioners in regular psychiatric treatment reported a significantly higher improvement in condition. In terms of the objective quality measure, the number of further inpatient treatment days in the observation period, the two groups did not differ significantly, which can be interpreted as encouragement for the use of this new, increasingly established form of treatment.

Compression of room impulse responses for compact storage and fast low-latency convolution

Room impulse responses (RIRs) are used in several applications, such as augmented reality and virtual reality. These applications require a large number of RIRs to be convolved with audio, under strict latency constraints. In this paper, we consider the compression of RIRs, in conjunction with fast time-domain convolution. We consider three different methods of RIR approximation for the purpose of RIR compression and compare them to state-of-the-art compression. The methods are evaluated using several standard objective quality measures, both channel-based and signal-based. We also propose a novel low-rank-based algorithm for fast time-domain convolution and show how the convolution can be carried out without the need to decompress the RIR. Numerical simulations are performed using RIRs of different lengths, recorded in three different rooms. It is shown that compression using low-rank approximation is a very compelling option to the state-of-the-art Opus compression, as it performs as well or better than on all but one considered measure, with the added benefit of being amenable to fast time-domain convolution.

A Single-Frame and Multi-Frame Cascaded Image Super-Resolution Method.

The objective of image super-resolution is to reconstruct a high-resolution (HR) image with the prior knowledge from one or several low-resolution (LR) images. However, in the real world, due to the limited complementary information, the performance of both single-frame and multi-frame super-resolution reconstruction degrades rapidly as the magnification increases. In this paper, we propose a novel two-step image super resolution method concatenating multi-frame super-resolution (MFSR) with single-frame super-resolution (SFSR), to progressively upsample images to the desired resolution. The proposed method consisting of an L0-norm constrained reconstruction scheme and an enhanced residual back-projection network, integrating the flexibility of the variational model-based method and the feature learning capacity of the deep learning-based method. To verify the effectiveness of the proposed algorithm, extensive experiments with both simulated and real world sequences were implemented. The experimental results show that the proposed method yields superior performance in both objective and perceptual quality measurements. The average PSNRs of the cascade model in set5 and set14 are 33.413 dB and 29.658 dB respectively, which are 0.76 dB and 0.621 dB more than the baseline method. In addition, the experiment indicates that this cascade model can be robustly applied to different SFSR and MFSR methods.

Quality Measurement in Oncology: Time to Take the Next Step!

Oncology is a complex clinical specialty often requiring the close interaction of teams of different medical specialists for a successful outcome. The field is rapidly evolving scientifically, with successive discoveries of oncologic driver mutations soon followed by therapeutic agents able to interrupt the neoplastic process. Unfortunately, objective quality measurement demonstrates that many patients are not receiving optimal care, from diagnostic accuracy, therapeutic, or end-of-life perspectives. Quality measurement, reporting, and payment programs have the potential to focus attention on these care gaps and drive improvement. The federal government, as the largest single payer of health care services in the United States, has a compelling national interest to ensure that the medical care of Americans is at the highest level achievable. Accordingly, quality reporting and payment programs have been established in federal health care payment programs to drive improvements in care. This article reviews the science of quality measurement, documented gaps in oncology care, and ways to use new information technologies to decrease clinician burden associated with quality reporting. The article reviews how a measure is developed and incorporated into a Centers for Medicare & Medicaid Services (CMS) program. It also summarizes federal programs relevant to oncology care and the individual measures used in these programs. CMS looks forward to working jointly with the oncology community to drive continuous improvements in care.

Biomarkers of sleep-wake disturbance as predictors of cognitive decline and accelerated disease progression.

In older adults, where sleep disturbances and cognitive impairment are common, mounting evidence suggests a potential connection between sleep and cognitive function, highlighting the significance of utilizing sleep as a biomarker for early detection of cognitive impairment to improve clinical outcomes in a noninvasive, cost-effective manner. This review describes the relationship between sleep and cognitive function in older adults, encompassing both subjective and objective measures of sleep quality, duration, architecture, and sleep-disordered breathing. The authors consider the directionality of the associations observed in prospective and cross-sectional studies, exploring whether sleep disturbances precede cognitive decline or vice versa. Furthermore, they discuss the potential bidirectional relationships between sleep and Alzheimer's disease (AD) risks in older adults while also examining the neurodegenerative pathways of this relationship. Routine sleep monitoring in primary care settings has the potential to bolster early detection and treatment of sleep disturbance, and by extension, reduce the risk of dementia. Improving sleep assessment tools, such as wearables, provide scalable alternatives to traditional methods like polysomnography, potentially enabling widespread monitoring of sleep characteristics. Standardized measurement and inclusive participant recruitment are needed to enhance generalizability, while longitudinal studies are essential to understand the interaction between sleep and AD pathology.

OP20 Objective Measurement of Quality of Life: First Results of the Project "Machine Intelligence for the Objective Determination of Individual Quality of Life" - MI-Lq

OP20 Objective Measurement of Quality of Life: First Results of the Project "Machine Intelligence for the Objective Determination of Individual Quality of Life" - MI-Lq

Quantifying image quality in AOSLO images of photoreceptors.

The use of "quality" to describe the usefulness of an image is ubiquitous but is often subject to domain specific constraints. Despite its continued use as an imaging modality, adaptive optics scanning light ophthalmoscopy (AOSLO) lacks a dedicated metric for quantifying the quality of an image of photoreceptors. Here, we present an approach to evaluating image quality that extracts an estimate of the signal to noise ratio. We evaluated its performance in 528 images of photoreceptors from two AOSLOs, two modalities, and healthy or diseased retinas. The algorithm was compared to expert graders' ratings of the images and previously published image quality metrics. We found no significant difference in the SNR and grades across all conditions. The SNR and the grades of the images were moderately correlated. Overall, this algorithm provides an objective measure of image quality that closely relates to expert assessments of quality in both confocal and split-detector AOSLO images of photoreceptors.

Punished for Success? A Natural Experiment of Displaying Clinical Hospital Quality on Review Platforms

The healthcare market struggles with information asymmetry, limiting patients’ ability to make informed hospital choices. Aiming to bridge this gap, review platforms like Yelp have begun displaying hospitals’ clinical quality data alongside consumer reviews. However, our research uncovers that Yelp’s introduction of maternity care clinical quality measures unexpectedly resulted in lower subsequent Yelp ratings for high-quality hospitals with insufficient staffing. Employing precise foot traffic data and transfer deep learning, we discovered that high-quality, yet understaffed, hospitals experienced a surge in patient volume, which strained their resources and diminished patient satisfaction, leading to negative reviews. This finding has significant implications, signaling the unintended consequences of revealing clinical quality measures, including potential financial losses for hospitals because of reduced federal funding. This research not only contributes to our understanding the dynamics of patient satisfaction but also, offers actionable insights for high-quality hospitals to mitigate the negative impacts of unexpected visibility on review platforms. Our research underscores the importance for patients to discern between objective clinical quality measures and self-reported subjective ratings in their decision-making process. This research applies machine learning and transfer deep learning techniques to healthcare analytics, offering a deeper understanding of the interplay between information disclosure, online reviews, patient satisfaction, and hospital management.

Don't judge a book or health app by its cover: User ratings and downloads are not linked to quality.

To analyse the relationship between health app quality with user ratings and the number of downloads of corresponding health apps. Utilising a dataset of 881 Android-based health apps, assessed via the 300-point objective Organisation for the Review of Care and Health Applications (ORCHA) assessment tool, we explored whether subjective user-level indicators of quality (user ratings and downloads) correlate with objective quality scores in the domains of user experience, data privacy and professional/clinical assurance. For this purpose, we applied spearman correlation and multiple linear regression models. For user experience, professional/clinical assurance and data privacy scores, all models had very low adjusted R squared values (< .02). Suggesting that there is no meaningful link between subjective user ratings or the number of health app downloads and objective quality measures. Spearman correlations suggested that prior downloads only had a very weak positive correlation with user experience scores (Spearman = .084, p = .012) and data privacy scores (Spearman = .088, p = .009). There was a very weak negative correlation between downloads and professional/clinical assurance score (Spearman = -.081, p = .016). Additionally, user ratings demonstrated a very weak correlation with no statistically significant correlations observed between user ratings and the scores (all p > 0.05). For ORCHA scores multiple linear regression had adjusted R-squared = -.002. This study highlights that widely available proxies which users may perceive to signify the quality of health apps, namely user ratings and downloads, are inaccurate predictors for estimating quality. This indicates the need for wider use of quality assurance methodologies which can accurately determine the quality, safety, and compliance of health apps. Findings suggest more should be done to enable users to recognise high-quality health apps, including digital health literacy training and the provision of nationally endorsed "libraries".

Technical assessment of resolution of handheld ultrasound devices and clinical implications.

Since handheld ultrasound devices are becoming increasingly ubiquitous, objective criteria to determine image quality are needed. We therefore conducted a comparison of objective quality measures and clinical performance. A comparison of handheld devices (Butterfly IQ+, Clarius HD, Clarius HD3, Philips Lumify, GE VScan Air) and workstations (GE Logiq E10, Toshiba Aplio 500) was performed using a phantom. As a comparison, clinical investigations were performed by two experienced ultrasonographers by measuring the resolution of anatomical structures in the liver, pancreas, and intestine in ten subjects. Axial full width at half maximum resolution (FWHM) of 100µm phantom pins at depths between one and twelve cm ranged from 0.6-1.9mm without correlation to pin depth. Lateral FWHM resolution ranged from 1.3-8.7mm and was positively correlated with depth (r=0.6). Axial and lateral resolution differed between devices (p<0.001) with the lowest median lateral resolution observed in the E10 (5.4mm) and the lowest axial resolution (1.6mm) for the IQ+ device. Although devices showed no significant differences in most clinical applications, ultrasonographers were able to differentiate a median of two additional layers in the wall of the sigmoid colon and one additional structure in segmental portal fields (p<0.05) using cartwheel devices. While handheld devices showed superior or similar performance in the phantom and routine measurements, workstations still provided superior clinical imaging and resolution of anatomical substructures, indicating a lack of objective measurements to evaluate clinical ultrasound devices.

Person-centred quality indicators are associated with unplanned care use following hospital discharge

ObjectivePerformance indicators are used to evaluate the quality of healthcare services. The majority of these, however, are derived solely from administrative data and rarely incorporate feedback from patients who receive...

Algorithmic Evaluations in Breast Cancer: the Case of Champalimaud Foundation

Algorithmic evaluations are increasingly used to make decisions thanks to the perception of objective measures of quality and performance. However, little is known about how the current evaluation methods change with ML algorithms and with what consequences for the actors and organizations being evaluated. We conducted an exploratory case study in the breast unit of the Champalimaud Foundation in Lisbon. Gioia methodology guided the collection and analysis of semi-structured interviews and archival data. Our results show that besides generating visible and direct changes (e.g., extraction and quantification of relevant criteria with systematic approaches), algorithmic evaluations trigger indirect and less visible dynamics (e.g., adding a new dimension - aesthetic score – in the evaluation of research units), which have profound implications on how institutions operate and how resources are allocated based on the ranking lists. We contribute to digital undertow and institutional displacement and human ML collaborations by explaining the processes through which the new methods are used in medical communities and their less visible yet impactful consequences.

Sleep and electroencephalography biomarkers in preclinical Alzheimer’s Disease

AbstractBackgroundAccumulating evidence supports a bi‐directional relationship between sleep and Alzheimer’s Disease, including sleep disruptions in preclinical Alzheimer’s Disease (pAD), prior to onset of overt cognitive symptoms. Subsequently, sleep phenotypic variables and electroencephalography (EEG) features are attractive noninvasive biomarkers for pAD. The Biomarkers of Alzheimer’s Disease in Sleep and EEG (BASE) study seeks to develop such sleep‐EEG biomarkers for pAD.MethodCommunity‐dwelling participants (n = 52, mean age: 70.8 ± 4.5 years) underwent cognitive testing including Montreal Cognitive Assessment (MOCA, general cognition), Craft Story 21 (CS21, memory), and Trails A and B (visuospatial, executive); performance was z‐scored by age, sex, and education. Objective measures of sleep quality were obtained using actigraphy over 4‐14 (mean 9.1) days at home: wake time after sleep onset (WASO), number of awakenings (NoA), and sleep efficiency. In‐lab overnight polysomnography was performed, and EEG features were extracted during NREM sleep from F3, F4, C3, and C4 channels: relative slow and fast delta power (RSDP, RFDP), spindle density, and slow wave density. The following morning (9‐10AM), CSF was obtained by fasted lumbar puncture, and assessed for amyloid‐b‐42 and tau; pAD was determined by tau/amyloid‐b‐42 ratio. Correlations between cognitive performance and EEG /sleep variables were performed using linear models, adjusted for age, sex, education, and sleep apnea status. Interaction between pAD status and correlations were assessed.ResultThere were 36 biomarker‐negative healthy controls (HC) and 16 with pAD; groups did not significantly differ demographically. RSDP and WASO were negatively associated with CS21 (RSDP: p = 0.040; WASO: p = 0.034). RFDP and NoA interacted with pAD status for MOCA (RFDP: p = 0.010; NoA: p = 0.026), and RFDP interacted with pAD status for CS21 (p = 0.017).ConclusionWe assessed objective sleep quality and sleep‐EEG features against cognitive performance, and any interaction with pAD status. Worse sleep quality was associated with worse memory performance. Among the EEG features assessed, RFDP was strongly negatively correlated with memory performance in those with pAD, suggesting neurophysiological aberrations of NREM sleep in this cohort.

Debate 4: Morphological Assessment of Embryos is Outdated

Motion: For The Outdated Significance of Morphological Assessment in Embryo Selection and the Rise of Advanced Technologies in Reproductive Medicine This symposium lecture presents a compelling debate, shedding light on the diminishing relevance of traditional static morphological assessment as a primary criterion for embryo. The speaker aims to challenge the long-standing reliance on morphological evaluation and advocate for the integration of cutting-edge technologies as a more reliable and objective means of embryo quality assessment. During the debate, the speaker will examine the limitations of morphological assessment, acknowledging its subjective nature, potential bias, and lack of comprehensive insight into embryonic development. The traditional morphological assessment based solely on visual appearance may not adequately predict an embryo’s true potential for successful implantation and healthy pregnancy. A variety of available new technologies will be highlighted during the lecture, showcasing alternatives to morphological embryo assessment. Attendees will gain insight into how these innovative methods can offer more objective and precise measures of embryo quality, enhancing the success rates of assisted reproductive procedures. The symposium will foster an engaging environment, encouraging active participation and thoughtful discussions among attendees from the reproductive medicine community. Participants will have the opportunity to challenge prevailing notions and explore the implications of adopting new technologies in clinical practice. In summary, this debate aims to catalyze a paradigm shift in embryo evaluation, emphasizing the need to move beyond traditional morphological assessment towards embracing advanced technologies, to optimize embryo selection and lead to improved outcomes in IVF. Motion: Against Morphological Assessment of Embryos is Not Outdated In the era of new technologies and artificial intelligence, looking good has never been more important! On-time progression through specific events is requisite for human preimplantation development and provides important visual insights into the health and physiology of the embryo. The formation of 2 distinct pronuclei, the times and patterns of cleavage, and how the cells compact are all key markers of development. Following compaction, the formation of the blastocyst is not only a temporally regulated event, but also an energetically demanding process, one that reflects the metabolic activity (a biomarker of viability) of the embryo. Further, at the blastocyst stage it is possible to visualise and quantitate the formation of both the inner cell mass (ICM) and trophectoderm, with all parameters of blastocyst development linked to transfer outcomes. The development of time-lapse incubation, which can be described as embryo morphology over time, has led to the incorporation of several key morphological features to support embryo selection, further reflecting the significance of embryo morphology. Interestingly, AI algorithms used for embryo selection reflect predominantly those morphological parameters that are known to affect transfer outcomes, such as blastocyst quality. While only specific molecular tests can accurately determine the precise chromosomal composition of an embryo, key morphological features and events can also be used to tag those embryos at greatest risk of being genetically abnormal. In conclusion, key morphological developmental events indirectly inform us of the physiology of the embryo (degree of blastocyst expansion reflects metabolic activity for example), and hence this is why morphological grading systems (such as the Gardner Grade for blastocysts) have been shown to be effective in embryo selection for over the past 25 years, and further have proven to be as useful as AI or biomarker analysis for the majority of patients.

An examination of the impact of age and sleep quality on neurocognition within a multi‐ethnic sample

AbstractBackgroundOlder adults and ethnoracially diverse groups (e.g., non‐Latinx Black (NLB), Latinx) are at higher risk of poor sleep quality. Poor sleep is linked to neurocognitive (NC) decline in middle/older adults, but much of the sleep literature has relied on global NC screening measures. This study examined the effects of age and sleep quality on NC functioning within a multi‐ethnic sample of middle/older adults utilizing a multi‐domain NC battery.MethodThis cross‐sectional study included 119 middle/older adults (M age = 65.3, SD age = 6.9; 46% NLB, 31% Latinx, and 23% non‐Latinx White (NLW); 63% female) who completed demographic questionnaires, the Pittsburgh Sleep Quality Index (PSQI), and a comprehensive NC battery. PSQI global and component scores (e.g., Daytime Dysfunction; PSQI‐DD) measured subjective reporting of sleep quality. Demographically‐adjusted NC T‐scores were used to compute 8 NC‐domain and global average T‐scores. Pearson’s correlations, ANOVA, and multiple regressions were used to test hypotheses.ResultGlobal NC was not related to any PSQI components, and the PSQI components did not differ across ethnoracial groups (all p’s&lt;.05). However, within‐group correlations revealed that the relationship between PSQI components and NC domains significantly differed across ethnoracial groups. For example, frequency of sleep medication usage was significantly negatively correlated with executive functioning in the NLB group (r = ‐.39, p = .02), but not NLW or Latinx groups. Multiple regressions, including age and the interactions between race/ethnicity and PSQI component scores, significantly predicted 21‐39% of the variance in all NC domains (p’s&lt;.05), except attention/working memory (p = .60). The interaction between PSQI‐DD and ethnoracial status significantly predicted memory (p’s&lt;.05); this relationship was positive in the NLW group (B = 20.20), yet negative in the NLB (B = ‐1.16) and Latinx (B = ‐0.56) groups (ps&lt;.05).ConclusionDisordered sleep may have a greater impact on NC functioning, namely memory, among middle/older adults from diverse ethnoracial groups, who are already at heightened risk for NC decline. Importantly, global cognitive screening may be insufficient in examining the effects of sleep quality on NC in middle/older adults. Given the ethnoracial differences in sleep quality, future research should consider culturally‐tailored sleep interventions. Using objective sleep quality measures (e.g., actigraphy) may better quantify sleep components.

Understanding the Relationships Between Sleep Quality and Depression and Anxiety in Neurotrauma: A Scoping Review.

Sleep problems, depression, and anxiety are highly prevalent after a spinal cord injury (SCI) and traumatic brain injury (TBI) and may worsen functional outcomes and quality of life. This scoping review examined the existing literature to understand the relationships between sleep quality, depression, and anxiety in persons with SCI and TBI, and to identify gaps in the literature. A systematic search of seven databases was conducted. The findings of 30 eligible studies reporting associations between sleep quality and depression and/or anxiety after SCI or TBI were synthesized. The included studies were mostly cross-sectional and employed a range of subjective and objective measures of sleep quality. Poor subjective sleep quality and insomnia tended to be significantly associated with increased levels of depression and/or anxiety, but no such associations were reported when sleep quality was measured objectively. Two longitudinal studies observed worsening depressive symptoms over time were related to insomnia and persistent sleep complaints. Two interventional studies found that treating sleep problems improved symptoms of depression and anxiety. The findings of this review suggest that sleep and psychopathology are related in persons with neurotraumatic injuries. This has important therapeutic implications, because individuals may benefit from therapy targeting both sleep and psychological issues. More longitudinal and interventional studies are warranted to further understand the direction and strength of the relationships and how they impact patient outcomes.

Interprofessional staff perspectives on the adoption of or black box technology and simulations to improve patient safety: a multi-methods survey

IntroductionMedical errors still plague healthcare. Operating Room Black Box (ORBB) and ORBB-simulation (ORBBSIM) are innovative emerging technologies which continuously capture as well as categorize intraoperative data, team information, and audio-visual files, in effort to improve objective quality measures. ORBB and ORBBSIM have an opportunity to improve patient safety, yet a paucity of implementation literature exists. Overcoming implementation barriers is critical. This study sought to obtain rich insights while identifying facilitators and barriers to adoption of ORBB and ORBBSIM in alignment with Donabedian’s model of health services and healthcare quality. Enrichment themes included translational performance improvement and real-world examples to develop sessions.MethodsInterprofessional OR staff were invited to complete two surveys assessing staff’s perceptions using TeamSTEPPS’s validated Teamwork Perceptions Questionnaire (T-TPQ) and open-ended questions. Descriptive statistics were calculated for quantitative variables, and inductive phenomenological content analysis was used for qualitative.ResultsSurvey 1 captured 71 responses from 334 invited (RR 21%) while survey 2 captured 47 responses from 157 (RR 29.9%). The T-TPQ score was 65.2, with Communication (70.4) the highest construct and Leadership (58.0) the lowest. Quality Improvement (QI), Patient Safety, and Objective Case Review were the most common perceived ORBB benefits. Trends suggested a reciprocal benefit of dual ORBB and ORBBSIM adoption. Trends also suggested that dual implementation can promote Psychological Safety, culture, trust, and technology comfort. The need for an implementation plan built on change management principles and a constructive culture were key findings.ConclusionsFindings supported ORBB implementation themes from previous literature and deepened our understanding through the exploration of team culture. This blueprint provides a model to help organizations adopt ORBB and ORBBSIM. Outcomes can establish an empirical paradigm for future studies.

P030 Understanding the relationships between sleep quality, and depression and anxiety in neurotrauma: A scoping review.

Abstract Introduction Sleep problems, depression, and anxiety are highly prevalent following a spinal cord injury (SCI) and traumatic brain injury (TBI) and may worsen functional outcomes and quality of life. This scoping review examined the existing literature to understand the relationships between sleep quality, depression, and anxiety in people with SCI and TBI, and to identify gaps in the literature. Methods A systematic search of seven databases was conducted. The findings of 30 eligible studies reporting associations between sleep quality and depression and/or anxiety following SCI or TBI were synthesised. Results The included studies were mostly cross-sectional and employed a range of subjective and objective measures of sleep quality. Poor subjective sleep quality and insomnia tended to be significantly associated with increased levels of depression and/or anxiety, but no such associations were reported when sleep quality was measured objectively. Two longitudinal studies observed worsening depressive symptoms over time were related to insomnia and persistent sleep complaints. Two interventional studies found that treating sleep problems improved symptoms of depression and anxiety. Discussion The findings of this review suggest that sleep and psychopathology are related in people with neurotraumatic injuries. This has important therapeutic implications, as individuals may benefit from therapy targeting both sleep and psychological issues. More longitudinal and interventional studies are warranted to further understand the direction and strength of the relationships, and how they impact patient outcomes.

Pretreatment Cancer-Related Cognitive Impairment in Hodgkin Lymphoma Patients.

Cancer-related cognitive impairment (CRCI) is one of the most serious side effects of cancer that negatively impacts the quality of life of cancer patients and survivors. There is evidence of CRCI in Hodgkin lymphoma patients (HL); however, there is a lack of studies examining the presence of cognitive deficits before starting any treatment in HL patients. Forty adult patients (N = 40) newly diagnosed with HL (with no previous cancer diagnoses) and 40 healthy controls (N = 40) matched for age, sex, education, and premorbid intellect completed the neuropsychological battery and subjective and objective measures of affective distress and quality of life. The results showed impairment in three out of six cognitive domains: verbal memory and learning, speed of processing/psychomotor speed, and abstraction/executive functions in the HL patients before the initiation of any treatment. The speed of processing/psychomotor speed domain is negatively correlated with depression. Cognitive deterioration in verbal memory and learning and abstraction/executive functions domains in HL patients seems to occur before the initiation of treatment independently of anxiety, depression, or physical symptoms. This suggests that HL itself may cause cognitive deficits in these cognitive domains. However, the underlying causes of CRCI still remain unclear.