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Objective: The precise measurement of treatment fidelity (quantity and quality in the delivery of treatment strategies in an intervention) is essential for intervention development, evaluation, and implementation. Various informants are used in fidelity assessment (e.g., observers, practitioners [clinicians, teachers], clients), but these informants often do not agree on ratings. This scoping review aims to ascertain the state of science around multi-informant assessment of treatment fidelity. Method: A literature search of articles published through December 2021 identified 673 articles. Screening reduced the number of articles to 44, and the final study set included 35 articles. Results: There was substantial variability across studies regarding study design, how fidelity was operationalized, and how reliability was defined and assessed. Most studies evaluated the agreement between independent observers and practitioner-report, though several other informant pairs were assessed. Overall, findings suggest that concordance across fidelity informants was low to moderate, with a few key exceptions. Conclusions: It is difficult to draw clear conclusions about the degree to which single versus multiple informant assessment is needed to produce an accurate and complete picture of treatment fidelity. The field needs to take steps to determine how to leverage multi-informant assessment to accurately assess treatment fidelity.

Introduction: Due to usability, feasibility, and acceptability concerns, observational treatment fidelity measures are often challenging to deploy in schools. Teacher self-report fidelity measures with specific design features might address some of these barriers. This case study outlines a community-engaged, iterative process to adapt the observational Treatment Integrity for Elementary Settings (TIES-O) to a teacher self-report version designed to assess the use of practices to support children's social-emotional competencies in elementary classrooms. Method: Cognitive walkthrough interviews were conducted with teachers to improve the usability of the teacher self-report measure, called the Treatment Integrity for Elementary Schools-Teacher Report (TIES-T). Qualitative content analysis was used to extract themes from the interviews and inform changes to the measure. Results: Increasing clarity and interactive elements in the measure training were the dominant themes, but suggestions for the measure format and jargon were also suggested. Conclusion: The suggested changes resulted in a brief measure, training, and feedback system designed to support the teacher's use of practices to support children's social-emotional competencies in elementary classrooms. Future research with the TIES-T will examine the score reliability and validity of the measure.

Abstract Parasites, such as the malaria parasite P. falciparum, are critically dependent on host nutrients. Interference with nutrient uptake can lead to parasite death and, therefore, serve as a successful treatment strategy. P. falciparum parasites cannot synthesise cholesterol, and instead source this lipid from the host. Here, we tested whether cholesterol uptake pathways could be ‘hijacked’ for optimal drug delivery to the intracellular parasite. We found that fluorescent cholesterol analogues were delivered from the extracellular environment to the intracellular parasite. We investigated the uptake and inhibitory effects of conjugate compounds, where proven antimalarial drugs (primaquine and artesunate) were attached to steroids that mimic the structure of cholesterol. These conjugated antimalarial drugs improved the inhibitory effects against multiple parasite lifecycle stages, multiple parasite species, and drug-resistant parasites, whilst also lowering the toxicity to human host cells. Steroids with introduced peroxides also displayed antimalarial activity. These results provide a proof-of-concept that cholesterol mimics can be developed as a drug delivery system against apicomplexan parasites with the potential to improve drug efficacy, increase therapeutic index, and defeat drug resistance.

Abstract Background Healthcare restrictions during the COVID-19 pandemic, particularly in ophthalmology, led to a differential underutilization of care. An analytic approach is needed to characterize pandemic health services usage across many conditions. Methods A common analytical framework identified pandemic care utilization patterns across 261 ophthalmic diagnoses. Using a United States eye care registry, predictions of utilization expected without the pandemic were established for each diagnosis via models trained on pre-pandemic data. Pandemic effects on utilization were estimated by calculating deviations between observed and expected patient volumes from January 2020 to December 2021, with two sub-periods of focus: the hiatus (March-May 2020) and post-hiatus (June 2020–December 2021). Deviation patterns were analyzed using cluster analyses, data visualizations, and hypothesis testing. Results Records from 44.62 million patients and 2455 practices show lasting reductions in ophthalmic care utilization, including visits for leading causes of visual impairment (age-related macular degeneration, diabetic retinopathy, cataract, glaucoma). Mean deviations among all diagnoses are 67% below expectation during the hiatus peak, and 13% post-hiatus. Less severe conditions experience greater utilization reductions, with heterogeneities across diagnosis categories and pandemic phases. Intense post-hiatus reductions occur among non-vision-threatening conditions or asymptomatic precursors of vision-threatening diseases. Many conditions with above-average post-hiatus utilization pose a risk for irreversible morbidity, such as emergent pediatric, retinal, or uveitic diseases. Conclusions We derive high-resolution insights on pandemic care utilization in the US from high-dimensional data using an analytical framework that can be applied to study healthcare disruptions in other settings and inform efforts to pinpoint unmet clinical needs.

Student responsiveness's role in promoting intervention outcomes for students who exhibit problem behavior is understudied. Due to the relational nature of many interventions delivered by teachers that target social, emotional, or behavioral outcomes of students in classrooms, it is essential to assess how responsive students are to teachers' attempts to engage them in the intervention, particularly for students with problem behaviors that may impede teachers' attempts to engage these students in intervention effectively. In the current study, we combine samples from four randomized controlled trials to examine the relationship between student outcomes and teacher attempts to deliver BEST in CLASS, a Tier 2 intervention, via student responsiveness. Delivery of BEST in CLASS and student responsiveness were assessed through direct observations and teachers' reported measures. Results suggest that teacher adherence and competence in delivering BEST in CLASS practices was associated with reductions in problem behavior from pretest to post-test via student responsiveness. Limitations of the current study and implications for future research are discussed.

BackgroundPrevious work suggests that Google searches could be useful in identifying conjunctivitis epidemics. Content-based assessment of social media content may provide additional value in serving as early indicators of conjunctivitis and other systemic infectious diseases. ObjectiveWe investigated whether large language models, specifically GPT-3.5 and GPT-4 (OpenAI), can provide probabilistic assessments of whether social media posts about conjunctivitis could indicate a regional outbreak. MethodsA total of 12,194 conjunctivitis-related tweets were obtained using a targeted Boolean search in multiple languages from India, Guam (United States), Martinique (France), the Philippines, American Samoa (United States), Fiji, Costa Rica, Haiti, and the Bahamas, covering the time frame from January 1, 2012, to March 13, 2023. By providing these tweets via prompts to GPT-3.5 and GPT-4, we obtained probabilistic assessments that were validated by 2 human raters. We then calculated Pearson correlations of these time series with tweet volume and the occurrence of known outbreaks in these 9 locations, with time series bootstrap used to compute CIs. ResultsProbabilistic assessments derived from GPT-3.5 showed correlations of 0.60 (95% CI 0.47-0.70) and 0.53 (95% CI 0.40-0.65) with the 2 human raters, with higher results for GPT-4. The weekly averages of GPT-3.5 probabilities showed substantial correlations with weekly tweet volume for 44% (4/9) of the countries, with correlations ranging from 0.10 (95% CI 0.0-0.29) to 0.53 (95% CI 0.39-0.89), with larger correlations for GPT-4. More modest correlations were found for correlation with known epidemics, with substantial correlation only in American Samoa (0.40, 95% CI 0.16-0.81). ConclusionsThese findings suggest that GPT prompting can efficiently assess the content of social media posts and indicate possible disease outbreaks to a degree of accuracy comparable to that of humans. Furthermore, we found that automated content analysis of tweets is related to tweet volume for conjunctivitis-related posts in some locations and to the occurrence of actual epidemics. Future work may improve the sensitivity and specificity of these methods for disease outbreak detection.

Mental health clinicians and administrators are increasingly asked to collect and report treatment outcome data despite numerous challenges to select and use instruments in routine practice. Measurement-based care (MBC) is an evidence-based practice for improving patient care. We propose that data collected from MBC processes with patients can be strategically leveraged by agencies to also support clinicians and respond to accountability requirements. MBC data elements are outlined using the Precision Mental Health Framework (Bickman et al. in Adm Policy Mental Health Mental Health Serv Res 43:271-276, 2016), practical guidance is provided for agency administrators, and conceptual examples illustrate strategic applications of one or more instruments to meet various needs throughout the organization.

BackgroundProviding high-quality early childhood care and education is understood as key to maximizing children's potential to succeed later in life, as it stimulates young children's development of skills and competencies needed to promote optimal outcomes and success later in life. Despite the government's efforts to support the early childhood sector, educators in Singapore continue to report difficulties in implementing practices in classrooms that promote children's social, emotional, and cognitive development. To enhance educators' skills in these domains, we developed the Enhancing And Supporting Early development to better children's Lives (EASEL) Approach, a set of universal, educator-delivered practices for use with 3-6-year-old children in early childhood settings to improve social, emotional, behavioral, and executive functioning (SEB+EF) outcomes.MethodsThis study will evaluate the effectiveness and implementation of the EASEL Approach in improving early childhood educators' teaching practices and, in turn, children's SEB+EF outcomes. We will conduct a cluster randomized controlled trial with a type 2 hybrid effectiveness-implementation study in 16 childcare centers. The EPIS (Explore, Prepare, Implement, Sustain) Framework will be used to inform the implementation of the EASEL Approach. Implementation strategies include training, educator self-assessments, practice-based coaching, and data monitoring. Our primary outcome is educators' teaching practices. Secondary outcomes include educators' adoption of the EASEL Approach in everyday practice, the acceptability and feasibility of the EASEL Approach, and children's SEB+EF outcomes. Quantitative and qualitative data will be collected at baseline, six months, and after implementation.ConclusionFindings from this study will provide significant evidence on the effectiveness of the EASEL Approach in improving educators' teaching practices and its impact on children's SEB+EF outcomes and the implementation of the EASEL Approach in early childhood classrooms in Singapore.Trial registrationThis study was prospectively registered on ClinicalTrials.gov, Identifier: NCT05445947 on 6th July 2022.

Problem-solving (PS) has been identified as a therapeutic technique found in multiple evidence-based treatments for depression. To further understand for whom and how this intervention works, we undertook a systematic review of the evidence for PS's effectiveness in preventing and treating depression among adolescents and young adults. We searched electronic databases (PsycINFO, Medline, and Cochrane Library) for studies published between 2000 and 2022. Studies meeting the following criteria were included: (a) the intervention was described by authors as a PS intervention or including PS; (b) the intervention was used to treat or prevent depression; (c) mean or median age between 13-25 years; (d) at least one depression outcome was reported. Risk of bias of included studies was assessed using the Cochrane Risk of Bias 2.0 tool. A narrative synthesis was undertaken given the high level of heterogeneity in study variables. Twenty-five out of 874 studies met inclusion criteria. The interventions studied were heterogeneous in population, intervention, modality, comparison condition, study design, and outcome. Twelve studies focused purely on PS; 13 used PS as part of a more comprehensive intervention. Eleven studies found positive effects in reducing depressive symptoms and two in reducing suicidality. There was little evidence that the intervention impacted PS skills or that PS skills acted as a mediator or moderator of effects on depression. There is mixed evidence about the effectiveness of PS as a prevention and treatment of depression among AYA. Our findings indicate that pure PS interventions to treat clinical depression have the strongest evidence, while pure PS interventions used to prevent or treat sub-clinical depression and PS as part of a more comprehensive intervention show mixed results. Possible explanations for limited effectiveness are discussed, including missing outcome bias, variability in quality, dosage, and fidelity monitoring; small sample sizes and short follow-up periods.

This study examines the implications of the coronavirus pandemic for college students' health and education, with special attention to variation by disability status. Disaster research supports the hypothesis that students with disabilities will experience higher-than-usual levels of pandemic-related stress, which could lead to re-evaluations of their educational expectations and declines in health. We evaluate this hypothesis by modeling changes in students’ (1) mental and physical health and (2) educational expectations during the first year (spring of 2020 to spring of 2021) of the pandemic, using survey data collected from a population-based sample of college students in the state of Indiana. Although we observe across-the-board declines in both domains, students with disabilities were especially vulnerable. Mediation analyses suggest that differential exposure to financial and illness-related stressors is partially to blame, explaining a significant portion of the group differences between students with and without disabilities. We interpret these results as evidence of the unique vulnerabilities associated with disability status and its wide-ranging importance as a dimension of social stratification.

Background The current gold standard for measuring fidelity (specifically, adherence) to cognitive behavioral therapy (CBT) is direct observation, a costly, resource-intensive practice that is not feasible for many community organizations to implement regularly. Recent research indicates that behavioral rehearsal (i.e., role-play between clinician and individual with regard to session delivery) and chart-stimulated recall (i.e., brief structured interview between clinician and individual about what they did in session; clinicians use the client chart to prompt memory) may provide accurate and affordable alternatives for measuring adherence to CBT in such settings, with behavioral rehearsal yielding greater correspondence with direct observation. Methods Drawing on established causal theories from social psychology and leading implementation science frameworks, this study evaluates stakeholders’ intention to use behavioral rehearsal and chart-stimulated recall. Specifically, we measured attitudes, self-efficacy, and subjective norms toward using each, and compared these factors across the two methods. We also examined the relationship between attitudes, self-efficacy, subjective norms, and intention to use each method. Finally, using an integrated approach we asked stakeholders to discuss their perception of contextual factors that may influence beliefs about using each method. These data were collected from community-based supervisors ( n = 17) and clinicians ( n = 66). Results Quantitative analyses suggest moderately strong intention to use both methods across stakeholders. There were no differences in supervisors’ or clinicians’ attitudes, self-efficacy, subjective norms, or intention across methods. More positive attitudes and greater reported subjective norms were associated with greater reported intention to use either measure. Qualitative analyses identified participants’ specific beliefs about using each fidelity measure in their organization, and results were organized using the Consolidated Framework for Implementation Research. Conclusions Strategies are warranted to overcome or minimize potential barriers to using fidelity measurement methods and to further increase the strength of intention to use them. Plain Language Summary: The best way to measure fidelity, or how closely a clinician follows the protocol, to Cognitive Behavioral Therapy (CBT) is watching the session. This is an expensive practice that is not feasible for many community organizations to do regularly. Recent research indicates that behavioral rehearsal, or a role-play between the clinician and individual with regard to session delivery, and chart-stimulated recall, or a brief discussion between an individual and the clinician about what they did in session with the clinician having access to the chart to help them remember, may provide accurate and affordable alternatives for measuring fidelity to CBT. We just completed a study demonstrating that both methods are promising, with behavioral rehearsal offering scores that are the most similar to watching the session. Drawing on established theories from social psychology and leading implementation science frameworks, this study evaluates future supervisor and clinician motivation to use these fidelity measurement methods. Specifically, we measured supervisor (n = 17) and clinician (n = 66) attitudes, norms, self-efficacy, intentions, and anticipated barriers and facilitators to using each of these fidelity measurement tools. Quantitative and qualitative analyses suggest similar intention to use both methods, and concerns about barriers to using each method. Further research is warranted to minimize the burden associated with implementing fidelity measurement methods and deploying strategies to increase use.

BackgroundStudies suggest diurnal patterns of occurrence of some eye conditions. Leveraging new information sources such as web-based search data to learn more about such patterns could improve the understanding of patients’ eye-related conditions and well-being, better inform timing of clinical and remote eye care, and improve precision when targeting web-based public health campaigns toward underserved populations. ObjectiveTo investigate our hypothesis that the public is likely to consistently search about different ophthalmologic conditions at different hours of the day or days of week, we conducted an observational study using search data for terms related to ophthalmologic conditions such as conjunctivitis. We assessed whether search volumes reflected diurnal or day-of-week patterns and if those patterns were distinct from each other. MethodsWe designed a study to analyze and compare hourly search data for eye-related and control search terms, using time series regression models with trend and periodicity terms to remove outliers and then estimate diurnal effects. We planned a Google Trends setting, extracting data from 10 US states for the entire year of 2018. The exposure was internet search, and the participants were populations who searched through Google’s search engine using our chosen study terms. Our main outcome measures included cyclical hourly and day-of-week web-based search patterns. For statistical analyses, we considered P

Abstract Radiotherapy can effectively kill malignant cells, but the doses required to cure cancer patients may inflict severe collateral damage to adjacent healthy tissues. Recent technological advances in the clinical application has revitalized hyperthermia treatment (HT) as an option to improve radiotherapy (RT) outcomes. Understanding the synergistic effect of simultaneous thermoradiotherapy via mathematical modelling is essential for treatment planning. We here propose a theoretical model in which the thermal enhancement ratio (TER) relates to the cell fraction being radiosensitised by the infliction of sublethal damage through HT. Further damage finally kills the cell or abrogates its proliferative capacity in a non-reversible process. We suggest the TER to be proportional to the energy invested in the sensitisation, which is modelled as a simple rate process. Assuming protein denaturation as the main driver of HT-induced sublethal damage and considering the temperature dependence of the heat capacity of cellular proteins, the sensitisation rates were found to depend exponentially on temperature; in agreement with previous empirical observations. Our findings point towards an improved definition of thermal dose in concordance with the thermodynamics of protein denaturation. Our predictions well reproduce experimental in vitro and in vivo data, explaining the thermal modulation of cellular radioresponse for simultaneous thermoradiotherapy.

International students bring academic, cultural, and economic value to universities around the world. However, adjustments for these students can be difficult as a result of culture shock, resulting in early exit from the university. In order to help inform university personnel on how to better assist international students, this study examines the interpersonal, psychological, and physiological symptoms of culture shock of three Korean international graduate students at a large public university in the southwest United States. Data were collected through three interviews and seven weekly online journals. The findings uncovered the existence of culture shock for each of the three participants to differing degrees at various times throughout the semester. In particular, a comparatively higher incidence of interpersonal and psychological culture shock symptoms compared with physiological ones was displayed, thus showing strong support for theories that conceptualize culture shock as individualized in nature. In addition, the data revealed that personal characteristics, family, religion, and exercise all played a role in the participants' abilities to cope with culture shock. The results of this study could help universities better understand and support international students, ensuring that the university can benefit from the unique value these students bring to campus.

BackgroundIn a prior study at the start of the pandemic, we reported reduced numbers of Google searches for the term “conjunctivitis” in the United States in March and April 2020 compared with prior years. As one explanation, we conjectured that reduced information-seeking may have resulted from social distancing reducing contagious conjunctivitis cases. Here, after 1 year of continued implementation of social distancing, we asked if there have been persistent reductions in searches for “conjunctivitis,” and similarly for other communicable disease terms, compared to control terms. ObjectiveThe aim of this study was to determine if reduction in searches in the United States for terms related to conjunctivitis and other common communicable diseases occurred in the spring-winter season of the COVID-19 pandemic, and to compare this outcome to searches for terms representing noncommunicable conditions, COVID-19, and to seasonality. MethodsWeekly relative search frequency volume data from Google Trends for 68 search terms in English for the United States were obtained for the weeks of March 2011 through February 2021. Terms were classified a priori as 16 terms related to COVID-19, 29 terms representing communicable conditions, and 23 terms representing control noncommunicable conditions. To reduce bias, all analyses were performed while masked to term names, classifications, and locations. To test for the significance of changes during the pandemic, we detrended and compared postpandemic values to those expected based on prepandemic trends, per season, computing one- and two-sided P values. We then compared these P values between term groups using Wilcoxon rank-sum and Fisher exact tests to assess if non-COVID-19 terms representing communicable diseases were more likely to show significant reductions in searches in 2020-2021 than terms not representing such diseases. We also assessed any relationship between a term’s seasonality and a reduced search trend for the term in 2020-2021 seasons. P values were subjected to false discovery rate correction prior to reporting. Data were then unmasked. ResultsTerms representing conjunctivitis and other communicable conditions showed a sustained reduced search trend in the first 4 seasons of the 2020-2021 COVID-19 pandemic compared to prior years. In comparison, the search for noncommunicable condition terms was significantly less reduced (Wilcoxon and Fisher exact tests, P

Purpose: To describe a unique case of LASIK flap fungal keratitis confirmed by next generation sequencing. Observations: A 56-year-old female presented with refractory keratitis involving her LASIK flap 21 years after surgery. Confocal was positive for filamentous structures. The patient underwent immediate flap amputation followed by topical antifungal treatment. Corneal culture was positive for Acremonium sp. Metagenomic deep sequencing confirmed Acremonium as the primary source of infection and also identified Fusarium as a likely contributor of a mixed fungal infection. Sequencing also identified hay as the likely source of the infection. Treatment resulted in eradication of the infection. The patient's final best corrected visual acuity was 20/30 with rigid contact lens overrefraction. Conclusions: Metagenomic deep sequencing is a novel diagnostic tool that is increasingly being utilized for diagnosis of refractory keratitis. This case demonstrates the diagnostic potential of deep sequencing for identifying post-LASIK keratitis and reinforces the utility of LASIK flap amputation in the setting of tectonic flap instability due to keratolysis. Importance: This case highlights several important clinical points for treating LASIK flap keratitis and highlights the emerging role metagenomic sequencing has in the diagnosis of infectious keratitis. This is first known case using next generation sequencing to diagnose a post-LASIK infectious keratitis.

In this exploratory study, we studied and qualitatively evaluated a prototype video data collection system to capture and analyze fish behavior in a small-scale indoor aquaculture operation. The research objective was to design and develop a hardware / software system that would have the potential to capture meaningful data from which to extract fish size, swim trajectory, and swim velocity, ultimately as information toward an assessment of fish health. The initial work presented in this paper discusses the development choices of the prototype system, including various combinations of lighting and camera positions both inside and outside of the aquaculture tanks, and several post-processing techniques to isolate fish in video, calibrate the distance from camera to fish through water, and infer fish trajectories and swim velocities. Preliminary results provided a qualitative assessment of such a system. Specific results on the system's ability to detect fishes' positions, trajectories, and velocities are presently limited to observational outcomes and descriptive statistics rather than large-scale quantitative analysis. The present work lays a foundation for a future commercially hardened system that would be required for the collection of larger datasets, which would in turn facilitate the future development of machine learning (ML) algorithms to begin to statistically correlate data to fish conditions and behaviors in near-real time.

The study of urinary phase II sulfate metabolites is central to understanding the role and fate of endogenous and exogenous compounds in biological systems. This study describes a new workflow for the untargeted metabolic profiling of sulfated metabolites in a urine matrix. Analysis was performed using ultra-high-performance liquid chromatography-high resolution tandem mass spectrometry (UHPLC-HRMS/MS) with data dependent acquisition (DDA) coupled to an automated script-based data processing pipeline and differential metabolite level analysis. Sulfates were identified through k-means clustering analysis of sulfate ester derived MS/MS fragmentation intensities. The utility of the method was highlighted in two applications. Firstly, the urinary metabolome of a thoroughbred horse was examined before and after administration of the anabolic androgenic steroid (AAS) testosterone propionate. The analysis detected elevated levels of ten sulfated steroid metabolites, three of which were identified and confirmed by comparison with synthesised reference materials. This included 5α-androstane-3β,17α-diol 3-sulfate, a previously unreported equine metabolite of testosterone propionate. Secondly, the hydrolytic activity of four sulfatase enzymes on pooled human urine was examined. This revealed that Pseudomonas aeruginosa arylsulfatases (PaS) enzymes possessed higher selectivity for the hydrolysis of sulfated metabolites than the commercially available Helix pomatia arylsulfatase (HpS). This novel method provides a rapid tool for the systematic, untargeted metabolic profiling of sulfated metabolites in a urinary matrix.

Abstract Background This paper is part of a series comparing different psychometric approaches to evaluate patient-reported outcome (PRO) measures using the same items and dataset. We provide an overview and example application to demonstrate 1) using item response theory (IRT) to identify poor and well performing items; 2) testing if items perform differently based on demographic characteristics (differential item functioning, DIF); and 3) balancing IRT and content validity considerations to select items for short forms. Methods Model fit, local dependence, and DIF were examined for 51 items initially considered for the Patient-Reported Outcomes Measurement Information System® (PROMIS®) Depression item bank. Samejima’s graded response model was used to examine how well each item measured severity levels of depression and how well it distinguished between individuals with high and low levels of depression. Two short forms were constructed based on psychometric properties and consensus discussions with instrument developers, including psychometricians and content experts. Calibrations presented here are for didactic purposes and are not intended to replace official PROMIS parameters or to be used for research. Results Of the 51 depression items, 14 exhibited local dependence, 3 exhibited DIF for gender, and 9 exhibited misfit, and these items were removed from consideration for short forms. Short form 1 prioritized content, and thus items were chosen to meet DSM-V criteria rather than being discarded for lower discrimination parameters. Short form 2 prioritized well performing items, and thus fewer DSM-V criteria were satisfied. Short forms 1–2 performed similarly for model fit statistics, but short form 2 provided greater item precision. Conclusions IRT is a family of flexible models providing item- and scale-level information, making it a powerful tool for scale construction and refinement. Strengths of IRT models include placing respondents and items on the same metric, testing DIF across demographic or clinical subgroups, and facilitating creation of targeted short forms. Limitations include large sample sizes to obtain stable item parameters, and necessary familiarity with measurement methods to interpret results. Combining psychometric data with stakeholder input (including people with lived experiences of the health condition and clinicians) is highly recommended for scale development and evaluation.

Background: Developing pragmatic assessment tools to measure clinician use of evidence-based practices is critical to advancing implementation of evidence-based practices in mental health. This case study details our community-partnered process of developing the Therapy Process Observation Coding Scale-Self-Reported Therapist Intervention Fidelity for Youth (TPOCS-SeRTIFY), a pragmatic, clinician-report instrument to measure cognitive behavioral therapy (CBT) delivery. Approach: We describe a five-step community-partnered development process. Initial goals were to create a self-report instrument that paralleled an existing direct observation measure of clinician delivery of CBT use to facilitate later assessment of measure performance. Cognitive interviews with community clinicians ( n = 6) and consultation with CBT experts ( n = 6) were used to enhance interpretability and usability as part of an iterative refinement process. The instrument was administered to 247 community clinicians along with an established self-reported measure of clinician delivery of CBT and other treatments to assess preliminary psychometric performance. Preliminary psychometrics were promising. Conclusion: Our community-partnered development process showed promising success and can guide future development of pragmatic implementation measures both to facilitate measurement of ongoing implementation efforts and future research aimed at building learning mental health systems. Plain language summary Developing brief, user-friendly, and accurate tools to measure how therapists deliver cognitive behavioral therapy (CBT) in routine practice is important for advancing the reach of CBT into community settings. To date, developing such “pragmatic” measures has been difficult. There is little known about how researchers can best develop these types of assessment tools so that they (1) are easy for clinicians in practice to use and (2) provide valid and useful information about implementation outcomes. As a result, there are few well-validated measures in existence that measure therapist use of CBT that are feasible for use in community practice. This paper contributes to the literature by describing our community-partnered process for developing a measure of therapist use of CBT (Therapy Process Observation Coding Scale -Self-Reported Therapist Intervention Fidelity for Youth; TPOCS-SeRTIFY). This descriptive case study outlines the community-partnered approach we took to develop this measure. This case study will contribute to future research by serving as a guide to others aiming to develop pragmatic implementation measures. In addition, the TPOCS-SeRTIFY is a pragmatic measure of clinician use of CBT that holds promise for its use by both researchers and clinicians to measure the success of CBT implementation efforts.

Gut integrity impairment leading to increased intestinal permeability (IP) is hypothesized to be a trigger of critically illness. Approximately 15–20% of human ischemic stroke (IS) victims require intensive care, including patients with impaired level of consciousness or a high risk for developing life-threatening cerebral edema. Local and systemic inflammatory reactions are a major component of the IS pathophysiology and can significantly aggravate brain tissue damage. Intracerebral inflammatory processes following IS have been well studied. Until now, less is known about systemic inflammatory responses and IS consequences apart from a frequently observed post-IS immunosuppression. Here, we provide a hypothesis of a crosstalk between systemic acute phase response (APR), IP and potential secondary brain damage during acute and subacute IS stages supported by preliminary experimental data. Alterations of the acute phase proteins (APPs) C-reactive protein and lipopolysaccharide-binding protein and serum level changes of antibodies directed against Escherichia coli-cell extract antigen (IgA-, IgM-, and IgG-anti-E. coli) were investigated at 1, 2, and 7 days following IS in ten male sheep. We found an increase of both APPs as well as a decrease of all anti-E. coli antibodies within 48 h following IS. This may indicate an early systemic APR and increased IP, and underlines the importance of the increasingly recognized gut-brain axis and of intestinal antigen release for systemic immune responses in acute and subacute stroke stages.