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Currently, suicidality is inadequately engaged with in suicide prevention methods. The key focus is on preventing people from dying, rather than validating suicidal ideation as a legitimate experience. As Alexandre Baril (2017; 2018; 2002) argues, in this refusal to validate suicidality, suicidal people are subjected to suicidism – a term Baril coined to describe the oppression suicidal people face which silences them and views their desire to die as illegitimate. Baril (2017) argues for a harm reduction approach to suicide which not only recognizes the validity of suicidality, but also supports suicidal people should they choose to die. In this paper, I seek to highlight Baril’s argument on affirming the choices of suicidal people through an engagement with three of his ideas: epistemic violence, biopower, and the injunction to happiness. While I agree with Baril’s harm reduction approach to suicide, I also contend that his argument becomes more complex when shifting from theory to practice. Therefore, alongside Baril’s work, I highlight the work of Kai Cheng Thom, who recognizes that failing to fight for suicidal people is equally as ableist as failing to listen to them.

BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. OBJECTIVES: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50≤50mg/kg)], and nontoxic chemicals (LD50>2,000mg/kg). METHODS: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. RESULTS: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results. DISCUSSION: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495.

Studying humor in the rehabilitation professions is important given its positive effects on health and well-being. We conducted a scoping review to understand how the use of humor has been explored in the existing literature in four rehabilitation professions. The rehabilitation professions included audiology, speech-language pathology, physical therapy, and occupational therapy. The five-stage method identified by Arksey and O’Malley was used to conduct this review. Six databases were searched. We included 57 articles in our final review, summarized in a narrative synthesis. We generated seven themes in our analysis: (1) humour as a management strategy in therapy; (2) humour as a power establisher vs. equalizer; (3) humour as a coping mechanism in rehabilitation; (4) conceptualizations of non-verbal humor cues in therapy; (5) Is humour trainable? (6) Humor used to foster group cohesion; and (7) Attitudes and beliefs surrounding humor practice. Our findings emphasize the importance of using humor in the rehabilitation professions, and the ways in which humor is conceptualized in a multitude of ways for both clinician and client. Future work is needed to further understand the presence and use of humor in rehabilitation professions.IMPLICATIONS FOR REHABILITATIONIn a scoping review of the literature, this study showed that humor was used mainly positively in rehabilitation by the included professions of audiology, speech-language pathology, physical therapy, and occupational therapy and contributed to a sense of belonging.Humor may be an effective way to improve management of client/clinician relations as well as improving group cohesion in rehabilitation settings.In the rehabilitation professions of audiology, speech-language pathology, physical therapy, and occupational therapy, non-verbal humor cues were used in instances where communication was difficult or impaired for clients. In a scoping review of the literature, this study showed that humor was used mainly positively in rehabilitation by the included professions of audiology, speech-language pathology, physical therapy, and occupational therapy and contributed to a sense of belonging. Humor may be an effective way to improve management of client/clinician relations as well as improving group cohesion in rehabilitation settings. In the rehabilitation professions of audiology, speech-language pathology, physical therapy, and occupational therapy, non-verbal humor cues were used in instances where communication was difficult or impaired for clients.

Background To understand our performance with respect to the collection and reporting of patient-reported outcome (PRO) measure (PROM) data, we examined the protocol content, data completeness and publication of PROs from interventional trials conducted at the Royal Marsden NHS Foundation Trust (RM) and explored factors associated with data missingness and PRO publication. Design From local records, we identified closed, intervention trials sponsored by RM that opened after 1995 and collected PROMs as primary, secondary or exploratory outcomes. Protocol data were extracted by two researchers and scored against the SPIRIT-PRO (PRO protocol content checklist; score 0–100, higher scores indicate better completeness). For studies with locally held datasets, the information team summarized for each study, PRO completion defined as the number of expected (as per protocol) PRO measurements versus the number of actual (i.e. completed) PRO measurements captured in the study data set. Relevant publications were identified by searching three online databases and chief investigator request. Data were extracted and each publication scored against the CONSORT-PRO (PRO manuscript content checklist; scored as SPIRIT-PRO above). Descriptive statistics are presented with exploratory comparisons of point estimates and 95% confidence intervals. Results Twenty-six of 65 studies were included in the review. Nineteen studies had accessible datasets and 18 studies published at least one article. Fourteen studies published PRO results. Most studies had a clinical (rather than PRO) primary outcome (16/26). Across all studies, responses in respect of 35 of 69 PROMs were published. Trial protocols scored on average 46.7 (range 7.1–92.9) on the SPIRIT-PRO. Among studies with accessible data, half (10/19) had less than 25% missing measurements. Publications scored on average 80.9 (range 36–100%) on the CONSORT-PRO. Studies that published PRO results had somewhat fewer missing measurements (19% [7–32%] vs 60% [− 26 to 146%]). For individual PROMs within studies, missing measurements were lower for those that were published (17% [10–24%] vs 41% [18–63%]). Studies with higher SPIRIT-PRO scores and PROs as primary endpoints (13% [4–22%] vs 39% [10–58%]) had fewer missing measurements. Conclusions Missing data may affect publication of PROs. Extent of inclusion of SPIRIT-PRO protocol items and PROs as primary endpoints may improve data completeness. Preliminary evidence from the study suggests a future larger study examining the relationship between PRO completion and publication is warranted.

Having a measure of confidence in computational predictions of biological activity from in silico tools is vital when making predictions for new chemicals, for example, in chemical risk assessment. Where predictions of biological activity are used as an indicator of a potential hazard, false-negative predictions are the most concerning prediction; however, assigning confidence in inactive predictions is particularly challenging. How can one confidently identify the absence of activating features? In this study, we present methods for assigning confidence to both active and inactive predictions from structural alerts for protein-binding molecular initiating events (MIEs). Structural alerts were derived through an iterative statistical method. Confidence in the activity predictions is assigned by measuring the Tanimoto similarity between Morgan fingerprints of chemicals in the test set to relevant chemicals in the training set, and suitable cutoff values have been defined to give different confidence categories. To avoid a potential compound series bias in the test set and hence overestimate the performance of the method, we measured the biological activity of 27 compounds with 24 proteins, which gave us an additional 648 experimental measurements; many of the measurements are currently nonexistent in the literature and databases. This data set was complemented with newly measured biological activities published in ChEMBL25 and formed a combined independent validation data set. Applying the confidence categories to the computational predictions for the new data leads to the identification of chemicals for which one should be confident of either an inactive or active prediction, allowing model predictions to be used responsibly.

Deep learning neural networks, constructed for the prediction of chemical binding at 79 pharmacologically important human biological targets, show extremely high performance on test data (accuracy 92.2 ± 4.2%, MCC 0.814 ± 0.093 and ROC-AUC 0.96 ± 0.04). A new molecular similarity measure, Neural Network Activation Similarity, has been developed, based on signal propagation through the network. This is complementary to standard Tanimoto similarity, and the combined use increases confidence in the computer's prediction of activity for new chemicals by providing a greater understanding of the underlying justification. The in silico prediction of these human molecular initiating events is central to the future of chemical safety risk assessment and improves the efficiency of safety decision making., Deep learning neural networks, constructed for the prediction of chemical binding at 79 pharmacologically important human biological targets, show extremely high performance on test data (accuracy 92.2 ± 4.2%, MCC 0.814 ± 0.093, ROC-AUC 0.96 ± 0.04).

A molecular initiating event (MIE) is the gateway to an adverse outcome pathway (AOP), a sequence of events ending in an adverse effect. In silico predictions of MIEs are a vital tool in a modern, mechanism-focused approach to chemical risk assessment. For 90 biological targets representing important human MIEs, structural alert-based models have been constructed with an automated procedure that uses Bayesian statistics to iteratively select substructures. These models give impressive average performance statistics (an average of 92% correct predictions across targets), significantly improving on previous models. Random Forest models have been constructed from physicochemical features for the same targets, giving similarly impressive performance statistics (93% correct predictions). A key difference between the models is interpretation of predictions-the structural alert models are transparent and easy to interpret, while Random Forest models can only identify the most important physicochemical features for making predictions. The two complementary models have been combined in a consensus model, improving performance compared to each individual model (94% correct predictions) and increasing confidence in predictions. Variation in model performance has been explained by calculating a modelability index (MODI), using Tanimoto coefficient between Morgan fingerprints to identify nearest neighbor chemicals. This work is an important step toward building confidence in the use of in silico tools for assessment of toxicity.

Lower income households, significantly less likely to have a computer or internet at home, were disproportionately impacted by the historic job losses in the Spring of 2020. In response, a Seattle-based workforce development nonprofit in partnership with the City of Seattle launched a program called Digital Bridge. The program distributed 197 refurbished computers and 174 internet hotspots and gave participants access to the Northstar Digital Literacy Assessment, online curriculum, and a technical support phone line. To understand Digital Bridge recipient needs, program impacts, and experiences of case managers implementing the program, we conducted a mixed methods study using a survey, Northstar Digital Literacy assessments, audio diaries, interviews, and a focus group. We found that most Digital Bridge participants needed individualized training and structured support to complete online training and look for employment. Case managers became participants’ default help desk without sufficient training and time allocated to properly support their clients. Participants did not use the technical support line but relied on family, friends, and their case manager when they needed assistance. Participants also wanted more structured support such as one-on-one walk throughs of their new devices and formal digital literacy training. After the initial pandemic shutdowns, more temporary federal funding has been allocated to support digital inclusion efforts. This study found that simply distributing technology will not get someone meaningfully connected; recipients want and need assistance from programs and people that they know and trust. Organizations implementing these programs need additional funding to support the time intensive personnel costs; funding cannot be limited to distributing the technology. Additionally, programs addressing digital inequalities need to work with broader social and economic assistance programs for their participants to access living wage careers.

Electroconvulsive therapy, also known as shock therapy and electroshock, is a psychiatric treatment that sends electricity into the brain of the patient with the purpose of inducing a seizure in that patient’s brain. A brief overview of relevant literature introduces an autobiographical narrative account of what it is to experience shock therapy. The author, a woman who had been given a diagnosis of schizoaffective disorder to explain her natural and expected responses to trauma and adversity, concludes with a critically reflective commentary on ECT.

Radiotherapy-induced damage to non-cancerous gastrointestinal mucosa has effects on secretory and absorptive functions and can interfere with normal gastrointestinal physiology. Nutrient absorption and digestion may be compromised. Dietary manipulation is an attractive option with sound rationale for intervention. The aim of this review was to synthesise published evidence for the use of elemental formulae, low or modified fat diets, fibre, lactose restriction and probiotics, prebiotics and synbiotics to protect the bowel from gastrointestinal side effects during long-course, radical pelvic radiotherapy. Thirty original studies (recruitingn3197 patients) were identified comprising twenty-four randomised controlled trials, four cohort studies and two comparator trials. Endpoints varied and included symptom scales (Inflammatory Bowel Disease Questionnaire, Common Technology Criteria for Adverse Events, Radiation Therapy Oncology Group) and Bristol Stool Scale. Dietary and supplement interventions were employed with many studies using a combination of interventions. Evidence from RCT was weak for elemental, low or modified fat and low-lactose interventions and modestly positive for the manipulation of fibre during radiotherapy. Evidence for probiotics as prophylactic interventional agents was more promising with a number of trials reporting positive results but strength and strains of interventions vary, as do methodologies and endpoints making it difficult to arrive at firm conclusions with several studies lacking statistical power. This consolidated review concludes that there is insufficient high-grade evidence to recommend nutritional intervention during pelvic radiotherapy. Total replacement of diet with elemental formula could be effective in severe toxicity but this is unproven. Probiotics offer promise but cannot be introduced into clinical practice without rigorous safety analysis, not least in immunocompromised patients.

Corey Wedlake is an apprentice dental nurse by day and a retained firefighter by night – and at weekends. Here, he talks about compassionate care in both his guises