Attrition Rates Research Articles

Advancing Drug Safety in Drug Development: Bridging Computational Predictions for Enhanced Toxicity Prediction.

The attrition rate of drugs in clinical trials is generally quite high, with estimates suggesting that approximately 90% of drugs fail to make it through the process. The identification of unexpected toxicity issues during preclinical stages is a significant factor contributing to this high rate of failure. These issues can have a major impact on the success of a drug and must be carefully considered throughout the development process. These late-stage rejections or withdrawals of drug candidates significantly increase the costs associated with drug development, particularly when toxicity is detected during clinical trials or after market release. Understanding drug-biological target interactions is essential for evaluating compound toxicity and safety, as well as predicting therapeutic effects and potential off-target effects that could lead to toxicity. This will enable scientists to predict and assess the safety profiles of drug candidates more accurately. Evaluation of toxicity and safety is a critical aspect of drug development, and biomolecules, particularly proteins, play vital roles in complex biological networks and often serve as targets for various chemicals. Therefore, a better understanding of these interactions is crucial for the advancement of drug development. The development of computational methods for evaluating protein-ligand interactions and predicting toxicity is emerging as a promising approach that adheres to the 3Rs principles (replace, reduce, and refine) and has garnered significant attention in recent years. In this review, we present a thorough examination of the latest breakthroughs in drug toxicity prediction, highlighting the significance of drug-target binding affinity in anticipating and mitigating possible adverse effects. In doing so, we aim to contribute to the development of more effective and secure drugs.

The Effect of Intersectionality on Attrition among US General Surgery Trainees.

To examine the association between intersectionality of race, ethnicity, and sex on retention of U.S. general surgery residents. There are limited data on the role that intersectionality plays on the US general surgery resident experience. Analysis was performed using Association of American Medical Colleges (AAMC) data for general surgery residents who started their training between 2005-2015 (followed through completion). Regression analyses were used to assess demographic associations with time to attrition or successful completion of residency training. Associations between faculty and resident demographics were assessed. 25,029 residents were included. Over the decade-long study period, the number of underrepresented in medicine (UIM) residents as a percentage of all residents remained similar from 17% to 19% (P=0.24). The percent of UIM males starting training in 2005 was 11% and 12% in 2015 (P-value=0.38). UIM females comprised 5.5% of trainees in 2005 and increased to 6.9% (P-value=0.003) in 2015; and female non-UIM residents increased from 23 to 28% (P-value<0.001). The overall rate of resident attrition was 15%. UIM females had the highest yearly attrition rate at 21% compared to non-UIM males at 13% (HR 1.7, P<0.001). UIM females were more likely to leave residency compared to UIM males (HR: 1.5; P<0.001). The percent of UIM faculty was positively correlated with percent of UIM residents (r=0.64, P<0.001). Increasing intersectionality is positively associated with attrition during surgery residency. The diversity of faculty appears to be associated with resident diversity.

Feasibility of continuous smart health monitoring in pregnant population: A mixed-method approach.

The utilization of smart monitoring technology offers potential for enhancing health outcomes, yet its feasibility and acceptance among Hispanic pregnant individuals remain uncertain. This is particularly crucial to investigate within the context of apparently healthy individuals identified as low risk, who still face a 10% likelihood of complications. Given their frequent underrepresentation in healthcare services and relative lack of attention, improving the feasibility of remote monitoring in this population could yield significant benefits. To address this gap, our study aimed to adapt and evaluate the practicality of a smart monitoring platform among healthy Hispanic pregnant women during the second and third trimesters of pregnancy, as well as one week following childbirth, a period when complications often arise. This longitudinal study followed n = 16 participants for an average of 17 weeks. Participants were instructed to wear the Oura ring for objective data collection, including activity, sleep, and heart rate, and to complete survey questions through REDcap to assess mental health and lifestyle factors. The study framework utilized the RE-AIM approach, with acceptability and adherence as key components of the feasibility evaluation. Our findings revealed that completion rates for biweekly and monthly surveys remained consistently high until after childbirth (approximately 80%), while daily question completion remained above 80% until 38th week of gestation, declining thereafter. The wearing rate of the Oura ring remained consistently above 80% until the 35th gestational week, decreasing to around 31% postpartum. Participants cited barriers to wearing the ring during the postpartum period, including difficulties managing the newborn, forgetfulness, and concerns about scratching the baby's skin. The enrollment rate was 71.42%, with an attrition rate of 6.25%. Thematic analysis of one-on-one interviews identified three main themes: personal desire for health improvement, social acceptability and support, and conditions influencing device/platform efficiency. In conclusion, while adherence varied based on gestational week and survey frequency, the study demonstrated strong acceptability of the smart monitoring platform among the study population, indicated by the high enrollment rate. Qualitative insights underscored the significance of personal motivation, social support, and device/platform efficiency in enhancing patient engagement with digital health monitoring during pregnancy, offering valuable considerations for future healthcare interventions in this domain.

Assessing the Impact of an Artificial Intelligence-Based Model for Intracranial Aneurysm Detection in CT Angiography on Patient Diagnosis and Outcomes (IDEAL Study)—a protocol for a multicenter, double-blinded randomized controlled trial

BackgroundThis multicenter, double-blinded, randomized controlled trial (RCT) aims to assess the impact of an artificial intelligence (AI)-based model on the efficacy of intracranial aneurysm detection in CT angiography (CTA) and its influence on patients’ short-term and long-term outcomes.MethodsStudydesign: Prospective, multicenter, double-blinded RCT.Settings: The model was designed for the automatic detection of intracranial aneurysms from original CTA images.Participants: Adult inpatients and outpatients who are scheduled for head CTA scanning.Randomization groups:(1) Experimental Group: Head CTA interpreted by radiologists with the assistance of the True-AI-integrated intracranial aneurysm diagnosis strategy (True-AI arm).(2) Control Group: Head CTA interpreted by radiologists with the assistance of the Sham-AI-integrated intracranial aneurysm diagnosis strategy (Sham-AI arm).Randomization: Block randomization, stratified by center, gender, and age group.Primary outcomes: Coprimary outcomes of superiority in patient-level sensitivity and noninferiority in specificity for the True-AI arm to the Sham-AI arm in intracranial aneurysms.Secondary outcomes: Diagnostic performance for other intracranial lesions, detection rates, workload of CTA interpretation, resource utilization, treatment-related clinical events, aneurysm-related events, quality of life, and cost-effectiveness analysis.Blinding: Study participants and participating radiologists will be blinded to the intervention.Sample size: Based on our pilot study, the patient-level sensitivity is assumed to be 0.65 for the Sham-AI arm and 0.75 for the True-AI arm, with specificities of 0.90 and 0.88, respectively. The prevalence of intracranial aneurysms for patients undergoing head CTA in the hospital is approximately 12%. To establish superiority in sensitivity and noninferiority in specificity with a margin of 5% using a one-sided α = 0.025 to ensure that the power of coprimary endpoint testing reached 0.80 and a 5% attrition rate, the sample size was determined to be 6450 in a 1:1 allocation to True-AI or Sham-AI arm.DiscussionThe study will determine the precise impact of the AI system on the detection performance for intracranial aneurysms in a double-blinded design and following the real-world effects on patients’ short-term and long-term outcomes.Trial registrationThis trial has been registered with the NIH, U.S. National Library of Medicine at ClinicalTrials.gov, ID: NCT06118840. Registered 11 November 2023.

The wellbeing shelf: A mixed methods study exploring the impact of a resilience web resource for first year nursing and midwifery students

BackgroundNurturing a resilient nursing and midwifery workforce is vital for the National Health Service's sustainability. Higher Education Institutions (HEIs) must support students, given the challenges and attrition rates. Nursing and midwifery education uniquely balances tuition and placements, posing challenges, especially for first-year students, who face stressors including lack of familiarity, knowledge gaps, and emotional exposure. ObjectivesThis study aimed to introduce and evaluate a co-designed web-based intervention called ‘The Wellbeing Shelf’ to enhance resilience among first-year nursing and midwifery students. DesignAn exploratory mixed methods approach was employed, combining quantitative pre- and post-intervention questionnaires and qualitative focus groups. Settings and participantsThe study involved 353 first-year nursing and midwifery students at Queen's University Belfast. Methods‘The Wellbeing Shelf’ was developed through co-design workshops. Quantitative measures included the Connor Davidson Resilience Scale (CD-RISC) and the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS). Qualitative data were collected through focus group interviews. ResultsQuantitative data showed a decrease in both resilience and wellbeing scores over time. The CD-RISC scores decreased significantly from Time 1 to Time 3. Qualitative findings revealed three themes: “Acquiring” knowledge about wellbeing, “Actioning” self-care strategies, and “Advocating” for self-care among peers and family. ConclusionsThe study introduced ‘The Wellbeing Shelf’ as a resource to enhance resilience among nursing and midwifery students. Whilst the resource offered a variety of activities and fostered a sense of belonging, challenges in resource accessibility and student confidence were identified. The study also highlighted the importance of students advocating for self-care practices. Despite the resource's introduction, resilience and wellbeing scores decreased over time, suggesting a need for further research and potentially a control group. Understanding the initial lower resilience of nursing and midwifery students is crucial for future interventions in this high-demand program.

Undergraduate dissertation problems: an aggregate cross-sectional analysis from five Latin American universities

ABSTRACT Latin America may have higher attrition rates than previously assumed. Many students in Latin America do not graduate on time because they cannot complete the traditional undergraduate dissertation. This paper examines the factors contributing to delayed graduation for a context-specific variable: dissertation problems. We designed a questionnaire survey based on multi-item scales and surveyed 480 university students from Argentina, Bolivia, Chile, Colombia, and Mexico. Aggregate-cross-sectional data and multilevel structural equation modeling show that institutional assistance and supervision quality [personal problems] reduce [increase] dissertation problems. These results may enable university authorities to identify undergraduate students with dissertation problems and thus improve their strategies for reducing attrition rates.

Dialysis nurse demand in Europe: An estimated prediction based on modelling.

Abstract Objective To estimate the projections of supply and demand for dialysis-nurses (DNs) over 5 years in 4 European countries (France, Italy, Spain, and United Kingdom). Methods This study modelled the nursing labour workforce across each jurisdiction, by estimating the current nursing labour force, number of nursing graduates and the attrition rate. Results France has currently the greater demand of DNs (51,325 patients on dialysis), followed by Italy, UK, and Spain with 40,661; 30,301; and 28,007 patients on dialysis, respectively. The number of in-centre haemodialysis patients (ICHD) is expected to increase in the four countries, while the number of patients on home-haemodialysis (HHD) or on peritoneal dialysis (PD) only is expected to increase in the UK. Currently Italy has the greater proportion of DNs (2.6%), followed by France (2.1%), Spain (1.7%), and United Kingdom (1.5%). The estimation of dialysis nursing staff growth rate over 5 years showed that the United Kingdom has the greater estimated growth rate (6%); followed by Italy (2%); France (2%), and Spain (1%). Conclusions Dialysis demand will increase in the coming years, which may exacerbate dialysis-nurse shortage. Additionally, competencies and training requirements of dialysis-nurses should be precisely defined. Finally, implementing and facilitating PD and HHD strategies would be helpful for patients, Health-care professionals, and Health care systems, and can even help ease the dialysis-nursing shortage.

Predictors of adherence to follow-up and treatment success in childhood obesity

IntroductionManagement of childhood obesity, based upon behavioural, physical activity and dietary guidance, usually achieves limited success and is hindered by a high attrition rate. The identification of potential predictors of either weight loss or early weight management attrition could help develop personalised management plans in order to improve patient outcomes. Patients and methodsWe conducted a retrospective study in a cohort of 1300 patients with obesity managed in speciality clinics for up to 5 years with outpatient conservative treatment. We studied the family background and personal characteristics (demographic, behavioural, psychosocial, anthropometric and metabolic) of patients who dropped out before completing the first year of the programme and patients who achieved significant weight loss, with a separate analysis of patients who achieved substantial reductions in weight compared to the rest of the cohort. ResultsThe mean age of the patients in the cohort was 10.46 years (SD, 3.48) the mean BMI z-score 4.01 (SD, 1.49); 52.8% of the patients were male, 53.3% were prepubertal, 75.8% were Caucasian and 19% Latin. We found a higher proportion of Latinla ethnicity and compulsive eating in the group of patients with early attrition from the weight management follow-up. In the group of patients with substantial weight loss, a greater proportion were male, there was a higher frequency of dietary intake control at home and obesity was more severe, and the latter factor was consistently observed in patients who achieved substantial weight loss at any point of the follow-up. ConclusionsSome family and personal characteristics in childhood obesity are associated with an increased risk of early withdrawal from follow-up or a greater probability of successful outcomes; however, the predictive value of these variables is limited.

Artificial Intelligence in Drug Identification and Validation: A Scoping Review.

The end-to-end process in the discovery of drugs involves therapeutic candidate identification, validation of identified targets, identification of hit compound series, lead identification and optimization, characterization, and formulation and development. The process is lengthy, expensive, tedious, and inefficient, with a large attrition rate for novel drug discovery. Today, the pharmaceutical industry is focused on improving the drug discovery process. Finding and selecting acceptable drug candidates effectively can significantly impact the price and profitability of new medications. Aside from the cost, there is a need to reduce the end-to-end process time, limiting the number of experiments at various stages. To achieve this, artificial intelligence (AI) has been utilized at various stages of drug discovery. The present study aims to identify the recent work that has developed AI-based models at various stages of drug discovery, identify the stages that need more concern, present the taxonomy of AI methods in drug discovery, and provide research opportunities. From January 2016 to September 1, 2023, the study identified all publications that were cited in the electronic databases including Scopus, NCBI PubMed, MEDLINE, Anthropology Plus, Embase, APA PsycInfo, SOCIndex, and CINAHL. Utilising a standardized form, data were extracted, and presented possible research prospects based on the analysis of the extracted data.

Therapeutic sleep deprivation for major depressive disorder: A randomized controlled trial

BackgroundMajor depressive disorder (MDD) is treated primarily using antidepressant drugs, but clinical effects may be delayed for weeks to months. This study investigated the efficacy of brief therapeutic sleep deprivation (TSD) for inducing rapid improvements in MDD symptoms. MethodsFrom November 2020 to February 2023, 54 inpatients with MDD were randomly allocated to TSD and Control groups. The TSD group (23 cases) remained awake for 36 h, while the Control group (31 cases) maintained regular sleep patterns. All participants continued regular drug therapy. Mood was assessed using the 24-item Hamilton Depression Scale (HAMD-24) at baseline and post-intervention in both groups. In the TSD group, the Visual Analogue Scale (VAS) was utilized to evaluate subjective mood during and after the intervention. Cognitive function was assessed at baseline and post-intervention using the Montreal Cognitive Assessment (MoCA). Objective sleep parameters were recorded in the TSD group by polysomnography. The follow-up period spanned one week. ResultsHAMD-24 scores did not differ between groups at baseline or post-intervention. However, the clinical response rate was 34.8 % higher in the TSD group on day 3 post-intervention compared to the Control group (3.2 %), but not sustained by day 7. Moreover, responders demonstrated a faster improvement in the VAS score during TSD than non-responders (p = 0.047). There were no significant differences in MoCA scores or objective sleep parameters between the groups. LimitationsSmall sample size and notable attrition rate. ConclusionsTherapeutic sleep deprivation can rapidly improve MDD symptoms without influencing sleep parameters or cognitive functions. Assessment of longer-term effects and identification of factors predictive of TSD response are warranted.

Brand Churn A Significant Percentage of Customers Leaving for Competitors

Abstract: Brand churn, characterized by a significant percentage of customers leaving for competitors, poses a substantial challenge for businesses across industries. To understand the underlying factors contributing to brand churn and devise effective retention strategies, a survey questionnaire method was employed. The questionnaire was designed to gather insights into customers' reasons for switching brands, their perceptions of competitor offerings, and their preferences for brand loyalty incentives. A diverse sample of respondents representing various demographic segments and purchasing behaviours was targeted to ensure comprehensive data collection. The survey findings revealed key drivers of brand churn, including dissatisfaction with product quality, pricing competitiveness, and customer service experiences. Additionally, insights into customers' perceptions of competitor brands and the effectiveness of loyalty programs in retaining customers were garnered. The results of this survey provide valuable insights for businesses seeking to mitigate brand churn by addressing customer needs and preferences effectively. By implementing targeted retention strategies informed by these findings, businesses can enhance customer loyalty, reduce churn rates, and maintain a competitive edge in the marketplace.

Employee Attrition Prediction

Employee attrition occurs when a worker leaves a company to join another firm for a better offer. It might also be referred to as Employee Defection. Representative downsizing is likely to be significant when there is a pressing demand for workers in a particular industry due to mass retirements or organizational growth. At one point, the programming industry had significant attrition rates due to abundant job opportunities in the software sector driven by the demand for software products across all industries. Reducing the employee attrition rate is a challenging challenge faced by HR managers. This study provides a clear viewpoint on predicting employee turnover using Machine Learning methods. The projection is completed using data obtained from IBM HR analysis. We employed Logistic Regression for the analysis and achieved an accuracy rate of 87%.

Patient-related factors associated with patient retention and non-completion in psychosocial treatment of borderline personality disorder: A systematic review.

The potential efficacy of psychosocial interventions in the treatment of borderline personality disorder (BPD) is impacted by significant treatment non-completion (TNC), with meta-analytic studies reporting rates of attrition of between 25% and 28%. Increasing patient retention could facilitate outcomes and improve resource utilization, given limited healthcare services. A systematic search of PsycINFO, CINAHL, EMBASE, CENTRAL, and Web of Science Core Collection identified 33 articles that met the criteria for inclusion. Although substantial heterogeneity in terms of methodology and quality of analysis limited conclusions that could be drawn in the narrative review, a few consistent patterns of findings were elucidated, such as Cluster B personality disorder comorbidities and lower therapeutic alliance were associated with TNC. Interestingly, the severity of BPD symptoms was not a predictor of TNC. These findings are discussed in terms of their potential theoretical contribution to TNC. Clinically, there may be value in applying mindfulness and motivational interviewing strategies early on in treatment for individuals who present uncertainty about engaging in treatment. Further research to develop this empirical landscape includes focusing on high-powered replications, examining burgeoning lines of research, and investigating dynamic predictors of TNC.

A study on factors influencing churn at Enerlife India Private Limited

This research is about a study on factors influencing churn at Enerlife India Private Limited (Nabati). This company provides fast-moving consumer goods products all over India. The origin of the company is from Indonesia. Nabati Group is a business group that has a business focus in the field of fast-moving consumer goods (FMCG), especially food. The company was initially only engaged in the snack food business with a home industry scale. Assessing the impact of factors such as job satisfaction, cost Implications, leadership and management, employee burnout, career development, and flexible work arrangements. Proposing recommendations and best practices for reducing employee churn and fostering a more engaged and stable workforce. By studying the external factors, that influence churn in the organization, job security perceptions and career advancement opportunities on churn are the objectives. This study contributes valuable insights to the existing literature on employee churn in the company by identifying new factors or confirming existing ones that influence churn rates within the organization. In research methodology a questionnaire to collect data from the employees. Stratified random sampling is a type of probability method using which a research organization can branch off the entire population into multiple non-overlapping, homogenous groups (strata) and randomly choose final members from various strata for research which reduces cost and improves efficiency. This research study underscores the importance of churn at the company. As the employees always looking for new roles for their career growth, the company should ensure that the employee will have their career growth in the company. Giving importance to the employee’s insights and suggestions will make as one of the retention strategies used by the company. Churn poses significant challenges for organizations, impacting productivity, morale, and financial stability.

Current Research on Matching Trauma-Focused Therapies to Veterans: A Scoping Review.

Trauma-focused (psycho)therapies (TFTs) are often used to treat post-traumatic stress disorder (PTSD) of (military) veterans, including prolonged exposure (PE), cognitive processing therapy (CPT), and eye movement desensitization and reprocessing. However, research thus far has not conclusively determined predictors of TFTs' success in this population. This scoping review's objectives are 1) to explore whether it is possible, based on currently available evidence, to match TFTs to veterans to maximize their outcomes, (2) to identify possible contraindications and adaptations of TFTs for this population, and (3) to identify gaps in the literature to guide future research. Standard scoping review methodology was used. "White" and "gray" literature searches resulted in 4963 unique items identified. Following title and abstract screening and full-text analysis, 187 sources were included in the review. After data extraction, a narrative summary was used to identify common themes, discrepancies between sources, and knowledge gaps. Included publications most often studied CPT and PE rather than eye movement desensitization and reprocessing. These TFTs were at least partly effective with mostly moderate effect sizes. Attrition rates were slightly higher for PE versus CPT. There was variance in the methodological quality of the included studies. The current literature on TFTs to treat PTSD in veterans contains several knowledge gaps, including regarding treatment matching. Future research should examine effectiveness of these treatments using multiple sources of outcomes, longer time periods, combination with other treatment, outcomes outside of PTSD symptoms (such as functioning), and resilience.

#2121 The Kidney-specific Psychosocial ASSessment and support (Kidney PASSPORT) feasibility trial

Abstract Background and Aims Psychosocial interventions for depressive and anxiety symptoms are effective in CKD, but studies mainly focus on people on dialysis. Little is known about the role of screening and prevention of common mental health difficulties in early CKD. This trial assessed the research feasibility of an intervention to screen for psychological distress in CKD and deliver prevention approaches for sub-threshold symptoms. The intervention was facilitated by an Assistant Wellbeing Practitioner (AWP), a Band 3 healthcare assistant familiar with renal services and upskilled with specific competency-based training. Method We conducted a mixed-methods, one-year, single-centre, prospective, single-blind, wait-list, randomised controlled feasibility trial. We anticipated screening 250 individuals to identify 100 eligible, with a 40% screening positivity rate, a 45% participation rate and 20% attrition rate, to give 36 participants in the feasibility study. Primary outcomes are shown in Table 1. Potential participants were screened using an online self-completion questionnaire. Participants were randomised to 6 months of immediate or wait-list intervention. Data was collected using online self-report surveys, clinical research forms and semi-structured qualitative interviews. The trial was overseen by a steering committee and received the relevant ethics approvals. Funders included Kidney Care UK, the British Renal Society, the Royal Devon and Exeter Research Capacity Awards and the Exeter Kidney Unit development fund. Results We approached n = 233 people. Feasibility outcomes are shown in Table 2. Due to logistical issues an extension was obtained and in total n = 24 participants were recruited, agreed by the steering committee. All clinical research forms were completed. The most common intervention components were self-management and liaison with the clinical team. The median (interquartile range) difference in baseline and post intervention PHQ-9 score was −5 (−7, 0), n = 19, p = 0.003) and GAD-7 score was −7 (−8, −2), n = 19, p = 0.0002). Qualitative findings showed the AWP was seen as filling in the gaps left by other parts of the service. Key themes were accessibility, time availability, empathy, patient empowerment, and ability to empower the individual. Balance—especially family, work and health—was noted to be a challenge for participants. Importantly, the AWP was able to help participants overcome previous negative experiences. The trial provided valuable learning regarding role implementation, including recruitment, training, work patterns, everyday practicalities, and supervision arrangements. Conclusion We propose a novel intervention for screening and addressing early mental health problems in people with CKD. A single-centre feasibility design was appropriate. The screening positivity rate was lower than anticipated, informing samples for future trials. Outcome data collection via self-report surveys was not feasible. The intervention was well received, with the AWP being valued and self-help and clinical liaison being core elements. Significant reductions in depression and anxiety screening scores were observed. Despite the rigorous design, limitations included slow initial recruitment impacting the sample size and AWP role vulnerability. Future work includes adapting the AWP training and role based on trial learning and considering suitability for other long-term conditions. In conclusion, the AWP role shows promise in routine screening for and prevention of common mental health difficulties in CKD.

Navigating the complexities of drug development for inflammatory bowel disease.

Inflammatory bowel disease (IBD) - consisting of ulcerative colitis and Crohn's disease - is a complex, heterogeneous, immune-mediated inflammatory condition with a multifactorial aetiopathogenesis. Despite therapeutic advances in this arena, a ceiling effect has been reached with both single-agent monoclonal antibodies and advanced small molecules. Therefore, there is a need to identify novel targets, and the development of companion biomarkers to select responders is vital. In this Perspective, we examine how advances in machine learning and tissue engineering could be used at the preclinical stage where attrition rates are high. For novel agents reaching clinical trials, we explore factors decelerating progression, particularly the decline in IBD trial recruitment, and assess how innovative approaches such as reconfiguring trial designs, harmonizing end points and incorporating digital technologies into clinical trials can address this. Harnessing opportunities at each stage of the drug development process may allow for incremental gains towards more effective therapies.

Early pharmacological interventions for prevention of post-traumatic stress disorder (PTSD) in individuals experiencing acute traumatic stress symptoms.

Acute traumatic stress symptoms may develop in people who have been exposed to a traumatic event. Although they are usually self-limiting in time, some people develop post-traumatic stress disorder (PTSD), a severe and debilitating condition. Pharmacological interventions have been proposed for acute symptoms to act as an indicated prevention measure for PTSD development. As many individuals will spontaneously remit, these interventions should balance efficacy and tolerability. To assess the efficacy and acceptability of early pharmacological interventions for prevention of PTSD in adults experiencing acute traumatic stress symptoms. We searched the Cochrane Common Mental Disorders Controlled Trial Register (CCMDCTR), CENTRAL, MEDLINE, Embase and two other databases. We checked the reference lists of all included studies and relevant systematic reviews. The search was last updated on 23 January 2023. We included randomised controlled trials on adults exposed to any kind of traumatic event and presenting acute traumatic stress symptoms, without restriction on their severity. We considered comparisons of any medication with placebo, or with another medication. We excluded trials that investigated medications as an augmentation to psychotherapy. We used standard Cochrane methodological procedures. Using a random-effects model, we analysed dichotomous data as risk ratios (RR) and calculated the number needed to treat for an additional beneficial/harmful outcome (NNTB/NNTH). We analysed continuous data as mean differences (MD) or standardised mean differences (SMD). Our primary outcomes were PTSD severity and dropouts due to adverse events. Secondary outcomes included PTSD rate, functional disability and quality of life. We included eight studies that considered four interventions (escitalopram, hydrocortisone, intranasal oxytocin, temazepam) and involved a total of 779 participants. The largest trial contributed 353 participants and the next largest, 120 and 118 participants respectively. The trials enrolled participants admitted to trauma centres or emergency departments. The risk of bias in the included studies was generally low except for attrition rate, which we rated as high-risk. We could meta-analyse data for two comparisons: escitalopram versus placebo (but limited to secondary outcomes) and hydrocortisone versus placebo. One study compared escitalopram to placebo at our primary time point of three months after the traumatic event. There was inconclusive evidence of any difference in terms of PTSD severity (mean difference (MD) on the Clinician-Administered PTSD Scale (CAPS, score range 0 to 136) -11.35, 95% confidence interval (CI) -24.56 to 1.86; 1 study, 23 participants; very low-certainty evidence), dropouts due to adverse events (no participant left the study early due to adverse events; 1 study, 31 participants; very low-certainty evidence) and PTSD rates (RR 0.59, 95% CI 0.03 to 13.08; NNTB 37, 95% CI NNTB 15 to NNTH 1; 1 study, 23 participants; very low-certainty evidence). The study did not assess functional disability or quality of life. Three studies compared hydrocortisone to placebo at our primary time point of three months after the traumatic event. We found inconclusive evidence on whether hydrocortisone was more effective in reducing the severity of PTSD symptoms compared to placebo (MD on CAPS -7.53, 95% CI -25.20 to 10.13; I2 = 85%; 3 studies, 136 participants; very low-certainty evidence) and whether it reduced the risk of developing PTSD (RR 0.47, 95% CI 0.09 to 2.38; NNTB 14, 95% CI NNTB 8 to NNTH 5; I2 = 36%; 3 studies, 136 participants; very low-certainty evidence). Evidence on the risk of dropping out due to adverse events is inconclusive (RR 3.19, 95% CI 0.13 to 75.43; 2 studies, 182 participants; low-certainty evidence) and it is unclear whether hydrocortisone might improve quality of life (MD on the SF-36 (score range 0 to 136, higher is better) 19.70, 95% CI -1.10 to 40.50; 1 study, 43 participants; very low-certainty evidence). No study assessed functional disability. This review provides uncertain evidence regarding the use of escitalopram, hydrocortisone, intranasal oxytocin and temazepam for people with acute stress symptoms. It is therefore unclear whether these pharmacological interventions exert a positive or negative effect in this population. It is important to note that acute traumatic stress symptoms are often limited in time, and that the lack of data prevents the careful assessment of expected benefits against side effects that is therefore required. To yield stronger conclusions regarding both positive and negative outcomes, larger sample sizes are required. A common operational framework of criteria for inclusion and baseline assessment might help in better understanding who, if anyone, benefits from an intervention. As symptom severity alone does not provide the full picture of the impact of exposure to trauma, assessment of quality of life and functional impairment would provide a more comprehensive picture of the effects of the interventions. The assessment and reporting of side effects may facilitate a more comprehensive understanding of tolerability.

Assigning practical tasks to candidates can better predict success

At colleges and universities throughout the country, student affairs departments are facing high attrition rates and ongoing staff shortages. These staffing challenges place even greater importance on good interviewing and hiring practices.

Using Clustering Methods to Map the Experience Profiles of Dementia Caregivers.

Caregivers of persons living with dementia report wide-ranging lived experiences, including feelings of burden and frustration but also positivity about caregiving. This study applies clustering methodology to novel survey data to explore variation in caregiving experience profiles, which could then be used to design and target caregiver interventions aimed at improving caregiver well-being. The k-means clustering algorithm partitioned a sample of 81 caregivers from the Midwest region of the United States on the basis of 8 variables capturing caregiver emotions, attitudes, knowledge, and network perceptions (adversity: burden, anxiety, network malfeasance; network nonfeasance; positivity: positive aspects of caregiving, preparedness and confidence in community-based care, knowledge about community services for older adults, and network uplift). The experience profile of each segment is described qualitatively and then regression methods were used to examine the association between (a) experience profiles and caregiver demographic characteristics and (b) experience profiles and study attrition. The clustering algorithm identified 4 segments of caregivers with distinct experience profiles: Thriving (low adversity, high positivity); Struggling with Network (high network malfeasance); Intensely Struggling (high adversity, low positivity); Detached (unprepared, disconnected, but not anxious). Experience profiles were associated with significantly different demographic profiles and attrition rates. How caregivers respond to support interventions may be contingent on caregivers' experience profile. Research and practice should focus on identifying public health strategies tailored to fit caregiver experiences. NCT03932812.