Significance Tests Research Articles

Modelling of passengers behaviour under the influence of noise in public transport buses: a structural equation approach

This study aims to investigate the impact of noise pollution levels on passengers during travel. Specifically, the aim was to explore the interconnections between noise-induced annoyance, sensitivity to noise, sleep disturbances, and physical health problems using a structural equation modelling (SEM) approach. 14 routes were selected for detailed analysis across different time periods. The noise levels were observed, and the impact of these levels on passengers was assessed through a questionnaire survey to know their perception towards noise and its impacts. A total of 252 responses from passengers were collected through the personal interview. Findings reveal that noise pollution levels exceeded 70 dBA on most of the routes. A significance test (t-test) conducted on 15-minute frequency intervals showed no significant difference in noise pollution levels during morning, evening, and afternoon periods. Subjective analysis indicates 31% of passenger were found to be highly annoyed due to noise within public buses. Additionally, 32% and 9% of passengers reported moderate and minimal annoyance, respectively, attributed to traffic and engine noise inside buses. Structural equation approach showed that sensitivity to noise affects the annoyance level most with coefficient 0.76, followed by physical health factors and sleep disturbance with coefficient 0.48 and 0.44 respectively.

A-346 Evaluating 14-3-3η Detection in Finger Prick Blood Using Lateral Flow Technology: Advancing Clinical Laboratory Diagnostics

Abstract Background The protein 14-3-3η is a critical biomarker in the diagnosis and monitoring of autoimmune rheumatologic disorders, and its early detection is pivotal for patient outcomes. Previous research has established the significance of 14-3-3η as a biomarker, particularly in inflammatory polyarthritis, as well as patients’ and physicians’ interest in near-patient testing. While 14-3-3η is traditionally measured in serum via ELISA, this study explores the innovative use of lateral flow technology (LFT) for its detection in finger prick blood, addressing the urgent need for near-patient testing.This research aims to evaluate the technical and clinical performance of 14-3-3η measurement using LFT in comparison to standard ELISA methods, with an emphasis on its detectability in finger prick blood. Methods This study included two phases of testing involving patient serum and spiked whole blood. In the serum phase, 53 samples (19 NEG, ≤0.19 ng/mL, and 34 POS, 0.27 to 28 ng/mL 14-3-3η) were tested using LFT. LFT results were compared to JOINTstat® ELISA measurements for concordance. For whole blood, recombinant 14-3-3η and ELISA-positive serum samples were spiked into whole blood at increasing concentrations (0.4 to 3.2 ng/mL) and tested with LFT. Concordance criteria included visual inspection of test and control lines, with results captured and analyzed using a reference key card. The study was extended to assess 14-3-3η levels in consented patients with 22 matched finger prick and venous serum samples​​. Results In serum testing, LFT demonstrated 100% positivity in detecting 14-3-3η for POS samples. Among NEG samples, 85% tested negative, with 15% positive, indicating a strong concordance between LFT and ELISA. The LFT's ability to semi-quantitatively measure 14-3-3η was confirmed by a significant Kruskal-Wallis test (p<0.0001) across four intensity groups. In whole blood testing, LFT correctly identified all samples spiked at concentrations ≥0.5 ng/mL. The Spearman correlation showed a strong and significant association (r=0.96 to 0.98, p=0.001) between LFT test line intensity and spiked 14-3-3η levels. Finally, the equivalence testing for finger prick and venous serum samples affirmed the LFT’s reliability, with a strong correlation (p<0.0001), underscoring its potential for near-patient testing​​. Conclusions The study validates LFT as a reliable and semi-quantitative method for detecting 14-3-3η in finger prick blood, demonstrating strong concordance with traditional ELISA measurements. The findings support the feasibility of LFT in near-patient testing for early detection, prognosis, and monitoring of autoimmune diseases, paving the way for enhanced patient accessibility. Future research will focus on integrating this technology into routine clinical care and examining its impact on patient management and outcomes.

Effect of Different Concentrations of Tomato Leaf Extract on Aphid Control in Rape Production in Zimbabwe

Rape (Brassica napus) is an important vegetable crop grown by smallholder farmers in Zimbabwe to achieve food and nutritional security. However, productivity and quality of rape are greatly dampened by aphids which reduce its palatability and quality. Chemical pesticides, while effective, pose environmental risks and can lead to pest resistance and resurgence, besides residual effects and bioaccumulation along the food chain. Tomato leaves are rich in phenolic and flavonoid compounds, that have shown promise as a botanical pesticide against aphids in other crops. This research aimed to establish the aphicidal components in tomato leaf extract using TLC and UV-Vis Spectroscopy; establish toxicity of the extract using laboratory bioassay, investigate the potential of different concentrations of tomato leaf extracts as a natural, environmentally friendly and sustainable approach to pest management against aphids in rape production at Kushinga Phikelela Agricultural College in Zimbabwe. A CRD with four treatments (0%, 20%, 40% and 60% of tomato leaf extract) and distilled water (negative control) replicated five times each was used. Aphid infestation (scored on a scale of 0-9), yield, leaf size, and plant height were measured fortnightly. Data was analysed for statistical significance using ANOVA while separation of significant means was done by Fisher’s Protected Least Significant Difference Test (LSD (5%). The results from combined analysis using TLC and UV- Vis Spectroscopy indicated that tomato leaf extract used in this research contained compounds (Solanine, Tomatine, Chaconine) which are known to be toxic to pests. There was a highly significant (p<0.001) difference among treatments on aphid mortality. The highest aphid mortality (95.57%) while the lowest (4%) was observed in 60% and 0% leaf extract respectively. Aphid infestation, leaf size and plant height were highly significant (P<0.001) during weeks 4, 6, 8 and 10 after transplanting. Aphid infestation in week 10 mean score was 8.8, 6.2, 3.8 and 0.8 for 0%, 20%, 40% and 60% tomato leaf extract respectively. Other parameters such as yield and leaf size were highest in the plots that received 60% tomato leaf extract sprays. Highly significant difference (P<0.001) in yield was observed in weeks 8 and 10, while significant difference (P<0.05) in yield was noted in weeks 4 and 6. However, in week two there were no significant differences among the treatments in yield and aphid infestation. Tomato leaf extracts contain secondary metabolites toxic to aphids and this can be used by resource constrained farmers. We recommend the use 60% tomato leaf extracts to control aphids in rape to sustainably achieve high yields.

The Impact of Retention Strategies on the Performance of Teachers in Private Secondary Schools: A Case of Dodoma City, Tanzania

The presence of persistent needs for motivated teaching staff to uphold the standards of education at secondary schools poses a significant challenge concerning the retention of competent teachers in private secondary schools. Teacher turnover poses significant tests for educational establishments, affecting both the stability of the schools and the quality of education provided. Like other educational institutions, the prevailing competition to recruit and retain highly qualified teachers, private secondary schools face the problem of maintaining competent teachers within a context characterized by higher rates of staff turnover. This article is to provide a comprehensive theoretical evaluation of strategies to sustain teachers' retention in private secondary schools by assessing the potential advantages associated with the implementation of effective retention measures. Moreover, the study probed into the existing literature to explore many retention features including, professional growth opportunities, organizational culture, leadership, and compensation to provide insights into the formulation of effective retention strategies to be applied by schools. By gaining a comprehensive understanding of the strategies, challenges, and potential outcomes, school management and educational policymakers can advance the efficacy, prosperity, and stability of learning environments for teaching staff and students. A cross-sectional survey design and the research approach combined both qualitative and quantitative paradigms. Simple random sampling (SRS) and purposive technic were used to draw a sample of eighty (80) respondents. SRS was adopted to interrogate teachers and purposive for key informants. Data analysis was employed by use of multiple responses, multiple linear regression, and analysis of variance (ANOVA). Salary, adequate learning facilities, a welcoming environment, and leadership style were identified as retention methods by the study's findings. The survey, however, identified the following barriers to implementing teachers' retention strategies including heavy workloads, lack of chances to advance, low pay and benefits, poor working conditions, and higher workplace stresses. Despite the outlined retention strategies, implementation matters including the lack of professional development opportunities, attractive incentive packages, and work-related benefits, unfavourable working conditions, and stress brought on by heavy workloads should be adequately addressed by school management and other decision-makers if they need to retain their valuable talented teachers.

The role of effect size and significance test in research design and analysis

Effect size is a straightforward method for measuring the difference between two groups and plays a critical role in research design and significance testing. This paper addresses the concept of effect size, explaining what it is, how it is calculated, and how it can be interpreted. It also explores related topics, such as statistical significance, meta-analysis, and power analysis. Effect sizes can be understood in the context of confidence intervals, which provide similar information to statistical significance tests but focus more on the magnitude of the effect rather than the size of the sample.

Deep-Learning-Based Disease Classification in Patients Undergoing Cine Cardiac MRI.

Automated approaches may allow for fast, reproducible clinical assessment of cardiovascular diseases from MRI. To develop an MRI-based deep learning (DL) disease classification algorithm to distinguish among normal subjects (NORM), patients with dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), and ischemic heart disease (IHD). Retrospective. A total of 1337 subjects (55% female), comprising normal subjects (N = 568), and patients with DCM (N = 151), HCM (N = 177), and IHD (N = 441). Balanced steady-state free precession cine sequence at 1.5/3.0 T. Bi-ventricular morphological and functional features and global and segmental left ventricular strain features were automatically extracted from short- and long-axis cine images. Variational autoencoder models were trained on the extracted features and compared against consensus disease label provided by two expert readers (13 and 14 years of experience). Adding unlabeled, normal data to the training was explored to increase specificity of NORM class. Tenfold cross-validation for model development; mean, standard deviation (SD) for measurements; classification metrics: area under the curve (AUC), confusion matrix, accuracy, specificity, precision, recall; 95% confidence intervals; Mann-Whitney U test for significance. AUCs of 0.952 for NORM, 0.881 for DCM, 0.908 for HCM, and 0.856 for IHD and overall accuracy of 0.778 were obtained, with specificity of 0.908 for the NORM class using both SAX and LAX features. Longitudinal strain features slightly improved classification metrics by 0.001 to 0.03 points, except for HCM-AUC. Differences in accuracy, metrics for NORM class and HCM-AUC were statistically significant. Cotraining using unlabeled data increased the specificity for the NORM class to 0.961. Cardiac function features automatically extracted from cine MRI have potential to be used for disease classification, especially for normal-abnormal classification. Feature analyses showed that strain features were important for disease labeling. Cotraining using unlabeled data may help to increase specificity for normal-abnormal classification. 3 TECHNICAL EFFICACY: Stage 1.

Exploring disparities: A comparative analysis of insulin-naïve, regular users, and inertia patients among type 2 diabetes mellitus outpatients in India

ABSTRACT Introduction: Insulin utilization pattern varies greatly in type 2 diabetes mellitus (T2DM) patients. Clinical inertia in treatment intensification hinders glycemic control in T2DM management. This study investigated insulin prescription trends and various predictors among insulin naive, user, and insulin inertia (II) patients in T2DM. Methodology: A retrospective analysis of T2DM patient records from the diabetes clinic at a tertiary care center was conducted. Data on socio-demographics, anthropometry, disease characteristics, comorbidities, adherence, and medication prescribing patterns were collected. Analysis was done using tests of significance, odds ratio (OR), and multivariate logistic regression. Results: A total of 950 records were analyzed, with 17.3% of patients identified as insulin users (IU), 70.9% being insulin-naïve (IN), and 11.8% having II. IUs had significantly higher glycemic levels including HbA1c, fasting, postprandial, and random blood sugars compared to the other groups. Higher HbA1c levels were associated with significantly increased odds of insulin usage (OR: 3.46, confidence interval (CI): 1.94–6.16), while individuals taking sulfonylureas had lower odds of insulin usage (OR: 0.27, CI: 0.08–0.91). A significant association was also seen with the total number of oral antidiabetic drugs prescribed (four drugs; OR: 15.6, and five drugs; OR: 9.1). Other factors did not show a significant association. The regression model showed HbA1c level as low as 7.9% could indicate a future insulin requirement in 22% of patients. Conclusion: The study outlines differences in characteristics and parameters among T2DM patients who require or do not require insulin and highlights the challenges in insulin initiation in Indian T2DM patients. Findings on II underscore the need for timely treatment intensification.

Assessment of rainfall trend over Periyar Vaigai Command area of Tamil Nadu

Rainfall trend analysis is critical for studying the effects of climate change. The most crucial aspect of understanding climate change at the basin level is, how it will affect water usage, planning, and development. The present study has been attempted to analyze the trend of annual and seasonal rainfall data over Periyar Vaigai Command area from 1982 – 2021 (40 years) employing different trend analysis methods i.e., Mann-Kendall test for trend significance, Sequential Mann-Kendall test for assessment of start and end of trend, Sen’s slope test for trend magnitude, Innovative Trend Analysis for combination of trends and linear regression analysis for trend detection. Statistically positive trend was detected in summer season using all methods whereas, annual and SWM rainfall showed a statistically significant decreasing trend. Winter and NEM rainfall resulted with no significant trend. The results from this study helps to adopt various water management practices and useful for policy makers to prepare appropriate mitigation strategies.

Quantitative analysis of antibacterial efficacy of herbal irrigants against endodontic microflora – A clinical study

Abstract Aims: The study aimed to assess the antimicrobial effectiveness of green tea and neem extract compared to sodium hypochlorite (NaOCl) against various root canal microorganisms. Materials and Methods: Thirty patients with pulpal necrosis were selected, providing 60 samples before and after irrigation. Groups were assigned as follows: Group A: 3% NaOCl (control), Group B: green tea, and Group C: neem extract. Samples were collected before and after irrigation in two phases. Samples were collected maintaining a strict sterile condition and stored in buffer solution at −80°C for bacterial-load measurement through real-time Polymerase chain reaction (PCR). Statistical analysis included within-group comparisons using Wilcoxon’s test and the paired t-test and inter-group comparisons using the Kruskal–Wallis test with post hoc Dunn’s test and one-way analysis of variance with post hoc Tukey’s honestly significant difference test (P ≤ 0.05). Results: While no irrigant achieved complete bacterial eradication, all solutions exhibited significant antimicrobial activity postirrigation. NaOCl yielded the most effective results, with green tea nearly comparable, and neem extract demonstrating the lowest efficacy. Conclusions: Herbal irrigants, particularly green tea, can serve as effective alternatives to chemical solutions. However, neem extract proved less effective than both green tea and NaOCl, indicating its inferiority in root canal disinfection.

Morphological and physiological plasticity of tomato in response to Azolla fern, a novel organic fertilizer of environmentally friendliness

Tomatoes are highly valued vegetable crops due to their excellent nutritional content. However, production remained low due to an incorrect combination of organic and inorganic soil nutrition. A pot experiment was conducted under shaded conditions with Azolla and inorganic nitrogen fertilization to determine the morphological and physiological plasticity of tomatoes. The study used a factorial combination of four levels of Azolla (0, 25, 50, and 75 g per pot) and four levels of nitrogen (0, 0.23, 0.46, and 0.69 g per pot) in a complete randomized design with three replications. We collected data on chlorophyll content (Chl a, Chl b, TChl), photosynthetic rate, water use efficiency, transpiration rate, stomata number, branch number (primary and secondary), plant height, leaf area, stomata conductance, relative water content, and number of leaves. Analysis of variance was employed to analyze the data, and the means were separated using the least significant differences test at a 5 % significance level. The results showed that primary and secondary branches, stomata number, transpiration rate, and water use efficiency were highly plastic due to the higher nitrogen levels and Azolla alone. The interaction effect of Azolla and nitrogen had a significant influence on chlorophyll content, photosynthesis rate, stomatal conductance, relative water content, number of leaves, plant height, and leaf area. It can be concluded that a balanced combination of organic and inorganic fertilizers remains essential for optimal tomato growth and physiology, emphasizing that the exclusive use of organic farming methods may not be the ideal solution.

Selecting scaling indicators in structural equation models (sems).

It is common practice for psychologists to specify models with latent variables to represent concepts that are difficult to directly measure. Each latent variable needs a scale, and the most popular method of scaling as well as the default in most structural equation modeling (SEM) software uses a scaling or reference indicator. Much of the time, the choice of which indicator to use for this purpose receives little attention, and many analysts use the first indicator without considering whether there are better choices. When all indicators of the latent variable have essentially the same properties, then the choice matters less. But when this is not true, we could benefit from scaling indicator guidelines. Our article first demonstrates why latent variables need a scale. We then propose a set of criteria and accompanying diagnostic tools that can assist researchers in making informed decisions about scaling indicators. The criteria for a good scaling indicator include high face validity, high correlation with the latent variable, factor complexity of one, no correlated errors, no direct effects with other indicators, a minimal number of significant overidentification equation tests and modification indices, and invariance across groups and time. We demonstrate these criteria and diagnostics using two empirical examples and provide guidance on navigating conflicting results among criteria. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Surgical Management of Complex Ankle Bony Impingement Combined With Chronic Ankle Instability.

Anterior ankle bony impingement, which can cause pain and dysfunction of the ankle, is commonly seen in sports injuries. Its primary cause is repeated injury due to chronic ankle instability. An excellent clinical result has been reported by surgically removing osteophytes and ankle stabilization. However, reports of complex anterior impingement combined with lateral ankle instability are rare, which remains challenging in clinical practice. The purpose of this study was to evaluate the clinical outcomes of anterior ankle bony impingement combined with lateral ankle instability with surgical dissection of osteophytes and stabilization. It was hypothesized that complex ankle osteophytes with instability would achieve optimal clinical outcomes through surgical management. Case series; Level of evidence, 4. A total of 57 patients with complex ankle bony impingement combined with lateral instability treated with surgical dissection of complex osteophytes between September 2013 and January 2019 were enrolled in the study. The clinical outcomes were evaluated by visual analog scale (VAS) for pain score, American Orthopedic Foot and Ankle Society (AOFAS) score, Karlsson score, and radiographic examination with a mean follow-up time of 39.6 months. Postoperative ankle function and complications were compared using the t test and post hoc Tukey significant difference test. The mean AOFAS score significantly increased at the 3-month, 1-year, and 2-year follow-ups compared with the preoperative condition (t = 10.57, P = .0001). The mean Karlsson score after surgery also significantly improved at each follow-up time compared with the preoperative score (t = 12.93, P = .0001). The preoperative VAS score significantly decreased at 3 months, 1 year, and 2 years postoperatively (t = 8.73, P = .001). A significant improvement of mean dorsiflexion difference was observed at 3 months and 1 year compared with the preoperative condition, but it seemed to have regressed at the 2-year follow-up (t = 2.11, P = .01). Tibial side recurrence was found in 9 cases, including 7 Scranton type 1 and 2 Scranton type 2. Talar side recurrence was also found in 3 of those cases. Our retrospective study demonstrated that complex ankle bony impingement combined with lateral instability can yield good clinical results when treated surgically with both ankle stabilization and osteophyte removal.

Influence of acepromazine on the cardiovascular effects of dobutamine in isoflurane anaesthetised horses premedicated with romifidine

ObjectiveTo explore the influence of acepromazine on the cardiovascular effects of dobutamine in isoflurane-anaesthetised horses premedicated with romifidine. Study designProspective randomised clinical trial. AnimalsA total of 18 horses undergoing elective arthroscopy were enrolled, of which 12 horses requiring dobutamine were included. Methodsorses were randomised to receive acepromazine 0.02 mg kg-1 (Group A+) intravenously (IV) or none (Group A-), 35 minutes before anaesthesia. Horses received xylazine 0.2 mg kg-1 concurrently to facilitate IV access. Horses were premedicated with romifidine 0.08 mg kg-1, induced with ketamine 2.2 mg kg-1 and diazepam 0.08 mg kg-1 IV, and maintained with isoflurane in oxygen. Dobutamine infusion was commenced when mean arterial pressure (MAP) was < 60 mmHg. Cardiovascular data were collected prior to dobutamine, and at a target MAP of ≥ 70 mmHg. Dobutamine start time from induction, duration and dose to reach target MAP were compared using Mann-Whitney U test. Cardiovascular variables were compared using repeated measures ANOVA and post-hoc Fisher’s least significant difference test. ResultsCardiac index (CI) and its percentage change was significantly higher at target MAP in group A+ [42.8 (17.0–68.7) %] than in A- [-4.05 (-21.2–13.0) %] (p = 0.003). Group A+ required significantly earlier dobutamine [20 (18–25) minutes] than group A- [36 (27–60) minutes] (p = 0.02). Group A+ required significantly higher dobutamine dose [1.5 (1–2.5) μg kg-1 minute-1] to reach target MAP than group A- [0.5 (0.5–1) μg kg-1 minute-1] (p = 0.009). No significant difference in infusion duration to reach target MAP was found between groups. Conclusion and clinical relevanceDobutamine significantly increased MAP and CI following pre-anaesthetic acepromazine sedation, in isoflurane-anaesthetised horses premedicated with romifidine. Without acepromazine, dobutamine increased MAP but not CI. Interactions between acepromazine, romifidine and dobutamine on the cardiovascular system should be considered.

Emergency physicians perspectives of state continuing medical education requirements for medical licensure.

This study aims to better understand the perspectives of emergency medicine physicians' on the role that state-mandated, topic-specific continuing medical education (CME) plays in addressing knowledge gaps, its relevance to current emergency practice, its reported burden and costs of CME activities to emergency physicians, and its perceived improvement in patient care. A cross-sectional survey was designed by the Coalition of Board-Certified Emergency Physicians (COBCEP) and distributed in February 2023 to all American Board of Emergency Medicine (ABEM)-certified physicians. Statistical tests of significance (Pearson's chi-square and Fisher's exact test) assessed the cost and time spent on CME as well as the perceived value placed on CME by ABEM-certified physicians to improve patient care. Data were summarized using descriptive statistics. There were 5562 (13.0%) responses from the 43656 physicians who received the survey-5506 responses were included for analysis. Over half of the physicians (53.0%) had more than 15 years of post-residency practice experience. Most physicians (57.3%) spent less than $5,000 per year on obtaining CME. Most physicians practicing in states with state-mandated, topic-specific CME requirements believed that participation in ABEM continuing certification could be used to reduce the need for state-mandated, topic-specific CME requirements (83.6%) and state-mandated, topic-specific requirements were believed to be unlikely to improve patient care (70.8%). Although well-intended, state CME requirements may lack relevancy and can, at times, place an undue burden on emergency physicians. Tailoring CME requirements to increase relevance to their patient populations and reduce barriers to completing CME could enhance knowledge translation and improve patient outcomes.

Node Centrality Inference via Hypothesis Testing

ABSTRACTCentral nodes, also known as vital or critical nodes, play a unique role in networks of various domains. To date, numerous centrality evaluation methods have been proposed to identify central nodes from different types of networks. However, most of existing methods did not address this issue from a rigorous significance testing perspective. As a result, it is hard for us to judge whether an identified central node is true or not and control the quality of reported nodes in a statistically sound manner. In this paper, we propose a centrality evaluation method based on hypothesis testing, where the test statistic is the degree sum of the neighbors of the node. We further derive an analytical p value and its upper bound under the Erdös–Rényi model, which can be employed as the centrality score for vital node recognition. To demonstrate the effectiveness of our method, extensive experiments are conducted on both simulated and real networks. The experimental results show that (1) our testing‐based centrality measure in terms of p value is capable of distinguishing central nodes from non‐central ones effectively and (2) our method is able to identify central nodes more accurately than those classic centrality measures and state‐of‐the‐art (SOTA) centrality evaluation methods.

Development and validation of a prognostic model to predict relapse in adults with remitted depression in primary care: secondary analysis of pooled individual participant data from multiple studies.

Relapse of depression is common and contributes to the overall associated morbidity and burden. We lack evidence-based tools to estimate an individual's risk of relapse after treatment in primary care, which may help us more effectively target relapse prevention. The objective was to develop and validate a prognostic model to predict risk of relapse of depression in primary care. Multilevel logistic regression models were developed, using individual participant data from seven primary care-based studies (n=1244), to predict relapse of depression. The model was internally validated using bootstrapping, and generalisability was explored using internal-external cross-validation. Residual depressive symptoms (OR: 1.13 (95% CI: 1.07 to 1.20), p<0.001) and baseline depression severity (OR: 1.07 (1.04 to 1.11), p<0.001) were associated with relapse. The validated model had low discrimination (C-statistic 0.60 (0.55-0.65)) and miscalibration concerns (calibration slope 0.81 (0.31-1.31)). On secondary analysis, being in a relationship was associated with reduced risk of relapse (OR: 0.43 (0.28-0.67), p<0.001); this remained statistically significant after correction for multiple significance testing. We could not predict risk of depression relapse with sufficient accuracy in primary care data, using routinely recorded measures. Relationship status warrants further research to explore its role as a prognostic factor for relapse. Until we can accurately stratify patients according to risk of relapse, a universal approach to relapse prevention may be most beneficial, either during acute-phase treatment or post remission. Where possible, this could be guided by the presence or absence of known prognostic factors (eg, residual depressive symptoms) and targeted towards these. NCT04666662.

Simulation methodologies to determine statistical power in laboratory animal research studies.

Null hypothesis significance testing is a statistical tool commonly employed throughout laboratory animal research. When experimental results are reported, the reproducibility of the results is of utmost importance. Establishing standard, robust, and adequately powered statistical methodology in the analysis of laboratory animal data is critical to ensure reproducible and valid results. Simulation studies are a reliable method for assessing the power of statistical tests, however, biologists may not be familiar with simulation studies for power despite their efficacy and accessibility. Through an example of simulated Harlan Sprague-Dawley (HSD) rat organ weight data, we highlight the importance of conducting power analyses in laboratory animal research. Using simulations to determine statistical power prior to an experiment is a financially and ethically sound way to validate statistical tests and to help ensure reproducibility of findings in line with the 4R principles of animal welfare.

Analysis of Factors that Affect the Length of Job Search for Educated Workers in West Lombok Regency

This research aims to analyze the influence of wage level, education level, age, gender, and job training on the length of time looking for work for educated workers in West Lombok Regency. This research uses a type of research, namely qualitative with secondary data. Data obtained from SAKERNAS in 2023. The amount of data obtained was 200 educated workers. The analytical tools used are multiple linear regression, coefficient of determination test (R2), partial significance test (t test) and simultaneous significance test (f test). The results of this study show that the variables of wage level, education level, age, gender and job training simultaneously do not have a significant effect on the length of looking for work. Meanwhile, the R2 value is 0.026, this means that 2.6% of the length of time looking for work for educated workers is influenced by variables above which the remainder is influenced by other variables outside this research.

PENGARUH KUALITAS PRODUK PERSEPSI HARGA DAN KUALITAS PELAYANAN TERHADAP KEPUASAN PELANGGAN PADA BENGKEL PLANET BAN RAYA DALUNG

Optimizing customer satisfaction is still one of the efforts in retaining Planet Tire Raya Dalung Workshop customers. Customer satisfaction is influenced by many factors. Some of these factors include product quality, price perception, and service quality. The formulation of the problem in this study is whether product quality, price perception and service quality partially and simultaneously affect customer satisfaction at Planet Ban Raya Dalung Workshop. The purpose of this study was to determine the effect of product quality, price perception, and service quality partially and simultaneously on customer satisfaction at the Planet Ban Raya Dalung workshop. The number of samples was determined by purposive random sampling technique with a sample of 85 respondents. Data analysis technique using validity and reliability test, classic assumption test, multiple linear regression analysis, determination analysis, partial significant test (T-test) and simultaneous significant test (F-test). The results showed that there was a positive and significant effect partially or simultaneously between product quality, perceived price and service quality on customer satisfaction of Planet Ban Raya Dalung.

Pengaruh Ease of Use dan Information Quality Terhadap Repurchase Intention Pengguna Aplikasi Grabfood Di Kota Mataram

This research aims to determine the effect of Ease of Use and Information Quality on Repurchase Intention of Grabfood application users in Mataram City. The population in this study were all Grabfood application users in Mataram City, while the sample for this study was 100 Grabfood users using purposive sampling techniques. This type of research is associative research. Data processing in this study used SPSS 25.0 for Windows, where validity tests, reliability tests, classical assumption tests, multiple linear regression tests, significance tests (t tests) and coefficient of determination (R2) were carried out. Based on the research results, it shows that: (1) Ease of Use has a positive and significant effect on Repurchase Intention (2) Information Quality has a positive and significant effect on Repurchase Intention