Investigating academic dishonesty and its relationship with moral competence and professional identity of nursing students: a cross-sectional study.

BACKGROUND: Academic dishonesty as a fundamental challenge in adherence of ethical principles in providing care to patients has caused concern to the scientific community of nurses. In addition, positive professional identity and high moral competence are important for nurses to perform multiple care roles in high quality care of patients. The purpose of the present study is of investigating academic dishonesty and its relationship with moral competence and professional identity of master's and PhD nursing students. METHODS: This descriptive-analytical study was conducted by census method on 65 master's and PhD nursing students in Shiraz University of Medical Sciences, Iran in 2023. Data collection tools included 4 questionnaires (Demographic information, Academic Dishonesty Scale (DAS), Nurses' moral competence and Professional Identity Scale for Nursing Students (PISNS)). Data collection was done within 2 months. Descriptive and inferential analyzes including independent t-test, Pearson correlation coefficient and linear regression were used to analyze the data. The collected data were analyzed by SPSS.V.22 software. P-value less than 0.05 was considered significant. RESULTS: The average age of 65 participants was 31.5 ± 5.61 years. The majority of the participants in this study were women 48 (73.8%). There is a significant and negative correlation between academic dishonesty and moral competence (r=-0.260, P-value = 0.036). There is no significant correlation between academic dishonesty and professional identity (r = 0.154, P-value = 0.22). Also, a significant positive correlation was found between moral competence and professional identity (r = 0.294, P-value = 0.018). CONCLUSION: Therefore, considering that the fact that students have a great impact on patient care, Researchers suggest that educational institutions should prevent the increase of academic dishonesty among students by establishing new rules and regulations.

Exploring the challenges to using telecardiology as perceived by pre-hospital emergency care personnel: a qualitative study.

BACKGROUND: Today, using the medical technology of telecardiology, as part of advanced medical services, plays an essential role in providing care to cardiac patients in life-threatening conditions who need emergency care. However, pre-hospital emergency care personnel are faced with certain challenges in using telecardiology, with adverse effects on their performance. Therefore, the present study aimed to investigate the challenges to using telecardiology as viewed by pre-hospital emergency care personnel in Southern Iran. METHODS: The present study is a qualitative work of research with a content analysis approach. Selected using purposeful sampling, 19 pre-hospital emergency care personnel were interviewed on a semi-structured, personal, in-depth basis. The qualitative data obtained were analyzed using the Graneheim and Lundman's conventional content analysis approach (2004). RESULTS: Based on the qualitative data analysis, 3 themes and 8 subthemes were obtained. The three main themes included professional barriers (lack of clinical knowledge of telecardiology, lack of clinical skill in telecardiology, violation of patients' privacy, lack of clinical guidelines on telecardiology), medical equipment and telecommunication barriers (poor reception and ineffective means of communication, low charge on the battery of tele-electrocardiogram machines), and organizational management barriers (serious lack of cardiologists available for medical counseling and lack of continual personal development of the telecardiology personnel). CONCLUSION: Senior managers in pre-hospital emergency care services are recommended to use the results of this study to identify the influential factors in using telecardiology and take the necessary measures to eliminate the existing barriers toward making optimal use of telemedicine, thereby improving the quality of care provided for cardiac patients.

MicroSweat: A Wearable Microfluidic Patch for Noninvasive and Reliable Sweat Collection Enables Human Stress Monitoring.

Stress affects cognition, behavior, and physiology, leading to lasting physical and mental illness. The ability to detect and measure stress, however, is poor. Increased circulating cortisol during stress is mirrored by cortisol release from sweat glands, providing an opportunity to use it as an external biomarker for monitoring internal emotional state. Despite the attempts at using wearable sensors for monitoring sweat cortisol, there is a lack of reliable wearable sweat collection devices that preserve the concentration and integrity of sweat biomolecules corresponding to stress levels. Here, a flexible, self-powered, evaporation-free, bubble-free, surfactant-free, and scalable capillary microfluidic device, MicroSweat, is fabricated to reliably collect human sweat from different body locations. Cortisol levels are detected corresponding to severe stress ranging from 25 to 125 ng mL-1 averaged across multiple body regions and 100-1000 ng mL-1 from the axilla. A positive nonlinear correlation exists between cortisol concentration and stress levels quantified using the perceived stress scale (PSS). Moreover, owing to the sweat variation in response to environmental effects and physiological differences, the longitudinal and personalized profile of sweat cortisol is acquired, for the first time, for various body locations. The obtained sweat cortisol data is crucial for analyzing human stress in personalized and clinical healthcare sectors.

Autonomous electrochemical biosensing of glial fibrillary acidic protein for point-of-care detection of central nervous system injuries.

The integration of electrochemical biosensors into fluid handling units such as paper-based, centrifugal, and capillary microfluidic devices has been explored with the purpose of developing point-of-care platforms for quantitative detection of bodily fluid markers. However, the present fluidic device designs largely lack the capacity of full assay automation, needing manual loading of one or multiple reagents or requiring external devices for liquid manipulation. Such fluidic handing platforms also require universality for detecting various biomarkers. These platforms are also largely produced using materials unsuitable for scalable manufacturing and with a high production cost. The mechanism of fluid flow also often induces noise to the embedded biosensors which adversely impacts the accuracy of biosensing. This work addresses these challenges by presenting a reliable design of a fully automated and universal capillary-driven microfluidic platform that automates several steps of label-free electrochemical biosensing assays. These steps include sample aliquoting, controlled incubation, removal of non-specific bindings, reagent mixing and delivery to sensing electrodes, and electrochemical detection. The multilayer architecture of the microfluidic device is made of polymeric and adhesive materials commercially used for the fabrication of point-of-care devices. The design and geometry of different components of the device (e.g., sampling unit, mixer, resistances, delay valves, interconnecting components) were optimized using a combined experimental testing and numerical fluid flow modeling to reach high reproducibility and minimize the noise-induced to the biosensor. As a proof of concept, the performance of this on-chip immunosensing platform was demonstrated for rapid and autonomous detection of glial fibrillary acidic proteins (GFAP) in phosphate-buffered saline (PBS). The microfluidic immunosensing device exhibited a linear detection range of 10-1000 pg mL-1 for the detection of GFAP within 30 min, with a limit of detection (LoD) and sensitivity of 3 pg mL-1 and 39 mL pg-1 mm-2 in PBS, respectively. Owing to its simplicity, sample-to-result performance, universality for handing different biofluids, low cost, high reproducibility, compatibility with scalable production, and short analysis time, the proposed biosensing platform can be further adapted for the detection of other biomarkers in different clinical bodily fluids for rapid diagnostic and prognostic applications.

Bi-ECDAQ: An electrochemical dual-immuno-biosensor accompanied by a customized bi-potentiostat for clinical detection of SARS-CoV-2 Nucleocapsid proteins.

Multiplex electrochemical biosensors have been used for eliminating the matrix effect in complex bodily fluids or enabling the detection of two or more bioanalytes, overall resulting in more sensitive assays and accurate diagnostics. Many electrochemical biosensors lack reliable and low-cost multiplexing to meet the requirements of point-of-care detection due to either limited functional biosensors for multi-electrode detection or incompatible readout systems. We developed a new dual electrochemical biosensing unit accompanied by a customized potentiostat to address the unmet need for point-of-care multi-electrode electrochemical biosensing. The two-working electrode system was developed using screen-printing of a carboxyl-rich nanomaterial containing ink, with both working electrodes offering active sites for recognition of bioanalytes. The low-cost bi-potentiostat system (∼$80) was developed and customized specifically to the bi-electrode design and used for rapid, repeatable, and accurate measurement of electrochemical impedance spectroscopy signals from the dual biosensor. This binary electrochemical data acquisition (Bi-ECDAQ) system accurately and selectively detected SARS-CoV-2 Nucleocapsid protein (N-protein) in both spiked samples and clinical nasopharyngeal swab samples of COVID-19 patients within 30 min. The two working electrodes offered the limit of detection of 116 fg/mL and 150 fg/mL, respectively, with the dynamic detection range of 1-10,000 pg/mL and the sensitivity range of 2744-2936 Ω mL/pg.mm2 for the detection of N-protein. The potentiostat performed comparable or better than commercial Autolab potentiostats while it is significantly lower cost. The open-source Bi-ECDAQ presents a customizable and flexible approach towards addressing the need for rapid and accurate point-of-care electrochemical biosensors for the rapid detection of various diseases.

A compact, low-cost, and binary sensing (BiSense) platform for noise-free and self-validated impedimetric detection of COVID-19 infected patients.

Electrochemical immuno-biosensors are one of the most promising approaches for accurate, rapid, and quantitative detection of protein biomarkers. The two-working electrode strip is employed for creating a self-supporting system, as a tool for self-validating the acquired results for added reliability. However, the realization of multiplex electrochemical point-of-care testing (ME-POCT) requires advancement in portable, rapid reading, easy-to-use, and low-cost multichannel potentiostat readers. The combined multiplex biosensor strips and multichannel readers allow for suppressing the possible complex matrix effect or ultra-sensitive detection of different protein biomarkers. Herein, a handheld binary-sensing (BiSense) bi-potentiostat was developed to perform electrochemical impedance spectroscopy (EIS)-based signal acquisition from a custom-designed dual-working-electrode immuno-biosensor. BiSense employs a commercially available microcontroller and out-of-shelf components, offering the cheapest yet accurate and reliable time-domain impedance analyzer. A specific electrical board design was developed and customized for impedance signal analysis of SARS-CoV-2 nucleocapsid (N)-protein biosensor in spiked samples and alpha variant clinical nasopharyngeal (NP) swab samples. BiSense showed limit-of-detection (LoD) down to 56 fg/mL for working electrode 1 (WE1) and 68 fg/mL for WE2 and reported with a dynamic detection range of 1 pg/mL to 10 ng/mL for detection of N-protein in spiked samples. The dual biosensing of N-protein in this work was used as a self-validation of the biosensor. The low-cost (∼USD$40) BiSense bi-potentiostat combined with the immuno-biosensors successfully detected COVID-19 infected patients in less than 10 min, with the BiSense reading period shorter than 1.5 min, demonstrating its potential for the realization of ME-POCTs for rapid and hand-held diagnosis of infections.

Immuno-biosensor on a chip: a self-powered microfluidic-based electrochemical biosensing platform for point-of-care quantification of proteins.

The realization of true point-of-care (PoC) systems profoundly relies on integrating the bioanalytical assays into "on-chip" fluid handing platforms, with autonomous performance, reproducible functionality, and capacity in scalable production. Specifically for electrochemical immuno-biosensing, the complexity of the procedure used for ultrasensitive protein detection using screen-printed biosensors necessitates a lab-centralized practice, hindering the path towards near-patient use. This work develops a self-powered microfluidic chip that automates the entire assay of electrochemical immuno-biosensing, enabling controlled and sequential delivery of the biofluid sample and the sensing reagents to the surface of the embedded electrochemical biosensor. Without any need for active fluid handling, this novel sample-to-result testing kit offers antibody-antigen immunoreaction within 15 min followed by the subsequent automatic washing, redox probe delivery, and electrochemical signal recording. The redox molecules ([Fe(CN)6]3-/4-) are pre-soaked and dried in fiber and embedded inside the chip. The dimensions of the fluidic design and the parameters of the electrochemical bioassay are optimized to warrant a consistent and reproducible performance of the autonomous sensing device. The uniform diffusion of the dried redox into the injected solution and its controlled delivery onto the biosensor are modeled via a two-phase flow computational fluid dynamics simulation, determining the suitable time for electrochemical signal measurement from the biosensor. The microfluidic chip performs well with both water-based fluids and human plasma with the optimized sample volume to offer a proof-of-concept ultrasensitive biosensing of SARS-CoV-2 nucleocapsid proteins spiked in phosphate buffer saline within 15 min. The on-chip N-protein biosensing demonstrates a linear detection range of 10 to 1000 pg mL-1 with a limit of detection of 3.1 pg mL-1. This is the first self-powered microfluidic-integrated electrochemical immuno-biosensor that promises quantitative and ultrasensitive PoC biosensing. Once it is modified for its design and dimensions, it can be further used for autonomous detection of one or multiple proteins in diverse biofluid samples.

Prediction of Arterial Blood Gas Factors from Venous Blood Gas Factors in Intensive Care Unit Admitted Patients.

BACKGROUND: Blood gas analysis is very important in the patients with respiratory problems. Arterial puncture may cause complications such as pain, local hematoma, infection and nerve injury. The procedure itself can be technically difficult. In contrast, venous sampling is an easier procedure with fewer complications. Therefore, this study aims to determine the possibility of replacement of venous blood gas (VBG) values by ABG values in ICU wards admitted patients. METHODS: In this study, 155 paired blood gas samples collected from patients admitted to ICU wards in Motahari hospital, Marvdasht, Fars, Iran. Statistical means of blood gas parameters, including PO2, PCO2, HCO3 and PH have been compared in both, arterial and venous, blood samples in parallel using paired t-test. RESULTS: Mean difference of arterial and venous gas parameters, PO2, PCO2 and HCO3 , was significantly differ. All paired gas parameters in arterial and venous blood samples were significantly correlated, while this correlation was stronger between PCO2 and HCO3. CONCLUSION: To predict the arterial blood gas parameters from VBG parameters, single regression models are of more statistical value compared to multiple regression models. Defined single regression prediction models could be used to predict arterial PCO2 and HCO3 , which may reduce arterial sampling in ICU wards.

A study of marital satisfaction among non-depressed and depressed mothers after childbirth in Jahrom, Iran, 2014.

INTRODUCTION: Birth is one of the most wonderful events in nature and pregnancy and delivery are major developments for most married women. Similar to the pregnancy period, the period of time following delivery is accompanied by certain mental and physical changes in women. During this time, mothers experience a full range of mental disorders, varying from minor to psychotic. The objective of this study was to examine marital satisfaction among non-depressed and depressed mothers who visited primary health centers in Jahrom after childbirth in 2014. MATERIALS & METHODS: This is a descriptive cross-sectional study. The study population consisted of 80 mothers, who were in the 6 to 12 weeks of delivery and had visited primary health centers in Jahrom from April to July, 2014.To select the participants, the researcher looked thorough the files at each center and chose the mothers who were qualified for the study based on convenience sampling. The criteria for participation were: being aged from 20 to 40; being in the 6-12 weeks since delivery; having a healthy newborn; willingness to participate in the study. The participants were divided into the two groups of mothers suffering from postpartum depression (40 women) and mothers not affected by postpartum depression (40 women) on basis of questionnaire. The study follows the ethics in a scientific study. The researcher personally visited the primary health centers and explained the objectives of the study to the participants. Subsequently, the participants were asked to complete a demographic questionnaire, Enrich Marital Satisfaction Scale, and Edinburgh Postpartum Depression Scale. The participants were allowed one hour to complete the questionnaires. RESULTS: The results showed that the average age of depressed and non-depressed women was respectively 28.1 ± 5 and 29.4 ± 5.5. Regarding the sex of the newborns, 53% of the depressed women had a son and 46.7% had a daughter. In the non-depressed group, 43.3% of the mothers had a son and 56.7% had a daughter. 56.7% of the depressed mothers were first-time mothers; however, 43.3% of the non-depressed mothers had experienced childbirth for the first time. Most of the women in both groups had a high-school diploma-53% of the depressed mothers and 51% of the non-depressed. 66.7% of the depressed mothers had had natural childbirths; 60% of the non-depressed mothers had had Cesareans. There was not a statistically meaningful difference between the two groups in terms of the demographic variables. The average depression score of the depressed group was 13.7 with a standard deviation of 3.2; the average depression score of the non-depressed group was 5.8 with a standard deviation of 2. There was a statistically significant difference between the two groups in terms of marital satisfaction. CONCLUSION: Postpartum depression is a major and common health problem, affects many women after childbirth and inflicts not only direct costs on the health care system, but causes extensive indirect losses due to mothers' inability to function. Though this condition is prevalent among new mothers, not many researchers have addressed it in small towns and investigated its relationship with marital satisfaction. In addition, most women suffering from postpartum depression know very little about the disorder. Accordingly, it is vital to educate women and conduct more studies on the issue.