Male nurses' views of gender in the nurse-family relationship in paediatric care.

AIMS: (1) To learn how male nurses view and manage their relationships with families of hospitalized children, in contrast to how they view those established by female nurses. (2) To know if male nurses' relationships with families of hospitalized children are influenced by gender roles and stereotypes. BACKGROUND: Relationships are essential in care. Prevailing gender stereotypes suggest that males have more difficulties with relationships than with technical aspects of nursing. METHOD: Descriptive qualitative research in a public tertiary hospital September-December 2015. Participants were male nurses who worked in maternal and child health. Purposive sampling, based on criteria of homogeneity-regularity and heterogeneity-diversity. Semi-structured interviews and content analysis. FINDINGS: Twelve male nurses participated. Two key themes emerged. (1) Establishment of professional-family relationship. Male nurses denied that male and female nurses established relationships with families differently, attributing any differences to personality rather than gender. (2) Management of relationships. Male nurses claimed that they set more limits on their relationships with families than female nurses. DISCUSSION: Male nurses both disrupted and reproduced gendered stereotypes about relationships with families, revealing new models of masculinity. CONCLUSION: Male nurses reject the stereotype that nursing is a women's profession, but they interpret their relationships with families in terms of gender roles and stereotypes. IMPLICATIONS FOR NURSING AND NURSING POLICY: These findings contribute to understandings of the influence of gender stereotypes in nursing. They support the work of professional associations and labour unions in Spain and other countries to combat gender stereotypes and gender differences in nursing.

[Commercial devices for monitoring symptoms in Parkinson's disease: benefits, limitations and trends]. / Dispositivos comerciales para la monitorización de síntomas en la enfermedad de Parkinson: beneficios, limitaciones y tendencias.

Parkinson's disease (PD) is a neurodegenerative disorder that significantly affects patients' quality of life. Treatment of PD requires accurate assessment of motor and non-motor symptoms, which is often complicated by subjectivity in reporting symptoms, and the limited availability of neurologists. Commercial wearable devices, which monitor PD symptoms continuously and outside the clinical setting, have appeared to address these challenges. These devices include PKG™, Kinesia 360™, Kinesia U™, PDMonitor™ and STAT-ON™. These devices use advanced technologies, including accelerometers, gyroscopes and specific algorithms to provide objective data on motor symptoms, such as tremor, dyskinesia and bradykinesia. Despite their potential, the adoption of these devices has been limited, due to concerns about their accuracy, complexity of use and the lack of independent validation. The correlation between the measurements obtained from these devices and traditional clinical observations varies, and their usability and patient adherence are critical areas for improvement. Validation and usability studies with a sufficient number of patients, standardised protocols and integration with hospitals' IT systems are essential to optimise their usefulness and improve patient outcomes.

TITLE: Dispositivos comerciales para la monitorización de síntomas en la enfermedad de Parkinson: beneficios, limitaciones y tendencias.Resumen. La enfermedad de Parkinson (EP) es un trastorno neurodegenerativo que afecta significativamente a la calidad de vida de los pacientes. El tratamiento de la EP requiere una evaluación precisa de los síntomas motores y no motores, que a menudo se complica por la subjetividad en el informe de síntomas y la limitada disponibilidad de neurólogos. Para abordar estos desafíos han surgido dispositivos comerciales vestibles que monitorizan los síntomas de la EP de manera continua y fuera del entorno clínico. Entre los principales dispositivos se encuentran PKG™, Kinesia 360™, Kinesia U™, PDMonitor™ y STAT-ON™. Estos dispositivos utilizan tecnologías avanzadas, como acelerómetros, giroscopios y algoritmos específicos, para proporcionar datos objetivos sobre síntomas motores, como temblores, discinesia y bradicinesia. A pesar de su potencial, la adopción de estos dispositivos es limitada, debido a preocupaciones sobre su precisión, la complejidad de su uso y la falta de validación independiente. La correlación entre las mediciones de estos dispositivos y las observaciones clínicas tradicionales varía, y la usabilidad y la adhesión del paciente son áreas críticas de mejora. Para optimizar su utilidad y mejorar los resultados para los pacientes, es esencial realizar estudios de validación y usabilidad con un número suficiente de pacientes, desarrollar protocolos estandarizados y asegurar la integración con sistemas informáticos hospitalarios.

Ten questions you should consider before submitting an article to a scientific journal. / Diez cuestiones que debería considerar antes de enviar un artículo a una revista científica.

Investigating involves not only knowing the research methods and designs; it involves knowing the strategies for disseminating and publishing the results in scientific journals. An investigation is considered complete when it is published and is disclosed to the scientific community. The publication of a manuscript is not simple, since it involves examination by a rigorous editorial process evaluator to ensure the scientific quality of the proposal. The objective of this article is to communicate to potential authors the main errors or deficiencies that typically and routinely explain the decision by the referees of scientific journals not to accept a scientific article. Based on the experience of the authors as referees of national and international journals in the field of nursing and health sciences, we have identified a total of 10 types or groups, which cover formulation errors, inconsistencies between different parts of the text, lack of structuring, imprecise language, information gaps, and the detection of relevant inaccuracies. The identification and analysis of these issues enables their prevention, and is of great use to future researchers in the dissemination of the results of their work to the scientific community. In short, the best publishing strategy is one that ensures the scientific quality of the work and spares no effort in avoiding the errors or deficiencies that referees routinely detect in the articles they evaluate.

Estimating bradykinesia severity in Parkinson's disease by analysing gait through a waist-worn sensor.

Bradykinesia is a cardinal symptom of Parkinson's disease (PD) and describes the slowness of movement revealed in patients. Current PD therapies are based on dopamine replacement, and given that bradykinesia is the symptom that best correlates with the dopaminergic deficiency, the knowledge of its fluctuations may be useful in the diagnosis, treatment and better understanding of the disease progression. This paper evaluates a machine learning method that analyses the signals provided by a triaxial accelerometer placed on the waist of PD patients in order to automatically assess bradykinetic gait unobtrusively. This method employs Support Vector Machines to determine those parts of the signals corresponding to gait. The frequency content of strides is then used to determine bradykinetic walking bouts and to estimate bradykinesia severity based on an epsilon-Support Vector Regression model. The method is validated in 12 PD patients, which leads to two main conclusions. Firstly, the frequency content of the strides allows for the dichotomic detection of bradykinesia with an accuracy higher than 90%. This process requires the use of a patient-dependant threshold that is estimated based on a leave-one-patient-out regression model. Secondly, bradykinesia severity measured through UPDRS scores is approximated by means of a regression model with errors below 10%. Although the method has to be further validated in more patients, results obtained suggest that the presented approach can be successfully used to rate bradykinesia in the daily life of PD patients unobtrusively.

Dyskinesia and motor state detection in Parkinson's disease patients with a single movement sensor.

Parkinson's Disease (PD) is a neurodegenerative disease that alters the patients' motor performance. Patients suffer many motor symptoms: bradykinesia, dyskinesia and freezing of gait, among others. Furthermore, patients alternate between periods in which they are able to move smoothly for some hours (ON state), and periods with motor complications (OFF state). An accurate report of PD motor states and symptoms will enable doctors to personalize medication intake and, therefore, improve response to treatment. Additionally, real-time reporting could allow an automatic management of PD by means of an automatic control of drug-administration pump doses. Such a system must be able to provide accurate information without disturbing the patients' daily life activities. This paper presents the results of the MoMoPa study classifying motor states and dyskinesia from 20 PD patients by using a belt-worn single tri-axial accelerometer. The algorithms obtained will be validated in a further study with 15 PD patients and will be enhanced in the REMPARK project.