Effect of Foot Reflexology Protocol on Premenstrual Syndrome Symptoms in Nursing Students: a Pre–Post Pilot Study

Background: Premenstrual syndrome is a highly prevalent cyclical disorder among women of childbearing age which interferes with daily activities, mood, and quality of life. Purpose: To evaluate the effects of a foot reflexology protocol on relieving pre-menstrual syndrome symptoms in nurs-ing students. Setting: Nursing School, São Paulo Uni-versity, Brazil. Participants: A convenience sample of 17 nursing students, diagnosed with moderate-to-severe premenstrual syn-drome as assessed by the Premenstrual Symptoms Screening Tool (PSST). Research design: A pre–post pilot inter-vention study. Intervention: The intervention consist-ed of eight reflexology sessions lasting 30 minutes for eight weeks. Main Outcome Measure: Evaluation of the participants by the PSST applied at the beginning and at the end of the study. Results: The participants had an average age of 21.7 (±2.6) years, ranging from 19 to 28 years; all were single, and most were in the third year of the course (58.8%); 75.6% lived with their family; 82.4% do not use contraceptives; 64.7% reported regular menstrual flow with an average duration of 5.1 (±1.1) days, and an average menstrual cycle interval of 29.3 (±4.9) days. The intervention significantly reduced the premenstrual symptoms assessed by the PSST (p<.017) with a pre–post difference of 10.2 points in the overall score, and the items score decreased between 1.2 to 3.4 for difficulty concentrating, insomnia, hy-persomnia, feeling overwhelmed, muscle/joint pain, bloating, weight gain; and be-tween 3.5 to 5.2 to anger/irritability, anxiety/tension, tearful, depressed mood, de-creased interest in daily activities, fatigue, overeating, and breast tenderness. There was a significant decrease regarding the functional impact of premenstrual symp-toms domain in the overall score with a pre–post difference of 10.7, and between 1.7 and 3.0 for all of the items (p<.04), except for the item “your home responsibilities”. Conclusion: Foot reflexology has shown promising results in reducing premen-strual syndrome symptoms.

Modeling the Adverse Childhood Experiences Questionnaire–International Version

Adverse childhood experiences (ACEs) are related to a host of deleterious physical and mental health outcomes. The ACE–International Questionnaire (ACE-IQ) was developed to assess categories of ACEs (e.g., sexual, emotional, and physical abuse) in internationally representative samples. Though the ACE-IQ has been used world-wide, little work has examined the structure of this measure. Further, much of the modeling techniques implemented lacked theoretical rationale. The present work used two principal components analyses (PCA) to evaluate the ACE-IQ structure using both the identified ACE categories as defined by the World Health Organization (WHO) and using the ACE-IQ items as individual indicators. Using the WHO method, a two-component structure was indicated. Alternatively, a PCA of the individual items yielded a six-component structure. Results highlight the importance of theoretically grounded measure evaluation and the potential distinctions amongst types of ACEs. Implications and future directions for research and practice are discussed.

Data and information needs of policymakers for palliative cancer care: a multi-country qualitative study

Background Despite regional efforts to address concerns regarding the burden of advanced cancer in Africa, urgent attention is still required. Widespread issues include late symptom presentation, inaccessibility of palliative care services, limited resources, poor data quality, disparity in data availability, and lack of stakeholder engagement. One way of helping to address these issues is by understanding and meeting the data and information needs of policymakers in palliative cancer care. Aims To explore the views of policymakers regarding data availability, data gaps and preferred data formats to support policy and decision making for palliative cancer care in Nigeria, Uganda and Zimbabwe. Methods A secondary analysis of interview data collected as part of a cross-sectional qualitative study that aimed to explore the data and information needs of patients, policymakers and caregivers in Nigeria, Uganda and Zimbabwe. Framework analysis, guided by the MEASURE evaluation framework, was used to qualitatively analyse the data. Results Twenty-six policymakers were recruited. The policymakers data and information concerns are aligned to the MEASURE evaluation framework of data and information use and include; assessing and improving data use (e.g. low prioritisation of cancer); identifying and engaging the data user (e.g. data processes); improving data quality (e.g. manual data collection processes); improving data availability (e.g. the accessibility of data); identifying information needs (e.g. what is ‘need to know’?); capacity building in core competencies (e.g. skills gaps); strengthening organisational data demand and use (e.g. policy frameworks); monitoring, evaluating and communicating of data demand and use (e.g. trustworthiness of data). Conclusions We present evidence of data sources, challenges to their access and use, guidance on data needs for policymakers, and opportunities for better engagement between data producers, brokers and users. This framework of evidence should inform the development of strategies to improve data access and use for policy and decision making to improve palliative cancer services in participating countries with relevance to the wider region.

Expanded and Filtered Features based ELM Model for Thyroid Disease Classification

Thyroid disorder affects the regulation of various metabolic processes throughout the human body. The structural and functional disorders can affect the body as well as the brain. The computer-aided diagnosis system can identify the kind of Thyroid disease. One such machine learning framework is presented in this paper to recognize disease existence and type. In this paper, a fuzzy adaptive feature filtration, expansion, and again filtration based model is presented for generating the most relevant and contributing features. This two-level filtration model is processed in a controlled fuzzy-based multi-measure evaluation. At the first level, the composite-fuzzy measures are combined with expert’s recommendations for identifying the ranked and relevant features. At the second level, the statistical computation based distance measure is applied for expanding the featureset. The fuzzification is applied to expanded featureset for transiting the continuous values to fuzzy-values. At this level, the fuzzy-based composite-measure is applied for selecting the most contributing and relevant features over the expanded dataset. This processing featureset is processed by the ELM classifier to predict the disease existence and class. Five experiments are conducted on two datasets for validating the performance and reliability of the proposed framework. The comparative analysis is conducted against the NaiveBayes, Decision Tree, Decision Forest, Random Tree, Multilevel Perceptron, and RBF Networks. The analysis outcome is taken in terms of accuracy, error, and relevancy based parameters. The proposed framework clams the significant gain in accuracy, relevancy, and reduction in the error rate.

Prediction of Stope Stability Using Variable Weight and Unascertained Measurement Technique

A new model is established to analyze mining stope stability, using variable weight theory to calculate the index weight for each factor in different stopes and unascertained measure evaluation technique to predict the risk grade of stope stability. In this model, an evaluation index system by virtue of the 7 most important factors is established, including rock saturated uniaxial compressive strength, rock quality designation, rock joint and fissure, stope span, condition of pillar, groundwater seepage volume, and rate of supporting pit roof. And each index is divided into 5 grades by assignment value and the classification method of standardization. Accordingly, the analysis result is also classified into 5 risk grades. This model is used for the 6 main stopes from the -270 m section in Xin-Qiao Mine, China. The results, giving risk grade for each stope and guiding the use of corresponding measures, avoided the problem of state out of balance caused by conventional invariable weight theory models and have ensured no accident occurred in mining production in recent years. This model can be used in other mines widely, by assigning values for the 7 factors on basis of current in situ cases.

FEATURES OF VALUATION OF NON-CURRENT TANGIBLE ASSETS IN THE ACCOUNTING SYSTEM

The question of evaluation is there key in accounting and financial reporting. In this In this context, valuation acts as a component of the method of accounting, according to which is used to measure the value of its objects. Based on information about their condition, investors make decisions about investment. For effective irreversible management tangible assets necessary is the settlement of issues that relate to their accounting, depreciation and determining the value of objects. Irreversible the assets of the enterprise, in particular its fixed assets, are the basis economic activity of the enterprise, one of the key elements production process and, therefore, one of the most important objects accounting and reporting, which characterizes the general property status enterprises, its economic potential and investment attractiveness. One of the most important elements of the method accounting is a reflection of its objects in one measure - evaluation. The latter is used as a tool for sharing and accounting acts of purchase and sale in terms of commodity-money relations. Valuation is the basis of accounting methodology accounting. From how correctly the method is chosen valuation of accounting objects depends reliability of financial statements and validity management decisions at the enterprise. In the analysis of the regulatory framework with regulation of accounting, in particular non-current assets, it becomes obvious the great importance of evaluation in modern accounting system. However, the current one stage of development of accounting characterized by the presence, on the one hand, fundamentally new requirements for professionals in the field accounting, on the other - the presence contradictions between regulations. Evaluation is an integral part of the method accounting and is closely related to others its elements. Using a money meter, simultaneously or separately with natural and labor, it is possible to generalize economic processes, means and sources of the enterprise. The basis for accounting and evaluation of non-current assets are regulations and International Financial Reporting Standards and accounting.

Ambo University Student’s Case Classification Models using Support Vector Machine

The main objective of ambo university is to provide quality education and improve the overall performance of an students by looking at individual students’ problems cases. One way to analysis students’ cases personally is to identify the problems causes and guide the students to solve the problems. Following this, the department Academic council and Academic Commission is whole authorized people to make the decision manually so this will consume more time and energy. This research focused to learning classification models for predicting students problems cases using support vector classification techniques. Finally, performance of the model evaluated using precision, recall and F-measure evaluation parameters.