scholarly journals Decision making and the bedside assessment: The Speech Language Therapists’ thinking when making a diagnosis at the bed

2021 ◽  
Vol 68 (1) ◽  
Author(s):  
Kim Coutts ◽  
Mershen Pillay
Keyword(s):  
Decision Making ◽  
Group Discussion ◽  
Second Phase ◽  
Data Sets ◽  
Assessment Data ◽  
Research Article ◽  
Assessment Measure ◽  
Phase Data ◽  
Assessment Measures ◽  
Two Phases

Background: The bedside assessment is often seen as a screener because of its high variability in sensitivity and specificity, whilst the instrumental measures are viewed as gold standards because of the ability of speech-language therapist (SLT) to visualise the swallow more objectively.Objectives: This research article explores how the value needs to be placed on the decision-making abilities of the SLT rather than on the assessment measure itself.Method: A mixed methodology concurrent triangulation design was employed to collect data in two phases: the first phase included observing seven SLTs conducting assessments using a standardised bedside measure together with pulse oximetry and cervical auscultation. The second phase was a focus group discussion based on the findings from the first phase. Data were analysed thematically using a bottom-up approach.Results: The following factors were found to influence the decision-making process at the bedside: bedside assessment data sets, patient, multidisciplinary team, context and then SLT. The availability of more data from the assessment from different data sets improved the confidence of the SLT at the bedside when needing to make clinical decisions. Clinical instincts are developed through experience and observation of those more experienced. These skills need to be developed from junior years.Conclusion: This research study showed that a bedside assessment can provide valuable information that will allow for diagnostic decisions to be made at the bedside. This study also highlighted the importance of critical thinking using clinical instincts, and that these are the factors that need to be valued and emphasised rather than the assessment measures themselves.

scholarly journals Self-Adaptive K-Means Based on a Covering Algorithm

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Yiwen Zhang ◽  
Yuanyuan Zhou ◽  
Xing Guo ◽  
Jintao Wu ◽  
Qiang He ◽  
...  
Keyword(s):  
Large Scale ◽  
Clustering Algorithm ◽  
Real Data ◽  
Second Phase ◽  
Data Sets ◽  
Number Of Clusters ◽  
Large Scale Data ◽  
Long Time ◽  
Two Phases ◽  
Selection Of

The K-means algorithm is one of the ten classic algorithms in the area of data mining and has been studied by researchers in numerous fields for a long time. However, the value of the clustering number k in the K-means algorithm is not always easy to be determined, and the selection of the initial centers is vulnerable to outliers. This paper proposes an improved K-means clustering algorithm called the covering K-means algorithm (C-K-means). The C-K-means algorithm can not only acquire efficient and accurate clustering results but also self-adaptively provide a reasonable numbers of clusters based on the data features. It includes two phases: the initialization of the covering algorithm (CA) and the Lloyd iteration of the K-means. The first phase executes the CA. CA self-organizes and recognizes the number of clusters k based on the similarities in the data, and it requires neither the number of clusters to be prespecified nor the initial centers to be manually selected. Therefore, it has a “blind” feature, that is, k is not preselected. The second phase performs the Lloyd iteration based on the results of the first phase. The C-K-means algorithm combines the advantages of CA and K-means. Experiments are carried out on the Spark platform, and the results verify the good scalability of the C-K-means algorithm. This algorithm can effectively solve the problem of large-scale data clustering. Extensive experiments on real data sets show that the accuracy and efficiency of the C-K-means algorithm outperforms the existing algorithms under both sequential and parallel conditions.

Diagnostic Decisions of Language Complexity Using Informal Language Assessment Measures

2021 ◽  
pp. 1-13
Author(s):  
Rebecca Bawayan ◽  
Jennifer A. Brown
Keyword(s):  
Decision Making ◽  
Measure Data ◽  
Assessment Data ◽  
Language Complexity ◽  
Narrative Assessment ◽  
School Based ◽  
Language Quality ◽  
Assessment Measures ◽  
Criterion Referenced ◽  
Language Sample

Purpose: The current study aimed to understand the clinical decision-making skills of school-based speech-language pathologists (SLPs) using narrative and expository discourse information from three sources: perception of language through listening to language alone, standardized criterion-referenced narrative assessment data, and word- and morpheme-level language sample analysis data. Method: Twenty-eight current school-based SLPs participated in the study. During this study, participants rated language quality and made decisions regarding the provision of language services after being provided information from informal assessment measures. Results: SLPs' ratings of language quality and complexity varied across the story retell, wordless picture book generation, and expository samples. There was a lack of consistency in ratings within each context across areas of clarity, sample complexity, language complexity, and vocabulary across all SLPs. Self-reported factors that influenced SLPs' ratings included components of structure, syntax, and semantics. SLPs did not indicate a need for services after listening alone. When provided with criterion-referenced narrative assessment scores and word- and morpheme-level language sample data, more SLPs made a recommendation for services. Conclusions: The study demonstrates the need for objective language measure data during diagnostic decision making. Additionally, SLPs may not realize the information obtained from real-time perception, and analysis of language samples may be an unreliable and inconsistent picture of a child's language abilities. The results of this study highlight the need to continue to rely on multiple sources of assessment data. SLPs should continue to incorporate systematic methods to minimize variability of perceptions in the process of making diagnostic decisions. Supplemental Material: https://doi.org/10.23641/asha.17707451

When prior knowledge overrules new evidence: Adaptive use of decision strategies and the role of behavioral routines 1The paper is based on a presentation held at the 16th SPUDM conference in Leeds, 1997. The research was supported by a grant from the Deutsche Forschungsgemeinschaft to Klaus Fiedler and Tilmann Betsch, within the Sonderforschungsbereich 504 at the Universities of Mannheim and Heidelberg. We are grateful to Frank Siebler for programming the Mouselab. Thanks are due to Susanne Haberstroh, Arndt Bröder, Bronwyn Jones and Esther Goldbloom for many helpful comments on earlier versions of the paper.

1999 ◽  
Vol 58 (3) ◽  
pp. 151-160 ◽  
Author(s):  
Tilmann Betsch ◽  
Babette Julia Brinkmann ◽  
Klaus Fiedler ◽  
Katja Breining
Keyword(s):  
Decision Making ◽  
Time Pressure ◽  
Time Lapse ◽  
Second Phase ◽  
Decision Strategies ◽  
Adaptive Use ◽  
Human Ability ◽  
Two Phases ◽  
Adaptive Decision Making ◽  
New Evidence

This paper focuses on behavioral routines in adaptive decision making. In an experiment consisting of two phases, participants worked on recurrent, multiattribute choice problems. In the first phase, routines were induced by relying upon the human ability to adapt to situational changes by changing decision strategies. To induce strategy change, time pressure was varied as a within factor. Payoffs were manipulated so that an adaptive change in strategy led participants to maximize choice frequency for one out of three options (routine acquisition). After a one week time lapse, participants worked on similar problems, containing the previously preferred routine option. In this second phase, payoffs favored deviation from the routine option. Results showed that choices were almost perfectly calibrated to payoffs under low time pressure. However, if time pressure increased, participants were more likely to prefer the routine option, even though search strategies were still used adaptively and evidence discouraged routine selection. Results are discussed with reference to the model of adaptive decision making ( Payne, Bettman & Johnson, 1993 ), and the MODE model of attitude-behavior relation ( Fazio, 1990 ).

Initial Northern Iroquoian Coalescence

2018 ◽  
pp. 89-105 ◽  
Author(s):  
Jennifer Birch ◽  
Ronald F. Williamson
Keyword(s):  
Decision Making ◽  
Social Organization ◽  
Second Phase ◽  
Regional Networks ◽  
Village Level ◽  
The Social ◽  
Males And Females ◽  
Two Phases ◽  
And Gender ◽  
The Village

Northern Iroquoian societies experienced two phases of community coalescence, one in the thirteenth century, which brought semi-sedentary populations together into the first true villages, and a second phase two centuries later that created large palisaded settlements. This chapter is primarily concerned with the first wave of village formation and the changes in social organization and gender and power relations that accompanied the transition to sedentism. This included more formalized decision-making at the village level as well as the development of recursive entanglements between regional networks defined by kin- and clan-based relations and materialized through ritual and mortuary programs. We argue that transformations in the social and physical labor performed by males and females at the village and regional levels is key to understanding this transition.

ACO_NB-Based Hybrid Prediction Model for Medical Disease Diagnosis

2021 ◽  
pp. 526-536
Author(s):  
Amit Kumar ◽  
Manish Kumar ◽  
Nidhya R.
Keyword(s):  
Prediction Model ◽  
Disease Diagnosis ◽  
Second Phase ◽  
Data Sets ◽  
Feature Subset ◽  
Hybrid Prediction ◽  
Related Data ◽  
Medical Disease ◽  
Proposed Model ◽  
Two Phases

In recent years, a huge increase in the demand of medically related data is reported. Due to this, research in medical disease diagnosis has emerged as one of the most demanding research domains. The research reported in this chapter is based on developing an ACO (ant colony optimization)-based Bayesian hybrid prediction model for medical disease diagnosis. The proposed model is presented in two phases. In the first phase, the authors deal with feature selection by using the application of a nature-inspired algorithm known as ACO. In the second phase, they use the obtained feature subset as input for the naïve Bayes (NB) classifier for enhancing the classification performances over medical domain data sets. They have considered 12 datasets from different organizations for experimental purpose. The experimental analysis advocates the superiority of the presented model in dealing with medical data for disease prediction and diagnosis.

Maximal Pattern Mining Using Fast CP-Tree for Knowledge Discovery

2012 ◽  
Vol 3 (1) ◽  
pp. 56-74 ◽  
Author(s):  
R. Vishnu Priya ◽  
A.Vadivel ◽  
R. S. Thakur
Keyword(s):  
Knowledge Discovery ◽  
Pattern Mining ◽  
Bench Mark ◽  
Second Phase ◽  
Data Sets ◽  
Item Order ◽  
Tree Construction ◽  
Item List ◽  
Transaction Database ◽  
Two Phases

The knowledge discovery from large database is useful for decision making in industry real-time problems. Given a large voluminous transaction database, the knowledge is discovered by extracting maximal pattern after some analysis. Various methods have been proposed for extracting maximal pattern including FP and CP trees. It has been noticed that time taken by these methods for mining is found to be large. This paper modifies tree construction strategy of CP-tree for mining maximal pattern and the strategy takes less time for mining. The proposed modified CP-tree is constructed in two phases. The first phase constructs the tree based on user given item order along with its corresponding item list. In the second phase, each node in the branch of the constructed tree is dynamically rearranged based on item sorted list. The maximal patterns are retrieved from the proposed tree using the FPmax algorithm. The proposed tree has been built to support both interactive and incremental mining. The performance is evaluated using both dense and sparse bench mark data sets such as CHESS, MUSHROOM, CONNECT-4, PUMSB, and RETAIL respectively. The performance of the modified CP-tree is encouraging compared to some of the recently proposed approaches.

Technical Papers in Support of the Canadian Study of Health and Aging

2001 ◽  
Vol 13 (S1) ◽  
pp. 5-6
Author(s):  
Ian McDowell ◽  
Kenneth Rockwood ◽  
Christina Wolfson
Keyword(s):  
Epidemiologic Studies ◽  
Second Phase ◽  
Data Sets ◽  
Journal Articles ◽  
Canadian Study ◽  
Comprehensive Description ◽  
Study Methods ◽  
The Public ◽  
Widespread Availability ◽  
Phase Data

The Canadian Study of Health and Aging (CSHA) is one of the largest epidemiologic studies of dementia conducted to date, with over 100 papers published or in press. The first (prevalence) phase data collection began in 1991, and the second (incidence) phase was completed in 1996. Publication of first and second phase data began in 1994 and 1998, respectively. The CSHA has contributed not only to our understanding of dementia, but also more broadly to the population health of elderly people. However, for those unfamiliar with the CSHA, gaining an understanding of the study's design and results has been difficult, due to the study's scope and complexity and necessarily brief descriptions of study methods in journal articles. Now, given the widespread availability of the data to the public at large and the research community, a comprehensive description of the study methods and data sets is desirable as a guide for potential users.

scholarly journals The Study Designing A Sustainable Financing Model For Health Promotion Services In Iran

2021 ◽  
Author(s):  
Hamideh Javadinasb ◽  
Aslan Nazari ◽  
Kimia Pourmohammadi ◽  
Ali Reza Yousefi ◽  
Ramin Hayati
Keyword(s):  
Health Promotion ◽  
Qualitative Interviews ◽  
Group Discussion ◽  
Health Financing ◽  
Second Phase ◽  
Financing Model ◽  
Two Phases ◽  
Sustainable Health ◽  
Sustainable Financing ◽  
Comprehensive Study

Abstract Background: Sustainable financing for Health Promotion Services (HPS) has always been challenged and attracted the attention of health domain politicians. This study was conducted to aim at designing a sustainable health financing model for HPS in IranMethods: This combined study was conducted in two phases. First, the published comparative study of sustainable financing for HPS and comprehensive study of the related current documents with this subject from 2005 to 2017 were used. In the second phase, the qualitative interviews for Iran’s current situation and capacities for sustainable health financing of HPS and Focus Group Discussion (FGD) meetings for finalized the aforementioned model were used.Results: The rules and advantages of levying sin tax, the related stakeholders in sustainable health financing, challenges and solutions of gathering, pooling, and purchasing of sustainable financial resources have been extracted.Conclusion: According to the results, there is no political and national commitment to executing sustainable health financing regulations in Iran. Lack of necessary infrastructures for their execution, resistance, and disagreement of harmful good industries are the barriers to executing these regulations. The model was suggested establishing a health promotion foundation and the permanent law for execution necessity and legitimacy of receiving public budget, sin tan, health tax, and duties will be provided.

A Protocol for Development of Holistic-Entrepreneur Graduates: Emotional Intelligence Perspectives

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Nurul Haerani Mohamad ◽  
◽  
Badaruddin Ibrahim ◽  
Asri Selamat ◽  
Affero Ismail ◽  
...  
Keyword(s):  
Emotional Intelligence ◽  
Targeted Delivery ◽  
Action Plan ◽  
Group Discussion ◽  
Document Analysis ◽  
Second Phase ◽  
Ministry Of Education ◽  
Third Phase ◽  
Phase Data ◽  
Vocational Courses

Entrepreneurship is seen as a potential career path for overcoming the problem of unemployment among TVET graduated especially during this Covid-19 outbreaks. However, this career has yet to get a second or even a last option TVET graduates in Malaysia. Various efforts have been undertaken by the stakeholders through the first surge of the Malaysia Education Blueprint 2015-2025 (Higher Education) and the continuation of the implementation of the Entrepreneurship Action Plan 2016-2020, the holistic development of human capital and entrepreneurial backbone graduate entrepreneurs in targeted delivery. However, based on current achievements, this is not easy to be implemented as the desire of entrepreneurship is not incredibly encouraging, especially graduates in technical and vocational courses. Therefore, this study was conducted to explore emotional intelligence attributes needed by TVET graduates to become a qualified graduated Holistic-Entrepreneur. This study was conducted qualitatively involved three phases. The first phase: data acquisition qualitatively based on document analysis; second phase: focus group discussion and, third phase: experts’ interview. The participants involved are from Ministry of Education and MTUN lecturers and they are expert in students’ development and entrepreneurship. The result shows there are six attributes of emotional intelligence needed by TVET graduates to become a holistic entrepreneur graduates. The implication of the proposed as guideline for relevant parties and TVET graduates in increasing student minded and desire towards entrepreneurship

scholarly journals Guidelines for educational administration based on sufficiency economy philosophy

2017 ◽  
Vol 7 (1) ◽  
pp. 20-29
Author(s):  
Prayuth Chusorn ◽  
Dawruwan Thawinkarna ◽  
Tang Keow Ngang
Keyword(s):  
Educational Administration ◽  
Qualitative Method ◽  
Group Discussion ◽  
Academic Development ◽  
School Curriculum ◽  
Second Phase ◽  
Optimal Outcomes ◽  
Administrative Management ◽  
Two Phases ◽  
Sufficiency Economy Philosophy

Abstract This study aimed to examine the existing situation of educational administration thus developed guidelines based on Sufficiency Economy Philosophy in the five educational extended schools under the Office of Khon Kaen Primary Education Service Area 4. Researchers utilized qualitative method multi-cases design. This study was carried out in two phases involving document analysis, interview and observation to examine the situation of educational administration followed by focus group discussion to develop guidelines. Data was analyzed using content analysis and presented it in descriptive manner. Results from the first phase of the study indicated that stakeholders are meeting together to set the vision and mission which integrated the Sufficiency Economy Philosophy in every administrative aspect in terms of policy. In addition, all the five research schools were implementing the specified mission and vision as they planned. Furthermore, stakeholders participated in planning for academic development and Sufficiency Economy Philosophy was integrated in school curriculum specifically in academic aspect. Improvement in the plan for the following year was conducted through evaluation. The second phase of the findings regarding the guidelines for educational administrators as such administrators and stakeholders should participate in setting policy based on the Sufficiency Economy Philosophy and implement it in school administrative management. Meanwhile the Sufficiency Economy Philosophy should be integrated in school curriculum by having stakeholders worked out the plan for academic development. The implementation of plans should be based on the concepts of saving, worthiness, and optimal outcomes. Finally environmental factors were needed for Sufficiency Economy Philosophy instruction. Keywords: Sufficiency Economy Philosophy, extended schools, guidelines, educational administration, education.

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