Alia Salam, Russell K. McIntire and Lucille B. Pilling
The purpose of this paper is to identify the severity of certain communication disorders (CD) in a sample of Syrian refugee children. There are a limited number of studies about…
Abstract
Purpose
The purpose of this paper is to identify the severity of certain communication disorders (CD) in a sample of Syrian refugee children. There are a limited number of studies about CD among refugee children.
Design/methodology/approach
Over a period of 22 months, 161 cases of CD – not caused by motor or structural disorders – were seen at a Mental Health Clinic in Beqaa, Lebanon. The authors calculated descriptive statistics (frequencies and percentages) and bivariate statistics to identify relationships between CD, demographics and school enrollment among cases.
Findings
Ages ranged between 3 and 16 years with a mean of 6.91. Male to female ratio was 1.6:1. The most prevalent category of CD was speech, followed by expressive language, then receptive language. Parents reported behavioral or emotional problems in 38 percent of the cases; emotional problems, mainly anxiety, were much more common than behavioral problems. Enrollment in school was associated with a lower number of impairments and less severe speech and language impairments.
Originality/value
The results highlight the importance of early detection and intervention among Syrian refugee children. Schools can alleviate some psychological issues that compound CD by enhancing resilient behaviors and providing social support. They can also implement measures for detection and intervention.
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Mojisola D. Kupolati, Una E. MacIntyre and Gerda J. Gericke
The aim of this review is to critically assess published articles on school-based nutrition education (NE) intervention to identify factors hindering or contributing to the…
Abstract
Purpose
The aim of this review is to critically assess published articles on school-based nutrition education (NE) intervention to identify factors hindering or contributing to the success of interventions. School-based NE possesses the capacity to influence learners’ nutrition behaviours.
Design/methodology/approach
An electronic search of articles was conducted in Medline, PubMed, the Cumulative Index to Nursing and Allied Health Literature databases, Google and snowballing. Included in the review were school-based studies with classroom NE with or without nutrition services and studies published between 2000 and 2013. School-based non-intervention studies and interventions that did not include a nutrition teaching component were excluded in the review.
Findings
Thirty-nine studies met the inclusion criteria. Features of successful NE interventions included the use of behavioural theories, especially the social cognitive theory and the involvement of trained teachers in the implementation of interventions. Capacity development for teachers, time constraints, school policies and implementation problems of multicomponent interventions were some of the identified challenges encountered in the studies reviewed.
Originality/value
Trained teachers are invaluable assets in interventions to improve nutrition behaviours of learners. Challenges associated with teacher-oriented school-based NE intervention can be overcome by properly designed and implemented interventions based on behavioural theory.
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Marketers must be aware that consumers do not evaluate all products in the same way. Even brands that are perceived as very similar overall are often selectively evaluated…
Abstract
Marketers must be aware that consumers do not evaluate all products in the same way. Even brands that are perceived as very similar overall are often selectively evaluated. Consumer product involvement, or concern with the actual purchase or use of the product, affects these selective perception processes in several ways. Implications for market segmentation, product differentiation, and communication strategies are discussed.
Krishnadas Nanath, Supriya Kaitheri, Sonia Malik and Shahid Mustafa
The purpose of this paper is to examine the factors that significantly affect the prediction of fake news from the virality theory perspective. The paper looks at a mix of…
Abstract
Purpose
The purpose of this paper is to examine the factors that significantly affect the prediction of fake news from the virality theory perspective. The paper looks at a mix of emotion-driven content, sentimental resonance, topic modeling and linguistic features of news articles to predict the probability of fake news.
Design/methodology/approach
A data set of over 12,000 articles was chosen to develop a model for fake news detection. Machine learning algorithms and natural language processing techniques were used to handle big data with efficiency. Lexicon-based emotion analysis provided eight kinds of emotions used in the article text. The cluster of topics was extracted using topic modeling (five topics), while sentiment analysis provided the resonance between the title and the text. Linguistic features were added to the coding outcomes to develop a logistic regression predictive model for testing the significant variables. Other machine learning algorithms were also executed and compared.
Findings
The results revealed that positive emotions in a text lower the probability of news being fake. It was also found that sensational content like illegal activities and crime-related content were associated with fake news. The news title and the text exhibiting similar sentiments were found to be having lower chances of being fake. News titles with more words and content with fewer words were found to impact fake news detection significantly.
Practical implications
Several systems and social media platforms today are trying to implement fake news detection methods to filter the content. This research provides exciting parameters from a viral theory perspective that could help develop automated fake news detectors.
Originality/value
While several studies have explored fake news detection, this study uses a new perspective on viral theory. It also introduces new parameters like sentimental resonance that could help predict fake news. This study deals with an extensive data set and uses advanced natural language processing to automate the coding techniques in developing the prediction model.
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The purpose of this paper is to draw attention to the range and depth of sustainability issues at their points of impact with company experience, and to pilot an illustration of…
Abstract
Purpose
The purpose of this paper is to draw attention to the range and depth of sustainability issues at their points of impact with company experience, and to pilot an illustration of how they could be imaginatively yet critically approached for management development purposes.
Design/methodology/approach
Citing and making sense of a variety of seminal or otherwise relevant sources in order to illustrate an imaginative yet critical approach to sustainability. This is a pilot demonstration to stimulate discussion and to help individuals develop their own sense making.
Findings
The need to allow space and time for reflection on the depth and breadth of sustainability approaches in order to enable personal understanding leading to wise action.
Research limitations/implications
This paper discusses planetary sustainability yet is confined to mainly Anglophone sources. Some of the latent environmental thought forms discussed, e.g. doom, may be largely restricted to them.
Practical implications
Divergent evaluations of trans-disciplinary, critical sustainability approaches are necessary for the longer-term development of motivation within companies.
Originality/value
This appears to be the first attempted trans-disciplinary yet critical business studies approach to sustainability at its points of impact with corporate operations. It aims to contribute to a new kind of management development path.
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Vassilios Kappatos and Evangelos Dermatas
In outside constructions (e.g. aircraft frames, bridges, tanks and ships) real‐life noises reduce significantly the capability of location and characterization of crack events…
Abstract
Purpose
In outside constructions (e.g. aircraft frames, bridges, tanks and ships) real‐life noises reduce significantly the capability of location and characterization of crack events. Among the most important types of noise is the rain, producing a signal similar to crack. This paper seeks to present a robust crack detection system with simultaneous raining conditions and additive white‐Gaussian noise at −20 to 20 dB signal‐to‐noise ratio (SNR).
Design/methodology/approach
The proposed crack detection system consists of two sequentially, connected modules: the feature extraction module where 15 robust features are derived from the signal and a radial basis function neural network is built up in the pattern classification module to extract the crack events.
Findings
The evaluation process is carried out in a database consisting of over 4,000 simulated cracks and drops signals. The analysis showed that the detection accuracy using the most robust 15 features ranges from 77.7 to 93 percent in noise‐free environment. This is a promising method for non‐destructive testing (NDT) by acoustic emission method of aircraft frame structures in extremely noisy conditions.
Practical implications
Continuous monitoring of crack events in the field requires the development of advance noise reduction and signal identification techniques. Robust detection of crack signals in noisy environment, including raining drops, improves significantly the reliability of real‐time monitoring systems in large and complex constructions and in adverse weather conditions.
Originality/value
As far as is known this is the first time that an efficient system is presented and evaluated which deals with the problem of crack detection in adverse environment including both stationary and non‐stationary noise components. Moreover, it provides further information on the engineering and efficiency problems associated with NDT techniques in the aircraft industry.
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This paper aims to chart the influence of McCarthyism and of FBI surveillance practices on a number of prominent American social scientists, market researchers, opinion pollsters…
Abstract
Purpose
This paper aims to chart the influence of McCarthyism and of FBI surveillance practices on a number of prominent American social scientists, market researchers, opinion pollsters and survey research practitioners during the post-war years. Hitherto disparate sets of historical evidence on how Red Scare tactics influenced social researchers and marketing scientists are brought together and updated with evidence from original archival research.
Design/methodology/approach
The paper draws on the existing secondary literature on how social research practitioners and social scientists reacted to the unusually high pressures on academic freedom during the McCarthy era. It supplements this review with evidence obtained from archival research, including declassified FBI files. The focus of this paper is set on prominent individuals, mainly Bernard Berelson, Samuel Stouffer, Hadley Cantril, Robert S. Lynd, Paul F. Lazarsfeld, Herta Herzog, Ernest Dichter, but also the Frankfurt School in exile.
Findings
Although some of the historiography presents American social scientists and practitioners in the marketing research sector as victims of McCarthyism and FBI surveillance, it can also be shown that virtually all individuals in focus here also developed strategies of accommodation, compromise and even opportunism to benefit from the climate of suspicion brought about by the prevailing anti-Communism.
Social implications
Anyone interested in questions about the morality of marketing, market research and opinion polling as part of the social sciences practiced in vivo will need to pay attention to the way these social-scientific practices became tarnished by the way prominent researchers accommodated and at times even abetted McCarthyism.
Originality/value
Against the view of social scientists as harassed academic minority, evidence is presented in this paper which shows American social scientists who researched market-related phenomena, like media, voters choices and consumer behaviour, in a different light. Most importantly, this paper for the first time presents archival evidence on the scale of Paul F. Lazarsfeld’s surveillance by the FBI.
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Ifeyimika O. Ajaiyeoba and Matthew J. Aplin-Houtz
This paper investigates the relationship between workplace incivility (WI) and nurses’ job and vocational turnover intentions. We introduce two moderators, organizational efficacy…
Abstract
Purpose
This paper investigates the relationship between workplace incivility (WI) and nurses’ job and vocational turnover intentions. We introduce two moderators, organizational efficacy (OE) and calling and investigate their influence on the relationship between WI and turnover intentions.
Design/methodology/approach
We surveyed 187 nurses in the Southwest US, currently employed in a clinical setting. We tested the hypothesized model using PLS-SEM for data analysis.
Findings
The results show that WI influences job turnover intentions but not vocational turnover intentions. OE and Calling both uniquely moderate the relationship between specific sources of WI and nurses’ turnover intentions.
Research limitations/implications
We offer insights into the effect various sources of WI have on nurses’ turnover intentions. Our findings imply that WI is less impactful on vocational turnover than job turnover. Also, OE and calling can be utilized to moderate the negative effects of WI.
Practical implications
Healthcare organizations should implement strategies that promote a positive work environment for all employees, particularly nurses. They should also strive to build a workplace culture that fosters calling among nurses.
Originality/value
The paper examines the differential impact of various sources of WI on two forms of turnover intentions, prominent and relevant in the nursing work environment. In addition, we introduce two new moderators – OE and calling – that significantly influence the relationship between WI and turnover intentions.
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Nafiu Olaniyi Oladokun, Moussa Larbani and Mustafa Omar Mohammed
– The purpose of this paper is to develop a Muzara’ah–supply chain model for the purpose of enhancing agricultural financing and productivity in Nigeria.
Abstract
Purpose
The purpose of this paper is to develop a Muzara’ah–supply chain model for the purpose of enhancing agricultural financing and productivity in Nigeria.
Design/methodology/approach
In this paper, an expert survey approach was employed to validate the newly developed model.
Findings
A survey result on the model reveals that majority of the respondents agreed with the Muzara’ah–supply chain model and preferred it to the existing models.
Research limitations/implications
The main limitation of this study is limited number of respondents.
Practical implications
With this newly developed financing model that is based risk sharing principles, the application of this model could help to reduce moral hazard and enhance agricultural productivity.
Originality/value
To the best knowledge of the researchers, such kind of study for financing agriculture does not exists in the case of Nigeria.