Dataset Information

The Development of a Bi-Lingual Assessment Instrument to Measure Agentic and Communal Consumer Motives in English and French.

ABSTRACT: Consumer behavior is driven, in part, by the degree to which goods and services appeal to underlying motives for agency and communion. The purpose of this research was to develop a brief individual differences measure of these motivations for use in behavioral research and theoretical and applied consumer psychology and marketing studies. We employed a bi-lingual scale development procedure to create the 10-item Agentic and Communal Consumer Motivation Inventory (ACCMI) in English and French. Two studies show that the ACCMI is language invariant, demonstrates convergent and discriminant validity with consumer, motivational, and interpersonal constructs, and predicts evaluations of products described in agentic and communal terms, respectively, in both languages. The general conclusion of this research is that agency and communion provide a useful framework for understanding and studying consumer buying motivations. Discussion focuses on the relevance of motivational factors for studying human behavior and the applied utility of the ACCMI.

SUBMITTER: Friedman M

PROVIDER: S-EPMC4980988 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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The Development of a Bi-Lingual Assessment Instrument to Measure Agentic and Communal Consumer Motives in English and French.

Friedman Mike M Bartier Anne-Laure AL Lown Josh J Hopwood Christopher J CJ

Frontiers in psychology 20160811

Consumer behavior is driven, in part, by the degree to which goods and services appeal to underlying motives for agency and communion. The purpose of this research was to develop a brief individual differences measure of these motivations for use in behavioral research and theoretical and applied consumer psychology and marketing studies. We employed a bi-lingual scale development procedure to create the 10-item Agentic and Communal Consumer Motivation Inventory (ACCMI) in English and French. Tw ...[more]

PMID: 27563295

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Project description:BACKGROUND:Debates have arisen in various non-English speaking countries over the chosen language of instruction in medical education, whether it has to be the English language or the mother tongue. English-based education supporters argue that English is the leading international language of medicine and research, and a crucial tool for Continuing Medical Education (CME), as well as for students who seek practice abroad. On the other hand, mother-tongue-based medical education supporters present it as a way to endorse communication and comprehension between medical practitioners and health care system users, to bridge the gap between practitioners and the paramedical staff, and to overcome linguistic dualism and the language thinking disparity while studying in another. This study aimed to evaluate one of the simplified bi-lingual approaches in terms of medical-educational-written texts for a non-English speaking population: Arabic speaking medical students in specific. METHODS:1546 Arabic-speaking-medical students from different countries participated in a one-step-interactive-experimental-online test. The test assessed participants' scientific comprehension of three distinct written paragraphs: The first paragraph used conventional mother tongue (Arabic), the second combined English terminology and simplified mother tongue (hybrid), and the third used an English excerpt (English). Two multiple-choice questions (First question in Arabic, second in English) followed each paragraph. Response time was communicated for each paragraph. Participants were asked to select their favorable method. Repeated Measures ANOVA models and Paired Samples t-Test were used for statistical analysis. RESULTS:Participants scored a mean of [0.10] for the Arabic paragraph, [0.72] for the hybrid paragraph, and [0.24] for the English paragraph (P?<? 0.001). Results showed a significantly higher mean of points and correct answers within the fastest time for the hybrid paragraph [0.68] compared to the Arabic [0.08] and English [0.18] paragraphs (P?<? 0.001). Moreover, 50% of participants preferred the hybrid paragraph over the other two paragraphs. CONCLUSIONS:Taking into consideration the large number of participants and the statistically significant results, authors propose that simplified Arabic combined with English terminology may present a viable alternative method for medical-educational-written texts in Arabic-speaking population.

Project description:Bilingual dictionaries for technical terms such as biomedical terms are an important resource for machine translation systems as well as for humans who would like to understand a concept described in a foreign language. Often a biomedical term is first proposed in English and later it is manually translated to other languages. Despite the fact that there are large monolingual lexicons of biomedical terms, only a fraction of those term lexicons are translated to other languages. Manually compiling large-scale bilingual dictionaries for technical domains is a challenging task because it is difficult to find a sufficiently large number of bilingual experts. We propose a cross-lingual similarity measure for detecting most similar translation candidates for a biomedical term specified in one language (source) from another language (target). Specifically, a biomedical term in a language is represented using two types of features: (a) intrinsic features that consist of character n-grams extracted from the term under consideration, and (b) extrinsic features that consist of unigrams and bigrams extracted from the contextual windows surrounding the term under consideration. We propose a cross-lingual similarity measure using each of those feature types. First, to reduce the dimensionality of the feature space in each language, we propose prototype vector projection (PVP)--a non-negative lower-dimensional vector projection method. Second, we propose a method to learn a mapping between the feature spaces in the source and target language using partial least squares regression (PLSR). The proposed method requires only a small number of training instances to learn a cross-lingual similarity measure. The proposed PVP method outperforms popular dimensionality reduction methods such as the singular value decomposition (SVD) and non-negative matrix factorization (NMF) in a nearest neighbor prediction task. Moreover, our experimental results covering several language pairs such as English-French, English-Spanish, English-Greek, and English-Japanese show that the proposed method outperforms several other feature projection methods in biomedical term translation prediction tasks.

Dataset Information

The Development of a Bi-Lingual Assessment Instrument to Measure Agentic and Communal Consumer Motives in English and French.

Publications

The Development of a Bi-Lingual Assessment Instrument to Measure Agentic and Communal Consumer Motives in English and French.

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