RESUMEN
Academic disciplines are often organized according to the behaviors they examine. While most research on a behavior tends to exist within one discipline, some behaviors are examined by multiple disciplines. Better understanding of behaviors and their relationships should enable knowledge transfer across disciplines and theories, thereby dramatically improving the behavioral knowledge base. We propose a taxonomy built on the World Health Organization's International Classification of Functioning, Disability, and Health (ICF), but design the taxonomy as a stand-alone extension rather than an improvement to ICF. Behaviors considered important enough to serve as the dependent variable in articles accepted for publication in top journals were extracted from nine different behavioral and social disciplines. A six-step development and validation process was employed, leading to the final taxonomy. A hierarchy of behaviors under the top banner of Engaging in activities/participating, reflective of ICF's D. hierarchy was constructed with eight immediate domains addressing behaviors ranging from learning, exercising, self-care, and substance use. The resulting International Classification of Behaviors (IC-Behavior), provides a behavior taxonomy targeted towards the interdisciplinary integration of nomological networks relevant to behavioral theories. While IC-Behavior has been labeled v.1.0 to communicate that it is by no means an endpoint, it has empirically shown to provide flexibility for the addition of new behaviors and is tested in the health domain.
Asunto(s)
Ciencias de la Conducta , Clasificación Internacional de Enfermedades/normas , Clasificación Internacional del Funcionamiento, de la Discapacidad y de la Salud/organización & administración , Humanos , Estudios Interdisciplinarios , Organización Mundial de la SaludRESUMEN
Trust and distrust are crucial aspects of human interaction that determine the nature of many organizational and business contexts. Because of socialization-borne familiarity that people feel about others, trust and distrust can influence people even when they do not know each other. Allowing that some aspects of the social knowledge that is acquired through socialization is also recorded in language through word associations, i.e., linguistic correlates, this study shows that known associations of trust and distrust can be extracted from an authoritative text. Moreover, the study shows that such an analysis can even allow a statistical differentiation between trust and distrust-something that survey research has found hard to do. Specifically, measurement items of trust and related constructs that were previously used in survey research along with items reflecting distrust were projected onto a semantic space created out of psychology textbooks. The resulting distance matrix of those items was analyzed by applying covariance-based structural equation modeling. The results confirmed known trust and distrust relationship patterns and allowed measurement of distrust as a distinct construct from trust. The potential of studying trust theory through text analysis is discussed.
RESUMEN
Likert scale surveys are frequently used in cross-cultural studies on leadership. Recent publications using digital text algorithms raise doubt about the source of variation in statistics from such studies to the extent that they are semantically driven. The Semantic Theory of Survey Response (STSR) predicts that in the case of semantically determined answers, the response patterns may also be predictable across languages. The Multifactor Leadership Questionnaire (MLQ) was applied to 11 different ethnic samples in English, Norwegian, German, Urdu and Chinese. Semantic algorithms predicted responses significantly across all conditions, although to varying degree. Comparisons of Norwegian, German, Urdu and Chinese samples in native versus English language versions suggest that observed differences are not culturally dependent but caused by different translations and understanding. The maximum variance attributable to culture was a 5% unique overlap of variation in the two Chinese samples. These findings question the capability of traditional surveys to detect cultural differences. It also indicates that cross-cultural leadership research may risk lack of practical relevance.
RESUMEN
A central goal of behavioral medicine is the creation of evidence-based interventions for promoting behavior change. Scientific knowledge about behavior change could be more effectively accumulated using "ontologies." In information science, an ontology is a systematic method for articulating a "controlled vocabulary" of agreed-upon terms and their inter-relationships. It involves three core elements: (1) a controlled vocabulary specifying and defining existing classes; (2) specification of the inter-relationships between classes; and (3) codification in a computer-readable format to enable knowledge generation, organization, reuse, integration, and analysis. This paper introduces ontologies, provides a review of current efforts to create ontologies related to behavior change interventions and suggests future work. This paper was written by behavioral medicine and information science experts and was developed in partnership between the Society of Behavioral Medicine's Technology Special Interest Group (SIG) and the Theories and Techniques of Behavior Change Interventions SIG. In recent years significant progress has been made in the foundational work needed to develop ontologies of behavior change. Ontologies of behavior change could facilitate a transformation of behavioral science from a field in which data from different experiments are siloed into one in which data across experiments could be compared and/or integrated. This could facilitate new approaches to hypothesis generation and knowledge discovery in behavioral science.
Asunto(s)
Investigación Biomédica/normas , Biología Computacional/métodos , Computación en Informática Médica , Vocabulario Controlado , Bases de Datos Factuales , Humanos , Semántica , Programas InformáticosRESUMEN
Advancement in science requires clarity of constructs.Like other fields in behavioral science, addiction research is being held back by researchers' use of different terms to mean similar things (synonymy) and the same term to mean different things (polysemy). Journals can help researchers to stay focused on novel and significant research questions by challenging new terms introduced without adequate justification and requiring authors to be parsimonious in their use of terms. To support construct lucidity, new modes of thinking about research integration are needed to keep up with the aggregate of relevant research.
Asunto(s)
Ciencias de la Conducta/estadística & datos numéricos , Investigación Biomédica/estadística & datos numéricos , Trastornos Relacionados con Sustancias , HumanosRESUMEN
BACKGROUND: When a construct such as patients' "transition to self-management" of chronic illness is studied by researchers across multiple disciplines, the meaning of key terms can become confused. This results from inherent problems in language where a term can have multiple meanings (polysemy) and different words can mean the same thing (synonymy). OBJECTIVES: The aim of this study was to test a novel quantitative method for clarifying the meaning of constructs by examining the similarity of published contexts in which they are used. METHODS: Published terms related to the concept transition to self-management of chronic illness were analyzed using the internomological network (INN), a type of latent semantic analysis performed to calculate the mathematical relationships between constructs based on the contexts in which researchers use each term. This novel approach was tested by comparing results with those from concept analysis, a best-practice qualitative approach to clarifying meanings of terms. By comparing results of the 2 methods, the best synonyms of transition to self-management, as well as key antecedent, attribute, and consequence terms, were identified. RESULTS: Results from INN analysis were consistent with those from concept analysis. The potential synonyms self-management, transition, and adaptation had the greatest utility. Adaptation was the clearest overall synonym but had lower cross-disciplinary use. The terms coping and readiness had more circumscribed meanings. The INN analysis confirmed key features of transition to self-management and suggested related concepts not found by the previous review. DISCUSSION: The INN analysis is a promising novel methodology that allows researchers to quantify the semantic relationships between constructs. The method works across disciplinary boundaries and may help to integrate the diverse literature on self-management of chronic illness.