Dataset Information

Why do you dance? Development of the Dance Motivation Inventory (DMI).

ABSTRACT: Dancing is a popular form of physical exercise and studies have show that dancing can decrease anxiety, increase self-esteem, and improve psychological wellbeing. The aim of the current study was to explore the motivational basis of recreational social dancing and develop a new psychometric instrument to assess dancing motivation. The sample comprised 447 salsa and/or ballroom dancers (68% female; mean age 32.8 years) who completed an online survey. Eight motivational factors were identified via exploratory factor analysis and comprise a new Dance Motivation Inventory: Fitness, Mood Enhancement, Intimacy, Socialising, Trance, Mastery, Self-confidence and Escapism. Mood Enhancement was the strongest motivational factor for both males and females, although motives differed according to gender. Dancing intensity was predicted by three motivational factors: Mood Enhancement, Socialising, and Escapism. The eight dimensions identified cover possible motives for social recreational dancing, and the DMI proved to be a suitable measurement tool to assess these motives. The explored motives such as Mood Enhancement, Socialising and Escapism appear to be similar to those identified in other forms of behaviour such as drinking alcohol, exercise, gambling, and gaming.

SUBMITTER: Maraz A

PROVIDER: S-EPMC4372397 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Why do you dance? Development of the Dance Motivation Inventory (DMI).

Maraz Aniko A Király Orsolya O Urbán Róbert R Griffiths Mark D MD Demetrovics Zsolt Z

PloS one 20150324 3

Dancing is a popular form of physical exercise and studies have show that dancing can decrease anxiety, increase self-esteem, and improve psychological wellbeing. The aim of the current study was to explore the motivational basis of recreational social dancing and develop a new psychometric instrument to assess dancing motivation. The sample comprised 447 salsa and/or ballroom dancers (68% female; mean age 32.8 years) who completed an online survey. Eight motivational factors were identified via ...[more]

PMID: 25803301

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Project description:The MUSIC® Model of Motivation is used to help instructors select strategies that can increase students' motivation and engagement in courses. The MUSIC model is comprised of five categories of strategies titled: empowerment, usefulness, success, interest, and caring. The purpose of this study was to examine the extent to which the MUSIC® Model of Academic Motivation Inventory (College Student version, short-form), demonstrates acceptable psychometric properties when used with students enrolled in a College of Veterinary Medicine. The inventory is comprised of five scales that correspond to the five MUSIC model components, and it measures the extent to which students perceive that: they have control in the course (empowerment); the activities in the course are useful to their future (usefulness); they can succeed in the course (success); the teaching activities and coursework are interesting (interest); and the instructor cares about students' learning and well-being (caring). The inventory has been validated for use with many different student populations, including students in different countries and of different ages (e.g., college students, middle and high school students, elementary school students). However, the inventory has not been validated for use with veterinary medicine students. We analyzed the data from 578 questionnaires that were obtained from students in six different courses at a College of Veterinary Medicine. We examined the psychometric properties of the MUSIC inventory by: (a) computing the internal consistency reliabilities for the scales; (b) calculating the fit indices and factor loadings obtained from confirmatory factor analyses; and (c) computing correlation coefficients between the inventory scales and students' self-reported effort in the course. The results provide evidence that the inventory demonstrates acceptable psychometric properties for use with veterinary medicine students. Consequently, the MUSIC Inventory can be used by researchers and instructors to assess students' motivation-related perceptions of courses.

Project description:Although construct measurement is critical to explanatory research and intervention efforts, rigorous measure development remains a notable challenge. For example, though the primary theoretical model for understanding health disparities among sexual minority (e.g., lesbian, gay, bisexual) adolescents is minority stress theory, nearly all published studies of this population rely on minority stress measures with poor psychometric properties and development procedures. In response, we developed the Sexual Minority Adolescent Stress Inventory (SMASI) with N = 346 diverse adolescents ages 14-17, using a comprehensive approach to de novo measure development designed to produce a measure with desirable psychometric properties. After exploratory factor analysis on 102 candidate items informed by a modified Delphi process, we applied item response theory techniques to the remaining 72 items. Discrimination and difficulty parameters and item characteristic curves were estimated overall, within each of 12 initially derived factors, and across demographic subgroups. Two items were removed for excessive discrimination and three were removed following reliability analysis. The measure demonstrated configural and scalar invariance for gender and age; a three-item factor was excluded for demonstrating substantial differences by sexual identity and race/ethnicity. The final 64-item measure comprised 11 subscales and demonstrated excellent overall (? = 0.98), subscale (? range 0.75-0.96), and test-retest (scale r > 0.99; subscale r range 0.89-0.99) reliabilities. Subscales represented a mix of proximal and distal stressors, including domains of internalized homonegativity, identity management, intersectionality, and negative expectancies (proximal) and social marginalization, family rejection, homonegative climate, homonegative communication, negative disclosure experiences, religion, and work domains (distal). Thus, the SMASI development process illustrates a method to incorporate information from multiple sources, including item response theory models, to guide item selection in building a psychometrically sound measure. We posit that similar methods can be used to improve construct measurement across all areas of psychological research, particularly in areas where a strong theoretical framework exists but existing measures are limited.

Project description:BackgroundThe first phase of an enterprise risk management (ERM) program is the identification of risks. Accurate identification is essential to a proactive and effective ERM function. The authors identified a lack of such risk identification in the literature and in practical cases when interviewing the chief risk officers from healthcare organizations. A risk inventory specific to healthcare organizations that includes detailed risk scenarios and risk impacts currently does not exist. Thus, the objective of this research is to develop an enterprise risk inventory for healthcare organizations to create a common understanding of how each type of risk impacts a healthcare organization.MethodERM guidelines and data from 15 interviews with chief risk officers were analyzed to create the risk inventory. The identified risks were confirmed through a survey of risk managers from a range of global healthcare organizations during the ASHRM conference in 2017. Descriptive statistics were developed and cluster analysis was performed using the survey results.ResultsThe risk inventory includes 28 risks and their specific risk scenarios. Cyberattack was ranked as the principal risk by the participants, followed by sentinel events and risks associated with human capital management (organizational culture, use of electronic medical records and physician wellness). The data analysis showed that the specific characteristics of the survey participants, such as the length of time working in risk management, the size of the organization, and the presence of a school of medicine, do not impact an individual's opinion of the importance of the risks identified. A personal background in risk management (clinical or enterprise) was a characteristic that showed a small difference in the perceived importance of the risks from the proposed risk inventory.ConclusionsIn addition to defining specific risk scenarios, the enterprise risk inventory presented in this research can contribute to guiding the risk identification phase of an ERM program and thereby support the development of a risk culture. Patient data security in hospitals that operate with high levels of technology is fundamental to delivering high quality and safe care to patients. At the top of the risk ranking, the identification of cyberattacks reflects the importance that healthcare risk managers place on this risk by allocating time and other resources. Exploring opportunities to improve cyber risk management and evaluating the benefits of using the risk inventory at the beginning of the risk identification phase in an ERM program are suggestions for future studies.

Dataset Information

Why do you dance? Development of the Dance Motivation Inventory (DMI).

Publications

Why do you dance? Development of the Dance Motivation Inventory (DMI).

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