Acute Effects of Neuromuscular-Training with Handheld-Vibration on Elbow Joint Position Sense

Context: Clinicians use exercises in rehabilitation to enhance sensorimotor-function, however evidence supporting their use is scarce. Objective: To evaluate acute effects of handheld-vibration on joint position sense (JPS). Design: A repeated-measure, randomized, counter-balanced 3-condition design. Setting: Sports Medicine and Science Research Laboratory. Patients or Other Participants: 31 healthy college-aged volunteers (16-males, 15-females; age=23+3y, mass=76+14kg, height=173+8cm). Interventions: We measured elbow JPS and monitored training using the Flock-of-Birds system (Ascension Technology, Burlington, VT) and MotionMonitor software (Innsport, Chicago, IL), accurate to 0.5°. For each condition (15,5,0Hz vibration), subjects completed three 15-s bouts holding a 2.55kg Mini-VibraFlex dumbbell (Orthometric, New York, NY), and used software-generated audio/visual biofeedback to locate the target. Participants performed separate pre- and post-test JPS measures for each condition. For JPS testing, subjects held a non-vibrating dumbbell, identified the target (90°flexion) using biofeedback, and relaxed 3-5s. We removed feedback and subjects recreated the target and pressed a trigger. We used SPSS 14.0 (SPSS Inc., Chicago, IL) to perform separate ANOVAs (p<0.05) for each protocol and calculated effect sizes using standard-mean differences. Main Outcome Measures: Dependent variables were absolute and variable error between target and reproduced angles, pre-post vibration training. Results: 0Hz (F1,61=1.310,p=0.3) and 5Hz (F1,61=2.625,p=0.1) vibration did not affect accuracy. 15Hz vibration enhanced accuracy (6.5±0.6 to 5.0±0.5°) (F1,61=8.681,p=0.005,ES=0.3). 0Hz did not affect variability (F1,61=0.007,p=0.9). 5Hz vibration decreased variability (3.0±1.8 to 2.3±1.3°) (F1,61=7.250,p=0.009), as did 15Hz (2.8±1.8 to 1.8±1.2°) (F1,61=24.027, p<0.001). Conclusions: Our results support using handheld-vibration to improve sensorimotor-function. Future research should include injured subjects, functional multi-joint/multi-planar measures, and long-term effects of similar training.

Employer participation in Florida school -to -work initiatives

This study used a cross-sectional design and descriptive research methodology to assess the characteristics and practices of employers participating in Florida school-to-work (STW) initiatives, the factors influencing their participation, and their STW partnerships with schools. The study also examined the relationships between employer characteristics and participation. ^ A sampling frame of 15,202 employers from the 28 Florida STW regions was constructed. Data were collected via a mail survey with a random sample of employers, using a researcher-designed questionnaire. Data were analyzed using descriptive statistics, correlational analysis, and analysis of variance. ^ At the 95% confidence level, it was estimated that the mean establishment size in the population is between 25 and 51 employees and that employers have been involved in STW partnerships between five and seven years. ^ The study revealed broad-based employer participation in three of four areas: Working with Students, Working with Educators, and Internal Company Practices Supporting STW. A fourth area, Building a System, showed generally low participation. Data indicate that workforce needs are important incentives to employer STW participation beyond their desire to contribute to education or the community. Data also indicate that lack of information on STW is the greatest barrier to employer participation. ^ Sample employers have more positive perceptions of the value of their partnerships with schools than of the quality of the partnerships. Ninety-four percent agreed that students are better prepared for work and careers as a result of the partnership's activities. More than half agreed that a sense of trust and good communication exist between educators and employer partners. ^ Employer variables found to have a significant, positive relationship with participation include size (coefficient of determination r2 = .116), years in STW partnerships (r2 = .128), and perceptions of partnership quality (r2 = .092) and value (r2 = .112). ^ A major conclusion based on the findings of this study is that employer participation is optimized in initiatives that achieve important STW outcomes for students and build long-term relationships between employers and schools. Another that in Florida, the STW Opportunities Act of 1994 has not resulted in substantially greater employer involvement in building a STW system. ^

Electoral rules and elite recruitment: A comparative analysis of the Bundestag and the U.S. House of Representatives

In this research, I analyze the effects of candidate nomination rules and campaign financing rules on elite recruitment into the national legislatures of Germany and the United States. This dissertation is both theory-driven and constitutes exploratory research, too. While the effects of electoral rules are frequently studied in political science, the emphasis is thereby on electoral rules that are set post-election. My focus, in contrast, is on electoral rules that have an effect prior to the election. Furthermore, my dissertation is comparative by design.^ The research question is twofold. Do electoral rules have an effect on elite recruitment, and does it matter? To answer these question, I create a large-N original data set, in which I code the behavior and recruitment paths and patterns of members of the American House of Representatives and the German Bundestag. Furthermore, I include interviews with members of the said two national legislatures. Both the statistical analyses and the interviews provide affirmative evidence for my working hypothesis that differences in electoral rules lead to a different type of elite recruitment. To that end, I use the active-politician concept, through which I dichotomously distinguish the economic behavior of politicians.^ Thanks to the exploratory nature of my research, I also discover the phenomenon of differential valence of local and state political office for entrance into national office in comparative perspective. By statistically identifying this hitherto unknown paradox, as well as evidencing the effects of electoral rules, I show that besides ideology and culture, institutional rules are key in shaping the ruling elite. The way institutional rules are set up, in particular electoral rules, does not only affect how the electorate will vote and how seats will be distributed, but it will also affect what type of people will end up in elected office.^

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

‘The past was never simply there to begin with and the future is not simply what will unfold’ : a posthumanist performative approach to qualitative longitudinal research

Peer reviewed

‘The past was never simply there to begin with and the future is not simply what will unfold’ : a posthumanist performative approach to qualitative longitudinal research

Peer reviewed

‘The past was never simply there to begin with and the future is not simply what will unfold’ : a posthumanist performative approach to qualitative longitudinal research

Peer reviewed

Participatory Methods for Climate Change and Mental Health Research: Photovoice in Nepal

Background: The relationship between mental health and climate change are poorly understood. Participatory methods represent ethical, feasible, and culturally-appropriate approaches to engage community members for mental health promotion in the context of climate change. Aim: Photovoice, a community-based participatory research methodology uses images as a tool to deconstruct problems by posing meaningful questions in a community to find actionable solutions. This community-enhancing technique was used to elicit experiences of climate change among women in rural Nepal and the association of climate change with mental health. Subjects and methods: Mixed-methods, including in-depth interviews and self-report questionnaires, were used to evaluate the experience of 10 women participating in photovoice. Quantitative tools included Nepali versions of Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI) and a resilience scale. Results: In qualitative interviews after photovoice, women reported climate change adaptation and behavior change strategies including environmental knowledge-sharing, group mobilization, and increased hygiene practices. Women also reported beneficial effects for mental health. The mean BDI score prior to photovoice was 23.20 (SD=9.00) and two weeks after completion of photovoice, the mean BDI score was 7.40 (SD=7.93), paired t-test = 8.02, p<.001, n=10. Conclusion: Photovoice, as a participatory method, has potential to inform resources, adaptive strategies and potential interventions to for climate change and mental health.

Using parent report to assess early lexical production in children exposed to more than one language

Limited expressive vocabulary skills in young children are considered to be the first warning signs of a potential Specific Language Impairment (SLI) (Ellis & Thal, 2008). In bilingual language learning environments, the expressive vocabulary size in each of the child’s developing languages is usually smaller compared to the number of words produced by monolingual peers (e.g. De Houwer, 2009). Nonetheless, evidence shows children’s total productive lexicon size across both languages to be comparable to monolingual peers’ vocabularies (e.g. Pearson et al., 1993; Pearson & Fernandez, 1994). Since there is limited knowledge as to which level of bilingual vocabulary size should be considered as a risk factor for SLI, the effects of bilingualism and language-learning difficulties on early lexical production are often confounded. The compilation of profiles for early vocabulary production in children exposed to more than one language, and their comparison across language pairs, should enable more accurate identification of vocabulary delays that signal a risk for SLI in bilingual populations. These considerations prompted the design of a methodology for assessing early expressive vocabulary in children exposed to more than one language, which is described in the present chapter. The implementation of this methodological framework is then outlined by presenting the design of a study that measured the productive lexicons of children aged 24-36 months who were exposed to different language pairs, namely Maltese and English, Irish and English, Polish and English, French and Portuguese, Turkish and German as well as English and Hebrew. These studies were designed and coordinated in COST Action IS0804 Working Group 3 (WG3) and will be described in detail in a series of subsequent publications. Expressive vocabulary size was measured through parental report, by employing the vocabulary checklist of the MacArthur-Bates Communicative Development Inventory: Words and Sentences (CDI: WS) (Fenson et al., 1993, 2007) and its adaptations to the participants’ languages. Here we describe the novelty of the study’s methodological design, which lies in its attempt to harmonize the use of vocabulary checklist adaptations, together with parental questionnaires addressing language exposure and developmental history, across participant groups characterized by different language exposure variables. This chapter outlines the various methodological considerations that paved the way for meaningful cross-linguistic comparison of the participants’ expressive lexicon sizes. In so doing, it hopes to provide a template for and encourage further research directed at establishing a threshold for SLI risk in children exposed to more than one language.

Combining Information from Multiple Sources in Bayesian Modeling

Surveys can collect important data that inform policy decisions and drive social science research. Large government surveys collect information from the U.S. population on a wide range of topics, including demographics, education, employment, and lifestyle. Analysis of survey data presents unique challenges. In particular, one needs to account for missing data, for complex sampling designs, and for measurement error. Conceptually, a survey organization could spend lots of resources getting high-quality responses from a simple random sample, resulting in survey data that are easy to analyze. However, this scenario often is not realistic. To address these practical issues, survey organizations can leverage the information available from other sources of data. For example, in longitudinal studies that suffer from attrition, they can use the information from refreshment samples to correct for potential attrition bias. They can use information from known marginal distributions or survey design to improve inferences. They can use information from gold standard sources to correct for measurement error.

This thesis presents novel approaches to combining information from multiple sources that address the three problems described above.

The first method addresses nonignorable unit nonresponse and attrition in a panel survey with a refreshment sample. Panel surveys typically suffer from attrition, which can lead to biased inference when basing analysis only on cases that complete all waves of the panel. Unfortunately, the panel data alone cannot inform the extent of the bias due to attrition, so analysts must make strong and untestable assumptions about the missing data mechanism. Many panel studies also include refreshment samples, which are data collected from a random sample of new

individuals during some later wave of the panel. Refreshment samples offer information that can be utilized to correct for biases induced by nonignorable attrition while reducing reliance on strong assumptions about the attrition process. To date, these bias correction methods have not dealt with two key practical issues in panel studies: unit nonresponse in the initial wave of the panel and in the

refreshment sample itself. As we illustrate, nonignorable unit nonresponse

can significantly compromise the analyst's ability to use the refreshment samples for attrition bias correction. Thus, it is crucial for analysts to assess how sensitive their inferences---corrected for panel attrition---are to different assumptions about the nature of the unit nonresponse. We present an approach that facilitates such sensitivity analyses, both for suspected nonignorable unit nonresponse

in the initial wave and in the refreshment sample. We illustrate the approach using simulation studies and an analysis of data from the 2007-2008 Associated Press/Yahoo News election panel study.

The second method incorporates informative prior beliefs about

marginal probabilities into Bayesian latent class models for categorical data.

The basic idea is to append synthetic observations to the original data such that

(i) the empirical distributions of the desired margins match those of the prior beliefs, and (ii) the values of the remaining variables are left missing. The degree of prior uncertainty is controlled by the number of augmented records. Posterior inferences can be obtained via typical MCMC algorithms for latent class models, tailored to deal efficiently with the missing values in the concatenated data.

We illustrate the approach using a variety of simulations based on data from the American Community Survey, including an example of how augmented records can be used to fit latent class models to data from stratified samples.

The third method leverages the information from a gold standard survey to model reporting error. Survey data are subject to reporting error when respondents misunderstand the question or accidentally select the wrong response. Sometimes survey respondents knowingly select the wrong response, for example, by reporting a higher level of education than they actually have attained. We present an approach that allows an analyst to model reporting error by incorporating information from a gold standard survey. The analyst can specify various reporting error models and assess how sensitive their conclusions are to different assumptions about the reporting error process. We illustrate the approach using simulations based on data from the 1993 National Survey of College Graduates. We use the method to impute error-corrected educational attainments in the 2010 American Community Survey using the 2010 National Survey of College Graduates as the gold standard survey.

'Lines of flight': digital musical instruments, inclusive music bands, meaningful engagement in music-making and learning

In this study I examine the development of three inclusive music bands in Cork city. Derived from Jellison’s research on inclusive music education, inclusive music bands involve students with disabilities coming together with typically developing peers to make and learn music that is meaningful (Jellison, 2012). As part of this study, I established three inclusive music bands to address the lack of inclusive music making and learning experiences in Cork city. Each of these bands evolved and adapted in order to be socio-culturally relevant within formal and informal settings: Circles (community education band), Till 4 (secondary school band) and Mish Mash (third level and community band). I integrated Digital Musical Instruments into the three bands, in order to ensure access to music making and learning for band members with profound physical disabilities. Digital Musical Instruments are electronic music devices that facilitate active music making with minimal movement. This is the first study in Ireland to examine the experiences of inclusive music making and learning using Digital Musical Instruments. I propose that the integration of Digital Musical Instruments into inclusive music bands has the potential to further the equality and social justice agenda in music education in Ireland. In this study, I employed qualitative research methodology, incorporating participatory action research methodology and case study design. In this thesis I reveal the experiences of being involved in an inclusive music band in Cork city. I particularly focus on examining whether the use of this technology enhances meaningful music making and learning experiences for members with disabilities within inclusive environments. To both inform and understand the person centered and adaptable nature of these inclusive bands, I draw theoretical insights from Sen’s Capabilities Approach and Deleuze and Guatarri’s Rhizome Theory. Supported by descriptive narrative from research participants and an indepth examination of literature, I discover the optimum conditions and associated challenges of inclusive music practice in Cork city.

Evaluating the Business Impact of Social Science: a report to the ESRC

This report presents the main findings from a project entitled ‘Evaluating the Business Impact of Social Science', commissioned by the Economic and Social Research Council (ESRC) and undertaken by a team of researchers from the University of Hull. In brief, the project involved an examination of the processes through which social science research and related activities impact upon business (defined broadly to incorporate large and small private sector businesses as well as social enterprises, but excluding public sector organisations) in relation to three of the UK’s leading business/management schools that have received significant amounts of ESRC funding in recent years: Cardiff Business School, Lancaster University Management School, and Warwick Business School

‘Never Let Me Down Again’1: Loyal customer attitudes towards ticket distribution channels for live music events: a netnographic exploration of the US leg of the Depeche Mode 2005–2006 World Tour

Ticket distribution channels for live music events have been revolutionised through the increased take-up of internet technologies, and the music supply-chain has evolved into a multi-channel value network. The assumption that this creates increased consumer autonomy and improved service quality is explored here through a case-study of the ticket pre-sale for the US leg of the Depeche Mode 2005–06 World Tour, which utilises an innovative virtual channel strategy, promoted as a service to loyal fans. A multi-method analysis, adopting Kozinets' (2002) Kozinets, R. V. 2002. The field behind the screen: using netnography for marketing research in online communities. Journal of Marketing Research, 39: 61–72. [CrossRef], [Web of Science ®] netnography methodology, is employed to map responses of the band's serious fan base on an internet message board (IMB) throughout the tour pre-sale. The analysis focuses on concerns of pricing, ethics, scope of the offer, use of technology, service quality and perceived brand performance fit of channel partners. Findings indicate that fans behaviour is unpredictable in response to channel partners' performance, and that such offers need careful management to avoid alienation of loyal consumers.

La Representación del Museo: Reflexionando sobre la Museología Reflexiva

En este artículo se analizan las definiciones aceptadas para el campo científico de la museología concebidas por los teóricos del ICOFOM que primero cuestionaron al “museo” como paradigma. Pretende señalar algunas de las inconsistencias en la museología filosófica strankiana con el fin de reformular el concepto de su objeto de estudio. Este debate requerirá una revisión de dicha perspectiva filosófica a través del punto de vista sociológico, a la luz de la teoría del actor-difusor de la red propuesta por Bruno Latour. Finalmente, el artículo sostiene que la relación hombre-realidad forjada en Occidente como una actuación del museo hegemónico no debería definir el objeto de estudio de la museología. Por el contrario, debería tener en cuenta todo tipo de posibles asociaciones entre las diferentes funciones que se realizan, evolucionando desde un corpus de reflexiones sobre el museo hacia una disciplina museológica reflexiva.