Development and validation of an instrument to predict online student success using faculty perceptions

Distance learning is growing and transforming educational institutions. The increasing use of distance learning by higher education institutions and particularly community colleges coupled with the higher level of student attrition in online courses than in traditional classrooms suggests that increased attention should be paid to factors that affect online student course completion. The purpose of the study was to develop and validate an instrument to predict community college online student course completion based on faculty perceptions, yielding a prediction model of online course completion rates. Social Presence and Media Richness theories were used to develop a theoretically-driven measure of online course completion. This research study involved surveying 311 community college faculty who taught at least one online course in the past 2 years. Email addresses of participating faculty were provided by two south Florida community colleges. Each participant was contacted through email, and a link to an Internet survey was given. The survey response rate was 63% (192 out of 303 available questionnaires). Data were analyzed through factor analysis, alpha reliability, and multiple regression. The exploratory factor analysis using principal component analysis with varimax rotation yielded a four-factor solution that accounted for 48.8% of the variance. Consistent with Social Presence theory, the factors with their percent of variance in parentheses were: immediacy (21.2%), technological immediacy (11.0%), online communication and interactivity (10.3%), and intimacy (6.3%). Internal consistency of the four factors was calculated using Cronbach's alpha (1951) with reliability coefficients ranging between .680 and .828. Multiple regression analysis yielded a model that significantly predicted 11% of the variance of the dependent variable, the percentage of student who completed the online course. As indicated in the literature (Johnson & Keil, 2002; Newberry, 2002), Media Richness theory appears to be closely related to Social Presence theory. However, elements from this theory did not emerge in the factor analysis.

Long-Term Effects of Adding Nutrients to an Oligotrophic Coastal Environment

Management of ecological disturbances requires an understanding of the time scale and dynamics of community responses to disturbance events. To characterize long-term seagrass bed responses to nutrient enrichment, we established six study sites in Florida Bay, USA. In 24 plots (0.25 m2) at each site, we regularly added nitrogen (N) and phosphorus (P) in a factorial design for 7 years. Five of the six sites exhibited strong P limitation. Over the first 2 years, P enrichment increased Thalassia testudinum cover in the three most P-limited sites. After 3 years, Halodule wrightii began to colonize many of the P-addition plots, but the degree of colonization was variable among sites, possibly due to differences in the supply of viable propagules. Thalassia increased its allocation to aboveground tissue in response to P enrichment; Halodule increased in total biomass but did not appear to change its aboveground: belowground tissue allocation. Nutrient enrichment did not cause macroalgal or epiphytic overgrowth of the seagrass. Nitrogen retention in the study plots was variable but relatively low, whereas phosphorus retention was very high, often exceeding 100% of the P added as fertilizer over the course of our experiments. Phosphorus retentions exceeding 100% may have been facilitated by increases in Thalassia aboveground biomass, which promoted the settlement of suspended particulate matter containing phosphorus. Our study demonstrated that lowintensity press disturbance events such as phosphorus enrichment can initiate a slow, ramped successional process that may alter community structure over many years.

The effect of reciprocal mapping on high-risk sixth-grade students' social studies achievement

Reading deficits in students in Grades 4 to 12 are evident in American schools. Informational text is particularly difficult for students. This quasi-experimental study (N=138) investigated sixth-grade students' achievement in social studies using the Reciprocal Mapping instructional routine, compared to sixth-grade students' achievement taught with a traditional approach. The Reciprocal Mapping instructional routine incorporated explicit instruction in text structure using graphic organizers. Students created their own graphic organizers and used them to write about social studies content. The comparison group used a traditional approach, students' reading the textbook and answering questions. Students for this study included sixth-graders in the seven sixth-grade classrooms in two public schools in a small, rural south Florida school district. A focus of this study was to determine the helpfulness of the intervention for at-risk readers. To determine students considered to be at-risk, the researcher used data from the reading portion of the Florida Comprehensive Assessment Test (FCAT), 2011-2012, that considers Level 1 and 2 as at-risk readers. The quasi-experimental study used a pretest-posttest control group design, with students assigned to treatment groups by class. Two teachers at the two rural sites were trained on the Reciprocal Mapping instructional routine and taught students in both the experimental and control groups for an equivalent amount of time over a 5-week period. Results of the 3 x 2 factorial ANCOVA found a significant positive difference favoring the experimental group's social studies achievement as compared to that of the comparison group as measured by the pre/post unit test from the social studies series (McGraw-Hill, 2013), when controlling for initial differences in students' reading FCAT scores. Interactions for high-risk struggling readers were investigated using the significance level p < .05. Due to no significant interaction the main effects of treatment were interpreted. The pretest was used as a covariate and the multivariate analysis was found to be significant. Therefore, analysis of covariance was run on each of the dependent variable as a follow-up. Reciprocal Mapping was found to be significant in posttest scores, independent of gender and level of risk, and while holding the pretest scores constant. Findings showed there was a significant difference in the performance of the high-risk reading students taught with the Reciprocal Mapping intervention who scored statistically better than students in the control group. Further study findings showed that teacher fidelity of implementation of the treatment had a statistically significant relationship in predicting posttest scores when controlling for pretest scores. Study results indicated that improving students' use of text structure through the Reciprocal Mapping instructional routine positively supported sixth-grade students' social studies achievement.

Acculturation and Hispanic identity/ethnicity as a predictor of change on the brief situational confidence questionnaire

The purpose of this study was to investigate whether level of acculturation among Hispanic adolescent males (n = 174) influenced treatment outcome in a substance abuse program, specifically on the Brief Situational Confidence Questionnaire (BSCQ) which measures relapse confidence. It was hypothesized that lower levels of acculturation were likely to be predictive of positive change, whereas higher levels of acculturation were likely to be predictive of no change or negative change. It was found that adolescents changed over time in BSCQ scores regardless of which acculturation variable was measured. Contrary to expectations, for those adolescents placed in family treatment, place of birth was not significantly associated with treatment response. However, both, U.S. and non-U.S. born adolescents demonstrated a change over time when receiving family treatment, suggesting that the family substance abuse treatment utilized in this intervention effected change over time.

Predictors of Independent Living Outcomes Among Older Women Receiving Informal Care

This study examined the predictors of independent living outcomes among community–living older women who received informal care. The central hypothesis was that older women’s level of functioning is influenced by their relationship with their informal caregiver. The study attempted to understand the independence of older women through the perspective of both informal caregivers and the older women themselves. The following eight variables were measured: 1) the older women’s independence (dependent variable); 2) the relationship between older women and their informal caregivers (independent variable); 3) roles of both the informal caregiver and older women (independent variable); 4) the older women’s attitudes toward aging (independent variable); 5) the older women’s age identity (independent variable); 6) the older women’s health (control variable); 7) the older women’s level of social support (control variable); and 8) the older women’s level of depression (control variable). The variables were measured from the perspective of the older woman herself and her informal caregiver. This study used an ecological and developmental framework along with role theory to understand the interaction among the aforementioned variables through a cross-sectional design. The recruited older women participants of this study were receiving ongoing care and personal assistance from two large home care agencies located in Miami, FL. An analysis was conducted through a mixed-methods incorporated into the study design. The present study aimed to contribute to the understanding of how the relationship between older women and their informal caregivers influences older women’s ability to maintain independent outcomes. The primary finding of this study was that there were both positive and negative experiences within the relationship dynamic of older women and their informal caregivers and that this relationship was either unidirectional or bi-directional.

Physical, Geochemical, Geomechanical, Geophysical and Hydrodynamic Characterization and Anisotropy Assessment of Corvio Sandstone

Corvio sandstone is a ~20 m thick unit (Corvio Formation) that appears in the top section of the Frontada Formation (Campoó Group; Lower Cretaceous) located in Northern Spain in the southern margin of the Basque-Cantabrian Basin. Up to 228 plugs were cored from four 0.3 x 0.2 x 0.5 m blocks of Corvio sandstone, to perform a comprehensive characterization of the physical, mineralogical, geomechanical, geophysical and hydrodynamic properties of this geological formation, and the anisotropic assessment of the most relevant parameters. Here we present the first data set obtained on 53 plugs which covers (i) basic physical and chemical properties including density, porosity, specific surface area and elementary analysis (XRF - CHNS); (ii) the curves obtained during unconfined and confined strengths tests, the tensile strengths, the calculated static elastic moduli and the characteristic stress levels describing the brittle behaviour of the rock; (iii) P- and S-wave velocities (and dynamic elastic moduli) and their respective attenuation factors Qp and Qs, electrical resistivity for a wide range of confining stress; and (iv) permeability and transport tracer tests. Furthermore, the geophysical, permeability and transport tests were additionally performed along the three main orthogonal directions of the original blocks, in order to complete a preliminary anisotropic assessment of the Corvio sandstone.

Roles of CTCF and YY1 in T Cell Receptor Gene Rearrangement And T Cell Development

Diversity of T cell receptors (TCR) and immunoglobulins (Ig) is generated by V(D)J recombination of antigen receptor (AgR) loci. The Tcra-Tcrd locus is of particular interest because it displays a nested organization of Tcrd and Tcra gene segments and V(D)J recombination follows an intricate developmental program to assemble both TCRδ and TCRα repertoires. However, the mechanisms that dictate the developmental regulation of V(D)J recombination of the Tcra-Tcrd locus remain unclear.

We have previously shown that CCCTC-binding factor (CTCF) regulates Tcra gene transcription and rearrangement through organizing chromatin looping between CTCF- binding elements (CBEs). This study is one of many showing that CTCF functions as a chromatin organizer and transcriptional regulator genome-wide. However, detailed understanding of the impact of specific CBEs is needed to fully comprehend the biological function of CTCF and how CTCF influences the generation of the TCR repertoire during thymocyte development. Thus, we generated several mouse models with genetically modified CBEs to gain insight into the CTCF-dependent regulation of the Tcra-Tcrd locus. We revealed a CTCF-dependent chromatin interaction network at the Tcra-Tcrd locus in double-negative thymocytes. Disruption of a discrete chromatin loop encompassing Dδ, Jδ and Cδ gene segments allowed a single Vδ segment to frequently contact and rearrange to diversity and joining gene segments and dominate the adult TCRδ repertoire. Disruption of this loop also narrowed the TCRα repertoire, which, we believe, followed as a consequence of the restricted TCRδ repertoire. Hence, a single CTCF-mediated chromatin loop directly regulates TCRδ diversity and indirectly regulates TCRα diversity. In addition, we showed that insertion of an ectopic CBE can modify chromatin interactions and disrupt the rearrangement of particular Vδ gene segments. Finally, we investigated the role of YY1 in early T cell development by conditionally deleting YY1 in developing thymocytes. We found that early ablation of YY1 caused severe developmental defects in the DN compartment due to a dramatic increase in DN thymocyte apoptosis. Furthermore, late ablation of YY1 resulted in increased apoptosis of DP thymocytes and a restricted TCRα repertoire. Mechanistically, we showed that p53 was upregulated in both DN and DP YY1-deficient thymocytes. Eliminating p53 in YY1-deficient thymocytes rescued the survival and developmental defects, indicating that these YY1-dependent defects were p53-mediated. We conclude that YY1 is required to maintain cell viability during thymocyte development by thwarting the accumulation of p53.

Overall, this thesis work has shown that CTCF-dependent looping provides a central framework for lineage- and developmental stage-specific regulation of Tcra-Tcrd gene expression and rearrangements. In addition, we identified YY1 as a novel regulator of thymocyte viability.

Essays on Microeconometrics

My dissertation has three chapters which develop and apply microeconometric tech- niques to empirically relevant problems. All the chapters examines the robustness issues (e.g., measurement error and model misspecification) in the econometric anal- ysis. The first chapter studies the identifying power of an instrumental variable in the nonparametric heterogeneous treatment effect framework when a binary treat- ment variable is mismeasured and endogenous. I characterize the sharp identified set for the local average treatment effect under the following two assumptions: (1) the exclusion restriction of an instrument and (2) deterministic monotonicity of the true treatment variable in the instrument. The identification strategy allows for general measurement error. Notably, (i) the measurement error is nonclassical, (ii) it can be endogenous, and (iii) no assumptions are imposed on the marginal distribution of the measurement error, so that I do not need to assume the accuracy of the measure- ment. Based on the partial identification result, I provide a consistent confidence interval for the local average treatment effect with uniformly valid size control. I also show that the identification strategy can incorporate repeated measurements to narrow the identified set, even if the repeated measurements themselves are endoge- nous. Using the the National Longitudinal Study of the High School Class of 1972, I demonstrate that my new methodology can produce nontrivial bounds for the return to college attendance when attendance is mismeasured and endogenous.

The second chapter, which is a part of a coauthored project with Federico Bugni, considers the problem of inference in dynamic discrete choice problems when the structural model is locally misspecified. We consider two popular classes of estimators for dynamic discrete choice models: K-step maximum likelihood estimators (K-ML) and K-step minimum distance estimators (K-MD), where K denotes the number of policy iterations employed in the estimation problem. These estimator classes include popular estimators such as Rust (1987)’s nested fixed point estimator, Hotz and Miller (1993)’s conditional choice probability estimator, Aguirregabiria and Mira (2002)’s nested algorithm estimator, and Pesendorfer and Schmidt-Dengler (2008)’s least squares estimator. We derive and compare the asymptotic distributions of K- ML and K-MD estimators when the model is arbitrarily locally misspecified and we obtain three main results. In the absence of misspecification, Aguirregabiria and Mira (2002) show that all K-ML estimators are asymptotically equivalent regardless of the choice of K. Our first result shows that this finding extends to a locally misspecified model, regardless of the degree of local misspecification. As a second result, we show that an analogous result holds for all K-MD estimators, i.e., all K- MD estimator are asymptotically equivalent regardless of the choice of K. Our third and final result is to compare K-MD and K-ML estimators in terms of asymptotic mean squared error. Under local misspecification, the optimally weighted K-MD estimator depends on the unknown asymptotic bias and is no longer feasible. In turn, feasible K-MD estimators could have an asymptotic mean squared error that is higher or lower than that of the K-ML estimators. To demonstrate the relevance of our asymptotic analysis, we illustrate our findings using in a simulation exercise based on a misspecified version of Rust (1987) bus engine problem.

The last chapter investigates the causal effect of the Omnibus Budget Reconcil- iation Act of 1993, which caused the biggest change to the EITC in its history, on unemployment and labor force participation among single mothers. Unemployment and labor force participation are difficult to define for a few reasons, for example, be- cause of marginally attached workers. Instead of searching for the unique definition for each of these two concepts, this chapter bounds unemployment and labor force participation by observable variables and, as a result, considers various competing definitions of these two concepts simultaneously. This bounding strategy leads to partial identification of the treatment effect. The inference results depend on the construction of the bounds, but they imply positive effect on labor force participa- tion and negligible effect on unemployment. The results imply that the difference- in-difference result based on the BLS definition of unemployment can be misleading

due to misclassification of unemployment.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Valuation of Ecosystem Services for Environmental Decision Making in South Florida

The Greater Everglades system imparts vital ecosystem services (ES) to South Florida residents including high quality drinking water supplies and a habitat for threatened and endangered species. As a result of the altered Everglades system and regional dynamics, restoration may either improve the provision of these services or impose a tradeoff between enhanced environmental goods and services and competing societal demands. The current study aims at understanding public preferences for restoration and generating willingness to pay (WTP) values for restored ES through the implementation of a discrete choice experiment. A previous study (Milon et al., 1999) generated WTP values amongst Floridians of up to $3.42 -$4.07 billion for full restoration over a 10-year period. We have collected data from 2,905 respondents taken from two samples who participated in an online survey designed to elicit the WTP values for selected ecological and social attributes included in the earlier study (Milon et al. 1999). We estimate that the Florida general public is willing to pay up to $854.1- $954.1 million over 10 years to avoid restrictions on their water usage and up to $90.8- $183.7 million over 10 years to restore the hydrological flow within the Water Conservation Area.

The Validity of Broad and Narrow Personality Traits For Predicting Job Performance: The Differential Effects of Time

Research into the dynamicity of job performance criteria has found evidence suggesting the presence of rank-order changes to job performance scores across time as well as intraindividual trajectories in job performance scores across time. These findings have influenced a large body of research into (a) the dynamicity of validities of individual differences predictors of job performance and (b) the relationship between individual differences predictors of job performance and intraindividual trajectories of job performance. In the present dissertation, I addressed these issues within the context of the Five Factor Model of personality. The Five Factor Model is arranged hierarchically, with five broad higher-order factors subsuming a number of more narrowly tailored personality facets. Research has debated the relative merits of broad versus narrow traits for predicting job performance, but the entire body of research has addressed the issue from a static perspective -- by examining the relative magnitude of validities of global factors versus their facets. While research along these lines has been enlightening, theoretical perspectives suggest that the validities of global factors versus their facets may differ in their stability across time. Thus, research is needed to not only compare the relative magnitude of validities of global factors versus their facets at a single point in time, but also to compare the relative stability of validities of global factors versus their facets across time. Also necessary to advance cumulative knowledge concerning intraindividual performance trajectories is research into broad vs. narrow traits for predicting such trajectories. In the present dissertation, I addressed these issues using a four-year longitudinal design. The results indicated that the validities of global conscientiousness were stable across time, while the validities of conscientiousness facets were more likely to fluctuate. However, the validities of emotional stability and extraversion facets were no more likely to fluctuate across time than those of the factors. Finally, while some personality factors and facets predicted performance intercepts (i.e., performance at the first measurement occasion), my results failed to indicate a significant effect of any personality variable on performance growth. Implications for research and practice are discussed.

(Table 1) Radiocarbon ages of foraminifera from a Piston and a Trigger Weight from Ceara Rise

Radiocarbon-age measurements on single species of foraminifera from a core on the Ceara Rise demonstrate the importance of the joint effect of bioturbation and variable rain abundance of foraminifera. The relatively high mixed layer ages for Pulleniatina obliquiloculata reflect, at least in part, an early Holocene peak in its abundance while the relatively young ages for Globorotalia menardii reflect the delay until mid Holocene of its reappearance in the Atlantic Ocean. These results clearly demonstrate that core-top sediment samples need not be representative foraminifera falling from today's surface ocean. Rather, at least on the Ceara Rise, such samples consist of a composite of changing species groupings. These results also reconfirm the pitfalls associated with attempts to reconstruct the radiocarbon age of deep ocean water on the basis of benthic-planktonic foraminiferal age differences.

Effects of retirement on cognitive function: A gender and international perspecive

Background: As the global population is ageing, studying cognitive impairments including dementia, one of the leading causes of disability in old age worldwide, is of fundamental importance to public health. As a major transition in older age, a focus on the complex impacts of the duration, timing, and voluntariness of retirement on health is important for policy changes in the future. Longer retirement periods, as well as leaving the workforce early, have been associated with poorer health, including reduced cognitive functioning. These associations are hypothesized to differ based on gender, as well as on pre-retirement educational and occupational experiences, and on post-retirement social factors and health conditions. Methods: A cross-sectional study is conducted to determine the relationship between duration and timing of retirement and cognitive function, using data from the five sites of International Mobility in Aging Study (IMIAS). Cognitive function is assessed using the Leganes Cognitive Test (LCT) scores in 2012. Data are analyzed using multiple linear regressions. Analyses are also done by site/region separately (Canada, Latin America, and Albania). Robustness checks are done with an analysis of cognitive change from 2012 to 2014, the effect of voluntariness of retirement on cognitive function. An instrumental variable (IV) approach is also applied to the cross-sectional and longitudinal analyses as a robustness check to address the potential endogeneity of the retirement variable. Results: Descriptive statistics highlight differences between men and women, as well as between sites. In linear regression analysis, there was no relationship between timing or duration of retirement and cognitive function in 2012, when adjusting for site/region. There was no association between retirement characteristics and cognitive function in site/region/stratified analyses. In IV analysis, longer retirement and on time or late retirement was associated with lower cognitive function among men. In IV analysis, there is no relationship between retirement characteristics and cognitive function among women. Conclusions: While results of the thesis suggest a negative effect of retirement on cognitive function, especially among men, the relationship remains uncertain. A lack of power results in the inability to draw conclusions for site/region-specific analysis and site-adjusted analysis in both linear and IV regressions.

Degeneracy of velocity constraints in rigid body systems

The equations governing the dynamics of rigid body systems with velocity constraints are singular at degenerate configurations in the constraint distribution. In this report, we describe the causes of singularities in the constraint distribution of interconnected rigid body systems with smooth configuration manifolds. A convention of defining primary velocity constraints in terms of orthogonal complements of one-dimensional subspaces is introduced. Using this convention, linear maps are defined and used to describe the space of allowable velocities of a rigid body. Through the definition of these maps, we present a condition for non-degeneracy of velocity constraints in terms of the one dimensional subspaces defining the primary velocity constraints. A method for defining the constraint subspace and distribution in terms of linear maps is presented. Using these maps, the constraint distribution is shown to be singular at configuration where there is an increase in its dimension.

Effectiveness and cost-effectiveness of a physical activity loyalty scheme for behaviour change maintenance: a cluster randomised controlled trial

Background
Increasing physical activity in the workplace can provide employee physical and mental health benefits, and employer economic benefits through reduced absenteeism and increased productivity. The workplace is an opportune setting to encourage habitual activity. However, there is limited evidence on effective behaviour change interventions that lead to maintained physical activity. This study aims to address this gap and help build the necessary evidence base for effective, and cost-effective, workplace interventions

Methods/design
This cluster randomised control trial will recruit 776 office-based employees from public sector organisations in Belfast and Lisburn city centres, Northern Ireland. Participants will be randomly allocated by cluster to either the Intervention Group or Control Group (waiting list control). The 6-month intervention consists of rewards (retail vouchers, based on similar principles to high street loyalty cards), feedback and other evidence-based behaviour change techniques. Sensors situated in the vicinity of participating workplaces will promote and monitor minutes of physical activity undertaken by participants. Both groups will complete all outcome measures. The primary outcome is steps per day recorded using a pedometer (Yamax Digiwalker CW-701) for 7 consecutive days at baseline, 6, 12 and 18 months. Secondary outcomes include health, mental wellbeing, quality of life, work absenteeism and presenteeism, and use of healthcare resources. Process measures will assess intervention “dose”, website usage, and intervention fidelity. An economic evaluation will be conducted from the National Health Service, employer and retailer perspective using both a cost-utility and cost-effectiveness framework. The inclusion of a discrete choice experiment will further generate values for a cost-benefit analysis. Participant focus groups will explore who the intervention worked for and why, and interviews with retailers will elucidate their views on the sustainability of a public health focused loyalty card scheme.

Discussion
The study is designed to maximise the potential for roll-out in similar settings, by engaging the public sector and business community in designing and delivering the intervention. We have developed a sustainable business model using a ‘points’ based loyalty platform, whereby local businesses ‘sponsor’ the incentive (retail vouchers) in return for increased footfall to their business.