Search results

Inclusion of members of the target population in research is an increasing priority in the social sciences; however, relatively few studies employ approaches that involve persons with lived experience of the mental health system in mental health services research, particularly in the USA. The purpose of this paper is to describe one such approach, the employment of peer interviewers in the evaluation of a peer respite program.

The paper describes how peer interviewers were recruited, hired, trained, and supervised. The authors discuss some benefits and challenges associated with the approach.

Peer interviewer benefits and challenges: the shared lived experience between the peer interviewers and study participants contributed to increased comfort and a high response rate overall. The study opened up professional opportunities for peers, but inconsistent work hours were a challenge and resulted in turnover and difficulty filling vacant positions. The lead evaluator and supervisors worked closely with peer interviewers to ensure conflict of interest was mitigated to reduce bias.

This paper adds to the limited literature describing peer representation in research, outlining one avenue for partnering with peers to align research with the values of the intervention under study without compromising – and perhaps increasing – scientific rigor. The authors expect that even more peer involvement in the oversight, analysis, and interpretation of results would have improved the overall quality of the evaluation. Future efforts should build upon and incorporate the approach alongside more comprehensive efforts to partner with service users.

In the past decade, scholars across social sciences shifted their attention towards creative and dynamic research methods. Despite the growing popularity of LEGO^® Serious Play^® method across social sciences, few studies applied the method in tourism and hospitality research. This method represents a powerful tool which uses a toy to solve problems, explore ideas and achieve objectives in business, research and community work. This paper aims to provide insights into qualitative multi-method approach incorporating LEGO^® Serious Play^® to gain a deeper understanding of hosts-guest experiences in volunteer tourism exchange programme.

The empirical material mentioned in the paper is based on an interpretive study investigating hosts-guest experiences on organic farms. The study used a multi-method approach, and the data were collected through unstructured interviews, observation, reflexive notes and LEGO^® Serious Play^® workshops with 32 participants in total.

The paper highlights the benefits and limitations of the qualitative multi-method study, specifically focusing on LEGO^® Serious Play^® as a novel approach for tourism and hospitality research.

This study contributes to making the current body of knowledge on qualitative multi-method methodologies and creative visual methodologies in the field of tourism and hospitality. As such, the paper provides an overview of the LEGO^® Serious Play^® method. Specifically, this exploratory paper brings attention to how and to what end existing LEGO^® Serious Play^® has been modified and adopted in this multi-method study. Furthermore, the paper highlights the future use to benefit the tourism and hospitality academics and industry professionals.

The purpose of this study is to introduce the reproducing kernel algorithm for treating classes of time-fractional partial differential equations subject to Robin boundary conditions with parameters derivative arising in fluid flows, fluid dynamics, groundwater hydrology, conservation of energy, heat conduction and electric circuit.

The method provides appropriate representation of the solutions in convergent series formula with accurately computable components. This representation is given in the W(Ω) and H(Ω) inner product spaces, while the computation of the required grid points relies on the R_(y,s) (x, t) and r_(y,s) (x, t) reproducing kernel functions.

Numerical simulation with different order derivatives degree is done including linear and nonlinear terms that are acquired by interrupting the n-term of the exact solutions. Computational results showed that the proposed algorithm is competitive in terms of the quality of the solutions found and is very valid for solving such time-fractional models.

Future work includes the application of the reproducing kernel algorithm to highly nonlinear time-fractional partial differential equations such as those arising in single and multiphase flows. The results will be published in forthcoming papers.

The study included a description of fundamental reproducing kernel algorithm and the concepts of convergence, and error behavior for the reproducing kernel algorithm solvers. Results obtained by the proposed algorithm are found to outperform in terms of accuracy, generality and applicability.

Developing analytical and numerical methods for the solutions of time-fractional partial differential equations is a very important task owing to their practical interest.

This study, for the first time, presents reproducing kernel algorithm for obtaining the numerical solutions of some certain classes of Robin time-fractional partial differential equations. An efficient construction is provided to obtain the numerical solutions for the equations, along with an existence proof of the exact solutions based upon the reproducing kernel theory.

Since the development of the COVID-19 vaccinations, questions surrounding race have been prominent in the literature on vaccine uptake. Early in the vaccine rollout, public health officials were concerned with the relatively lower rates of uptake among certain racial/ethnic minority groups. We suggest that this may also be patterned by racial/ethnic residential segregation, which previous work has demonstrated to be an important factor for both health and access to health care.

In this study, we examine county-level vaccination rates, racial/ethnic composition, and residential segregation across the U.S. We compile data from several sources, including the American Community Survey (ACS) and Centers for Disease Control (CDC) measured at the county level.

We find that just looking at the associations between racial/ethnic composition and vaccination rates, both percent Black and percent White are significant and negative, meaning that higher percentages of these groups in a county are associated with lower vaccination rates, whereas the opposite is the case for percent Latino. When we factor in segregation, as measured by the index of dissimilarity, the patterns change somewhat. Dissimilarity itself was not significant in the models across all groups, but when interacted with race/ethnic composition, it moderates the association. For both percent Black and percent White, the interaction with the Black-White dissimilarity index is significant and negative, meaning that it deepens the negative association between composition and the vaccination rate.

The analysis is only limited to county-level measures of racial/ethnic composition and vaccination rates, so we are unable to see at the individual-level who is getting vaccinated.

We find that segregation moderates the association between racial/ethnic composition and vaccination rates, suggesting that local race relations in a county helps contextualize the compositional effects of race/ethnicity.