Multilevel Modeling and Policy Development: Guidelines and Applications to Medical Travel

García-Garzón, Eduardo; Zhukovsky, Peter; Haller, Elisa; Plakolm, Sara; Fink, David C.; Petrova, Dafina; Mahalingam, Vaishali; Menezes, Igor Gomes; Ruggeri, Kai

doi:10.3389/fpsyg.2016.00752

Cited by 4 publications

(6 citation statements)

References 47 publications

(61 reference statements)

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“…Considering the evidence available in light of the patterns of behavior as well as challenges presented, a multi-year study covering multiple key aspects of medical travel was carried out by a large team of researchers from a number of countries (predominantly from Europe and North America) [1,9,10,11,12,14,16,17]. The largest of these studies involved a sophisticated decision-making instrument for assessing likelihood of travel that would have the potential to inform policy through validating the strongest predictions of behavior.…”

Section: Factors Influencing Medical Travel Decisionsmentioning

confidence: 99%

“…These methods, known as stated preferences, act as reliable proxies for inferring future real behavior [20,21]. We used a binary discrete choice experiment to capture patients' stated preferences for medical travel [16].…”

Section: Instrumentmentioning

confidence: 99%

“…Further justification for the use of such models can be found in the literature [16]. For multilevel logistic regression models, coefficients are relative measures of effect, known as odds ratio.…”

Section: Statistical Frameworkmentioning

confidence: 99%

“…For the second level of the model, observations were clustered around the country of destination. Variable coding and a rationale for the selection of the reference categories can be found in a previous publication [16]. In this case, multilevel modelling corrected the effect of each set of questions being encompassed by a single country, where responses given to the same country of destination were expected to be clustered.…”

Section: Statistical Frameworkmentioning

confidence: 99%

“…Countries were ranked according to the probability that they were chosen as medical travel destinations ( Table 2) Table 2 reflect estimated percentages based on all responses, weighted by factors for each scenario in consideration of previous responses from individuals (see [16]). The values indicate the likelihood of choosing travel in a specific scenario after controlling for procedure, reason and the other socio-demographic variables, and not the total number of prospective medical travelers who would be willing to receive care in a given country.…”

Section: Geographical Effects On Medical Travelmentioning

confidence: 99%

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An evidence-based policy for improving choice in global health access through medical travel

et al. 2018

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Global medical travel has had an increasing trend without a comprehensive, evidence-driven policy to ensure safe and effective practice. To identify key factors that influence medical travel, a series of studies culminating with a preference and decision-making component of over 500 prospective medical travelers from a number of countries. Results indicated that quality of care was the most critical factor in the decision, followed by lower costs of procedure and shorter waiting times. Lower costs were less of a factor if the procedure was more invasive, which also increased the importance of waiting time in the decision. The most desired destinations for care were in Europe (United Kingdom, Germany) and North America (United States). Building on these insights and previous literature, we present a model that for implementing applications from these factors and additional insights generated across the series of studies toward an effective policy framework.

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Section: Factors Influencing Medical Travel Decisionsmentioning

confidence: 99%

Section: Instrumentmentioning

confidence: 99%

Section: Statistical Frameworkmentioning

confidence: 99%

Section: Statistical Frameworkmentioning

confidence: 99%

Section: Geographical Effects On Medical Travelmentioning

confidence: 99%

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An evidence-based policy for improving choice in global health access through medical travel

et al. 2018

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Application of Hierarchical/Multilevel Models and Quality of Reporting (2010–2020): A Systematic Review

Asampana Asosega,

Adebanji,

Aidoo

et al. 2024

The Scientific World Journal

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Introduction. Multilevel models have gained immense popularity across almost every discipline due to the presence of hierarchy in most data and phenomena. In this paper, we present a systematic review on the adoption and application of multilevel models and the important information reported on the results generated from the use of these models. Methods. The review was performed by searching Google Scholar for original research articles on the application of multilevel models published between 2010 and 2020. The search strategy involved topics such as “multilevel models,” “hierarchical linear models,” and “mixed models with hierarchy.” The search placed more emphasis on the application of hierarchical models in any discipline but excluded software methodological development and related articles. Results. A total of 121 articles were initially obtained from the search results. However, 65 articles met the inclusion criteria for the review. Out of the 65 articles reviewed, 46.2% were related to health/epidemiology, 15.4% to education and psychology, and 16.9% to social life. The majority of the articles (78.5%) were two-level models, and most of these studies modelled univariate responses. However, the few that modelled more than one response modelled them separately. Moreover, 83.1% were cross-sectional design, and 9.2% and 6.2% were longitudinal and repeated measures, respectively. Moreover, a little over half (55.4%) of articles reported on the intraclass correlation measure, and all articles indicated the response variable distribution where most (47.7%) were normally distributed. Only 58.5% of articles reported on the estimation methods used as Bayesian (20%) and MLE (18.5%). Again, model validation measures and statistical software were reported in 70.8% and 90.8% articles, respectively. Conclusion. There is an increase in the utilization of multilevel modelling in the last decade, which could be attributed to the presence of clustered and hierarchically correlated data structures. There is a need for improvement in the area of measurement and reporting on the intraclass correlation, parameter estimation, and variable selection measures to further improve the quality of the application of multilevel models. The integration of spatial effects into multilevel models is very limited and needs to be explored in the future.

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Health and Wellness–Related Travel: A Scoping Study of the Literature in 2010-2018

et al. 2021

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Health and wellness–related travel, also known as medical tourism, is a topical phenomenon with a wide range of effects in both local and transnational contexts. This scoping study examines the literature on this phenomenon from the perspective of travelers. The literature search was conducted using three databases (EBSCOhost, Web of Science, and SCOPUS) and covered the period from 2010 to 2018. The results show that the literature is divided into two academic fields: social sciences and tourism. Travel from the Global North to the Global South still dominates the field of medical travel research, and studies on South-to-South or intra-regional travel are underrepresented. There is a need for a more in-depth qualitative understanding of travelers’ lived experiences and for studies with more advanced quantitative methods and longitudinal research designs. We call for more interdisciplinary and theoretical approaches to health and wellness–related travel and propose a conceptual model that considers travelers’ intent (medical/wellness) and status (patient/tourist).

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Multilevel Modeling and Policy Development: Guidelines and Applications to Medical Travel

Cited by 4 publications

References 47 publications

An evidence-based policy for improving choice in global health access through medical travel

An evidence-based policy for improving choice in global health access through medical travel

Application of Hierarchical/Multilevel Models and Quality of Reporting (2010–2020): A Systematic Review

Health and Wellness–Related Travel: A Scoping Study of the Literature in 2010-2018

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