Effects of a web-based decision aid regarding diagnostic self-testing. A single-blind randomized controlled trial

Ickenroth, Martine H. P.; Grispen, Janaica E J; Vries, Nanne K. de; Dinant, Geert-Jan; Ronda, Gaby

doi:10.1093/her/cyw014

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…Patients scored one point for each correct answer. One point was deducted for each incorrect answer; no points were given if the patient did not know the answer (appendix E) [34] .…”

Section: Methodsmentioning

confidence: 99%

A patient decision aid for breast cancer patients deciding on their radiation treatment, no change in decisional conflict but better informed choices

Raphael

Russell

Winkens

et al. 2021

Technical Innovations & Patient Support in Radiation Oncolo

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Highlights No difference was found in decisional conflict with or without PtDA use. Patients who used the PtDA had more knowledge, suggesting a better informed choice. Patients who used the PtDA chose more often for a less intensive treatment. The use of the PtDA was not significant associated with a longer consultation time.

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“…Patients scored one point for each correct answer. One point was deducted for each incorrect answer; no points were given if the patient did not know the answer (appendix E) [34] .…”

Section: Methodsmentioning

confidence: 99%

A patient decision aid for breast cancer patients deciding on their radiation treatment, no change in decisional conflict but better informed choices

Raphael

Russell

Winkens

et al. 2021

Technical Innovations & Patient Support in Radiation Oncolo

Self Cite

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“…Interactive visualizations can be particularly useful for location-allocation analyses given that these analyses can result in many charts and maps depending on the number of evaluated scenarios and optimisation criteria [ 23 , 24 ]. Importantly, previous research has demonstrated that interactive information can have greater impact than passive information [ 25 , 26 ]. Furthermore, the application can also serve as an interactive simulator that allows users to create and explore their own scenarios regarding health facility allocation and how this influences accessibility and health outcomes [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

Guiding placement of health facilities using multiple malaria criteria and an interactive tool

Toh

Millar

Psychas

et al. 2021

Malar J

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Background Access to healthcare is important in controlling malaria burden and, as a result, distance or travel time to health facilities is often a significant predictor in modelling malaria prevalence. Adding new health facilities may reduce overall travel time to health facilities and may decrease malaria transmission. To help guide local decision-makers as they scale up community-based accessibility, the influence of the spatial allocation of new health facilities on malaria prevalence is evaluated in Bunkpurugu-Yunyoo district in northern Ghana. A location-allocation analysis is performed to find optimal locations of new health facilities by separately minimizing three district-wide objectives: malaria prevalence, malaria incidence, and average travel time to health facilities. Methods Generalized additive models was used to estimate the relationship between malaria prevalence and travel time to the nearest health facility and other geospatial covariates. The model predictions are then used to calculate the optimisation criteria for the location-allocation analysis. This analysis was performed for two scenarios: adding new health facilities to the existing ones, and a hypothetical scenario in which the community-based healthcare facilities would be allocated anew. An interactive web application was created to facilitate efficient presentation of this analysis and allow users to experiment with their choice of health facility location and optimisation criteria. Results Using malaria prevalence and travel time as optimisation criteria, two locations that would benefit from new health facilities were identified, regardless of scenarios. Due to the non-linear relationship between malaria incidence and prevalence, the optimal locations chosen based on the incidence criterion tended to be inequitable and was different from those based on the other optimisation criteria. Conclusions This study findings underscore the importance of using multiple optimisation criteria in the decision-making process. This analysis and the interactive application can be repurposed for other regions and criteria, bridging the gap between science, models and decisions.

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“…Interactive visualizations can be particularly useful for location-allocation analyses given that these analyses can result in many charts and maps depending on the number of evaluated scenarios and optimization criteria (e.g., [22,23]). Importantly, previous research has demonstrated that interactive information can have greater impact than passive information (e.g., [24,25]). Furthermore, the application can also serve as an interactive simulator that allows users to create and explore their own scenarios regarding health facility allocation and how this influences accessibility and health outcomes [26].…”

Section: Introductionmentioning

confidence: 99%

Guiding placement of health facilities using malaria criteria and interactive tool

Toh

Millar

Psychas³

et al. 2021

Preprint

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Background: Access to healthcare is important in controlling malaria burden and, as a result, distance or travel time to health facilities is often a significant predictor in modeling malaria prevalence. Adding new health facilities may reduce overall travel time to health facilities and may decrease malaria transmission. To help guide local decision makers as they scale up community-based accessibility, we explore how the allocation of new health facilities might influence malaria prevalence in Bunkpurugu-Yunyoo district in northern Ghana. We perform a location-allocation analysis to find optimal locations of new health facilities by minimizing three district-wide objectives separately: malaria prevalence, malaria incidence, and average travel time to health facilities. Methods: We used generalized additive model to model malaria prevalence as a function of travel time to health facility and other geospatial covariates. The model predictions are used to calculate the optimization criteria and to conduct spatial optimization. This analysis was performed for two scenarios: adding new health facilities to the existing ones, and a hypothetical scenario in which the community-based healthcare facilities would be allocated anew. We created an interactive web application to facilitate efficient presentation of this analysis and allow users to experiment with their choice of health facility location and optimization criteria. Results: Using malaria prevalence and travel time as optimization criteria, we found two locations that were not covered by existing community-based health services that would benefit from new health facilities, regardless of scenarios. Due to the non-linear relationship between malaria incidence and prevalence, the optimal locations chosen by using incidence criterion tend to be inequitable and are different from those based on the other optimization criteria. Conclusion: Our findings underscore the importance of using multiple optimization criteria in the decision-making process. We believe that our analysis and interactive application can be repurposed for other regions and criteria, bridging the gap between science, models and decisions.

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Effects of a web-based decision aid regarding diagnostic self-testing. A single-blind randomized controlled trial

Abstract: Dutch Trial Register: NTR 3149.

Cited by 4 publications

References 14 publications

A patient decision aid for breast cancer patients deciding on their radiation treatment, no change in decisional conflict but better informed choices

A patient decision aid for breast cancer patients deciding on their radiation treatment, no change in decisional conflict but better informed choices

Guiding placement of health facilities using multiple malaria criteria and an interactive tool

Guiding placement of health facilities using malaria criteria and interactive tool

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