Involving Children in Creating a Healthy Environment in Low Socioeconomic Position (SEP) Neighborhoods in The Netherlands: A Participatory Action Research (PAR) Project.
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SUBMITTER: Wilderink L
PROVIDER: S-EPMC8624284 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundPeople with a low socioeconomic position (SEP) are less likely to benefit from eHealth interventions, exacerbating social health inequalities. Professionals developing eHealth interventions for this group face numerous challenges. A comprehensive guide to support these professionals in their work could mitigate these inequalities.ObjectiveWe aimed to develop a web-based guide to support professionals in the development, adaptation, evaluation, and implementation of eHealth interventions for people with a low SEP.MethodsThis study consisted of 2 phases. The first phase involved a secondary analysis of 2 previous qualitative and quantitative studies. In this phase, we synthesized insights from the previous studies to develop the guide's content and information structure. In the second phase, we used a participatory design process. This process included iterative development and evaluation of the guide's design with 11 professionals who had experience with both eHealth and the target group. We used test versions (prototypes) and think-aloud testing combined with semistructured interviews and a questionnaire to identify design requirements and develop and adapt the guide accordingly.ResultsThe secondary analysis resulted in a framework of recommendations for developing the guide, which was categorized under 5 themes: development, reach, adherence, evaluation, and implementation. The participatory design process resulted in 16 requirements on system, content, and service aspects for the design of the guide. For the system category, the guide was required to have an open navigation strategy leading to more specific information and short pages with visual elements. Content requirements included providing comprehensible information, scientific evidence, a user perspective, information on practical applications, and a personal and informal tone of voice. Service requirements involved improving suitability for different professionals, ensuring long-term viability, and a focus on implementation. Based on these requirements, we developed the final version of "the inclusive eHealth guide."ConclusionsThe inclusive eHealth guide provides a practical, user-centric tool for professionals aiming to develop, adapt, evaluate, and implement eHealth interventions for people with a low SEP, with the aim of reducing health disparities in this population. Future research should investigate its suitability for different end-user goals, its external validity, its applicability in specific contexts, and its real-world impact on social health inequality.
| S-EPMC10728791 | biostudies-literature
Project description:Acute colon cancer surgery has a poor 90-day mortality of 21.0% compared with only 3% after elective colorectal cancer surgery in Denmark. The high mortality after acute colon cancer surgery compared with elective surgery emphasizes the importance of identifying factors associated with acute onset and poor short-term survival after acute surgery. Socioeconomic position has previously showed to be a risk factor for acute versus elective onset of colorectal cancer. Furthermore, if patients with low socioeconomic position have higher postoperative mortality this could reflect differences in the treatment of patients according to their socioeconomic position.
The aim of the clinical study is:
1. To examine if patients with short education, low income, living alone, or living in rural areas are more likely to undergo acute colorectal cancer surgery than elective surgery compared with patients with longer educations, higher income, living with a partner, or living in urban areas.
2. To examine if there is an association between education, income, cohabitation, or urbanicity and 1-year mortality after acute colorectal cancer surgery.
| 2277284 | ecrin-mdr-crc
Project description:Accessing high-resolution, timely socioeconomic data such as data on population, employment, and enterprise activity at the neighborhood level is critical for social scientists and policy makers to design and implement location-based policies. However, in many developing countries or cities, reliable local-scale socioeconomic data remain scarce. Here, we show an easily accessible and timely updated location attribute-restaurant-can be used to accurately predict a range of socioeconomic attributes of urban neighborhoods. We merge restaurant data from an online platform with 3 microdatasets for 9 Chinese cities. Using features extracted from restaurants, we train machine-learning models to estimate daytime and nighttime population, number of firms, and consumption level at various spatial resolutions. The trained model can explain 90 to 95% of the variation of those attributes across neighborhoods in the test dataset. We analyze the tradeoff between accuracy, spatial resolution, and number of training samples, as well as the heterogeneity of the predicted results across different spatial locations, demographics, and firm industries. Finally, we demonstrate the cross-city generality of this method by training the model in one city and then applying it directly to other cities. The transferability of this restaurant model can help bridge data gaps between cities, allowing all cities to enjoy big data and algorithm dividends.
| S-EPMC6681720 | biostudies-literature
Project description:BackgroundSocioeconomic disparities in the adoption of preventive health programs represent a well-known challenge, with programs delivered via the web serving as a potential solution. The preventive health program examined in this study is a large-scale, open-access web-based platform operating in the Netherlands, which aims to improve the health behaviors and wellness of its participants.ObjectiveThis study aims to examine the differences in the adoption of the website and mobile app of a web-based preventive health program across socioeconomic groups.MethodsThe 83,466 participants in this longitudinal, nonexperimental study were individuals who had signed up for the health program between July 2012 and September 2019. The rate of program adoption per delivery means was estimated using the Prentice, Williams, and Peterson Gap-Time model, with the measure of neighborhood socioeconomic status (NSES) used to distinguish between population segments with different socioeconomic characteristics. Registration to the health program was voluntary and free, and not within a controlled study setting, allowing the observation of the true rate of adoption.ResultsThe estimation results indicate that program adoption across socioeconomic groups varies depending on the program's delivery means. For the website, higher NSES groups have a higher likelihood of program adoption compared with the lowest NSES group (hazard ratio 1.03, 95% CI 1.01-1.05). For the mobile app, the opposite holds: higher NSES groups have a lower likelihood of program adoption compared with the lowest NSES group (hazard ratio 0.94, 95% CI 0.91-0.97).ConclusionsPromoting preventive health programs using mobile apps can help to increase program adoption among the lowest socioeconomic segments. Given the increasing use of mobile phones among disadvantaged population groups, structuring future health interventions to include mobile apps as means of delivery can support the stride toward diminishing health disparities.
| S-EPMC8851331 | biostudies-literature
Project description:BackgroundAt present, the maternity care system in the Netherlands is being reorganized into an integrated model of care, shifting the focus of midwives to include increasing numbers of births in hospital settings and clients with medium risk profiles. In light of these changes, it is useful for midwives to have a tool which may help them in reflecting upon care practices that promote physiological childbirth practices. The Optimality Index-US is an evidence based tool, designed to measure optimal perinatal care processes and outcomes. It has been validated for use in the United States (OI-US), United Kingdom (OI-UK) and Turkey (OI-TR). The objective of this study was to adapt the OI-US for the Dutch maternity care setting (OI-NL).MethodsTranslation and back translation were applied to create the OI-NL. A panel of maternity care experts (n = 10) provided input for face validation items in the OI-NL. Assessment of inter-rater reliability and ease of use was also conducted. Following this, the OI-NL was used prospectively to collect data on 266 women who commenced intrapartum care under the responsibility of a midwife. Twice groups were compared, based on parity and on care-setting at birth. Mean scores between these groups, corrected for perinatal background factors were assessed for discriminant validity.ResultsFace validity was established for OI-NL on the basis of expert input. Discriminant validity was confirmed by conducting multiple regressions analyses for parity (β = 6.21, P = 0.00) and for care-setting (β = 12.1, p = 0.00). Inter-rater reliability was 98%, with one item (Apgar score) sensitive to scoring differences.ConclusionOI-NL is a valid and reliable tool for use in the Dutch maternity care setting. In addition to its value for assessing evidence-based maternity care processes and outcomes, there is potential for use for learning and reflection. Against the backdrop of a changing maternity care system, and due to the specificity of its items OI-NL may be of value as a tool for detecting subtle changes indicative of escalating medicalization of childbirth in the Netherlands.
| S-EPMC5902845 | biostudies-literature
Project description:BACKGROUND:Gameful designs (gamification), using design pieces and concepts typically found in the world of games, is a promising approach to increase users' engagement with, and adherence to, electronic health and mobile health (mHealth) tools. Even though both identifying and addressing users' requirements and needs are important steps of designing information technology tools, little is known about the users' requirements and preferences for gameful designs in the context of self-management of chronic conditions. OBJECTIVE:This study aimed to present findings as well as the applied methods and design activities from a series of participatory design workshops with patients with chronic conditions, organized to generate and explore user needs, preferences, and ideas to the implementation of gameful designs in an mHealth self-management app. METHODS:We conducted three sets of two consecutive co-design workshops with a total of 22 participants with chronic conditions. In the workshops, we applied participatory design methods to engage users in different activities such as design games, scenario making, prototyping, and sticky notes exercises. The workshops were filmed, and the participants' interactions, written products, ideas, and suggestions were analyzed thematically. RESULTS:During the workshops, the participants identified a wide range of requirements, concerns, and ideas for using the gameful elements in the design of an mHealth self-management app. Overall inputs on the design of the app concerned aspects such as providing a positive user experience by promoting collaboration and not visibly losing to someone or by designing all feedback in the app to be uplifting and positive. The participants provided both general inputs (regarding the degree of competitiveness, use of rewards, or possibilities for customization) and specific inputs (such as being able to customize the look of their avatars or by having rewards that can be exchanged for real-world goods in a gift shop). However, inputs also highlighted the importance of making tools that provide features that are meaningful and motivating on their own and do not only have to rely on gameful design features to make people use them. CONCLUSIONS:The main contribution in this study was users' contextualized and richly described needs and requirements for gamefully designed mHealth tools for supporting chronic patients in self-management as well as the methods and techniques used to facilitate and support both the participant's creativity and communication of ideas and inputs. The range, variety, and depth of the inputs from our participants also showed the appropriateness of our design approach and activities. These findings may be combined with literature and relevant theories to further inform in the selection and application of gameful designs in mHealth apps, or they can be used as a starting point for conducting more participatory workshops focused on co-designing gameful health apps.
| S-EPMC6315237 | biostudies-literature
Project description:BACKGROUND:When studying the influence of socioeconomic position (SEP) on health from data where individual-level SEP measures may be missing, ecological measures of SEP may prove helpful. In this paper, we illustrate the best use of ecological-level measures of SEP to deal with incomplete individual level data. To do this we have taken the example of a study examining the relationship between SEP and breast cancer (BC) stage at diagnosis. METHODS:Using population based-registry data, all women over 18 years newly diagnosed with a primary BC in 2007 were included. We compared the association between advanced stage at diagnosis and individual SEP containing missing data with an ecological level SEP measure without missing data. We used three modelling strategies, 1/ based on patients with complete data for individual-SEP (n = 1218), or 2/ on all patients (n = 1644) using an ecological-level SEP as proxy for individual SEP and 3/ individual-SEP after imputation of missing data using an ecological-level SEP. RESULTS:The results obtained from these models demonstrate that selection bias was introduced in the sample where only patients with complete individual SEP were included. This bias is redressed by using ecological-level SEP to impute missing data for individual SEP on all patients. Such a strategy helps to avoid an ecological bias due to the use of aggregated data to infer to individual level. CONCLUSION:When individual data are incomplete, we demonstrate the usefulness of an ecological index to assess and redress potential selection bias by using it to impute missing individual SEP.
| S-EPMC6604477 | biostudies-other
Project description:BackgroundWorkers with a low socioeconomic position (SEP) have a higher risk for health problems and premature dropout from the workforce. Unfavorable working conditions and unhealthy behaviors are more prevalent among this group of workers. The Participatory Approach (PA), is an evidence-based method to identify and solve problems at the workplace related to health issues of the worker. Health problems among workers with a low SEP are usually caused by an interplay of problems in and outside the workplace. To solve health problems on multiple life domains for workers with a low SEP we aim to adapt this approach to a broader perspective.MethodsAn Intervention Mapping (IM) protocol was used to adapt the PA. First, a needs assessment was conducted combining literature with data from interviews and focus groups with workers with a low SEP, employers and occupational health professionals (OHPs). Based on the needs assessment a program goal and performance and change objectives were defined, which resulted in methods and practical strategies to solve problems on multiple life domains. Based on the results of these steps, the PA was adapted and an implementation and evaluation plan were developed.ResultsThe needs assessment confirmed that an interplay of problems on multiple life domains affect work functioning and health of workers with a low SEP. Moreover, they perceived difficulties with solving problems or used passive or avoidant coping styles towards these problems. The program goal is to identify and solve problems on multiple life domains that affect healthy functioning at work. To achieve this workers need support from OHPs to solve problems. The PA protocol and materials were adapted using theoretical concepts of the Self-Determination Theory (SDT), which resulted in the Grip on Health intervention. For OHPs a training was developed on how to implement this intervention in practice. The intervention will be evaluated in a pilot implementation study among workers with a low SEP and other relevant stakeholders.ConclusionsIM was a valuable tool for the adaptation of the PA to better support workers with a low SEP to improve their work functioning and health from a broader perspective.
| S-EPMC7304135 | biostudies-literature
Project description:BackgroundWhile differences in population health across neighborhoods with different socioeconomic characteristics are well documented, health disparities across neighborhoods with similar socioeconomic characteristics are less well understood. We aimed to estimate population health inequalities, both within and between neighborhoods with similar socioeconomic status, and assessed the association of neighborhood characteristics and socioeconomic spillover effects from adjacent neighborhoods.MethodsBased on Dutch whole-population data we determined the percentage of inhabitants with good or very good self-assessed health (SAH) and the percentage of inhabitants with at least one chronic disease (CD) in 11,504 neighborhoods. Neighborhoods were classified by quintiles of a composite neighborhoods socioeconomic status score (NSES). A set of spatial models was estimated accounting for spatial effects in the dependent, independent, and error components of the model.ResultsSubstantial population health disparities in SAH and CD both within and between neighborhoods NSES quintiles were observed, with the largest SAH variance in the lowest NSES group. Neighborhoods adjacent to higher SES neighborhoods showed a higher SAH and a lower prevalence of CD. Projected impacts from the spatial regressions indicate how modest changes in NSES among the lowest socioeconomic neighborhoods can contribute to population health in both low- and high-SES neighborhoods.ConclusionPopulation health differs substantially among neighborhoods with similar socioeconomic characteristics, which can partially be explained by a spatial socio-economic spillover effect.
| S-EPMC8327128 | biostudies-literature
Project description:BACKGROUND: Since its initiation in 2005, the Harvard Personal Genome Project has enrolled thousands of volunteers interested in publicly sharing their genome, health and trait data. Because these data are highly identifiable, we use an 'open consent' framework that purposefully excludes promises about privacy and requires participants to demonstrate comprehension prior to enrollment. DISCUSSION: Our model of non-anonymous, public genomes has led us to a highly participatory model of researcher-participant communication and interaction. The participants, who are highly committed volunteers, self-pursue and donate research-relevant datasets, and are actively engaged in conversations with both our staff and other Personal Genome Project participants. We have quantitatively assessed these communications and donations, and report our experiences with returning research-grade whole genome data to participants. We also observe some of the community growth and discussion that has occurred related to our project. SUMMARY: We find that public non-anonymous data is valuable and leads to a participatory research model, which we encourage others to consider. The implementation of this model is greatly facilitated by web-based tools and methods and participant education. Project results are long-term proactive participant involvement and the growth of a community that benefits both researchers and participants.
| S-EPMC3978420 | biostudies-literature