Taking a patient-oriented approach in exercise interventions for pregnant women: a commentary

Taking a patient-oriented approach to developing lifestyle interventions includes incorporating the patient into the program’s design, delivery, and evaluation. This commentary assumes that a patient-oriented approach has not yet been implemented and tested in exercise-based interventions designed for pregnant women. We outline and define a patient-oriented approach to conduct exercise-based research and review previous physical activity interventions designed for pregnant women to determine whether a patient-oriented approach was applied. In addition, pregnant women living with obesity may have unique barriers to engaging in prenatal exercise interventions that have not been previously addressed, such as having experienced weight stigma before pregnancy in healthcare and fitness settings. We propose suggestions for future trials to effectively take a patient-oriented approach when designing and implementing prenatal exercise interventions to address patient-informed barriers and incorporate suggested facilitators for physical activity. Given that prenatal activity levels are low and pregnant women may have unique barriers to engaging in exercise interventions, a patient-oriented approach may be an effective strategy to improve inclusivity and equity and, as a result, increase uptake and adherence to the intervention.     

Exploring the main and moderating effects of individual-level characteristics on consumer responses to sugar taxes and front-of-pack nutrition labels in an experimental marketplace

InterventionThis study examined whether the impacts of sugar taxes and front-of-pack (FOP) nutrition labels differ across socio-demographic subgroups.Research questionWhat are the main and moderating effects of individual-level characteristics on the nutrient content of participants’ purchases in response to varying taxation levels and FOP labels?MethodsData from an experimental marketplace were analyzed. A sample of 3584 Canadians aged 13 years and older received $5 to purchase an item from a selection of 20 beverages and 20 snack foods. Participants were shown products with one of five FOP labels and completed eight within-subject purchasing tasks with different tax conditions. Linear mixed models were used to estimate the main and moderating effects of 11 individual-level variables on the sugars, sodium, saturated fats, and calorie content of participants’ purchases.ResultsParticipants who were younger, male, and more frequent consumers of sugary drinks purchased products containing more sugars, sodium, saturated fats, and calories. Sex and age moderated the relationship between tax condition and sugars or calories purchased: female participants were more responsive than males to a tax that included fruit juice, and younger participants were more responsive to all sugar tax conditions than older participants. Reported thirst and education level also moderated the relationship between tax condition and calories purchased. No individual-level characteristics moderated the effects of FOP labels.ConclusionA small proportion (7 of 176) of the moderating effects tested in this study were significant. Sugar taxes and FOP labelling policies may therefore produce similar effects across key socio-demographic groups.Supplementary InformationThe online version contains supplementary material available at 10.17269/s41997-021-00475-x.     

Measuring physician practice site characteristics: A comparison of data from SK&A and a practice site survey

ObjectiveTo evaluate the comparability of commercially available practice site data from SK&A with survey data to understand the implications of using SK&A data for health services research.Data sourcesResponses to the Comprehensive Primary Care Plus (CPC+) Practice Survey and SK&A data.Study designComparison of CPC + Practice Survey responses to SK&A information for 2698 primary care practice sites.Data collectionCPC + Practice Survey data collected through a web‐only survey from April through September 2017, and SK&A data purchased in November 2016.Principal findingsInformation was similar across data sources, although some discrepancies were common. For example, 56% of practice sites had differences in the reported number of practitioners, and larger sites tended to have larger differences. Among practice sites with 1 practitioner in the survey, only 1.3% had a difference of 3 or more practitioners between the data sources, whereas 63% of practice sites with 11 or more practitioners had a difference of 3 or more practitioners.ConclusionsDiscrepancies between data sources could reflect differences of interpretation when defining practice site characteristics, changes over time in those characteristics, or data errors in either SK&A or the survey. Researchers using SK&A data should consider possible ramifications for their studies.     

Who contextualises clinical epidemiological evidence? A political analysis of the problem of evidence-based medicine in the layered Dutch healthcare system

We critically examine the discussion on the role of evidence-based medicine (EBM) in healthcare governance. We take the institutionally layered Dutch healthcare system as our case study. Here, different actors are involved in the regulation, provision and financing of healthcare services. Over the last decades, these actors have related to EBM to inform their actor specific roles. At the same time, EBM has increasingly been problematised. To better understand this problematisation, we organised focus groups and interviews. We noticed that particularly EBM’s reductionist epistemology and its uncritical use by ‘professional others’ are considered problematic. However, our analysis also reveals that something else seems to be at stake. In fact, all the actors involved underwrite EBM’s reductionist epistemology and emphasise that evidence should be contextualised. They however do so in different ways and with different contexts in mind. Moreover, the ways in which some actors contextualise evidence has consequences for the ways in which others can do the same. We therefore emphasise that behind EBM’s scientific problematisation lurks a political issue. A dispute over who should contextualise evidence how, in a layered healthcare system with interdependent actors that cater to both individual patients and the public. We urge public administration scholars and policymakers to open-up the political confrontation between healthcare actors and their sometimes irreconcilable, yet evidence-informed perspectives.     

Fertility and digital technology: narratives of using smartphone app ‘Natural Cycles’ while trying to conceive

Fertility awareness apps, which help to identify the ‘fertile window’ when conception is most likely, have been hailed as ‘revolutionising’ women’s reproductive health. Despite rapidly growing popularity, little research has explored how people use these apps when trying to conceive and what these apps mean to them. We draw on in‐depth, qualitative interviews, adopting a critical digital health studies lens (a sub‐field of science and technology studies), to explore the experiences of cisgender women and partners with one such app, Natural Cycles, in the context of their daily lives. We found that many women valued the technology as a ‘natural’, inobtrusive alternative to biomedical intervention, and a means of controlling and knowing their bodies, amid a dearth of fertility‐related education and care. Yet this technology also intervened materially and affectively into the spaces of their lives and relationships and privileged disembodied metrics (temperature) over embodied knowledge. Meanwhile, app language, advertising and cost have contributed to characterising ‘typical’ users as white, heterosexual, affluent, cisgender women without disabilities. In the context of neoliberal shifts towards bodily self‐tracking, technologies appealing as novel, liberating and ‘natural’ to individuals who can access them may nevertheless reproduce highly gendered reproductive responsibilities, anxieties and broader health and social inequalities.     

Clinical prediction models to predict the risk of multiple binary outcomes: a comparison of approaches

Clinical prediction models (CPMs) can predict clinically relevant outcomes or events. Typically, prognostic CPMs are derived to predict the risk of a single future outcome. However, there are many medical applications where two or more outcomes are of interest, meaning this should be more widely reflected in CPMs so they can accurately estimate the joint risk of multiple outcomes simultaneously. A potentially naïve approach to multi‐outcome risk prediction is to derive a CPM for each outcome separately, then multiply the predicted risks. This approach is only valid if the outcomes are conditionally independent given the covariates, and it fails to exploit the potential relationships between the outcomes. This paper outlines several approaches that could be used to develop CPMs for multiple binary outcomes. We consider four methods, ranging in complexity and conditional independence assumptions: namely, probabilistic classifier chain, multinomial logistic regression, multivariate logistic regression, and a Bayesian probit model. These are compared with methods that rely on conditional independence: separate univariate CPMs and stacked regression. Employing a simulation study and real‐world example, we illustrate that CPMs for joint risk prediction of multiple outcomes should only be derived using methods that model the residual correlation between outcomes. In such a situation, our results suggest that probabilistic classification chains, multinomial logistic regression or the Bayesian probit model are all appropriate choices. We call into question the development of CPMs for each outcome in isolation when multiple correlated or structurally related outcomes are of interest and recommend more multivariate approaches to risk prediction.     

A framework for considering the risk‐benefit trade‐off in designing noninferiority trials using composite outcome approaches

When a new treatment regimen is expected to have comparable or slightly worse efficacy to that of the control regimen but has benefits in other domains such as safety and tolerability, a noninferiority (NI) trial may be appropriate but is fraught with difficulty in justifying an acceptable NI margin that is based on both clinical and statistical input. To overcome this, we propose to utilize composite risk‐benefit outcomes that combine elements from domains of importance (eg, efficacy, safety, and tolerability). The composite outcome itself may be analyzed using a superiority framework, or it can be used as a tool at the design stage of a NI trial for selecting an NI margin for efficacy that balances changes in risks and benefits. In the latter case, the choice of NI margin may be based on a novel quantity called the maximum allowable decrease in efficacy (MADE), defined as the marginal difference in efficacy between arms that would yield a null treatment effect for the composite outcome given an assumed distribution for the composite outcome. We observe that MADE: (1) is larger when the safety improvement for the experimental arm is larger, (2) depends on the association between the efficacy and safety outcomes, and (3) depends on the control arm efficacy rate. We use a numerical example for power comparisons between a superiority test for the composite outcome vs a noninferiority test for efficacy using the MADE as the NI margin, and apply the methods to a TB treatment trial.     

Understanding what people think and feel about adult vaccinations and the associated barriers in Greece: Development and validation of the attitude towards adult vaccination (ATAVAC) scale

Despite the unequivocal value of vaccination in reducing the global burden of infectious diseases, the anti-vaccination movement thrives. The vast majority of the existing validated tools explore attitudes regarding vaccination in children. The aim of our study was to develop and validate a scale assessing attitudes towards adult immunisation. This national cross-sectional study included adult healthcare users who visited 23 Greek Primary Healthcare Units. The development of the scale was the result of literature review, semi-structured interviews and pilot testing of its preliminary versions. The initial version contained 15 items measuring respondents’ attitudes on a 6-point Likert scale. The sample was randomly split into two halves. Exploratory factor analysis, performed in the first sample, was used for the creation of multi-item scales; confirmatory factor analysis was used in the second sample to assess goodness of fit. Moreover, concurrent validity, internal consistency reliability, test–retest reliability and ceiling and floor effects were explored. The total sample consisted of 1,571 individuals. Overall ‘Cronbach's alpha’ (0.821) indicated good internal consistency. The initial exploratory factor analysis resulted in a three-factor model. The subsequent confirmatory factor analysis indicated that an 11-item version of the scale provided the best fit of the model to the data (RMSEA = 0.050, SRMR = 0.053, TLI = 0.937, CFI = 0.955, AIC = 24,999.949). All subscales (‘value of adult vaccination’, ‘safety concerns’ and ‘perceived barriers’) demonstrated strong concurrent associations with participants’ attitudes and behaviour regarding vaccination (p < .001). No ceiling or floor effects were noted for any of the subscales (0.13%, 2.61% and 0.51%; 0.13%, 0.57% and 0.45% respectively). The 11-item ATAVAC scale proved to be a reliable and valid tool, suitable for assessing attitudes towards adult vaccination.