Hypothetical Intervention Research Articles

Acceptability of an online intervention for insomnia in children with neurodevelopmental disorders

BackgroundMost children with neurodevelopmental disorders (NDDs) experience insomnia. Online interventions may provide a way to reduce barriers to treatment access. AimsWe explored whether parents of children with NDDs and their health care professionals (HCPs) perceived an online insomnia intervention as acceptable and the perceived pros and cons of this intervention delivery method. Methods and proceduresParticipants included 43 parents of children with NDDs and 44 HCPs who work with children with NDDs. During focus groups/interviews participants shared their perceptions of a hypothetical online insomnia intervention. Responses were analyzed using qualitative content analysis and codes were grouped into pros and cons. Outcomes and resultsParents and HCPs reported similar pros and cons. Pros focused on the intervention’s accessibility, credibility, usability, usefulness, and design, whereas cons focused on feasibility of implementation. Participants felt that external support (e.g., an online coach) would improve the intervention’s acceptability. Conclusions and implicationsOverall, the majority of parents and HCPs perceived an online intervention for insomnia as acceptable but concerns about implementation were noted and need to be taken into account when developing online interventions

Do people with epilepsy want to participate in an exercise intervention randomized controlled trial? – Results of a brief survey and its preliminary application

Our goal was to survey people with epilepsy (PWE) about their interest in and factors that may influence willingness and ability to participate in an exercise randomized controlled trial (RCT). A brief survey was administered to 100 PWE asking if they would take part in a hypothetical 6-week exercise intervention RCT. Follow-up questions queried reasons for and against participation and why participation would be difficult. Sixty-nine percent of respondents indicated willingness to participate. The top reason for participation was “to improve overall health with exercise” (n = 49). The top reason for why participation would be difficult was they “do not have a reliable source of transportation” (n = 27). The top reason for not participating was “not interested in research participation” (n = 19). Preliminary results were used to budget for transportation in a prospective RCT (NCT04959019). Of the first 27 PWE enrolled (63 % female; 44 % African American/Black), six (50 % female; 50 % African American/Black) have used the transportation service. The majority of PWE surveyed were interested in participating in an exercise RCT, but some indicated barriers. Accommodating transportation in an ongoing RCT has facilitated recruitment of PWE who would otherwise not be able to participate. Barriers to participation should be accounted for when designing studies.

Evaluation in green building design for conversion projects: Case studies and comparative approaches

By 2020, the manufacturing and construction industries sector is responsible for 16.3 percent of Europe’s greenhouse gas emissions, third after the energy industries sector (31.4%) and transportation sector (29.0%). The built heritage is one of the first targets for mitigation and improvement of current environmental conditions. Carl Elefante’s now famous statement “The Greenest Building Is... One That Is Already Built” wide the aspiration of the green concept to building design not only to new construction but also to the existing building stock. The purpose of the hypothetical intervention would aim at improving the three dimensions of sustainability - environmental, economic, and social - as applied to the building artifact. The dimensions of sustainability related with the concept of green building, that aims to implement user health through the design of healthy indoor environments. As a result of providing the definitions of Green Building design mainly found in the literature, the first approach of the paper is a critical reading of three case studies in the field of sustainable building, the criteria used in ex-ante evaluation, comparing their results, and providing a general procedural a logical framework to understand the initial part of the design process approaching to sustainability.

Hypothetical interventions on emergency ambulance and prehospital acetylsalicylic acid administration in myocardial infarction patients presenting without chest pain

BackgroundMyocardial infarction (MI) patients presenting without chest pain are a diagnostic challenge. They receive suboptimal prehospital management and have high mortality. To elucidate potential benefits of improved management, we analysed expected outcome among non-chest pain MI patients if hypothetically they (1) received emergency ambulances/acetylsalicylic acid (ASA) as often as observed for chest pain patients, and (2) all received emergency ambulance/ASA.MethodsWe sampled calls to emergency and non-emergency medical services for patients hospitalized with MI within 24 h and categorized calls as chest pain/non-chest pain. Outcomes were 30-day mortality and a 1-year combined outcome of re-infarction, heart failure admission, and mortality. Targeted minimum loss-based estimation was used for all statistical analyses.ResultsAmong 5418 calls regarding MI patients, 24% (1309) were recorded with non-chest pain. In total, 90% (3689/4109) of chest pain and 40% (525/1309) of non-chest pain patients received an emergency ambulance, and 73% (2668/3632) and 37% (192/518) of chest pain and non-chest pain patients received prehospital ASA. Providing ambulances to all non-chest pain patients was not associated with improved survival. Prehospital administration of ASA to all emergency ambulance transports of non-chest pain MI patients was expected to reduce 30-day mortality by 5.3% (CI 95%: [1.7%;9%]) from 12.8% to 7.4%. No significant reduction was found for the 1-year combined outcome (2.6% CI 95% [− 2.9%;8.1%]). In comparison, the observed 30-day mortality was 3% among ambulance-transported chest pain MI patients.ConclusionsOur study found large differences in the prehospital management of MI patients with and without chest pain. Improved prehospital ASA administration to non-chest pain MI patients could possibly reduce 30-day mortality, but long-term effects appear limited. Non-chest pain MI patients are difficult to identify prehospital and possible unintended effects of ASA might outweigh the potential benefits of improving the prehospital management. Future research should investigate ways to improve the prehospital recognition of MI in the absence of chest pain.

Using Social Media to Engage Justice-Involved Young Adults in Digital Health Interventions for Substance Use: Pilot Feasibility Survey Study.

Young adults involved in the justice system have high rates of substance use disorders and low rates of treatment engagement. Most justice-involved young adults are supervised in the community-not incarcerated in jail or prison-where they have ongoing access to substances and experience significant barriers to care. When they do engage in treatment, they tend to have worse outcomes than justice-involved adolescents and older adults. Despite the need to develop targeted treatments, there are unique challenges in recruiting this population into clinical research. Digital health technology offers many novel avenues for recruiting justice-involved young adults into clinical research studies and disseminating substance use disorder treatments to justice-involved young adults. Because the vast majority of young adults regularly use one or more social media platforms, social media may offer a cost-effective and efficient way to achieve these goals. This study aimed to describe the process and feasibility of using social media platforms (Facebook and Reddit) to recruit justice-involved young adults into clinical research. Justice-involved young adults recruited from these platforms completed a survey assessing the acceptability of digital health interventions to address substance use in this population. Justice-involved young adults (aged 18-24 years) were recruited through paid advertisements placed on Facebook and Reddit. Participants responded to a web-based survey focused on their substance use, treatment use history, and acceptability of various digital health interventions focused on substance use. A national sample of justice-involved young adults were successfully enrolled and completed the survey (N=131). Participants were racially diverse (8/131, 6.1% American Indian individuals; 27/131, 20.6% Asian individuals; 23/131, 17.6% Black individuals; 26/131, 19.8% Latinx individuals; 8/131, 6.1% Pacific Islander individuals; 49/131, 37.4% White individuals; and 2/131, 1.5% individuals who identified as "other" race and ethnicity). Advertisements were cost-effective (US $0.66 per click on Facebook and US $0.47 per click on Reddit). More than half (72/131, 54.9%) of the participants were on probation or parole in the past year and reported hazardous alcohol (54/131, 51.9%) or drug (66/131, 57.4%) use. Most of the participants (103/131, 78.6%) were not currently participating in substance use treatment. Nearly two-third (82/131, 62.6%) of the participants were willing to participate in one or more hypothetical digital health interventions. Social media is a feasible and cost-effective method for reaching justice-involved young adults to participate in substance use research trials. With limited budgets, researchers can reach a broad audience, many of whom could benefit from treatment but are not currently engaged in care. Proposed digital health interventions focusing on reducing substance use, such as private Facebook groups, SMS text message-based appointment reminders, and coaching, had high acceptability. Future work will build on these findings to develop substance use treatment interventions for this population.

EE542 Health Experiences, Well-Being and Preferences in Health Priority Settings

The aim of the paper is to evaluate how the Swedish population values hypothetical interventions aimed at reducing the number of deaths due to suicide, pancreatic cancer, breast cancer and acute myocardial infarction, controlling for the respondents’ well-being, their own experiences or knowing someone else, family or friends, who suffered or died due to any of these four diagnoses.

Impact of lowering fine particulate matter from major emission sources on mortality in Canada: A nationwide causal analysis

Emissions of fine particulate matter (PM2.5) from human activities have been linked to substantial disease burdens, but evidence regarding how reducing PM2.5 at its sources would improve public health is sparse. We followed a population-based cohort of 2.7 million adults across Canada from 2007 through 2016. For each participant, we estimated annual mean concentrations of PM2.5 and the fractional contributions to PM2.5 from the five leading anthropogenic sources at their residential address using satellite observations in combination with a global atmospheric chemistry transport model. For each source, we estimated the causal effects of six hypothetical interventions on 10-y nonaccidental mortality risk using the parametric g-formula, a structural causal model. We conducted stratified analyses by age, sex, and income. This cohort would have experienced tangible health gains had contributions to PM2.5 from any of the five sources been reduced. Compared with no intervention, a 10% annual reduction in PM2.5 contributions from transportation and power generation, Canada's largest and fifth-largest anthropogenic sources, would have prevented approximately 175 (95%CI: 123-226) and 90 (95%CI: 63-117) deaths per million by 2016, respectively. A more intensive 50% reduction per year in PM2.5 contributions from the two sources would have averted 360 and 185 deaths per million, respectively, by 2016. The potential health benefits were greater among men, older adults, and low-income earners. In Canada, where PM2.5 levels are among the lowest worldwide, reducing PM2.5 contributions from anthropogenic sources by as little as 10% annually would yield meaningful health gains.

Flood Modeling in a Coastal Town in Northern Colombia: Comparing MODCEL vs. IBER

In Riohacha the La Niña, phenomenon generates intense rains with consequent serious flooding. To address this reality, MODCEL, a conceptual cell-based model, had been applied and calibrated in a previous project. In this research, we compare MODCEL with IBER, a well-known, physically based 2D hydraulic model. The purpose is twofold: (i) to illustrate how system schematization can be carried out in the two modeling frameworks, which is not a trivial task and implies several choices and assumptions; (ii) to point out the strengths and weaknesses of these two models in a comparative fashion. Here, IBER has been calibrated and validated with the same data used for MODCEL. MODCEL performs slightly better, both in calibration and validation possibly because of the low resolution of the topographic information, an essential element for IBER. Furthermore, in IBER it is not possible to represent adequately all the different hydraulic works spread across the town. MODCEL, in turn, is not easy to apply because it requires a deep insight into the actual behavior of the physical system and time-consuming schematization attempts where a deep experience is needed; furthermore, it is by far less user-friendly than IBER. In any case, the two models capture sufficiently well the behavior of urban flooding and its changes according to hypothetical interventions.

Concrete Counterfactual Tests for Process Tracing: Defending an Interventionist Potential Outcomes Framework

This article uses the interventionist theory of causation, a counterfactual theory taken from philosophy of science, to strengthen causal analysis in process tracing research. Causal claims from process tracing are re-expressed in terms of so-called hypothetical interventions, and concrete evidential tests are proposed which are shown to corroborate process tracing claims. In particular, three steps are prescribed for an interventionist investigation, and each step in turn is shown to make the causal analysis more robust, amongst others by disambiguating causal claims and clarifying or strengthening the existing methodological advice on counterfactual analysis. The article's claims are then illustrated using a concrete example, Haggard and Kaufman's analysis of the Argentinian transition to democracy. It is shown that interventionism could have strengthened the authors’ conclusions. The article concludes with a short Bayesian analysis of its key methodological proposals.

Supporting pregnant women not ready to quit smoking: an economic evaluation

ObjectivesSome pregnant women are not ready or do not want to quit smoking completely, and currently there is no support provided for these women in the UK. Offering help to reduce smoking could reduce the health risks associated with smoking and increase the limited reach of the NHS Stop Smoking Services (SSS) for pregnant women. This study aimed to design and evaluate a hypothetical intervention aimed at pregnant women who are not yet ready or do not want to quit smoking entirely.MethodsA hypothetical intervention, the Reduced Smoking During Pregnancy (RSDP) intervention, was conceptualised based on the best available evidence. The intervention was evaluated, using a decision-analytic model developed for SDP interventions. Two different scenarios, a base-case and a cautious-case were developed, and a cost-utility analysis and return on investment analysis were conducted. The uncertainty around the estimates was assessed, using deterministic and probabilistic sensitivity analyses.ResultsThe RSDP intervention could prevent the loss of 13 foetuses and generate 43 quitters 1 year after delivery per 1000 women. In the lifetime analysis, the intervention was cost-effective in both scenarios, with an incremental cost of £363 (95% CI £29 to £672) and 0.44 (95% CI 0.32 to 0.53) QALYs gained in the base-case.ConclusionsThe study found that the hypothetical reduction intervention would produce significant health benefits, reduce smoking and be cost-effective. Offering pregnant smokers help to reduce smoking could reduce health inequalities, widen the reach of SSS and improve health. This economic evaluation of a novel, intensive intervention could inform the piloting of such interventions.

Estimating Causal Effects of Interventions on Early-life Environmental Exposures Using Observational Data.

We discuss how epidemiologic studies have used observational data to estimate the effects of potential interventions on early-life environmental exposures. We summarize the value of posing questions about interventions, how a group of techniques known as "g-methods" can provide advantages for estimating intervention effects, and how investigators have grappled with the strong assumptions required for causal inference. We identified nine studies that estimated health effects of hypothetical interventions on early-life environmental exposures. Of these, six examined air pollution. Interventions evaluated by these studies included setting exposure levels at a specific value, shifting exposure distributions, and limiting exposure levels to less than a threshold value. Only one study linked exposure contrasts to a specific intervention on an exposure source, however. There is growing interest in estimating intervention effects of early-life environmental exposures, in part because intervention effects are directly related to possible public health actions. Future studies can build on existing work by linking research questions to specific hypothetical interventions that could reduce exposure levels. We discuss how framing questions around interventions can help overcome some of the barriers to causal inference and how advances related to machine learning may strengthen studies by sidestepping the overly restrictive assumptions of parametric regression models. By leveraging advancements in causal inference and exposure science, an intervention framework for environmental epidemiology can guide actionable solutions to improve children's environmental health.

Valuing Depression Using the Well-Being Valuation Approach

The continuously dramatic rise of the number of people suffering from depression is attracting an increasing demand for effective ways of preventing depression. Besides the need for new interventions, there is also a continuous call for a more robust framework for economic evaluation of public interventions. Taking into account people’s preferences for public goods is not straightforward to quantify, and therefore, in addition to designing a new technique for valuing nonmarket goods and services, it is equally important to use valuation methods that are not yet established as traditional. One less commonly used method to assess the cost of depression in monetary terms is the well-being valuation method or the life satisfaction approach, which requires answers to only a few questions that are significantly less time demanding for the respondents than more traditional approaches. We added a well-being question to a contingent valuation web-survey that describes hypothetical interventions aimed to prevent depression in Sweden and estimated that the loss in life satisfaction for individuals who experienced depression varies between approximately 350 and 45,000 euros per year. The monetary compensation would be, on average, higher for individuals who experienced own depression than for those who know someone near, family or friend, who experienced depression, for men than for women, and for middle-aged than for younger and older individuals, respectively.

Projecting the Epidemiological and Economic Impact of Chronic Kidney Disease Using Patient-Level Microsimulation Modelling: Rationale and Methods of InsideCKD.

Chronic kidney disease (CKD) is a serious condition associated with significant morbidity and healthcare costs. Despite this, early-stage CKD is often undiagnosed, and globally there is substantial variation in the effectiveness of screening and subsequent management. Microsimulations can estimate future epidemiological costs, providing useful insights for clinicians, policymakers and researchers. InsideCKD is a programme designed to analyse the projected prevalence and burden of CKD for countries across the world, and to simulate hypothetical intervention strategies that can then be assessed for potential impact on health and economic outcomes at a national and aglobal level. InsideCKD uses a population-based approach that creates virtual individuals for a given country, with this simulated population progressing through a microsimulation in 1-year increments. A series of data inputs derived from national statistics and key literature defined the likelihood of a change in health state for each individual. Input modules allow for the input of nationally specific demographic and CKD status (including prevalence, diagnosis rates, disease stage and likelihood of renal replacement therapy), disease progression, critical comorbidities, and mortality. Health economics are reflected in cost data and a flexible intervention module allows for the testing of hypothetical policies-such as screening strategies-that may alter disease progression and outcomes. Using input data from the UK as a case study and a 6-year simulation period, InsideCKD estimated a prevalence of 9.2 million individuals (both diagnosed and estimated undiagnosed) with CKD by 2027 and a 5.0% increase in costs for diagnosed CKD and renal replacement therapy. External validation and sensitivity analyses confirmed the observed trends, substantiating the robustness of the microsimulation. Using a microsimulation approach, InsideCKD extends the reach of current CKD policy analyses by factoring in multiple inputs that reflect national healthcare systems and enable analysis of the effect ofmultiple hypothetical screening scenarios on disease progression and costs.

The preventable productivity burden of sleep apnea in Australia: a lifetime modelling study.

Obstructive sleep apnea (OSA) is a common disorder. OSA is associated with cardiovascular disease (CVD), type 2 diabetes mellitus (T2DM) and depression, among other comorbidities. We aim to determine the productivity burden of OSA in Australia using productivity-adjusted life-years (PALYs). Using life table modelling, we built a multistate Markov model to estimate the impact of moderate to severe OSA on the whole working-age Australian population in 2021 (aged 20-65 years) with OSA until retirement (aged 66 years). The model also captured the impact of OSA on CVD, T2DM, depression, and vehicle-related accidents. Data for OSA and comorbidities and Australian specific labour data, were extracted from published sources. A second cohort was then modelled to test the effect of a hypothetical intervention, assuming a 10% reduction in OSA prevalence and a 10% reduction in comorbidities in patients with OSA. The primary outcome of interest were PALYs accrued. All outcomes were discounted 5% annually. Over a lifetime, the Australian population with OSA accrued 193,713,441 years of life lived and 182,737,644 PALYs. A reduction of 10% in OSA prevalence and comorbidities would result in 45,401 extra years of life lived and 150,950 extra PALYs. This resulted in more than AU$25 billion of gained gross domestic product over the lifetime of the working population. Our study highlights the substantial burden of OSA on the Australian population and the need to tailor interventions at the population level to reduce the health and economic impacts.

Well-Defined Interventions and Causal Variable Choice

AbstractThere has been much debate among scientists and philosophers about what it means for (hypothetical) interventions invoked in causal inference to be “well-defined” and how considerations of this sort should constrain the choice of causal variables. In this article, I propose that an intervention is well-defined just in case the effect of interest is well-defined, and that the intervention can serve as a suitable means to identify that effect. Based on this proposal, I identify several types of ambiguous intervention. Implications for variable choice are discussed using case studies drawn from the sciences.

Potential benefits of joint hypothetical interventions on diet, lead, and cadmium on mortality in US adults

BackgroundPrevious studies reported associations between high blood lead levels (BLLs) and urinary cadmium (UCd) concentrations and all-cause and cause-specific mortality. It is hypothesized that these associations are mediated by inflammation; therefore, adherence to an anti-inflammatory diet may mitigate these effects. We sought to estimate the potential effects of joint hypothetical interventions on metals levels and adherence to an anti-inflammatory diet or fruits and vegetables (FV) intake on the expected mortality distributions.MethodsWe used data on 14,311 adults aged ≥ 20 years enrolled in the NHANES-III between 1988 and 1994 and followed up through Dec 31, 2015. We estimated daily FV servings and adherence to the dietary inflammatory index at baseline using 24-hour dietary recalls. Mortality was determined from the National Death Index records. We used the parametric g-formula with pooled logistic regression models to estimate the absolute risk of all-cause, cardiovascular, and cancer mortality under different hypothetical interventions compared to the natural course (no intervention).ResultsOverall, we observed a decreased mortality risk when intervening to lower metals levels or increasing adherence to an anti-inflammatory diet or the daily FV servings. The joint intervention to lower BLLs and UCd and increase the adherence to the anti-inflammatory diet had the strongest impact on cancer mortality risk (risk difference [RD] = -1.50% (-2.52% to -0.62%)) compared to the joint intervention only on metals levels RD= -0.97% (-1.89 to 0.70). The same pattern of associations was observed for the joint intervention to lower both metals and increased daily FV servings and cardiovascular diseases mortality risk.ConclusionHigher diet quality may constitute a complementary approach to the interventions to reduce exposures to cadmium and lead to further minimize their effects on mortality. A paradigm shift is required from a pollutant-focused only to a combination with a human-focused approach for primary prevention against these metals.

FCMpy: a python module for constructing and analyzing fuzzy cognitive maps

FCMpy is an open-source Python module for building and analyzing Fuzzy Cognitive Maps (FCMs). The module provides tools for end-to-end projects involving FCMs. It is able to derive fuzzy causal weights from qualitative data or simulating the system behavior. Additionally, it includes machine learning algorithms (e.g., Nonlinear Hebbian Learning, Active Hebbian Learning, Genetic Algorithms, and Deterministic Learning) to adjust the FCM causal weight matrix and to solve classification problems. Finally, users can easily implement scenario analysis by simulating hypothetical interventions (i.e., analyzing what-if scenarios). FCMpy is the first open-source module that contains all the functionalities necessary for FCM oriented projects. This work aims to enable researchers from different areas, such as psychology, cognitive science, or engineering, to easily and efficiently develop and test their FCM models without the need for extensive programming knowledge.

Predictive analysis of COVID 19 disease based on mathematical modelling and machine learning techniques

ABSTRACT During the emergence of a novel pandemic, predictive modelling process is more important in the phase of public health planning and response. Relating models to data provides a view into unseen variables, such as the occurrence of cryptic transmission and the prevalence of infection. These models allow exploration of counterfactuals and hypothetical interventions. Predictive modelling is a valuable model based on the clear definition and estimation of the variables. Researchers or policy makers who use the model outputs have a clear understanding of what can and cannot be achieved by this method. The results of this study are suggested that substantially more cases were present in many countries than were reported in the official statistics. In this paper we have identified the potential discrepancy between reported cases and true disease burden provided a crucial early warning to the international community. In this research paper we proposed statistical modelling and data-driven computer simulations provided accurate projections of global epidemic dispersal, quantifying the role of physical distancing in places and reductions in international travel on the spatiotemporal pattern of spread of COVID-19 based on Linear regression analysis.

Racial/ethnic disparities in phthalate metabolite mixtures and risk of preterm birth: A pooled study of 16 US cohorts

BACKGROUND AND AIM. Environmental phthalate exposure is ubiquitous in pregnancy and may be a risk factor for preterm delivery. In the United States (US), large racial/ethnic disparities in phthalate exposure may be an important contributor to the racial/ethnic disparities in preterm birth. Utilizing the largest study of phthalates and preterm birth to date, we 1) investigated racial/ethnic disparities in phthalate exposure and 2) estimated how racial/ethnic disparities in preterm birth might improve by equitably reducing phthalate exposure. METHODS. We pooled individual-level data from 16 US cohorts (N=6,045) on 9 prenatal urinary phthalate metabolites. We categorized participant race/ethnicity as non-Hispanic white (43%), non-Hispanic Black (13%), Hispanic/Latina (38%), or Other (5%; based on sparsity of sub-categories). We investigated confounder-adjusted differences in urinary phthalate metabolite concentrations by maternal race/ethnicity. We used g-computation to estimate changes in preterm birth by race/ethnicity after simultaneous, racial/ethnic-specific reductions in the concentration of all 9 phthalate metabolites. Our hypothetical intervention eliminated racial/ethnic disparities in the distributions of metabolite concentrations. RESULTS. For 8 of the 9 phthalate metabolites, concentrations were highest among non-Hispanic Black participants and lowest among non-Hispanic whites. Covariate-adjusted differences in metabolite concentrations were most pronounced for monoethyl phthalate and mono-isobutyl phthalate, which were 143% (95% confidence interval [95CI]: 114%, 175%) and 80% (95CI: 66%, 95%) higher among non-Hispanic Black compared to non-Hispanic white participants, respectively. The hypothetical intervention to simultaneously reduce concentrations of metabolites by race/ethnicity, principally among non-white racial/ethnic groups, showed significant reductions in preterm birth. For non-Hispanic Black participants, the pre- and post-intervention probability of preterm birth was 117 (95CI: 94, 141) and 88 (95CI: 61, 118) preterm per 1,000 live births, respectively, representing a relative reduction of 25% (95CI: 16%, 35%). CONCLUSIONS. Considerable differences in exposure to phthalates could play an important role in the racial/ethnic disparities in preterm birth within the US.

Hypothetical interventions on dietary intakes to mitigate lead and cadmium induced mortality in US adults

Hypothetical interventions on dietary intakes to mitigate lead and cadmium induced mortality in US adults