Loss to Follow-Up in Cohort Studies: How Much is Too Much?

Loss to follow-up is problematic in most cohort studies and often leads to bias. Although guidelines suggest acceptable follow-up rates, the authors are unaware of studies that test the validity of these recommendations. The objective of this study was to determine whether the recommended follow-up thresholds of 60-80% are associated with biased effects in cohort studies. A simulation study was conducted using 1000 computer replications of a cohort of 500 observations. The logistic regression model included a binary exposure and three confounders. Varied correlation structures of the data represented various levels of confounding. Differing levels of loss to follow-up were generated through three mechanisms: missing completely at random (MCAR), missing at random (MAR) and missing not at random (MNAR). The authors found no important bias with levels of loss that varied from 5 to 60% when loss to follow-up was related to MCAR or MAR mechanisms. However, when observations were lost to follow-up based on a MNAR mechanism, the authors found seriously biased estimates of the odds ratios with low levels of loss to follow-up. Loss to follow-up in cohort studies rarely occurs randomly. Therefore, when planning a cohort study, one should assume that loss to follow-up is MNAR and attempt to achieve the maximum follow-up rate possible.     

Tho’ Much is Taken,Much Abides: Asylum Seekers’ Subjective Wellbeing

The influence of psychosocial factors on the subjective wellbeing of asylum-seekers residing in host Western countries has scarcely been explored qualitatively. Qualitative data derived from a mixed methods prospective study investigated the subjective wellbeing of 56 community-dwelling asylum-seekers and refugees at baseline and an average of 15.7 months later. Positive and negative experiences over time were explored in relation to self-perceived emotional health. Nineteen positive and 15 negative categories of experience emerged. Distinct psychosocial and protective factors were salient regarding the valence of experiences over time, with positive experiences comprising employment, improved financial circumstances, and social support or connectivity. Negative experiences included news of adversity from one’s homeland, un(der)employment, poor health, and factors relating to the refugee determination process. Positive and negative experiences were contemporaneous, indicating that employment and social support may ameliorate the detrimental impact of traversing the protracted process of refugee status determination for asylum-seekers in particular.     

How Much Is Postacute Care Use Affected by Its Availability?

OBJECTIVE: To assess the relative impact of clinical factors versus nonclinical factors-such as postacute care (PAC) supply-in determining whether patients receive care from skilled nursing facilities (SNFs) or inpatient rehabilitation facilities (IRFs) after discharge from acute care. DATA SOURCES AND STUDY SETTING: Medicare acute hospital, IRF, and SNF claims provided data on PAC choices; predictors of site of PAC chosen were generated from Medicare claims, provider of services, enrollment file, and Area Resource File data. STUDY DESIGN: We used multinomial logit models to predict PAC use by elderly patients after hospitalizations for stroke, hip fractures, or lower extremity joint replacements. DATA COLLECTION/EXTRACTION METHODS: A file was constructed linking acute and postacute utilization data for all medicare patients hospitalized in 1999. PRINCIPAL FINDINGS: PAC availability is a more powerful predictor of PAC use than the clinical characteristics in many of our models. The effects of distance to providers and supply of providers are particularly clear in the choice between IRF and SNF care. The farther away the nearest IRF is, and the closer the nearest SNF is, the less likely a patient is to go to an IRF. Similarly, the fewer IRFs, and the more SNFs, there are in the patient's area the less likely the patient is to go to an IRF. In addition, if the hospital from which the patient is discharged has a related IRF or a related SNF the patient is more likely to go there. CONCLUSIONS: We find that the availability of PAC is a major determinant of whether patients use such care and which type of PAC facility they use. Further research is needed in order to evaluate whether these findings indicate that a greater supply of PAC leads to both higher use of institutional care and better outcomes-or whether it leads to unwarranted expenditures of resources and delays in returning patients to their homes.     

How Much Risk Pooling Is There in the Individual Insurance Market?

OBJECTIVE: To examine how much pooling of risks occurs among potential purchasers in the individual market, how much pooling occurs among those who purchase coverage, and whether there is greater pooling among longer-term enrollees. DATA SOURCES: The data are administrative records for enrollees in individual insurance plans in California in 2001, and from a survey of Californians enrolled in the individual insurance market and the uninsured. STUDY DESIGN: Logit models were estimated for 5 health outcome measures to compare the insured and uninsured after adjusting for other factors that affect insurance status and health. Multivariate models were also estimated to explore the relationship between health and three measures of pooling in the market: plan type, pricing tier, and the actuarially adjusted premium paid by the enrollee. PRINCIPAL FINDINGS: Those who purchase individual health insurance are in better health than those who remain uninsured. On the other hand, a large share of people with health problems does obtain individual insurance. The distribution of subscribers across plan type and pricing tier varies with their health status. Those in poor health are less likely to purchase low benefit plans. There is less separation of risks for those who become sick after enrollment based on the measure of pricing tier. The distribution of subscribers across plan type for those who have health problems at enrollment and those who become sick differs, but so does the distribution of those who become sick and those who remain healthy. CONCLUSIONS: Despite small differences among the healthy and sick, our results support the conclusion that there is considerable risk pooling in the individual market. To some extent, this pooling occurs because underwriting happens at the time people enroll and there is greater pooling among those who become sick than those who enroll sick. Our results however suggest that health savings accounts may further fragment the market.     

How Much Money Is Enough? Poverty and Health in Older People

The journal of nutrition, health & aging - We examined the relationship between absolute income, adequacy of disposable income, and self-rated health among participants aged 60 years and over....     

How Much Positivity Is Needed to Buffer the Impact of Parental Negativity on Children?

Previous research suggests that a couple's ability to balance adverse interactions with positivity is a better predictor of relationship outcomes than negativity per se. The purpose of this study was to extend the findings on couples to parents by examining the positive‐to‐negative ratio in parental interaction as a predictor of child adjustment. Three hundred seventy‐five parents completed questionnaires on the negative and positive interactions in their intimate relationship and their child's functioning online. Different interparental positive–negative ratios were identified by latent class analysis and then linked to children's adjustment. Children whose parents were characterized by more negativity relative to positivity scored higher in externalizing problems compared to children whose parents' negativity was outbalanced by positive interactions. Girls with parents yielding the highest positive–negative ratios were reported to show most prosocial behavior. The findings suggest that parental positivity should be expressed at least twice as much as parental negativity for the sake of children's well‐being.     

A Food,a Bite,a Sip: How Much Allergen Is in That?

Detailed information about the amount of allergenic protein ingested by the patient prior to an allergic reaction yields valuable information for the diagnosis, guidance and management of food allergy. However, the exact amount of ingredients is often not declared on the label. In this study the feasibility was studied for estimating the amount of allergenic protein from milk, eggs, peanuts and hazelnuts in frequently consumed composite and non-composite foods and per bite or sip size in different age groups in the Netherlands. Foods containing milk, egg, peanut or hazelnut most frequently consumed were selected for the age groups 2–3, 4–6 and 19–30 years. If the label did not yield clear information, the amount of allergenic protein was estimated based on food labels. Bite or sip sizes were determined in these age groups in 30 different foods. The amount of allergenic protein could be estimated in 47/70 (67%) of composite foods, which was complex. Estimated protein content of milk, egg, peanut and hazelnut was 2–3 g for most foods but varied greatly from 3 to 8610 mg and may be below threshold levels of the patient. In contrast, a single bite or sip can contain a sufficient amount of allergenic protein to elicit an allergic reaction. Bite and sip sizes increased with age. In every day practice it is hard to obtain detailed and reliable information about the amount of allergenic protein incorporated in composite foods. We encourage companies to disclose the amount of common allergenic foods on their labels.     

The Contingency of Contingent Valuation How Much Are People Willing to Pay against Alzheimer's Disease?

The present work focuses on the choice of the elicitation technique within a contingent valuation (CV) framework. We simultaneously apply three different elicitation techniques to elicit willingness-to-pay (WTP) values for three programs against Alzheimer's disease. First, the dichotomous choice approach is used, which is the standard procedure. However, giving respondents only a yes/no response alternative seems to result in overestimated WTP values. Therefore, we secondly apply the dissonance-minimizing format which screens respondents for their preferences and thus avoids possible yea-saying and protest answers against the payment vehicle. The third format, a modified version of the payment card, allows respondents to express a level of voting certainty and to make less of a commitment. With our findings we show that a well-designed CV method is a suitable instrument for helping decision makers in the health care sector and that the Swiss population favors highly a program which improves the situation of informal caregivers.     

How Much Does Gender Explain in Sexual Attitudes and Behaviors? A Survey of Canadian Adults

While it is common for gender to be included as a predictor variable in studies of sexuality, this is not the case for other demographic variables. This study examined the predictive value of gender, along with other demographic variables, including age, marital status, education, religiosity, and geographic region using data from a national survey of Canadian adults over the age of 18 (N = 1479). The survey was conducted by the COMPAS survey organization using computer assisted telephone technology. The outcome variables examined included frequency of sexual thoughts, oral sex, age at first intercourse, number of sexual partners, and casual sex intentions. For each of the variables, men were more sexually permissive and more sexually active than were women. Other demographic variables increased the explanatory power of the models but gender still remained a significant predictor of sexual attitudes and behaviors despite statistical control for other demographic variables. The findings demonstrate the influence of gender on sexuality but also illustrate the value of taking into account other demographic variables when analyzing gender differences in sexuality.     

Too Much Ado about Instrumental Variable Approach: Is the Cure Worse than the Disease?

ObjectiveTo review the efficacy of instrumental variable (IV) models in addressing a variety of assumption violations to ensure standard ordinary least squares (OLS) estimates are consistent. IV models gained popularity in outcomes research because of their ability to consistently estimate the average causal effects even in the presence of unmeasured confounding. However, in order for this consistent estimation to be achieved, several conditions must hold. In this article, we provide an overview of the IV approach, examine possible tests to check the prerequisite conditions, and illustrate how weak instruments may produce inconsistent and inefficient results.MethodsWe use two IVs and apply Shea's partial R-square method, the Anderson canonical correlation, and Cragg–Donald tests to check for weak instruments. Hall–Peixe tests are applied to see if any of these instruments are redundant in the analysis.ResultsA total of 14,952 asthma patients from the MarketScan Commercial Claims and Encounters Database were examined in this study. Patient health care was provided under a variety of fee-for-service, fully capitated, and partially capitated health plans, including preferred provider organizations, point of service plans, indemnity plans, and health maintenance organizations. We used controller–reliever copay ratio and physician practice/prescribing patterns as an instrument. We demonstrated that the former was a weak and redundant instrument producing inconsistent and inefficient estimates of the effect of treatment. The results were worse than the results from standard regression analysis.ConclusionDespite the obvious benefit of IV models, the method should not be used blindly. Several strong conditions are required for these models to work, and each of them should be tested. Otherwise, bias and precision of the results will be statistically worse than the results achieved by simply using standard OLS.     

Much Ado about nothing? The responsiveness of the healthcare system in Poland through patients’ eyes

This article analyzes the outcomes of the key healthcare reforms undertaken in Poland and assesses how successful they have been. Contrary to the governmental perspective on success, understood in terms of economic efficiency, we define it in terms of patient satisfaction. As such, health policy is treated as a political system’s response to the problems emerging in the public agenda. The analysis therefore focuses on the responsiveness of the healthcare system through patients’ eyes.This analysis takes three main reforms undertaken in post-1989 Poland as reference points. These were: Regional Sickness Funds (Kasy Chorych, 1999); the National Health Fund (Narodowy Fundusz Zdrowia, 2003/2004); and the waiting lists package and the oncological package (pakiet kolejkowy and pakiet onkologiczny, 2015). Each introduced key institutional changes, but also sparked media interest, public attention, and mass discourse. The article presents the main goals and the most important consequences of the reforms for patients.For the purposes of the analysis, the following patient-oriented indicators of reform success were chosen: (1) public satisfaction with healthcare, (2) waiting times, (3) number of health professionals. The assembled data from national and international databases leads to the conclusion that the reforms have not succeeded.