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OBJECTIVES: We investigate the impact of data collection mode on responses to variables in NSHAP Round 4 and discuss how potential mode differences should (and should not) be addressed in substantive analyses. METHODS: Among the set of respondents who were eligible to be contacted remotely in Round 4, we randomly selected 398 to be contacted instead for an in-person interview. We compare response rates and the distributions of selected key outcomes among those 398 respondents to those among the control group who were initially approached remotely. As a contrast, we compare all R4 respondents according to the mode in which they completed the interview, including those not part of the randomized experiment. RESULTS: Among those included in the experiment, there was no evidence of systematic differences in responses to physical and mental health questions between remote and in-person modes, nor in responses to number recall measures. In-person respondents scored moderately lower on cognitive function measures requiring careful attention to a figure and/or task, though this difference became less with each similar item. Remote respondents named fewer social network members. Comparing all respondents according to their final mode yielded substantially different results in all cases. DISCUSSION: Mode did not appear to affect reports of physical and mental health based on a randomized comparison, though it did moderately affect other items in predictable ways. Naïve estimates of mode effects based on comparing all respondents according to mode yielded misleading results, and should not be used to adjust for mode differences in analyses.

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OBJECTIVES: This article, and corresponding articles for the earlier rounds of the National Social Life, Health, and Aging Project (NSHAP), provide the scientific underpinning for the statistical analysis of NSHAP data. The 2015-2016 round of data collection for NSHAP comprised the third wave of data collection for the original cohort born 1920-1947 (C1) and the first wave of data collection for a second cohort born 1948-1965 (C2). Here we describe (a) our protocol for reinterviewing C1; (b) our approach to the sample design for C2, including the frame construction, stratification, clustering, and within-household selection; and (c) the construction of cross-sectional weights for the entire 2015-2016 sample when analyzed at the individual level or when analyzed as a sample of cohabiting couples. We also provide guidance on computing design-based standard errors. METHODS: The sample for C2 was drawn independently of the C1 sample using the NORC U.S. National Sampling Frame. A probability sample of households containing at least one individual born 1948-1965 was drawn, and from these, each age-eligible individual was included together with their cohabiting spouse or partner (even if not age-eligible). This C2 sample was combined with the C1 sample to yield a sample representative of the U.S. population of adults born 1920-1965. RESULTS: Among C1, we conducted 2,409 interviews corresponding to a 91% conditional response rate (i.e., among previous respondents); the unconditional three-wave response rate for the original C1 sample was 71%. Among C2, we conducted 2,368 interviews corresponding to a response rate of 76%. DISCUSSION: Together C1 and C2 permit inference about the U.S. population of home-dwelling adults born from 1920 to 1965. In addition, three waves of data from C1 are now available, permitting longitudinal analyses of health outcomes and their determinants among older adults.

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OBJECTIVES: In this article, we seek to provide assistance to those who might want to use data from the National Social Life, Health, and Aging Project (NSHAP) Rounds 1-3 to compare those born in different cohorts. We outline 2 theoretical models that underlie the design of NSHAP-the life course model and the birth cohorts model-and review examples of social and political changes that may have differentially affected cohorts of older adults. Then we present 2 ways that NSHAP data might be used to compare cohorts, show examples of analyses of cohort differences in measures in NSHAP, and discuss features of the data that might affect their use for this purpose. METHODS: Round 3 of the NSHAP added a group of respondents born between 1948 and 1965, the Baby Boom. Together with data from an earlier cohort, interviewed in Rounds 1-3, these data allow analysis of birth cohorts of older adults in the United States. We show examples of some approaches. RESULTS: Our age-matched cohort differences approach included all observations where the respondent was aged 57-67 at the time of interview in different time periods (3,816 observations overall; 2,316 for the Silent Generation cohort and 1,500 for the Baby Boom cohort). Our second approach, age, period, and cohort effects, models the effects of age and birth year using restricted cubic splines, with one model excluding the linear effect of birth year, and the other excluding the linear effect of period. We present examples of analyses using each of these methods. DISCUSSION: We describe features of the NSHAP data of which researchers should be aware when conducting cohort analyses with these data.

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[This corrects the article DOI: 10.1371/journal.pone.0235191.].

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Leading academic institutions, governments, and funders of research across the world have spent the last few decades fretting publicly about the need for scientists and research organisations to engage more widely with the public and be open about their research. While a global literature asserts that public communication has changed from a virtue to a duty for scientists in many countries and disciplines, our knowledge about what research institutions are doing and what factors drive their 'going public' is very limited. Here we present the first cross-national study of N = 2,030 research institutes within universities and large scientific organisations in Brazil, Germany, Italy, Japan, the Netherlands, Portugal, the United Kingdom, and the United States of America. We find that institutes embrace communication with non-peers and do so through a variety of public events and traditional news media-less so through new media channels-and we find variation across countries and sciences, yet these are less evident than we expected. Country and disciplinary cultures contribute to the level of this communication, as do the resources that institutes make available for the effort; institutes with professionalised staff show higher activity online. Future research should examine whether a real change in the organisational culture is happening or whether this activity and resource allocation is merely a means to increase institutional visibility.

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This study investigated the relationship between religious influence and sexual expression in older Americans, with specific attention to gender. Using the National Social Life, Health, and Aging Project, a nationally-representative survey of older adults, we created a composite measure of religious influence on sexual expression using Latent Class Analysis. We found more variability within denominations than between in terms of membership in the high-influence class; this indicated that religious influence on sexual expression was diverse within faiths. We show that religious influence was associated with higher self-reported satisfaction with frequency of sex, as well as higher physical and emotional satisfaction with sex, but only for men. Men were also significantly more likely than women to report that they would only have sex with a person they love. These results persisted in the presence of controls for demographic characteristics, religious affiliation, church attendance, intrinsic religiosity, political ideology, and functional health.

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OBJECTIVES: The sample for the second wave (2010) of National Social Life, Health, and Aging Project (NSHAP) was designed to increase the scientific value of the Wave 1 (2005) data set by revisiting sample members 5 years after their initial interviews and augmenting this sample where possible. METHOD: There were 2 important innovations. First, the scope of the study was expanded by collecting data from coresident spouses or romantic partners. Second, to maximize the representativeness of the Wave 2 data, nonrespondents from Wave 1 were again approached for interview in the Wave 2 sample. RESULTS: The overall unconditional response rate for the Wave 2 panel was 74%; the conditional response rate of Wave 1 respondents was 89%; the conditional response rate of partners was 84%; and the conversion rate for Wave 1 nonrespondents was 26%. DISCUSSION: The inclusion of coresident partners enhanced the study by allowing the examination of how intimate, household relationships are related to health trajectories and by augmenting the size of the NSHAP sample size for this and future waves. The uncommon strategy of returning to Wave 1 nonrespondents reduced potential bias by ensuring that to the extent possible the whole of the original sample forms the basis for the field effort. NSHAP Wave 2 achieved its field objectives of consolidating the panel, recruiting their resident spouses or romantic partners, and converting a significant proportion of Wave 1 nonrespondents.

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OBJECTIVES: The paper discusses the sample design of the National Social Life, Health, and Aging Project (NSHAP) and how the design affects how estimates should be calculated from the survey data. The NSHAP study allows researchers to study the links between sexuality and health in older adults. The goal of the design was to represent adults aged 57-85 years in six demographic domains. METHODS: The sample design begins with a national area probability sample of households, carried out jointly with the 2004 round of the Health and Retirement Study. Selection of respondents for NSHAP balanced age and gender subgroups and oversampled African Americans and Latinos. Data collection was carried out from July 2005 to March 2006. RESULTS: The survey obtained an overall response rate of 75.5%. DISCUSSION: The complex sample design requires that the selection probabilities and the field implementation be accounted for in estimating population parameters. The data set contains weights to compensate for differential probabilities of selection and response rates among demographic groups. Analysts should use weights in constructing estimates from the survey and account for the complex sample design in estimating standard errors for survey estimates.

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The National Opinion Research Center, led by a team of investigators at the University of Chicago, conducted more than 3,000 in-person interviews with a nationally representative sample of adults aged 57-85 years. Data collection included in-person questionnaire items, an extensive array of biomeasures, and a postinterview self-administered questionnaire. The National Social Life, Health, and Aging Project (NSHAP) interview included the collection of 13 biomeasures: weight, waist circumference, height, blood pressure, smell, saliva collection, taste, a self-administered vaginal swab for female respondents, "Get Up and Go," distance vision, touch, oral mucosal transudate (Orasure) human immunodeficiency virus test, and blood spots. This article discusses the development of NSHAP's instruments and implementation of the study design. Measures, such as response and cooperation rates, are also provided to evaluate the effectiveness of the design and implementation.

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BACKGROUND: Despite the aging of the population, little is known about the sexual behaviors and sexual function of older people. METHODS: We report the prevalence of sexual activity, behaviors, and problems in a national probability sample of 3005 U.S. adults (1550 women and 1455 men) 57 to 85 years of age, and we describe the association of these variables with age and health status. RESULTS: The unweighted survey response rate for this probability sample was 74.8%, and the weighted response rate was 75.5%. The prevalence of sexual activity declined with age (73% among respondents who were 57 to 64 years of age, 53% among respondents who were 65 to 74 years of age, and 26% among respondents who were 75 to 85 years of age); women were significantly less likely than men at all ages to report sexual activity. Among respondents who were sexually active, about half of both men and women reported at least one bothersome sexual problem. The most prevalent sexual problems among women were low desire (43%), difficulty with vaginal lubrication (39%), and inability to climax (34%). Among men, the most prevalent sexual problems were erectile difficulties (37%). Fourteen percent of all men reported using medication or supplements to improve sexual function. Men and women who rated their health as being poor were less likely to be sexually active and, among respondents who were sexually active, were more likely to report sexual problems. A total of 38% of men and 22% of women reported having discussed sex with a physician since the age of 50 years. CONCLUSIONS: Many older adults are sexually active. Women are less likely than men to have a spousal or other intimate relationship and to be sexually active. Sexual problems are frequent among older adults, but these problems are infrequently discussed with physicians.

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