Abstract (en): The National Longitudinal Study of Adolescent Health (Add Health) is a longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-1995 school year. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents' social, economic, psychological, and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. This component of the Add Health restricted data is the Biomarker Data. The Glucose/HbA1c data file contains two measures of glucose homeostasis based on assays of the Wave IV dried blood spots: Glucose (mg/dl) and Hemoglobin A1c (HbA1c, %). Six additional constructed measures -- fasting duration, classification of fasting glucose, classification of non-fasting glucose, classification of HbA1c, diabetes medication, and a joint classification of glucose, HbA1c, self-reported history of diabetes, and anti-diabetic medication use -- are also included. The Lipids data file contains measures of triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol, and total cholesterol to high-density lipoprotein cholesterol ratio. Additional variables include, measurement method for triglycerides (TG), total cholesterol (TC), high-density lipoprotein choleserol (HDL-C), Antihyperlipidemic medication use, joint classification of self-reported history of Hyperlipidemia and Antihyperlipidemic medication use, and fasting duration. For more information, please see the study website. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Standardized missing values.; Checked for undocumented or out-of-range codes.. Adolescents in grades 7-12 and their families. Wave I, Stage 1 School sample: stratified, random sample of all high schools in the United States. A school was eligible for the sample if it included an 11th grade and had a minimum enrollment of 30 students. A feeder school, a school that sent graduates to the high school and that included a 7th grade, was also recruited from the community. Wave I, Stage 2: An in-home sample of 27,000 adolescents was drawn consisting of a core sample from each community plus selected special over samples. Eligibility for over samples was determined by an adolescent's responses on the In-School Questionnaire. Adolescents could qualify for more than one sample. In addition, parents were asked to complete a questionnaire about family and relationships. The Wave II in-home interview sample is the same as the Wave I in-home interview sample, with a few exceptions. Information about neighborhoods/communities was gathered from a variety of previously published databases. Wave III: The in-home Wave III sample consists of Wave I respondents who could be located and re-interviewed six years later. Wave III also collected High School Transcript Release Forms as well as samples of urine and saliva. 2013-11-14 Public release of documentation guides and codebooks.2013-11-07 Part 4 was added and it includes new Biomarker Lipid Data.2013-03-08 Part 2 was updated following a resupply of the data by the Principal Investigators. Specifically, additional variables added to the data file, and CRP and EBV values have been recalculated, resulting in minimal changes to the data. The associated documentation and codebook files were also updated. Finally, a user guide describing measures of inflammation and immune function for Part 2 was also added.2012-11-07 The codebook associat...

The Panel Study of Income Dynamics–Social, Health, and Economic Longitudinal File (PSID-SHELF) provides an easy-to-use and harmonized longitudinal file for the Panel Study of Income Dynamics (PSID), the longest-running nationally representative household panel survey in the world.PSID-SHELF accentuates the PSID's strengths through (1) its household panel structure that follows the same families over multiple decades; and (2) its multigenerational genealogical design that follows the descendants of panel families that were originally sampled in 1968, with immigrant sample refreshers in 1997–1999 and 2017. Every individual who has ever been included in the PSID's main study is included in the PSID-SHELF data, with over 80,000 people observed, some of them across more than 40 survey waves (1968–present). The current version of PSID-SHELF includes 41 waves of survey data, ranging from 1968 to 2019.The file contains measures on a wide range of substantive topics from the PSID's individual and family files, including variables on demographics, family structure, educational attainment, family income, individual earnings, employment status, occupation, housing, and wealth—as well as the essential administrative variables pertaining to key survey identifiers, panel status, sample weights, and household relationship identifiers. PSID-SHELF thus covers some of the most central variables in PSID that have been collected for many years. PSID-SHELF can easily be merged with other PSID data products to add other public-use variables by linking variables based on a survey participant’s individual and family IDs.Despite a focus on longitudinally consistent measurement, many PSID variables change over waves, e.g., thanks to new code frames, topcodes, question splitting, or similar. PSID-SHELF provides harmonized measures to increase the ease of using PSID data, but by necessity this harmonization involves analytic decisions that users may or may not agree with. These decisions are described at a high level in the PSID-SHELF User Guide and Codebook, but only a close review of the Stata code used to construct variables in the data will fully reveal each analytic decision. The Stata code underlying PSID-SHELF is openly accessible not only to allow for such review but also to encourage users, as they become more comfortable with PSID, to use and alter the full code or selected code snippets for their own analytic purposes. PSID-SHELF is entirely based on publicly released data and therefore can be recreated by anyone who has registered for PSID data use.Despite careful and multiple code reviews, it is possible that the code used to produce PSID-SHELF contains errors. The authors therefore encourage users to review the codes carefully, to report any mistakes and errors to us (psidshelf.help@umich.edu), and take no responsibility for any errors arising from the provided codes and files. Current VersionPSID-SHELF, 1968–2019, Beta Release 2023.01Recommended CitationsPlease cite PSID-SHELF in any product that makes use of the data. Anyone who uses PSID-SHELF should cite the data or the PSID-SHELF User Guide and Codebook—and, as required by the PSID user agreement, the main PSID data.PSID-SHELF data:Pfeffer, Fabian T., Davis Daumler, and Esther M. Friedman. PSID-SHELF, 1968–2019: The PSID’s Social, Health, and Economic Longitudinal File (PSID-SHELF), Beta Release. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor],

Once-daily oral HIV pre-exposure prophylaxis (PrEP) is an effective strategy to prevent HIV, but is highly dependent on adherence. Men who have sex with men (MSM) who use substances face unique challenges maintaining PrEP adherence. Digital pill systems (DPS) allow for real-time adherence measurement through ingestible sensors. Integration of DPS technology with other digital health tools, such as digital phenotyping, may improve understanding of nonadherence triggers and development of personalized adherence interventions based on ingestion behavior. This study explored the willingness of MSM with substance use to share digital phenotypic data and interact with ancillary systems in the context of DPS-measured PrEP adherence. Adult MSM on PrEP with substance use were recruited through a social networking app. Participants were introduced to DPS technology and completed an assessment to measure willingness to participate in DPS-based PrEP adherence research, contribute digital phenotyping data, and interact with ancillary systems in the context of DPS-based research. Medical mistrust, daily worry about PrEP adherence, and substance use were also assessed. Participants who identified as cisgender male and were willing to participate in DPS-based research (N = 131) were included in this subsample analysis. Most were White (76.3%) and non-Hispanic (77.9%). Participants who reported daily PrEP adherence worry had 3.7 times greater odds (95% CI: 1.03, 13.4) of willingness to share biometric data via a wearable device paired to the DPS. Participants with daily PrEP adherence worry were more likely to be willing to share smartphone data (p = 0.006) and receive text messages surrounding their daily activities (p = 0.003), compared to those with less worry. MSM with substance use disorder, who worried about PrEP adherence, were willing to use DPS technology and share data required for digital phenotyping in the context of PrEP adherence measurement. Efforts to address medical mistrust can increase advantages of this technology for HIV prevention.

Abstract (en): A Data Guide for this study is available as a web page and for download. The India Human Development Survey 2005 (IHDS) is a nationally representative, multi-topic survey of 41,554 households in 1,503 villages and 971 urban neighborhoods across India. Two one-hour interviews in each household covered topics concerning health, education, employment, economic status, marriage, fertility, gender relations, and social capital. Children aged 8-11 completed short reading, writing and arithmetic tests. Additional village, school, and medical facility interviews are also available. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Created variable labels and/or value labels.; Standardized missing values.; Checked for undocumented or out-of-range codes.. Response Rates: Response rates were calculated as 82 percent for the recontact sample, 98 percent for the new sample, and 92 percent for the total response rate. Datasets:DS0: Study-Level FilesDS1: IndividualDS2: HouseholdDS3: MedicalDS4: Non-ResidentDS5: Primary SchoolDS6: Birth HistoryDS7: VillageDS8: Crops Nationally representative sample of Indian households. Smallest Geographic Unit: state Nationally representative, multi-topic survey of 41,554 households in 1,503 villages and 971 urban neighborhoods across India. 2018-08-08 Added an updated version of the Data Guide documentation.2017-05-10 Added Data Guide.2016-02-16 This collection has been updated with a user guide and revised questionnaires obtained from the India Human Development Survey Documentation page.2013-06-17 The Household data (Part 2) were updated to add the following eight variables that had been mistakenly omitted from the dataset: NWORK, NFARM, NANIMAL, NAGWAGE, NNONAG, NSALARY, NBUSINESS, and INCOTHER. The Household data codebook was also updated.2010-06-29 Additional documentation file has been added.2010-05-04 Additional documentation files have been added.2010-03-25 At the principal investigator's request, an ID variable was removed.2010-02-17 Added village-level and crop data as new parts2009-08-25 Added updated versions of the Medical and Primary School questionnaires.2009-06-22 Added updated versions of the Household and the Individual datasets, and added Medical, Non-Resident, School, and Birth History datasets.2009-02-10 Added the original questionnaires that were used during data collection.2008-12-11 At the principal investigator's request, an ID variable was removed and the citation was updated2008-08-22 The title for Part 1 has been revised and response rate information has been added. Funding insitution(s): United States Department of Health and Human Services. National Institutes of Health. Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD041455). record abstracts coded on-site observation cognitive assessment test face-to-face interview mixed mode on-site questionnaire