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How-To HINTS: A Practical Workshop

On May 4, 2016, presenters from the National Cancer Institute and the U.S. Food and Drug Administration came together to provide an overview of HINTS, review optimal ways for analyzing HINTS data, and present case studies that used HINTS data in an interactive workshop and webinar. Videos from this webinar are found below.

Dr. Brad Hesse of the National Cancer Institute (NCI) presents an introduction to the Health Information National Trends Survey (HINTS) during the May 4th event “How-To HINTS: A Practical Workshop”. This presentation reviews the history and goals of the HINTS program, discusses the HINTS sampling methodology, and the strengths and limitations of HINTS data.

Dr. Alexandra Greenberg of the Mayo Clinic (at the time of the presentation a part of the National Cancer Institute) discusses how to merge HINTS data over multiple cycles, using an example from a study using Healthy People 2020 benchmarks, during the May 4th event “How-To HINTS: A Practical Workshop”.

Dr. Richard Moser of the National Cancer Institute (NCI) presents a variety of analytic techniques for Health Information National Trends Survey (HINTS) data during the May 4th event “How-To HINTS: A Practical Workshop”. This presentation reviews importing and formatting HINTS data, using SUDAAN and SAS-callable SUDAAN for HINTS analyses, analytic recommendations for the latest HINTS dataset, and how to merge HINTS data across cycles.

Dr. Elisabeth Donaldson of the US Food and Drug Administration (FDA) discusses an example STATA analysis using HINTS-FDA data during the May 4th event “How-To HINTS: A Practical Workshop”.

Dr. Alexandra Greenberg of the Mayo Clinic (at the time of the presentation a part of the National Cancer Institute) discusses how to merge HINTS data over multiple cycles, using an example from a study using Healthy People 2020 benchmarks, during the May 4th event “How-To HINTS: A Practical Workshop”.

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HINTS Data Terms of Use

It is of utmost importance to ensure the confidentiality of survey participants. Every effort has been made to exclude identifying information on individual respondents from the computer files. Some demographic information such as sex, race, etc., has been included for research purposes. NCI expects that users of the data set will adhere to the strictest standards of ethical conduct for the analysis and reporting of nationally collected survey data. It is mandatory that all research results be presented/published in a manner that protects the integrity of the data and ensures the confidentiality of participants.

In order for the Health Information National Trends Survey (HINTS) to provide a public-use or another version of data to you, it is necessary that you agree to the following provisions.

  1. You will not present/publish data in which an individual can be identified. Publication of small cell sizes should be avoided.
  2. You will not attempt to link nor permit others to link the data with individually identified records in another database.
  3. You will not attempt to learn the identity of any person whose data are contained in the supplied file(s).
  4. If the identity of any person is discovered inadvertently, then the following should be done;
    1. no use will be made of this knowledge,
    2. the HINTS Program staff will be notified of the incident,
    3. no one else will be informed of the discovered identity.
  5. You will not release nor permit others to release the data in full or in part to any person except with the written approval of the HINTS Program staff.
  6. If accessing the data from a centralized location on a time sharing computer system or LAN, you will not share your logon name and password with any other individuals. You will also not allow any other individuals to use your computer account after you have logged on with your logon name and password.
  7. For all software provided by the HINTS Program, you will not copy, distribute, reverse engineer, profit from its sale or use, or incorporate it in any other software system.
  8. The source of information should be cited in all publications. The appropriate citation is associated with the data file used. Please see Suggested Citations in the Download HINTS Data section of this Web site, or the Readme.txt associated with the ASCII text version of the HINTS data.
  9. Analyses of large HINTS domains usually produce reliable estimates, but analyses of small domains may yield unreliable estimates, as indicated by their large variances. The analyst should pay particular attention to the standard error and coefficient of variation (relative standard error) for estimates of means, proportions, and totals, and the analyst should report these when writing up results. It is important that the analyst realizes that small sample sizes for particular analyses will tend to result in unstable estimates.
  10. You may receive periodic e-mail updates from the HINTS administrators.