2022 Request for Applications: Emotional Well-being and Health Data Analysis Award

By PAA Web posted 08-23-2022 13:46

  

Two research networks funded by the National Institutes of Health are requesting applications for analyses utilizing large scale cohort studies to examine psychosocial predictors and correlates of health and aging. The Network for Emotional Well-being: Science, Practice, and Measurement, a collaborative project between UCSF, UC Berkeley, and Harvard, in partnership with the NIA-funded Stress Measurement Network, will support applicants for secondary data analysis projects with a $10,000.00 Emotional Well-being & Health Data Analysis Award. We expect to give out 4-5 awards.

The goal of this award program is to support work that takes advantage of existing measures of psychosocial stress and/or of emotional well-being that are already available in large scale publicly available cohort studies. Cohorts that may be used include but are not limited to the Health and Retirement Study (HRS), Midlife in the United States Study (MIDUS), the English Longitudinal Study of Ageing (ELSA), the Survey of Health, Ageing, and Retirement in Europe (SHARE), the Mexican Health and Aging Study (MHAS), and Longitudinal Aging Study in India (LASI). It can also be useful to examine relationships in more than one country-wide study if harmonized measures are available. This award cannot be used for primary data collection or analysis of investigator-owned proprietary data but rather for analysis of existing data available through large-scale national public datasets.

Work involving human subjects is not eligible for the Data Analysis award. Data Fellowship funds must be used to support an applicant’s work analyzing data from existing, anonymize ddata available in large-scale cohort studies, and for writing up the findings in manuscripts that will be submitted to peer-reviewed journals.

For work considering emotional well-being, we are interested in analyses that specifically focus on positive emotional well-being, broadly defined as a multidimensional composite that encompasses how an individual feels generally, in the moment, and about life overall (features can include the emotional quality of everyday experiences as well as judgments about life satisfaction, sense of meaning or purpose in life, and other related concepts). For work considering stress, we are interested in analyses that leverage high quality stress measures. Applicants are encouraged to review the Stress Measurement Network’s website of relevant resources (www.stressmeasurement.org), and particularly to examine the Network’s joint stress variable harmonization project conducted along with the Gateway to Global Aging Data Initiative (see www.stressmeasurement.org/hrs-harmonization-project).

Applications should address one or more of these questions:

A. What forms of stress and/or emotional well-being predict health broadly defined over time (i.e. cognitive health, physical health, disability, and other aging-related outcomes)?

B. How do trajectories and experiences of stress and emotional well-being differ across time when comparing various demographic groups (e.g. age, race, gender, geographic region such as rural vs. urban, SES group)?

C. How do the circumstances in which people are born, grow, live, work, and age, or societal systems or structural factors interact with individual-level stress experiences and/or emotional well-being in ways that influence physical health outcomes? For example, applicants might consider effects of systemic racism (examples of potential measures here: www.stressmeasurement.org/systemic-racism-measures) or income inequality in different regions.

Analyses can utilize data from a single study or from two or more studies to compare patterns and findings cross-nationally. When describing their approach for the proposed research, applicants should include a description of their experience working with the proposed (or similar) dataset(s), provide some scientific premise for the research question, provide specificity regarding which measures of stress and/or emotional well-being they plan to use, describe their proposed analytic methods, and, if the applicant is still a trainee (doctoral student or post-doctoral fellow), describe the mentorship or team that will support the applicant in this effort. Information on many (but not all) existing freely available large-scale studies can be found through the Gateway to Global Aging Data (g2aging.org). If interested, the Networks may pair early stage investigators with expert mentors who are advisors to our networks and familiar with the datasets (please state if you are interested in this, at the end of your application).

Application: Please include a single PDF with PI last name as the filename that includes:

1) Project title and narrative description (up to 3 pages, single-spaced, excluding references). This narrative should include specific aims (including hypotheses), background and significance, analysis plan (including specificity on specific measures planned for use) and statistical approach, and a description of the research team, as well as the information noted above regarding experience with these types of datasets and analyses and a mentorship team if appropriate.

2) CV/Biosketch for all key study personnel.

Eligibility: Research scholars with an accredited University affiliation. We encourage early-stage investigators and under-represented minority scholars to apply. Postdocs and graduate students should send a letter of support from a faculty advisor. PIs on selected projects should be prepared to present initial analyses via videoconference in September 2023 to Network leadership, with projects completed by February 2024.

Date due: Accepting applications until November 11th, 2022.

Award announcements: November 30th, 2022.

Contact: Grant-specific questions can be directed to Dr. Emiliana Simon-Thomas at emotionalwellbeing@berkeley.edu. Scientific questions can be directed to Dr. Aric Prather (Aric.Prather@ucsf.edu).

Funding for these projects is provided by the National Institutes of Health (R24AG048024; U24AG072699)

See more.


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