Supporting Statement

PRA_SupportingStatement_CommunityRASPlanning_Aug2021.docx

NIST Generic Clearance for Community Resilience Data Collections

Supporting Statement

OMB: 0693-0078

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U.S. Department of Commerce

National Institute of Standards and Technology

Generic Clearance for Community Resilience Data Collections

OMB CONTROL NO. 0693-0078

Expiration Date 07/31/2022


Community Resilience, Adaptation, and Sustainability Planning User Elicitation




1. Explain who will be surveyed and why the group is appropriate to survey.


This study will gather information from community officials (e.g. municipal government staff) across the U.S. regarding their experiences and expectations with community planning related to resilience, climate change adaptation, and sustainability ("RAS planning"). The purpose of this research is to better understand the experiences and expectations of communities regarding RAS planning. Not enough is currently known about how U.S. communities approach these increasingly critical urban planning, infrastructure planning, and hazard mitigation issues; about the barriers that prevent related goals from being achieved; or about municipal staff needs and priorities for external information and support. Local government officials are appropriate to recruit for this survey because they have the necessary practical experience and technical knowledge to implement new theoretical, technical, and practical methods to enhance community resilience alongside addressing community climate change adaptation and community sustainability objectives.


2. Explain how the survey was developed including consultation with interested parties, pretesting, and responses to suggestions for improvement.


The survey was developed by members of the NIST Community Resilience Group, based on prior research conducted by the research team and a review of literature on related resilience, adaptation, and sustainability planning topics (Clavin et al. 2021). Based on our research interests in identifying the current experiences and barriers to RAS planning, the research team created initial survey items (self-generated), on questions such as respondents’ individual professional background related to RAS planning, their community’s prior efforts of RAS planning, barriers that they see as having prevented the effective pursuit of RAS planning, and their experience with, sources of, and future needs for external information and support regarding RAS planning.


The research team also gathered multiple iterations of instrument feedback from fellow internal NIST researchers, academic researchers, and community officials (the survey sample) to ensure that it covered desired topics while being clearly understandable to recipients. The final approved survey will be made available online using the SurveyMonkey platform, for which a license has been procured via the NIST Engineering Lab.



3. Explain how the survey will be conducted, how customers will be sampled if fewer than all customers will be surveyed, expected response rate, and actions your agency plans to take to improve the response rate.


A national online survey will be used to ask local staff with experience in RAS planning about (1) their individual and community background related to RAS planning; (2) prioritization and effectiveness of resilience, adaptation, and/or sustainability planning in their community; (3) any barriers that have prevented the effective pursuit of RAS planning; and (4) their experience with, sources of, and needs for external information and support regarding RAS planning. The sampling frame for this study includes community officials who have had professional experience with RAS planning, including but not limited to staff from offices of urban planning, city management/administration, emergency management, economic development, environmental management, parks and recreation, community resilience, community sustainability, and public works, as well as elected officials. The sample will be generated primarily by obtaining permission to utilize contact emails (email lists, listservs, newsletter lists) from national, regional, and state organizations and conferences affiliated with community RAS planning. An inventory of such organizations and conferences will be developed from the research team members’ existing knowledge and networks, as well as a comprehensive internet-based search conducted by a trained research assistant. After compiling the email lists, the master list will be assessed for obvious errors and to minimize the potential for duplication of recruitment emails.


For this study, we are interested in acquiring a sample that includes representation from across U.S. regions (e.g. Northeast, Midwest, Southwest) and community sizes (e.g. < 50,000; 50,000 < 100,000; 100,000 < 500,000), preferably with a large enough respondent subgroups within each category to perform comparative analyses. However, without knowing the exact makeup of the potential respondent contact lists (see prior paragraph), we are unable to estimate the exact number of community officials that will be reached out to. We will therefore set an upper threshold of 500 responses, after which we will close the survey (take it down and cut off responses). The survey is estimated to take 20 minutes per response, which results in 167 total burden hours (500 respondents x 20 mins per response = 10,000 min; 10,000 min / 60 min = 166.67 hours).


4. Describe how the results of the survey will be analyzed and used to generalize the results to the entire customer population.


Responses will be collected via (and some of the analysis will be conducted within) the SurveyMonkey platform. Additional analysis, especially of the optional open-ended responses, will be conducted using MaxQDA qualitative analysis software. Crosstab and regression analyses will form the bulk of the analytics for this study, along with qualitative analysis of the open-ended responses, and will be conducted by the research team (PI and co-PIs), with help from a trained research assistant(s).

File Typeapplication/vnd.openxmlformats-officedocument.wordprocessingml.document
AuthorHelgeson, Jennifer (Fed)
File Modified0000-00-00
File Created2022-06-24

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