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511 Automation of Home Food Inventory Scoring to Standardize Reporting, Enhance Clinical Utility, and Operationalize Delivery of Personalized Behavioral Targets

OBJECTIVES/GOALS: The Fulkerson Home Food Inventory (HFI) is widely used to assess the home food environment, a key target of behavioral weight loss trials. However, no standardized report is available. We created publicly available procedures to automate and standardize HFI reporting, yielding a pe...

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Autores principales: Bean, Melanie, Smith, Danyel, Farthing, Sarah, Adams, Elizabeth, Naumann, Thomas, Meyer, Morgan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209077/
http://dx.doi.org/10.1017/cts.2022.305
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author Bean, Melanie
Smith, Danyel
Farthing, Sarah
Adams, Elizabeth
Naumann, Thomas
Meyer, Morgan
author_facet Bean, Melanie
Smith, Danyel
Farthing, Sarah
Adams, Elizabeth
Naumann, Thomas
Meyer, Morgan
author_sort Bean, Melanie
collection PubMed
description OBJECTIVES/GOALS: The Fulkerson Home Food Inventory (HFI) is widely used to assess the home food environment, a key target of behavioral weight loss trials. However, no standardized report is available. We created publicly available procedures to automate and standardize HFI reporting, yielding a personalized report to enhance this measures clinical utility. METHODS/STUDY POPULATION: Parents in the TEENS adolescent behavioral weight loss trial complete the HFI at 0-, 2-, 4-, 8-, and 12m and receive personalized reports at each timepoint. In REDCap, participants identify foods available in their home. HFI syntax is applied to calculate the obesogenic home food availability score. Categories of foods found are identified, with specific guidance provided to enhance their home food environment. Prior to automation, procedures were time intensive and error prone. To address this, HFI data are exported into Excel by a PowerShell (v7.2) command-line script using Python (v3.10) with the REDCap API. Results are calculated with F# (v6.0) using Microsoft Excel Interop API and inserted into a report template with F# using the Microsoft Publisher Interop API. This process is repeated at each timepoint. RESULTS/ANTICIPATED RESULTS: The new automated procedures significantly reduce time to generate reports and enhance accuracy. Procedures yield a 2-page individualized report that includes the obesogenic home food environment score and identifies categories of healthy items found (e.g., fruits, vegetables, whole grains) as well as areas of improvement (e.g., high-fat dairy products, processed meats). Specific items found in each category are identified. The report identifies food found in the home (e.g., chicken nuggets) with suggested healthier substitutions (e.g., lean chicken breast). This syntax and commands will be made publicly available for use in the scientific and clinical community. DISCUSSION/SIGNIFICANCE: These publicly available procedures optimize, automate, and standardize reporting for the HFI. Procedures improve efficiency within large-scale clinical trials and yield a personalized report to enhance the clinical utility of this measure and empower participants to make informed decisions about their health behaviors.
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spelling pubmed-92090772022-07-01 511 Automation of Home Food Inventory Scoring to Standardize Reporting, Enhance Clinical Utility, and Operationalize Delivery of Personalized Behavioral Targets Bean, Melanie Smith, Danyel Farthing, Sarah Adams, Elizabeth Naumann, Thomas Meyer, Morgan J Clin Transl Sci Workforce Development OBJECTIVES/GOALS: The Fulkerson Home Food Inventory (HFI) is widely used to assess the home food environment, a key target of behavioral weight loss trials. However, no standardized report is available. We created publicly available procedures to automate and standardize HFI reporting, yielding a personalized report to enhance this measures clinical utility. METHODS/STUDY POPULATION: Parents in the TEENS adolescent behavioral weight loss trial complete the HFI at 0-, 2-, 4-, 8-, and 12m and receive personalized reports at each timepoint. In REDCap, participants identify foods available in their home. HFI syntax is applied to calculate the obesogenic home food availability score. Categories of foods found are identified, with specific guidance provided to enhance their home food environment. Prior to automation, procedures were time intensive and error prone. To address this, HFI data are exported into Excel by a PowerShell (v7.2) command-line script using Python (v3.10) with the REDCap API. Results are calculated with F# (v6.0) using Microsoft Excel Interop API and inserted into a report template with F# using the Microsoft Publisher Interop API. This process is repeated at each timepoint. RESULTS/ANTICIPATED RESULTS: The new automated procedures significantly reduce time to generate reports and enhance accuracy. Procedures yield a 2-page individualized report that includes the obesogenic home food environment score and identifies categories of healthy items found (e.g., fruits, vegetables, whole grains) as well as areas of improvement (e.g., high-fat dairy products, processed meats). Specific items found in each category are identified. The report identifies food found in the home (e.g., chicken nuggets) with suggested healthier substitutions (e.g., lean chicken breast). This syntax and commands will be made publicly available for use in the scientific and clinical community. DISCUSSION/SIGNIFICANCE: These publicly available procedures optimize, automate, and standardize reporting for the HFI. Procedures improve efficiency within large-scale clinical trials and yield a personalized report to enhance the clinical utility of this measure and empower participants to make informed decisions about their health behaviors. Cambridge University Press 2022-04-19 /pmc/articles/PMC9209077/ http://dx.doi.org/10.1017/cts.2022.305 Text en © The Association for Clinical and Translational Science 2022 https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
spellingShingle Workforce Development
Bean, Melanie
Smith, Danyel
Farthing, Sarah
Adams, Elizabeth
Naumann, Thomas
Meyer, Morgan
511 Automation of Home Food Inventory Scoring to Standardize Reporting, Enhance Clinical Utility, and Operationalize Delivery of Personalized Behavioral Targets
title 511 Automation of Home Food Inventory Scoring to Standardize Reporting, Enhance Clinical Utility, and Operationalize Delivery of Personalized Behavioral Targets
title_full 511 Automation of Home Food Inventory Scoring to Standardize Reporting, Enhance Clinical Utility, and Operationalize Delivery of Personalized Behavioral Targets
title_fullStr 511 Automation of Home Food Inventory Scoring to Standardize Reporting, Enhance Clinical Utility, and Operationalize Delivery of Personalized Behavioral Targets
title_full_unstemmed 511 Automation of Home Food Inventory Scoring to Standardize Reporting, Enhance Clinical Utility, and Operationalize Delivery of Personalized Behavioral Targets
title_short 511 Automation of Home Food Inventory Scoring to Standardize Reporting, Enhance Clinical Utility, and Operationalize Delivery of Personalized Behavioral Targets
title_sort 511 automation of home food inventory scoring to standardize reporting, enhance clinical utility, and operationalize delivery of personalized behavioral targets
topic Workforce Development
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209077/
http://dx.doi.org/10.1017/cts.2022.305
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