August 14, 2018
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August 22, 2018
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July 12, 2019
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September 24, 2014
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May 2, 2017 (Final data collection date for primary outcome measure)
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- change in # of vegetable servings consumed by child measured by averaging vegetable serving data extracted from 3, 24-hr recalls. [ Time Frame: change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention) ]
Number of vegetable servings were assessed from 3, 24-hr dietary recalls, collected by trained study personnel in-person and over the phone from each child, using Nutrition Data System for Research (NDSR®)software). The 3, 24-hr recalls were averaged to come up with an aggregate # of vegetable servings.
- change in # of vegetable servings consumed by child measured by averaging vegetable serving data extracted from 3, 24-hr recalls. [ Time Frame: change from baseline to 6 months post-baseline ]
Number of vegetable servings were assessed from 3, 24-hr dietary recalls, collected by trained study personnel in-person and over the phone from each child, using Nutrition Data System for Research (NDSR®)software). The 3, 24-hr recalls were averaged to come up with an aggregate # of vegetable servings.
- change in # of vegetable servings consumed by child measured by averaging vegetable serving data extracted from 3, 24-hr recalls. [ Time Frame: change from baseline to 12 months post-baseline ]
Number of vegetable servings were assessed from 3, 24-hr dietary recalls, collected by trained study personnel in-person and over the phone from each child, using Nutrition Data System for Research (NDSR®)software). The 3, 24-hr recalls were averaged to come up with an aggregate # of vegetable servings.
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Same as current
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- change in liking of vegetables by child (liking rating scale was comprised of values across a 10-point labeled hedonic scale (1 -"Hate it" to 5 - "It's okay" to 10 - "Love it")) [ Time Frame: change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention) ]
Each child rated his/her liking of 37 different vegetables.The liking rating scale was comprised of values across a 10-point labeled hedonic scale (1 -"Hate it" to 5 - "It's okay" to 10 - "Love it"). This type of liking rating scale has been validated for testing with children. (Kroll, B.J. 1990. Evaluating rating scales for sensory testing with children. Food Technology, 44(11), 78-86.) An aggregate vegetable liking score representing mean liking rating across all vegetables was calculated for each child.
- change in liking of vegetables by child ( liking rating scale was comprised of values across a 10-point labeled hedonic scale (1 -"Hate it" to 5 - "It's okay" to 10 - "Love it")) [ Time Frame: change from baseline to 6-months post baseline ]
Each child rated his/her liking of 37 different vegetables.The liking rating scale was comprised of values across a 10-point labeled hedonic scale (1 -"Hate it" to 5 - "It's okay" to 10 - "Love it"). This type of liking rating scale has been validated for testing with children. (Kroll, B.J. 1990. Evaluating rating scales for sensory testing with children. Food Technology, 44(11), 78-86.) An aggregate vegetable liking score representing mean liking rating across all vegetables was calculated for each child.
- change in liking of vegetables by child ( liking rating scale was comprised of values across a 10-point labeled hedonic scale (1 -"Hate it" to 5 - "It's okay" to 10 - "Love it")) [ Time Frame: change from baseline to 12-months post baseline ]
Each child rated his/her liking of 37 different vegetables.The liking rating scale was comprised of values across a 10-point labeled hedonic scale (1 -"Hate it" to 5 - "It's okay" to 10 - "Love it"). This type of liking rating scale has been validated for testing with children. (Kroll, B.J. 1990. Evaluating rating scales for sensory testing with children. Food Technology, 44(11), 78-86.) An aggregate vegetable liking score representing mean liking rating across all vegetables was calculated for each child.
- change in number different of vegetables tried by child [ Time Frame: change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention) ]
Each child was asked the question "Have you ever tried (name of vegetable)" with following response options: Yes/No/Don't know. An aggregate score per child was tabulated by summing all "yes" answers.
- change in number different of vegetables tried by child [ Time Frame: change from baseline to 6-months post-baseline ]
Each child was asked the question "Have you ever tried (name of vegetable)" with following response options: Yes/No/Don't know. An aggregate score per child was tabulated by summing all "yes" answers.
- change in number different of vegetables tried by child [ Time Frame: change from baseline to 12-months post-baseline ]
Each child was asked the question "Have you ever tried (name of vegetable)" with following response options: Yes/No/Don't know. An aggregate score per child was tabulated by summing all "yes" answers.
- change in number of available vegetables in the child's home [ Time Frame: change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention) ]
Each of the child's parent was asked to complete a validated Home Food Inventory developed by Fulkerson and colleagues [Fulkerson JA, Nelson MC, Lytle L, Moe S, Heitzler C, Pasch KE. The validation of a home food inventory. Int J Behav Nutr Phys Act. 2008;5:55. doi:10.1186/1479-5868-5-55], to self-report the availability of different vegetables currently in their home. Response options for each question asking if the vegetable was currently in the home were "yes /no/ don't know" . Final number of available vegetables in the home was calculated by summing the number of vegetables for which the parent answered "yes."
- change in number of available vegetables in the child's home [ Time Frame: change from baseline to 6-months post baseline ]
Each of the child's parent was asked to complete a validated Home Food Inventory developed by Fulkerson and colleagues [Fulkerson JA, Nelson MC, Lytle L, Moe S, Heitzler C, Pasch KE. The validation of a home food inventory. Int J Behav Nutr Phys Act. 2008;5:55. doi:10.1186/1479-5868-5-55], to self-report the availability of different vegetables currently in their home. Response options for each question asking if the vegetable was currently in the home were "yes /no/ don't know" .Final number of available vegetables in the home was calculated by summing the number of vegetables for which the parent answered "yes."
- change in number of available vegetables in the child's home [ Time Frame: change from baseline to 12-months post baseline ]
Each of the child's parent was asked to complete a validated Home Food Inventory developed by Fulkerson and colleagues [Fulkerson JA, Nelson MC, Lytle L, Moe S, Heitzler C, Pasch KE. The validation of a home food inventory. Int J Behav Nutr Phys Act. 2008;5:55. doi:10.1186/1479-5868-5-55], to self-report the availability of different vegetables currently in their home. Response options for each question asking if the vegetable was currently in the home were "yes /no/ don't know" . Final number of available vegetables in the home was calculated by summing the number of vegetables for which the parent answered "yes."
- change in child's body mass index (as measured by collected height (m) and weight (kg) from child) [ Time Frame: change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention) ]
Child Body Mass Index (BMI) was calculated from collected height and weight of child that were combined to report BMI in kg/m^2
- change in child's body mass index (as measured by collected height (m) and weight (kg) from child) [ Time Frame: change from baseline to 6-months post baseline ]
Child Body Mass Index (BMI) was calculated from collected height and weight of child that were combined to report BMI in kg/m^2
- change in child's body mass index (as measured by collected height (m) and weight (kg) from child) [ Time Frame: change from baseline to 12-months post baseline ]
Child Body Mass Index (BMI) was calculated from collected height and weight of child that were combined to report BMI in kg/m^2
- change in child's Healthy Eating Index 2010 score (a measure of dietary quality) [ Time Frame: change from baseline to immediate post-intervention (i.e, 9 weeks post-baseline) ]
Child dietary data was assessed through from 3, 24-hr dietary recalls, collected by trained study personnel in-person and over the phone using Nutrition Data System for Research (NDSR) software.The 3, 24-hr recalls were averaged to come up with an aggregate score for each nutrient. NDSR data was imported into a SAS® program (version 9.4) (SAS Institute Inc. Cary, NC 2014), created by National Institutes of Health-NCI, Division of Cancer Control & Population Studies that calculated a Healthy Eating Index 2010 score, a validated measure of dietary quality, for each child (Guenther PM, Casavale KO, Reedy J, Kirkpatrick SI, Hiza HAB, Kuczynski KJ, et al. Update of the Healthy Eating Index: HEI-2010. J Acad Nutr Diet. 2013;113:569-80..
- change in child's Healthy Eating Index 2010 score (a measure of dietary quality) [ Time Frame: change from baseline to 6-months post baseline ]
Child dietary data was assessed through from 3, 24-hr dietary recalls, collected by trained study personnel in -person and over the phone using Nutrition Data System for Research (NDSR) software.The 3, 24-hr recalls were averaged to come up with an aggregate score for each nutrient. NDSR data was imported into a SAS® program (version 9.4) (SAS Institute Inc. Cary, NC 2014), created by National Institutes of Health-NCI, Division of Cancer Control & Population Studies that calculated a Healthy Eating Index 2010 score, a validated measure of dietary quality, for each child.
- change in child's Healthy Eating Index 2010 score (a measure of dietary quality) [ Time Frame: change from baseline to 12-months post baseline ]
Child dietary data was assessed through from 3, 24-hr dietary recalls, collected by trained study personnel in -person and over the phone using Nutrition Data System for Research (NDSR) software.The 3, 24-hr recalls were averaged to come up with an aggregate score for each nutrient. NDSR data was imported into a SAS® program (version 9.4) (SAS Institute Inc. Cary, NC 2014), created by National Institutes of Health-NCI, Division of Cancer Control & Population Studies that calculated a Healthy Eating Index 2010 score, a validated measure of dietary quality, for each child.
- change in child's dietary energy (in kilocalories) intake [ Time Frame: change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention) ]
Child dietary data was assessed through from 3, 24-hr dietary recalls, collected by trained study personnel in -person and over the phone using Nutrition Data System for Research (NDSR) software.The 3, 24-hr recalls were averaged to come up with an aggregate score for each nutrient (e.g., dietary energy in kilocalories)
- change in child's dietary energy (in kilocalories) intake [ Time Frame: change from baseline to 6-months post-baseline ]
Child dietary data was assessed through from 3, 24-hr dietary recalls, collected by trained study personnel in -person and over the phone using Nutrition Data System for Research (NDSR) software.The 3, 24-hr recalls were averaged to come up with an aggregate score for each nutrient (e.g., dietary energy in kilocalories)
- change in child's dietary energy (in kilocalories) intake [ Time Frame: change from baseline to 12-months post-baseline ]
Child dietary data was assessed through from 3, 24-hr dietary recalls, collected by trained study personnel in -person and over the phone using Nutrition Data System for Research (NDSR) software.The 3, 24-hr recalls were averaged to come up with an aggregate score for each nutrient (e.g., dietary energy in kilocalories)
- change in child cooking skills self-efficacy as measured by a validated survey to measure child cooking self-efficacy [ Time Frame: change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention) ]
Child cooking skills self-efficacy was measured using scales that have shown internal consistency and test-retest reliability in a psychometric evaluation of a cooking-based nutrition education intervention among low-income 9-11 year old children (Cronbach α = ≥ 0.74, test-retest r ≥ 0.66).(Lohse B, Cunningham-Sabo L, Walters LM, Stacey JE. Valid and Reliable Measures of Cognitive Behaviors toward Fruits and Vegetables for Children Aged 9 to 11 Years. J Nutr Educ Behav. 2011;43:42-49. doi:10.1016/j.jneb.2009.12.006). Response options for the child self-efficacy questions: 1 = YES! - 5 = NO!). The child-self-efficacy scale was calculated by summing 8 items measuring self-efficacy. A lower score indicated greater self-efficacy and more positive attitudes toward cooking.
- change in adult cooking skills confidence as measured by a validated survey to measure adult cooking confidence. Response options for the cooking confidence questions: (4 items, 1 = not at all confident - 5 = very confident). [ Time Frame: change from baseline to 9 weeks post-baseline (i.e., immediate post-intervention) ]
Parents completed the Cooking Matters for Families Before and After Course Survey to assess change in cooking skills confidence. Internal consistency and ability of the scales to reflect positive self-reported changes were previously among low-income adults (Pinard CA, Uvena LM, Quam JB, Smith TM, Yaroch AL. Development and testing of a revised cooking matters for adults survey. Am J Health Behav. 2015;39(6):866-873. doi:10.5993/AJHB.39.6.14). Response options for the 4 cooking confidence questions: (4 items, 1 = not at all confident - 5 = very confident). An aggregate score for each parent was tabulated by averaging the 4 questions. A higher score indicated greater cooking skills confidence.
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Same as current
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Not Provided
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Not Provided
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A Trial to Increase Child Vegetable Intake Through Behavioral Strategies
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A Controlled-intervention Trial to Increase Child Vegetable Intake Through Parent-implemented Behavioral Strategies
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A community nutrition trial among a diverse low-income population that tested the effect of parent-child cooking nutrition intervention on vegetable intake among 9-12 children.
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This study was a nonrandomized, controlled trial to determine whether a series of 6 weekly parent-child vegetable cooking skills classes and parent-led strategies informed by behavioral economics (1/week) (intervention group) improved dietary and non-dietary outcomes of a racially and ethnically diverse sample of low-income children (ages 9-12) more than a vegetable cooking skills program alone (control group).
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Interventional
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Not Applicable
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Allocation: Non-Randomized Intervention Model: Parallel Assignment Intervention Model Description: controlled, non-randomized community nutrition intervention Masking: Single (Participant) Primary Purpose: Prevention
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Obesity, Childhood
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Behavioral: Parent-led behavioral strategies
Intervention parents participated in an additional 20-25-min segment led by the nutrition educator during which the week's behavioral strategy was introduced. The following six behavioral strategies were introduced (one each week) as a segment of each cooking skills session: 1) have your child help prepare vegetables for meals (Child Help), 2) use a plate that shows the amount of vegetables to include for a meal (My Plate), 3) make vegetables visible and accessible by removing other foods from the dining area during the meal and leaving the vegetables (Make Avail/Visible), 4) serve at least 2 vegetables with the meal (Serve 2), 5) serve vegetables before the meal (Serve First), and 6) use a bigger spoon to serve the vegetables (Big Spoon).
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- Experimental: Intervention
The intervention consisted of an enhanced Cooking Matters® for Families program that included behavioral strategies derived from behavioral economics, to be implemented by parents at home for increasing vegetable intake of low-income 9-12 year old children
Intervention: Behavioral: Parent-led behavioral strategies
- No Intervention: Control
The control arm consisted of the enhanced Cooking Matters® for Families program alone--without lessons about the behavioral strategies for the parents
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- Overcash F, Ritter A, Mann T, Mykerezi E, Redden J, Rendahl A, Vickers Z, Reicks M. Impacts of a Vegetable Cooking Skills Program Among Low-Income Parents and Children. J Nutr Educ Behav. 2018 Sep;50(8):795-802. doi: 10.1016/j.jneb.2017.10.016. Epub 2017 Dec 12.
- Overcash FM, Reicks M, Ritter A, Leak TM, Swenson A, Vickers Z. Children Residing in Low-Income Households Like a Variety of Vegetables. Foods. 2018 Jul 20;7(7). pii: E116. doi: 10.3390/foods7070116.
- Overcash FM, Vickers Z, Ritter AE, Mann T, Mykerezi E, Redden J, Rendahl AK, Davey C, Reicks M. An in-home intervention of parent-implemented strategies to increase child vegetable intake: results from a non-randomized cluster-allocated community trial. BMC Public Health. 2019 Jul 4;19(1):881. doi: 10.1186/s12889-019-7079-4.
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Completed
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103
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Same as current
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May 2, 2017
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May 2, 2017 (Final data collection date for primary outcome measure)
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Inclusion Criteria:
- Participant child must be 9-12 years old
- Parent must be the main food preparer for the household
- The family must qualify for some form of public assistance
- Have a phone
- Must not have participated in a previous Cooking Matters for Families in the past 3 years
- Be able to read, speak, and understand English (or Spanish for Spanish-only courses).
Exclusion criteria:
*No exclusions other than those that do not meet inclusion criteria
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Sexes Eligible for Study: |
All |
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9 Years and older (Child, Adult, Older Adult)
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Yes
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Contact information is only displayed when the study is recruiting subjects
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Not Provided
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NCT03641521
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1111S06501
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No
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Studies a U.S. FDA-regulated Drug Product: |
No |
Studies a U.S. FDA-regulated Device Product: |
No |
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Plan to Share IPD: |
Yes |
Plan Description: |
Although there is no formal plan in place, the investigative team will share any of the information with other researchers (study protocol, statistical analysis plan, informed consent form, analytic code/data). We are in the process of publishing the results of our trial in a peer-reviewed journal. |
Supporting Materials: |
Study Protocol |
Supporting Materials: |
Statistical Analysis Plan (SAP) |
Supporting Materials: |
Informed Consent Form (ICF) |
Supporting Materials: |
Clinical Study Report (CSR) |
Supporting Materials: |
Analytic Code |
Time Frame: |
No time frame |
Access Criteria: |
Email Study Contact |
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University of Minnesota
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University of Minnesota
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Not Provided
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Principal Investigator: |
Marla Reicks, PhD |
University of Minnesota |
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University of Minnesota
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July 2019
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