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| Name | Class |
|---|---|
| University of California, San Francisco | OTHER |
| Miami University | OTHER |
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The study will use a between-subjects design in a sample of individuals with BMI greater than or equal to 28 from the Los Angeles community (N=330). Participants will be randomly assigned to a weight stigma vs. control manipulation. Changes to the following health behaviors will be subsequently measured in their everyday lives: 3-day diet as captured by ecological momentary assessment (EMA) food diaries, objectively measured eating of obesogenic foods, objectively measured physical activity captured by 24-hour actigraphy, and sleep, captured objectively by overnight actigraphy and subjectively self-reported sleep measures. The investigators hypothesize that weight stigma causes decrements in health behaviors (e.g., sleep, eating, and physical activity) in everyday life.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Experimental (Weight Stigma) Arm | Experimental | Participants undergoing the experimental (Weight Stigma) arm are exposed to an interaction partner (a trained confederate) who endorses anti-fat attitudes. Prior to their interaction, participants exchange a "Getting to Know You Questionnaire" with the confederate, where the confederate endorses anti-fat attitudes. During their interaction with the confederate, participants are told they will be completing consumer rating tasks with another participant in the study. During the ostensible consumer rating task, participants in the experimental condition rate items such as a diet magazine, body sunscreen, running shoes, and a size small T-shirt labeled as size large to bolster the weight stigma manipulation. |
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| Control Arm | No Intervention | Participants undergoing the control arm are also exposed to an interaction partner (a trained confederate) who does not endorse anti-fat attitudes. Prior to their interaction, participants exchange a "Getting to Know You Questionnaire" with the confederate; however, the confederate does not endorse anti-fat attitudes. During their interaction with the confederate, participants are told they will be completing consumer rating tasks with another participant in the study. During the ostensible consumer rating task, participants in the control condition rate items such as an interior design magazine, face sunscreen, regular (non-running) shoes, and a size large T-shirt correctly labeled as size large to avoid weight stigma. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Weight stigma intervention | Behavioral | Those undergoing the weight stigma manipulation will be exposed to an interaction partner (a trained confederate) who will endorse anti-fat attitudes. The purpose of this interaction is to examine the causal effects of weight stigma on eating behaviors, physical activity, and sleep. |
| Measure | Description | Time Frame |
|---|---|---|
| Hyperpalatable Food Intake | Hyperpalatable food intake will initially be measured in grams and then converted into kilocalories. The food will consist of the following items: chocolate chip cookies, M&Ms, potato chips, and Sprite. These foods were chosen because processed foods, added sugars, refined grains, starchy vegetables, and sugar sweetened beverages are foods to avoid according to the 2019 American Diabetes Association Nutrition Consensus Report and are high in carbohydrates and glycemic index. | Hyperpalatable food intake will be measured directly after the intervention, on average 10 minutes later. |
| Change in Self-reported Dietary Intake | Dietary intake data for food recalls will be collected and analyzed using the Automated Self-Administered 24-hour (ASA24) Dietary Assessment Tool developed by the National Cancer Institute, Bethesda, MD. The primary eating outcome for the food diaries will be kilocalories. | Change in self-reported dietary intake will be assessed by measuring self-reported dietary intake 72 hours before the intervention as part of the baseline, and 72 hours after the intervention. |
| Change in Physical Activity | Physical activity, quantified as Metabolic Equivalent of Task (MET) units, will be assessed using ActivPAL4 actigraphs. | Change in physical activity will be assessed by measuring physical activity for 72 hours before the intervention as part of the baseline, and 72 hours after the intervention. |
| Change in Sleep Duration | Change in sleep duration will be assessed using an Actiwatch-2 (Philips Respironics). Data will be captured in 30-second epochs and validated. Actiware 6.0.9 software algorithms will be used to estimate sleep parameters with the following sleep/wake algorithm: D = A-2*(1/25) + A1*(1/5) + A*(1) + A + 1*(1/5) + A + 2*(1/25), where AX = accelerometer activity for that minute. | Change in sleep duration will be assessed by measuring sleep duration for three days before the intervention as part of the baseline, and three days after the intervention. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| A. Janet Tomiyama, Ph.D. | University of California, Los Angeles | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of California, Los Angeles | Los Angeles | California | 90034 | United States |
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We excluded participants who did not meet all of our inclusion criteria: a BMI of greater >= 28; English-speaking; no diagnosis of major mental disorders including any eating disorder, mood disorder, schizophrenia, or PTSD within past year; no diagnosis of major physical conditions that limit physical movement within past; no recent diagnosis of a sleep disorder within past year; and no allergy to any of the foods in the food buffet. Four participants dropped out prior to manipulation.
Recruitment strategies included online postings (e.g., Facebook), physical flyers around the surrounding community, listings on clinicaltrials.gov, clinicaltrials.ucla.edu, and other study recruitment portals such as researchmatch.com, and the psychology subject pools for our university, as well churches and beauty salons/barber shops, and recruitment at community centers and events. Recruitment took place from April 2022 to July 2024.
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| ID | Title | Description |
|---|---|---|
| FG000 | Control Group | At visit one, participants completed a baseline questionnaire-which included all resilience measures-and received training in how to use the ActivPAL4, Actiwatch-2, and ASA24 to track their physical activity, sleep, and eating behavior, respectively. Then, participants wore the ActivPAL4 for 72 hours and the Actiwatch-2 for three nights, while they used the ASA24 to record their eating behavior. We chose an assessment period of three days in order to balance reliable measurement of health behaviors with feasibly capturing the effects of our manipulation. Each morning after having worn the Actiwatch-2, participants completed the questionnaire assessing self-reported measures of the past night's sleep. At visit two, participants completed the control condition, followed by the objective eating behavior task. Following this, participants again wore the ActivPAL4 for 72 hours and the Actiwatch-2 for three nights, used the ASA24 to record their eating behavior, and completed the sleep questionnaire. Lastly, participants were debriefed at visit three upon completion of the 72-hour tracking period to return their devices. |
| FG001 | Experimental Group | At visit one, participants completed a baseline questionnaire-which included all resilience measures-and received training in how to use the ActivPAL4, Actiwatch-2, and ASA24 to track their physical activity, sleep, and eating behavior, respectively. Then, participants wore the ActivPAL4 for 72 hours and the Actiwatch-2 for three nights, while they used the ASA24 to record their eating behavior. We chose an assessment period of three days in order to balance reliable measurement of health behaviors with feasibly capturing the effects of our manipulation. Each morning after having worn the Actiwatch-2, participants completed the questionnaire assessing self-reported measures of the past night's sleep. At visit two, participants completed the weight stigma manipulation, followed by the objective eating behavior task. Following this, participants again wore the ActivPAL4 for 72 hours and the Actiwatch-2 for three nights, used the ASA24 to record their eating behavior, and completed the sleep questionnaire. Lastly, participants were debriefed at visit three upon completion of the 72-hour tracking period to return their devices. |
| Title | Milestones | Reasons Not Completed | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
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| ID | Title | Description |
|---|---|---|
| BG000 | Control Group | At visit one, participants completed a baseline questionnaire-which included all resilience measures-and received training in how to use the ActivPAL4, Actiwatch-2, and ASA24 to track their physical activity, sleep, and eating behavior, respectively. Then, participants wore the ActivPAL4 for 72 hours and the Actiwatch-2 for three nights, while they used the ASA24 to record their eating behavior. We chose an assessment period of three days in order to balance reliable measurement of health behaviors with feasibly capturing the effects of our manipulation. Each morning after having worn the Actiwatch-2, participants completed the questionnaire assessing self-reported measures of the past night's sleep. At visit two, participants completed the control condition, followed by the objective eating behavior task. Following this, participants again wore the ActivPAL4 for 72 hours and the Actiwatch-2 for three nights, used the ASA24 to record their eating behavior, and completed the sleep questionnaire. Lastly, participants were debriefed at visit three upon completion of the 72-hour tracking period to return their devices. |
| Units | Counts |
|---|---|
| Participants |
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| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Continuous | Years |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | Hyperpalatable Food Intake | Hyperpalatable food intake will initially be measured in grams and then converted into kilocalories. The food will consist of the following items: chocolate chip cookies, M&Ms, potato chips, and Sprite. These foods were chosen because processed foods, added sugars, refined grains, starchy vegetables, and sugar sweetened beverages are foods to avoid according to the 2019 American Diabetes Association Nutrition Consensus Report and are high in carbohydrates and glycemic index. | Posted | Mean | Standard Deviation | kilocalories | Hyperpalatable food intake will be measured directly after the intervention, on average 10 minutes later. |
|
From enrollment until end of follow-up, up to 2 weeks
Adverse events were defined as in clinicaltrials.gov
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | Experimental (Weight Stigma) Arm | Participants undergoing the experimental (Weight Stigma) arm are exposed to an interaction partner (a trained confederate) who endorses anti-fat attitudes. Prior to their interaction, participants exchange a "Getting to Know You Questionnaire" with the confederate, where the confederate endorses anti-fat attitudes. During their interaction with the confederate, participants are told they will be completing consumer rating tasks with another participant in the study. During the ostensible consumer rating task, participants in the experimental condition rate items such as a diet magazine, body sunscreen, running shoes, and a size small T-shirt labeled as size large to bolster the weight stigma manipulation. |
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| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| A. Janet Tomiyama | University of California, Los Angeles | 310.206.6875 | janetto@ucla.edu |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Dec 23, 2025 | Dec 23, 2025 | Prot_SAP_000.pdf |
| ICF | No | No | Yes | Informed Consent Form | Dec 23, 2025 | Dec 23, 2025 | ICF_001.pdf |
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| ID | Term |
|---|---|
| D009765 | Obesity |
| D000079322 | Weight Prejudice |
| D009043 | Motor Activity |
| ID | Term |
|---|---|
| D050177 | Overweight |
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D009750 | Nutritional and Metabolic Diseases |
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| Change in Self-reported Sleep Quality | Participants will respond to a single item assessing past night's sleep quality, with response options ranging from 1 (very bad) to 4 (very good). Change in subjective sleep quality will be calculated by taking the difference of the item score pre- and post-intervention. The possible minimum for change in self-reported sleep quality is -3 and the possible maximum is 3. In this difference score, higher scores indicate improvements in sleep quality from baseline to post. | Change in self-reported sleep quality will be assessed by measuring self-reported sleep quality during the mornings of the first 72 hour baseline period before the intervention, and in the mornings of the 72 hour period after the intervention. |
| Change in Sleep Onset Latency | Change in sleep onset latency will be assessed using an Actiwatch-2 (Philips Respironics). Data will be captured in 30-second epochs and validated. Actiware 6.0.9 software algorithms will be used to estimate sleep parameters with the following sleep/wake algorithm: D = A-2*(1/25) + A1*(1/5) + A*(1) + A + 1*(1/5) + A + 2*(1/25), where AX = accelerometer activity for that minute. Sleep onset is operationalized as after 10 consecutive minutes of D ≤ 40 (as D > 40 indicates participants are awake). | Change in sleep onset latency will be assessed by measuring sleep onset latency for three days before the intervention as part of the baseline, and three days after the intervention. |
| Change in Sleep Efficiency | Change in sleep efficiency will be assessed using an Actiwatch-2 (Philips Respironics). Data will be captured in 30-second epochs and validated. Actiware 6.0.9 software algorithms will be used to estimate sleep parameters with the following sleep/wake algorithm: D = A-2*(1/25) + A1*(1/5) + A*(1) + A + 1*(1/5) + A + 2*(1/25), where AX = accelerometer activity for that minute. The possible minimum value is -100 and the possible maximum value is 100. Higher scores indicate better sleep efficiency. | Change in sleep efficiency will be assessed by measuring sleep efficiency for three days before the intervention as part of the baseline, and three days after the intervention. |
| BG001 | Experimental Group | At visit one, participants completed a baseline questionnaire-which included all resilience measures-and received training in how to use the ActivPAL4, Actiwatch-2, and ASA24 to track their physical activity, sleep, and eating behavior, respectively. Then, participants wore the ActivPAL4 for 72 hours and the Actiwatch-2 for three nights, while they used the ASA24 to record their eating behavior. We chose an assessment period of three days in order to balance reliable measurement of health behaviors with feasibly capturing the effects of our manipulation. Each morning after having worn the Actiwatch-2, participants completed the questionnaire assessing self-reported measures of the past night's sleep. At visit two, participants completed the weight stigma manipulation, followed by the objective eating behavior task. Following this, participants again wore the ActivPAL4 for 72 hours and the Actiwatch-2 for three nights, used the ASA24 to record their eating behavior, and completed the sleep questionnaire. Lastly, participants were debriefed at visit three upon completion of the 72-hour tracking period to return their devices. |
| BG002 | Total | Total of all reporting groups |
| Standard Deviation |
| years |
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| Sex/Gender, Customized | Count of Participants | Participants |
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| Race/Ethnicity, Customized | Count of Participants | Participants |
|
| OG001 | Experimental Group | At visit one, participants completed a baseline questionnaire-which included all resilience measures-and received training in how to use the ActivPAL4, Actiwatch-2, and ASA24 to track their physical activity, sleep, and eating behavior, respectively. Then, participants wore the ActivPAL4 for 72 hours and the Actiwatch-2 for three nights, while they used the ASA24 to record their eating behavior. We chose an assessment period of three days in order to balance reliable measurement of health behaviors with feasibly capturing the effects of our manipulation. Each morning after having worn the Actiwatch-2, participants completed the questionnaire assessing self-reported measures of the past night's sleep. At visit two, participants completed the weight stigma manipulation, followed by the objective eating behavior task. Following this, participants again wore the ActivPAL4 for 72 hours and the Actiwatch-2 for three nights, used the ASA24 to record their eating behavior, and completed the sleep questionnaire. Lastly, participants were debriefed at visit three upon completion of the 72-hour tracking period to return their devices. |
|
|
| Primary | Change in Self-reported Dietary Intake | Dietary intake data for food recalls will be collected and analyzed using the Automated Self-Administered 24-hour (ASA24) Dietary Assessment Tool developed by the National Cancer Institute, Bethesda, MD. The primary eating outcome for the food diaries will be kilocalories. | Posted | Mean | Standard Deviation | kilocalories | Change in self-reported dietary intake will be assessed by measuring self-reported dietary intake 72 hours before the intervention as part of the baseline, and 72 hours after the intervention. |
|
|
|
| Primary | Change in Physical Activity | Physical activity, quantified as Metabolic Equivalent of Task (MET) units, will be assessed using ActivPAL4 actigraphs. | Posted | Mean | Standard Deviation | Metabolic Equivalent of Task (MET) units | Change in physical activity will be assessed by measuring physical activity for 72 hours before the intervention as part of the baseline, and 72 hours after the intervention. |
|
|
|
| Primary | Change in Sleep Duration | Change in sleep duration will be assessed using an Actiwatch-2 (Philips Respironics). Data will be captured in 30-second epochs and validated. Actiware 6.0.9 software algorithms will be used to estimate sleep parameters with the following sleep/wake algorithm: D = A-2*(1/25) + A1*(1/5) + A*(1) + A + 1*(1/5) + A + 2*(1/25), where AX = accelerometer activity for that minute. | Posted | Mean | Standard Deviation | hours | Change in sleep duration will be assessed by measuring sleep duration for three days before the intervention as part of the baseline, and three days after the intervention. |
|
|
|
| Primary | Change in Self-reported Sleep Quality | Participants will respond to a single item assessing past night's sleep quality, with response options ranging from 1 (very bad) to 4 (very good). Change in subjective sleep quality will be calculated by taking the difference of the item score pre- and post-intervention. The possible minimum for change in self-reported sleep quality is -3 and the possible maximum is 3. In this difference score, higher scores indicate improvements in sleep quality from baseline to post. | Posted | Mean | Standard Deviation | likert scale | Change in self-reported sleep quality will be assessed by measuring self-reported sleep quality during the mornings of the first 72 hour baseline period before the intervention, and in the mornings of the 72 hour period after the intervention. |
|
|
|
| Primary | Change in Sleep Onset Latency | Change in sleep onset latency will be assessed using an Actiwatch-2 (Philips Respironics). Data will be captured in 30-second epochs and validated. Actiware 6.0.9 software algorithms will be used to estimate sleep parameters with the following sleep/wake algorithm: D = A-2*(1/25) + A1*(1/5) + A*(1) + A + 1*(1/5) + A + 2*(1/25), where AX = accelerometer activity for that minute. Sleep onset is operationalized as after 10 consecutive minutes of D ≤ 40 (as D > 40 indicates participants are awake). | Posted | Mean | Standard Deviation | minutes | Change in sleep onset latency will be assessed by measuring sleep onset latency for three days before the intervention as part of the baseline, and three days after the intervention. |
|
|
|
| Primary | Change in Sleep Efficiency | Change in sleep efficiency will be assessed using an Actiwatch-2 (Philips Respironics). Data will be captured in 30-second epochs and validated. Actiware 6.0.9 software algorithms will be used to estimate sleep parameters with the following sleep/wake algorithm: D = A-2*(1/25) + A1*(1/5) + A*(1) + A + 1*(1/5) + A + 2*(1/25), where AX = accelerometer activity for that minute. The possible minimum value is -100 and the possible maximum value is 100. Higher scores indicate better sleep efficiency. | Posted | Mean | Standard Deviation | efficiency score | Change in sleep efficiency will be assessed by measuring sleep efficiency for three days before the intervention as part of the baseline, and three days after the intervention. |
|
|
|
| 0 |
| 125 |
| 0 |
| 125 |
| 0 |
| 125 |
| EG001 | Control Arm | Participants undergoing the control arm are also exposed to an interaction partner (a trained confederate) who does not endorse anti-fat attitudes. Prior to their interaction, participants exchange a "Getting to Know You Questionnaire" with the confederate; however, the confederate does not endorse anti-fat attitudes. During their interaction with the confederate, participants are told they will be completing consumer rating tasks with another participant in the study. During the ostensible consumer rating task, participants in the control condition rate items such as an interior design magazine, face sunscreen, regular (non-running) shoes, and a size large T-shirt correctly labeled as size large to avoid weight stigma. | 0 | 123 | 0 | 123 | 0 | 123 |
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| D001835 |
| Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D011287 | Prejudice |
| D012919 | Social Behavior |
| D001519 | Behavior |