5 Self-Report Measures
5.1 Childhood Trauma Questionnaire (CTQ)
The Childhood Trauma Questionnaire (CTQ) is a standardized self-report inventory that measures the severity of childhood trauma and participants’ tendency to underreport maltreatment, and has been validated in both clinical and non-clinical populations (Bernstein et al., 1997; Villano et al., 2004). The CTQ is a retrospective 28-item self-report inventory that measures the severity of different types of childhood trauma, producing five clinical subscales each comprised of five items: Emotional Abuse, Physical Abuse, Sexual Abuse, Emotional Neglect, Physical Neglect. The measure also includes a three-item Minimization/Denial scale indicating the potential underreporting of maltreatment. Participants respond to each item in the context of “when you were growing up” and answer according to a five-point Likert scale ranging from “never” = 1 to “very often” = 5, producing scores of 5 to 25 for each trauma subscale. The three items comprising the Minimization/Denial scale are dichotomized (“never” = 0, all other responses = 1) and summed; a total of one (1) or greater suggests the possible underreporting of maltreatment (false negatives).
Scoring
Scoring for the CTQ includes:
Renaming variables with descriptive names
Creating sum scores for each subscale (5 items for each of the 5 subscales)
Dichotomizing items for the minimization scale
Summing dichotimized items to create the minimization score
Key Variables
All variables below with appendix _25 reflect the final scoring of weighted subscale sum scores with < 25% missing data.
ctq_emo_abuse_25
ctq_phys_abuse_25
ctq_sex_abuse_25
ctq_emo_neglect_25
ctq_phys_neglect_25
ctq_minimize_complete (CTQ minimization score - completers only)
5.2 Demographics
Demographics captured in the current study include: Race, Sexual Orientation, Gender, Ethnicity, Student Status, Working Status, Current Living Situation, Assessment Date, and Age
Scoring
Demographics are primarily drawn from the data collection form (measure prefix ‘dcf’). Cleaning steps include:
1. Selection of variables that are part of the data collection form (prefix ‘dcf’) and winnow variables to be included in the master dataset.
2-3. Removal of HIPPA Identifiers - Calculation of age in years and remove birthdate; Changing assessment date to only capture month and year of assessment for further de-identification.
4. Binning categorical variables to response options most appropriate for race and ethnicity
Key Variables
age (Participant Age in Years)
race (Participant Race, recoded to: White[0], Black[1], Asian[2], Mixed Race/Other[3])
ethnicity (Hispanic[1] or non-Hispanic[0])
race_eth_1 (Race and ethnicity recoded to: White[0], Non-Hispanic Black [1], Non-Hispanic Asian [2], Hispanic [3], Mixed/Other [4])
race_eth_2 (Race and ethnicity recoded to: White [0], Asian [1], Other [2])
sex_orientation (Participant sexual orientation, recoded to: Heterosexual [0], Bi/Pansexual [1], Gay/Lesbian [2])
sex_minority (Participant sexual orientation recoded to Hetersoxesual[0] or Sexual Minority[1])
gender (Participant gender identity recoded to Male[0], Female [1], NonBinary/Other[2])
gender_TNB (Participant gender identity recoded to: Cisgender [0] or Trans/Nonbinary [1])
gender_female_nb (Participant gender identity coded to Male [0] and Female/Nonbinary = [1])
sex_gender_minority (Participant sexual and gender identity coded to CisHet [0] or Sexual/Gender Minority [1])
assessment_month (assessment recoded to assessment month and year)
5.3 Dieting and Weight History Questionnaire (DWHQ)
The Dieting and Weight History Questionnaire (DWHQ), was developed by Witt et al. (2013) to measure three dimensions of dieting: (1) frequency of past dieting and overeating (i.e. history of dieting), (2) current dieting to lose weight, and (3) weight suppression, or the difference between an individual’s current weight and his or her highest previous weight.
Scoring
Key Variables
5.4 Eating Disorder and Weight History
Eating Disorder History was assessed via a combination of the ED100k.V3 along with additional items assessing eating disorder and weight history. Dieting abd Weight history items were primarily taken from the Dieting and Weight History Questionnaire.
ED100K.V3 questionnaire is a self-report, ED assessment based on the Structured Clinical Interview for DSM-5, Eating Disorders(Thornton et al., 2018). Items assess DSM-5 criteria for AN, BN, BED, and other specified feeding and eating disorders (OSFED). The ED100K-V1 was found to be a valid measure of eating disorders and eating disorder behaviors. Positive predictive values for AN Criterion B, Criterion C, and binge eating ranged from 88 to 100% in the validation sample. Among women who had a negative screen, the probability of not having these criteria or behaviors ranged from 72 to 100% in the validation sample. The correlation between questionnaire and interview for lowest illness-related BMI was 0.91. Overall, the questionnaire captures historical: eating disorder diagnosis, eating disorder symptoms, eating disorder course of illness, and diagnostic fluctuation within eating disorder diagnosis.
Additional eating disorder history items were developed by the EMBARK Lab for the current project to capture ED history in this sample. It was used in baseline assessment for the current project prior to September, 2022, at which point the ED100k items were added (and generally supercede ED history items) as it has been supported through initial validation for this purpose. The Eating Disorder History Questionnaire follows diagnostic algorithmic scoring to assess (via self-report) for history of eating disorder behaviors along with DSM-5 Anorexia Nervosa, Atypical Anorexia Nervosa, Bulimia Nervosa, Binge Eating Disorder, and Subclinical Eating Pathology.
Scoring
Data cleaning steps include:
1-2. selects variables; recodes the compensatory exercise variable to remove missing codes, and recodes intentional weight control variables to remove missing codes and set ‘0’ equal to a ‘No/Never’ answer
3. overrides skip logic for exercise and other weight control variables such that if individuals have an initial ‘no’ answer where skip logic has overridden future questions, a ‘0’ (reflecting a ‘no/never’ answer) is entered in the subsequent question regarding details of the behavior.
4. Second recode for these questions such that missing codes are change to ‘NA’ and the ‘0’ answers are labelled appropriately
5-7. specifically calculate logic necessary to specify exercise-related outcome variables, described in key variables below.
8. cleans up the dataset by removing erroneous variables that are no longer needed.
After these steps ar complete, additional weight suppression variables are calculated and added to the data in the R-script
Key variables
ED100k_exercise_icb (Was exercise ever used as a behavior to intentionally control weight or shape?)ED100k_ex_compulsive (Ever felt compelled to exercise for wt and shape control OR uneasy / distressed if unable to exercise)ED100k_ex_interfere (Did exercise ever interfere in one’s life (changing eating habits, declining opportunities to be with friends, exercising despite illness or injury)ED100k_ex_excessive (>1 month of psychologically driven exercise every day or nearly every day)ED100k_ex_addictive (Having psychologically compulsive/driven exercise (feeling compelled to exercise or distressed if unable) that lasted for at least one month AND at least one life interfering symptom)ED100k_ex_compulsive_1mo (Compulsive/Driven Exercise that lasted for at least one month)ED100k_ex_maladaptive_1mo (reports driven exercise for at least one month OR any compensatory exercise)ex_current (Do you currently exercise to control weight and shape AND feel compelled to exercise or distress if unable to exercise?)Eating Disorder Behavior Variables
Case Status Variables
Weight suppression variables
ED100k_wt_suppress_high_current - current weight suppressionED100k_wt_suppress_high_lowest - difference between highest weight and lowest weight at adult heightED100k_wt_suppress_high_AN - difference between highest ever weight at adult height and weight during an AN episodeED100k_wt_suppress_current_AN - difference between current weight and weight duirng an AN episodeED100k_bmi_suppress_high_current : current BMI suppressionED100k_bmi_suppress_high_lowest: high-low BMI suppressionED100k_bmi_suppress_high_AN : high-AN BMI suppressionED100k_bmi_suppress_current_AN : current-AN BMI suppression (difference between current BMI and AN BMI)5.5 Eating Disorder Fear Questionnaire (EDFQ)
The EDFQ is a self-report measure of eating disorder specific fears, which was developed and validated in undergraduate college students along with a clinical sample of eating disorder patients by Levinson et al. (2019). A five-factor strucutre for the EDFQ was established, consisting of subscales assessing fear of weight gain, social consequences, personal consequences, physical sensations, and social eating. The EDFQ demonstrates good internal consistency and convergent, divergent, incremental, and construct validity.
Scoring
Key Variables
5.6 Eating Pathology Symptom Inventory
We used the 45-item Eating Pathology Symptom Inventory (EPSI; (Forbush et al., 2013)) to assess eating disorder symptoms at pre-intervention, post-intervention, and 8-week follow-up. The EPSI has been validated in clinical, college, and community samples, with 7-8 subscales in various populations, with the 8-subscale version being the most commonly-employed version of the measure (Coniglio et al., 2018). The 8 subscales includ: Body Dissatisfaction, Binge Eating, Cognitive Restraint, Purging, Restricting, Excessive Exercise, Negative Attitudes toward Obesity, and Muscle Building. Each item is scored on a 5-point Likert-style scale (0 = Never; 4= Often) to describe how well each item describes the participant experiences. Scores are derived by summing responses across the questions included in each subscale.
Scoring
Cleaning steps include:
1-2. selecting only the variables that are relevant for the current measure and renaming raw variables to appropraite names that are easy to understand
3. Creating eight additional variables based on sum scores reflecting eight subscales of the questionnaire: Body Dissatisfaction, Binge Eating, Cognitive Restraint, Purging, Restricting, Excessive Exercise, Negative Attitudes toward Obesity, and Muscle Building
4. Creating final variables for use that include calculated average variables for all individuals missing less than 25% of data on a given subscale. For those with missing data, weighted scores are used.
Key Variables
All variables below reflect the final scoring of weighted subscale sum scores with < 25% missing data.
epsi_body_dissatisfaction_25
epsi_binge_25 (binge eating)
epsi_restraint_25
epsi_purging_25
epsi_restrict_25
epsi_exercise_25 (excessive exercise)
epsi_neg_attitude_25 (negative attidtude towards obesity)
epsi_muscle_building_25
5.7 Fat Phobia Scale - Short Form
The shortened Fat Phobia Scale (FPS) utilizes 14 questions to assess fatphobia (from the 50-item original scale). It is intended to measure fat phobia levels in the tested population through various personality traits and whether there is bias when people apply them to an overweight person (Bacon et al. (2001)). The shortened FPS questionnaire demonstrates high reliability when compared to the original 50 question scale. The FPS uses a 5-point sliding scale with 1 being equal to a different negative descriptive variable for each respective question and 5 being equal to a different positive variable for each respective question. Some items are reverse scored prior to data aggregation such that th 1 (negative) to 5 (positive) valuation is maintained across the scale.
Scoring
Data Cleaning includes:
1-2. Selecting and renaming variables to include descriptive terms from questions in the scale.
3. Coding all items such that the negative descriptor is labeled as 1 and the positive descriptor is labeled as 5.
4. Computing a mean score using all 14-items
Key Variables
fps_mean_25 (Mean score of all 14 items, < 25% missing)
5.8 USDA Adult Food Security Survey Module (FSSM)
The U.S. Adult Food Security - Survey Module (FSSM) (Carlson et al., 1999) was developed by the USDA Food and Nutrition Services in 1995 for assessing food security within households, specifically for use in the Current Population Survey. The FSSM is primarily designed as a unidimensional, 10-item scale. Previous use in college students indicates that students respond differently to FSSM items relative to the general population, that the FSSM may be a less reliable measure of food insecurity in college students relative to other adults in the US population (Nikolaus et al., 2019), and that there is potential for misclassification of FI college students (Nikolaus et al., 2020), which is a note of caution when interpreting findings from this measure in our young adult sample. however, at present, there is no alternative measure of FI amongst college students with a more robust track-record of validity.
Responses of “yes,” “often,” “sometimes,” “almost every month,” and “some months but not every month” are coded as affirmative. The sum of affirmative responses to the 10 questions in the Adult Food Security Scale is then the raw score on the scale.
Food security status is assigned as follows: | | - Raw score 0: High food security | - Raw score 1-2: Marginal food security | - Raw score 3-5: Low food security | - Raw score 6-10: Very low food security | |When dichotomizing, the food security status of the first two categories in combination is described as food secure and the latter two as food insecure.
Scoring
Data cleaning includes:
1-2. Select and rename variables to include numbering of questions in the scale and name of scale being utilized
3. Recode scores in accordance with recommendations (noted above)
4. Create sum scores for dichotomized questions - fssm_total, and average of frequency items fssm_average_freq.
5. Create Food Security Status variable - as outlined above
Key Variables
fssm_total_25 (sum of 10-item FSSM, those with 25% or less missing - weighted by N completed)
fssm_average_freq_complete (average of scores measuring how many days were impacted by previous questions with yes no scores regarding previous 28 days of access and measures taken because of food insecurity - completers)
5.9 Generalized Anxiety Disorder 7-item (GAD-7)
Generalized Anxiety Disorder 7-item (GAD-7) (Spitzer et al., 2006) is a seven-item instrument that is used to measure or assess the severity of generalised anxiety disorder (GAD). Each item asks the individual to rate the severity of his or her symptoms over the past two weeks. Response options include “not at all”, “several days”, “more than half the days” and “nearly every day”. The GAD-7 is a widely-used and well-validated measure for anxiety screening (Sapra et al., 2020). the GAD-7 is scored on a unidimensional scale summing all 7 items, with cutoffs that can also be employed for interpretation of clinical severity: | | Minimal anxiety = 0-4 | Mild Anxiety = 5-9 | Moderate Anxiety = 10-14 | Severe Anxiety = 15-21. | | A score of 10 points or higher indicates probably anxiety disorder, with 89% sensitivity and 82% specificity for GAD.
Scoresheet
Data Cleaning includes:
1-2 Selecting only the variables that are relevant for the current measure and recoding raw variables to make them consistent with the way of scoring: not at all = 0, several days =1, over half the days = 2, nearly every day =3
3-5 creation an additional variable based on sum scores reflecting the participant’s anxiety levels
6 creating a dichotomized measure of likely anxiety (cutoff score of 10 or greater), along with clinical severity index (minimal, mild, moderate, severe)
Key variables
gad_sum_25 (Sum of GAD-7, 25% or less items missing and weighted by N items completed)
gad_cutoffs (GAD-7 with anxiety severity cutoffs employed)
gad_anx_disorder (GAD-7 probable anxiety disorder Yes/No)
5.10 Goldfarb Fear of Fat Scale
The Goldfarb Fear of Fat Scale (GFFS) is a 10-item scale which was introduced in 1985 as a diagnostic tool to measure one’s fear of fat as it can be an indicator for the development of an eating disorder (Goldfarb et al., 1985). When used as a screening tool for both clinical and non-clinical groups, GFFS has strong test-retest reliability and psychometric properties (Przybyta-Basista et al., 2022). In addition, the test also has shown high validity for both populations with and without eating disorders (Goldfarb, 2010) While original factor structure is defined as a single-factor, Przybyta-Basista et al. (2022) also supported a two-factor structure in a non-clinical sample: (1) fear of weight gain and (2) fear of losing control over eating/weight. GFFS uses a 4-point scale with 1 being equal to very untrue and 4 being equal to very true
Scoring
Data Cleaning includes:
1-2. Select and rename variables; recode labels scale to begin at 0 instead of 1 with very untrue being equal to 0 and very true being equal to 3.
3-4. Sum the total scores and create a variable to reflect only those completing > 75% of items. Also create two subscales (FOWG and Fear of LOC) for alternative scoring.
|Scoring Note Our GFFS scoring procedure re-scales the item scores to be 0-3 instead of 1-4, meaning that sum scores are scaled 0-21 instead of 7-28. To compare our means to other studies using the GFFS, add 7 to the sum score.
Key Variables
For variables below, _25 appendix reflects that individuals with <25% missing items on a scale were included with weighted sums based on number of items completed
gffs_sum_25 (sum of all items)
gffs_fowg_25 (sum of fear of weight gain subscale)
gffs_loc_25 (sum of loss of control items)
5.11 Ideal Body Stereotype Scale - Revised (IBSS-R)
The Ideal Body Stereotype Scale - Revised (IBSS-R), is a brief (6-item), unidimensional scale designed to measure internalization of an ideal-body stereotype (specifically for women), developed by Stice et al. (1996). The IBSS-R has be utilized as a measure of thin-ideal internalization in eating disorder prevention research (Stice et al., 2019), making it suitable as a benchmark measure for existing effect sizes.
Scoring
Scoring includes:
1. Selecting and renaming variables.
2. Creating a mean score from all 6 IBSS items
Key Variables
ibss_mean_25 (Mean of all IBSS items, 25% or less missing)
5.12 Positive and Negative Affect Schedule (PANAS)
The Positive and Negative Affect Schedule (PANAS) js a 20-item, 2 dimensional measure which was introduced in 1988 to measure one’s positive and negative moods (Watson et al., 1988). Compared to other scales measuring positive and negative affect, PANAS has high internal consistency and validity. In addition, the scale also shows consistent reliability, even when measured across gender (Crawford & Henry, 2004). The PANAS asks respondents to indicate how they have felt over the previous week using a 5-point likert scale with 1 = very slightly or not at all and 5 = extremely. The two dimensions include a 10-item positive affect subscale and 10-item negative affect subscale
Scoring
Data cleaning includes:
1. Selecting and renaming variables
2. Computing subscale sum scores:
panas_positive_sum- Sum the total scores of questions 2, 4, 6, 7, 10, 12, 14, 17, 19 as
panas_negative_sum
Key Variables
Sum scores below reflect weighted sums with 25% or less missing data:
panas_positive_sum_25 (sum of scores for questions identifying positive affect over the course of the last week)
panas_negative_sum_25 (sum of scores for questions identifying negative affect over the course of the last week)
5.13 Patient Health Questionnnaire -9 (PHQ-9)
The 9-question Patient Health Questionnaire is a diagnostic tool introduced in 2001 to screen adult patients in a primary care setting for the presence and severity of depression Kroenke & Spitzer (2002). A PHQ-9 score > or =10 had a sensitivity of 88% and a specificity of 88% for major depression. PHQ-9 scores of 5, 10, 15, and 20 represented mild, moderate, moderately severe, and severe depression, respectively.
Scoresheet
Cleaning steps include:
1-2. Selecting raw variables being used for the current measure; recode labels scale to begin at 0 instead of 1 with “not at all” = 0, and “nearly every day” = 4
3. Sum the total scores
4. Create severity index and ‘probable depression’ diagnostic cutoff
Key Variables
phq_sum_25 (represents total score of the PHQ-9; weighted sum 25% or less missing items)
phq_dep_severity (severity index of minimal, mild, moderate, moderately severe, and severe depression)
phq_dep_probable (Probable depression yes/no based on score of 10 or greater)
5.14 Sociocultural Attitudes Towards Appearance Questionnaire (SATAQ)
The Sociocultural Attitudes Towards Appearance Questionnaire-4 (SATAQ) is a 22-item measure designed to assess societal and interpersonal aspects of appearance ideals. The SATAQ has five validated factors: Internalization of Thin/Low Body Fat, Internalization of Muscular/Athletic, Pressures from Family, Pressures from Media, and Pressures from Peers. This scale structure was confirmed in 3 independent and geographically diverse samples of women from the United States (East Coast N = 440, West Coast N = 304, and North/Midwest N = 349). SATAQ-4 scale scores demonstrated excellent reliability and good convergent validity with measures of body image, eating disturbance, and self-esteem. The measure was also validated in college males from the United States (N = 271); however, there was some evidence of an underlying structure unique to men. For the purposes of the current data, the 5-factor structure is employed in scoring.
Scoresheet
Cleaning Steps include:
1-3. Selecting raw variables being used and renaming variables to include numbering for order of questions in the scale; recoding labels scale to begin at 0
4. Generate total score and subscale scores:
Internalization of thinness/low Body Fat: 3,4,5,8, 9
Internalization of muscular/athletic: 1, 2,6 7, 10
Pressures - family: 11, 12, 13, 14
Pressures - peers: 15,16,17,18
Pressures - media: 19, 20, 21, 22
Key Variables
Variables with the _25 appendix indicate that these variables include those with 25% or less missing data
sataq_mean_25 (mean of SATAQ)
sataq_thin_ideal_25 (mean of internalization of the thin ideal)
sataq_athletic_ideal_25 (mean of internalization of athletic ideal)
sataq_parental_pressure_25 (mean of parental pressure)
sataq_peer_pressure_25 (mean of peer pressure)
sataq_media_pressure_25 (mean of media pressure)
5.15 Traditional Masculinity-Femininity Scale (TMFS)
The Traditional Masculinity-Femininity Scale (TMFS) which was introduced in 2016 to assess self-ascribed masculinity and femininity (Kachel et al., 2016). The TMFS has demonstrated high reliability for both sexes. Additionally, TMFS shows validity due to its ability to reduce issues of social desirability when given as a self-assessment. TMFS uses a 7-point likert scale with 1 being equal to totally masculine and 7 being equal to totally feminine. In terms of scoring, the mean is taken of all given answers with an average less than 4 implying masculinity and an average greater than 4 implying femininity.
Scoresheet
Data cleaning steps include:
1-2 selecting and renaming variables to include numbering of questions in the scale
3-4. Taking the mean total score and rename as tmfs_mean. Create mean variable with 25% or less missing data.
Key Variables
tmfs_mean_25 (average of scores in response to questions asking about different situations where one could consider their femininity and masculinity. 25% or less missing data)
5.16 Universal Measure of Bias - Fat (UMB-fat)
This companion file is for the Universal Measure of Bias - Fat (UMB-Fat) which was introduced in 2008 to assess weight bias and demonstrates strong psychometric properties when utilized as an assessment (Durso & Latner, 2008). It has been compared alongside two other scales measuring universal bias against ‘gay’ or ‘Muslim’ individuals and demonstrates high internal consistency and construct validity (Latner et al., 2008). Further, higher BMI is not associated with any differences in weight bias. The UMB-Fat uses a 7-point likert scale with 1 being equal to strongly agree and 7 being equal to strongly disagree. In terms of scoring, sums of scores are separated amongst four categories of bias: adverse judgement, social distance, attraction, and equal rights.
Scoring
Data cleaning includes:
1. Selecting and renaming variables to include descriptors of questions asked in the scale
2. Reverse coding questions 5, 7, 8, 9, 12, 15, 16, and 19 so that higher scores indicate greater stigma
3. Creation of subscale scores:
Sum the total scores of questions 5, 7, 12 ,15 , 16 =
umb_adverse_judgement_sumSum the total scores of questions 2, 8, 17, 19, 20 =
umb_social_distance_sumSum the total scores of questions 3, 4, 6, 9, 10 =
umb_attraction_sumSum the total scores of questions 1, 11, 13, 14, 18 =
umb_equal_rights_sumSum the total score with sum of all items as
umb_sum_total
Key Variables
All variables below reflect the final scoring of subscale sum scores with < 25% missing data (weighted sums used for those with any missing data).
umb_adverse_judgement_sum_25 (adverse judgement against fat people)
umb_social_distance_sum_25 (bias in the form of social distance from fat people)
umb_attraction_sum_25 (bias in the form of attraction towards fat people)
umb_equal_rights_sum_25 (bias in the form of opinons of equal rights for fat people)
umb_sum_total_25 (sum of total umb-FAT scores - 25% or less missing)