The Yale Food Addiction Scale, Version 2.0 (YFAS V2.0) measures addiction-like eating of palatable foods based on the eleven diagnostic criteria for substance use disorder in the fifth revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5).

scoring_yfas(data, items = 1:35, keep = TRUE)

Arguments

data

a data.frame containing the YFAS 2.0 items orderd from 1 to 35. The data.frame may contain further variables.

items

A character vector with the YFAS 2.0 item names ordered from 1 to 35, or a numeric vector indicating the column numbers of the YFAS 2.0 items in data.

keep

Logical, whether to keep the single items and whether to return variables containing the number of non-missing items on each scale for each respondent. The default is TRUE.

Value

Based on the dichotomized YFAS items, the function returns 14 variables:

  • score.yfas.act: Activity Score (4 items)

  • score.yfas.amo: Amount Score (3 items)

  • score.yfas.att: Attempts Score (4 items)

  • score.yfas.con: Consequences Score (2 items)

  • score.yfas.cra: Craving Score (2 items)

  • score.yfas.obl: Obligations Score (2 items)

  • score.yfas.pro: Problems Score (3 items)

  • score.yfas.sit: Situations Score (3 items)

  • score.yfas.tim: Time Score (3 items)

  • score.yfas.tol: Tolerance Score (2 items)

  • score.yfas.wit: Withdrawal Score (5 items)

  • score.yfas.imp: Impairment Score (2 items)

  • score.yfas.sympnum: Number of Symptoms (MAX = 11)

  • cutoff.yfas.foodadd: Food Addiction, categorized

Details

  • Number of items: 35

  • Item range: 0 to 7

  • Reverse items: none

  • Score range: 0 to 11 SUD (Substance Use Disorder) criteria

  • Cut-off-values: mild = 2–3 symptoms plus impairment or distress; moderate = 4–5 symptoms plus impairment or distress; severe = 6 or more symptoms plus impairment or distress

  • Minimal clinically important difference: none

  • Treatment of missing values: not reported

References

Schulte, Gearhardt 2017 (http://doi.wiley.com/10.1002/erv.2515)

Meule et al. 2017 (https://doi.org/10.1026/0012-1924/a000047)

Examples

if (FALSE) { library(dplyr) items.yfas <- paste0("YFAS_", seq(1, 35, 1)) scoring_yfas(mydata, items = items.yfas) }