Relationships between alexithymia and food addiction: The Finnish version of Yale Food Addiction Scale and preliminary test of its psychometric properties
Bibliographic record
Abstract
Background It has long been suggested that addictive behaviors are associated with alexithymia, a personality trait characterized by difficulties in emotional awareness and expression. However, little is known about the role of alexithymia in food addiction. Objectives The aim of this study was to investigate the relationship between alexithymia and food addiction. As part of the study, the validity of the Finnish version of Yale Food Addiction Scale (YFAS-F) was also investigated. Methods The sample consisted of 360 parents from the FinnBrain Birth Cohort Study. The structural validity of the YFAS-F was evaluated by confirmatory factor analysis (CFA). Exploratory factor analysis (EFA) was used to explore the structure when proposed models were not supported by CFA. The associations of alexithymia as measured by the 20-item Toronto Alexithymia Scale and food addiction were examined using regression analyses followed by structural equation modeling. Results Higher alexithymia was associated with more food addiction by conducting linear regression analysis (B = 0.013, p = 0.011) and structural equation modeling (β = 0.24, p < 0.001). Furthermore, a single-factor model for the 8 criteria of the YFAS-F was supported by CFA and showed acceptable internal reliability (KR-20 = 0.72), and a three-factor solution for the 20 items of the scale was suggested by EFA with good internal reliability (McDonald’s ω = 0.91 for the YFAS-F, 0.91 for component 1, 0.87 for component 2, and Spearman-Brown coefficient = 0.89 for component 3). Conclusion The current study determined a significant relationship between alexithymia and food addiction, which suggests alexithymia as a relevant factor for food addiction and may provide clinical implications for interventions. Moreover, the YFAS-F appeared to be a valid and reliable tool to evaluate food addiction in our Finnish general population sample. Further studies on the psychometric properties of the YFAS-F in more diverse populations are recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".