HarmoniCA
Collection
Harmonizing Clinical Assessments: enabling integration of symptom measures in large multi-site studies. • 6 items • Updated
How to use julia-pfarr/HarmoniCA_depression with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("julia-pfarr/HarmoniCA_depression")
sentences = [
"The weather is lovely today.",
"It's so sunny outside!",
"He drove to the stadium."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]Part of the HarmoniCA collection for harmonising psychiatric questionnaire items across studies. This model assigns items from depression questionnaires to one of five theoretically motivated symptom dimensions.
| ID | Label | Description |
|---|---|---|
| 1 | Mood & Affective Symptoms | dysphoria, sadness, hopelessness, feeling low |
| 2 | Cognitive & Self-Perception | guilt, worthlessness, self-criticism, pessimism, narratives of the past and future |
| 3 | Somatic & Vegetative Symptoms | sleep, appetite, fatigue, weight changes, physical symptoms |
| 4 | Activity & Interest Deficit | anhedonia, loss of interest, psychomotor signs, reduced functioning |
| 5 | Anxiety & Distress | irritability, agitation, worry, tension, nervousness |
Items rated as not belonging to the depression construct are assigned dimension -1 (Does not fit).
Evaluated on 126 held-out items from unseen questionnaires against expert labels.
| Cohen's κ | Accuracy |
|---|---|
| 0.746 | 79.4% |
Cross-validation (leave-one-questionnaire-out, 14 folds): mean accuracy 86.9% ± 11.9%.
in preparation
Base model
BAAI/bge-large-en-v1.5