Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Transformers for prompt-level EMA non-response prediction   Ecological Momentary Assessments (EMAs) are an important psychological data
source for measuring current cognitive states, affect, behavior, and
environmental factors from participants in mobile health (mHealth) studies and
treatment programs. Non-response, in which participants fail to respond to EMA
prompts, is an endemic problem. The ability to accurately predict non-response
could be utilized to improve EMA delivery and develop compliance interventions.
Prior work has explored classical machine learning models for predicting
non-response. However, as increasingly large EMA datasets become available,
there is the potential to leverage deep learning models that have been
effective in other fields. Recently, transformer models have shown
state-of-the-art performance in NLP and other domains. This work is the first
to explore the use of transformers for EMA data analysis. We address three key
questions in applying transformers to EMA data: 1. Input representation, 2.
encoding temporal information, 3. utility of pre-training on improving
downstream prediction task performance. The transformer model achieves a
non-response prediction AUC of 0.77 and is significantly better than classical
ML and LSTM-based deep learning models. We will make our a predictive model
trained on a corpus of 40K EMA samples freely-available to the research
community, in order to facilitate the development of future transformer-based
EMA analysis works.

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The categories of this paper are: cmp-lg
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The categories of this paper are: ao-sci
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The categories of this paper are: supr-con
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The categories of this paper are: chem-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-lat
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The categories of this paper are: acc-phys
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The categories of this paper are: dg-ga
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The categories of this paper are: patt-sol
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The categories of this paper are: atom-ph
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The categories of this paper are: adap-org
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The categories of this paper are: math
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The categories of this paper are: stat
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The categories of this paper are: physics
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The categories of this paper are: q-fin
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The categories of this paper are: alg-geom