ArticleBiomedical informatics insights2017
A Machine Learning Approach to Evaluating Illness-Induced Religious Struggle.
Article in Biomedical informatics insights, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Religious Concerns about the Integration of Artificial Intelligence into Clinical Medicine and Patient Care.Journal of religion and health · 2026Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Religious or spiritual struggles are clinically important to health care chaplains because they are related to poorer health outcomes, involving both mental and physical health problems. Identifying persons experiencing religious struggle poses a challenge for chaplains. One potentially underappreciated means of triaging chaplaincy effort are prayers written in chapel notebooks. We show that religious struggle can be identified in these notebooks through instances of negative religious coping, such as feeling anger or abandonment toward God. We built a data set of entries in chapel notebooks and classified them as showing religious struggle, or not. We show that natural language processing techniques can be used to automatically classify the entries with respect to whether or not they reflect religious struggle with as much accuracy as humans. The work has potential applications to triaging chapel notebook entries for further attention from pastoral care staff.
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