Online Guided Self-help Cognitive Behavioral Therapy With Exposure to Anxiety and Problem Solving in Type 1 Diabetes Mellitus: Case Study
Bibliographic record
Abstract
BACKGROUND: Type 1 diabetes mellitus (T1DM) is dependent on self-care to avoid short- and long-term complications. There are several problem areas in diabetes that could be addressed by psychological interventions, such as suboptimal problem-solving strategies and fear of hypoglycemia. There is empirical support for a few psychological interventions, most often cognitive behavioral therapy, with various treatment aims. However, these interventions are largely unavailable in regular diabetes health care. Online guided self-help cognitive behavioral therapy could help achieve greater outreach. OBJECTIVE: We tested a manualized treatment in the early stage for further development, with the long-term aim to increase access to care. The purpose of this report was to show the potential of this newly developed online intervention by describing 2 illustrative cases. METHODS: An online guided self-help cognitive behavioral therapy protocol featuring problem solving and exposure was developed. The treatment was administered from a secure online platform and lasted for 8 weeks. Case 1 was a male participant. He had a number of diabetes-related complications and was worried about his future. He reported that he had a general idea that he needed to change his lifestyle but found it difficult to get started. Case 2 was a female participant. She had fear of hypoglycemia and unhelpful avoidance behaviors. She kept her blood glucose levels unhealthily high in order to prevent hypoglycemic episodes. Furthermore, she avoided contact with diabetes health care. RESULTS: The 2 participants showed clinically significant improvements in their most relevant problem areas. In case 1, the participant's blood glucose levels reduced, and he was able to establish healthy routines, such as increase physical exercise and decrease overeating. In case 2, the participant's fear of hypoglycemia greatly decreased, and she was able to confront many of her avoided situations and increase necessary visits to her diabetes clinic. Treatment satisfaction was high, and no adverse events were reported. CONCLUSIONS: It is possible to deliver a cognitive behavioral therapy intervention aimed at problem areas in diabetes online. Problem solving appears to help with problems in everyday routines and lifestyle choices. Exposure to aversive stimuli appears to be a plausible intervention specifically aimed at the fear of hypoglycemia. Larger and controlled studies are needed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".