Key factors for overcoming psychological insulin resistance: an examination of patient perspectives through content analysis
Bibliographic record
Abstract
Objective: To understand participant perceptions about insulin and identify key behaviors of healthcare professionals (HCPs) that motivated initially reluctant adults from seven countries (n=40) who had type 2 diabetes (T2D) to start insulin treatment. Research design and methods: Telephone interviews were conducted with a subset of participants from an international investigation of adults with T2D who were reluctant to start insulin (EMOTION). Questions related to: (a) participants' thoughts about insulin before and after initiation; (b) reasons behind responses on the survey that were either 'not helpful at all' or 'helped a lot'; (c) actions their HCP may have taken to help start insulin treatment; and (d) advice they would give to others in a similar situation of starting insulin. Responses were coded by two independent reviewers (kappa 0.992). Results: Starting insulin treatment was perceived as a negative experience that would be painful and would lead down a 'slippery slope' to complications. HCPs engaged in four primary behaviors that helped with insulin acceptance: (1) showed the insulin pen/needle and demonstrated the injection process; (2) explained how insulin could help with diabetes control and reduce risk of complications; (3) used collaborative communication style; and (4) offered support and willingness to answer questions so that participants would not be 'on their own'. Following initiation, most participants noted that insulin was not 'as bad as they thought' and recommended insulin to other adults with T2D. Conclusions: Based on these themes, two actionable strategies are suggested for HCPs to help people with psychological insulin resistance: (1) demonstrate the injection process and discuss negative perceptions of insulin as well as potential benefits; (2) offer autonomy in a person-centred collaborative approach, but provide support and accessibility to address concerns. These findings help HCPs to better understand ways in which they can engage reluctant people with T2D with specific strategies.
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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 | 0.011 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".