Call me, later! Patients’ experiences of Swedish healthcare call-back services and access to healthcare
Bibliographic record
Abstract
Objective: Despite the wide use of telephone call-back services in Swedish healthcare, there has been little research on how it affects patients. This study explores individual experiences of a call-back service, concentrating on barriers to healthcare, and healthcare-seeking behavior.Methods: The study was conducted at Angered Hospital and Angered Primary Care Rehabilitation Center in Gothenburg, Sweden. Ten informants, 28-82 years old, who had used the call-back service participated in interviews about their experience of the call-back service. Thematic analysis was used to analyze data from the interviews.Results: Three themes were identified in the analysis: (1) features and functions of the call-back service; (2) the call-back service as a barrier to or facilitator of healthcare; and (3) adjustments to the call-back service. Most informants were content with the call-back function. Negative experiences were related to language difficulties and the length of time allowed during the phone call. Lack of available appointments and telephone access were problems reported. Informants suggested a longer time frame for calls, longer opening hours regarding telephone access, more language and voicemail options, and the possibility of speaking to a person.Conclusions: Informants in this study mostly had a positive impression of seeking healthcare using call-back services. Barriers related to language and time frame for calls could be explored in larger studies. The results from this explorative study suggests that a combination of approaches – with other options added to the call-back services - might increase equal access to health care. The use and effects of call-back services warrant further investigation.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".