Hearing the unheard: an integrative review on telephone interviewing in public safety research
Bibliographic record
Abstract
Purpose In the current article, we explore how telephone interviewing can enhance disclosure among public safety personnel (PSP), a population often constrained by stigma, institutional barriers and confidentiality concerns. We address a gap in qualitative methods literature by centering voice and psychological safety in PSP research. Design/methodology/approach Through an integrative review and reflexive methodological analysis, the study synthesizes relevant literature on telephone interviewing, focusing on its application in PSP contexts. Thirteen epistemological considerations are organized thematically, and grounded in principles of methodological credibility, researcher positionality, adaptability and alignment with PSP communication preferences. Findings Telephone interviews reduce visual bias, foster disinhibition and may enhance/inhibit psychological safety. The method is particularly effective for reticent or hidden populations. Such circumstances suggest the method supports rich, candid engagement, offering both practical and ethical advantages in sensitive occupational settings. Research limitations/implications This reflexive review offers rigor but is not systematic and primarily focused on the North American context. It does not extensively engage with emerging modalities such as VoIP or smartphone-based interviews, which merit further investigation. Originality/value The study offers a novel framework for assessing the trade-offs of telephone interviewing in PSP research and applied the concept of disinhibition and emotional distance as a key consideration in this form of qualitative inquiry. We contribute original insights into how telephone methods can ethically and effectively access stigmatized voices in hidden populations, particularly PSP inhibited from speaking candidly.
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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 | 0.057 | 0.162 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".