Support Needs for Canadian Health Providers Responding to Disaster: New Insights from a Grounded Theory Approach
Bibliographic record
Abstract
Introduction: An earlier descriptive study exploring the various supports available to Canadian health and social service providers who deployed to the 2010 earthquake disaster in Haiti, indicated that when systems are compromised, professionals are at physical, emotional and mental risk during overseas deployment.While these risks are generally well-identified, there is little literature that explores the effectiveness of the supports in place to mitigate this risk.This study provides evidence to inform policy development regarding future disaster relief, and the effectiveness of supports available to responders assisting with international disaster response.Methods: This study follows Strauss and Corbin's 1990 structured approach to grounded theory to develop a framework for effective disaster support systems.N=21 interviews with Canadian health and social service providers, who deployed to Haiti in response to the 2010 earthquake, were conducted and analyzed.Resulting data were transcribed, coded and analysed for emergent themes.Results and Discussion: Three themes were identified in the data and were used to develop the evolving theory.The interview data indicate that the experiences of responders are determined based on an interaction between the individual's 'lens' or personal expectations, as well as the supports that an organization is able to provide.Therefore, organizations should consider the following factors: experience, expectations, and supports, to tailor a successful support initiative that caters to the needs of the volunteer workforce.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.032 | 0.014 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".