Challenges, Coping Strategies, and Recommendations Related to the HIV Services Field in the HAART Era: A Systematic Literature Review of Qualitative Studies from the United States and Canada
Bibliographic record
Abstract
Qualitative research methods have been utilized to study the nature of work in the HIV services field. Yet current literature lacks a Highly Active Anti-Retroviral Treatment (HAART) era compendium of qualitative research studying challenges and coping strategies in the field. This study systematically reviewed challenges and coping strategies that qualitative researchers observed in the HIV services field during the HAART era, and their recommendations to organizations. Four online databases were searched for peer-reviewed research that utilized qualitative methods, were published from January 1998 to February 2012, utilized samples of individuals in the HIV services field; occurred in the U.S. or Canada, and contained information related to challenges and/or coping strategies. Abstracts were identified (n=846) and independently read and coded for inclusion by at least two of the four first authors. Identified articles (n=26) were independently read by at least two of the four first authors who recorded the study methodology, participant demographics, challenges and coping strategies, and recommendations. A number of challenges affecting those in the HIV services field were noted, particularly interpersonal and organizational issues. Coping strategies were problem- and emotion-focused. Summarized research recommendations called for increased support, capacity-building, and structural changes. Future research on challenges and coping strategies must provide up-to-date information to the HIV services field while creating, implementing, and evaluating interventions to manage current challenges and reduce the risk of burnout.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".