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Record W2978474702 · doi:10.1097/qad.0000000000002339

Workforce development needs in HIV care

2019· letter· en· W2978474702 on OpenAlexaff
Daria Boccher‐Lattimore, Mari Millery, Karen McKinnon, Mingjie Li, Francine Cournos

Bibliographic record

VenueAIDS · 2019
Typeletter
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsColumbia College
Fundersnot available
KeywordsWorkforceMental healthMedicineHealth careWorkforce developmentDelphi methodNursingMandatePsychological interventionPopulationPublic healthGerontologyPolitical scienceEnvironmental healthPsychiatry

Abstract

fetched live from OpenAlex

Remien et al.[1] rightly contend that ‘efforts to end the HIV epidemic… will not be achieved without addressing the significant mental health and substance use problems among people living with HIV (PLWH) and people vulnerable to acquiring HIV.’ They point out that we have ‘the necessary screening tools and efficacious treatments to treat mental health problems’ in this population. However, insufficient attention has been given to the how of integration. Barriers to implementing efficacious interventions have been extensively documented [2]. In reality, ‘global access to mental healthcare’ for PLWH is only aspirational without a workforce and care system that can put the integration of behavioral healthcare and HIV care into practice. We used the Delphi method [3] to investigate what HIV experts, clinicians and leaders perceive as the most urgent HIV workforce training needs in US Department of Health and Human Services (USDHHS) Region 2: New Jersey, New York, Puerto Rico, and the US Virgin Islands. The study was conducted in 2016 by the Northeast/Caribbean AIDS Education and Training Center (NECA AETC), which is funded by the Ryan White Part F AETC program to serve USDHHS Region 2. The AETC mandate is to ensure a public health response to HIV that builds the capacity of the healthcare system and develops a skilled and culturally competent workforce. Our study involved three rounds of surveys consistent with the Delphi technique [4] for reaching expert consensus on needs with the highest urgency to address. To obtain a comprehensive perspective, the survey team identified 116 expert panel members in the NECA region representing four areas: training (e.g., Program Managers or Clinical Directors of training programs), healthcare policy development (e.g., Medical Director of State Department of Health), healthcare systems (e.g., Chief Executive Officer of a healthcare program), and clinical leadership (e.g., Clinical Director of an HIV medicine program in an academic medical center). Panel members had substantive knowledge and expertise in HIV healthcare systems and training needs. Individuals with multiple roles were classified according to their primary nonclinical administrative positions; thus, exclusively clinical leaders were a small group. Panelists were invited to participate in this Delphi study through E-Mail invitation. No compensation was available. Panel composition in each round of the survey and Round 3 results are displayed in Table 1.Table 1: Delphi panel composition in each survey round and Round 3 top 10 urgent training priorities ranked by panelists.In the first survey round, panelists were asked to list 5–10 ‘specific HIV-related needs that are important to address through training and technical assistance’. Following collection of the first round of survey responses, the research team consolidated the received written answers into a new structured questionnaire. To do so, two separate research team members reviewed all written responses and independently grouped them into categories. Responses with identical or similar wording and meaning were combined. The researchers then met to create a combined categorization of the responses, based on discussion of responses that required interpretation. In total, 42 items were identified. This entire list of items was included in the second-round ratings. In the second round, the Delphi panelists received this new survey asking them to rate each extracted item on an urgency level using a five-point Likert scale: ‘Not urgent’, ‘A little urgent’, ‘Moderately urgent’, ‘Very urgent’, and ‘Extremely urgent’ (coded as 1–5). Items with the highest mean ratings were included in the next round survey. Finally, the panelists received another new survey asking them to rank the previously highest rated items. The final results are based on the collective average round three rankings among the panel members (Table 1). Although we knew that mental health was important, we were surprised to see ‘HIV and mental health’ identified as the most urgent training need, surpassing such topics as retention in care and viral suppression. The survey represents the voices of healthcare providers and leaders in a highly HIV-impacted region of the United States. If ‘HIV and mental health’ is the most urgent training need in our region, we can assume that there is considerable awareness of the impact of behavioral health problems on the HIV care continuum but a great gap in confidence that we are successfully addressing those needs. We cannot improve access to mental healthcare for PLWH without a workforce and healthcare system with the capacity to provide that care. History has shown that efforts to build the workforce will pay for themselves as the epidemic comes under better control and new infections are averted [5]. Acknowledgements The current work was supported by USDHHS HRSA grant number U1OHA29291. Conflicts of interest There are no conflicts of interest.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.293
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.003

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.

Opus teacher head0.029
GPT teacher head0.316
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations3
Published2019
Admission routes1
Has abstractyes

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