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Record W4285613051 · doi:10.1177/26334895221112693

Training primary health care providers in Colombia, Mexico and Peru to increase alcohol screening: Mixed-methods process evaluation of implementation strategy

2022· article· en· W4285613051 on OpenAlex
Daša Kokole, Eva Jané‐Llopis, Guillermina Natera Rey, Natalia Bautista Aguilar, Perla Sonia Medina Aguilar, Juliana Mejía‐Trujillo, Katherine Mora, Natalia Restrepo, Inés Bustamante, Marina Piazza, Amy O’Donnell, Adriana Solovei, Liesbeth Mercken, Christiane Sybille Schmidt, Hugo López‐Pelayo, Silvia Matrai, Fleur Braddick, Antoni Gual, Jürgen Rehm, Peter Anderson, Hein de Vries

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueImplementation Research and Practice · 2022
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of TorontoMental Health Research Canada
FundersH2020 Societal ChallengesNational Institute for Health and Care Research
KeywordsMedicineFamily medicineDocumentationPrimary careNursingMedical educationPsychology

Abstract

fetched live from OpenAlex

Background: Initial results from the SCALA study demonstrated that training primary health care providers is an effective implementation strategy to increase alcohol screening in Colombia, Mexico and Peru, but did not show evidence of superior performance for the standard compared to the shorter training arm. This paper elaborates on those outcomes by examining the relationship of training-related process evaluation indicators with the alcohol screening practice. Methods: A mix of convergent and exploratory mixed-methods design was employed. Data sources included training documentation, post-training questionnaires, observation forms, self-report forms and interviews. Available quantitative data were compared on outcome measure - providers' alcohol screening. Results: Training reach was high: three hundred fifty-two providers (72.3% of all eligible) participated in one or more training or booster sessions. Country differences in session length reflected adaptation to previous topic knowledge and experience of the providers. Overall, 49% of attendees conducted alcohol screening in practice. A higher dose received was positively associated with screening, but there was no difference between standard and short training arms. Although the training sessions were well received by participants, satisfaction with training and perceived utility for practice were not associated with screening. Profession, but not age or gender, was associated with screening: in Colombia and Mexico, doctors and psychologists were more likely to screen (although the latter represented only a small proportion of the sample) and in Peru, only psychologists. Conclusions: Primary health care providers can play an important role in detecting heavy drinkers among their consulting patients, and training can be an effective implementation strategy to increase alcohol screening and detection. Existing training literature predominantly focuses on evaluating trainings in high-income countries, or evaluating their effectiveness rather than implementation. As part of SCALA (Scale-up of Prevention and Management of Alcohol Use Disorders in Latin America) study, we evaluated training as implementation strategy to increase alcohol screening in primary health care in a middle-income context. Overall, 72.3% of eligible providers attended the training and 49% of training attendees conducted alcohol screening in practice after attending the training. Our process evaluation suggests that simple intervention with sufficient time to practice, adapted to limited provider availability, is optimal to balance training feasibility and effectiveness; that booster sessions are especially important in context with lower organizational or structural support; and that ongoing training refinement during the implementation period is necessary.

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.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.317
GPT teacher head0.614
Teacher spread0.298 · 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