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Record W2768921520 · doi:10.1186/s12889-017-4919-y

Theories, models and frameworks used in capacity building interventions relevant to public health: a systematic review

2017· review· en· W2768921520 on OpenAlex

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

VenueBMC Public Health · 2017
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of TorontoUniversity of WaterlooPublic Health Ontario
Fundersnot available
KeywordsGrey literatureManagement sciencePsychological interventionCapacity buildingPublic healthSystematic reviewGovernment (linguistics)Knowledge managementMedicineData scienceComputer scienceMEDLINENursingPolitical scienceEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: There is limited research on capacity building interventions that include theoretical foundations. The purpose of this systematic review is to identify underlying theories, models and frameworks used to support capacity building interventions relevant to public health practice. The aim is to inform and improve capacity building practices and services offered by public health organizations. METHODS: Four search strategies were used: 1) electronic database searching; 2) reference lists of included papers; 3) key informant consultation; and 4) grey literature searching. Inclusion and exclusion criteria are outlined with included papers focusing on capacity building, learning plans, professional development plans in combination with tools, resources, processes, procedures, steps, model, framework, guideline, described in a public health or healthcare setting, or non-government, government, or community organizations as they relate to healthcare, and explicitly or implicitly mention a theory, model and/or framework that grounds the type of capacity building approach developed. Quality assessment were performed on all included articles. Data analysis included a process for synthesizing, analyzing and presenting descriptive summaries, categorizing theoretical foundations according to which theory, model and/or framework was used and whether or not the theory, model or framework was implied or explicitly identified. RESULTS: Nineteen articles were included in this review. A total of 28 theories, models and frameworks were identified. Of this number, two theories (Diffusion of Innovations and Transformational Learning), two models (Ecological and Interactive Systems Framework for Dissemination and Implementation) and one framework (Bloom's Taxonomy of Learning) were identified as the most frequently cited. CONCLUSIONS: This review identifies specific theories, models and frameworks to support capacity building interventions relevant to public health organizations. It provides public health practitioners with a menu of potentially usable theories, models and frameworks to support capacity building efforts. The findings also support the need for the use of theories, models or frameworks to be intentional, explicitly identified, referenced and for it to be clearly outlined how they were applied to the capacity building intervention.

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)0.086
metaresearch head score (Gemma)0.054
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.468
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0860.054
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.001
Bibliometrics0.0020.003
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.005
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 head0.875
GPT teacher head0.698
Teacher spread0.177 · 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