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Record W2009798066 · doi:10.3138/physio/60/1/40

Theory-Based Programme Development and Evaluation in Physiotherapy

2008· article· en· W2009798066 on OpenAlexaffvenue
Maria Huijbregts, Theresa Kay, Beth Klinck

Bibliographic record

VenuePhysiotherapy Canada · 2008
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsUniversity of TorontoLakehead UniversityBaycrest Hospital
Fundersnot available
KeywordsProcess managementProcess (computing)Computer scienceTheory of changeKey (lock)Management scienceKnowledge managementEngineering

Abstract

fetched live from OpenAlex

PURPOSE: Programme evaluation has been defined as "the systematic process of collecting credible information for timely decision making about a particular program." Where possible, findings are used to develop, revise, and improve programmes. Theory-based programme development and evaluation provides a comprehensive approach to programme evaluation. SUMMARY OF KEY POINTS: In order to obtain meaningful information from evaluation activities, relevant programme components need to be understood. Theory-based programme development and evaluation starts with a comprehensive description of the programme. A useful tool to describe a programme is the Sidani and Braden Model of Program Theory, consisting of six programme components: problem definition, critical inputs, mediating factors, expected outcomes, extraneous factors, and implementation issues. Articulation of these key components may guide physiotherapy programme implementation and delivery and assist in the development of key evaluation questions and methodologies. Using this approach leads to a better understanding of client needs, programme processes, and programme outcomes and can help to identify barriers to and enablers of successful implementation. Two specific examples, representing public and private sectors, will illustrate the application of this approach to clinical practice. CONCLUSIONS: Theory-based programme development helps clinicians, administrators, and researchers develop an understanding of who benefits the most from which types of programmes and facilitates the implementation of processes to improve programmes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.110
GPT teacher head0.471
Teacher spread0.361 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2008
Admission routes2
Has abstractyes

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