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Record W2055163597 · doi:10.1155/2014/245347

Long-Term Effect of Interactive Online Dietician Weight Loss Advice in General Practice (LIVA) Protocol for a Randomized Controlled Trial

2014· article· en· W2055163597 on OpenAlexaff
Carl J. Brandt, Vibeke Brandt, Mathilde Pedersen, Dorte Glintborg, Søren Toubro, Jesper Bo Nielsen, Günther Eysenbach, Kirsten Brandt, Jens Søndergaard

Bibliographic record

VenueInternational Journal of Family Medicine · 2014
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsInstitute of Health Services and Policy ResearchUniversity of Toronto
Fundersnot available
KeywordsRandomized controlled trialMedicineAdvice (programming)Protocol (science)Term (time)Weight lossGeneral practiceAlternative medicineFamily medicineComputer scienceInternal medicinePathology

Abstract

fetched live from OpenAlex

Background. Internet-based complex interventions aiming to promote weight loss and optimize healthy behaviors have attracted much attention. However, evidence for effect is lacking. Obesity is a growing problem, resulting in an increasing demand for cost efficient weight loss programs suitable for use on a large scale, for example, as part of standard primary care. In a previous pilot project by Brandt et al. (2011) without a control group, we examined the effects of online dietician counseling and found an average weight loss of 7.0 kg (95% CI: 4.6 to 9.3 kg) after 20 months. Aims and Methods. To analyze the effects of a complex intervention using trained dieticians in a general practice setting combined with internet-based interactive and personalized weight management support compared with conventional advice with a noninteractive internet support as placebo treatment in 340 overweight patients during a 2-year period. Primary endpoints are weight loss and lowering of cholesterol (LDL). We will also explore patients' sociodemographics and use of the intervention as well as the health professionals' views and perceptions of the intervention (their role and the advice and support that they provide). Perspective. The project will generate knowledge on the cost-effectiveness of a complex internet-based intervention in a general practice setting and on barriers and acceptability among professionals and patients.

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)0.010
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.050
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.520
Teacher spread0.477 · 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.

Study designRandomized trial
Domainnot available
GenreProtocol

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

Citations11
Published2014
Admission routes1
Has abstractyes

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