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Record W4214868455 · doi:10.2196/35332

Evaluation of Digital Interventions for Physical Activity Promotion: Protocol for a Scoping Review

2022· review· en· W4214868455 on OpenAlexvenueno aff
Karina Karolina De Santis, Tina Jahnel, Lea Mergenthal, Hajo Zeeb, Katja Matthias

Bibliographic record

VenueJMIR Research Protocols · 2022
Typereview
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
FundersLeibniz-GemeinschaftFreie Hansestadt Bremen
KeywordsPsycINFOCINAHLSystematic reviewContext (archaeology)Inclusion (mineral)Grey literaturePsychological interventionMEDLINEHealth promotionPromotion (chess)MedicineIntervention (counseling)PsychologyMedical educationNursingPublic healthPolitical scienceSocial psychology

Abstract

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BACKGROUND: Digital interventions (DIs) could support physical activity (PA) promotion, according to recent reviews. However, it remains unclear if and how DIs for PA promotion are evaluated; thus, it is unclear if they support behavior change in real-world settings. A mapping of evidence from published reviews is required to focus on the evaluation of DIs for PA promotion. OBJECTIVE: The aim of our study is to investigate evaluation strategies for any outcome in the context of DIs for PA promotion by conducting a scoping review of published reviews. METHODS: Our scoping review adheres to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The information sources include bibliographic databases (MEDLINE, PsycINFO, and CINAHL) and the bibliographies of the selected studies. The electronic search strategy was developed and conducted in collaboration with an experienced database specialist. The electronic search was conducted in English with no limits up to March 19, 2021, for sources with the terms digital intervention AND evaluation AND physical activity in titles or abstracts. After deduplication, 300 reviews selected from 4912 search results were assessed for eligibility by 2 authors working independently. The inclusion criteria were (1) healthy or clinical samples (population), (2) DIs for PA promotion (intervention), (3) comparisons to any other intervention or no intervention (comparison), (4) evaluation strategies (methods, results, or frameworks) for any outcome in the context of DIs for PA promotion (outcome), and (5) any published review (study type). According to the consensus reached during a discussion, 40 reviews met the inclusion criteria-36 from the electronic search and 4 from the manual search of the bibliographies of the 36 reviews. All reviews reported the evaluation strategies for any outcomes in the context of DIs for PA promotion in healthy or clinical samples. Data coding and the quality appraisal of systematic reviews are currently being performed independently by 2 authors. RESULTS: Our scoping review includes data from 40 published reviews (1 rapid review, 9 scoping reviews, and 30 systematic reviews). The focus of data coding is on evaluation strategies in the context of DIs for PA promotion and on the critical appraisal of the included systematic reviews. The final consensus regarding all data is expected in early 2022. CONCLUSIONS: Interventions for PA promotion that are supported by digital technologies require evaluation to ensure their efficacy in real-world settings. Our scoping review is needed because it addresses novel objectives that focus on such evaluations and are not answered in the published reviews identified in our search. The evaluation strategies addressing DIs for PA promotion will be mapped to synthesize the results that have been reported in published reviews so far. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35332.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptMetaresearch
Domain: Methods · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
opusMetaresearchMeta-epidemiology (broad)
Domain: Methods · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewmedium
models splitAgreement compares identical category sets and study designs across arms.

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)0.008
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.495
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.001
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 head0.934
GPT teacher head0.787
Teacher spread0.147 · 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

Labeled directly by 2 models reading the full record.

MetaresearchMeta-epidemiology (broad)

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review
DomainMethods
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
Published2022
Admission routes1
Has abstractyes

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