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Record W2767582930 · doi:10.2196/resprot.7755

The Effect of the Move More Pack on the Physical Activity of Cancer Survivors: Protocol for a Randomized Waiting List Control Trial with Process Evaluation

2017· article· en· W2767582930 on OpenAlexvenueno aff
Justin Webb, Chris Fife‐Schaw, Jane Ogden, J. Foster

Bibliographic record

VenueJMIR Research Protocols · 2017
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersUniversity of SurreyMacmillan Cancer Support
KeywordsProtocol (science)Randomized controlled trialMedicineProcess (computing)Physical therapyPsychologyComputer scienceAlternative medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Physical activity can improve many common side effects of cancer treatment as well as improve physical function and quality of life (QOL). In addition, physical activity can improve survival rate and reduce cancer recurrence. Despite these benefits, only 23% of cancer survivors in England are active to recommended levels. Cancer survivors are interested in lifestyle behavior change. Home-based interventions offer a promising means for changing physical activity behavior. Prediagnosis levels of physical activity and self-efficacy have been reported to be predictors of physical activity behavior change. The Move More Pack, which has undergone revision, is a printed resource with supporting Internet-based tools that aims to increase the physical activity of cancer survivors in the United Kingdom. The revised Move More Pack is underpinned by the theory of planned behavior and the social cognitive theory. OBJECTIVE: The aim of this proposed study was to investigate the effect of the revised Move More Pack, supported by Internet-based tools, on physical activity, self-efficacy, and health-related QOL (HRQOL) of cancer survivors in the United Kingdom. METHODS: This study is a two-arm waiting list randomized control trial with embedded process evaluation. A sample of 99 participants per arm will be recruited by invitation through an email database of cancer survivors held by UK charity Macmillan Cancer Support and an advert placed on the Macmillan Cancer Support Facebook page. Each participant is randomized to receive brief physical activity information and the UK guidelines for physical activity, or brief physical activity information and the revised Move More Pack with supporting Internet-based tools. The intervention and control arm will be followed up at 12 weeks to identify changes in self-reported physical activity, self-efficacy, and HRQOL based on Web-based questionnaires. The control arm will receive the revised Move More Pack at 12 weeks with follow-up at 24 weeks. The intervention arm is followed up at 24 weeks to determine maintenance of reported changes. Subgroup analyses will be completed based on participants' prediagnosis level of physical activity and baseline self-efficacy as possible predictors of positive changes. Use of each component of the revised Move More Pack will be assessed using a 4-point Likert scale. Semistructured phone interviews will evaluate the use and perceived usefulness of the revised Move More Pack. RESULTS: Participant recruitment started in March 2017. Projected completion of this study is October 2018. CONCLUSIONS: This study's findings will identify if the proposed low-cost broad reach intervention improves physical activity, self-efficacy, and the HRQOL of cancer survivors. The process evaluation is designed to contextualize the use and perceived usefulness of the revised Move More Pack, help augment its efficient distribution, and identify potential improvements to its design.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.080
Threshold uncertainty score0.268

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.029
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0110.005
Bibliometrics0.0030.003
Science and technology studies0.0040.005
Scholarly communication0.0040.004
Open science0.0030.002
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0800.012

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 head0.170
GPT teacher head0.585
Teacher spread0.415 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2017
Admission routes1
Has abstractyes

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