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Record W2766322322 · doi:10.2196/humanfactors.7670

Formative Assessment: Design of a Web-Connected Sedentary Behavior Intervention for Females

2017· article· en· W2766322322 on OpenAlexvenueno aff
Amber W. Kinsey, Matthew Whipple, Lauren A. Reid, Olivia Affuso

Bibliographic record

VenueJMIR Human Factors · 2017
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsFormative assessmentIntervention (counseling)PsychologyWorld Wide WebComputer scienceApplied psychologyMathematics education

Abstract

fetched live from OpenAlex

BACKGROUND: Sedentary behavior (SB) is a significant risk factor for heart disease, diabetes, obesity, and early mortality, particularly among women, and the health consequences associated with SB are independent of physical activity status. Interventions utilizing wearable technologies can improve SB, but their effectiveness is influenced by individual preferences, device engagement strategies, and technological features, which may affect user compliance. Gathering a priori insight from target populations on their preferences for program tools and strategies may assist researchers in identifying effective methods to improve the efficacy of SB interventions. OBJECTIVE: The objective of this study was to (1) explore the likeability (likes and dislikes) and usability (engagement intentions and navigation) of a wearable device (Movband) and its accompanying website (dashboard), (2) examine social incentive preferences (teammates), and (3) assess the feasibility (participants' experiences during an activity-monitoring period) of these tools for use in an intervention to reduce SB in girls and women. METHODS: A total of 9 girls (mean age: 8.9 years, standard deviation [SD] 1.1 years) and 11 college-aged women (mean age: 22.6 years, SD 3.2 years) participated in this study. Separate focus groups were held for girls and women, and all participants attended one before and the other following a 7-day activity-monitoring period. During the focus groups, participants were prompted with questions to address the study aims, and the nominal group technique was used to compile lists of group-specific preferences for the activity-monitoring system. The top three ranking likes and dislikes were reverse coded to determine likeability. RESULTS: The top-ranking responses for the girls and women were the following: visual display of movements and ease of navigation (dashboard like), boring to look at and no calorie-tracking function (dashboard dislike), backlight and long battery life (Movband like), and color and not waterproof (tied for girls) and vertical time display (Movband dislike). Additionally, participants identified several aesthetic preferences and functional limitations. At the second focus group visit, the majority of the participants self-reported less SB during the previous week. Objective data from the activity-monitoring period revealed that the average steps per day for girls and women were 12,373.4 (SD 2617.6) and 8515.8 (SD 3076.7), respectively. CONCLUSIONS: These results suggest that the girls and women liked many features of the Movband and dashboard. However, several dislikes were mentioned, which may negatively influence compliance and the effectiveness of the activity-monitoring system and require improvements before using in an SB 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.

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)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.183
GPT teacher head0.459
Teacher spread0.276 · 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 designNot applicable
Domainnot available
GenreMethods

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".

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Citations1
Published2017
Admission routes1
Has abstractyes

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