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Record W3022091634 · doi:10.5539/jedp.v10n1p71

Reliability and Validity of the Perceived Neighborhood Food Environment Scale

2020· article· en· W3022091634 on OpenAlexvenueno aff
Mihono Komatsu, Rie Akamatsu, Emi Yoshii, Mika Saiki

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2020
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceUniversity of TokyoCabinet Office, Government of Japan
KeywordsPsychologyCronbach's alphaScale (ratio)Confirmatory factor analysisReliability (semiconductor)ValidityExploratory factor analysisCriterion validitySocial psychologyStructural equation modelingConstruct validityApplied psychologyClinical psychologyPsychometricsStatisticsMathematicsGeography

Abstract

fetched live from OpenAlex

In order for people to make healthy food choices, the food environment needs to be improved and residents must be aware of it. This research aimed to assess the reliability and validity of the Perceived Neighborhood Food Environment (PNFE) scale, which assesses participants’ perceptions of the present condition of their food environment. Data from the Survey on the Present Condition and Consciousness of Dietary Education conducted by the Cabinet Office of Japan in 2010 were used, and 1,853 participants were included. We performed an exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), and examined internal consistency and the criterion-related validity of the PNFE. The PNFE comprised two factors: “regional food culture” (5 items) and “physical availability of food” (3 items). The model fitness indices were good (GFI = .97, AGFI = .95, CFI = .96, RMSEA = .073) and Cronbach’s α was .77 for the whole scale. Reasonable results were obtained for criterion-related validity. We confirmed the reliability and validity of the PNFE scale. By utilizing the scale for future research in other countries, its reliability and validity for a wider range of residents will likely be confirmed. In addition, consideration should be given to the items used for confirming the validity of the scale in the next study to ensure that they are appropriate for other countries included in the research.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.298
Teacher spread0.260 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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