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Record W2283569805 · doi:10.1186/s12906-016-1059-3

Reasons for continuing use of Complementary and Alternative Medicine (CAM) in students: a consumer commitment model

2016· article· en· W2283569805 on OpenAlexafffund
Fuschia M. Sirois, Anita Salamonsen, Agnete E. Kristoffersen

Bibliographic record

VenueBMC Complementary and Alternative Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsUniversity of Windsor
FundersUniversity of Windsor
KeywordsVariance (accounting)Test (biology)PsychologyPerceptionSocial psychologyVariablesValue (mathematics)Sample (material)MedicineClinical psychologyApplied psychologyStatisticsMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: Research on continued CAM use has been largely atheoretical and has not considered the broader range of psychological and behavioral factors that may be involved. The purpose of this study was to test a new conceptual model of commitment to CAM use that implicates utilitarian (trust in CAM) and symbolic (perceived fit with CAM) in psychological and behavioral dimensions of CAM commitment. METHODS: A student sample of CAM consumers, (N = 159) completed a survey about their CAM use, CAM-related values, intentions for future CAM use, CAM word-of-mouth behavior, and perceptions of being an ongoing CAM consumer. RESULTS: Analysis revealed that the utilitarian, symbolic, and CAM commitment variables were significantly related, with r's ranging from .54 to .73. A series hierarchical regression analyses controlling for relevant demographic variables found that the utilitarian and symbolic values uniquely accounted for significant and substantial proportion of the variance in each of the three CAM commitment indicators (R(2) from .37 to .57). CONCLUSIONS: The findings provide preliminary support for the new model that posits that CAM commitment is a multi-dimensional psychological state with behavioral indicators. Further research with large-scale samples and longitudinal designs is warranted to understand the potential value of the new model.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.163
GPT teacher head0.398
Teacher spread0.236 · 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 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

Citations26
Published2016
Admission routes2
Has abstractyes

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