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Effect of Mobile Phone SMS on M-Health

2015· book-chapter· en· W2503699141 on OpenAlexaffabout
Mahmud Akhter Shareef, Jashim Uddin Ahmed, Vinod Kumar, Uma Kumar

Bibliographic record

VenueAdvances in human and social aspects of technology book series · 2015
Typebook-chapter
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsCarleton University
Fundersnot available
KeywordsMobile phonePerceptionMobile commerceAdvertisingPath analysis (statistics)PhonePsychologyShort Message ServiceBusinessUnified theory of acceptance and use of technologyMarketingInternet privacyTelecommunicationsApplied psychologyComputer scienceSocial psychologyExpectancy theory

Abstract

fetched live from OpenAlex

This chapter is engaged in identifying consumer perceptions regarding short message service (SMS) of the mobile phone as an alternative service delivery channel for Mobile-health (M-health) and studying the cultural impact of this change. In this connection, the Unified Theory of Acceptance and Use of Technology (UTAUT) model was used as the theoretical base to perceive consumer perceptions about M-health. The authors have performed an empirical study of diabetic patients in Bangladesh and Canada. Path analysis was conducted on the results of both samples. Analysis results confirmed that the UTAUT model fits quite nicely in predicting consumer perceptions of M-health-driven mobile technology. It also acknowledged that differences in cultural traits have an impact on consumer behavior.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.846
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.010
GPT teacher head0.316
Teacher spread0.306 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations5
Published2015
Admission routes2
Has abstractyes

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