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Record W2294971371 · doi:10.2196/mhealth.4764

Preferred Tone of Nutrition Text Messages for Young Adults: Focus Group Testing

2016· article· en· W2294971371 on OpenAlexvenueno aff
Christina Pollard, Peter Howat, I. Pratt, Carol J. Boushey, Edward J. Delp, Deborah A. Kerr

Bibliographic record

VenueJMIR mhealth and uhealth · 2016
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersHealthway
KeywordsFocus groupYoung adultFacilitatorPsychologyPreferenceHealth communicationHealth promotionPerceptionMedicineSocial psychologyDevelopmental psychologyPublic healthCommunication

Abstract

fetched live from OpenAlex

BACKGROUND: Young adults are a particularly hard to reach group using conventional health promotion practices as they do not see nutrition messages as personally relevant to them. Text messaging (short message service, SMS) offers an innovative approach to reaching young adults to support and promote dietary behavior change. OBJECTIVE: The aim of this study was to develop and test tonal preferences for nutrition text messages among young adults using focus groups. METHODS: A total of 39 young adults aged 18-30 years residing in Perth, Western Australia participated in four focus groups. Participants briefly discussed their perception of healthy eating and their responses to messages about increasing fruit and vegetables, and reducing "junk food" and alcohol intake. They ranked their preference for 15 nutrition messages across 3 dietary behaviors (fruit and vegetables, junk food, and alcohol) with 5 different message tones (authoritative, empathetic, generation Y, solutions, and substitutions) and identified the messages most likely to persuade young adults to change their diet. A 5-point ranking of the nutrition messages was from the most likely to least likely to persuade (1-5). The focus groups were conducted by a trained facilitator and observer and were recorded. Data driven content analysis was used to explore themes. Tonal preferences and potential motivators were collated and frequencies presented. RESULTS: Participants ranked offering substitutes (29%, 11/39) and using empathy (22%, 9/39) as the most persuasive message techniques in improving diets of young adults, with low responses for Generation Y (17%, 7/39), solutions (17%, 7/39), and authoritative (15%, 6/39) tones. Females were more likely to consider substitution messages persuasive (35%, 7/20) compared with males (22%, 4/19). A greater proportion of males compared with females considered authoritative messages persuasive: (22%, 4/19) compared with (7%, 1/20). There is a strong preference for a substitution tone for fruit and vegetable messages (52%, 20/39), and no overall message tone preference for junk food and alcohol messages. Substitutions were viewed as helpful and practical. Empathy was liked as it acknowledged previous efforts. Responses to authoritative tone were mixed with some feeling guilt while others found them informative. Acceptability of the solutions depended on the behavioral change and acceptability of the solution proposed. Generation Y tone had some support for junk food and alcohol messages, and if favored, was considered casual, humorous, catchy, and motivational. CONCLUSIONS: Substitutions and tone of empathy were favored as the most likely execution styles to motivate nutrition behavior change across all participants. There is no "one size fits all" with different tones preferred by individuals for different dietary behaviors. Although text messaging provides instant message delivery direct to the individual, these results demonstrate the complexity of developing motivational nutrition message for young adults. These findings reveal the importance of considering the tone and content and pretesting messages for health promotion text message interventions.

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)0.002
metaresearch head score (Gemma)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
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 head0.085
GPT teacher head0.447
Teacher spread0.362 · 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 designOther design
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

Citations43
Published2016
Admission routes1
Has abstractyes

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