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Record W7027488666

Creating persuasive messages to promote abstinence from alcohol during pregnancy

2011· dissertation· en· W7027488666 on OpenAlexaboutno aff

Bibliographic record

VenueAustralasian Journal of Paramedicine · 2011
Typedissertation
Languageen
FieldArts and Humanities
TopicHistorical and Religious Studies of Rome
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsFormative assessmentAbstinencePregnancyFocus groupExploratory researchAlcoholHealth communication
DOInot available

Abstract

fetched live from OpenAlex

While the rates of Fetal Alcohol Spectrum Disorder within Australia are unknown, the rates of alcohol use during pregnancy and at-risk alcohol use by women of childbearing age highlight the need for universal prevention strategies addressing prenatal alcohol exposure. Though many awareness-raising campaigns for alcohol use during pregnancy have been conducted, predominantly in North America, they have rarely been developed using formative research nor have they been comprehensively evaluated (Saskatchewan Prevention Institute, 2009; Elliott et al., 2008). This lack of published information on the development and evaluation of campaigns makes it difficult to determine what communication elements are most credible and persuasive for the target audience. This study conducted theory-based formative research to develop and test messages suitable for a mass media campaign targeting women who may consume low to moderate levels of alcohol during pregnancy. In alignment with the Australian national guidelines for alcohol use by pregnant women (National Health and Medical Research Council, 2009), the aim was to create messages that increased women‟s intentions to abstain from alcohol during pregnancy. An exploratory phase comprising four focus groups with pregnant women and women of childbearing age living in Perth, Western Australia identified motivators for behaviour change and provided insight into the theoretical constructs that could be used to guide the creation of persuasive messages. Positive motivations for abstinence, such as a desire to feel in control and gain social approval were identified, as were several negative motivations, such as wanting to be free of fear and worry, and to avoid possible poor pregnancy outcomes. Along with constructs from social cognition models such as Protection Motivation Theory (Maddux & Rogers, 1983; Rogers, 1983, 1975), these data underpinned the development of a series of communication objectives and communication materials, such as television concept executions, and copy and graphics for print media. The communication materials were then tested through five focus groups with pregnant women, women of childbearing age and male partners to identify those that were most motivating, and to identify specific copy and execution elements that appeared to enhance the persuasiveness and credibility of messages. Two television concept executions, one a threat appeal based on fear and worry, and the other a positive appeal based on self-efficacy, had particularly good potential to motivate behaviour change. These became the basis for five final concept executions that were tested against a control with 685 women (520 women of childbearing age and 165 pregnant women). Results showed the concept executions containing a threat appeal were significantly more effective at increasing women‟s intentions to abstain from alcohol during pregnancy, compared with the control and positive appeal. This study provides evidence of messages effectively increasing women‟s intentions to abstain from alcohol during pregnancy. It demonstrates the value of using theory-based formative research with the target audience to inform the creation of messages that promote abstinence from alcohol during pregnancy. The results and recommendations have direct implications for the potential use of threat appeals and self-efficacy messages in mass media campaigns aimed at preventing prenatal alcohol exposure.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.268
Teacher spread0.240 · 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 designQualitative
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

Citations0
Published2011
Admission routes1
Has abstractyes

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