Uptake of Tailored Text Message Smoking Cessation Support in Pregnancy When Advertised on the Internet (MiQuit): Observational Study.

BACKGROUND: Smoking in pregnancy is a major public health concern. Pregnant smokers are particularly difficult to reach, with low uptake of support options and few effective interventions. Text message-based self-help is a promising, low-cost intervention for this population, but its real-world uptake is largely unknown. OBJECTIVE: The objective of this study was to explore the uptake and cost-effectiveness of a tailored, theory-guided, text message intervention for pregnant smokers ("MiQuit") when advertised on the internet. METHODS: Links to a website providing MiQuit initiation information (texting a short code) were advertised on a cost-per-click basis on 2 websites (Google Search and Facebook; £1000 budget each) and free of charge within smoking-in-pregnancy webpages on 2 noncommercial websites (National Childbirth Trust and NHS Choices). Daily budgets were capped to allow the Google and Facebook adverts to run for 1 and 3 months, respectively. We recorded the number of times adverts were shown and clicked on, the number of MiQuit initiations, the characteristics of those initiating MiQuit, and whether support was discontinued prematurely. For the commercial adverts, we calculated the cost per initiation and, using quit rates obtained from an earlier clinical trial, estimated the cost per additional quitter. RESULTS: With equal capped budgets, there were 812 and 1889 advert clicks to the MiQuit website from Google (search-based) and Facebook (banner) adverts, respectively. MiQuit was initiated by 5.2% (42/812) of those clicking via Google (95% CI 3.9%-6.9%) and 2.22% (42/1889) of those clicking via Facebook (95% CI 1.65%-2.99%). Adverts on noncommercial webpages generated 53 clicks over 6 months, with 9 initiations (9/53, 17%; 95% CI 9%-30%). For the commercial websites combined, mean cost per initiation was £24.73; estimated cost per additional quitter, including text delivery costs, was £735.86 (95% CI £227.66-£5223.93). Those initiating MiQuit via Google were typically very early in pregnancy (median gestation 5 weeks, interquartile range 10 weeks); those initiating via Facebook were distributed more evenly across pregnancy (median gestation 16 weeks, interquartile range 14 weeks). CONCLUSIONS: Commercial online adverts are a feasible, likely cost-effective method for engaging pregnant smokers in digital cessation support and may generate uptake at a faster rate than noncommercial websites. As a strategy for implementing MiQuit, online advertising has large reach potential and can offer support to a hard-to-reach population of smokers.

Cognitive and Behavioral Predictors of Quit Attempts and Biochemically-Validated Abstinence During Pregnancy.

INTRODUCTION: Initiating a quit attempt and achieving abstinence are distinct behaviors that have distinct correlates in general smokers. Studies predicting prenatal smoking have not addressed this. METHODS: Pregnant smokers (N = 207), recruited to a cessation intervention trial, were used as an observational cohort. Women completed measures at baseline and 12-week follow-up (mid-late pregnancy). Outcomes were having made at least one quit attempt since baseline, and cotinine-validated 7-day abstinence at follow-up in attempters. Baseline predictors included demographics (age, deprivation, partner's smoking), smoking behaviors (nicotine dependence, quit attempt history, previous prenatal smoking), and smoking beliefs (self-efficacy, determination, intention to quit, nonsmoker identity, social support, pregnancy-outcome beliefs). For each outcome, variables reaching p < .1 in logistic regression analyses were entered into a multivariate model controlling for trial arm. A complete case analysis was undertaken, with missing data assumptions tested in sensitivity analyses. RESULTS: One hundred seventy-five women (85%) completed follow-up. Intention and determination to quit (p < .001), self-efficacy, nonsmoker identity, and not having previously smoked in pregnancy (p < .05) were univariate predictors of making a quit attempt, with stronger intention to quit the only independent predictor (multivariate odds ratio [OR] = 2.41, 95% confidence interval [CI] 1.19-4.87). Only nicotine dependence predicted validated abstinence among those who made a quit attempt (multivariate OR = 0.25, 95% CI 0.10-0.60). CONCLUSIONS: Initiating a quit attempt and achieving abstinence during pregnancy were found to have different correlates. For women yet to make a quit attempt in their pregnancy, smoking beliefs may be important intervention targets, but once they are engaged in quitting, nicotine dependence appears of prime importance. IMPLICATIONS: This study suggests that cognitive, particularly motivational, variables predict whether pregnant smokers will make a quit attempt, but they do not predict successful abstinence in those who attempt to quit, where nicotine dependence dominates. Interventions should facilitate quit attempts by targeting motivational variables among pregnant women who continue to smoke, but should focus on managing withdrawal once a woman initiates a quit attempt.

The BioMedical Admissions Test for medical student selection: issues of fairness and bias.

BACKGROUND: The BioMedical Admissions Test (BMAT) forms part of the undergraduate medical admission process at the University of Cambridge. The fairness of admissions tests is an important issue. AIMS: Aims were to investigate the relationships between applicants' background variables and BMAT scores, whether they were offered a place or rejected and, for those admitted, performance on the first year course examinations. METHOD: Multilevel regression models were employed with data from three combined applicant cohorts. Admission rates for different groups were investigated with and without controlling for BMAT performance. The fairness of the BMAT was investigated by determining, for those admitted, whether scores predicted examination performance equitably. RESULTS: Despite some differences in applicants' BMAT performance (e.g. by school type and gender), BMAT scores predicted mean examination marks equitably for all background variables considered. The probability of achieving a 1st class examination result, however, was slightly under-predicted for those admitted from schools and colleges entering relatively few applicants. Not all differences in admission rates were accounted for by BMAT performance. However, the test constitutes only one part of a compensatory admission system in which other factors, such as interview performance, are important considerations. CONCLUSION: Results are in support of the equity of the BMAT.

The predictive validity of the BioMedical Admissions Test for pre-clinical examination performance.

CONTEXT: Some medical courses in the UK have many more applicants than places and almost all applicants have the highest possible previous and predicted examination grades. The BioMedical Admissions Test (BMAT) was designed to assist in the student selection process specifically for a number of 'traditional' medical courses with clear pre-clinical and clinical phases and a strong focus on science teaching in the early years. It is intended to supplement the information provided by examination results, interviews and personal statements. This paper reports on the predictive validity of the BMAT and its predecessor, the Medical and Veterinary Admissions Test. METHODS: Results from the earliest 4 years of the test (2000-2003) were matched to the pre-clinical examination results of those accepted onto the medical course at the University of Cambridge. Correlation and logistic regression analyses were performed for each cohort. RESULTS: Section 2 of the test ('Scientific Knowledge') correlated more strongly with examination marks than did Section 1 ('Aptitude and Skills'). It also had a stronger relationship with the probability of achieving the highest examination class. CONCLUSIONS: The BMAT and its predecessor demonstrate predictive validity for the pre-clinical years of the medical course at the University of Cambridge. The test identifies important differences in skills and knowledge between candidates, not shown by their previous attainment, which predict their examination performance. It is thus a valid source of additional admissions information for medical courses with a strong scientific emphasis when previous attainment is very high.

Measurement of body size and shape perception in eating-disordered and control observers using body-shape software.

A disturbance in the perception of personal body size and shape is a key feature of both anorexia and bulimia nervosa, but it has proved difficult to quantify. Previous attempts have used methods like the distorting video technique (DVT), which alters an image by stretching the figure in either the X- or Y-axis. This is a poor representation of the way fat is added to or lost from the body, and the pattern of distortion provides a host of cues to the degree to which the image has been altered. To overcome these problems we have used a specially designed software system that uses biometric data based on real body shapes, instead of simply stretching or compressing images of bodies. This technique also allows individual body parts to be altered separately, so we can determine whether a specific body part is overestimated relative to others. We can also calculate the apparent body mass index (BMI) of our modified pictures, using the perimeter-area ratio (PAR). This allows us to compare an observer's actual BMI with that calculated for their estimated and ideal bodies. We tested 30 anorexic, 30 bulimic and 137 control observers. Our results show that all three observer groups tend to overestimate their body size, but not significantly so. Both the control and bulimic observers prefer an ideal body with a BMI of 20, which is at the lower end of the 'normal' BMI range. However, the anorexics ideal BMI is 15, which is on the border between the emaciated and underweight BMI categories.