Nicodermal patch adherence and its correlates

Alterman, Arthur I.; Gariti, Peter; Cook, Terry; Cnaan, Avital

doi:10.1016/s0376-8716(98)00124-0

Cited by 76 publications

(84 citation statements)

References 13 publications

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“…P = primary outcome; S = secondary outcome;* significant at P < 0.05;** significant at P < 0.01;*** significant at P < 0.001;RaR = rate ratio; RR = relative risk; OR = odds ratio; MD = mean difference;Ω range of population SD reflects the CI of the expected effect size;α range of population SD based on opinion on a viable effect; a one‐directional relationship was assumed in all instances; Based on:a 31;b 32;c 33;d 34;e 35;f 36;g values specified in the sample size calculation;h 37;i 38;j 39;k 40;l 41;m 42;n 43;o 44;p 45;q 46;r 47;s 48;t 49;u 50;v 51;w 52;z 53;y values specified in the sample size calculation.HAMD = Hamilton Rating Scale for Depression; p.p.m. = parts per million.…”

Section: Methodsmentioning

confidence: 99%

Using Bayes factors for testing hypotheses about intervention effectiveness in addictions research

et al. 2016

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Background and AimsIt has been proposed that more use should be made of Bayes factors in hypothesis testing in addiction research. Bayes factors are the ratios of the likelihood of a specified hypothesis (e.g. an intervention effect within a given range) to another hypothesis (e.g. no effect). They are particularly important for differentiating lack of strong evidence for an effect and evidence for lack of an effect. This paper reviewed randomized trials reported in Addiction between January and June 2013 to assess how far Bayes factors might improve the interpretation of the data.MethodsSeventy‐five effect sizes and their standard errors were extracted from 12 trials. Seventy‐three per cent (n = 55) of these were non‐significant (i.e. P > 0.05). For each non‐significant finding a Bayes factor was calculated using a population effect derived from previous research. In sensitivity analyses, a further two Bayes factors were calculated assuming clinically meaningful and plausible ranges around this population effect.ResultsTwenty per cent (n = 11) of the non‐significant Bayes factors were < ⅓ and 3.6% (n = 2) were > 3. The other 76.4% (n = 42) of Bayes factors were between ⅓ and 3. Of these, 26 were in the direction of there being an effect (Bayes factor > 1 and < 3); 12 tended to favour the hypothesis of no effect (Bayes factor < 1 and > ⅓); and for four there was no evidence either way (Bayes factor = 1). In sensitivity analyses, 13.3% of Bayes Factors were < ⅓ (n = 20), 62.7% (n = 94) were between ⅓ and 3 and 24.0% (n = 36) were > 3, showing good concordance with the main results.ConclusionsUse of Bayes factors when analysing data from randomized trials of interventions in addiction research can provide important information that would lead to more precise conclusions than are obtained typically using currently prevailing methods.

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Section: Methodsmentioning

confidence: 99%

Using Bayes factors for testing hypotheses about intervention effectiveness in addictions research

et al. 2016

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“…This threat to intervention efficacy has been noted previously. Alterman et al (1999) found that only 55% of general smoking treatment participants used the patch as prescribed, and that at the group level, patch use was related to outcomes. Similarly, Cooper et al (2004) found that patch use was associated with better treatment participation and cessation outcomes, and that perfect adherence occurred in only one-third of participants.…”

Section: Discussionmentioning

confidence: 99%

A Test of Motivational Plus Nicotine Replacement Interventions for HIV Positive Smokers

2007

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The purpose of this study was to test two combination motivational plus pharmacological interventions for smoking cessation among HIV positive smokers. Participants were 40 adults receiving HIV care who smoked daily reporting interest in smoking reduction. Measures were administered at baseline, 1-month, and 3-month follow-ups. Participants were randomly assigned to self-guided reading plus nicotine patch (n = 18) or motivational interviewing plus nicotine patch (n = 22). Groups did not differ at 3 months on biochemically-verified abstinence. The sample reduced cigarettes per day by half a pack and the percent of smoking days by 41%, and 22% were abstinent at 3-month follow-up. Compliance with the nicotine patch was poor and declined over time, but patch use was unrelated to carbon monoxide level at 3-month follow-up. Smoking cessation interventions for people with HIV can be helpful and should include components that encourage some smoke-free days, increase self-efficacy, and attend to adherence to nicotine replacement treatment.

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“…For subjects who dropped out of treatment in the first week of the study and never returned any patches, this variable was coded as 0% adherence. This method of data collection for the measurement of nicotine patch adherence is somewhat similar to methods used in other reports (Alterman et al, 1999); however, we did not have an item or items assessing the total number of patches consumed (e.g., "Of the 42 patches you received, how many did you use? "; Jolicoeur et al, 2000, p. 506).…”

Section: Methodsmentioning

confidence: 99%

“…Studies assessing adherence rates with transdermal nicotine patch use have generally reported relatively low rates (Alterman, Gariti, Cook, & Cnaan, 1999;Orleans et al, 1994;Stapleton et al, 1995). Additionally, many investigations have shown a relationship between nicotine patch adherence and smoking cessation treatment outcome (Alterman et al, 1999;Cooper et al, 2004;Jolicoeur et al, 2000), and one study showed that advice from health care providers was related to adherence to the nicotine patch (Orleans et al, 1994).…”

Section: Adherence To Nicotine Patch Treatment For Smoking Cessationmentioning

confidence: 99%

“…Additionally, many investigations have shown a relationship between nicotine patch adherence and smoking cessation treatment outcome (Alterman et al, 1999;Cooper et al, 2004;Jolicoeur et al, 2000), and one study showed that advice from health care providers was related to adherence to the nicotine patch (Orleans et al, 1994). Although adherence has been examined in nicotine patch treatment, no studies to date have explored assessment tools to evaluate this important construct.…”

Section: Adherence To Nicotine Patch Treatment For Smoking Cessationmentioning

confidence: 99%

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Factor structure and validity of the Medication Adherence Questionnaire (MAQ) with cigarette smokers trying to quit

Toll

McKee

Martin

et al. 2007

Nicotine & Tobacco Res.

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The Medication Adherence Questionnaire (MAQ) is a scale used to evaluate adherence to medications. The present study assessed the factor structure and validity of the MAQ with cigarette smokers. A principal components analysis was conducted on MAQ scores from a sample of smokers presenting for treatment in a clinical trial of naltrexone and nicotine patch for smoking cessation (N=385). Indices of convergent and predictive validity were tested using electronic medication caps for naltrexone, nicotine patch counts, plasma drug levels of naltrexone, and treatment outcomes. The principal components analysis revealed two factors. Factor 1, labeled "unintentional nonadherence," measured the extent to which individuals were nonadherent because they were careless or forgot to take their medications. Factor 2, labeled "purposeful nonadherence," assessed nonadherence related to purposefully stopping medication use after feeling better or worse. Only the second factor was shown to have good convergent and predictive validity. Specifically, this factor was related to pilltaking behavior measured with electronic medication caps and drug plasma levels and nicotine patch use based on nicotine patch count data, and it was associated with smoking cessation outcome. Thus the purposeful nonadherence factor of the MAQ may be used as a brief screening tool for medication adherence with cigarette smokers seeking treatment. Information obtained with this questionnaire could be used to counsel patients regarding the importance of medication adherence.

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Nicodermal patch adherence and its correlates

Cited by 76 publications

References 13 publications

Using Bayes factors for testing hypotheses about intervention effectiveness in addictions research

Using Bayes factors for testing hypotheses about intervention effectiveness in addictions research

A Test of Motivational Plus Nicotine Replacement Interventions for HIV Positive Smokers

Factor structure and validity of the Medication Adherence Questionnaire (MAQ) with cigarette smokers trying to quit

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