Dana Quade

Self-Help Quit Smoking Interventions: Effects of Self-Help Materials, Social Support Instructions, and Telephone Counseling.

Smokers requesting self-help materials for smoking cessation (N = 2,021) were randomized to receive (a) an experimental self-quitting guide emphasizing nicotine fading and other nonaversive behavioral strategies, (b) the same self-quitting guide with a support guide for the quitters family and friends, (c) self-quitting and support guides along with four brief counselor calls, or (d) a control guide providing motivational and quit tips and referral to locally available guides and programs. Subjects were predominantly moderate to heavy smokers with a history of multiple previous quit attempts and treatments. Control subjects achieved quit rates similar to those of smokers using the experimental quitting guide, with fewer behavioral prequitting strategies and more outside treatments. Social support guides had no effect on perceived support for quitting or on 8- and 16-month quit rates. Telephone counseling increased adherence to the quitting protocol and quit rates.

Using Weighted Rankings in the Analysis of Complete Blocks with Additive Block Effects

Abstract The standard nonparametric procedures for testing the hypothesis of no treatment effects in a complete blocks experiment depend entirely on the within-block rankings. If block effects are assumed additive, however, then between-block information may be recovered by weighting these rankings according to their credibility with respect to treatment ordering. (For the special case of only two treatments, the sign test exemplifies use of unweighted rankings and the signed-rank test weighted.) A general family of weighted-rankings test statistics for comparing two or more treatments is presented. They are simple to compute, are strictly distribution free, and have asymptotic chi-squared distributions.

Measuring the use of mammography: two methods compared.

Population studies often estimate mammography use using womens self-reports. In one North Carolina county, we compared self-report surveys with a second method--counting mammograms per population--for 1987 and 1989. Estimates from self-reports (35% in 1987, 55% in 1989) were considerably higher than those from mammogram counts (20% in 1987, 36% in 1989). We then confirmed 66% of self-reports in the past year. Self-reported use is more accurate regarding whether a woman has had a mammogram than when she had it, but self-reports accurately measure change over time.

Treatment of depression in cancer patients is associated with better life adaptation: a pilot study.

&NA; Major depression occurs in a significant number of cancer patients, and there is evidence that cancer patients with depression do not receive adequate antidepressant treatment. In an uncontrolled pilot study, the authors assess the degree of depression and the quality of life after the initiation of antidepressant medication treatment in 12 depressed cancer patients who received adequate antidepressant drugs and in 10 depressed cancer patients who received inadequate antidepressant treatment. These preliminary findings suggest that cancer patients with major depression benefit from antidepressant medication treatment and may experience an improved psychosocial adjustment to cancer. Controlled clinical trials will be necessary to verify these preliminary findings.

A hospital quit-smoking consult service: clinical report and intervention guidelines.

A minimal-contact quit-smoking consult service was established to treat hospital inpatients and outpatients referred for behavioral smoking cessation treatment. Sixty-two consecutively referred patients were evaluated and triaged to one of three standardized quitting protocols: motivational counseling; standard behavioral abstinence counseling; or abstinence counseling plus nicotine fading. Consultations included personalized self-quit materials and planned telephone follow-up to enhance compliance. Triage differentiated patients with different levels of quitting readiness and nicotine dependence. Six months after treatment, 27% of patients had quit smoking (informant-verified). Predictors of quit attempts were shorter smoking history and lower nicotine dependence. Variables predicting cessation or substantial reductions in estimated daily nicotine intake included higher educational level, stronger beliefs in smoking health harms, higher trait anxiety, a greater desire to quit and quitting self-efficacy, and the recall of direct quitting advice from the referring physician. Results compare favorably with those of more intensive treatments with similar patient groups. Recommendations are presented for controlled follow-up research to explore promising findings in this clinical report.

The detection of depression by patient self-report in women with gynecologic cancer

We examined the utility of patient self-report forms in identifying those gynecologic oncology patients who would be diagnosed by an experienced consultation-liaison psychiatrist as suffering from major depression. Sixty-five women with gynecologic tumors were evaluated by a consultation-liaison psychiatrist, using standardized (DSM-III) criteria. Each patient also completed a Carroll Rating Scale for Depression (CRS). The CRS demonstrated sensitivity and specificity of 87 percent and 58 percent, respectively. Used as a screening instrument to rule out depression, the CRS yielded a negative predictive value of 94 percent. We identified a priori forty items from the CRS which should not be influenced by the non-psychiatric biologic effects of gynecologic tumors, and compared the performance of this non-cancer related symptoms subscale (NCSG) to that of the CRS. The NCSG did not significantly outperform the CRS; its sensitivity and specificity were 87 percent and 62 percent, respectively. Because our study population was relatively homogeneous (i.e., non-ovarian gynecologic oncology patients without severe debilitation who were not receiving chemotherapy, radiation therapy, or other invasive procedures), the findings should not be generalized to other oncologic populations at this time. Our results suggest that patient self-report forms can be effective screening devices for identifying those non-ovarian, gynecologic oncology patients who should then be carefully evaluated for coexisting clinical depression.

U-statistics for skewness or symmetry

We propose certain U-statistics as intuitively reasonable measures of skewness and as criteria for asymptotically distribution-free tests of symmetry. Some comparisons are made with the moment-skewness b1 in terms of small-sample power and asymptotic relative efficiency.

A nonparametric comparison of two multiple regressions by means of a weighted measure of correlation

Let (R1j,....,Rmj) j=1,2, be two rankings of m items; let Tk , k=l,...,m. be the number of items with rank ≤ k in both rankings; and let T = ∑Tk/k. Then T is a measure of rank correlation which gives greater weight to items of low rank than high. Such a measure is particularly useful in comparing the ordering of the regressors in two multiple regressions. We discuss the distribution of T, presenting both exact tables and practical approximations, and extend the concept to other situations

Panic, suicide, and agitation: Independent correlates of the TSH response to TRH in depression

We investigated the relationship between suicidality, agitation, panic attacks, and the thyrotropin-stimulating hormone (TSH) response to thyrotropin-releasing hormone (TRH), and tested the hypothesis that panic would account for the association between a reduced TSH response and the other conditions. Twenty-seven euthyroid primary unipolar depressed inpatient women received a TRH test and systematic psychiatric assessment. Panic attacks were insufficient to explain the link between the TSH response and suicidal intent, lethality, and agitation; each condition was independently associated with a lower TSH response. In an additive fashion, copresence of conditions further reduced TSH response. The symptom constellation of panic, agitation, and suicidality in depression may correlate with the greatest reduction in TSH response.

The Minimally Important Difference Significant Criterion for Sample Size

For a wide range of tests of single-df hypotheses, the sample size needed to achieve 50% power is readily approximated by setting N such that a significance test conducted on data that fit one’s assumptions perfectly just barely achieves statistical significance at one’s chosen alpha level. If the effect size assumed in establishing one’s N is the minimally important effect size (i.e., that effect size such that population differences or correlations smaller than that are not of any practical or theoretical significance, whether statistically significant or not), then 50% power is optimal, because the probability of rejecting the null hypothesis should be greater than .5 when the population difference is of practical or theoretical significance but lower than .5 when it is not. Moreover, the actual power of the test in this case will be considerably higher than .5, exceeding .95 for a population difference two or more times as large as the minimally important difference (MID). This minimally important difference significant (MIDS) criterion extends naturally to specific comparisons following (or substituting for) overall tests such as the ANOVA F and chi-square for contingency tables, although the power of the overall test (i.e., the probability of finding some statistically significant specific comparison) is considerably greater than .5 when the MIDS criterion is applied to the overall test. However, the proper focus for power computations is one or more specific comparisons (rather than the omnibus test), and the MIDS criterion is well suited to setting sample size on this basis. Whereas Nmids(the sample size specified by the MIDS criterion) is much too small for the case in which we wish to prove the modified H0 that there is no important population effect, it nonetheless provides a useful metric for specifying the necessary sample size. In particular, the sample size needed to have a 1 – α probability that the (1 − α)-level confidence interval around one’s population parameter includes no important departure from H0 is four times Nmids when H0 is true and approximately [4/(1 – b)2].NMIDS when b (the ratio between the actual population difference and the minimally important difference) is between zero and unity. The MIDS criterion for sample size provides a useful alternative to the methods currently most commonly employed and taught.