Massage with aromatherapy: effectiveness on anxiety of users with personality disorders in psychiatric hospitalization

OBJECTIVE To investigate the effectiveness of aromatherapy massage using the essential oils (0.5%) of Lavandula angustifolia and Pelargonium graveolens for anxiety reduction in patients with personality disorders during psychiatric hospitalization. METHOD Uncontrolled clinical trial with 50 subjects submitted to six massages with aromatherapy, performed on alternate days, on the cervical and the posterior thoracic regions. Vital data (heart and respiratory rate) were collected before and after each session and an anxiety scale (Trait Anxiety Inventory-State) was applied at the beginning and end of the intervention. The results were statistically analyzed with the chi square test and paired t test. RESULTS There was a statistically significant decrease (p < 0.001) of the heart and respiratory mean rates after each intervention session, as well as in the inventory score. CONCLUSION Aromatherapy has demonstrated effectiveness in anxiety relief, considering the decrease of heart and respiratory rates in patients diagnosed with personality disorders during psychiatric hospitalization.

Job satisfaction and life satisfaction: Analysis of a reciprocal model with social demographic moderators

The general objective of the study was to empirically test a reciprocal model of job satisfaction and life satisfaction while controlling for some social demographic variables. 827 employees working in 34 car dealerships in Northern Quebec (56% responses rate) were surveyed. The multiple item questionnaires were analysed using correlation analysis, chi square and ANOVAs. Results show interesting patterns emerging for the relationships between job and life satisfaction of which 49.2% of all individuals have spillover, 43.5% compensation, and 7.3% segmentation type of relationships. Results, nonetheless, are far richer and the model becomes much more refined when social demographic indicators are taken into account. Globally, social demographic variables demonstrate some effects on each satisfaction individually but also on the interrelation (nature of the relations) between life and work satisfaction.

Comparison of neoadjuvant cisplatin-based chemotherapy versus radiochemotherapy followed by resection for stage III (N2) NSCLC.

OBJECTIVE: Comparison of prospectively treated patients with neoadjuvant cisplatin-based chemotherapy vs radiochemotherapy followed by resection for mediastinoscopically proven stage III N2 non-small cell lung cancer with respect to postoperative morbidity, pathological nodal downstaging, overall and disease-free survival, and site of recurrence. METHODS: Eighty-two patients were enrolled between January 1994 to June 2003, 36 had cisplatin and doxetacel-based chemotherapy (group I) and 46 cisplatin-based radiochemotherapy up to 44 Gy (group II), either as sequential (25 patients) or concomitant (21 patients) treatment. All patients had evaluation of absence of distant metastases by bone scintigraphy, thoracoabdominal CT scan or PET scan, and brain MRI, and all underwent pre-induction mediastinoscopy, resection and mediastinal lymph node dissection by the same surgeon. RESULTS: Group I and II comprised T1/2 tumors in 47 and 28%, T3 tumors in 45 and 41%, and T4 tumors in 8 and 31% of the patients, respectively (P=0.03). There was a similar distribution of the extent of resection (lobectomy, sleeve lobectomy, left and right pneumonectomy) in both groups (P=0.9). Group I and II revealed a postoperative 90-d mortality of 3 and 4% (P=0.6), a R0-resection rate of 92 and 94% (P=0.9), and a pathological mediastinal downstaging in 61 and 78% of the patients (P<0.01), respectively. 5y-overall survival and disease-free survival of all patients were 40 and 36%, respectively, without significant difference between T1-3 and T4 tumors. There was no significant difference in overall survival rate in either induction regimens, however, radiochemotherapy was associated with a longer disease-free survival than chemotherapy (P=0.04). There was no significant difference between concurrent vs sequential radiochemotherapy with respect to postoperative morbidity, resectability, pathological nodal downstaging, survival and disease-free survival. CONCLUSIONS: Neoadjuvant cisplatin-based radiochemotherapy was associated with a similar postoperative mortality, an increased pathological nodal downstaging and a better disease-free survival as compared to cisplatin doxetacel-based chemotherapy in patients with stage III (N2) NSCLC although a higher number of T4 tumors were admitted to radiochemotherapy.

Ratio maps and correspondence analysis

We compare two methods for visualising contingency tables and developa method called the ratio map which combines the good properties of both.The first is a biplot based on the logratio approach to compositional dataanalysis. This approach is founded on the principle of subcompositionalcoherence, which assures that results are invariant to considering subsetsof the composition. The second approach, correspondence analysis, isbased on the chi-square approach to contingency table analysis. Acornerstone of correspondence analysis is the principle of distributionalequivalence, which assures invariance in the results when rows or columnswith identical conditional proportions are merged. Both methods may bedescribed as singular value decompositions of appropriately transformedmatrices. Correspondence analysis includes a weighting of the rows andcolumns proportional to the margins of the table. If this idea of row andcolumn weights is introduced into the logratio biplot, we obtain a methodwhich obeys both principles of subcompositional coherence and distributionalequivalence.

The contributions of rare objects in correspondence analysis

Correspondence analysis, when used to visualize relationships in a table of counts(for example, abundance data in ecology), has been frequently criticized as being too sensitiveto objects (for example, species) that occur with very low frequency or in very few samples. Inthis statistical report we show that this criticism is generally unfounded. We demonstrate this inseveral data sets by calculating the actual contributions of rare objects to the results ofcorrespondence analysis and canonical correspondence analysis, both to the determination ofthe principal axes and to the chi-square distance. It is a fact that rare objects are oftenpositioned as outliers in correspondence analysis maps, which gives the impression that theyare highly influential, but their low weight offsets their distant positions and reduces their effecton the results. An alternative scaling of the correspondence analysis solution, the contributionbiplot, is proposed as a way of mapping the results in order to avoid the problem of outlying andlow contributing rare objects.

Asymptotic robustness in multi-sample analysis of multivariate linear relations

Standard methods for the analysis of linear latent variable models oftenrely on the assumption that the vector of observed variables is normallydistributed. This normality assumption (NA) plays a crucial role inassessingoptimality of estimates, in computing standard errors, and in designinganasymptotic chi-square goodness-of-fit test. The asymptotic validity of NAinferences when the data deviates from normality has been calledasymptoticrobustness. In the present paper we extend previous work on asymptoticrobustnessto a general context of multi-sample analysis of linear latent variablemodels,with a latent component of the model allowed to be fixed across(hypothetical)sample replications, and with the asymptotic covariance matrix of thesamplemoments not necessarily finite. We will show that, under certainconditions,the matrix $\Gamma$ of asymptotic variances of the analyzed samplemomentscan be substituted by a matrix $\Omega$ that is a function only of thecross-product moments of the observed variables. The main advantage of thisis thatinferences based on $\Omega$ are readily available in standard softwareforcovariance structure analysis, and do not require to compute samplefourth-order moments. An illustration with simulated data in the context ofregressionwith errors in variables will be presented.

Asymptotic robust inferences in the analysis of mean and covariance structures

Structural equation models are widely used in economic, socialand behavioral studies to analyze linear interrelationships amongvariables, some of which may be unobservable or subject to measurementerror. Alternative estimation methods that exploit different distributionalassumptions are now available. The present paper deals with issues ofasymptotic statistical inferences, such as the evaluation of standarderrors of estimates and chi--square goodness--of--fit statistics,in the general context of mean and covariance structures. The emphasisis on drawing correct statistical inferences regardless of thedistribution of the data and the method of estimation employed. A(distribution--free) consistent estimate of $\Gamma$, the matrix ofasymptotic variances of the vector of sample second--order moments,will be used to compute robust standard errors and a robust chi--squaregoodness--of--fit squares. Simple modifications of the usual estimateof $\Gamma$ will also permit correct inferences in the case of multi--stage complex samples. We will also discuss the conditions under which,regardless of the distribution of the data, one can rely on the usual(non--robust) inferential statistics. Finally, a multivariate regressionmodel with errors--in--variables will be used to illustrate, by meansof simulated data, various theoretical aspects of the paper.

Longitudinal and cross-sectional changes in active commuting to school among Brazilian schoolchildren.

OBJECTIVE: The objective of the study is to evaluate cross-sectional and longitudinal changes in children's commuting to school in a representative sample of a Brazilian city. METHODS: Two school-based studies were carried out in 2002 (n=2936; 7-10years old) and 2007 (n=1232; 7-15years old) in Florianopolis, Brazil. Cross-sectional data were collected from children aged 7 to 10years in 2002 and 2007. Longitudinal analyses were performed with data from 733 children participating in both surveys. Children self-reported their mode of transportation to school using a validated illustrated questionnaire. Changes were tested with chi square statistics and McNemar's test. RESULTS: Cross-sectional data showed a 17% decline in active commuting; a decrease from 49% in 2002 to 41% in 2007. On the other hand, active commuting among the 733 children increased as they entered adolescence 5years later, rising from 40% to 49%. CONCLUSION: Active commuting to school decreased in Brazilian children aged 7-10years over a five year period; whereas, it increased among children entering adolescence. Policies should focus on safety and environmental determinants to increase active commuting.

Scaled and adjusted restricted tests in multi-sample analysis of moment structures

We extend to score, Wald and difference test statistics the scaled and adjusted corrections to goodness-of-fit test statistics developed in Satorra and Bentler (1988a,b). The theory is framed in the general context of multisample analysis of moment structures, under general conditions on the distribution of observable variables. Computational issues, as well as the relation of the scaled and corrected statistics to the asymptotic robust ones, is discussed. A Monte Carlo study illustrates thecomparative performance in finite samples of corrected score test statistics.

Power transformations in correspondence analysis

Power transformations of positive data tables, prior to applying the correspondence analysis algorithm, are shown to open up a family of methods with direct connections to the analysis of log-ratios. Two variations of this idea are illustrated. The first approach is simply to power the original data and perform a correspondence analysis this method is shown to converge to unweighted log-ratio analysis as the power parameter tends to zero. The second approach is to apply the power transformation to thecontingency ratios, that is the values in the table relative to expected values based on the marginals this method converges to weighted log-ratio analysis, or the spectral map. Two applications are described: first, a matrix of population genetic data which is inherently two-dimensional, and second, a larger cross-tabulation with higher dimensionality, from a linguistic analysis of several books.

Weighted metric multidimensional scaling

This paper establishes a general framework for metric scaling of any distance measure between individuals based on a rectangular individuals-by-variables data matrix. The method allows visualization of both individuals and variables as well as preserving all the good properties of principal axis methods such as principal components and correspondence analysis, based on the singular-value decomposition, including the decomposition of variance into components along principal axes which provide the numerical diagnostics known as contributions. The idea is inspired from the chi-square distance in correspondence analysis which weights each coordinate by an amount calculated from the margins of the data table. In weighted metric multidimensional scaling (WMDS) we allow these weights to be unknown parameters which are estimated from the data to maximize the fit to the original distances. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing a matrix and displaying its rows and columns in biplots.

Measuring subcompositional incoherence

Subcompositional coherence is a fundamental property of Aitchison s approach to compositional data analysis, and is the principal justification for using ratios of components. We maintain, however, that lack of subcompositional coherence, that is incoherence, can be measured in an attempt to evaluate whether any given technique is close enough, for all practical purposes, to being subcompositionally coherent. This opens up the field to alternative methods, which might be better suited to cope with problems such as data zeros and outliers, while being only slightly incoherent. The measure that we propose is based on the distance measure between components. We show that the two-part subcompositions, which appear to be the most sensitive to subcompositional incoherence, can be used to establish a distance matrix which can be directly compared with the pairwise distances in the full composition. The closeness of these two matrices can be quantified using a stress measure that is common in multidimensional scaling, providing a measure of subcompositional incoherence. The approach is illustrated using power-transformed correspondence analysis, which has already been shown to converge to log-ratio analysis as the power transform tends to zero.

Tying up the loose ends in simple correspondence analysis

Although correspondence analysis is now widely available in statistical software packages and applied in a variety of contexts, notably the social and environmental sciences, there are still some misconceptions about this method as well as unresolved issues which remain controversial to this day. In this paper we hope to settle these matters, namely (i) the way CA measures variance in a two-way table and how to compare variances between tables of different sizes, (ii) the influence, or rather lack of influence, of outliers in the usual CA maps, (iii) the scaling issue and the biplot interpretation of maps,(iv) whether or not to rotate a solution, and (v) statistical significance of results.

Subset correspondence analysis: Visualizing relationships among a selected set of response categories from a questionnaire survey

It is shown how correspondence analysis may be applied to a subset of response categories from a questionnaire survey, for example the subset of undecided responses or the subset of responses for a particular category. The idea is to maintain the original relative frequencies of the categories and not re-express them relative to totals within the subset, as would normally be done in a regular correspondence analysis of the subset. Furthermore, the masses and chi-square metric assigned to the data subset are the same as those in the correspondence analysis of the whole data set. This variant of the method, called Subset Correspondence Analysis, is illustrated on data from the ISSP survey on Family and Changing Gender Roles.

The Effect of Amifostine on Acute and Late Radiation Side Effects in Head and Neck Cancer Patients

Objective: We aimed to investigate the effect of amifostine on acute and late side effects, and its tolerability in head and neck cancer patients treated with radiotherapy (RT). Material and Methods: The study included 87 patients with primary head and neck cancers and cervical lymph node metastases from unknown primary cancers treated with RT alone or combined with chemotherapy (CT). Forty-one patients (47%) received amifostine combined with RT (ART group) and 46 patients (52%) received RT without amifostine (RT group). The patients were evaluated every week during the treatment and at month 1 and 2 after the completion of RT for acute side effects and month 3, 6, 9, 12, and 24 after the treatment for late side effects according to SOMA/LENT scale. Amifostine was administered prior to RT, along with anti-emetic prophylaxis. The two groups were compared with the Student's t and Mann-Whitney U and Chi-square tests. Results: The ART group had significantly less toxicity (grade! 1 mucositis, grade 2 fibrosis) than patients in the RT group (p=0.001, p=0.03, respectively). At week 3 of RT grade 2 mucositis developed in two patients (5%) in the ART group and 10 patients (22%) in the RT group (p=0.02). The protective effect of amifostine on skin reactions developed at week 4 of RT (p=0.05). Grade 3 xerostomia at 9, 12, and 15 months of follow-up (p=0.02, p=0.02, and p=0.02, respectively), grade 2 xerostomia at 18 and 24 months (p=0.02 and p=0.01, respectively) and fibrosis at 15, 18 and 24 months (p=0.05, p=0.02 and p=0.02, respectively) decreased markedly in the ART group compared with the RT group. Emesis was the most common adverse effect of amifostine. Conclusion: Daily administration of amifostine during RT was effective in avoiding late grade 2-3 xerostomia, as well as grade 2 fibrosis.