Measuring professional satisfaction and nursing workload among nursing staff at a Greek Coronary Care Unit

ABSTRACT Objective To explore potential associations between nursing workload and professional satisfaction among nursing personnel (NP) in Greek Coronary Care Units (CCUs). Method A cross-sectional study was performed involving 66 members of the NP employed in 6 randomly selected Greek CCUs. Job satisfaction was assessed by the IWS and nursing workload by NAS, CNIS and TISS-28. Results The response rate was 77.6%. The reliability of the IWS was α=0.78 and the mean score 10.7 (±2.1, scale range: 0.5-39.7). The most highly valued component of satisfaction was “Pay”, followed by “Task requirements”, “Interaction”, “Professional status”, “Organizational policies” and “Autonomy”. NAS, CNIS and TISS-28 were negatively correlated (p≤0.04) with the following work components: “Autonomy”, “Professional status”, “Interaction” and “Task requirements”. Night shift work independently predicted the score of IWS. Conclusion The findings show low levels of job satisfaction, which are related with nursing workload and influenced by rotating shifts.

Manipulating Greek musical modes and tempo affects perceived musical emotion in musicians and nonmusicians

The combined influence of tempo and mode on emotional responses to music was studied by crossing 7 changes in mode with 3 changes in tempo. Twenty-four musicians aged 19 to 25 years (12 males and 12 females) and 24 nonmusicians aged 17 to 25 years (12 males and 12 females) were required to perform two tasks: 1) listening to different musical excerpts, and 2) associating an emotion to them such as happiness, serenity, fear, anger, or sadness. ANOVA showed that increasing the tempo strongly affected the arousal (F(2,116) = 268.62, mean square error (MSE) = 0.6676, P < 0.001) and, to a lesser extent, the valence of emotional responses (F(6,348) = 8.71, MSE = 0.6196, P < 0.001). Changes in modes modulated the affective valence of the perceived emotions (F(6,348) = 4.24, MSE = 0.6764, P < 0.001). Some interactive effects were found between tempo and mode (F (1,58) = 115.6, MSE = 0.6428, P < 0.001), but, in most cases, the two parameters had additive effects. This finding demonstrates that small changes in the pitch structures of modes modulate the emotions associated with the pieces, confirming the cognitive foundation of emotional responses to music.

Some notes on a historical perspective of panic disorder

This article aims to describe important points in the history of panic disorder concept, as well as to highlight the importance of its diagnosis for clinical and research developments. Panic disorder has been described in several literary reports and folklore. One of the oldest examples lies in Greek mythology - the god Pan, responsible for the term panic. The first half of the 19th century witnessed the culmination of medical approach. During the second half of the 19th century came the psychological approach of anxiety. The 20th century associated panic disorder to hereditary, organic and psychological factors, dividing anxiety into simple and phobic anxious states. Therapeutic development was also observed in psychopharmacological and psychotherapeutic fields. Official classifications began to include panic disorder as a category since the third edition of the American Classification Manual (1980). Some biological theories dealing with etiology were widely discussed during the last decades of the 20th century. They were based on laboratory studies of physiological, cognitive and biochemical tests, as the false suffocation alarm theory and the fear network. Such theories were important in creating new diagnostic paradigms to modern psychiatry. That suggests the need to consider a wide range of historical variables to understand how particular features for panic disorder diagnosis have been developed and how treatment has emerged.

Development of Anatomophysiologic Knowledge Regarding the Cardiovascular System: From Egyptians to Harvey

Our knowledge regarding the anatomophysiology of the cardiovascular system (CVS) has progressed since the fourth millennium BC. In Egypt (3500 BC), it was believed that a set of channels are interconnected to the heart, transporting air, urine, air, blood, and the soul. One thousand years later, the heart was established as the center of the CVS by the Hippocratic Corpus in the medical school of Kos, and some of the CVS anatomical characteristics were defined. The CVS was known to transport blood via the right ventricle through veins and the pneuma via the left ventricle through arteries. Two hundred years later, in Alexandria, following the development of human anatomical dissection, Herophilus discovered that arteries were 6 times thicker than veins, and Erasistratus described the semilunar valves, emphasizing that arteries were filled with blood when ventricles were empty. Further, 200 years later, Galen demonstrated that arteries contained blood and not air. With the decline of the Roman Empire, Greco-Roman medical knowledge about the CVS was preserved in Persia, and later in Islam where, Ibn Nafis inaccurately described pulmonary circulation. The resurgence of dissection of the human body in Europe in the 14th century was associated with the revival of the knowledge pertaining to the CVS. The main findings were the description of pulmonary circulation by Servetus, the anatomical discoveries of Vesalius, the demonstration of pulmonary circulation by Colombo, and the discovery of valves in veins by Fabricius. Following these developments, Harvey described blood circulation.

A determinação dos números de indivíduos mínimos necessários na experimentação genética

The main object of the present paper consists in giving formulas and methods which enable us to determine the minimum number of repetitions or of individuals necessary to garantee some extent the success of an experiment. The theoretical basis of all processes consists essentially in the following. Knowing the frequency of the desired p and of the non desired ovents q we may calculate the frequency of all possi- ble combinations, to be expected in n repetitions, by expanding the binomium (p-+q)n. Determining which of these combinations we want to avoid we calculate their total frequency, selecting the value of the exponent n of the binomium in such a way that this total frequency is equal or smaller than the accepted limit of precision n/pª{ 1/n1 (q/p)n + 1/(n-1)| (q/p)n-1 + 1/ 2!(n-2)| (q/p)n-2 + 1/3(n-3) (q/p)n-3... < Plim - -(1b) There does not exist an absolute limit of precision since its value depends not only upon psychological factors in our judgement, but is at the same sime a function of the number of repetitions For this reasen y have proposed (1,56) two relative values, one equal to 1-5n as the lowest value of probability and the other equal to 1-10n as the highest value of improbability, leaving between them what may be called the "region of doubt However these formulas cannot be applied in our case since this number n is just the unknown quantity. Thus we have to use, instead of the more exact values of these two formulas, the conventional limits of P.lim equal to 0,05 (Precision 5%), equal to 0,01 (Precision 1%, and to 0,001 (Precision P, 1%). The binominal formula as explained above (cf. formula 1, pg. 85), however is of rather limited applicability owing to the excessive calculus necessary, and we have thus to procure approximations as substitutes. We may use, without loss of precision, the following approximations: a) The normal or Gaussean distribution when the expected frequency p has any value between 0,1 and 0,9, and when n is at least superior to ten. b) The Poisson distribution when the expected frequecy p is smaller than 0,1. Tables V to VII show for some special cases that these approximations are very satisfactory. The praticai solution of the following problems, stated in the introduction can now be given: A) What is the minimum number of repititions necessary in order to avoid that any one of a treatments, varieties etc. may be accidentally always the best, on the best and second best, or the first, second, and third best or finally one of the n beat treatments, varieties etc. Using the first term of the binomium, we have the following equation for n: n = log Riim / log (m:) = log Riim / log.m - log a --------------(5) B) What is the minimun number of individuals necessary in 01der that a ceratin type, expected with the frequency p, may appaer at least in one, two, three or a=m+1 individuals. 1) For p between 0,1 and 0,9 and using the Gaussean approximation we have: on - ó. p (1-p) n - a -1.m b= δ. 1-p /p e c = m/p } -------------------(7) n = b + b² + 4 c/ 2 n´ = 1/p n cor = n + n' ---------- (8) We have to use the correction n' when p has a value between 0,25 and 0,75. The greek letters delta represents in the present esse the unilateral limits of the Gaussean distribution for the three conventional limits of precision : 1,64; 2,33; and 3,09 respectively. h we are only interested in having at least one individual, and m becomes equal to zero, the formula reduces to : c= m/p o para a = 1 a = { b + b²}² = b² = δ2 1- p /p }-----------------(9) n = 1/p n (cor) = n + n´ 2) If p is smaller than 0,1 we may use table 1 in order to find the mean m of a Poisson distribution and determine. n = m: p C) Which is the minimun number of individuals necessary for distinguishing two frequencies p1 and p2? 1) When pl and p2 are values between 0,1 and 0,9 we have: n = { δ p1 ( 1-pi) + p2) / p2 (1 - p2) n= 1/p1-p2 }------------ (13) n (cor) We have again to use the unilateral limits of the Gaussean distribution. The correction n' should be used if at least one of the valors pl or p2 has a value between 0,25 and 0,75. A more complicated formula may be used in cases where whe want to increase the precision : n (p1 - p2) δ { p1 (1- p2 ) / n= m δ = δ p1 ( 1 - p1) + p2 ( 1 - p2) c= m / p1 - p2 n = { b2 + 4 4 c }2 }--------- (14) n = 1/ p1 - p2 2) When both pl and p2 are smaller than 0,1 we determine the quocient (pl-r-p2) and procure the corresponding number m2 of a Poisson distribution in table 2. The value n is found by the equation : n = mg /p2 ------------- (15) D) What is the minimun number necessary for distinguishing three or more frequencies, p2 p1 p3. If the frequecies pl p2 p3 are values between 0,1 e 0,9 we have to solve the individual equations and sue the higest value of n thus determined : n 1.2 = {δ p1 (1 - p1) / p1 - p2 }² = Fiim n 1.2 = { δ p1 ( 1 - p1) + p1 ( 1 - p1) }² } -- (16) Delta represents now the bilateral limits of the : Gaussean distrioution : 1,96-2,58-3,29. 2) No table was prepared for the relatively rare cases of a comparison of threes or more frequencies below 0,1 and in such cases extremely high numbers would be required. E) A process is given which serves to solve two problemr of informatory nature : a) if a special type appears in n individuals with a frequency p(obs), what may be the corresponding ideal value of p(esp), or; b) if we study samples of n in diviuals and expect a certain type with a frequency p(esp) what may be the extreme limits of p(obs) in individual farmlies ? I.) If we are dealing with values between 0,1 and 0,9 we may use table 3. To solve the first question we select the respective horizontal line for p(obs) and determine which column corresponds to our value of n and find the respective value of p(esp) by interpolating between columns. In order to solve the second problem we start with the respective column for p(esp) and find the horizontal line for the given value of n either diretly or by approximation and by interpolation. 2) For frequencies smaller than 0,1 we have to use table 4 and transform the fractions p(esp) and p(obs) in numbers of Poisson series by multiplication with n. Tn order to solve the first broblem, we verify in which line the lower Poisson limit is equal to m(obs) and transform the corresponding value of m into frequecy p(esp) by dividing through n. The observed frequency may thus be a chance deviate of any value between 0,0... and the values given by dividing the value of m in the table by n. In the second case we transform first the expectation p(esp) into a value of m and procure in the horizontal line, corresponding to m(esp) the extreme values om m which than must be transformed, by dividing through n into values of p(obs). F) Partial and progressive tests may be recomended in all cases where there is lack of material or where the loss of time is less importent than the cost of large scale experiments since in many cases the minimun number necessary to garantee the results within the limits of precision is rather large. One should not forget that the minimun number really represents at the same time a maximun number, necessary only if one takes into consideration essentially the disfavorable variations, but smaller numbers may frequently already satisfactory results. For instance, by definition, we know that a frequecy of p means that we expect one individual in every total o(f1-p). If there were no chance variations, this number (1- p) will be suficient. and if there were favorable variations a smaller number still may yield one individual of the desired type. r.nus trusting to luck, one may start the experiment with numbers, smaller than the minimun calculated according to the formulas given above, and increase the total untill the desired result is obtained and this may well b ebefore the "minimum number" is reached. Some concrete examples of this partial or progressive procedure are given from our genetical experiments with maize.

Plesiophysa dolichomastix sp. n. (Gastropoda: Planorbidae)

A new species of planorbid mollusc, Plesiophysa dolichomastix (Greek dolichos = long, mastix = flagellum), collected from Lagoa da Pedra, municipality of Santa Rosa, state of Goiás, Brazil (15°01'S, 47°13'W) is described. It is indistinguishable by the shell characters from the five congeneric species described so far: P. striata (Orbigny, 1841), P. granulata ("Shuttleworth" Sowerby, 1873), P. guadeloupensis ("Fischer" Mazé, 1883), P. ornata (Haas, 1938) and P. hubendicki Richards & Ferguson, 1962. It differs from the anatomically studied species in the following characters: about 50 ovotestis diverticula, against 12 in granulata, 100 in ornata, unstated in hubendicki; and length of flagella - about as long as the penial complex -, against about 1/3 to 1/6 in the other three.

Schistosoma mansoni major egg antigen Smp40: molecular modeling and potential immunoreactivity for anti-pathology vaccine development

The pathogenesis of Schistosoma mansoni infection is largely determined by host T-cell mediated immune responses such as the granulomatous response to tissue deposited eggs and subsequent fibrosis. The major egg antigens have a valuable role in desensitizing the CD4+ Th cells that mediate granuloma formation, which may prevent or ameliorate clinical signs of schistosomiasis.S. mansoni major egg antigen Smp40 was expressed and completely purified. It was found that the expressed Smp40 reacts specifically with anti-Smp40 monoclonal antibody in Western blotting. Three-dimensional structure was elucidated based on the similarity of Smp40 with the small heat shock protein coded in the protein database as 1SHS as a template in the molecular modeling. It was figured out that the C-terminal of the Smp40 protein (residues 130 onward) contains two alpha crystallin domains. The fold consists of eight beta strands sandwiched in two sheets forming Greek key. The purified Smp40 was used for in vitro stimulation of peripheral blood mononuclear cells from patients infected with S. mansoni using phytohemagglutinin mitogen as a positive control. The obtained results showed that there is no statistical difference in interferon-g, interleukin (IL)-4 and IL-13 levels obtained with Smp40 stimulation compared with the control group (P > 0.05 for each). On the other hand, there were significant differences after Smp40 stimulation in IL-5 (P = 0.006) and IL-10 levels (P < 0.001) compared with the control group. Gaining the knowledge by reviewing the literature, it was found that the overall pattern of cytokine profile obtained with Smp40 stimulation is reported to be associated with reduced collagen deposition, decreased fibrosis, and granuloma formation inhibition. This may reflect its future prospect as a leading anti-pathology schistosomal vaccine candidate.