Increases in tongue teeth (more than the normal number of teeth) are cancer have also been observed in the United King- common problems buy discount silagra on line erectile dysfunction age young. Tooth agenesis occurs in about dom where oral snuff and chewing tobacco are infre- 20% of the population cheap silagra 50mg impotence zantac, and third molars are by far the quently used (Blot et al buy silagra cheap online erectile dysfunction labs, 1996) buy online silagra impotence doctor. Missing maxillary lat- adults appears to be associated with the traditional eral incisors and mandibular premolars occur at the risk factors of tobacco smoking, drinking alcohol and next highest frequency (Graber, 1978). Most super- low consumption of fruit and vegetables, rather than numerary teeth are present in the anterior maxillary due to any unique or new etiological agent region (Garvey et al, 1999). However, aside from the com- Oral Cancer Etiology mon variation of third molars, the pattern often is transmitted through multiple generations of families, Oral cancer presents a highly complex challenge indicating that the cause is due to a single gene of in terms of understanding its etiology, diagnosis and major effect. A large number of factors influ- recently been identified as the cause of different forms ence risk of developing oral and pharyngeal cancers: of hereditary tooth agenesis (Vastardis, 2000; and Stockton et al, 2000). Persons who con- It is likely that there are disparities in access to sume large quantities of both tobacco and alcohol treatment for malocclusion and tooth agenesis. Just have an estimated 80-fold higher risk of oral over 30% of White teenagers receive orthodontic and pharyngeal cancers than do people that never treatment in the United States, nearly three times as used these substances. Cessation of tobacco and many as in the Hispanic population and four times alcohol use is associated with a significant reduction as many as in the African American population of risk after about 5 to 10 years. For example, a removable appliance-based, computer- x Diets high in fresh fruits and possibly some veg- assisted treatment modality has been introduced for etables have been associated with a 50% reduc- minor tooth movement in adults. The profession tion in risk for oral and pharyngeal cancers, even should continue to evaluate the efficacy of new treat- after adjusting for the effects of tobacco and alco- ment modalities to increase access to ortho-dontic hol (Blot et al, 1996; and La Vecchia et al, 1997). Appropriate peer review of studies and claims is required to assure evidence-based treatment. However, current data suggest that only a rel- died from this disease (Greenlee et al, 2000). This perspective empha- x Inherited susceptibility influences both chances of sizes that even fully successful treatment of the oral becoming addicted to heavy alcohol and tobacco cancer itself by no means restores patients to a nor- use, and activities of carcinogen-metabolizing genes mal level of health (Skarsgard et al, 2000). Although oral cancer does not generally appear to be as heritable as some other forms of Oral examinations by dental professionals and cancer, risk has consistently been shown to be ele- education of the public about oral and pharyngeal vated in close relatives of oral cancer cases cancers are important steps to increasing early diag- (Jefferies and Foulkes, 2001). Early detection and surgical removal of lesions when they are small and localized greatly Concern has been raised about possible increased improve prognosis. Five-year survival rates relative risk associated with use of alcohol-containing to individuals of similar ages who are not affected by mouthwashes, but recent studies indicate risks appear oral cancer are 81% when the tumor is localized, 44% to be relatively small compared to the major risk when restricted to the oral region, but only 21% when attributable to high levels of alcohol drinking (Elmore metastasized to distant locations (Ries et al, 2000). Unfortunately, health professionals perform thorough After adjusting for age, African American males oral examinations far too infrequently, and only 36% have about a 50% higher incidence of oral and pha- of oral and pharyngeal cancers are diagnosed when ryngeal cancers than males of European ancestry (Ries the disease is confined to the local area. Five-year survival (relative to the rest of There is very sound scientific justification to the population of similar age) is 29% for male African encourage examinations for these cancers as stan- Americans and 53% for White males in the United dard practice, especially for individuals at high risk States. The difference in mortality is due primarily to due to advanced age or heavy use of tobacco and the more advanced stage at which oral cancers are alcohol. Furthermore, there may be benefits to the usually detected in African Americans (only 15% at a dental profession in terms of health insurance com- localized stage when treatment is much more effective, pensation, which may be strongly justified for the versus 37% for Whites) (Ries et al, 2000). Unfortunately, in 1992 only 15% of United cases, only about 30% of White and 40% of African States adults reported that they had ever had an oral Americans die from an outcome directly related to cancer examination, and only 7% of respondents their oral cancer within five years. Instead, 30% of over age 40 had received such an examination in the newly diagnosed White oral cancer cases and 40% of previous year (Yellowitz et al, 2000). African American oral cancer cases die due to other Standard treatment for oral and pharyngeal can- causes within five years (Arbes et al, 1999b). This cers depends on the size, location, and histopatho- "other" mortality is much higher than expected for logical state of the lesions and usually includes sur- average individuals in the population of the same gery and radiation. Similar to lichen planus, apht- Mucosal Diseases hous stomatitis appears to be the result of cell-medi- ated immune injury. Yet, the clinical manifestations Oral mucosal diseases represent an array of con- of the two conditions are very different. The ditions, such as stomatotoxic reactions associated immunologic complexity of pemphigoid is only now with drug and radiation therapies for cancer. Identification of autoantigens has The overall frequency of these diseases and con- shown that they differ among anatomic sites affect- ditions is high. The fact that lichen planus affects 1-2% of adults over the age of oral mucous membrane pemphigoid is a disease of 50 years (Scully et al, 1998). About 20% of indi- the elderly may suggest the development of abnor- viduals who receive chemotherapy develop painful mal basement membrane antigens to which destruc- mucositis of such severity as to require significant tive autoantibodies are produced. Pemphigus vul- intervention or alteration in their cancer treatment garis, in contrast, develops at a younger age (fourth plan (Epstein and Schubert, 1999). Among patients or fifth decade) and has an immunogenetic predis- with head and neck cancer who are treated with position. Linkages of the disease to certain genetic radiation, mucositis is virtually a universal event regions among large percentages of patients at risk often resulting in the need for breaks in treatment for the condition support this hypothesis. The explosive onset of erythema multiforme Whereas aphthous stomatitis typically has an age (Laskaris and Satriano, 1993) and its predisposition of onset in the first or second decade, lichen planus, for young males set this condition apart from other pemphigoid and pemphigus vulgaris tend to occur oral blistering diseases. Erythema mul- disease is often sequelae to Herpes Simplex Virus tiforme is most common in the second decade. A major area of controversy surrounds one of the With the exception of mucosal injury induced by most common mucosal diseases, lichen planus, and radiation or drug therapy for cancer, virtually all of focuses on its pre-malignant potential. Strong cases the oral mucosal diseases are thought to be manifes- have been made on both sides of the issue tations of autoimmune processes, although the (Silverman, 2000; and Eisenberg, 2000). Nonethe- nature of their etiology is not fully understood less, despite issues with diagnostic criteria, a review (Popovsky and Camisa, 2000). The complexity of of studies in the area leads to the conclusion that the etiopathogenesis of these conditions is illustrat- patients with some forms of lichen planus are at risk ed by aphthous stomatitis, which is the most com- for developing oral cancer. If the estimated frequency of lichen planus Some of the infections seen in immunocompromised is 1%, then among that age group there are 510,000 patients were, hitherto, very unlikely to be seen by cases of lichen planus. Herpes viruses are char- the issue of lichen planus as a premalignant lesion acterized by their ability to establish latent infec- needs to be better defined and studied. It seems like- tions that can be reactivated, especially in the ly that not all forms of lichen planus are at equiva- immunocompromised patient (Oakley et al, 1997). For many of these condi- ulcers are most frequently found on keratinized tions, current treatment is palliative and/or anti- mucosa (Regezzi and Sciubba, 1989). New immunosuppressed patients can develop lesions at molecular biological techniques, the definition of any intraoral site, with nonkeratinized sites repre- the human genome, and the association between senting half of all sites involved (Woo and Lee, specific genes with effector proteins should lead to a 1997; and Oakley et al, 1997). Oropharyngeal candidiasis is perhaps the most frequently encountered fungal Other Infections infection and constitutes a major cause of morbid- ity and mortality in immunocompromised patients The mouth is home to a great variety of organ- (Lynch, 1994; and Phelan et al, 1997). Fortunately, the majority of these are not of patients the organism isolated is Candida albicans any serious health consequence. Nevertheless, (Odds et al, 1989), but in recent years other knowledge about infectious agents and their natural Candida species such as Candida glabrata are histories is essential for the practicing dentist. Unfortunately, infections and be aware of the role of the "carrier" the widespread long-term use of fluconazole in (an apparently healthy individual who shows no recent years has lead to the development of resist- sign of an infectious disease but is able to transmit ance of oral isolates to azole drugs and, in some the disease to others). Federal and mouth are related to Treponema pallidum, state regulations have been formulated which can Mycobacterium tuberculosis and Neisseria gonor- lead to monetary fines and other sanctions if these rhae. These include tions have a low incidence, but in some regions of the widespread use of agents that suppress the the United States certain fungal infections are epi- immune system, as well as immunosuppressive demic (i. Saliva modulates oral microbial ecosystems, aids More than 300 medications can cause oral dry- in the preparation of the food bolus, lubricates oral ness, and certain classes of medications are more tissues, and supports other critical oral functions. The initial phases of dental caries development are These include sedatives, antipsychotics, antide- reversed in part by saliva, which buffers acids and is pressants, antihistamines and certain anti-hyper- supersaturated with calcium and phosphorus. Medi-cations with anticholinergic salivary mucins are a heterogeneous population of activity can potentially decrease salivation glycoproteins that bathe and protect oral soft tissues (Atkinson and Fox, 1992). Any patient with salivary gland dysfunction The most pronounced salivary dysfunction occurs will benefit from an aggressive oral hygiene pro- in three groups of patients: gram that includes the use of topical fluorides (Ripa, 1989). The use of pilocarpine and the oxygen searchers primarily use one of three sets of crite- radical scavenger amifostine during radiation ria to select patients for studies (Fox, 1997). This treatment may decrease damage to glands (Valdez lack of uniformity in patient selection represents et al, 1993; and Jha et al, 2000). The availability in the last decade of systemic x Patients who have received therapeutic radiation agents that can stimulate salivary output to the head and neck. At doses above 40 Gy, the damage is rapid however, they have significant side effects that and irreversible, and the mechanisms for this unfor- limit their utility and patient acceptance. Eval- out malocclusions, joint anatomy, and skeletal mal- uation should encompass examination of orofacial formations as significant etiological factors. However, the consid- Le Resche, 1992); however, its clinical utility and eration of psychosocial factors has the potential for validity as a research tool have not been established. Surgical approaches may be necessary in a known why some patients progress and others do not. Dental practice must evolve and broad- metal-free restorations is likely to expand with the en to incorporate this knowledge. Furthermore, dif- introduction of improved composite-based materials, ferences in the burden of oral disease, evident through- and new "smart" biomaterials to provide improved out the United States, will challenge the profession to resistance to recurrent caries and wear. Future efforts are needed to treat the infec- categories are hardly inclusive of all dentistry. Addressing this aspect in the environment of Dentistry is the aging of the population. It should be families and extended families is a major public noted that with fewer severe carious lesions and fewer health issue for the future. The association of dental extractions, a continuing decrease in eden- increased caries incidence and impaired cognitive tulism means that older individuals will retain more development needs further study. These individuals will require more pre- Caries Risk Assessment ventive and therapeutic dental care. Conservative management of periodontally involved teeth will be Caries management by risk assessment will be the rule for this segment of the population. General essential in the future of dentistry (Anusavice, 2000; dentists and dental hygienists can be expected to and Featherstone, 2000).

This classification also allows for the fact that there may be some overlap between the clinical defects in the same or different members of a family purchase silagra with a visa erectile dysfunction doctors in fresno ca. Because the mutant gene is on one of the autosomes there is a 50% chance of an affected individual passing this on to each offspring generic silagra 100mg otc erectile dysfunction treatment thailand. The primary and permanent dentitions are generally both involved order cheapest silagra what causes erectile dysfunction in diabetes, although the permanent dentition may be the more severely affected of the two (Fig discount silagra 50 mg otc erectile dysfunction statistics uk. The enamel may be thin and hard with normal translucency but may be difficult to discern on radiographs because of its limited thickness. In some cases the enamel may be both hypoplastic and hypomineralized, in which case the enamel is thin and discoloured with a loss of normal translucency. Some patients may have enamel of normal thickness which is poorly mineralized, and yet others may have enamel of normal thickness which lacks the normal translucency and is therefore regarded as showing features of hypomaturation. Occasionally, subtle enamel defects may only be identified on histopathological examination of extracted teeth. Anterior open bite may occur in autosomal dominant amelogenesis imperfecta as well as in other inheritance patterns. The mechanism producing the sometimes associated anterior open bite has not yet been elucidated. Aetiology The enamelin gene on chromosome 4 has been shown to be mutated in some families with autosomal dominant amelogenesis imperfecta. Other genes involved in normal enamel formation have been implicated in autosomal dominant amelogenesis imperfecta. Autosomal recessive amelogenesis imperfecta Autosomal recessive conditions are typically seen when there is parental consanguinity, so that that the parents may be first cousins (Fig. There may be cultural reasons for this or, alternatively, consanguinity may be seen in isolated communities with little outside contact and where there is consequently a limited gene pool. In other recessive conditions, such as cystic fibrosis, these restrictions do not apply and the relative prevalence of the condition is related to the frequency of gene carriers in the population. Where the parents are close relatives, both carrier adults will be unaffected but there will be a one in four chance of offspring inheriting two copies of the mutant gene. Autosomal recessive mutations causing amelogenesis imperfecta seem to be uncommon apart from Polynesia, where, presumably, the mutation is relatively common. A gene on chromosome 2 has been linked to autosomal recessive amelogenesis imperfecta associated with ocular defects. X-linked amelogenesis imperfecta X-linked amelogenesis imperfecta is characterized by a difference in the appearance of the teeth of affected males and females. The majority of families studied to date have an alteration in the amelogenin gene on the short arm of the X chromosome. Affected males cannot pass on the condition to their sons (by virtue of passing on their Y chromosome to their sons) but their daughters (to whom they necessarily pass on their X chromosome) will all inherit the mutant gene. Such daughters will always show some dental features although these might be subtle in some cases. The enamel in both sexes may be hypoplastic, hypomineralized, or show elements of both features. The appearance seen will be the result of the exact nature of the change in the amelogenin gene and the sex of the patient. Males, by virtue of having a single X chromosome, will be more severely and uniformly affected. The enamel may be thin (hypoplastic⎯reduced in quantity) or discoloured (with affected mineralisation) or a combination of both (Fig. Females within the same family who inherit the affected gene will show a vertical pattern of markings of the enamel, either vertical ridges and grooves (the equivalent of the male, uniform hypoplasia), with or without discolouration or loss of translucency of the enamel (where the mineralization is affected) (Fig. Aetiology The amelogenin gene, which encodes the enamel protein amelogenin, is located on the short arm of the X chromosome. Mutations in the gene are responsible for most cases of X-linked amelogenesis imperfecta but there also appears to be another gene on the long arm of the X chromosome which is responsible for similar clinical appearances in another family. Genetic enamel defects associated with generalized disorders Widespread enamel defects can be seen in a number of conditions with extraoral manifestations. These include conditions such as epidermolysis bullosa, tuberous sclerosis, oculo-dento-osseus dysplasia, as well as the amelogenesis imperfecta associated with tricho-dento-osseous syndrome. The exact genomic relationship between these and other conditions and amelogenesis imperfecta remains to be established in most cases. Key Points Amelogenesis imperfecta • Inheritance, • Autosomal dominant, • Autosomal recessive, • X-linked, • Apparently sporadic. Phenotype Hypoplastic +/- hypomineralization (hypocalcification to hypomaturity) Pure hypoplasia or hypomineralization are probably rare Profound hypomineralization leads to teeth so soft that they are reduced in size although this is, in fact, a later change. Molar-incisor hypoplasia In recent years reports have been published of children with mineralization defects of the first permanent molars and, sometimes, the permanent incisors. The defects in the incisors⎯which are usually less severe and most likely to show isolated mottling⎯will likewise be irregularly distributed. To the best of our knowledge, this is the first publication of such a familial association. The cause of this anomaly, and even whether it represents a new phenomenon, is uncertain. It has been suggested that there might be a genetic predisposition combining with an environmental insult that produces these changes, but this has yet to be substantiated. The destruction of the molar teeth in particular, although probably a post-eruptive change, presents in many cases at a time when children are not acclimatized to dental treatment. Treatment options should include a careful analysis of the occlusion, since many of the molar teeth are severely compromised, and the child may benefit in the long term by their elective loss as part of a comprehensive treatment plan. For the 2 years between the eruption of the first permanent molar teeth and the commonly recommended time for their removal, management may be difficult. It is clear that many children with this condition are apprehensive patients for dental treatment. This is likely to be because, in its early stages, practitioners adopt a minimalist approach with the attempted use of fissure sealants and adhesive restorations. These are often applied without local anaesthesia, are painful in the process, and frequently unsuccessful anyway. Preformed metal crowns applied under local anaesthesia provide a useful measure in these cases. The incisor defects are not noticeably uncomfortable and should be managed with the techniques described in Chapter 10835H. Within this sense we include both a systemic upset and the result of a local factor involving a developing tooth (as discussed previously in Section 13. Where there is a systemic insult the teeth will be affected in a chronological pattern, so that a band of abnormal enamel is seen in horizontal distribution at some part on the tooth crown. A knowledge of the timing of commencement of formation of the teeth will aid in understanding the timing of such an insult. Systemic (chronological) enamel defects Enamel formation in utero may be affected by a wide range of maternal and foetal conditions. These will include endocrine disturbances (hypoparathyroidism), infections (rubella), drugs (thalidomide), nutritional deficiencies, and haematological and metabolic disorders (Rhesus incompatibility). In such cases, the enamel covering the incisal portions of the crowns of the primary incisors will typically be affected in the pattern shown in Fig. It is not yet clear whether this is associated with the use of intubation for these children in the neonatal period although the latter has been identified as a local cause affecting forming incisors only. When there is a systemic upset or marked physiological changes occur at birth or in the neonatal period, corresponding enamel defects may be seen in the primary dentition. Illness in the neonatal period may also affect the tips of the first permanent molars as these commence development at around birth. Enamel defects may also arise as a result of acute or chronic childhood illnesses (Fig. This will include hypothyroidism and hypoparathyroidism, chronic renal disease, and gastrointestinal disorders producing malabsorption, such as coeliac disease. The use of tetracycline during pregnancy and childhood is to be avoided because of deposition of the tetracycline in developing dental matrices, producing a distinctive blue/grey discolouration of the teeth, sometimes in a chronologically banded distribution (Fig. In the past, exanthematous fevers caused by measles and other infections were associated with a disturbance of normal enamel formation and a corresponding chronological hypoplasia affecting the crowns of developing teeth. Modern medical care has now made this uncommon, unless such changes may occur in the case of babies and infants who develop pneumonia. Excessive intake of fluoride, either from naturally occurring sources such as drinking water with fluoride levels over 1-2 ppm, or from over use of fluoride supplements or fluoride toothpastes, can cause enamel mottling. The condition is dose-dependant, with increasing intake of fluoride being associated with more marked opacity, areas of discolouration of the enamel as well as pitting, and more extensive hypoplastic defects (Fig. One distinguishing feature may be that amelogenesis imperfecta does not show a chronological distribution and that fluorosis, depending on the timing of the excessive intake, does. Local, fluorotic lesions may respond very well to the microabrasion technique (Fig. Children with a cleft lip and palate often have enamel defects of the maxillary incisors. Sometimes this may be related to surgical treatment rather than the effect of the cleft per se. Treatment The treatment of children with enamel defects requires more consideration than simply mechanical treatment of the teeth. This is a serious issue and requires the most sensitive handling by professionals. Affected adult family members will often describe their own childhood in lurid and painful terms. Typically, as well as the aesthetics, there may be thermal, contact or osmotic sensitivity of the teeth.

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Thus buy discount silagra 100mg online erectile dysfunction young, you should always compute a measure of effect size for any significant result 50mg silagra mastercard erectile dysfunction doctor visit, because this is the only way to determine whether your independent variable is important in influencing a behavior buy genuine silagra on-line erectile dysfunction doctor visit. In fact buy silagra cheap impotence doctor, the American Psychological Association requires published research to report effect size. Effect Size Using Cohen’s d One way to describe the impact of an independent variable is in terms of how big a difference we see between the means of our condi- tions. For example, we saw that the presence/absence of hypnosis produced a differ- ence in recall scores of 3. However, the problem is that we don’t know whether, in the grand scheme of things, 3 is large, small, or in between. We need a frame of reference, and here we use the estimated population standard deviation. Recall that the standard deviation reflects the “average” amount that scores differ from the mean and from Describing the Relationship in a Two-Sample Experiment 281 each other. Individual scores always differ much more than their means, but this still provides a frame of reference. For example, if individual scores differ by an “average” of 20, then we know that many large differences among scores occur in this situation. Therefore, a difference of 3 between two samples of such scores is not all that impres- sive. Because smaller differ- ences occur in this situation, a difference between conditions of 3 is more impressive. Thus, we standardize the difference between our sample means by comparing it to the population standard deviation. This is the logic behind the measure of effect size known as Cohen’s d: It measures effect size as the magnitude of the difference between the conditions, relative to the population standard deviation. The formulas for Cohen’s d are: Independent-samples t-test Related-samples t-test X1 2 X2 D d 5 d 5 s2 s2 3 pool 3 D For the independent-samples t-test, the difference between the conditions is meas- ured as X1 2 X2 and the standard deviation comes from the square root of the pooled variance. For the related-samples t-test, the difference between the conditions is measured by D and the standard deviation comes from finding the square root of the estimated vari- ance 1s2. First, the larger the absolute size of d, the larger the impact of the independent variable. In fact, Cohen1 proposed the following interpretations when d is the neighborhood of the following amounts: Values of d Interpretation of Effect Size d 5. Second, we can compare the relative size of different ds to determine the relative impact of a variable. Others think of d as the amount of impact the independent variable has, which can- not be negative. Effect Size Using Proportion of Variance Accounted For This approach measures effect size, not in terms of the size of the changes in scores but in terms of how consistently the scores change. Here, a variable has a greater impact, the more it “causes” everyone to behave in the same way, producing virtually the same score for everyone in a particular condition. This then is an important variable, because by itself, it pretty much controls the score (and behavior) that everyone exhibits. Thus, in an experiment, the proportion of variance accounted for is the pro- portional improvement achieved when we use the mean of a condition as the predicted score of participants tested in that condition compared to when we do not use this approach. Put simply it is the extent to which individual scores in each con- dition are close to the mean of the condition, so if we predict the mean for someone, we are close to his or her actual score. When the independent variable has more con- trol of a behavior, everyone in a condition will score more consistently. Then scores will be closer to the mean, so we will have a greater improvement in accurately pre- dicting the scores, producing a larger proportion of variance accounted for. On the other hand, when the variable produces very different, inconsistent scores in each condition, our ability to predict them is not improved by much, and so little of the variance will be accounted for. In Chapter 8, we saw that the computations for the proportion of variance accounted for are performed by computing the squared correlation coefficient. For the two-sample experiment, we compute a new correlation coefficient and then square it. The squared point-biserial correlation coefficient indicates the propor- tion of variance accounted for in a two-sample experiment. This pb can produce a proportion as a low as 0 (when the variable has no effect) to as high as 1. In real research, however, a variable typically accounts for between about 10% and 30% of the variance, with more than 30% being a very substantial amount. Statistics in Published Research: The Two-Sample Experiment 283 The formula for computing r2 is pb 1t 22 2 obt rpb 5 2 1tobt2 1 df This formula is used with either the independent-samples or related-samples t-test. Then, for independent samples, df 5 1n1 2 12 1 1n2 2 12 For related samples, df 5 N 2 1. Hypnosis is not of major importance here, because scores are not consis- tently very close to the mean in each condition. Therefore, hypnosis is only one of a number of variables that play a role here, and, thus, it is only somewhat important in determining recall. Further, fewer other variables need to be considered in order to completely predict scores, so this is an important relationship for understanding phobias and the therapy. We also use the proportion of variance accounted for to compare the relationships from different studies. Thus, the role of therapy in determining fear scores (at 67%) is about three times larger than the role of hypnosis in determining recall scores (which was only 22%). Thus, a published report of our independent-samples hypnosis study might say, “The hypnosis group (M 5 23. Obviously, you perform the independent-samples t-test if you’ve cre- ated two independent samples and the related-samples t-test if you’ve created two related samples. In both procedures, if tobt is not significant, consider whether you have sufficient power. If tobt is significant, then focus on the means from each condition so that you summarize the typical score—and typical behavior—found in each condition. Use effect size to gauge how big a role the independent variable plays in determining the behaviors. Finally, interpret the relationship in terms of the underlying behaviors and causes that it reflects. For either, the program indicates the at which tobt is significant, but for a two-tailed test only. It also computes the descriptive statistics for each condition and automatically computes the confidence interval for either 1 2 2 or D. Two samples are independent when participants are randomly selected for each, without regard to who else has been selected, and each participant is in only one condition. The independent-samples t-test requires (a) two independent samples, (b) normally distributed interval or ratio scores, and (c) homogeneous variance. Homogeneity of variance means that the variances in the populations being represented are equal. The confidence interval for the difference between two ms contains a range of differences between two s, one of which is likely to be represented by the difference between our two sample means. Two samples are related either when we match each participant in one condition to a participant in the other condition, or when we use repeated measures of one group of participants tested under both conditions. The confidence interval for mD contains a range of values of D, any one of which is likely to be represented by the sample’s D. The power of a two-sample t-test increases with (a) larger differences in scores between the conditions, (b) smaller variability of scores within each condition, and (c) larger ns The related-samples t-test is more powerful than the independent-samples t-test. Effect size indicates the amount of influence that changing the conditions of the independent variable had on the dependent scores. Cohen’s d measures effect size as the magnitude of the difference between the conditions. The proportion of variance accounted for (computed as r2 ) measures effect pb size as the consistency of scores produced within each condition. The larger the proportion, the more accurately the mean of a condition predicts individual scores in that condition. All other things being equal, should you create a related-samples or an independent-samples design? We study the relationship between hot or cold baths and the amount of relaxation they produce. The relaxation scores from two independent samples are Sample 1 (hot): X 5 43, s2 5 22. We investigate if a period of time feels longer or shorter when people are bored compared to when they are not bored. Using independent samples, we obtain these estimates of the time period (in minutes): Sample 1 (bored): X 5 14. A researcher asks if people score higher or lower on a questionnaire measuring their well-being when they are exposed to much sunshine compared to when they’re exposed to little sunshine. A sample of 8 people is measured under both levels of sunshine and produces these well-being scores: Low: 14 13 17 15 18 17 14 16 High: 18 12 20 19 22 19 19 16 (a) Subtracting low from high, what are H0 and Ha? A researcher investigates whether classical music is more or less soothing to air- traffic controllers than modern music. She gives each person an irritability question- naire and obtains the following: Sample A (classical): n 5 6, X 5 14. We predict that children exhibit more aggressive acts after watching a violent television show. The scores for ten participants before and after watching the show are Sample 1 (After) Sample 2 (Before) 5 6 4 4 7 3 2 1 4 3 (a) Subtracting before from after, what are H0 and Ha?

The Y intercept indicates the starting point from which the Y scores begin to change generic silagra 50 mg amex can you get erectile dysfunction young age. Thus buy silagra 50mg on-line impotence bike riding, together order silagra with a mastercard impotence hypertension medication, the slope and intercept describe how cheap silagra master card best erectile dysfunction pills treatment, starting at a particular Y score, the Y scores tend to change by a specific amount as the X scores increase. As an example, say that we have developed a test to identify (predict) those indi- viduals who will be good or bad workers at a factory that makes “widgets. The predictor (X) variable is participants’ scores on the widget test, and the criterion (Y) variable is the number of widgets they produced. This is a very strong, positive linear relationship, and so the test will be what researchers call “a good predictor” of widget-making. The numerator of the formula for b is the same as the numerator in the formula for r, and the denominator of the formula for b is the left-hand quantity in the denominator of the formula for r. This positive slope indicates a positive relationship, which fits with the positive r of 1. Had the rela- tionship been negative, the formula would have produced a negative number here. Computing the Y Intercept The formula for the Y intercept of the linear regression line is a 5 Y 2 1b21X2 First, multiply the mean of all X scores times the slope of the regression line. Describing the Linear Regression Equation Once you have computed the Y intercept and the slope, rewrite the regression equation, substituting the computed values for a and b. Plotting the Regression Line We use the finished regression equation to plot our linear regression line. To draw a line, we need at least two data points, so choose a low and high X score, insert each into the regression equation, and compute the Y¿ for that X. Therefore, we also use the finished regression equation to predict anyone’s Y score if we know their X score. In fact, computing any Y¿ using the equation is the equivalent of going to the graph and traveling vertically from the X score up to the regression line and then left to the value of Y¿ on the Y axis. We can compute Y¿ for any value of X that falls within the range of Xs in our data, even if it’s a score not found in the original sample: No one scored an X of 1. Our regression equa- tion is based only on widget test scores between 1 and 4, so we shouldn’t predict a Y for an X of, for example, 6. This is because we can’t be sure what the nature of the relationship is at 6—maybe it’s curvilinear or has a steeper slope. Putting all of this together, the preceding computations are summarized in Table 8. Substitute the values of a and b into the formula for the regression equation: Y¿ 5 1b21X2 1 a 5. The components of the regression equation to To use X to predict Y in these scores, compute first are the ______ and ______. Compute b for the following scores: X Y X Y 1 1 2 2 3 3 4 Compute b: ©X 5 12, ©Y 5 25, ©X2 5 28, 4. To describe the amount of prediction error we expect when predicting unknown scores, we first determine how well we can predict the actual Y scores in our sample: We pretend we don’t know the scores, predict them, and then compare the predicted Y¿ scores to the actual Y scores. The error in a single prediction is the amount that a participant’s Y score differs from the corresponding predicted Y¿ score: In symbols this is Y 2 Y¿, and it is literally the dif- ference between the score a participant got and the score we predict he or she got. The predictions for some participants will be closer to their actual Y scores than for others, so we would like to compute something like the average error across all predictions. To find the average error, we first compute Y¿ for everyone in the sample and sub- tract their Y¿ from their actual Y score. Statisticians equate errors with deviations, so Describing Errors in Prediction 169 Y 2 Y¿ equals the amount that Y deviates from Y¿. To get the average error, we would like to simply sum these deviations and then find the average, but we cannot. Therefore, the Ys are equally spread out around their Y¿ scores, in the same way that previously we saw that Xs are spread out around their X. Because of this, like with the mean, the positive and nega- tive deviations with Y will cancel out, always producing a sum equal to zero. The sum of the squared deviations of Y 2 Y¿ is not necessarily zero, so neither is the average squared deviation. Computing the Variance of the Y Scores Around Y9 The variance of the Y scores around Y¿ is the average squared difference between the actual Y scores and their corresponding predicted Y¿ scores. The S2 indicates sample variance or error, and the subscript Y¿ indi- Y¿ cates that it is the error associated with using Y¿ to predict Y scores. The formula that defines the variance of the Y scores around Y¿ is ©1Y 2 Y¿ 22 S2 5 Y¿ N Like other definitional formulas we’ve seen, this formula is important because it shows the core calculation involved: We subtract the Y¿ predicted for each participant from his or her actual Y score giving us a measure of our error. The answer is one way to measure roughly the “average” amount of error we have when we use linear regression to predict Y scores. Note: Among the approaches we might use, the regression procedures described in this chapter produce the smallest error in predictions possible, thereby producing the smallest sum of squared deviations possible. In the defining formula, we can replace Y¿ with the formulas for finding Y¿ (for finding a, b, and so on). Among all of these formulas we’ll find the com- ponents for the following computational formula. The computational formula for the variance of the Y scores around Y9 is S2 5 S2 11 2 r22 Y¿ Y Much better! Therefore, finish the computations of S2 using the formula at the begin- Y ning of this chapter. Although this variance is a legitimate way to compute the error in our predictions, it is only somewhat like the “average” error, because of the usual problems when interpreting variance. First, squaring each difference between Y and Y¿ produces an unrealistically large number, inflating our error. Second, squaring produces error that is measured in squared units, so our predictions above are off by 2. To distinguish the standard deviation found in regression, we call it the standard error of the estimate. Computing the Standard Error of the Estimate The standard error of the estimate is similar to a standard deviation of the Y scores around their Y¿ scores. It is the clearest way to describe the “average error” when using Y¿ to predict Y scores. By computing the square root, the answer is a more realistic number and we are no longer dealing with a squared variable. The core calcu- lation, however, is still to find the error between participants’ actual Y scores and their predicted Y¿ scores, and this is as close as we will come to computing the “average error” in our predictions. Then we find the square root of the quantity 1 2 r2 and then multiply it times the standard deviation of all Y scores. Therefore, we conclude that when using the regression equation to predict the number of widgets produced per hour based on a per- son’s widget test score, when we are wrong, we will be wrong by an “average” of about 1. It is appropriate to compute the standard error of the estimate anytime you compute a correlation coefficient, even if you do not perform regression—it’s still important to know the average prediction error that your relationship would produce. The symbol for the variance of the Y scores around errors in prediction when using regression, which Y¿ is ______. Y¿ Y¿ Interpreting the Standard Error of the Estimate In order for S (and S 2) to accurately describe our prediction error, and for r to accu- Y¿ Y¿ rately describe the relationship, you should be able to assume that your data generally meet two requirements. Homoscedasticity occurs when the Y scores are spread out to the same degree at every X. Because the vertical spread of the Y scores is constant at every X, the strength of the relationship is relatively constant at both low Xs and at high Xs, so r will accurately describe the relationship for all Xs. Further, the vertical distance sepa- rating a data point above or below the regression line on the scatterplot is a way to visualize the difference between someone’s Y and the Y¿ we predict. Heteroscedasticity occurs when the spread in Y is not equal throughout the relationship. Now part of the relationship is very strong (forming a nar- row ellipse) while part is much weaker (forming a fat ellipse). Therefore, r will not accurately describe the strength of the relationship for all Xs. Second, we assume that the Y scores at each X form an approximately normal distri- bution. That is, if we constructed a frequency polygon of the Y scores at each X, we should have a normal distribution centered around Y¿. Recall that in a normal distribution approximately 68% of the scores fall between ;1 standard deviation from the mean. The Strength of a Relationship and Prediction Error Finally, although the standard error of the estimate is the way to quantify our “average” prediction error, be sure you understand why this error is communicated by the size of r. A larger r indicates a stronger relationship and the strength of a relationship determines the amount of prediction error that occurs. This is because the strength of a relationship is the amount of variability—spread—in the Y scores at each X. Thus, there is small vertical spread in the Ys at each X, so the data points are close to the regression line. When the data points are close to the regression line it means that participants’ actual Y scores are relatively close to their corresponding Y¿ scores. Therefore, we will find relatively small differences between the participants’ Y scores and the Y¿ we predict for them, so we will have small error, and S and S2 Y¿ Y¿ will be small. This indicates that the Y scores are more spread out vertically around the regression line. Therefore, more often, participants’ actual Y scores are farther from their Y¿ scores, so we will have greater error, and S and S2 will be larger. This is why, as we Y¿ Y¿ saw in the previous chapter, the size of r allows us to describe the X variable as a good or poor “predictor” for predicting Y scores. When r is large, our prediction error, as measured by S or S2 is small, and so the X variable is a good predictor.

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So if you want to be well and stay well cheap silagra 50 mg visa latest news erectile dysfunction treatment, stay away from doc- tors and hospitals discount silagra on line causes of erectile dysfunction in 40 year old, have lower medical insurance rates and bills trusted 50 mg silagra erectile dysfunction protocol download free, have more vitality silagra 100 mg visa impotence reasons and treatment, and function into your senior years then move every day! Do something daily that gets your heart rate up (aerobics), challenges your muscles (strength training), and causes you to extend and contract ligaments, muscles, and tendons (flexibility). Thinking about how we evolved and the amount of movement done by healthy aging cultures, we need to expect movement ev- ery day—not three days per week, but every day, for a minimum of a half-hour per day. If you shoot for one hour and fall short a day or two, two things usually happen: 1. Daily structured movement has to be as important and expected as brushing your teeth, taking a shower, combing your hair, and other normal and expected activities of daily living. When you get to the point where not exercising feels “not right,” the way you’d feel if you didn’t brush your teeth for the day, then you have built the exercise habit. When you don’t go home from work until you exercise, you have built the exercise habit. When you are looking for ways to exercise when you are away from home on business or vacation, you have built the exercise habit. When you don’t try to make an excuse for not exer- cising, you have built the exercise habit. If you say, “Some exercise is better than no exercise” when you can’t do your regular exercise routine, and you do something else involving movement, you have developed the exercise habit. It’s about Time and Consistency More than Intensity and Technique If you are new to the exercise game, it is going to take three to nine months before you build the exercise habit and it becomes “part of you. It doesn’t matter at first what type of exercise, as long as it is some type of aerobic, big muscle-moving exercise and is safe. Success with exercise is more about consistency and time than it is about technique and intensity. If you build in the time to exercise as part of your normal day and are consistent with your exercise program, you will see results and will naturally start to pick up the intensity and duration of the - 161 - staying healthy in the fast lane exercise after a few weeks. For the average person it is far more important to have lots of victories to keep your exer- cise program alive than to push through pain and injure yourself or be so sore you quit. Nagging injuries, persistent soreness, and pain are “killers” to building the exercise habit. Down the road, af- ter exercising three months to a year, if you really want to push yourself, give it a try. The most common excuse I get in the clinic is “I can’t exercise because I am too busy (and/ or too tired). I am very efficient with my exercise from strength training to aerobics and my flexibility work. You want to have a good cardiovascular system, be strong, and be flexible—and you want to do the exercises fast, efficiently, and safely. When you have that exerciser’s mentality—when that exercise habit is part of you—you will see the opportunities within your daily life to exercise efficiently and safely. How to Increase “Non-Exercise” Exercise More traditional cultures get their exercise from “non-exer- cise” exercise. Just the work they have to do to feed themselves, their daily jobs, and taking care of their dwellings provide some vigorous physical activity. If you are older and all you have is canned products around, use the cans as dumb bells. We are talking about a few extra minutes, not hours, be- cause you choose to walk. I have heard some very successful weight-loss specialists talk about how important it is to get obese people to add this “non- exercise” exercise to a structured exercise program. He committed himself to using the stairs during his hospital rounds versus the elevator and was amazed at how much exercise he got while seeing patients in his very busy medical practice. Just think: These basic examples only cover the simple things we can do as a part of our daily routines. They don’t even begin to account for all the exercise opportunities just waiting to be incor- porated into our “fun” time! Exercising when Traveling for Business or Pleasure When staying at a hotel, always ask if there is a fitness room. Trips can be stressful enough (whether for business or plea- sure), so it’s critical to have a space to exercise, take a little edge off, and do something good for your body. Just because the setup is dif- ferent or less optimal than your home or personal gym, be creative. By not skipping a day when travel- ing, even if you do less than you normally do, you are more likely - 164 - the triad exercise program to stay with your overall program and ultimately be successful in your fitness goals. If the hotel does not have an exercise room, look for a space in your room to stretch and do push-ups, chair-dips, etc. Also, ask the concierge or front-desk staff if there is a safe place to walk around the hotel. On a cruise or at an all-inclusive resort, check out the gym and see if there are any classes you might like to sign up for (yoga, aero- bics, dance, etc. If there is something physically active you like to do (dancing, swimming, snorkeling, boogie boarding, hiking, aerobics, yoga, etc. I’m a dancer, so I always check out salsa and lindy hop dance venues near where I am going on vacation or business. If your vacation is outdoors and near nature, hiking and swim- ming are enjoyable and productive ways to exercise. You won’t lose that much from your regular fitness routine if you do some- thing while away from home. If you haven’t been exercising in a while and/or are overweight or have cardiac issues, you should see your doctor first. Think about it: How much of your normal daily activity can you make into movement? I can’t think of anything more important than exercising and spending quality time with your family; it is a “win-win. The combination isn’t important; keeping - 166 - the triad exercise program yourself from getting bored and moving for at least thirty minutes is important! You could exercise for fifteen min- utes on the stair-stepper at your business gym and then walk with your family/spouse for a half-hour when you get home. Or maybe go to a martial arts class in the eve- ning or dance for an hour (keep a vision in the back of your mind of a total goal of one hour per day). For exam- ple, play tennis two days per week, walk two days, take an aerobics class two days, and hike one day. First and foremost, you don’t have to spend hours in the gym to get a really cut body and be strong. With a focused, - 167 - staying healthy in the fast lane fifteen-minute circuit training program three to four days per week, you can have a great physique and be strong. It may sound egotistical, but I know it because I do it, and I get compliments on my fifty-plus-year-old body frequently. You also have to eat right and get lean if you want your physique to show definition. You don’t need to be downing protein-rich sports drinks, or eating tons of meat and eggs daily or immediately after exercising. If you choose to have animal foods, which are not necessary for muscles or for good health, then eat lean meat, poultry (grass-fed, free-ranged, hormone- and antibiotic-free), and fish in the context of your three daily meals surrounded by lots of unrefined plant foods. You meat-eating and dairy-supplementing gym rats have been duped into thinking you have to consume lots of protein and animal foods to be strong and athletic. He was telling me about his weight issues and medical problems with diabetes, hypertension, and kidney issues. He was a classic “dairy-aholic” and was stunned when I told him to elimi- nate the dairy, cut back on the meat, and eat more vegetables, and that he’d still be fine in the gym. I also told him he’d drop some weight and probably improve his diabetes and kidney function. He was fearful of not being strong and muscular if he cut back on those foods (meat and dairy, to which he was addicted). Americans have been brainwashed by the propaganda that you have to consume meat, poultry, fish, and dairy products to be healthy and strong. He or she doesn’t have hours and hours to train in the gym, is not an elite athlete train- ing for some type of competition, and is not a movie star trying to tweak a particular area of his or her body. That said, building lean body mass is not only healthy for our metabolism (blood sugar control and immune function), but also helps us function in our daily lives, especially as we get older. It is fast; there are no weights to put away; it is safe; you don’t need a partner or coach; it works different muscle groups in their full range of motion; it works the body symmetrically; it is easy for anyone to use after maybe one or two sessions of instruction; and it has some cardiovascular benefit (not a lot) if you keep moving. I included fifteen minutes because that is what it takes me: fifteen minutes at a consistent pace to do six different upper-body exer- cises and six lower-body exercises. Just do circuit training in the above-mentioned fashion for two months (along with a whole-food, plant-strong diet). If you want to speed up the process, do the circuit training every other day for a month. If you want to spend twenty-five to thirty minutes doing circuit training, do just ten to twelve different upper-body exer- cises and ten to twelve different lower-body exercises. The key is moving steadily between stations; alternate arm and leg exercises so you don’t fatigue a group of muscles. Do as many different ex- ercises as the machines allow before repeating an exercise so you work as many different muscle groups and go through as many different ranges of motion as possible.

Sample B shows a less 2 4 80 80 33 28 40 60 consistent relationship: Sometimes different Ys occur 2 4 80 79 33 20 40 60 at a particular X buy cheap silagra 100mg on line erectile dysfunction fact sheet, and the same Y occurs with different 3 6 85 76 43 27 45 60 Xs buy 100 mg silagra mastercard impotence due to diabetes. Sample C shows no relationship: The same Ys tend 3 6 85 75 43 20 45 60 to show up at every X buy silagra amex erectile dysfunction drugs gnc. In a graph we have the X and Y axes and the X and Y scores purchase silagra 50mg mastercard erectile dysfunction over the counter drugs, but how do we decide which variable to call X or Y? In any study we implicitly ask this question: For a given score on one variable, I wonder what scores The Logic of Research 19 occur on the other variable? The variable you identify as your “given” is then called the X variable (plotted on the X axis). Once you’ve identified your X and Y variables, describe the relationship using this general format: “Scores on the Y variable change as a function of changes in the X variable. Then, to read a graph, read from left to right along the X axis and ask, “As the scores on the X axis increase, what happens to the scores on the Y axis? Here, as the X scores increase, the data points move upwards, indicating higher Y scores, so this shows that as the X scores increase, the Y scores also increase. Further, because every- one who obtained a particular X obtained the same Y, the graph shows perfectly consis- tent association because there is one data point at each X. Graph B shows test errors as a function of the number of hours studied from Table 2. Further, because several different error scores occurred with each study-time score, we see a vertical spread of different data points above each X. Again, decreasing Y scores occur with increasing X scores, but here there is greater vertical spread among the data points above each X. This indicates that there are greater differences among the error scores at each study time, indicating a weaker relationship. For any graph, whenever the data points above each X are more vertically spread out, it means that the Y scores differ more, and so a weaker relationship is present. The graph shows this because the data points in each group are at about the same height, indicating that about the same eye-blink scores were paired with each chocolate score. Whenever a graph shows an essentially flat pattern, it reflects data that do not form a relationship. However, because we are always talking about samples and populations, we distinguish between descrip- tive statistics, which deal with samples, and inferential statistics, which deal with populations. Descriptive Statistics Because relationships are never perfectly consistent, researchers are usually confronted by many different scores that may have a relationship hidden in them. Descriptive statistics are proce- dures for organizing and summarizing sample data so that we can communicate and describe their important characteristics. Thus, for our study-time research, we would use descriptive statistics to answer: What scores occurred? On the one hand, descriptive procedures are useful because they allow us to quickly and easily get a general understanding of the data without having to look at every single score. For example, hearing that the average error score for 1 hour of study is 12 simplifies a bunch of different scores. Likewise, you can summarize the overall relationship by men- tally envisioning a graph that shows data points that follow a downward slanting pattern. On the other hand, however, there is a cost to such summaries, because they will not precisely describe every score in the sample. A major goal of behavioral science is to be able to predict when a particular behavior will occur. This translates into predicting individuals’ scores on a variable that measures the behavior. To do this we use a relationship, because it tells us the high or low Y scores that tend to naturally occur with a particular X score. Then, by knowing someone’s X score and using the relationship, we can predict his or her Y score. Thus, from our previous data, if I know the number of hours you have studied, I can predict the errors you’ll make on the test, and I’ll be reasonably accurate. Inferential Statistics After answering the above questions for our sample, we want to answer the same ques- tions for the population being represented by the sample. Thus, although technically descriptive statistics are used to describe samples, their logic is also applied to popula- tions. Because we usually cannot measure the scores in the population, however, we must estimate the description of the population, based on the sample data. But remember, we cannot automatically assume that a sample is representative of the population. Therefore, before we draw any conclusions about the relationship in the population, we must first perform inferential statistics. Inferential statistics are proce- dures for deciding whether sample data accurately represent a particular relationship in the population. Essentially, inferential procedures are for deciding whether to believe what the sample data seem to indicate about the scores and relationship that would be found in the population. Thus, as the name implies, inferential procedures are for mak- ing inferences about the scores and relationship found in the population. If the sample is deemed representative, then we use the descriptive statistics com- puted from the sample as the basis for estimating the scores that would be found in the population. Thus, if our study-time data pass the inferential “test,” we will infer that a relationship similar to that in our sample would be found if we tested everyone after they had studied 1 hour, then tested everyone after studying 2 hours, and so on. Like- wise, we would predict that when people study for 1 hour, they will make around 12 errors and so on. Statistics versus Parameters Researchers use the following system so that we know when we are describing a sam- ple and when we are describing a population. A number that is the answer from a de- scriptive procedure (describing a sample of scores) is called a statistic. On the other hand, a number that describes a charac- teristic of a population of scores is called a parameter. Thus, for example, the average in your statistics class is a sample average, a descrip- tive statistic that is symbolized by a letter from the English alphabet. If we then esti- mate the average in the population, we are estimating a parameter, and the symbol for a population average is a letter from the Greek alphabet. Inferential proce- dures are for estimating parameters, which describe a population of scores and are symbolized using the Greek alphabet. Although we discuss a number of descriptive and inferential procedures, only a few of them are appropriate for a particular study. First, your choice depends on what it is you want to know—what question about the scores do you want to answer? A study’s design is the way the study is laid out: how many samples there are, how the partici- pants are tested, and the other specifics of how a researcher goes about demonstrating a relationship. Therefore, part of learning when to use different statistical procedures is to learn with what type of de- sign a procedure is applied. To begin, research can be broken into two major types of designs because, essentially, there are two ways of demonstrating a relationship: exper- iments and correlational studies. Experiments In an experiment the researcher actively changes or manipulates one variable and then measures participants’ scores on another variable to see if a relationship is produced. For example, say that we examine the amount of study time and test errors in an exper- iment. We decide to compare 1, 2, 3, and 4 hours of study time, so we randomly select four samples of students. We ask one sample to study for 1 hour, administer the test, and count the number of errors that each participant makes. We have another sample study for 2 hours, administer the test, and count their errors, and so on. Then we look to see if we have produced the relationship where, as we increase study time, error scores tend to decrease. To select the statistical procedures you’ll use in a particular experiment, you must understand the components of an experiment. The Independent Variable An independent variable is the variable that is changed or manipulated by the experimenter. Implicitly, it is the variable that we think causes a change in the other variable. In our studying experiment, we manipulate study time because we think that longer studying causes fewer errors. Or, in an experiment to determine whether eating more chocolate causes people to blink more, the experimenter would manipulate the Understanding Experiments and Correlational Studies 23 independent variable of the amount of chocolate a person eats. You can remember the independent variable as the variable that occurs independently of the participants’ wishes (we’ll have some participants study for 4 hours whether they want to or not). Technically, a true independent variable is manipulated by doing something to par- ticipants. However, there are many variables that an experimenter cannot manipulate in this way. For example, we might hypothesize that growing older causes a change in some behavior. Instead, we would manipulate the variable by selecting one sample of 20-year-olds and one sample of 40-year-olds. Similarly, if we want to examine whether gender is related to some behavior, we would select a sample of females and a sample of males. In our discussions, we will call such variables independent variables because the experimenter controls them by controlling a characteristic of the samples. In essence, a participant’s “score” on the independent variable is assigned by the experimenter. In our examples, we, the researchers, decided that one group of students will have a score of 1 hour on the variable of study time or that one group of people will have a score of 20 on the variable of age. Conditions of the Independent Variable An independent variable is the overall variable that a researcher examines; it is potentially composed of many different amounts or categories.

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Allopurinol is used to treat chronic, tophaceous gout because it reduces the size of the estab- lished tophi; colchicine is administered concomitantly during the first week of therapy to pre- vent gouty arthritis. Allopurinol inhibits the synthesis of uric acid by inhibiting xanthine oxidase, an enzyme that converts hypoxanthine to xanthine and xanthine to uric acid. Allopurinol is metabolized by xanthine oxidase to alloxanthine, which also inhibits xanthine oxidase. This agent more rarely causes hypersensitivity, including fever, hepatic dysfunction, and blood dyscrasias. Allopurinol should be used with caution in patients with liver disease or bone marrow depression. Glucocorticoids, cyclosporine, tacrolimus (Prograf), and siroli- mus (rapamycin) (Rapamune) inhibit the activation or actions of specific cells of the immune system and are generally less toxic than the nonspecific agents. Suppression of the immune system increases the risk of opportunistic viral, bacterial, and fun- gal infections. To overcome an allergic reaction, small quantities of antigen are administered gradually to develop tolerance, most probably as a result of the induction of IgG antibodies to neutralize a subsequent IgE reaction with the allergen. Immunosuppressive agents are used to treat syndromes or diseases that reflect imbalances in the immune system, including rheumatoid arthritis, systemic lupus erythematosus, inflamma- tory bowel disease, chronic active hepatitis, lipoid nephrosis, Goodpasture syndrome, and autoimmune hemolytic anemia. Immunosuppressive agents are also used to prevent allograft rejection, which results when cy- totoxic T lymphocytes develop in response to incompatible transplanted organs. Glucocorticoids are thought to interfere with the cell cycle of activated lymphoid cells and stimulate apoptosis in some lymphoid lineages. Glucocorticoids are important agents in suppressing allograft rejection; they are often used in combination with either cyclosporine or a cytotoxic agent. Cyclosporine has a biphasic t1/2, with a terminal phase of 10–25 hours; it is metabolized in the liver and eliminated primarily in bile. The main use of cyclosporine is in short- and long-term suppression of organ rejection in transplants of the kidney, liver, and heart. Cyclosporine as an ophthalmic emulsion (Restasis) is used to increase tear production in patients with ocular inflammation associated with keratoconjunctivitis sicca. Cyclosporine causes nephrotoxicity in 25%–75% of patients, with a reduction in glomerular filtration and renal plasma flow; hypertension in 30% of patients; neurotoxicity (tremor and seizures) in 5%–50% of patients; and hirsutism and gingival hyperplasia in 10%–30% of patients. Cyclosporine is synergistically nephrotoxic with other drugs that affect kidney function. In- hibition of hepatic microsomal enzymes elevates plasma concentration; the induction of drug-metabolizing enzymes enhances clearance. The adverse effects are similar to those with cyclosporine; tacrolimus can damage the kid- neys and nervous system, manifest by tremors, headache, and renal impairment. Sirolimus is approved for renal transplantation; its efficacy in liver transplant has not been determined. Many of the adverse effects of sirolimus follow from growth factor inhibition and include suppression of all blood elements, impaired wound healing, and rashes; metabolic effects include increased plasma cholesterol and triglycerides. Azathioprine is a cytotoxic agent that suppresses T-cell activity to a greater degree than B- cell activity. Dose reduction is necessary when azathioprine is administered with allopurinol, which reduces xanthine oxidase activity. Azathioprine is used with prednisone in transplantation procedures and in some diseases of the immune system, including systemic lupus erythematosus and rheumatoid arthritis. This agent is the drug of choice in the treatment of Wegener granulomatosis; it is also used in severe cases of rheumatoid arthritis and other autoimmune disorders. Methotrexate has been used for graft rejection and for autoimmune and inflammatory diseases. This agent has also proved beneficial in the treatment of severe psoriasis that is refractory to other agents. Antithymocyte globulin (Atgam) (1) Polygonal antibodies raised against human thymic lymphocytes Chapter 6 Autocoids, Ergots, Anti-inflammatory Agents, and Immunosuppressive Agents 171 (2) Following intravenous administration, T lymphocytes are removed from the circulation, resulting in decreased T-cell–mediated immune response. Which of the following drugs is most asthma clinic complaining that he is sneezing likely responsible for the adverse renal effect? He (A) Ibuprofen indicates that he seems to have a month or so of (B) Prednisone these symptoms every spring. Which of the fol- (C) Colchicine lowing drugs would be most appropriate to treat (D) Probenecid this patient? A neonate is identified as having atrial septal (B) Scopolamine defect of congenital origin that will require sur- (C) Fexofenadine gical repair. Adequate systemic perfusion (D) Cetirizine requires that the patency of the ductus arterio- sus be maintained. Following a prolonged first labor, an alert agents would best accomplish this goal? Lately, (B) Buspirone however, she has had more frequent symp- (C) Methylergonovine toms, so she increased the dose of the medi- (D) Methysergide cation. She now asks her friend, who is a medical student, to explain to her how exactly 3. Agonist activity (B) It modulates the release of dopamine and at which of the following receptors would be the serotonin best target for your new treatment? An elderly patient has a history of taking both prescription medications and over-the-counter 7. She is not diabetic and has no history of kid- that he has been taking aspirin for many years ney disease. The doc- acute renal failure and comments that the pain tor suspects gastritis and prescribes a trial of in her hands has become much worse in the last medication that might be helpful to this patient. A fetal heart monitor (B) Desloratadine shows that the fetus is currently in no acute dis- (C) Cetrizine tress. Sterile examination shows the patient to (D) Famotidine be minimally dilated without significant efface- (E) Buspirone ment. A 70-year-old man suffers a myocardial in- like to know how this medication works. A catheterization procedure is sched- 1D (C) It blocks reuptake of serotonin uled. She also complains of (C) Aspirin is a weak acid milky discharge from her breasts and lack of (D) Aspirin is excreted by the kidneys menstruation in the last 3 months. Which medica- tion would most likely benefit this patient if she is deemed not a good operative candidate? Cetirizine is a second-generation antihistamine, but it still has some sedating effects. Methylergonovine produces powerful contraction of uterine smooth muscle that can reduce postpartum bleeding. The other agents also interact with serotonin receptors but would not be effective in this case. Prednisone is effective in alleviating the inflammation in rheumatoid arthritis but is not associated with adverse renal effects. Inhibi- tors of prostaglandin biosynthesis, indomethacin and celecoxib, cause closure of the ductus. Bromocriptine is a dopaminergic agonist used to treat hyperprolactinemia, as with pituitary adenomas, or for suppression of normal lactation. Heme iron is also an essential component of muscle myoglobin and of several enzymes, such as catalase, peroxidase, the cytochromes, and others. Absorption and transport (1) Heme iron is much more readily absorbed across the intestine than inorganic iron. Regulation (1) Except for menstruation and bleeding disorders, very little iron is lost from the body, and no mechanism exists for increasing excretion. All are essentially equivalent thera- peutically if doses are adjusted according to iron content (gluconate, sulfate, and fuma- rate forms are 12%, 20%, and 33% iron by weight, respectively; a polysaccharide–iron complex is also available). Administered systemati- cally or by gastric lavage, deferoxamine binds iron and promotes excretion. Sideroblastic anemias are characterized by decreased hemoglobin synthesis and intracellular accumulation of iron in erythroid precursor cells. Sideroblastic anemias are often caused by agents that antagonize or deplete pyridoxal phosphate. Sideroblastic anemias are sometimes seen in alcoholics, in patients undergoing antituberculin therapy with isoniazid and pyrazinamide, and in certain inflammatory and malignant disorders. Sideroblastic anemia is treated with pyridoxine (vitamin B6) administered orally (preferred route) or parenterally. The endogenous cobalamins in humans are methylcobalamin and 5-deoxyadenosylcobalamin. Transport and absorption (1) In the stomach, dietary vitamin B12 complexes with intrinsic factor, a peptide secreted by the parietal cells. The intrinsic factor–vitamin B12 complex is absorbed by active transport in the distal ileum. The appearance of large macrocytic (megaloblastic) red cells in the blood is characteristic of this deficiency. Vitamin B12 is not synthesized by eukaryotic cells and is normally obtained from microbial synthesis.