Three years ago, I was visiting an urban school in Columbus, Ohio, that had in place a program of surprisingly explicit training of young children for the modern marketplace. Starting in kindergarten, children in the school were asked to think about the jobs they might choose when they grew up. The posters that surrounded them made clear which kinds of jobs they were expected to select.

“Do you want a manager’s job?” the first line of a kindergarten poster asked.

“What job do you want?” a second question asked in an apparent effort to expand the range of choices that these 5-year-olds might wish to make.

But the momentary window that this second question seemed to open into other possible careers was closed by the next and final question on the wall: “How will you do the manager’s job?”

The tiny hint of choice afforded by the second question was eradicated by the third, which presupposed that all the kids had said yes to the first. No written question asked the children: “Do you want a lawyer’s job, a nurse’s job, a doctor’s job, a poet’s job, a preacher’s job?” Sadly, the teacher had not even thought to ask if anybody in the class might someday like to be a teacher.

Work-related themes were carried over into almost every classroom. In a 1st-grade class, for instance, the names of children and their assigned classroom tasks were posted on the wall, an ordinary thing to see in classrooms everywhere. But in this case there was a novel twist: All the jobs were described as management positions! There was a “Coat Room Manager” and a “Door Manager,” a “Pencil Sharpener Manager” and a “Soap Manager.”

In the upper grades, the management positions became more sophisticated and demanding. In 4th grade, for example, I was introduced to a “Time Manager” who was assigned to hold the timer to be sure the teacher didn’t wander from her schedule and that everyone adhered to the prescribed number of minutes that had been assigned to every classroom task.

In another 4th-grade class, an “earnings chart” had been taped to every child’s desk. On each chart, a number of important writing skills had been spelled out and, next to each, the corresponding earnings that a child would receive if written answers he or she provided in the course of classroom exercises displayed the necessary skills. There was also a Classroom Bank in which the children’s earnings accrued. A wall display beneath the heading of the Classroom Bank presented an enticing sample of real currency in order to make clear the nexus between cash rewards and writing proper sentences.

As I chatted with the principal, I asked her whether there was a reason those two words “management” and “manager” kept popping up throughout the school. “We want every child to be working as a manager while he or she is in this school,” the principal explained. “We want to make them understand that, in this country, companies will give you opportunities to work, to prove yourself, no matter what you’ve done.”

I wasn’t sure of what she meant by “no matter what you’ve done” and asked her to explain. “Even if you have a felony arrest,” she said, “we want you to understand that you can be a manager someday.”

Students as Workers

“We must start thinking of students as workers,” said a high-ranking official of one of the nation’s teachers unions at a forum convened by Fortune magazine in 1988. Is this really what it all comes down to? Is future productivity to be the primary purpose of the education we provide our children? Is this to be the way in which we will decide whether teachers are complying with their obligations to their students and society?

Admittedly, the economic needs of a society are bound to be reflected to some rational degree within the policies and purposes of public schools. But even so, most of us are inclined to believe there must be something more to life as it is lived by 6-year-olds or 10-year-olds or by teen-agers for that matter than concerns about successful global competition. Childhood is not merely basic training for utilitarian adulthood. It should have some claims upon our mercy, not for its future value to the economic interests of competitive societies, but for its present value as a perishable piece of life itself.

Few people who are not involved with inner-city schools have any idea of the extremes to which the mercantile distortion of the purposes and character of education have been taken or how unabashedly proponents of these practices are willing to defend them. For instance, the head of a Chicago school who was criticized for emphasizing rote instruction, which, his critics said, was turning children into robots, found no reason to dispute the charge. “Did you ever stop to think that these robots will never burglarize your home and will never snatch your pocketbooks? He asked, “These robots are going to be producing taxes.”

In November 1999, the Institute of Medicine released a report entitled To Err Is Human: Building a Safer Health System,1 which found that each year, between 44,000 and 98,000 people in the United States die as a result of preventable, hospital-based medical errors. The report generated ripples of concern throughout the American public, and caused many organizations, both private and public, to focus their attention on ways to improve the quality of health care in the U.S.

Since the release of To Err Is Human, dozens of surveys of the landscape of American health care have been conducted, with sometimes surprising - and frightening - results. One survey, conducted by the Kaiser Family Foundation, the Agency for Healthcare Research and Quality, and the Harvard School of Public Health and published in November 2004,2 reviewed the status of the average American’s perceptions about the quality of health care, along with their experiences with their health care providers and the quality of health-related information they receive. The survey shows that despite the efforts of hospitals, doctors, health plans and insurance companies to reduce medical errors and improve the quality of ‘ care, more than half of all American adults are dissatisfied with the current quality of health care provided in the U.S. In addition, a significant percentage believe that the quality of health care in the United States has actually gotten worse, not better, in the 5 years since To Err Is Human was published.

The survey was performed between July 2004 and September 2004, and conducted by telephone to a random sample of 2,012 adults across the United States. The respondents were asked a series of questions about their perception of the quality of health care; their awareness (and use) of quality information in making choices about health care; and previous experiences with health care providers. They were also read a common definition of “medical errors,” and asked about their knowledge of (and any personal experience with) medical errors.

Overall Perceptions

In terms of consumers’ overall perceptions about their medical care, an analysis of the responses showed downward trends in satisfaction and quality of care. According to the survey:

* Over half (55%) of the public stated that they are currently dissatisfied with the quality of health care in this country, compared to 44% who reported the same in 2000. Conversely, about four in ten (41%) reported that they are satisfied with the quality of health care in this country, compared to 54% in 2000.

* Four in ten (40%) say the quality of health care has “gotten worse” in the past five years, compared to 17% who say it has “gotten better” and 38% who say it has “stayed about the same.”

* Nearly half (48%) of the adults surveyed say they are at least somewhat worried about the health care that they and their family receive, including 22% who say they are “very worried.”

With more than half of the public dissatisfied with the quality of their health care and 40% believing that it has “gotten worse,” it is no wonder why almost half of all adults are at least somewhat worried about their health care. It is clear that the confidence barometer is falling.

Personal Experience With Medical Errors

More and more people (43%) have become familiar with the term “medical errors.” The number of people familiar with the term is not that far ahead of those who have been involved in medical errors through personal experience, or that of a loved one. In fact, according to the survey, having knowledge of, or personally experiencing, a medical error has almost become a fact of life as far as medical care is concerned:

* Thirty-four percent of the public say that they have been involved in a situation where a preventable medical error was made in their care or the care of a family member. This includes 21% who say that the medical error they were involved with most recently had serious health consequences, including severe pain (16%); serious loss of time at work, school, or other important life activities (16%); temporary disability (12%); long-term disability (11%); and/or death (8%).

* Among those who say they or a family member has experienced a medical error, nearly three in four (72%) say the doctor involved has “a lot of responsibility” for the error.

* Among those who say they or a family member has experienced a medical error, 11 % (or four percent of the total public) report they or their family member sued a health care professional for malpractice after experiencing the medical error.

* Of those who say the medical error they or their family member experienced had serious health consequences, 14% (or three percent of the total public) report they or their family member sued a health care professional for malpractice after experiencing the medical error.

* Several issues were indicated as being “very important” causes of medical errors. Seventy-four percent of those surveyed said that “overwork, stress or fatigue of health professionals” could cause a serious medical error, followed by doctors not having enough time with patients (70%), too few nurses (69%), health providers “not working together or not communicating as a team (68%), poor training (58%), the influence of HMOs and other managed care plans on treatment decisions (55%), and poor handwriting by health care providers (52%).

Natural rubber latex allergy is recognized as an important public health issue and continues to be addressed in both the public and private sectors through rule making, educational efforts, and research. (1) Coincident with the increased recognition of glove reactions in the late 1980s and clinical natural rubber latex allergy in the early 1990s, the US Food and Drug Administration (FDA) began to receive reports describing various health effects, such as contact dermatitis and allergic reactions, that were associated by the reporters with the use of medical gloves. (2) The term medical glove, from the FDA’s regulatory perspective, refers to a wide variety of glove products with specific barrier claims that are labeled and marketed for medical use as either surgeon’s gloves or patient examination gloves. (3) Currently, medical gloves are required to receive FDA premarket clearance under section 510(k) of the Food, Drug, and Cosmetic Act before they can be marketed legally in the United States. They also are subject to mandatory reporting requirements outlined under the FDA’s Medical Device Reporting (MDR) regulations. (4) Gloves that are not labeled for medical use, such as cleaning gloves, painter’s gloves, and hobby gloves, are not covered under the FDA’s jurisdiction. The FDA’s reporting system does not capture problems directly associated with the use of consumer glove products. The aim of this study was to provide a descriptive analysis and summary of health effects reported to the FDA in association with the use of medical gloves made from either natural rubber latex formulations or synthetic materials.

THE FDA’S REPORTING SYSTEM

Since 1973, the FDA has maintained a nationwide voluntary reporting program for adverse events associated with medical devices. Currently administered as part of the FDA’s MedWatch program, the program accepts information voluntarily submitted to the FDA by health care providers and consumers. Beginning in 1984, the FDA’s MDR regulations require device manufacturers and importers to submit reports to the FDA concerning medical device-related deaths, serious injuries, and device malfunctions. Since 1991, facilities that use medical devices also have been required to report device-related deaths and serious injuries to either the manufacturer or the FDA. Facilities that use medical devices subject to mandatory reporting include hospitals, nursing homes, outpatient diagnostic and treatment facilities, ambulatory surgery centers, ambulance services, and home health care service providers. Private offices of physicians, dentists, or other health care professionals are exempt from the FDA’s mandatory reporting requirements, but practitioners can report problems voluntarily to the FDA. From 1990 to 1996, medical device distributors also were required to report certain types of events. Both the mandatory and voluntary reporting systems continue to capture information about medical device-related adverse events, and the FDA’s adverse event databases currently contain more than one million reports. The FDA uses the information reported through these programs to assist in the early identification and characterization of emerging medical device problems and related public health issues.

METHODS

The FDA’s medical device adverse event databases were searched via computer using text search criteria (eg, red, rash, allergic, anaphylaxis, asthma, wheezing, reaction, swollen, swell, itch, passed out) developed to identify reports describing local or systemic reactions associated with the use of any type of medical glove. The search covered information submitted from the inception of the database in 1973 through March 31, 1999. Duplicate reports describing the same event were identified and merged into a single adverse event report, yielding a total of 2,639 candidate reports. A secondary manual review of the candidate reports resulted in the identification of a subset of 2,396 unique reports of glove-associated reactions that served as the subject of the study.

Certain prescribed information (eg, patient age, gender, location of event) must be included in mandatory adverse event reports submitted to the FDA unless it cannot be obtained by the reporter. Since 1993, voluntary reporters have been asked to supply basic data elements as part of a standard adverse event report format developed by the FDA, but voluntary reports are accepted regardless of whether the minimal requested information is provided by the reporter. Narrative information is requested for all adverse event reports; however, the FDA’s adverse event databases are not designed to capture and code detailed clinical information associated with an individual device-related event, and there are no specific content requirements for the narrative sections of the report form. When supplied, the quality of narrative information varies substantially between reports.

This study required the use of a secondary database and the development of a unique coding scheme that allowed for manual abstraction and organization of the coded narrative and information of interest. The coding system entailed the creation of dichotomous and nominal variables to represent the information of interest in the reports for entry into the secondary database. The computerized database was created with checks to assume the correct entry of values for the variables. The manual abstraction was intended to identify, categorize, and record demographic and clinical information contained in the selected reports, particularly when such information was provided exclusively in the narrative sections of a report. Clinical information included symptoms, physical findings, or diagnostic terms that were reported in association with a specific glove reaction. This information then was used to assign each report to one or more of the following clinical response categories:

Having the same last name as the company you work for may be seen as a blessing by some, but brothers J. Mario Molina, M.D., and John Molina, J.D., now that it can also be a curse.

As President and CEO of Molina Healthcare, Dr. J. Mario Molina, son of Dr. C. David Molina, the founder of the company, admits that “the biggest negative is that sometimes because it is a family business people don’t take you as seriously.”

John Molina, the company’s Executive Vice President of Financial Affairs and Chief Financial Officer, agrees: “I remember during our time when we were trying to get people to invest in the company, despite the fact that we had a 23-year track record, people always questioned if we had staying power.”

As one of the leading and fastest-growing publicly-traded managed health care companies, Molina Healthcare, Inc. (NYSE: MOH) projects annual revenues of $1.6 billion for this year. Their presence in Southern California has been steadily growing for 20 years, beginning with their three healthcare clinics in the South Bay area of Los Angeles (one was in Wilmington and two in Long Beach, which is also where their current headquarter base is). Within the past few years, the company has grown astronomically; they now serve 800,000 members nationwide and have 21 care clinics in California. Molina Healthcare, Inc. also now has health plans available in Utah, Michigan, Washington and New Mexico. (At the time of this interview the company was in the process of obtaining their HMO license in Indiana.)

As the company was expanding, the Molina brothers contemplated changing the name of their business because they felt that the name would not mean anything to patients outside of Los Angeles.

“We decided we wanted the name Molina Healthcare out there because we wanted people to know that we really stand behind the company,” says J. Mario Molina, adding with a chuckle, “It’s funny, sometimes people will say, ‘Oh, there really is a Dr. Molina?’”

C. David Molina is the patriarch behind one of todays most successful Hispanic-owned companies. Twenty years ago, he envisioned starting a medical practice to specifically treat the neediest of all: low-income patients.

“He was working in the emergency room and seeing people who did not have a regular doctor that they could go to often because they were Medicaid patients,” J. Mario Molina recalls.

His idea was not an instant success; he constantly received negative feedback and criticism from medical colleagues. In fact, he had to overcome the initial obstacle of finding specialty physicians who would accept referrals for his Medicaid patients.

John Molina says, “Doctors were reluctant to deal with Medicaid patients because of low reimbursement rates and because of the paperwork involved. And back in the early days, there was a misconception that the Medicaid population was seen as more litigious than the average population.”

Nevertheless, Molina Senior pressed on, even to the point of mortgaging the home which housed his wife and five children when he needed capital for the fledging business.

“He felt there was a need to provide care to people who were low-income, who were getting their healthcare paid through government programs like Medicaid, and who just didn’t have access to a family doctor or pediatrician,” J. Mario Molina says.

According to their website (www.molinahealthcare.com), Molina Healthcare, Inc. is “among the most experienced managed healthcare compares serving patients who have traditionally faced barriers to quality healthcare–including individuals covered under Medicaid, the Healthy Families Program, the State Children’s Health Insurance Program (SCHIP) and other government-sponsored health insurance programs.”

To put the concept of managed healthcare in simple terms, Molina Healthcare, Inc. essentially receives a fixed amount per month to provide or arrange for all of a patient’s healthcare needs.

Says Dr. Joseph Molina: “A lot of times people don’t know where to go or what to do, they have difficulty, finding specialists when they need specialty care. They don’t have someone they can call in the middle of the night when they have a problem. Our job is to try and coordinate the whole healthcare system so they get what they need, including preventive healthcare services, in a timely manner and [that they] don’t get lost in the system.”

Caring for Low-Income Patients

Another important reason for starting Molina Healthcare was to provide low-income families with direct medical access.

“My father wanted to have doctors that patients could go to in their own neighborhoods not build a huge medical center and expect people to drive twenty or thirty miles for care,” John Molina says.

His brother adds: “We’ve always taken that approach. We’ve tried to have doctors that are either employees or that are contracted with us close to the patient.”

The aim of this paper is to examine possible determinants of the prevalence of private medical insurance (PMI) in England. The entire British public has access to free care in the National Health Service (NHS) financed by general taxation and national insurance paid by all employed United Kingdom (U.K.) residents. There is no option for U.K. residents to opt out of contributing to the NHS, and NHS coverage is comprehensive. Thus, PMI is supplementary, typically purchased to guarantee faster access to health care (particularly specialists) and in some cases, better amenities in health care facilities. In the United Kingdom, PMI covers treatment for curable, short-term illness or injury. PMI does not cover general practitioner (GP) services, chronic conditions, or conditions an individual had prior to taking out insurance. At the end of year 2000, 6.88 million people in the U.K. (approximately 11.5 percent of the population) were covered by PMI and the value of the PMI market was estimated at 2.45 billion [pounds sterling] (Laing and Buisson 2001), 5.1 percent of the estimated year 2000/2001 NHS expenditure of 48 billion [pounds sterling].

Since 1988, Laing and Buisson, an independent specialist consultancy in health and community care, have reviewed the U.K. PMI market. The number of subscribers covered through an employer-paid plan has increased by approximately 23 percent since 1990, while during the same period, the number of subscribers who were either paying individually or as employees (as partial payment of a company plan) declined by about 6 percent (Laing and Buisson 2001). At the end of 2000, 66.5 percent of PMI subscribers were in plans fully paid for by their employer (Laing and Buisson 2001).

Tax policies introduced between 1979 and 1997 encouraged both employer-paid and individual PMI subscription. Employers did not pay employers’ National Insurance contributions on PMI provided to employees as a benefit-in-kind. (1) And in 1990, tax relief on the total premium cost, at the marginal tax rate, was provided to holders of individual PMI over age 60 years.

Some of these incentives were weakened in 1997. Tax relief for individual PMI premiums paid by those over the age of 60 years was discontinued (Laing and Buisson 2000b) and the Insurance Premium Tax on all PMI policies (in effect, a sales tax on PMI purchase) was increased to 5 percent from 4 percent (introduced in October 1994 at an initial rate of 2.5 percent [HM Customs and Excise 2001]). Also, in April 2000 the government extended employer-paid national insurance contributions (2) to cover PMI benefits in kind (Laing and Buisson 2000b). Evidence exists to suggest that incentives intended to increase PMI prevalence were expensive, and largely unsuccessful in stimulating demand (Emmerson, Frayne, and Goodman 2001). Furthermore, the elimination of tax relief for those over age 60 years increased premiums for individual subscribers in this age group by 29.9 percent (Emmerson, Frayne, and Goodman 2001).

The future trend of PMI prevalence may be influenced by two factors: substantial increases in premiums on individual PMI policies (over the calendar year 1999 they were estimated to have increased by over 15 percent or five times the rate of inflation in 1999 [Laing and Buisson 2001; U.K. National Statistics 2001] and the current government’s significant increase in funding to the NHS, pledging to increase real NHS spending by 7.3 percent in each year until 2007 [HM Treasury 2002]).

Data from the British Household Panel Survey (BHPS) 1997-2000, the U.K. Department of Health and Laing’s Healthcare Market Review 1999-2000, are used in this analysis. The panel nature of the survey allows a national, representative sample of households to be followed over the years for which data on PMI subscription are available. The BHPS has not previously been used to examine determinants of PMI prevalence. Previous analysis utilized cross-sectional data that do not well reflect the dynamic nature of the PMI market. Insurance status, PMI policy changes, individual circumstances and waiting lists are all subject to change over time. Our analysis also incorporates data from other sources. We include data on inpatient and outpatient waiting times estimated at the health authority (HA) and regional level (provided by the NHS Waiting Times Team), as well as data on the number of private acute care beds, at the regional level (Laing and Buisson 2000a), and estimates of the regional distribution of physicians working in the private health care sector (DH 2001). The results provide new evidence as to what factors determine the size of the PMI market in England.

MODELLING THE DECISION TO PURCHASE PMI

Several factors impact on the decision to purchase PMI. These include the perceived magnitude of a potential loss because of illness, relative to income and an individual’s degree of risk aversion (Cutler and Zeckhauser 2000; Santerre and Neun 2000). Choice and convenience, as offered by a private health care alternative, are also benefits sought by PMI subscribers (Bosanquet and Pollard 1997; Barr 1998). In some cases quality of care available through private insurance, relative to that available through an NHS system, may also be an incentive (Besley, Hall, and Preston 1999).

The Career History Archival Medical and Personnel System is a database that provides information on cancer, chronic diseases, occupational and preventive medicine, epidemiological research, and the use of health care in the Navy and Marine Corps. It was created at the Naval Health Research Center for enlisted Navy personnel, and it is being expanded to encompass all military personnel. Its objective is to provide a comprehensive, chronologically ordered database of career and medical events in all active duty military service members and to track career and disease events in order from the date of entry to service to the date service ended. Events include the dates of beginning and ending of each specific military occupation, all assignments to a military units or ships, all hospitalized diseases, and other events. The database contains detailed epidemiological data on more than six million members of the military services. It is the largest known epidemiological database in the United States.

This article describes the design and uses of the Career History Archival Medical and Personnel System (CHAMPS), a comprehensive database of career and medical information on all individuals who have served on active duty in the Navy and Marine Corps, and, in more recent years, all Department of Defense (DoD) services.1 The database covers the period from January 1, 1965 to the present for enlisted Navy service members. For all other services, medical events and denominator data are available from 1988 to the present. This report describes use of the database for epidemiological research on health and performance in the military.

CHAMPS was developed and is maintained by the Naval Health Research Center (NHRC) in San Diego, California. The CHAMPS system compiles highly detailed career and medical histories on individuals in the military from a variety of sources. Records are arranged for each individual as events in chronological order, and a set of event records for an individual provides a logical and comprehensive history from his/her time of enlistment to his/her time of ending service. Each event record contains variables that reflect the type and date of the event and the member’s status at the time of the event. There are two categories of event records: career and medical.

Career data for Navy and Marine Corps service members were compiled from Bureau of Naval Personnel and Marine Corps Headquarters electronic files. Medical records for enlisted Navy members were compiled from hospitalization records from military hospitals, medical board findings, physical evaluation board findings, and death records. All data were edited for accuracy and consistency before being entered into CHAMPS. All social security numbers (SSNs) were verified, and numbers that could not be verified were corrected, using name and birth date as alternate identifiers. All changes in content or coding were documented in a cumulative electronic documentation file. As new files for the Army, Air Force, and Coast Guard are made available, they are being integrated into CHAMPS. CHAMPS tracks cross-service changes, such as from Navy to Air Force, and changes from enlisted to officer status.

The first event in CHAMPS histories is the accession event record for the individual. Variables in the accession event record include term (length) of enlistment, whether the member is on regular or reserve status, pay grade or rank, primary and secondary military occupations, education, age, type of enlistment, and branch and component where the member served in the past, if the individual had previous military service. The career data in the accession event record provide a comprehensive description of the characteristics of the incoming recruit. The career data include data obtained from recruits during their health and mental status examinations during military entry processing at Military Entry Processing Stations throughout the United States. Subsequent records describe events in the individual’s career as they occur.

Event records are created for changes in occupation, duty station, pay grade, name, SSN, unauthorized absences, desertions, and discharges. The values for commonly used variables, such as age, pay grade, occupation, duty station, marital status, dependents, and length of service, are current for the event date. The most important variables recorded as events are primary occupation (rate); secondary occupation; duty station activity (type of ship or duty station); home port or base zip code; name and previous names if any; SSN, previous SSNs, and current verified SSN; date of loss from military service; and DoD manpower separation code.

Another series of event records describe all hospitalizations and certain other medical events. Variables in the hospitalization record include all discharge diagnoses (up to eight per hospitalization), number of diagnoses (from 1 to 8), dates admitted and discharged, number of days hospitalized, type of release, military theater of operation, pay grade, occupational specialty, and cause, when the hospitalization is a result of an accident, poisoning, or violence. Other medical records are also included when available, such as results of medical and physical evaluation boards, death, human immunodeficiency virus (HIV) testing and serological status, existence of a condition before enlistment, and identification of the hospital. Data elements that vary over time, such as age, pay grade, and occupation, are obtained from personnel records because demographic and current status data contained in medical records are often inaccurate. Age at event, for example, is computed by subtracting the birth date from the date of the event.

Essential medical education, Teachers training, G.N. Prabhakara (Mehta Publishers, New Delhi). 2003. pages: 334. Price Rs.325/-ISBN 81-88039-17-9

At first sight, the book appears quite impressive in its size and coverage. Several areas of Educational Science and Technology, both old and new, have been included. Materials from several sources have been complied. Had the sources been properly cited, the value of the book could have been much more. The sections on Management, Principles and Technique are vast in scope but written in a sketchy manner. The section on microteaching is written in detail.

Since the aim is to cater to educators of various health sciences, it is important to highlight the deficiencies of the book, which need to be corrected in later editions. In the current era of knowledge explosion and scientific advances, it is difficult for a single author to do justice to such vast areas as covered in this book. The manuscript could have done well with professional help from an English language consultant and also subject experts from different medical disciplines as well as educational science. This book, though extensive in its coverage, is found to be full of errors. Some of the prominent errors in this book are as follows:

The word AIDS has been wrongly expanded as ‘Auto Immune Deficiency Syndrome (page vi). QRS is not “An ECG reading” but a “Component of ECG record” (page vii). In chapter 1, “Affective Domain” is not an adjective as mentioned; it is a term and therefore a noun. The explanations for cybernetics and group discussions are partly wrong and need correction. ‘Halo effect’ and Objective” have been explained in a confusing manner in chapter 1, though in other sections, these are correctly described. A non-expert and even a computer can do Item Analysis; but the book says otherwise. The terms validity and accuracy are mixed up and the definition of workshop is vague. In chapter 3, the essence of ethics is lost. This chapter could have been made cohesive by competent editing and erudite write-up. On page 79, humane has become human and career has been spelt as carrier”. In section 3.3 on Pedagogy (page 24), Table 2, listing the distinction between lecturing and teaching is totally misleading and needs to be deleted. The concept attainment model has been ignored and the diagram 3 on page 27 needs correction. The diagram 7 on page 37 on P.G. Research in also incorrect.

Section 3.7 on ROME Programme 1977 is written in great detail and is laudatory. However, the reasons for its failure are left out. Table 7 on Total Quality Management TQM in Health Care is wrongly put up as (TQM) in Medical Education. section 3.15, Evidence Based Medicine is one of the ongoing revolutions in medical practice and not confined to medical education. It is discussed very superficially. Table 9 on page 75 is erroneous on differences between educational and training institution. (Training focuses mainly on skills whereas the education is holistic and includes inculcation value system that is relevant to learners). Figure 3 1 on page 76 in ‘Educational spiral’ shows teaching and learning in diametrically opposite positions. Teaching and learning should go hand in hand.

Some examples of objectives on page 78 are wrongly classified. For example, “conduct of normal delivery” is said to be a specific objective; but “ECG reading” is said to be a departmental objective. Such misclassified examples are bound to confuse the readers. Another example in Table 12, ‘to develop clinical skills and logical reasoning’ is, according to author, relevant only for tertiary care. However, it is equalK important for primary and intermediate health care. Tables 10, 11 and 12 need to be reconstructed after eliminating several such errors that have crept in. Examples on problem based and topic based modules on page 94 overlap and are confusing. Table 20 differentiating between curriculum and syllabus is misleading and needs deletion or re-writing. The Model Eesson Plan on page 127 is planned for 60 minutes but planned activities total for 70 minutes. Fig. 51 on page 147, labelled as’Dale’s cone of experience’ is wrong. In the section of Simulated Patient Management Problem (SPMP) on pages 160 and 161, the author has written a set of hypothetical scores and attempted to calculate various indices. These are full of mistakes and will mislead the readers. In section 7.5. problem based learning and problem solving exercises are mixed up. It is essential to differentiate between these two. The case study for problem solving exercises is quite detailed and may be useful for teachers of community medicine. Chapter 8 on Teaching-Learning (T-L) methods lists obsolete methods like ‘teaching slide programme’ under new methods. The chapter also lists microteaching as a T-L method which is not correct. The “Bowing effect” of learner attention in class room is described well on page 1 80 but has not been taken into account for the model lesson plan on page 126. The model plan includes no activity to arouse learner’s attention in mid lecture. Under Section 8.4, computer-assisted learning is full of outdated facts and statements. This section needs to be re-written based on rapid developments in the field. section 9 on T-L Media is quite detailed. However, epidiascope is repeatedly misspelt as epedeoscope. Table 48 on page 227 on Advantages and Disadvantages of Laptop is full of errors and needs professional help for corrections. No web link has been cited in the whole book. There are excellent internet sites, which offer learning resource materials of great value in all aspects of medical education. These Internet links could have been very useful. Section 11 on Education-Evaluation is written in some detail. It needs editing to correct some mistakes like the upside down ECG printed in page 268.

Clinical Quiz questions are based on selected articles in this issue. Answers appear in this issue.

American Family Physician has been approved by the American Academy of Family Physicians as having educational content acceptable for Prescribed credit hours. Term of approval covers issues published within one year from the beginning distribution date of July 2002. This issue has been reviewed and is acceptable for up to 3 Prescribed credit hours. One half hour of these credit hours conforms AAFP criteria for evidence-based CME clinical content. Credit may be claimed for one year from the date of this issue. When reporting CME credit hours, AAFP members should report total Prescribed credit hours earned for this activity. It is not necessary for members to label credit hours as evidence-based CME Prescribed for CME reporting purposes.

The American Academy of Family Physicians is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

The AAFP designates this educational activity for a maximum of 3 hours in Category 1 credit toward the American Medical Association Physician’s Recognition Award. Each physician should claim only those hours of credit that he or she actually spent in the educational activity.

AAFP Credit

Each copy of AFP contains a Clinical Quiz answer card. AAFP members may use this card to obtain the designated number of Prescribed credit hours for the year in which the card is postmarked.

AMA/PRA Category 1 Credit

AAFP members who satisfy the Academy’s continuing medical education requirements are automatically eligible for the AMA/PRA.

Physicians who are not members of the AAFP are eligible to receive the designated number of credit hours in Category 1 of the AMA/PRA on completion and return of the Clinical Quiz answer card. AFP keeps a record of AMA/PRA Category 1 credit hours for nonmember physicians. This record will be provided on request; however, nonmembers are responsible for reporting their own Category 1 CME credits when applying for the AMA/PRA or other certificates or credentials.

For health care professionals who are not physicians and are AFP subscribers, a record of CME credit is kept by AAFP and will be provided to you on written request. You are responsible for reporting CME hours to your professional organization.

NOTE: The full text of AFP is available online (www.aafp.org/afp), including each issue’s Clinical Quiz. The table of contents for each online issue will link you to the Clinical Quiz. Just follow the online directions to take the quiz and, if you’re an AAFP member, you can submit your answers for CME credit.

INSTRUCTIONS

(1) Read each article, answer all questions on the quiz pages and transfer your answers to the Clinical Quiz answer card (bound into your copy of AFP). This will help you avoid errors and permit you to check your answers against the correct answers.

(2) Mail the Clinical Quiz answer card within one year (by July 31, 2003). The bar code on the answer card contains your identification for CME credit hours.

Before beginning the test, please note:

Each Clinical Quiz includes two types of questions: Type A and Type X.

Type A questions have only one correct answer and may have four or five choices. Here is a typical Type A question:

Q1. Most allergic reactions to foods are:

[ ] A. Due to IgA deficiency.
[ ] B. Due to IgG and IgM antibodies.
[check] C. IgE-mediated.
[ ] D. Due to enzyme deficiencies.
[ ] E. Due to toxins.

Type X questions may have one or more correct answers. They are multiple true-false questions with four options. Here is a typical Type X question:

Q2. Causes of varicosities in pregnancy
include:

[check] A. Hormonal changes.
[check] B. Venous compression.
[check] C. Familial tendency.
[check] D. Prolonged sitting and standing.

Clinical Quiz questions are written by the associate and assistant editors of AFP.

Context.-It is important that the total long-term precision of laboratory methods meet the medical needs of the patients being served.

Objectives.-To determine the long-term within- and between-laboratory variation of cortisol, ferritin, thyroxine, free thyroxine, and thyroid-stimulating hormone measurements using commonly available methods and to determine if these variations are within accepted medical needs.

Design.-Two vials of pooled frozen serum were mailed 6 months apart to laboratories participating in 2 separate College of American Pathologists surveys. The data from those laboratories that analyzed an analyte in both surveys were used to determine for each method the total variance and the within- and between-laboratory components.

Setting.-The study included the A mailing of the 2003 College of American Pathologists Ligand Survey and the C mailing of the Chemistry Survey.

Main Outcome Measures.-For each analyte, total variance was partitioned into within- and between-laboratory components for each analytic method. The within-laboratory variations were then compared with imprecision criteria based on biological variation.

Participants.-The laboratories that reported results on the same analyte using the same method in both surveys.

Results.-For each analyte, the median of the long-term within-laboratory variances of each peer group was 78% to 95% of its total-survey variance, and the median long-term within-laboratory coefficients of variation varied from 5.1 % to 7.6%. The number of methods that met within-laboratory imprecision goals based on biological criteria were 5 of 5 for cortisol; 5 of 7 for ferritin; 0 of 7 for thyroxine and free thyroxine; and 8 of 8 for thyroid-stimulating hormone.

Conclusions.-For all analytes tested, the total within-laboratory component of variance was the major source of variability in this study. In addition, there are several methods, especially for thyroxine and free thyroxine, that may not meet analytic goals in terms of their imprecision.

(Arch Pathol Lab Med. 2005;129:318-322)

Since 1974, College of American Pathologists (CAP) surveys have been utilized to study the sources of variation of clinical laboratory tests. Several of these studies1-4 have reported long-term variability using different types of replicate proficiency testing material sent out several months apart. Unfortunately, it was not known if proficiency testing materials accurately reflected clinical material with respect to long-term imprecision.

In 1994, CAP implemented a fresh frozen sera study hoping to better understand methodologic biases and matrix effects.5 In that study, a pool of sera was frozen in aliquots, which were mailed as part of the Chemistry Survey. In 2003, a similar study was done to examine both common chemistry and endocrine analytes. Because 1 aliquot of the same frozen serum pool was mailed in both the Chemistry and Ligand surveys, there were replicate samples sent during a period of 6 months to many laboratories. This provided an opportunity to examine the total (long-term) within-laboratory precision of the common methods for several tests using material that represents real patient samples. Although several CAP studies1-4 have examined the within-laboratory and between-laboratory variability components of the total variance, none had used the fresh serum specimen. The purpose of this study was to determine the long-term within-laboratory variation of cortisol, ferritin, thyroxine, free thyroxine, and thyroid-stimulating hormone measurements using fresh frozen serum replicate samples for commonly available methods and to determine if these variations are within accepted medical needs.

MATERIALS AND METHODS

Samples and Study Design

The preparation and the chemical characteristics of the fresh frozen serum samples have been described previously.6 In the A mailing of the 2003 CAP Ligand Survey, an aliquot of the fresh frozen serum pool was sent as 1 of the 5 challenges. Approximately 6 months later, an aliquot of the same fresh frozen serum pool was included in the C mailing of the 2003 Chemistry Survey. Both samples were analyzed by the survey participants in the manner prescribed by the Clinical Laboratory Improvement Amendments of 1988.7

Data

The results obtained for the fresh frozen serum samples were analyzed and reported back to the participants in the manner typical of the respective surveys. The data were then re-analyzed in a manner similar to a previous study involving therapeutic drugs.1 That is, the data were run through a 2-pass, 3-SD screening program to remove outliers. Only those laboratories participating in both surveys using the same analytic method were included. In addition, those data from methods not specified or from methods with fewer than 20 participants were not included, because these data tended to produce unreliable variance distributions. The analytic methods studied are listed in Table 1.

RESULTS

Tables 2 and 3 show the summary of the study results. For each analyte, the median total within-laboratory variance ranged from 78.4% to 95.2% of the total-survey variance. The lowest percentage of within-laboratory variance for any individual method was 64.1% (ferritin). In addition, the least precise method for an analyte typically had within-laboratory and total-survey coefficients of variation that were approximately 2 to 3.5 times that of the most precise method.

Medicalization and commodification of the body through technology in the form of Viagra and other erectile dysfunction drugs is reinforcing the cultural expectations that ageing men are required to age well to maintain youthful masculinity. Ageing well is explored as it relates the construction of masculinity, sexuality and ageing men’s bodies.

Key words: aging, masculinity, men, bodies, sexuality, cultural expectations

Old age is full of death and full of life. It is a tolerable
achievement and it is a disaster. It transcends desire and it
taunts it. It is long enough and far from long enough. Ronald
Blythe, 1979, p. 29

[The male organ has been a seen as many things over the course
of history], both noble and coarse. The penis was an icon of
creativity; it was the link between the human and the sacred,
an agent of bodily and spiritual ecstasy that hinted of communion
with the eternal. Yet it was also a weapon against women, children,
and weaker men. It was a force of nature, revered for its
potency, yet just as amoral. It tied man to the cosmic energy
that covered the fields each year with new herds and corps–and
just as often destroyed them. The organ’s “animal” urgency didn’t
trouble the ancients. Didn’t the gods combine the human and savage
in their own amours? All these complexities and contradictions,
the very unpredictability of life itself, were embodied by one
body part above all in antiquity–the penis.
David Friedman (2001)

Introduction

The demand that little boys give up their dependency for a masculinity based on dominance and performance continues to have many consequences for the aging man. Boys start the process of discounting nature and human connections and in the end their own humanity and sense of dignity in the face of aging and dependency. The construction of masculinity within the dominant American culture is based on independence and competition and central to this masculine construct is youthful energy and physicality. Masculinity requires not only success in the competitive world of work but sexual dominance and prowess for men to maintain their “youthful” masculine identity. Aging men are faced with not only the inevitable fact of aging but with the social constructs of what that means to them or should mean to them from a society that is oriented toward youth. The paradox for men is that even though “ageism” has been attacked and challenged, in reality it still exists and is deeply engrained in our youth oriented society. In its place has come the “aging well” or positive ageing agenda whereby society still derides those who do not “age well.” Men are now faced with aging that must have the air of youthfulness and vitality, and this includes sexual performance.

Viagra and the newer erectile dysfunction drugs are a part of this increasing expectation that has very quickly become a cultural phenomenon spread across the mass media. Viagra has entered into the mainstream of conversations and is a part of American culture. This paper explores the medicalization and commodification of men’s sexual functioning and its impact on aging men and their sense of masculinity.

A Culture of Aging Well

As in most life matters today, the meaning of what it is to “age” has been turned over to the professional, in this instance the geriatric social worker, urologist, gerontologists, geriatric medical specialists, and economic interests. Over the past century “old age was removed from its ambiguous place in life’s spiritual journey, rationalized, and redefined as a scientific problem” (Cole, 1992, p. xx.). Medicalization and commodification now provide the “scientific” management of aging. The concern produced is not only with understanding and controlling the aging process, but expectations that one must “age well” as if “aging” was merely a disembodied process that can be managed and kept at bay. The consequence of this scientific enterprise has been to find out how to treat illness and diseases that afflict the person as he ages and it has extended the life expectancy and produced better health for many. This rational approach has paralleled the critique of “ageism” which proclaims that chronological age does not determine the quality of one’s life. The assumption is that older people should be physically healthy and sexually active.

Both men and women are now presented with a culture that does not see growing old as a natural process, as part of the human condition, but a “problem” to overcome. There is a demand that men and women remain vibrant, healthy and functioning. When men or women show vulnerabilities or signs of aging, our social and personal constructs produce a level of contempt and hostility toward this physical and mental decline. In particular, contempt and hostility are directed at the physical consequence of aging in women (Susan Sontag, 1979). For men, the outer appearance of graying hair and lines can bring a “look of distinction” for a brief while. Men’s aging vulnerability is most often focused on his sexual performance, his penis. Weak or nonexistent erections are a “secret” fear for most men as they age. The new culture of “Aging Well” for men means that an aging penis should still perform well. Within the past several years since the advent of Viagra and Senator Dole promoting erectile dysfunction as acceptable for prime time television, an enormous cultural shift is taking place that supports and promotes this cultural and personal expectation that all penises, regardless of age, should maintain a youthful performance standard.