How do you measure beauty?
How to measure beauty The measurement starts from the forehead hairline to the spot between the eyes, then to bottom of the nose and from there to the bottom of the chin.
Why is skin analysis important when seeing clients?
Whether managing a clinical dermatology practice or a spa, proper skin analysis is vital when seeing clients, especially if they are new. Old-fashioned or insufficient analysis can involve skipping steps, guessing, “eyeballing” clients, or simply using the latest trends, even when not applicable.
What do surgical institutions use to measure quality of care?
Surgical institutions often use “operative mortality . . . complication rates, length of stay, readmission rates, patient satisfaction, functional health status, and other measures of health-related quality of life.” (6) Outcome measurement is considered the gold standard, as it assesses the value of the services provided.
How to do a skin analysis?
Proper skin analysis starts with a thorough intake procedure. New clients obviously need a full workup, while those who have not been to the clinic or spa in some time need updating akin to a new client. The chart for regular clients should be reviewed at the start of each appointment, and it should be asked of the client whether they have made any changes to the factors listed below. Of course, implicit is the idea that records for each client are meticulously maintained, so any professional stepping in can understand the client’s history, conditions, previous treatments, and ongoing concerns.
How to do an analytical facial?
Throughout the analytical process, the professional should approach the face methodically, first looking at the overall skin, then focusing on specific areas, making sure to work around the entire face and neck. Touching the skin is also important, to feel for elasticity and texture.
How is skin type determined?
Skin type is largely determined by how much oil the skin produces, which changes over time, particularly with age but also with environment, stress, diet, hormones, medical conditions, and medications. Clients can also have elements of both dry and oily skin, such as those with essentially oily skin but dry skin on the surface. Treating that type of dryness requires a different approach than managing a truly dry skin profile. This is a perfect example of why thorough skin analysis should be a precursor to any treatment.
What does hydration tell you?
This is a measure of the amount of free water in the epidermis. Hydration tells the professional about the client’s overall hydration throughout the body. It also indicates how effective the skin is functioning as a barrier system.
What is dry skin?
Dry skin is naturally lacking in oil throughout. Comedones are absent, and the surface will often be patchy, red, or irritated. Clients may complain their face feels “tight.” Usually, the skin’s proper pH is also off, which can be restored with the use of mild washing and toning products. Good moisturizers for day and night, preferably with a humectant component, are essential with dry skin to assist the skin in its barrier function and to improve its feel and appearance. Dry skin can also be tackled from within with improved hydration and nutrition, and the client’s environment should be controlled to the degree possible, as well (for example, harsh interior heating or a dry climate).
Why is my skin oily?
Genetics, stress, and hormones are all key factors in precipitating oily skin. The key with this type of skin is to control excess oil without stripping the skin. Treating surface bacteria may also be helpful. Moisturizers, sunscreens, and makeup should be oil-free.
How many elements of skin are there in an analysis?
There are four essential elements of the skin to measure when doing an analysis. It is key to understand these first before discussing the hands-on analytical process and instrumentation (see below).
Beauty and women
Beauty of the soul, we have always heard this saying, but when compared to reality, we find that formal beauty is the beauty of attention, as evidenced by the competitions to choose the beauty of an area, and beauty, whether the beauty of the soul or the body, femininity remains the standard.
Arab beauty standards
Beauty measures vary among Arabs compared to the West, and after studies conducted by Arabs to see the standards of beauty, it turned out that the most important measures of beauty for women:
Measures of beauty in the West
For the West, the scales are different, because of their different cultures. Their beauty is:
Why is clinical outcome measurement important?
But, ensure measurements cross constructs and domains. Don’t solely rely on patient reports. And, don’t claim effectiveness based on observation. We must acknowledge the complexity. No one is saying clinical outcomes measurement is not important, or is not illustrative of important concepts. Clinical data and outcomes are vital to self-reflection, integration of evidence, health services, and overall care processes. But, the plural of anecdote is not data, and outcome measures can not illustrate effectiveness. That’s not an argument to not measure outcomes. It’s an argument to improve measurement, and more importantly, understanding.
Why is multifactorial treatment so complicated?
The multi-factorial nature of treatment mechanisms, complicate the ability to clinically observe effectiveness. The myriad of reasons why individuals may report and/or exhibit improvements in symptoms, function, and other constructs make “outcomes” a dynamic and complicated subject. Perhaps the condition has a favorable natural history or regression to the mean is present. And, perhaps the patient would have progressed more quickly with a more effective treatment approach. It’s complicated. Don’t take all the credit, and don’t take all the blame. So, what should we do?
How does outcome management work?
Some outcome management systems do allow for determining effectiveness. If the system has enough data in it and the data is risk adjusted, the system can predict the outcome based on all the data in the system for similar patients. The prediction can be used to determine effectiveness – the patient either reaches the predicted outcome or does not. If the patient reaches the outcome, the episode of care was effective.
When we mistake outcomes for effectiveness, we risk assuming causation and subsequently treatment mechanism?
Care must be to taken to avoid leaps in logic regarding effectiveness and mechanism of action. A review of the evolution of understanding of manual therapy mechanisms illustrates how continued observation of positive clinical outcomes likely reinforced inaccurate interpretations based upon hypothetical anatomy and biomechanics devoid of true physiology and actual tissue mechanics. We now know much more.
Is reaching a predicted outcome effective?
Reaching a predicted clinical outcome, while positive, is not effectiveness. The quote, and manuscript it’s from, at the beginning of my post address this issue outright. The clinical outcome is a completely separate construct from the effectiveness (or efficacy) of the treatment. A clinical outcome in isolation, or even the routine attainment of a predicted outcome, can not illustrate effectiveness of an intervention itself. Usually, we assume that better clinical outcomes will be obtained by utilizing the most efficacious and effective interventions. But, the reverse is not necessarily true. Better clinical outcomes does not equate to effectiveness. And, of course, utilizing effective interventions does not guarantee a specific clinical outcome given the multitude of factors that may exhibit an effect. I think it’s much more complicated than it appears.
Do outcome measures work at individual level?
Thanks for your comment and contribution. I’d agree, outcome measures function at individual (n=1) level, and absolutely should be utilized to track outcomes and inform progress clinically. We likely can’t manage what we don’t measure. And, obviously outcomes are improved when the best available interventions and care processes are implemented. We should be striving to implement the most evidence based interventions and approaches with the best researched efficacy and subsequent effectiveness. I’m in no way suggesting that interventions lack effect. As you mention, that’s quite a lardaceous conclusion.
Do physical therapists need to use randomized control trials?
No. Quite the contrary. In addition, to selecting appropriate outcomes measurements, clinicians must integrate and understand appropriate current clinical, mechanistic, and basic science research. As science based practitioners, physical therapists are charged to select effective, plausible, safe, and efficient approaches to care that are focused on the individual patient. This is not an argument for the utilization of only specific outcome measurements and interventions with strong randomized control trial level evidence. Plausibility matters. The individual person matters. It’s complicated. And, it’s easy to fool ourselves. Richard Feynman suggests:
How to assure yourself that your measure has clear instructions?
Finally, the very best way to assure yourself that your measure has clear instructions, includes sufficient practice, and is an appropriate length is to test several people. (Family and friends often serve this purpose nicely). Observe them as they complete the task, time them, and ask them afterward to comment on how easy or difficult it was, whether the instructions were clear, and anything else you might be wondering about. Obviously, it is better to discover problems with a measure before beginning any large-scale data collection.
What to do instead of using an existing measure?
Creating Your Own Measure. Instead of using an existing measure, you might want to create your own. Perhaps there is no existing measure of the construct you are interested in or existing ones are too difficult or time-consuming to use.
How do people react to being measured?
Be aware also that people can react in a variety of ways to being measured that reduce the reliability and validity of the scores. Although some disagreeable participants might intentionally respond in ways meant to disrupt a study, participant reactivity is more likely to take the opposite form. Agreeable participants might respond in ways they believe they are expected to. They might engage in socially desirable responding. For example, people with low self-esteem agree that they feel they are a person of worth not because they really feel this way but because they believe this is the socially appropriate response and do not want to look bad in the eyes of the researcher. Additionally, research studies can have built-in demand characteristics: subtle cues that reveal how the researcher expects participants to behave. For example, a participant whose attitude toward exercise is measured immediately after she is asked to read a passage about the dangers of heart disease might reasonably conclude that the passage was meant to improve her attitude. As a result, she might respond more favorably because she believes she is expected to by the researcher. Finally, your own expectations can bias participants’ behaviors in unintended ways.
Why is it important to have a brevity measure?
The need for brevity, however, needs to be weighed against the fact that it is nearly always better for a measure to include multiple items rather than a single item . There are two reasons for this. One is a matter of content validity. Multiple items are often required to cover a construct adequately.
What would you measure if you had only a vague idea?
If you had only a vague idea that you wanted to measure people’s “memory,” for example, you would have no way to choose whether you should have them remember a list of vocabulary words, a set of photographs, a newly learned skill, an experience from long ago, or have them remember to perform a task at a later time.
How many steps are there in measuring psychological constructs?
How should you proceed? Broadly speaking, there are four steps in the measurement process: (a) conceptually defining the construct, (b) operationally defining the construct, (c) implementing the measure, and (d) evaluating the measure. In this section, we will look at each of these steps in turn.
What is a good measurement?
Good measurement begins with a clear conceptual definition of the construct to be measured. This is accomplished both by clear and detailed thinking and by a review of the research literature.
What should be included in outcome measurement?
Patient Reported Wellbeing and Clinical Analysis: Both patient perceptions of wellbeing and clinical analysis of health should be included in outcome measurement. Monitoring and evaluation systems must be able to analyze both subjective, nuanced patient accounts, and scientific, standardized clinical measurements. (10)
What are structural measures?
Structural measures, or outputs, reflect characteristics of the health care delivery system—namely the hospital’s physical resources and staff organization. Procedure volume is the most common of these variables and is often used as a proxy for surgical quality, due the loose correlation between high procedure volume and improved long-term survival. Other common structural measures include the staff’s level of training, the organization of hospital personnel, and the availability of up-to-date technology and financial resources. The main advantage of using these metrics to assess an organization’s impact is that they can be measured inexpensively and relatively quickly using existing administrative data. The problem with this method is that these variables are “imperfect proxies for outcomes.” (4) Providing patients with surgery, staff and high-tech equipment does not necessarily mean that those outputs will always have the desired impact. As discussed in Outcomes Are Essential in Global Health, “when assessing the impact of an organization, it is critical to keep in mind that distribution does not equal value.” (5)
How does cataract surgery affect quality of life?
A study of vision-related quality of life in rural China tracked the impact of cataract surgery on patients’ visual acuity. The authors found that of 87 operated patients, 12% had postoperative visual acuity of 6/18 (equivalent to 20/60) or better in both eyes, and 24% had visual acuity worse than 6/60 (20/200, or legally blind). Of 116 operated eyes, 25% had visual acuity of 6/18 or better and 44.8% had worse than 6/60. This case clearly demonstrates the importance of going beyond structural and procedural measures to focus on surgical outcomes. Simply counting the number of surgeries performed—87 patients, 116 eyes—does not accurately portray the impact that this medical care had on patients, as nearly a quarter of the study’s subjects had poor outcomes. Equipped with these outcome measures, the researchers can work to improve patient care and ensure that future services have the desired impact on patients’ quality of life. (7)
What defines a successful surgery?
Operational Definitions: What defines a successful surgery? Establishing measurable standards is essential for quantifying outcomes. For emergency surgery, the operation is considered successful simply if the patient lives. However, defining a positive outcome for procedures that treat non-life-threatening conditions requires a bit more nuance. For example, what change in visual acuity score is required for cataract surgery to be considered helpful? What degree of closure is necessary for obstetric fistula repair to be successful?
What is surgical agar score?
The Surgical Apgar Score is a 10-point tally based on three parameters: the estimated intraoperative blood loss, the lowest heart rate, and the lowest mean arterial pressure. The score is designed to provide rapid feedback for clinical teams, and is predictive of morbidity and mortality, even after controlling for preoperative patient factors. A study evaluating the Surgical Apgar Score in eight countries found that a higher score was correlated with lower rates of complications. For example, those who scored 0-4 had complication rates of 32.9% and death rates of 7.9%, while those who scored a 10 (the best score) had complication rates of 3% and death rates of 0.5%. (27) This study corroborates the importance of measuring outcomes, and supports the Surgical Apgar Score as an accurate predictive measure for doing so.
What can organizations use data from a statistical analysis?
Publishing Results: Once data has been analyzed, organizations can use the results to report to patients, staff, donors, colleagues, governmental bodies, and other partners. Given the complexity of the statistics, it is important to plan the best way to present the data to each audience so that the information is both understandable and comprehensive. (12)
What is the most robust method of measuring impact?
Monitoring direct outcomes is by far the most robust method of measuring impact, as it measures not only the hospital’s distribution of care, but also the impact of that care on patients’ quality of life. Surgical institutions often use “operative mortality . . . complication rates, length of stay, readmission rates, patient satisfaction, functional health status, and other measures of health-related quality of life.” (6) Outcome measurement is considered the gold standard, as it assesses the value of the services provided.
