The activities offered are always contextualized with the content. That is, they deliver significant value to those who consume the material. In practice, this response is what he seeks when interacting with the content. As far as your brand is concerned, the idea is to generate engagement and proximity to access information authorized by the user. When offering the interaction content, there is also the request for some essential data, as it happens on a traditional landing page.
The most interesting thing is that an interactive assessment is useful in several segments, for audiences of different types and with very specific expectations. The rise of interactive assessment is because Content Marketing must always be interesting to the user.
Good content engages with greater ease, but it needs to deliver value to those on the other side of the computer — or smartphone. Below are a few points that will help you understand why interactive assessment has gradually become an indispensable tool.
It is not new that the web user wants to have more participation in the content they consume. Every interactive assessment aims at delivering some value to those who consume it. Therefore, you can use different strategies and approaches. The users know that, by interacting with the content and providing data, they will receive in return some information that will be relevant to their situation.
Such assemblies can confound sequence-based biological inference and, when deposited in public databases, may be included in downstream analyses by users unaware of underlying problems.
We present BlobToolKit, a software suite to aid researchers in identifying and isolating non-target data in draft and publicly available genome assemblies. At this same time, they may recruit or select controls from the population without the outcome of interest. One way to identify or recruit cases is through a surveillance system. In turn, investigators can select controls from the population covered by that system. This is an example of population-based controls. Investigators also may identify and select cases from a cohort study population and identify controls from outcome-free individuals in the same cohort study.
This is known as a nested case-control study. Were the same underlying criteria used for all of the groups involved? The investigators should have used the same selection criteria, except for study participants who had the disease or condition, which would be different for cases and controls by definition.
Therefore, the investigators use the same age or age range , gender, race, and other characteristics to select cases and controls. Information on this topic is usually found in a paper's section on the description of the study population. For this question, reviewers looked for descriptions of the validity of case and control definitions and processes or tools used to identify study participants as such.
Was a specific description of "case" and "control" provided? Is there a discussion of the validity of the case and control definitions and the processes or tools used to identify study participants as such? They determined if the tools or methods were accurate, reliable, and objective.
For example, cases might be identified as "adult patients admitted to a VA hospital from January 1, to December 31, , with an ICD-9 discharge diagnosis code of acute myocardial infarction and at least one of the two confirmatory findings in their medical records: at least 2mm of ST elevation changes in two or more ECG leads and an elevated troponin level.
All cases should be identified using the same methods. Unless the distinction between cases and controls is accurate and reliable, investigators cannot use study results to draw valid conclusions. When it is possible to identify the source population fairly explicitly e. When investigators used consecutive sampling, which is frequently done for cases in prospective studies, then study participants are not considered randomly selected.
In this case, the reviewers would answer "no" to Question 8. However, this would not be considered a fatal flaw. If investigators included all eligible cases and controls as study participants, then reviewers marked "NA" in the tool. If percent of cases were included e. If this cannot be determined, the appropriate response is "CD. A concurrent control is a control selected at the time another person became a case, usually on the same day.
This means that one or more controls are recruited or selected from the population without the outcome of interest at the time a case is diagnosed. Investigators can use this method in both prospective case-control studies and retrospective case-control studies. For example, in a retrospective study of adenocarcinoma of the colon using data from hospital records, if hospital records indicate that Person A was diagnosed with adenocarcinoma of the colon on June 22, , then investigators would select one or more controls from the population of patients without adenocarcinoma of the colon on that same day.
This assumes they conducted the study retrospectively, using data from hospital records. The investigators could have also conducted this study using patient records from a cohort study, in which case it would be a nested case-control study. Investigators can use concurrent controls in the presence or absence of matching and vice versa.
A study that uses matching does not necessarily mean that concurrent controls were used. Investigators first determine case or control status based on presence or absence of outcome of interest , and then assess exposure history of the case or control; therefore, reviewers ascertained that the exposure preceded the outcome. For example, if the investigators used tissue samples to determine exposure, did they collect them from patients prior to their diagnosis?
If hospital records were used, did investigators verify that the date a patient was exposed e. For an association between an exposure and an outcome to be considered causal, the exposure must have occurred prior to the outcome.
This is important, as it influences confidence in the reported exposures. Equally important is whether the exposures were assessed in the same manner within groups and between groups. This question pertains to bias resulting from exposure misclassification i. For example, a retrospective self-report of dietary salt intake is not as valid and reliable as prospectively using a standardized dietary log plus testing participants' urine for sodium content because participants' retrospective recall of dietary salt intake may be inaccurate and result in misclassification of exposure status.
Similarly, BP results from practices that use an established protocol for measuring BP would be considered more valid and reliable than results from practices that did not use standard protocols. A protocol may include using trained BP assessors, standardized equipment e. Blinding or masking means that outcome assessors did not know whether participants were exposed or unexposed. To answer this question, reviewers examined articles for evidence that the outcome assessor s was masked to the exposure status of the research participants.
An outcome assessor, for example, may examine medical records to determine the outcomes that occurred in the exposed and comparison groups. In this case, the outcome assessor would most likely not be blinded to exposure status. A reviewer would note such a finding in the comments section of the assessment tool. One way to ensure good blinding of exposure assessment is to have a separate committee, whose members have no information about the study participants' status as cases or controls, review research participants' records.
To help answer the question above, reviewers determined if it was likely that the outcome assessor knew whether the study participant was a case or control. If it was unlikely, then the reviewers marked "no" to Question Outcome assessors who used medical records to assess exposure should not have been directly involved in the study participants' care, since they probably would have known about their patients' conditions. If blinding was not possible, which sometimes happens, the reviewers marked "NA" in the assessment tool and explained the potential for bias.
Investigators often use logistic regression or other regression methods to account for the influence of variables not of interest. This is a key issue in case-controlled studies; statistical analyses need to control for potential confounders, in contrast to RCTs in which the randomization process controls for potential confounders. In the analysis, investigators need to control for all key factors that may be associated with both the exposure of interest and the outcome and are not of interest to the research question.
A study of the relationship between smoking and CVD events illustrates this point. Such a study needs to control for age, gender, and body weight; all are associated with smoking and CVD events.
Well-done case-control studies control for multiple potential confounders. Matching is a technique used to improve study efficiency and control for known confounders. For example, in the study of smoking and CVD events, an investigator might identify cases that have had a heart attack or stroke and then select controls of similar age, gender, and body weight to the cases.
For case-control studies, it is important that if matching was performed during the selection or recruitment process, the variables used as matching criteria e. NHLBI designed the questions in the assessment tool to help reviewers focus on the key concepts for evaluating a study's internal validity, not to use as a list from which to add up items to judge a study's quality.
Internal validity for case-control studies is the extent to which the associations between disease and exposure reported in the study can truly be attributed to the exposure being evaluated rather than to flaws in the design or conduct of the study. In other words, what is ability of the study to draw associative conclusions about the effects of the exposures on outcomes?
In critical appraising a study, the following factors need to be considered: risk of potential for selection bias, information bias, measurement bias, or confounding the mixture of exposures that one cannot tease out from each other.
High risk of bias translates to a poor quality rating; low risk of bias translates to a good quality rating. Again, the greater the risk of bias, the lower the quality rating of the study. In addition, the more attention in the study design to issues that can help determine whether there is a causal relationship between the outcome and the exposure, the higher the quality of the study.
If a study has a "fatal flaw," then risk of bias is significant; therefore, the study is deemed to be of poor quality. An example of a fatal flaw in case-control studies is a lack of a consistent standard process used to identify cases and controls.
Generally, when reviewers evaluated a study, they did not see a "fatal flaw," but instead found some risk of bias. By focusing on the concepts underlying the questions in the quality assessment tool, reviewers examined the potential for bias in the study.
For any box checked "no," reviewers asked, "What is the potential risk of bias resulting from this flaw in study design or execution? By examining questions in the assessment tool, reviewers were best able to assess the potential for bias in a study. Specific rules were not useful, as each study had specific nuances.
In addition, being familiar with the key concepts helped reviewers assess the studies. Examples of studies rated good, fair, and poor were useful, yet each study had to be assessed on its own. Did the authors describe the eligibility criteria applied to the individuals from whom the study participants were selected or recruited?
In other words, if the investigators were to conduct this study again, would they know whom to recruit, from where, and from what time period? Here is a sample description of a study population: men over age 40 with type 2 diabetes, who began seeking medical care at Phoenix Good Samaritan Hospital, between January 1, and December 31, The population is clearly described as: 1 who men over age 40 with type 2 diabetes ; 2 where Phoenix Good Samaritan Hospital ; and 3 when between January 1, and December 31, Another sample description is women who were in the nursing profession, who were ages 34 to 59 in , had no known CHD, stroke, cancer, hypercholesterolemia, or diabetes, and were recruited from the 11 most populous States, with contact information obtained from State nursing boards.
To assess this question, reviewers examined prior papers on study methods listed in reference list when necessary. Question 3. Study participants representative of clinical populations of interest. The participants in the study should be generally representative of the population in which the intervention will be broadly applied. Studies on small demographic subgroups may raise concerns about how the intervention will affect broader populations of interest.
For example, interventions that focus on very young or very old individuals may affect middle-aged adults differently. Similarly, researchers may not be able to extrapolate study results from patients with severe chronic diseases to healthy populations. Did the authors present their reasons for selecting or recruiting the number of individuals included or analyzed?
Did they note or discuss the statistical power of the study? This question addresses whether there was a sufficient sample size to detect an association, if one did exist. An article's methods section may provide information on the sample size needed to detect a hypothesized difference in outcomes and a discussion on statistical power such as, the study had 85 percent power to detect a 20 percent increase in the rate of an outcome of interest, with a 2-sided alpha of 0. In any case, if the reviewers determined that the power was sufficient to detect the effects of interest, then they would answer "yes" to Question 5.
Another pertinent question regarding interventions is: Was the intervention clearly defined in detail in the study? Did the authors indicate that the intervention was consistently applied to the subjects?
Did the research participants have a high level of adherence to the requirements of the intervention? Or did a large percentage of participants end up not taking the specific dose of Drug A indicated in the study protocol? Reviewers ascertained that changes in study outcomes could be attributed to study interventions. If participants received interventions that were not part of the study protocol and could affect the outcomes being assessed, the results could be biased. This question is important because the answer influences confidence in the validity of study results.
But even with a measure as objective as death, differences can exist in the accuracy and reliability of how investigators assessed death. For example, did they base it on an autopsy report, death certificate, death registry, or report from a family member? Another example of a valid study is one whose objective is to determine if dietary fat intake affects blood cholesterol level cholesterol level being the outcome and in which the cholesterol level is measured from fasting blood samples that are all sent to the same laboratory.
An example of a "no" would be self-report by subjects that they had a heart attack, or self-report of how much they weight if body weight is the outcome of interest. Blinding or masking means that the outcome assessors did not know whether the participants received the intervention or were exposed to the factor under study.
To answer the question above, the reviewers examined articles for evidence that the person s assessing the outcome s was masked to the participants' intervention or exposure status. Sometimes the person applying the intervention or measuring the exposure is the same person conducting the outcome assessment.
In this case, the outcome assessor would not likely be blinded to the intervention or exposure status. In assessing this criterion, the reviewers determined whether it was likely that the person s conducting the outcome assessment knew the exposure status of the study participants.
If not, then blinding was adequate. An example of adequate blinding of the outcome assessors is to create a separate committee whose members were not involved in the care of the patient and had no information about the study participants' exposure status. Using a study protocol, committee members would review copies of participants' medical records, which would be stripped of any potential exposure information or personally identifiable information, for prespecified outcomes.
Higher overall followup rates are always desirable to lower followup rates, although higher rates are expected in shorter studies, and lower overall followup rates are often seen in longer studies. Usually an acceptable overall followup rate is considered 80 percent or more of participants whose interventions or exposures were measured at baseline.
However, this is a general guideline. In accounting for those lost to followup, in the analysis, investigators may have imputed values of the outcome for those lost to followup or used other methods. For example, they may carry forward the baseline value or the last observed value of the outcome measure and use these as imputed values for the final outcome measure for research participants lost to followup.
Were formal statistical tests used to assess the significance of the changes in the outcome measures between the before and after time periods? The reported study results should present values for statistical tests, such as p values, to document the statistical significance or lack thereof for the changes in the outcome measures found in the study.
Were the outcome measures for each person measured more than once during the course of the before and after study periods? Multiple measurements with the same result increase confidence that the outcomes were accurately measured. Group-level interventions are usually not relevant for clinical interventions such as bariatric surgery, in which the interventions are applied at the individual patient level. In those cases, the questions were coded as "NA" in the assessment tool. The questions in the quality assessment tool were designed to help reviewers focus on the key concepts for evaluating the internal validity of a study.
They are not intended to create a list from which to add up items to judge a study's quality. Internal validity is the extent to which the outcome results reported in the study can truly be attributed to the intervention or exposure being evaluated, and not to biases, measurement errors, or other confounding factors that may result from flaws in the design or conduct of the study. In other words, what is the ability of the study to draw associative conclusions about the effects of the interventions or exposures on outcomes?
Critical appraisal of a study involves considering the risk of potential for selection bias, information bias, measurement bias, or confounding the mixture of exposures that one cannot tease out from each other. High risk of bias translates to a rating of poor quality; low risk of bias translates to a rating of good quality.
In addition, the more attention in the study design to issues that can help determine if there is a causal relationship between the exposure and outcome, the higher quality the study. These issues include exposures occurring prior to outcomes, evaluation of a dose-response gradient, accuracy of measurement of both exposure and outcome, and sufficient timeframe to see an effect.
Generally, when reviewers evaluate a study, they will not see a "fatal flaw," but instead will find some risk of bias. By focusing on the concepts underlying the questions in the quality assessment tool, reviewers should ask themselves about the potential for bias in the study they are critically appraising. For any box checked "no" reviewers should ask, "What is the potential risk of bias resulting from this flaw in study design or execution? The best approach is to think about the questions in the assessment tool and how each one reveals something about the potential for bias in a study.
Specific rules are not useful, as each study has specific nuances. In addition, being familiar with the key concepts will help reviewers be more comfortable with critical appraisal. Keeping that in mind, make sure that your company will have everything necessary to implement plans, create content, and measure results.
In addition to that, we strongly suggest becoming familiar with case studies, as they can inspire you. Do you want to see another successful marketing strategy to get inspired? Sign up to receive Rock Content blog posts. Sign up to receive our content by email and be a member of the Rock Content Community! Rock Content Writer Content writer. Build Trust and Boost Brand Awareness After each question, or at the end of a questionnaire, your business provides personalized feedback that indicates solutions and shows that it has extensive knowledge, which proves your capability of effectively helping customers.
Increase Lead Generation and Engagement Among the benefits, there is also an increase in lead generation and engagement. Create Highly Personalized Content Another advantage is that interactive content enables your company to gather detailed data and information about your prospects.
Lead Quizzes Lead Quizzes is an online tool to build numerous types of quizzes, surveys, and lead forms, but it can also be used to create assessments. Typeform This platform is specialized in forms and surveys through its versatility enables its users to easily create different types of content, such as questionnaires, quizzes, polls, or assessments. Survey Anyplace Survey Anyplace is a responsive online software to create quizzes, assessments, surveys, and other types of tests.
Riddle Riddle enables its users to create a wide variety of questionnaires, supports branching logic, and the inclusion of several types of content, like images, GIFs, YouTube videos, for example. Ion Interactive The services offered by Ion Interactive cover all the steps to create several types of interactive content, including interactive assessments.
FedEx As a part of its digital marketing strategy, FedEx created an interactive assessment on its website to allow small business owners to determine if they are ready for international expansion, to identify problems in their shipping models, and to discover resources that can help them to improve their processes concerning these matters. Korn Ferry The organizational consulting firm used an interactive assessment in its marketing campaign that could show how salaries would rise in according to different job levels, countries, and regions.
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