Medical Example Using Key Features

Cognitive Model Development

In our medical example, we evaluate the examinee's understanding of the difference between two common respiratory illnesses. To solve the problem, examinees are required to understand key features that differentiate the common cold from the seasonal flu. To create a cognitive model, we start by selecting a parent item, and we evaluate the possible variations that can be produced from the item.

A 22-year-old female sees her doctor and reports that she's been experiencing a mild cough and slight body aches that have developed over a few days. Upon examination, she presents with an oral temperature of 37°C. What is the most likely diagnosis?

  • (A) Hay Fever
  • (B) Ear Infection
  • (C) Common Cold *
  • (D) Acute Sinusitis
  • (E) Seasonal Flu

The content domain, which is described as the problem in the top panel of our cognitive model, for the parent item is a respiratory illness. Two scenarios will be modelled for this problem: common cold and seasonal flu. These scenarios were included in the model because they both measure the problem of respiratory illness, and they display different features using the same list of symptoms. The symptom list includes the following four features.

A 22-year-old female sees her doctor and reports that she's been experiencing a mild cough and slight body aches that have developed over a few days. Upon examination, she presents with an oral temperature of 37°C. What is the most likely diagnosis?

Common Cold

The feature list can be classified, more generally, into two sources of information: history (cough type, body aches, onset) and examination (temperature). In addition to these four features, we can include additional features to vary in the item generation process. In our example, age is not a key feature for solving the item, but it can be varied to produce item heterogeneity. The final item structure is presented as follows:

A female sees her doctor and reports that she's been experiencing a and that have developed . Upon examination, she presents with an oral temperature of . What is the most likely diagnosis?

Once we have defined the features in our cognitive model, we can then define the possible variations of the patient presentations. These variations are called elements. Elements can be specified as either string or integer values. We begin with the correct options.

Common cold

Seasonal flu

Next, we vary each of the values for our five features. When varying these features, it is critical that each value we vary either match one or both of the correct options. Values that do not match the correct options will not be included in the generated items.

18..30 by 1

  • 1. mild
  • 2. hacking
  • 3. severe

  • 1. slight body aches
  • 2. slight body pains
  • 3. severe body aches 4 . severe body pains

  • 1. over a few days
  • 2. within 3-6 hours
  • 3. suddenly

  • 1 . 37°C
  • 2 . 37.8°C
  • 3 . 39°C
  • 4 . 39.5°C

Our next step is to define the relations for each of the values. By "define the relations," we mean that each value in the feature list is associated with the correct options.

1. Common cold

(CC)

2. Seasonal flu

(SF)

18..30 by 1

(CC, SF)

1. mild

(CC)

2. hacking

(CC)

3. severe

(SF)

1. slight body aches

(CC)

2. slight body pains

(CC)

3. severe body aches

(SF)

4 . severe body pains

(SF)

1. over a few days

(CC)

2. within 3-6 hours

(SF)

3. suddenly

(SF)

«TEMPERATURE>

1. 37°C

(CC)

2. 37.8°C

(CC)

3. 3 9 °C

(SF)

4. 39.5°C

(SF)

Item Model Development

Once a cognitive model is specified and the content in the model is organized and coded, we can proceed to the item modelling step. The item model is used to format the content identified in the cognitive model. The item model for the medical example is presented as follows:

Stem

A [AGE] female sees her doctor and reports that she's been experiencing a [COUGH] and [BODY_ACHES] that have developed [ONSET].

Upon examination, she presents with an oral temperature of [TEMPERATURE]. What is the most likely diagnosis?

Elements

AGE: 18 to 30, by 1

COUGH: (1) mild cough, (2) hacking cough, (3) severe cough

BODY ACHES: (1) slight body aches, (2) slight body pains, (3) severe body aches, (4) severe body pains

ONSET: (1) over a few days, (2) within 3-6 hours, (3) suddenly

TEMPERATURE: (1) 37°C, (2) 37.8°C, (3) 39°C, (4) 39.5°C

Key

Common cold, seasonal flu

The item model should produce items without any additional corrections or changes. Also, the item model should be formatted so that it can include future edits (e.g., updating information in the model to accommodate changes in medical practices) and additional expansions (e.g., including more layers in the model). The first change in the item model for our example is obvious—the word "cough" is repeated in the element [COUGH]. Then we can modify the element so that it is formatted correctly (we introduce a new element [COUGH_TYPE: (1) mild, (2) hacking, (3) severe] to highlight this change). The same change is applied to the element [TEMPERATURE] variable. The second change is a bit trickier. Suppose we do not want to keep the article "A" for the entire age range element. When the element [AGE] takes a value of 18, for example, assume we want to change the article to "An". We can address this linguistic requirement by moving the article into the age element and adding an extra variable [AGE_RANGE].

AGE: (1) An 18, (2) A [AGE_RANGE]

AGE RANGE: 19 to 30, by 1

The final item model is presented as follows:

Stem

[AGE] female sees her doctor and reports that she's been experiencing a [COUGH TYPE] cough and [BODY ACHES] that have developed [ONSET]. Upon examination, she presents with an oral temperature of [TEMPERATURE]°C. What is the most likely diagnosis?

Elements

AGE: (1) An 18, (2) A [AGE _ RANGE]

AGE RANGE: 19 to 30, by

COUGH TYPE: (1) mild, (2) hacking, (3) severe

BODY ACHES: (1) slight body aches, (2) slight body pains, (3) severe body aches, (4) severe body pains

ONSET: (1) over a few days, (2) within 3-6 hours, (3) suddenly

TEMPERATURE: (1) 37, (2) 37.8, (3) 39, (4) 39.5

Key

Common cold, seasonal flu

 
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