Never Spell Word

The idea behind Never Spell Word (NSW) is simple: Every project has its own language and every publisher has its own preferences. NSW enables an editor to create a project- and/or publisher-specific preference list and have it applied to each article or chapter of a project.

NSW has the following tabs: Never Spell Word, Drugs, Organisms, Terms of Art, Studies/Trials, and Names Persons/Places. We will highlight just the NSW tab here. All work similarly and the videos give a more comprehensive view of NSW.

Creating or Accessing a Dataset

The NSW Manager is how the datasets that makeup the NSW macro are accessed. Using the NSW Manager, an editor can open an existing dataset (i.e., project or publisher preference file) or create a new project.

If a new dataset is created, it is done either from a blank dataset or by copying an existing dataset and then modifying it.

Adding Words & Phrases

In the Manager's main area is found the list of words and phrases that make up the dataset. (Each tab has its own dataset and making changes to one has no effect on the others.) It is here that an editor can add new words and phrases to the dataset or delete them. For example, if the preferred style for Williams and Wilkins is Williams & Wilkins, the editor can enter the information here.

(The asterisks in the image below indicate that the entry is case sensitive so that for the change to occur the found term must match the find term exactly. In this case the found term must match Williams and Wilkins, thus the macro will not find WIlliams and Wilkins. To make the search for a term case sensitive, just check the Case Sensitive box when adding the term to the dataset.)

Now Williams and Wilkins will (1) automatically be corrected and (2) when corrected (a) the correction will be made with tracking on and (b) the correction will be highlighted in cyan as a visual cue.

Visual Cues

NSW and all the datasets associated with it, such as Journals, rely on visual cues to make editing quicker and more accurate. Here is what the colors signify:

When adding words to a dataset, the editor assigns the color that the word is to be highlighted. In some cases, the color choice is grayed out. That means the program automatically applies a particular color. For example, when the editor wants a word or phrase changed to something else, the change is always highlighted in cyan.

The following is a sample of what you might see in a document after running NSW. The sample illustrates how NSW can increase editing speed and accuracy.

In the sample, the project style is for health care to be healthcare. NSW made the correction (1) with tracking on and highlighted the change in cyan. Because it is highlighted in cyan, indicating correct form, the editor is visually cued that the change complies with the style and doesn't have to question it. [NOTE: You can choose to run the NSW macro with Tracking on or off. We recommend always running it with Tracking on.]

Ziprasidone (2a) is highlighted in green, indicating that the name is correct. Because it is highlighted in green, the editor knows — from the visual cue — that it is correct and does not have to pause to verify the spelling. Contrast this with aripiprazole (2b) which is not highlighted. The lack of highlighting tells the editor that this drug is not in the drug dataset and if the editor is unfamiliar with the drug, that the name has to be checked. After verifying that the name is spelled correctly the editor can use the NSW Manager to enter the drug into the drug dataset. Adding aripiprazole to the drug dataset means that the next time the NSW macro is run, instances of aripiprazole will be highlighted in green, visually telling the editor that the name is correct.

Sometimes an editor doesn't want a word to be automatically corrected but does want attention drawn to the word. That is the function of the gray highlight (3).

Finally, AMA style for "30 milligrams per day" is 30 mg/d. This project's style, however, is to spell out day. By having "/day" in the dataset, NSW highlights "/day" in cyan (4), visually telling the editor that this is correct and a publisher-specific exception to AMA style.

As you can see, the use of visual cues — the highlighting by NSW — helps increase editing speed and efficiency, promotes consistency if multiple editors are involved, and can reduce errors.