Waiting-room and fit-label associations: meaning and application

In association research you come across statements that are neither positive nor negative, yet are mentioned often and quickly: "let's see first", "not now", "not for me". If you read them as indifference, you miss what they are telling you. Waiting-room and fit-label associations are Neurofactor working concepts for such strong but neutral associations.

A waiting-room association is a strong, neutral association that expresses waiting: "proof first", "not now", "it depends". A fit label is a strong, neutral association that classifies the topic instead of rejecting it: "not my priority", "something for later", "for a different kind of person".

Both are Neurofactor working concepts, not a validated scientific classification. They help you distinguish a neutral judgement that carries a lot of weight from a weak or indifferent response. With a waiting room you offer evidence and conditions; with a fit label you work on relevance and classification.

An association is a meaning that people connect with something (see Association: meaning and application). Associations differ in valence (positive, neutral or negative) and in strength: how firmly they are linked to the topic and how quickly they come to mind (see Association strength and Association salience).

Among neutral associations, Neurofactor distinguishes two working concepts for associations that are in fact strong:

• Waiting-room association: the judgement sits in a waiting room. The person does not reject the topic but waits for evidence, a better moment or a condition.
• Fit label, also called a classifying node: the person places the topic in a category, such as "not my priority" or "something for a different kind of person". The judgement of the topic itself may be neutral or even positive; it simply does not fit their own situation.

A neutral association can mean three different things:

1. Weak or absent: the topic evokes little and the association does not come to mind quickly.
2. Indifferent: the person knows the topic, but it does not matter to them.
3. Strong-neutral: the association comes up quickly and often and has clear content, but that content is not a judgement of good or bad. It describes a position: waiting or classifying.

The next step differs. With weak associations, awareness comes first; with indifference, relevance. With strong-neutral associations a clear position already exists, and shouting louder does not address it.

Calculations that multiply valence by strength give a neutral association zero, however strong it is. So look at strength and wording separately.

That a neutral score can hide different states has long been known in attitude psychology. In 1972 Kaplan described the "ambivalence-indifference problem" of bipolar scales and proposed measuring positive and negative evaluations separately (Kaplan, 1972). Thompson, Zanna and Griffin developed this in a chapter titled "Let's not be indifferent about (attitudinal) ambivalence" (Thompson, Zanna & Griffin, 1995). According to Priester and Petty's discussion, ambivalence in their approach increases as positive and negative reactions become more similar and more intense. Priester and Petty note that a "neutral" answer on a bipolar scale loses much information about underlying conflict and indecision (Priester & Petty, 1996).

Waiting-room and fit-label associations are not ambivalence in this sense, but the research shows that neutral in data can mean more than "no opinion".

Kulas and Stachowski found for personality items that respondents choose the middle category for a variety of reasons. Middle responses went together with relatively long response times, an "it depends" meaning and less clear items (Kulas & Stachowski, 2009). Nadler, Weston and Voyles asked participants what the midpoint meant to them. Interpretations varied widely, including "no opinion", "don't care", "unsure", "neutral", "equal/both" and "neither" (Nadler, Weston & Voyles, 2015).

For association research this means that a neutral rating is a question, not an answer. "It depends" looks like a waiting room, but it may also point to an unclear question.

The waiting-room association links to research on choice deferral. Tversky and Shafir showed that people more often choose to delay a decision or look for other options when the choice involves more conflict (Tversky & Shafir, 1992). In a series of studies, Dhar found that consumers more often opted for "no choice" when the options differed little in attractiveness, and explained this through uncertainty about their own preference (Dhar, 1997).

That research concerns choices in experiments, not associations, but it makes plausible that deferral is something other than rejection.

The fit label links to research on categorisation. Sujan showed that consumers do not always weigh every attribute but also evaluate on a category basis. When information matched the expectations of a category, they formed an impression faster and mentioned fewer individual product attributes (Sujan, 1985).

For a fit label this may mean that someone who has classified a topic as "something for homeowners" judges new information through that category. Arguments about individual benefits then land less well. This is an interpretation based on categorisation research, not a tested claim about fit labels.

Neurofactor uses three working criteria:

1. Neutral valence: the participant rates the association as neutral, or the coding shows no clear judgement.
2. High strength: the association comes up quickly, is mentioned often or receives a high strength rating, depending on the measurement design (see How do you measure associations?).
3. Wording: the words point to waiting or to classifying.

The follow-up question is often decisive. "Something for later" can be a waiting room ("if the rent goes down") or a fit label ("something for when you're older").

A deal-breaking association rules an option out, however positive the rest may be. Waiting rooms and fit labels are not rejection, but in behaviour the result can look the same: nothing happens. Treat a waiting room as a deal-breaker and you refute objections that do not exist. Treat a deal-breaker as a waiting room and you provide evidence for something already ruled out.

The following directions are editorial advice based on the working concepts, not tested effects.

With a waiting-room association the question is: what is the person waiting for? Make the condition concrete and provide fitting evidence, such as a trial period, a guarantee or an explanation of what happens if the situation changes. More urgency does not answer the open question.

With a fit label the question is: which category is the topic in, and is that classification right? Work on reclassification: show that the topic fits people in the same situation, or make its relevance to their own priorities visible. Listing more benefits helps little if someone attributes them to others.

Test messages before using them widely.

1. Define the choice context: which topic, which group and which decision?
2. Measure valence and strength separately.
3. Select neutral associations with high strength and read the literal wording.
4. Code provisionally as waiting room, fit label or other, preferably with two coders.
5. Ask follow-up questions: which condition or which category lies behind it?
6. Check the distribution: does a neutral mean come from neutral answers or from opposing judgements?
7. Translate into a testable message: evidence and conditions, or reclassification.

This example is fictional. No research results are attached to it.

Situation and choice question. A fictional landlord offers tenants solar panels on their home for a monthly fee. Few tenants respond: are they rejecting it, or is something else going on?

Available information. An exploratory association measurement yields statements that are mentioned often and quickly and rated as neutral: "let's see what it yields first", "what if I move?", "something for homeowners" and "not my priority right now".

Suitable approach. The researcher provisionally codes the first two as waiting-room associations: they name evidence or a condition. The last two are provisionally fit labels: they assign the offer to a different group or ranking. Follow-up conversations ask what would need to happen and who solar panels are meant for.

Possible interpretation. If the conversations confirm this picture, the issue is not rejection. Some tenants are waiting for certainty about yield and moving house; others see solar panels as something for owners.

Next step. The landlord develops two messages to test: one that explains the yield and the arrangement when moving, and one that shows the offer is designed for tenants. Outcome measure and assessment are set in advance; results are not known.

• Equating neutral with indifferent: strength and wording then remain out of view.
• Looking only at averages: a neutral mean can consist of opposing judgements.
• Coding on single words: "later" can be a condition or a category.
• Answering a waiting room with urgency: the question of evidence remains open.
• Answering a fit label with more benefits: the "not for me" classification stays in place.
• Using the concepts as types of people: they describe associations in context, not people.

Waiting-room and fit-label associations are working definitions. There is no validated scale or threshold for "high strength" or for the classification itself.

• You can: make strong neutral associations visible, form hypotheses about what holds a group back and test messages in a targeted way.
• You can't: infer the meaning of a neutral answer without wording, follow-up questions and context; neutral can also be uncertainty, ambivalence or no opinion.
• You can't: predict what one person will do, or conclude that evidence or reclassification changes behaviour without testing it.

Associations can also shift. Repeat the measurement when the context changes.

Not every neutral association is weak or indifferent. Waiting-room associations express waiting, fit labels classify the topic, and both call for a different approach than rejection. Use the working concepts to separate these meanings, and check them with wording, follow-up questions and context.