Remembering the Pre-Aversive Stimulus

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There are some terms and concepts from behavioral psychology’s past that have found themselves buried in time. Tucked away in a journal here or there but largely forgotten. The older research that tracked rates of behavior following “noxious stimuli”, for example- A phrase we don’t use anymore.  Time has also changed the fascination with respondent conditioning and effects that just two (or more) paired stimuli somewhere along the line could change responding for a lifetime. Powerful principles, which with progress now seem so mundane. Somewhere in there, we have the pre-aversive stimulus.

The pre-aversive stimulus had a great role in early behavioral science animal research to describe responding patterns, but the concept easily applies to humans as well. A pre-aversive stimulus, simply put, is the stimulus that reliably precedes an aversive stimulus. Have you ever heard the term avoidance responding? Some people may call that “escape-maintained behavior” in the field but it is effectively just that- engaging in behavior (responding) to avoid a stimulus that was aversive in the past. Running away. Getting away. Dodging it. What signals that, then? The pre-aversive stimulus. It goes even further. Just through respondent conditioning, the pre-aversive stimulus can take on features of the aversive stimulus and become a conditioned aversive stimulus itself. Then there’s another pre-aversive stimulus that could reliably precede that, and with enough second-order conditioning, you could get messy (over)generalization and find all sorts of related stimuli as aversive. Generalized Anxiety Disorder theoretically works on this same principle. It’s not hard to see how this kind of thing can tangle up a person’s life- whether they are able to realize it and vocalize it or not.

 

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Wait! Isn’t a pre-aversive stimulus just a kind of SD?

Let’s not jump to any conclusions and mistake a pre-aversive stimulus for an SD just yet. They have some things in common. They’re both stimuli (but so is almost everything else). They can both be considered antecedent stimuli when we look at the framework of the avoidance responding that sometimes follows them. They signal something. All good comparisons- but here’s a big distinction if you don’t remember: A discriminative stimulus (SD) signals reinforcer availability for a specific type of response.

The per-aversive stimulus does not necessarily have to.

In some situations, you could conceptualize a case for negatively reinforced behavior, but that might muddy the definitions of both terms being used concurrently. They speak to different phenomena even though they could describe one particular stimulus. The big difference is that the cue for available reinforcement is not necessary for a pre-aversive stimulus. It is simply a stimulus that has commonly preceded something aversive, or bad.

Example: An individual has been stung by a wasp before. Maybe several times if they were unlucky. Prior to the stinging, they heard the buzzing around a wasp nest.

That buzzing could likely become a pre-aversive stimulus, and through respondent conditioning, a conditioned aversive stimulus itself in the future.

In the research, pre-aversive stimuli tended to evoke “anxiety” in respondents- which was quasi-operationalized to the term conditioned emotional response (CER), also called conditioned suppression. That’s an important distinction to keep in mind. Here, a pre-aversive stimulus appears to suppress or decrease responding- not signal reinforcement for a response like an SD would.

Like freezing near a wasp nest when buzzing is heard. The usual comfortable walking pace (response) is suppressed in the presence of the buzzing sound (pre-aversive antecedent stimulus).

 

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Anxiety! Conditioned Emotional Responses! Conditioned Suppression!

Respondent conditioning research has some fascinating lessons that are just as relevant today as they were decades ago. Sometimes in the day to day practice of behavior analysis- things get oversimplified for the sake of ease of practice.

Behavior goes up? Reinforcement is at work.

Behavior goes down? Punishment is at work.

To a degree, those definitions work. Even with our wasp nest example earlier, those initial stings could absolutely punish some future walking behavior. But we can’t forget about the little things- the little preceding stimuli that have so much to do with the actual phenomenon. The buzzing didn’t punish the walking. Don’t forget the antecedents. Don’t forget the respondent conditioning. Taking the time to examine just one more step explains the process so much more clearly.

What conditioned pre-aversive stimuli appear to evoke conditioned emotional responses in your day to day life? Do you see conditioned suppression of behavior, as a result, that would have otherwise been there? What pre-aversive stimuli could be “tagging on” to the effects of an aversive stimulus you’re aware of? Does it evoke any avoidance behavior?

Too simple? Laurence Miller ‘s (1969) work on compounding pre-aversive stimuli might whet your broader research appetite. Citation below.

Thoughts? Comment! Question! Like!

 

References:

Coleman, D. A., Hemmes, N. S., & Brown, B. L. (1986). Relative durations of conditioned stimulus and intertrial interval in conditioned suppression. Journal of the Experimental Analysis of Behavior,46(1), 51-66. doi:10.1901/jeab.1986.46-51
COOPER, JOHN O.. HERON, TIMOTHY E.. HEWARD, WILLIAM L. (2018). APPLIED BEHAVIOR ANALYSIS. S.l.: PEARSON.
Miller, L. (1969). Compounding of pre-aversive stimuli1. Journal of the Experimental Analysis of Behavior,12(2), 293-299. doi:10.1901/jeab.1969.12-293
Ormrod, J. E. (2016). Human learning. Harlow, Essex, England: Pearson.
Image Credits:
http://www.pexels.com, photographer Hubert Mousseign

Love, Psychologically

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There are some things that are just fun to study because of their vast importance. Love is one of them. There are as many theories about love as there are grains of sand on a shore, but if you’re a scientist, especially a behavioral scientist; you want to focus on the aspects that can be studied; things that we can at least see, hear, or touch, so that we can come to some kind of agreement on their existence. So it might not be so much an invisible force called “Love” we’re using terminology on, but rather “loving”. The romantic relationship, the affiliation between people; what they do, how they do it, how it maintains. What makes loving, and being loved, a unique experience and one that people tend to pursue for years (while others, sometimes, much shorter).

As humans in general, we cannot see any invisible qualia of romantic “love”, but we can see how people respond to one another, how they draw selective attention, how that attention strengthens and becomes a bond, and how they share in that exchange of the affiliation, that relationship. If we think about “love” as magical, and inexplicable, then that makes it very hard to study, doesn’t it? But if we look at what it “looks like”, what people “do” or “exhibit”, then we get somewhere. Love. It happens so much that there surely have to be some common features, and since we are all human, after all, we must share aspects and patterns that over-arch large groups of us. Even entire populations must share some feature, some pattern, that we can call “loving”. How else would there be so much advice out there?

There has been psychological research on this. An abundance of it. Dorothy Tennov’s work on “Love and Limerence”, Keith Davis’ “Relationship Rating”, Beverly Fehr’s “Love and Commitment”, and even Marshall Dermer’s behavioral account of “Romantic Loving”. There are just a few (there are thousands) of many, that will be used to explore some theoretical frameworks for what makes a working relationship work, what the features are, and the appeal of specific patterns of behavior that make up a “loving” affiliation.

We have to assume a little with this. Everyone is different, so specifics are where we would lose this account’s effectiveness of loving. If we assume everyone likes brightly colored eyes, when in fact many find darker color eyes reinforcing (rewarding/appealing), then we’ve assumed too much. If we, on the other hand, assume that every human on earth is subjectively polyamorous, and can come to no conclusions, then we assume too little. We have to find a middle ground that might not explain everything but explains enough.  We want an account of “loving” that is stable, desired, and explains a fully functioning relationship.

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What is Love & Loving? (and what’s not?)

Let’s let out some ground rules for our interpretation of this framework. To best interpret this research, and create something that we can actually put into real testable practice, we need to make sure we keep it in the realm of reality. So when we talk about “Love” going forward, we are going to talk about events/behaviors from ourselves and others. Some may be private (inside our head), some may be public (an action we engage in with another person), but all of these things can be more or less concretely defined. Let’s call the process of experiencing and doing these things “loving”. You can engage in love with another person, and they can engage in loving events/behaviors with you. Sounds fun. Now that we have an operational definition to work with; what might that exclude? Let’s talk about Limerence.

Dorothy Tennov developed this concept in 1979 to explain the experience of being “head over heels” with someone. It’s intense. It’s all consuming. Even a little obsessive. As she, and another researcher Lynn Willmott, describe it;  “an involuntary potentially inspiring state of adoration and attachment to a limerent object (the target of infatuation) involving intrusive and obsessive thoughts, feelings and behaviors from euphoria to despair, contingent on perceived emotional reciprocation”.  Let’s break this down and make it a little more “behavioral”. So limerence, is like love, except people exhibit:

  • Intrusive and obsessive thoughts about the person (Private Events).
  • Attachment to a Limerent Object (the person they are obsessed with). Thoughts and interactions with this individual become highly reinforcing, and behaviors seeking them are thus highly reinforced.
  • Reciprocity determines “euphoria” or “despair”. If that Limerent Object ( the person who is being obsessed over) gives a specific type of perceived behavior; it can either be incredibly reinforcing (rewarding), or incredibly aversive. These are two very extreme states.

According to Tennov, this is the type of “loving” we would hope to turn into a relationship or affiliation of “loving” behaviors between two people, but it could not maintain itself as it is. It’s not stable. It’s intense, a flash, but is based on perceptions and obsession (highly repeated private events or “thoughts” about that person). These behaviors do not operate in a healthy way to create or build a relationship. They seem to seek out the other person intensely, but you might notice, they do not seem to hold that person in a regard where a relationship could flourish. This type of limerence is what Tennov found to be dangerous.

It’s not a feeling so much as it is a pattern, and she found 3 ways that it subsides.

Consummation, where the feelings are reciprocated, and ideally, the limerence becomes a more healthy form of attachment. This is the best case scenario.

Starvation, or as behaviorists call it “Extinction”, where the behaviors of obsession/seeking are not reinforced; the other person doesn’t respond. The seeker gets nothing of what they were seeking, so the seeking undergoes behavioral extinction because it no longer serves its function. This is a painful process, the “despair” Tennov spoke of.

Then there’s Transference where the limerence stays, but the limerent object changes. The person they are focusing on gets replaced with another person, and the cycle of intense emotion, intrusive thoughts, etc continues in another direction. In behavioral terms, the response class remains, but the target of those behaviors changes. This type of seeking also seems incredibly unhealthy and hard to sustain a balanced life around.

According to our original operational definition of “loving”, this limerence is not going to work, conventionally. We cannot apply these patterns to a broad population and hope for good outcomes. This is where we need to turn to Keith Davis’ research and Marshall Dermer’s behavioral account of loving to help us out. These researchers took features of “loving” relationships and broke them down into components that most people tend to exhibit. On top of that, they also came up with strategies that might maintain them. Having a loving relationship is good, but maintaining it is also something worth looking into. You might have seen the word reinforcer or reinforcing used a few times. Humans rely on patterns. It’s a big part of how we operate. Think of reinforcers as “things” that keep a pattern going, and reinforcement as the process of strengthening that pattern. Let’s talk “loving” reinforcement and these components of caring.

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Features of “Loving” and Reinforcing (Maintaining) Them

They (Davis, Todd, as well as Dermer) break down “loving” into three classes of features; Caring, Passion, and Friendship. These are behaviors and traits exhibited in regular patterns and are consistent. They are a common part of the functioning relationship or affiliation with one another. I’ll present a few words from the researchers, and follow up with some actual behaviors that represent examples that a person might engage in.

Features of Caring:

  1. The person “gives their utmost” to the other. Behaviorally speaking, we mean that the effort put in to engage with the other person, and acting for their benefit, is high. Some might say foregoing one’s own reinforcers (rewards) so that the other are reinforced (rewarded).  Here are some examples.
      • Engaging regularly.
      • Being present and focused during engaging.
      • Potentially putting maximum effort for that individual.
      • Potentially sacrificing their own rewarding opportunities, for the sake of the opportunities of the other.

     

  2. The person “championing and advocating” for the other. This is not a quid pro quo situation based on measuring out little bits of effort and support, this is committing to the betterment of that person. It involves social reinforcement.
      • Socially praising that person for actions.
      • Socially praising and supporting efforts of that person.
      • Putting forward resources and social effort for the successes, or approximate successes of that other person.

     

Features of Passion:

  1. “Fascinating” about the other. By fascinating, they mean engaging in thinking or imagining about the other person even when that person is absent. (Think of this as a tempered version of the limerence we spoke about above). These events are what behavioral psychologists call “private events”. They are not observable to anyone else but the respondent.
      • Thinking about the other person regularly.
      • Imagining the other person regularly.

     

  2. Mutual “desiring and experiencing sexual intimacy”. This one is the more obvious “passion” feature. These are both overt and covert (private) behaviors, but most importantly, this behavior is shared between both simultaneously. The reinforcement (rewarding) from one to another is mutual or shared.
      • Engaging and reinforcing “desiring” behaviors between one another.
      • Engaging and reinforcing “sexual intimacy” behaviors between one another.

     

  3. “Desiring mutual exclusivity” with the other person. This is where behaviors are used specifically with one another. One person presents specific, and unique, behavior towards the other and do not engage in these specific behaviors broadly with others outside of the relationship.
      • Unique thoughts or feelings about the other.
      • Unique ways of speaking or responding to one another.
      • Unique patterns of daily behavior with one another.

     

Features of Friendship:

  1. “Enjoying one’s company”. At a very basic level, being around someone should be enjoyable if a relationship is to maintain. This enjoyment could come from;
      • Enjoyment gained from a shared history and specific important events.
      • Enjoyment gained from a conditioning, shared desirable features that have become attributed to one another.
      • Enjoying the repertoire of social behaviors, or activities that person engages in regularly.

     

  2. “Being able to confide” in the individual. Sharing information that has the risk of being exploited, or showing vulnerability. Being able to express specific thoughts or intents with the other person and not expecting a reprisal or betrayal on the part of the other.
      • Sharing secrets, hopes, dreams, aspirations that represent vulnerability.
      • Being able to speak frankly and honestly on topics.

     

  3. “Behaving spontaneously”. With strangers, predictability is the best bet at cooperation and interaction so that no one is put off. This feature represents a tolerance for spontaneity and surprise where there is the potential for the unexpected, and in a sense, a chance of the unknown or risk.
      • Engaging in behaviors that are novel towards the other, with the other in mind.
      • Engaging in novel activities with the other.

     

  4. “Understanding” the other. The verbal behavior (spoken words) make sense to the other and are not misinterpreted.
      • Shared meanings of certain histories or features.
      • A shared understanding of tone of voice.
      • A shared understanding of facial expressions or other predictors others might not pick up on.

     

  5. “Respecting the other”. This is where the judgment, intents, and meaning of the other person are held in a regard that is not distrustful, or disingenuous.
      • Allowing one person to engage in an activity and having faith in that other person’s ability.
      • Engaging socially in terms that promote dignity and value the other.

     

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Reinforcing the Relationship

These are a lot to juggle at one time. If all of these features are important for both people to engage in while in that state of loving, and the relationship is to maintain for long periods, there must be some way for people to have the time and ability to do so, right? This is where we discuss how and when we can use those features above as practical behaviors, and making those practical behaviors reinforcers (rewards). Reinforcers aren’t just prizes or tangible objects; they can be ANY behavior or change in a stimulus that strengthens another behavior. It’s not just one direction either. One person can reinforce another’s behavior, and have that person reinforce theirs right back. It becomes a cycle, it becomes an interaction where both sides are engaging in these loving features, those romantic behaviors, and being strengthened by one another’s. Here are some suggestions from the research.

Reinforcing a Relationship with Generic and Abundant Reinforcers-

Don’t let the words generic scare you off. This does not mean boring or unoriginal. This means using the common stuff and using it often to strengthen the romantic/loving behaviors in the other person. These are things you have a lot of, or behaviors that are low cost to you, that you can use repeatedly and consistently. This sort of behavioral framework is good for maintaining a relationship.

Given the opportunity, how many Friendship, Caring, and Passion behaviors could you exhibit abundantly an hour? How about per day? Or month? Try looking at these.

  • Smiling
  • Laughing
  • Engaging in a positive tone.
  • Taking the time to understand a point of view.
  • Physical closeness.
  • “Checking in”- frequent social interaction.

Just to name a few. These are easy, quick, require little effort, and can maintain a relationship, or series of interactions through those quick and abundant psychological reinforcement effects. Remember; A big surprise is great, but if you get absolutely nothing from the individual, not a smile, not a word, in between, big surprises aren’t strong enough. The relationship gets frayed, thin. That’s why you use “generic and abundant” social reinforcers from your assumedly impressive romantic repertoire of skills.

Reinforcing a Relationship with Scarce and Idiosyncratic Reinforcers

Now the big surprises come in. These can’t maintain a long and complex relationship by themselves. They, by definition, are scarce, therefore very interesting. These are things you can not provide to another person very often, and they are varied enough that the other person probably would not be able to expect them. These are the high shock-value interactions or rewards, the things that provide a revitalization.  Remember the spontaneity feature? This is where it comes in. These come in when the generic and abundant reinforcers lose efficacy. Sometimes when a thing is too common, people adapt, so you need to throw a little “strange” out there to mix up the predictable delivery of these romantic reinforcers. You can’t expect the scarce big reinforcers to maintain a relationship, but without them, the generic and abundant undergo habituation. Sometimes when something is too predictable and common it loses its reinforcing features. You need to change it up. The mixture of both is where the long-term maintaining of romantic behaviors on both sides meets a good equilibrium.

What about these? Are there any scarce or idiosyncratic reinforcers you could think up from the Caring, Friendship and Passion categories? Can you think of a few specific reinforcers you enjoy? Can you think of a few specific ones that another person might? Try them out and see if they work, or engage in some confiding features to request them. You might just learn something!

Comments? Questions? Leave them below!

References:

  1. Cooper, J. O., Heron, T. E., & Heward, W. L. (1987). Applied behavior analysis. Columbus: Merrill Pub. Co.
  2. Willmott, L., & Bentley, E. (2014). Love and limerence: harness the limbic brain. United States: Lathbury House Limited.
  3. Tennov, D. (1999). Love and limerence the experience of being in love. Lanham, MD: Scarborough House.
  4. Davis, K. E. (1999). What Attachment Styles and Love Styles Add to the Understanding of Relationship Commitment and Stability. Handbook of Interpersonal Commitment and Relationship Stability, 221-237. doi:10.1007/978-1-4615-4773-0_13
  5. Davis, K. E., & Todd, M. J. (1982). Friendship and love relationships. In K. E. Davis, and T. O. Mitchell (Eds.), Advances in descriptive psychology (Vol. 2, p. 79-112)
  6. Dermer, M. L. (2006). Towards understanding the meaning of affectionate verbal behavior; towards creating romantic loving. The Behavior Analyst Today, 7(4), 452-480.

 

Image Credits: http://www.pixabay.com

Click-Bait Psychology- How To Beat Misinformation

The world of Psychology has a vast appeal to public interest. We all want to know the inner workings of our minds, and the minds of others. We also like that information in a form that is easily accessible, and quick to understand. For better or worse, there is a great deal of psychological information at our fingertips on the internet; but the kicker is that there is also a disproportionate amount of misinformation. I am going to talk about how to get the right information, how you know whether that information you are consuming is supported (founded) or not, and the tricks being used to grab viewers towards misinformation for the sake of monetization (clicks which generate advertisement revenue). We risk taking these assertions and titles as fact, when in truth there may be little evidence to support it.

 

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What Psychology is, and what it is not.

Psychology is a field of study. People who undertake psychological research often have years of coursework under their belt, and when they publish it is often in the form of academic journals which are peer reviewed. That peer review is the important part. It means that other people with the same amount of skill and experience went over the study and found that the methods and findings were acceptable for publication, and (hopefully) replication. This does not mean the study is true, necessarily, but it does mean that the methods and findings pass the rigor that you would expect from empirical findings.

What Psychology is not; unfounded hypotheses based on invented constructs that have not been tested or platitudes. Let’s look at the difference of a few statements that are either founded or unfounded. Founded is based in fact, or at least the seeking of it. Unfounded is speculative, or unsupported by research into real phenomena, and usually entices readers by a reaction. Usually, the unfounded “click-bait” article is created to gather broad interest by using concrete claims that have very little evidence behind them. If you were to compare any peer-reviewed research article to the “click-bait”, you would see a huge difference in how these are written and how the findings are presented. One attempts to explain something by supporting it, the other takes an assumption as fact and generalizes it to get max appeal/shock.

Example Time!

“Based on a 2003 study, Researcher A and Researcher B found a correlation between the color red and aggression levels in teens.”– This is something we could begin to consider founded. We have three big hints:

  • Reference to an actual study. You could read it yourself and come to your own conclusions.
  • The names of the authors/researchers. The reader could look them up, or even contact them for better understanding or replication.
  • The word correlation and not “causes”. This is a big hint that it was actual research with a sample of people. Research often infers, it does not conclude broadly.

 

“10 Things Men or Women Do Differently! Women/Men ALWAYS…”– This seems unfounded. We have some hints.

  • The click-bait style title. Lists are commonly used to draw in interest to a website or article.
  • The word “Always”. Empirically designed research works on philosophic doubt and evidence in a subject. When something is studied, it is usually done with a sample; a small group of people to represent larger groups. These do not mean that it is a perfect causal effect to be applied to all humanity across time or the entire world.

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“Pop-Psych Platitudes” and Title Hooks:

Here are some tricks that are used by “bad”-psychology to get your interest. Hooks. One liners. These are titles and phrases that throw out a topic you could easily agree with, but do not lead you to the “meat” of the matter. That kind of article would not tell you what research it referenced, or even worse, it could misinterpret research to fit a broader and more appealing finding that never existed. A good rule of thumb is; If they can condense 40 pages of research into one statement, you’re probably missing out on the actual findings. They use things called “Pop-Psych Platitudes”; things that appeal to what appears to be a truism and avoid actual empirical findings. Look at some of these examples:

  • Why Your Dog Is Always Right About Your Mate- They Have Senses.
  • Women/Men Choose Better- It’s In The Genes!
  • Read Lies In the Eyes- 5 Big Tips To Liars.
  • If You’re Not Happy, You’re Not Using Mindfulness.
  • Smart People Get Hurt More Easily By Rejection.
  • Every Time You Forgive, Your Brain Becomes Happier.
  • Trust Is Earned, Not Free.
  • 10 Things Anxious People Know.

The titles above have some appealing points to them, don’t they? You could apply them to an experience you may have had before, or a belief you have on a topic. You might really want to affirm that by clicking on it and reading a few persuasive paragraphs on the personal experiences of the writer (these are called anecdotal statements, not research). They appeal to the reader’s biases or personal experiences by using broad language and big claims they want to read. They may reference a single research article to support their claims, but fail to mention the techniques in the article, the sample used in the article, and the actual conclusion of the article itself. They may also have cherry picked a single article (line or paragraph) that had not been replicated by other researchers to support a broad claim. These give the semblance of academic research, but fail several benchmarks of being empirical and trusted as a true representation of a discovered or explored phenomena.

Another big trick is a Title Hook. You remember the trick of putting a number in the title? “8 Things You Won’t Know About Anxiety!”. Just 8? Sure. Why not. We all have time to read 8 statements. Right? Sometimes they will employ a stronger hook to get you to read. “8 Things You Won’t Know About Anxiety! Number 5 Will SHOCK you!”. See what they did there? You are tempted to look at number 5, which leads you through over half of their statements separated by clicks to different pages. Those pages are probably monetized, and most likely have very little in the way of actual facts or research supported claims.

 

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The Risks of Being Misinformed

There are risks to misinformation. It gives you, the reader, the experience of feeling as though you have learned something, or reaffirmed a belief you had, without the benefit of using real scientific methods and without the benefit of knowing that this topic was rigorously studied. When researchers take a topic, more often than not, they come away with what is called a Null Hypothesis. A Null Hypothesis is the condition in which the researcher could not prove what they set out to prove. That is what real research runs the risk of every time. Not every hypothesis that’s put to the test works out. Many times, a hypothesis has to be refined several times, with multiple caveats. “No, we couldn’t prove that Disorder A coincides with candy bar eating, but we were able to show that Food Additive B might have an effect on a symptom of Disorder A, based on…”. This is the type of wording you would find in the conclusion section of many research based and peer reviewed articles. See how different it is from the click-bait?

Many times research is not instantly easy to interpret, has a conclusion that is not always completely confirmed , and raises more questions than it was set out to answer. But it is the spirit of science. You find correlation, links or connections between factors, but never the always.

If you would like to further your knowledge in psychology, read some articles with true empirical weight, I suggest you take a look at the National Institute of Mental Health’s webpage (https://www.nimh.nih.gov/) . It has articles free of cost on almost any topic you could have an interest in. I implore you to take a look and see what a truly rigorous study looks like. Much like a good story, it has a beginning, middle, and end that beats out a click-bait unfounded affirmation any day.

 

Questions? Comments? Reply Below!

 

References:

  1. Wood, S. E., Wood, E. R., & Wood, E. R. (1996). The world of psychology. Boston: Allyn and Bacon.
  2. Cooper, J. O., Heron, T. E., & Heward, W. L. (1987). Applied behavior analysis. Columbus: Merrill Pub. Co.
  3. NIMH » Home. (n.d.).  https://www.nimh.nih.gov/index.shtml

Photo Credits:

  1. pexels.com Pexels Stock Photos

 

Social Data: Getting the Most of Your Polls, Questionnaires, and Surveys

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Self Report Studies:

Self-report studies; you see them all the time online: surveys, polls, and questionnaires. You even see them on your receipts after you order a coffee. Your opinion counts. People want your social data. Some of these are used for marketing, and others are just done for the fun of it.

The reason they are called Self-Report Studies is that they rely on that group to give their own interpretation or information on the subject. The information that the group provides (or self-reports) is called data. Data, especially social data, is important to a lot of people because it gives a voice to a target audience. Many social media networks (Facebook, Twitter, etc) now give their users the ability to do their own self-report studies with only a few clicks of a button. Here are some tips to make sure yours are made with a scientific understanding of the principles!

Sample!

A sample is the selection of a population that you are using for your study (poll, questionnaire, etc). These are the respondents to your self-report study. They are the ones providing your data. Since they make up the entirety of the feedback you will be receiving in your study, you probably want to get the most out of your sample, right?

There are two main ways you can do this. Scope of your study, and size/diversity of your sample.

Scope: The scope of your study, or poll, is the breadth of information you are looking for. It is the net you are casting to catch the information on your topic. [1,2]

You can use a narrow scope: using a topic that is relevant only to the select population you are targeting “Hello, Members of the Elephant Watching Club! Which is your favorite type of elephant?”.

Or, you can use a broad scope: using a topic that has broader relevance on a larger topic: “Hello, Members of the Elephant Watching Club! What do you think about Politician A?”

You might have noticed something in those examples. The survey is only able to track the Members of the Elephant Watching Club. The Elephant Watching Club is the extent of their sample. If the person wanted to get an answer that applied specifically to members within that club, then they would be fine with either scope; just so long as they did not interpret that as an example of a broader population. This leads us to the next one: size/diversity. [1,2]

Sample Size/Diversity:  This refers to the size of your sample, and the diversity of people/opinions within it. If you want to, say, get a representative sample for the United States of America, would you only sample the Elephant Club? Probably not! They most likely do not have the diversity or size to be of use. You would want a sample that is representative, or represents, the diversity in opinion of the target audience you are inferring from.

This may sound difficult for polling. How would you do it? Many researchers use what is called a “Random Sample”, which is a sampling method that gives every member of a population being studied an equal chance of being selected for that sample. It gives broader reach, as well as less hand-picking by the researcher which could lead to bias. If this is something that your current self-report study media does not do, try and adjust your topics to account for Scope, and Sample Size/Diversity! [1,2]

 

Tip! Target your self-report study to fit closely to your sample! Know the population you are studying and gear what you are looking for to fit within that group.

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Types of Questions:

There are two types of questions used in self-report studies: Open Questions, and Closed Questions.

Closed questions are questions which provide a limited choice, especially if the answer is taken from a predetermined list. This provides what is called quantitative (numerical) data, but do not allow the participant to give in-depth insights. They are “closed” because they give the respondents a pre-selected set of options to choose from. Polls often used Closed Questions for numerical data. [1,2]

  • Examples: “Pick your favorite ice cream from the following list: Vanilla, Chocolate, Strawberry”. or   “Do you like apples? Yes or No”.

Open questions are those questions which invite the respondent to provide answers in their own words and provide what is called qualitative data.  These questions give you more in-depth answering in the respondent’s own words, but do not allow you to quantify them as easily and compare them to others. They are “open” because the answer may be anything the respondent writes down or replies with. Questionnaires and Surveys include Open Questions for respondent-detailed replies. [1,2]

  • Examples: “Tell us what you think about our service?” or  “What about the apple grove did you like best?”

 

Social Media Example: A Poll would be Closed Question Data. The replies written by users would be Open Question Data.

Each type of data has its own benefits and drawbacks. You would want Closed Questions to provide you data that you could numerically analyze quickly. Everyone responding has the same answers, so it is like comparing apples to apples (so many apple examples…). But, if you wanted a more nuanced answer for the sake of feedback that did not have the same comparability, you could use Open Data to get more detail from your sample. [1,2]

 

Tip! Use the data that fits the type of output you want most. Want descriptive feedback (which you do not need to represent in a graph)? Use Open Questions. Want to make a graph and get numerical data? Use Closed Questions.

 

That’s Mean! (Median, and Mode):

Now let’s talk about some data analysis we can use for quantitative (numerical) data. You might get many responses from your sample that you’ve tailored both the scope, and sample size/diversity for maximum accuracy! What now? Now that you have the data, it’s time to interpret it. Sometimes the media or software you are using would do this for you. If not, take notice of these three terms: Mean, Median, and Mode.  These are what are called “Measures of Central Tendency”, and are used in statistics. If you want to know what most people in your sample are responding, while avoiding fringes; these might be useful to you. [1,2]

Mean is the average of the group of scores you get back. All numbers/responses being equal, this is taking all of them and finding the average response. You do this by adding up all the scores, and then dividing by the sum of the scores. [1,2] It looks like this:

  • Scores: 1, 3, 5, 3, 8. Mean (Average)= 1+3+5+3+8, then dividing by 5 (the number of scores) to get 4.

Median is taking the middle value or score when the responses are arranged from lowest to highest.  [1,2] This gets you a representation of the “middle guy” in the group, and looks something like this:

  • Scores: 1, 3, 3, 5, 8. Median= 3.

Mode is the score that occurs the most within your responses. When you want to see which exact response was chosen over the others, you can look at mode.  [1,2] It looks like this:

  • Scores, 1, 3, 5, 3, 8. Mode= 3. 3 was chosen twice.

 

Tip! Use the measure that gives you the most out of your self-report study! Mean (Average) is the most common you will see and is well liked for easy data output. Mode is when you are curious about the dead center respondents in your sample. Median is what you want if you are curious about the popularity of a specific answer being chosen.

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Oh no! Response Bias:

You’re doing great! You have your sample, you have your scope and representative size/diversity, and now you even have your quantitative measures of central tendency! What could go wrong?

Well, sometimes the people responding. Their bias, or factors that influence how they pick selections in a self-report study, can give us skewed or inaccurate results. Sometimes we are able to adjust our self-report study ahead of time (by wording questions a certain way) to mitigate this, and other times it is simply a part of it. Keep in mind that when ever someone is responding to a survey or poll, it is their interpretation that makes up the data; it is not a direct observation of reality. [1,2] Here are some types of biases that you should be aware of:

Self-Serving Bias: This is when successes are attributed to internal factors (themselves) and failures are attributed to external factors (others). [1,2]

  • Example of a question susceptible to Self-Serving Bias: “Do you feel as though you have been passed over for a job for someone less qualified than you?”

Acquiescence Bias:  This is when respondents say “yes” based not on the question, but rather on the favorability of that response (even though it may be anonymous) to the studier.  [1,2]

  • Example of a question susceptible to Acquiescence Bias: “Look at this pic! Am I pretty today? Yes or No!”

Extreme Responding Bias: This is where respondents prefer to pick the most extreme responses possible from a selection. (ie. Something is “literally the best/worst!”). [1,2]

  • Example of a question susceptible to Extreme Responding Bias: “On a scale from 1 to 10, how good was that episode of TVSHOW?” 10! 10! 10! 1! 10!

Social Desirability Bias: In this one, people respond with the most socially appropriate (or inappropriate) answers that conform to the expected desirability of the group or studier. [1,2]

  • Examples of questions susceptible to Social Desirability Bias:  “Do you give to charity? Yes or No”, “Do you ever have rebellious instincts?? Yes or No!”

Do you see how these biases may affect the interpretation of data? Keep them in mind!

 

Tip! Know your audience, and know your questions. Even one favorable (or unfavorable) word in a question could get your respondents to reply according to these biases. Think about what type of biases may be expressed when answering your questions.

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Get it Valid and Reliable:

There is one more important thing when you are studying a topic in social science: Validity and Reliability. These are factors that the person studying and presenting the self-report study should build in as best as possible before sending out their self-report materials to the world. These factors are what you use to make sure that you are studying something real, and that you are studying it accurately! [1,2]

Validity is the ability for a test/study to measure what it is intended to measure.  An example of this might be, if you are trying to study something like people’s opinions on a specific topic, does your question cover it, and is that question worded to target the topic specifically? [1,2]

  • Example: We are studying whether people enjoy the taste of chocolate. We ask “Do you enjoy the taste of chocolate?” 76% say yes! So long as everything is defined and specific, we could call this valid. 76% of respondents enjoy chocolate.
  • Non-Example: Whether people enjoy the taste of chocolate. We ask “Do you like sweet foods?” 84% say yes!, and in our study we conclude that that 84% of people enjoy chocolate. Wait a minute. Was that our question? Was our question tailored to fit the validity of the study? We used Sweet in our question, but we concluded on the factor of Chocolate. This is not valid.

Reliability is the ability of our test to yield (nearly) the same result each time we test with it. If we are able to test a sample with these questions, and provide an alternative test (on the same topic), we would get similar responses both time. The reason we need this is to be sure that it is not a fault or mistake in the test that is giving an inaccurate conclusion. Sometimes biased-wording, text errors, or jargon, can lead to responses being skewed or erratic. If 2 tests, or the same test twice, can get stead and similar responses from the same population, then we know that variability in responses is based on the respondents, and not our questions. [1,2]

  • Example: If you run the Chocolate Preference Test twice, and the first set of responses equal 80% while the next equals 81%; this is as close to reliable as you might be able to expect.
  • Non-Example: If you run the Chocolate Preference Test twice, and the first set of responses equal 17%, while the next equals 54%; there is something wrong. Assuming this is the same sample or even population, you might want to look at your test as a factor which influenced results incorrectly.

Both of these methods assure that you, the designer of the study, are not including factors that could effect the results you get. You want your results to match the respondents, not artifacts (unrelated data) embedded in your questions.

 

Tip! Test and re-test. If you have an audience, rephrasing questions on the same topic and presenting them again may get you a better picture when you keep validity and reliability in mind.

Questions? Comments?

 

References:

  1. Wood, S. E., Wood, E. R., & Wood, E. R. (1996). The world of psychology. Boston: Allyn and Bacon.
  2. Cooper, J. O., Heron, T. E., & Heward, W. L. (1987). Applied behavior analysis. Columbus: Merrill Pub. Co.

Photo Credits: https://stock.adobe.com, http://www.unsplash.com (Luis Llerena, Kate Serbin)