psych

Interpretation in Therapy

/ Chris Sawyer, M.Ed.,BCBA / Leave a comment

Imagine for a moment, the process of therapy. It is a give and take where the participant wants change to occur, both in themselves, and in how they interact in the world. Something in the past has not gone as right as they’d like, and this process is meant to help them explore a better path ahead. Imagine also the clinician is in the room with them, listening intently as they speak about their experiences and works on the formulation of hypotheses to explain the client’s behavior both in and outside of therapy. In the therapy setting, even listening to these stories and relations of what happened in the past, the clinician is still limited in their full understanding of the information and experience. They do not have enough information, even from detailed stories, to come to a full conclusion.

In an experimental setting, a behavior analyst might find ways to mimic the natural environment, and contrive similar situations and stimuli for the client to engage with in order to get more information. They may try to manipulate the environment as best they could to see how the client responds to simulated contingencies. It could be roleplay. Something close to the original but not exactly that, something controlled with just enough of the original event to elicit similar behavior. It might even come close, and shed more details on what factors maintain certain behavior patterns. Progress. You would not want exposure to something that was expressed in confidence and trust, especially something fearful or aversive, to be presented without preparation or complete consent. It would be carefully chosen, described, and all features of the design and presentation would be agreed on. Progress would grow from mutually prepared steps.

But there is also a part that is somewhat subjective on the part of the clinician. Even if they did a great deal of functional analytic work on both indirect assessments, through interview, and direct assessments, with an experimental scenario, an interpretation is necessary. In fact, it’s owed to the client. They want to have an explanatory system for what is going on, and what can be done to make things better. It needs to tie in and make sense with what they have told, and the experiences they related. It is the duty of the clinician to be as careful as possible with the information they have received, and made the best hypotheses, not out of thin air, but from research and the functional and relational frameworks that could be understood from it.

Interpretation has been around a very long time in psychology. From the old Freudian psychoanalytic methods, interpretation was a great deal of the process. A story, or memory, or dream would be related to the psychoanalyst, and from that there would be an interpretation based on what the analyst saw in the subconscious of that individual. Sometimes it was helpful. Sometimes it was not. Since then, the field has been split on those specific methods of interpretation. In behavior analysis, those intuitive leaps have largely been set aside for more concrete environmental events and not hypothetical subconscious features. A person’s environment, including all the people and experiences they have been affected by, are what behavior analysis largely deals in. There is a focus on the outer world, the experiences that shaped an individual, that is said to have more scientific bearing than trying to guess at a hypothetical construct of subconscious from another person.

In behavior analysis, we prefer to look at the longer behavioral patterns as having more predictability to them. When we see a long term pattern of behavior, it makes the process of contriving changes in the person’s environment more straight forward. We can introduce a new variable and see the change. If a person’s behavior is erratic over a long period, with a great deal of variability, it makes it all the more challenging to know what new change has any effect, if at all. Stable behavioral traits, and patterns, give something to base interpretation of results off of. It’s a baseline. Using a baseline is also helpful in interpretations as well. Think of it as the start of a story. The baseline is the opening of the therapeutic story. Imagine a 10 chapter story. This is chapter 1.

Next comes the data. In behavior analysis, it is the measurable and observable which is trusted most, but even someone relating a story of a past experience can be measured and observed when we make the features of that related information salient enough to test. If someone says they have trouble ditching cigarettes, we could ask how many they have a day, determine a baseline rate, and go from there. Changing variables onward, based on that daily average, can give us information which is observable and measurable (fewer cigarettes smoked). Stepping away from that example, let’s imagine the behavior is more anxiety based, perhaps avoidance of certain situations, people, or information. While we probe on past experiences we may learn something to base our treatment on. Also, during this period of probing and hypothesizing, there may be more uncovered. Information that was not salient before might pop up in the information related by the client.

In certain psychological traditions, this is the end. Catharsis is what it was called. Information that was deeply buried, eliciting a strong emotional response in therapy, was seen as curative in itself (that will be another topic in the next post). To many, it does feel that way. It feels like a relief. In behavior analysis, however, we try to take it a step further. The uncovering of a past trigger, or antecedent, is valuable. Absolutely. But then we ask, does that change the behavior we are targeting now? Does that expression in therapy, by itself, make the avoidance diminish? It may, but in many cases, it takes the behavior of the client afterwards to make lasting change and growth. But, we have causal information. Our hypothesis is stronger. We can use that in our framework for behavioral change and success. That is the next step in the therapeutic interpretation, the story, and let’s call that chapter’s 2-5. We have now determined a pattern, and have started an intervention to it.

Next, comes analysis. Imagine over the course of the following weeks we see a broader lasting change. Let’s say that when the new therapeutic change was put in place, and the behavior we wanted to see drop actually dropped in the long term, we can assume there is a degree of control there. The therapeutic technique seems to work. Now, we can’t say it works for everyone. We can’t say it works all the time. We can’t even say that if a bad day hits with all the old triggers for the maladaptive behavior, that it would not return. What we can interpret and say is that, given the situations we have tried here, we have a level of control that can be seen, and hopefully, the client has been happy with. It delivers the wind down of the process, which may lead to even more changes and tweaks along the way. There may be several more adjustments, different treatment options, different environmental changes that stem from. Let’s call this chapter 6-7. The story is not over.

Our interpretation here is verbal. It is a narrative, a story, an explanation of complex behavioral, neurological, and environmental change that is summed up in a way that makes sense to us. The analyst and the client can agree on what the important factors are, and the change is spoken of in a way that the client can understand. If the clinician values the use of an interpretation, they won’t over use scientific jargon if it’s unnecessary. A word like reinforcement might be key, but it would be used for the purpose of relating a specific useful piece of information within the interpretation. The interpretation isn’t magical either. It doesn’t solve the situation in itself. It is chapters 8-9. It gives an account of a behavioral pattern that has been explored, and changed, but without the false promise of that change lasting forever. When it is related to the client, they may understand how their past experiences, their environment and reinforcement or punishment history affected them, and with the intervention, changed in a better direction. The interpretation can be valuable to them to that degree. It codifies a type of behavioral transformation, a change, a growth, a learning experience. But we have to be very clear that this interpretation is not final, or complete. When looking at the lifespan of an individual, behavior is what they do from the start of life to the very end.

Chapter 10 doesn’t come until the end of a lifetime. There is no way to conceptualize the finality of a person’s behavior without the whole story. This is largely outside the scope of therapeutic interpretation, but is important to it. It is always ahead, which means that the therapeutic interpretation maybe complete in the short term, but will necessarily never be in the long.

Thoughts? Questions? Comments? Leave them below.

References:

Cooper, J. O., Heron, T. E., & Heward, W. L. (2020). Applied Behavior Analysis. Pearson Education Limited.

Dougher, M. J. (2000). Clinical behavior analysis. Context Press.

Madden, G. J., & Dube, W. V. (2013). Apa Handbook of Behavior Analysis. American Psychological Association.

Image Credits: pexels.com

Getting Back Up After Failure

/ Chris Sawyer, M.Ed.,BCBA / Leave a comment

Failure is a tough topic to bring up but a necessary one. When we are in it, it’s all we can think about. When we are past it, we often do not want any further reminders of it. Failure, behaviorally, and psychologically, is a part of everything we do as a variable, and factors in to every future strategy we use. It is a part of our past that defines how we interact with the future. In a previous writing I discussed “Overcoming the Fear of Failure”, but this one will be about what to do when it happens to us. How do we move on? How do we grow from it? How to we set our future expectancies to do better? To what do we attribute failure to? All of these and more are necessary to making each failure a stepping stone to a future success, or else we might find ourselves in a loop generating ever worse strategies. Instead, we need to learn to get back up. Let’s talk now about some of the research we have on the topic and how we might navigate failure and find motivation from it.

Mastery Orientation vs. Learned Helplessness

When it comes to deriving motivation from failures, both big and small, the strategies that we develop in childhood have a great deal of influence on our current behavior. You may have heard of the term “learned helplessness” before, which describes a pattern of behavior of low motivation and outputs after repeated failures. The individual receives so little reinforcement following their actions that they simply do not continue to try. Diener and Dweck (1978) popularized these concepts in a study on youths that they split into two groups based on patterns and strategies that they observed without being taught. They found that some children when faced with repeated challenges and varying degrees of failure would either consistently give up, and reduce responding, while others would re-assess and modify their responding based on the inputs of their failure. The researchers were very interested in the cognitive strategies that both of these groups displayed, all without any coaching, and determined that even at a very young age, there were clear distinctions on these two types by their ideas on their loci of control. A locus of control is a belief system that people use to determine whether they have control of outcomes, or if outside forces do. A person with an internal locus of control would see the results of their actions as largely based on their own actions and future control. An individual with an external locus of control would see the results of their actions as largely impacted by an outside force or their environment. Now, there is a part of this study that some consider a little unfair. No matter what answer the children gave to their respective stimuli at the start, they were told they were incorrect. How they responded afterwards largely correlated based on how they viewed their loci of control.

Mastery oriented individuals appeared to generally attribute their failures to a lack of effort or something they’d missed. Even at that age, their first reaction focused on pivoting and reassessing.

Learned helpless individuals tended to attribute the failures to the situation as largely beyond their control (in this case, without knowing it, they were technically right as far as the experiment was concerned).

So what happened?

Mastery oriented individuals kept trying, kept changing their responses based on feedback, and largely kept at the task longer than the other individuals. They showed no decline and became more sophisticated in their strategy use (which was eventually validated).

Learned helpless individuals tended to show a progressive decline in the use of good-problem solving strategies and began to include less sophisticated and poorer problem solving strategies. Ones that would be even less likely to work.

This model of attribution is still used to this day, but has a few caveats. Unlike this study, in the real world, people are not always one or the other. In many cases, and complex problems, it requires using multiple loci of control, but also understanding whether the factors we evaluate and learn from are stable (long term) or unstable (temporary). The stability of an attribution is its relative permanence as a factor. If you know you are good at jumping rope, meaning you have high ability, you have a stable factor to consider your next success with. But, if you attribute jumping rope to how much effort your legs can put out, then the source of success is unstable—effort can vary and has to be renewed on each occasion or else it disappears. We’ll talk a little more about how effort and ability works in a second. The important part is that when it comes to evaluating our part in the grand scheme, the internal locus of control tends to help us perform better.  Let’s look at some examples.

It rained today and we got all wet. We hate that. What if it rains tomorrow and we don’t want to be rained on? Would a belief system around an internal loci of control make sense if we focus purely on ourselves and ignore the sky? Not very well. No matter how many strategies we might attempt based on our own feedback, we are unlikely to change the weather. On the other hand, a person using this internal loci of control might decide to travel away from the storm as a strategy, bring an umbrella, or wear a rain coat, which has some functionality for them but the rain still happens where they once were. Internal loci of control work best when we take into account our solutions but do not ignore the immutable environmental factors.

What about using an external loci of control on task performance? Perhaps we’d like to pick up three items off of our room’s floor within ten minutes. We might begin to generate all the reasons why we cannot, and how far the floor is from our fingers, and how many other factors there are between the items and the trash can, leading to very low performance on this task within a time frame. It’s the room that’s messy. It’s been messy for days now. So messy. So much mess too. What if we just pick up one thing then go back to bed? It’s still messy. Might as well not. Then, we’ve just effectively wasted time generating non-functional thoughts (poor strategy), and nothing was done (poor outcome). That isn’t helpful either.

Generally speaking, when it comes to our own behavior, within our own repertoires of ability, it is wiser to use an internal locus of control to conceptualize our potential impact on tasks and problems. When there are larger systems and unavoidable outcomes from the outside, it does not hurt to consider what lies in an external locus of control. We, as individuals, cannot control everything. But, as we see above, when faced with continual failure feedback, utilizing an internal locus of control early on can help us come up with strategies which mitigate the external circumstances and perhaps land us in a better spot. There is no harm in generating increasingly sophisticated strategies to put ourselves into better conditions and allow the external factors outside of our control to be managed from ever increasing positions of control and strategy on our part. Sometimes when failure comes, it comes after we thought we had a great strategy focusing on our own improvement and it just did not work.

How do we do it? How do we take back some semblance of control when the waves of failures keep coming?

Consider that the concepts of a locus of control, and how our actions impact our goals are called attributions, and have an effect on our future behavior and how we respond to challenges. When we attribute too much to external causes, it can lead us to decrease our attempts. When we attribute too much to internal causes, it can sometimes lead to more sophisticated problem solving, but blind us to other factors might be outside of our control and narrow our perspective too much.

Mediating these attributions not just in the moment of the first failure we come across, but those that follow can help us create a better perspective on our situation. We can also rely on our social circle, relay our experiences, to see if others can help us see what we might have missed and help our future strategies find better success.

  • Evaluate your current attribution and locus of control of the problem.
  • What are some ways we can evaluate our own pattern of responding and improve it? (Internal Locus)
  • What are some environmental factors that impacted our failure that our behavior did not change (External Locus)
  • How do we refine our strategy so that our next attempt can put us in a better position against those environmental variables if they happen again? Can we mitigate what held us back?

Purposive Behaviorism and Re-Training our Attributions

As individuals we can create systems that help us maintain a level of reinforcement to offset failure, and as social creatures, help create an environment of positive interactions that can help us both realize our achievable goals and find strategies to access them. Thankfully, we have concepts and theories at our disposal to explain the hows and whys. Let’s talk Purposive Behaviorism and how we can re-training our Attributional Theories.

If you’ve read my other works on this site, behaviorism itself is familiar to you. Purposive Behaviorism goes beyond the more mechanistic systems of reinforcement and punishment, stimulus and response, that you see in some of the more traditional theories. Yes, reinforcement is important to keep us moving forward. Yes, punishment (failure) can knock us back. But we are human, and complex beings, and a good analysis always takes that into account. From a purposive behavior standpoint, we use goals and work hard to achieve them. That is an intrinsic part of what it is to be human. In older theories by Edward Tolman, the term cognitive map was developed to describe how we do that. Our cognitive map is how we envision our path to our goal. We all have beliefs, unspoken ones, that a specific action on our part will get us closer to an intended consequence or goal. Let’s call these expectancies. They cover both the behavior we intend to do, and the goal we intend to achieve with them. It’s a roadmap. Tolman also believed that we learn from our successes and failures largely through a latent process. There is an automaticity to reinforcement that helps us pick up what has worked and set aside what has not worked, and integrating more cognitive and conscious strategies to what we have learned latently is the best way to move forward. Keep in mind not just what you can remember and consciously recall, but also what might have been learned latently from the experience.

When we map out our actions to meet a goal, we often give ourselves a time frame (hopefully realistic) in which to reach them. By giving our goals, or conceptual map of how we achieve them, a context in time we help judge how to act and what to expect. Generally speaking, acting now is always better than acting later unless you have a more advantageous use of time further along to position towards your goal. With our expectancies in mind, we have our actions, our goals, and our time frame. As adults, we also learn to discriminate effort from ability. Effort can be defined as the amount of energy or resources we must expend to progress towards the goal, while ability may be defined by our existing proficiency or skills that can achieve it. In most situations it is a combination of both effort and ability that help us reach complex goals.

Let’s reintroduce failure here. Let’s say that we mapped out our goal, we made our attempt to the best of our effort and ability, and we find that we simply did not meet success. Perhaps we even see repeated failure. It can be easy to get disheartened, and even travel down that path of learned helplessness, but we should do everything we can to avoid it. Let’s imagine that we did our best to conceptualize our locus/loci of control, and they were as accurate as they could be, but we still missed the mark. We tried, we failed. Let’s say our expectancy, our goal and plan to reach it, is still very important and we do not want to change the goal. How do we use our time most effectively now to get back up and try again? We need to re-train ourselves, and that means re-training our attributions.

Do we have the ability to achieve this next step in our goal? What did our failure show us?

Did we apply the necessary effort to achieve the next step in our goal? What did our failure show us?

Were our attributions on stability based around factors that were stable (ability) or unstable (effort)?

The combination of evaluating our ability and effort and attribute our failure and successes along these variables is key to knowing when something can be achieved alone, if further training, resources, or additional help from others is needed, and how to adjust our plans going forward to include these more sophisticated and evaluated plans that came from the experience. Failure here is a teacher. It’s not always easy to maintain effort after a failed attempt even if the ability was there. To retrain ourselves to analyze our attributions of the failure correctly, we must take some time to evaluate the factors. Use this tool from Dweck (2000), who we saw in that earlier study too, below to take a particular situation you might have been in the past, and see where the attributions fall.

Plug some of your attributions in the grid above and see where they fall. Do you think anyone else evaluating your situation might have a different series of attributions for it?

We tend to get the best results out of ourselves and planning ahead by attributing a reasonable portion our previous successes to internal and stable causes. What went right in the situation within our ability, even if there was an ultimate failure, that we can consistently do again? Example: I might not have won the race, but this was close to my best personal time yet.

When analyzing our failures, we can go wrong in attributing things entirely to unstable and external causes. Things that we see as completely out of our control, and leaves nothing for us to work and grow on. Example: I was going to go in to work today but then the roads were so busy and you know I can’t drive on busy roads…

The take away:

  • Turning failures into successes takes analysis of what happened.
  • Sometimes we analyze the situation well and can think of some improvements for next time focusing on our internal factors.
    • “Stable Dimension” attributions help us reflect on our ability and how to improve it.
    • “Unstable Dimension” attributions help us reflect on our level of effort and if we can improve it next time.
  • If we see many attributions leaning in the unstable or external direction, maybe it could take an extra pair of eyes to help us get a new perspective.
    • Reaching out to a trusted friend, or experienced advisor on the topic.
    • Re-evaluating the attribution by considering internal factors.
  • Learned helplessness can arise from attributing too much to external factors, avoiding evaluation of internal factors, leading to poor problem solving and less sophisticated goal directed behavior.

Getting back up after failure requires analysis of our actions, re-training our attributions to avoid learned helplessness, and consistent effort going forward.

What are some attributions you’ve thought about recently? Have the behaviors you’ve used to reach those goals been effective? Have they been ineffective? How has your belief system on the locus of control impacted the process? Have you utilized others to help you with alternate perspectives?

Comments? Questions? Feedback? Leave them below.

References:

Cooper, J. O., Heron, T. E., & Heward, W. L. (1987). Applied Behavior Analysis. Merrill.

Edward Chace Tolman. (2015). Introduction to Theories of Learning, 302–326. https://doi.org/10.4324/9781315664965-16

Hoose, N. A.-V. (n.d.). Educational psychology. Lumen. Retrieved November 11, 2021, from https://courses.lumenlearning.com/edpsy/chapter/attribution-theory/.

Molden, D. C., & Dweck, C. S. (2000). Meaning and motivation. Intrinsic and Extrinsic Motivation, 131–159. https://doi.org/10.1016/b978-012619070-0/50028-3

Schunk, D. H., Meece, J. L., & Pintrich, P. R. (2014). Motivation in education: Theory, research, and applications. Pearson Education Ltd.

Tolman, E. C. (1967). Purposive behavior in animals and men. Irvington.

Image Citations:

Title image: Getty Images/iStockphoto
Attribution Grid: Christian Sawyer, M.Ed., BCBA

Remembering the Pre-Aversive Stimulus

/ Chris Sawyer, M.Ed.,BCBA / 1 Comment

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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

/ Chris Sawyer, M.Ed.,BCBA / Leave a comment

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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

/ Chris Sawyer, M.Ed.,BCBA / Leave a comment

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

/ Chris Sawyer, M.Ed.,BCBA / Leave a comment

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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)