Virtual View: results experiment 2

The analysis of the second experiment has taken a long time. At first there appeared to be no significant results on any of the variables, except on the heart-rate during the cognitive stress task. So I consulted different people with a degree and research experience and asked for help. I’ve really learned a lot from them. They all have different approaches and ways of working so I’ve picked out all the good tips and insights. My thanks go to Sarah, Malcolm and Marie. The latter is a researcher at Tilburg University, her knowledge of statistics dazzled me. She is the one who recommended a different analyses which has yielded more significant results.

Research questions

My main questions for this experiment were: Which type of stimulus results in the most stress reduction and relaxation? And which stimulus produces the highest heart-coherence? As I want the values on that variable do drive my landscape animation.
To test these questions I used the following dependant variables: BPM, heart coherence,
later I introduced heart-rate variability calculated from inter-beat interval, self reported stress and self reported relaxation. These were measured during the baseline measurement, the cognitive stress tasks and the stimulus sets.
The independent variables are: stimulus set 1 with 12 landscape photographs and synthetic nature sounds, stimulus set 2 with more abstract landscapes styled by me with the synthetic natures sounds in the background. Stimulus set 3 consisted of 12 photographs of kitchen utensils and a soundtrack of someone preparing a salad. The expected direction of the variables will be explained below.

Analyses

After struggling for some time with the non-significance of the variables in the different sets I discovered that the randomisation of the sets hadn’t been ideal. There were 33 participants who viewed the sets in 6 different orders. On top of that the group size per order was different. Some groups were only 4 participants, others 10. This is something I’ll have to take into account in my next experiment.
I used a repeated measures analyses. On my first, non-significant results, I used my baseline measurement as a covariate. Marie said that wasn’t the way to go. So I used just repeated measures where the baseline is just the first measurement, no covariates. And I did post hoc analysis (Bonferroni) to see the differences between the set results.
This is an overview of the results:
Results overview
Sarah made this clear lay-out of the research results compared to the expected results.
As you can see from the blue results the subjective stress measurements are significant compared to the baseline for all three stress tasks. For the first stress task (note this task isn’t connected to set 1, it is just the first task after the baseline measurement) the difference in heart-rate is significant during the stress task. There is also significant difference in HR during the landscape set. The kitchen utensil set heart-rate is also significant. Even though the heart-coherence is has the right direction non of the changes are significant. There are also no significant differences between the subjective relaxation questionnaires.

On Sarah’s recommendation I also looked at correlation between all the variables. That is very interesting as it reveals relationships between the variables. As the subjective relaxation questionnaire didn’t show any significant results I was curious to see how it correlates with the stress questionnaire. There should be a significant negative correlation between the two. And there is, it is especially strong for the baseline stress measurement and all relaxation measurements. On the other hand there was no correlation between subjective relaxation and heart-rate, a lowering of this value may be considered an indication of relaxation. All in all the relaxation questionnaire doesn’t give convincing results. There was a very strong correlation between heart-rate and heart-rate variability. In fact too strong, as Sarah pointed out they measure the same thing so it has no use including this variable in the results.

First set

As the stress stimulus was strongest the first time (view below) Marie advised me to do an analyses on the first set that was shown after the first stress task, independent of what kind of stimulus set it was. This was the distribution: set 1:    shown 11 times; set 2: 14; set 3: 8. The results from this analyses completely matched the other results. Heart-rate and heart-rate variability are significant (this is of course an average of all three sets shown), heart coherence and self reported relaxation were not. There was no interaction effect between the set shown and either the heart-rate or heart-rate variability which suggest that the order has no effects on the results.

Graphs

Stimulus overview

I made some manual graphs to see the effects of the stimuli on heart-rate and heart coherence side by side. There is no significant difference between the pictures in the three sets. For me it is still nice to see the difference between the pictures. The graph is done manually in Photoshop.

Stimuli used

HRV

After getting advice from Malcolm  about the results he suggested I calculate heart-rate variability from the inter-beat interval values that I’d logged. Heart-rate variability is known to correlate well with stress (negative) and relaxation (positive). So that’s valuable information to add to the results.
I wrote a script in Processing to calculate and visualise the HRV for the whole experiment divided in a 5 second windows. The white line is the baseline measurement, the red lines are the stress inductions and the green lines are the audiovisual stimuli. You can tell from the image that the stress induction has some effect.

HRV results
Looking at my correlation table however there is only a significant negative correlation between the baseline subjective stress measurement and the HRV. Neither the other stress measurements nor the subjective relaxation measurements show any correlation.
It is hard to tell from the image but the photo realistic landscape set has a significant difference from the baseline measurement. The third set is almost significant (p = .054).

Conclusions

The first conclusion should be that the differences between the stimuli in the sets are small. There are significant* differences in average heart-rate between the sets (68,26 (baseline); 66.46* (set 1); 66.75 (set 2); 66.32* (set 3)). But the differences are really small. There is reduction in all the sets. Set 3, the kitchen utensils has the lowest average.  The set isn’t very stimulating which might explain the low heart-rate. This conclusion is also backed by the fact that the results from using only the first set shown are comparable to when working with the individual sets.
Heart coherence, which I want to use for driving the animation and to trigger the interaction with the installation showed that the styled landscapes with sounds had the highest heart coherence average but the results were not significant.  It does not seem a good measure for pure relaxation. Heart coherence is a difficult term but this description gives a good indication of the different aspects of this state: In summary, psychophysiological coherence is a distinctive mode of function driven by sustained, modulated positive emotions. At the psychological level, the term “coherence” is used to denote the high degree of order, harmony, and stability in mental and emotional processes that is experienced during this mode. (From The Coherent Heart p. 12, Mccraty, Rollin Ph et all, Institute of HeartMath). On page 17 of that document it states that: “In healthy individuals as heart rate increases, HRV decreases, and vice versa.” As HRV and coherence are closely linked the same is true for heart coherence. Even though heart coherence is much broader than relaxation is also encompasses activation of the parasympathic nervous system which is also a marker for relaxation. Important in heart coherence is the inclusion of positive emotions. This is what I try to evoke by using landscapes based on generally preferred landscapes.
The Virtual View installation should provide a relaxing distraction for people in care environments. Cognitive states that relate to this goal are soft fascination and a sense of being away as introduced in the Attention restoration theory (ART) by Kaplan and Kaplan. I’m guessing now that heart coherence might correlate with those cognitive states. This is something I will explore in the next experiment.

The stress task was perceived as stressful judging from the subjective reports. These findings are partly backed by the physiological data. Only the heart-rate of the first stress task differs significantly from the baseline. Our goal by introducing a stress task was to create bigger differences in heart-rate. For that to be successful the stress task should really produce stress. Although people reported feeling stressed we can’t measure it three times in a row. So for the next experiment I’ll work with 3 groups who will all get only one stress stimulus and one landscape stimulus.

All in all this experiment doesn’t prove that my styled landscapes with synthetic nature sounds create the most relaxation and heart-coherence but the results neither prove that they don’t. So for the next experiment I’ll continue with the styled landscapes and introduce animation.

Virtual View: designing the first experiment

I had an idea what I wanted to research in my first experiment after reading the different articles. Looking at the end users, frequent visitors to hospitals and the chronically ill, I want the final piece to be first and foremost a pleasant and relaxing experience. It would be nice if there was an actual physical change that can be measured. The piece should have a stress reducing and restorative effect too. This can be both a subjective experience and a quantified measurement in form of heart-rate and heart coherence. And there are of course the landscapes and the sounds that should induce these states.

So how do you convert these goals into an experiment design? You follow a course and you ask people who have a lot more experience with designing psychological experiments!

I started out with way too complex idea. Combining stress induction and testing stimuli effects in one experiment. I’ve had great input from my professor Hein at the Open University, Sarah (PhD in psychology), Ilia (developer of stimulus creation software) and Malcolm (information scientist and psychologist) from Heartlive. Discussing my idea’s with them helped me a lot.

Together with the students I looked at the type of landscapes and sounds that would be most valuable to explore for the Virtual View installation. We’ve decided to test 5 sets with 6 landscape images based on, among other things, the most preferred landscapes as defined by Ulrich. We also explore the mystery aspect of landscapes as outlined in the attention restoration theory by Kaplan and Kaplan. Each set of images has a sound to go with it. We use one contrast set of neutral hospital interiors accompanied with hospital sounds. Another thing we want to explore is non photo realistic landscapes. As the final piece will consists of computer generated graphics with a certain degree of abstraction we want to compare the response to abstract landscape paintings to the photo realistic material.

From the little research that has been done on the effects of (nature) sounds we’ve come to different combinations of running water and birdsong. These are the sets and sounds {in curly braces}:

a. Preferred landscape with water element {running water}
b. Preferred landscape in autumn {repetitive bird calls}
c. Neutral hospital interiors {neutral hospital sounds}
d. Landscape with deflecting views {running water and melodious birdsong}
e. Preferred landscape as abstract painting {melodious birdsong}

While experiencing the stimuli the participants’ heart beat will be measured with the Heartlive sensor. This will give data in the form of beats per minute, inter beat interval and heart coherence. A questionnaire on the perceived relaxation state will give insight into how the different stimuli sets are experienced by the participants and how they effect their sense of relaxation.

We expect combination d) the have the most positive effect compared to the other sets: higher IBI values, lower BPM values and higher coherence and the most self reported relaxation. The neutral hospital interior we expect to score the lowest means on those variables.

The sets and the images in the sets are randomised for each participant. The sounds are attached to one set. The participants will see all the sets (repeated measures). In the end we’ll be able to compare the different means of all the sets.

In the next blog I’ll explain more about building the experiment in EventIDE, the stimulus creation software I mentioned above.

Virtual View: Literature research

To get a better idea of which type of landscapes and sound have the biggest effect on (experienced) relaxation explorative research is necessary. At the end of January I started the research trajectory for the project. This is a collaboration with students from the minor “Active ageing” from the Avans Hogeschool. The three students are: Simone van den Broek, Carlos Ramos Rodriguez and Denise Hereijgers. There is support from two teachers from Avans: Marleen Mares and Lowie van Doninck.

Both the students and I started on a literature study. The main questions being:

Which visual elements in a landscape and what landscape properties have the most effect on relaxation and heart rate variability?

Which nature sounds and sound properties have the most effect on relaxation and heart rate variability?

Which emotional, physical and cognitive aspects influence stress and relaxation in relation to nature and landscapes?

To get the students started I made a list of tags to search on: Environmental psychology, Stress, Arousal, Heartrate Variability (HRV), Heartrate coherence, Relaxation, Landscape Aesthetic Quality, View, Landscape preference, Environmental aesthetics, Restorative environments, Attention restoration theory (ART), Stress recovery, Sounds, Birdsong, Stress Recovery Theory (SRT), Skin Conductancy Level, Effortless attention, Soft fascination, Aesthetic, levels of complexity, pattern, depth, surface texture, mystery within an environment, acoustic properties of animal sounds: smoothness, intensity, pitch, biophilia.

There are a couple of authorities in this field: Roger Ulrich and Kaplan & Kaplan. They have done extensive research on visual landscape preferences and restorative properties of nature. While the students search was broader my main focus was on environmental psychology. There has been quite a lot of research on the effect of viewing landscapes and natural scenes versus urban scenes. A lot less research has gone into the effect of nature sounds on health and relaxation.

From Human responses to vegetation and landscapes Roger S. Ulrich (1985)

An example of a preferred landscape from the article Human responses to vegetation and landscapes Roger S. Ulrich (1985). This is the kind of landscapes we’ll use in our experiment.

For me this was my first experience of reading scientific articles on one theme. Some of the findings conflict and I had a hard time combining the theories and findings into a coherent story. (A more official article will follow later.) One of the students suggested looking at the virtual aspect of the piece and how that influences the experience. I hadn’t thought of that so that was valuable input to explore. Most difficult is to draw the line at one point and start thinking about the actual experiment.

For our experiment we’ll be using sets of static images accompanied by existing nature sounds. Three sets of landscapes are based on preferred and fascinating aspects of landscapes as researched by Ulrich and Kaplan & Kaplan. One set of landscapes consists preferred landscape scenes but in the form of abstract paintings. A contrast set consists of neutral hospital interiors. For the sounds we have chosen different combinations of water and bird song sound. As a contrast we’ll be using sounds from a hospital ward. More about the actual experiment design and consideration in the next blog.