Wednesday, May 14, 2014

Tips for presenting your research to applied audiences

I have been talking quite a few of you keen folks recently on issues around your analyses and how to present them to an applied/non-psych audience. Sometimes I felt like a little parrot, so here are some key themes that came up repeatedly.

Think about your theoretical or practical question

A lot of you worry about whether an analysis is significant or not. What I would like to see is that you engage with a theoretical or practical question. Identify a problem or intriguing question that can be answered. As consultants, you address problems. State your problem or question clearly. Find relevant literature or show practical examples that speak to the issue. Then look at your data to get an answer to your question or hypothesis. Is the hypothesis supported - good. Say what it means and where to go next (implications). If the results are not significant - this can be potentially be as meaningful. Why did you not see an effect? Is it a problem of how you tested it or does it tell you something meaningful about the phenomena? 

A related set of questions goes along something like this: Do we need to do a mediation or is a regression fine? Shall we do an ANOVA or a regression? Again, my answer comes back to the theoretical or practical question. Choose the test that is appropriate for answering your question with the data at hand. Both mediation and regression can be meaningful, but they will give you slightly different answers (also note that mediation is based on regression ;) Decide whether an ANOVA or regression is better suited for the variables that you are looking at.

Think about the theoretical process

A few of you are exploring mediation and moderation processes. Fantastic! Mediation is about 'causal' processes. Think of a  flow chart: variable A 'causes' variable B, which in turn then leads to changes in variable C. With this in mind, can satisfaction lead to more gender and then to more helping behaviour? Probably not in this physical universe (unless you have discovered a cunning option for turning happy people into a different gender). In cases like this, it often seems that moderation is the better option - for example, is satisfaction related to helping behaviour and does this relationship differ for males versus females? 
Can satisfaction lead to more work performance which then leads to more health? Potentially, but you need to have a good rationale for it. Maybe a different ordering of your variables might make better sense in the context of your data.

How important are your results?

A few of you are exploring effect sizes (e.g., explained variance). This is great. Now the big question is what is a good effect size? Are 3.5% explained variance good or bad? Would somebody in your non-psych audience understand what explained variance means in the first place? 
Translate these figures into something that is meaningful to a non-psych audience. For example, if you make $30,000 a year - would 3.5% more money be a good incentive for you to act or not? Alternatively, if you measured a variable with relatively little consequence (e.g., the happiness with your new garden chair) and you are able to explain 50% of that variability - is this important or meaningful for a manager? So think about the size of the effect and whether it important or meaningful. Baseline: What can you say about the effect and its importance for management?

Should I use a graph?

Yes - But! Think about what is on your graph and what a non-psych audience can take away from it. Putting a messy scatterplot with lots of dots and a funny line into your presentation may not be particularly meaningful. There are other ways of presenting correlations or regressions. Think of a flow chart or a path diagram - these can be interesting options for displaying relationships between variables. If you want to talk about the messiness of social sciences, a scatterplot can be good. But explain the key message that each graph or figure or picture is conveying. Colourful images just for the sake of it are not good communication!

Other issues? Post something on the discussion board or send me an email. If there are more common themes, I will update this post.

Overall, I love how engaged you are with your work. It is really cool and I sincerely look forward to seeing these presentations come alive :D

Friday, May 9, 2014

Feeling connected to nature is linked to more innovativeness

Feeling connected to nature is linked with more innovative and holistic thinking about problems. Carmen Leong, John McClure and myself just published a study in which tested this relationship in two studies with Singaporean students.

We measured two different thinking preferences. First, the KAI (shortened from the Kirton’s Adaption-Innovation Inventory) distinguishes two kinds of thinking style. Some of us are good at working efficiently and can apply learned rules fast, without much effort. This type of thinking is called an adaption thinking style but is not very innovative. The opposing end of this thinking style, on the other hand, is innovation focused: it emphasizes thinking outside the box, doing things differently and creating new solutions to problems. The second thinking style AHT (abbreviated from Analytic-Holistic Thinking) differentiates holistic from analytic thinking styles. When people are solving a problem, holistic thinkers consider the whole problem within an overall system. They think in terms of the big picture, considering how all parts of a problem are related and how a single issue connects to all the others. In contrast, analytical thinkers break problems down into smaller components and work through them carefully. They consider the details and work on them, but pay less attention to the overall puzzle and to how the various components interrelate. Both types of thinking – analytic and holistic – can be useful: while it is sometimes better to go through problems piece by piece, at other times it seems more appropriate to consider how everything fits together and to address issues with a helicopter view.

When we linked these two instruments to a feeling of connectedness to nature, we found that connectedness with nature is positively related to both innovative and holistic cognitive styles. Singaporean students who are more connected to nature prefer both innovative and holistic thinking. This means that the more people feel connected to nature, they are more likely to be better at coming up with novel solutions (thinking outside the box) and also consider the bigger picture when solving problems. This is a novel finding that shows how people who feel a stronger connection to nature are also more innovative and see the bigger picture.



The underlying mechanism that drives these correlations is not clear yet. Carmen's reason for proposing these relationships was linked to people’s inclination to develop close relationships with others as well as with the natural environment. While people in general have a strong motivation to connect with fellow human beings, some are more strongly motivated to do so than others. Those who feel strongly connected to others may broaden their own perspectives: they consider how other people think and feel and see problems from other points of view. This is a crucial element of innovative thinking styles – seeing problems from somebody else’s perspective. It may be possible that people can show this sense of connection in relation not only to other people but also to nature. Edward Wilson has written about this motivation at length in his Biophilia hypothesis (see here for a review for a review of his great autobiography, here is a summary of research on biophilia). We applied the idea and hypothesized that it could also help us to understand differences in thinking styles. We also believe that the way we think with a helicopter view is very similar to the way things work in nature. Holistic thinkers, for instance, place emphasis on the interconnectedness of ideas within a system; and our understanding of nature teaches us that everything in it (life cycles, ecosystems, etc.) is interrelated. Those who feel a greater connection with nature will also think in terms of the big picture. Our study is an important first step in this direction, however, we need more systematic work that explores the underlying mechanisms directly.

The study was based on a single time point in two separate samples, so we cannot draw any causal links from it. Yet, the pattern suggests that getting out into nature and appreciating nature's diversity and beauty may do you lots of good, not just improving your health and reducing stress, but also helping you to become more innovative and a big picture thinker.

Get off your chair and go for a walk now :D

If you want a copy of the paper, please get in touch via email or this blog. Happy to send interested people a copy.

Tuesday, May 6, 2014

Political correctness gone mad: The issue of the 'racist' survey in Auckland

Sad to say, but political correctness has gone mad and is undermining important social research that can help us to make society better. The issue centres around a recent survey sent out by Auckland City Council to members of the public in some suburbs that have high percentage of migrants.

The survey asked people to respond to various questions about how they feel about people from other ethnic and cultural groups. The issue is around the so-called feeling thermometer. It is a simple scale, typically ranging from 0 - 100, where people are asked how warm or cold they feel towards various social groups or targets. It has been a staple of social science research at least since the mid-1960s. The earlier use was in the context of forecasting election results (e.g., do people feel hotter or colder towards a party or candidate), but it worked so well that it has been used to evaluate attitudes towards all sorts of social groups in society. It is a cheap and efficient way to gauge public opinion about various social groups in a straightforward and reliable way. It is 'bang for bucks' if you want to find out about the levels of support for various social groups. 

Some members of the public and the council in Auckland are offended by these questions and label them racist. Some council members even want to prohibit similar kind of research in the future (see the remarks by George Wood, the North Shore councillor). 

My simple question to George Wood and other people outraged by these questions is: 
How are you going to plan policies and make decisions about ethnic relations, if you have no understanding of the intergroup relations in your community? 

Let's face it - NZ  is one of the most diverse country in the world and has pretty positive race relations (and this is great and we should be proud of it), but at the same time the levels of discrimination against migrants has increased over the last decade. A recent study by Ricci Harris and others from Otago found that racial discrimination against Asians (as a broad summary category) has increased from 2002 to 2006. More importantly, these levels of discrimination increase mental health and physical problems. This is costs to the tax payer!

NZ is one of the most diverse countries in the world (UN International Migration Report, 2013)

I was involved in a government contract project with colleagues at Victoria University of Wellington and the Centre for Applied Cross-Cultural Research a few years ago, where we looked into the intergroup relations in New Zealand depending on the number of recent migrants in a neighbourhood. What we found was that there was a relatively complex relationship. New Zealanders view migrants relatively positively overall, but only up to a point. Once the number of migrants reached a certain threshold, the perceptions became more negative. These complex patterns can not gained in any other way, apart from asking straightforward questions in general population samples. These findings have significant policy implications: Where should you settle new migrants? What strategies can we implement to counter this deterioration of community feelings? How can we provide better support to groups affected by discrimination? 

Put simply: you cannot have sound policy and useful political decision-making without understanding the issues! 


The survey questions that are creating this debate are a sensible and efficient way of gauging trends in a larger population. We need MORE of this research, not less! We need more SERIOUS attention to this type of social science research by politicians and decision-makers! Councillors talking to their constituencies and getting opinions from self-selected individuals does not and cannot replace sound scientific research in general population samples. The recall and the ill-focused debate that this has created is a significant step backward for New Zealand. The costs for New Zealand will be much larger than the costs of re-calling these surveys. It is a sad moment because we are taking all the wrong steps that will not help us to address the real issues of racism in our society.