It is no news that we’ve all probably joked about ‘new year, new me’ and never fully followed through with our plans. It is not hard to recognize that those goals we set for ourselves are probably good for us, but for various (valid and mayhaps some inexcusable) reasons, things never pan out the way we intend for it to. There could be reasons within and beyond our control, different people may come up with different explanations, but one thing we know for sure is that committing to bettering yourself is never a smooth process.
Trying to get professional help for mental health related problems is arguably, if not harder, just as tough. Despite the amount of people experiencing mental health problems annually in the UK, only a small fraction of them actually seek help. This is concerning, since delayed treatment can result in lower remission rates and aggravated symptoms. But hopefully, just like with setting new year’s resolutions, through reflecting on thought patterns, feelings, and behavior, we will eventually figure out the bigger picture of ‘why’, and work towards effective action plans that actually reach people in need.
What we know about help-seeking behavior
What is it about people that makes them more likely to seek help? Is it an issue of trusting the treatment and believing that it works, or is it more of an issue of knowing how to seek help? Could it be due to a certain personality trait you have, and could it be related to gender? How about stigmatizing beliefs that the society may hold? Answer is, many different studies have already confirmed that these factors matter, but we are unable to say for sure that some of these factors still matter when we compare all of them against each other. Human behavior is multifaceted: subjective beliefs, social norms, external factors that are beyond your control, even the mere belief of how much you think you can control a certain behavior or outcome can all combine to influence behavior. To study all these aspects of behavior separately is almost as if you are cherry picking patterns you wish to see.
Plus, there are more technical reasons for re-examining the link between these factors and help-seeking behavior. Older methods of statistical analysis are limited in their ability to reveal nuances. There could be meaningful subgroups within a population that older methods are unable to pick apart: the factor that best predicts help-seeking behavior in one subgroup in the population might not predict help-seeking behavior in another subgroup to the same degree. For instance, how and why mental health education might only work on some people but not others. While we can spend long days framing a study around a bunch of these questions manually, newer methods such as decision trees can directly reveal these relationships without the need to intentionally look for them. And this is exactly what we did!
What we did
We partnered with Thrive: Mental Wellbeing, a company that provides digital mental health services, to explore the correlates for mental health help-seeking behavior on a wider scale, encompassing a range of demographic and psychographic factors and how they might affect each other. We used data from Thrive’s marketing survey from late 2022 to early 2023, focusing on residents of the UK at large. We have defined psychological help-seeking in more professional terms, including but not limited to psychotherapy, counseling, medication, talking therapies etc. Our variables of interest can be broadly split into two categories: demographic and psychographic.
- Demographic: age, gender, highest level of education, employment status, industry, annual salary; and
- Psychographic: personality, help-seeking beliefs, past experiences with mental health problems, experiences with help-seeking, mental health literacy, and digital literacy.
We simply threw all these factors at a decision tree algorithm, and let it work its magic. Crucially, we have also intentionally split the sample by gender to explore gender differences more explicitly.
Our findings
Our findings not only confirmed existing findings, we have also revealed more nuances of how difference factors relate to each other. One’s openness to recognize mental health problems was of utmost importance, followed by two personality traits ‘agreeableness’ and ‘emotional stability’, as well as mental health literacy. We also see how higher mental health literacy can compensate for more negative attitudes when seeking psychological help.
We also found marked gender differences in beliefs about mental health, calling attention to how seeking psychological help also intersects with gender identity. Women displayed a higher openness to help-seeking overall, which is negatively linked with the ‘emotional stability’ trait to influence help-seeking outcomes; while the ‘agreeableness’ trait is positively linked to influence help-seeking outcomes in men. While our interpretation is speculative, this could mean that women seek help based more on their vulnerability to stress, and men who display warmer, sympathetic traits have a higher tendency to honor their negative emotions and anxiety and hence seek help as they see fit.
Implications, and where to go from here
Our findings are very encouraging since most of the resulting factors are actionable through intervention and campaigning. While idiosyncrasies in personality and gender related factors tend to be more stable and are less prone to change, our findings align with previous literature to show that this is not a be-all and end-all to success in seeking psychological help, since more actionable factors also have the power to change help-seeking behavior — through mental health education and possibly increased self awareness, favorable outcomes can still be achieved.
A big problem with using newer study designs to verify existing research is the fact that there are realistically very few studies to cross-check our findings with. There are also technical issues specifically regarding the decision tree design, relating to our rather small sample size and the decision tree being rather sensitive to small changes in the data, such that the same decision tree may not be easily generalizable to other populations even within the Uk. Nonetheless, our study gives way to exciting new directions of research for a deeper understanding of help-seeking behavior, which can in turn inform more targeted interventions and campaign designs.
Key references
Ajzen, I. (2002). Perceived Behavioral Control, Self-Efficacy, Locus of Control, and the Theory of Planned Behavior1. Journal of Applied Social Psychology, 32(4), 665–683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x
Bird, M. D., Chow, G. M., & Yang, Y. (2020). College students’ attitudes, stigma, and intentions toward seeking online and face-to-face counseling. Journal of Clinical Psychology, 76(9), 1775–1790. https://doi.org/10.1002/jclp.22956
Henderson, C., Evans-Lacko, S., & Thornicroft, G. (2013). Mental Illness Stigma, Help Seeking, and Public Health Programs. American Journal of Public Health, 103(5), 777–780. https://doi.org/10.2105/AJPH.2012.301056
Roskar, S., Bracic, M. F., Kolar, U., Lekic, K., Juricic, N. K., Grum, A. T., Dobnik, B., Postuvan, V., & Vatovec, M. (2017). Attitudes within the general population towards seeking professional help in cases of mental distress. International Journal of Social Psychiatry, 63(7), 614–621. https://doi.org/10.1177/0020764017724819
Shahwan, S., Lau, J. H., Goh, C. M. J., Ong, W. J., Tan, G. T. H., Kwok, K. W., Samari, E., Lee, Y. Y., Teh, W. L., Seet, V., Chang, S., Chong, S. A., & Subramaniam, M. (2020). The potential impact of an anti-stigma intervention on mental health help-seeking attitudes among university students. BMC Psychiatry, 20(1), 562. https://doi.org/10.1186/s12888-020-02960-y
Venkatasubramaniam, A., Wolfson, J., Mitchell, N., Barnes, T., JaKa, M., & French, S. (2017). Decision trees in epidemiological research. Emerging Themes in Epidemiology, 14(1), 11. https://doi.org/10.1186/s12982-017-0064-4
Wang, J., Yuan, G. F., Shi, X., Tang, A., & Shi, W. (2022). Factors influencing attitudes toward cyber-counseling among China’s Generation Z: A structural equation model. Archives of Psychiatric Nursing, 40, 124–131. https://doi.org/10.1016/j.apnu.2022.07.011