Attitude toward illness is one of the ten domains of context that we’ve documented in our work studying physicians’ skills at tailoring care to real patients’ needs. One thing that we often don’t appreciate is how important it can be for people to be able to explain their choices – not only to others, but also to themselves, in light of their past experiences and choices. We often experience our lives as unfolding stories, and we want those stories to make sense to us.
A recently published article in the journal Medical Decision Making looks at this (full disclosure: I am the editor-in-chief of that journal). In “My Lived Experiences Are More Important Than Your Probabilities: The Role of Individualized Risk Estimates for Decision Making About Participation in the Study of Tamoxifen and Raloxifene (STAR)“, Christine Holmberg and colleagues interviewed women who agreed or declined to participate in a trial of tamoxifen and raloxifene, medications that are used to reduce the risk of breast cancer but have potential side effects. These drugs appear to be underused, based on statistical evidence about the number of women who would, on the whole, benefit from them.
When they asked women about their decisions to join or decline the trial, they found that personal or family experiences with breast cancer and general concerns about the effects of taking medication were more important than information about the probability of breast cancer or side effects. The authors refer to this as “a decision-making process for or against STAR participation that was guided by personal experiences, attitudes, and beliefs.” Those who joined the trial and those who didn’t came to different decisions, but did so through similar considerations about their individual life context.
This work is in the tradition of decision psychology research by Nancy Pennington and Reid Hastie in what’s been called “explanation-based decision making” or the “story model”. Most often studied in jurors or consumers, the idea is that sometimes what seems to be important to people in their decision making is that they be able to explain their decisions – not only to others, but also to themselves. People want to place their choices in the context of their identity and lived experience, which is itself shaped by their past choices.
Combine these theories with work on “illness narratives” pioneered by Arthur Kleinman, and research on identity in health psychology, and the message is clear: no matter how “right” a choice may be on the evidence, it’s very hard for people to do it if it contradicts their personal story.
Physicians looking to engage with their patients need to be listening for these stories too.
Thanks for calling attention to a thought provoking study. I do have a question about a comment you made….You write “When they asked women about their decisions to join or decline the trial, they found that personal or family experiences with breast cancer and general concerns about the effects of taking medication were more important than information about the probability of breast cancer or side effects.” Wouldn’t information about the probability of breast cancer based on opting in or out of the trial have been unknown at the time of enrollment? Clinical trials, after all, are carried out when we don’t know which arm it better. In this case, participation meant randomization to either Tamoxifen or Raloxifen. If a subject opted out they could select either of those two treatments (or neither treatment) based on their personal preference, but without evidence that one is a better option than another. Wouldn’t the decision to participate then be based entirely on personal experiences and outlook (since there really isn’t any research evidence at the time of enrollment to inform the choice)?
Great question. In order to be eligible for the STAR trial itself, women had to have undergone a risk assessment (185,000 women did, and about 100,000 of them were eligible based on their risk), and they all received a report of their risk of cancer, the risks and benefits of the two drugs, and the risks and benefits of participating in the trial. So their decision to participate in the trial or not could potentially have been based entirely on probabilistic information (but wasn’t).