• Bibtex: @bryan2018
  • Bibliography: Bryan, C. J., & Rudd, M. D. (2018). Nonlinear Change Processes During Psychotherapy Characterize Patients Who Have Made Multiple Suicide Attempts. Suicide and Life-Threatening Behavior, 48(4), 386–400. https://doi.org/10.1111/sltb.12361

Example citation

Individuals with multiple suicide attempts have a tendency to ‘get stuck’ in states of more intense suicide ideation, whereas individuals with no or one attempt stabilize at a state of low risk

Key takeaways

  • n = 76 (active duty US army soldiers)
  • Participants received brief CBT for acute suicide risk
  • Multiple attempters (42.1%) / first-time attempters (43.4%) / ideators (14.5%)
  • They used only item 9 from the BDI to assess suicide ideation.
  • Multiple attempters showed more of a cusp catastrophe pattern than did first-time attempters or ideators, but it’s not as clear as Figure 2.
  • A cusp catastrophe strucutre is found when a cubic effect is significant, and a significant bifurcation parameter in the model, both of which should contribute beyond a linear/quadratic model fit.

All three groups had attractor set points at a low level of suicide ideation (x < 0.35), which suggests that, regardless of suicide attempt history, suicide ideation tended to be drawn toward and stabilize at a relatively low-risk state.

Multiple attempters also had a second attractor set point at a high level of suicide ideation (x3 = 2.25), however, indicating that suicide ideation tended to be drawn toward and stabilize at a relatively high-risk state as well.

Consistent with a cusp catastrophe model, in between these two stable states was a repeller set point from which suicide ideation was pushed away (x2 = 1.65), which indicates that suicide ideation tended to be unstable at moderate levels of risk.

Refs to read:

  • Wyder & De Leo, 2007
  • Witte, Fitzpatrick, Joiner & Schmidt, 2005
  • One of these is NSSI: Armey & Crowther, 2008; Armey, Nugent,&Crowther,2012;Butneretal., 2015; Clair, 1998; Hufford, 2001; Zeeman, 1976

So for multiple attempters, there are several points along the X-axis where the predicted change score is 0. This indicates that there are multiple “stable states”.

Negative slopes suggest an attractor set point (i.e., stable states), whereas the positive slope suggest a repeller set point (i.e., an unstable state)