Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2023 Jul 1.
Published in final edited form as: J Affect Disord. 2022 Apr 14;308:243–248. doi: 10.1016/j.jad.2022.04.033

Prospective Association of Psychological Pain and Hopelessness with Suicidal Thoughts

Elizabeth D Ballard 1, Cristan A Farmer 1, Jessica Gerner 1, Bartholt Bloomfield-Clagett 1, Lawrence T Park 1, Carlos A Zarate Jr 1
PMCID: PMC9133160  NIHMSID: NIHMS1800302  PMID: 35429526

Abstract

Background:

Early markers preceding suicide ideation (SI) may provide valuable information for both assessment and treatment. The glutamatergic modulator ketamine has rapid, transient effects on SI, creating an opportunity to observe potential antecedents of the re-emergence of SI. This analysis evaluated whether the interaction between two suicide risk factors—psychological pain and hopelessness—were prospectively associated with SI post-ketamine administration.

Methods:

Data were drawn from three ketamine clinical trials of participants with treatment-resistant major depressive disorder or bipolar disorder (n=108) with short- and/or long-term follow-up (three or 11 days). A random intercept cross-lagged panel model evaluated the longitudinal relationship between the correlated concepts, specifically whether the interaction between hopelessness and psychological pain was associated with future SI.

Results:

Psychological pain and hopelessness were not prospectively associated with SI in short-term or long-term analyses; rather, long-term analyses found that SI was associated with later psychological pain and hopelessness. Similarly, no relationship was observed for other suicide risk factors, including anhedonia, depressed mood, and impaired sleep.

Limitations:

Secondary analysis of clinical trial data not collected for this purpose; hopelessness and psychological pain were assessed via proxy measures from existing depression rating scales; the small sample size required a restricted statistical model.

Conclusions:

Psychological pain and hopelessness were not associated with the re-emergence of SI post-ketamine. These results may be due to limited variability in the data. The re-emergence of SI post-ketamine may also not follow patterns typically seen in non-pharmacologic contexts. Individuals with a history of SI warrant careful monitoring post-ketamine administration.

Keywords: suicidal ideation, ketamine, hopelessness, psychological pain

Introduction

Suicidal thoughts, behaviors, and deaths are a public health crisis. To date, research on suicide risk factors has been of limited benefit in lowering overall suicide rates. Indeed, although meta-analyses conducted over the last 50 years have repeatedly examined similar risk factors, little improvement has been observed in our ability to predict suicidal behavior (Franklin et al., 2017). As a result, new psychological theories of suicide have focused on an “ideation-to-action” framework, with the understanding that suicide ideation (SI, thinking about suicide) is distinct from suicidal behavior (acting on suicidal thoughts) (Klonsky and May, 2014; Klonsky et al., 2018). Such theories often examine SI and suicide attempts/death as characterized by distinct risk profiles. The frameworks can be used to isolate factors associated with the transition from a non-suicidal to a suicidal state, which is critical for developing targeted treatments for the suicidal crisis.

However, evaluating short-term antecedents for SI is difficult because researchers have a limited ability to determine which individuals will experience SI across a short period of time. In this context, clinical trials of the glutamatergic modulator ketamine provide a unique opportunity. Ketamine is associated with rapid, transient effects on SI in which individuals often have their SI completely resolve only to return within a few days (Grunebaum et al., 2018; Wilkinson et al., 2018). Because these clinical trials often include repeated measures of psychiatric symptoms across a range of domains, this research can also provide a framework to evaluate the antecedents of SI. Such an approach not only serves to evaluate specific suicide risk factors as potential early “warning signs” for a suicide crisis but can also point to potential factors for intervention that could prolong ketamine’s effects on SI.

Hopelessness and psychological pain are key psychological constructs associated with suicide risk that could be associated with short-term changes in suicidal thoughts. Hopelessness—broadly defined as negative expectations about the future—is one of the most commonly cited risk factors for long-term risk of suicidal thoughts, attempts, and death (Abramson et al., 1998; Beck et al., 1985; Smith et al., 2006). In addition, psychological pain—also described as psychache, psychic pain, or suffering—has appeared in the clinical literature for decades as a critical and necessary component of SI and suicidal behavior (Ducasse et al., 2018; Mee et al., 2011; Shneidman, 1993). Ideation-to-action theories of suicide risk, such as the Three-Step Theory (Klonsky and May, 2015), suggest that the combination of psychological pain and hopelessness co-occurs with SI. Both these constructs have also been evaluated using neuroimaging paradigms (Jollant et al., 2020; Katayama et al., 2019), suggesting potential neural targets for the prediction and/or treatment of SI.

This project sought to evaluate antecedents associated with SI re-emergence after ketamine administration. Building on the existing research literature, the hypothesis was that the co-occurrence of psychological pain and hopelessness would be prospectively associated with SI, but that SI would not be associated with future hopelessness and psychological pain. To determine whether these effects were unique to these constructs, the relationship between SI and other known suicide risk factors was also evaluated; these included impaired sleep, anhedonia, and depressed mood (Ballard et al., 2017; Pigeon et al., 2012).

Methods

Participants and Study Design

Data for this study were drawn from the active treatment arms of four inpatient, randomized, controlled trials studies conducted at the National Institutes of Health (NIH) Clinical Center in Bethesda, Maryland between 2006 and 2018 (NCT01204918, NCT00054704, NCT00088699; all trials were part of NIH protocol 04-M-0222). The studies included: the bipolar disorder (BP) trial, which comprised two substudies in which all participants were depressed at the time of their ketamine trial (Diazgranados et al., 2010; Zarate et al., 2012); the major depressive disorder (MDD) trial (Zarate et al., 2006); the mechanism of action (MOA) trial (Nugent et al., 2018); and the riluzole (RIL) trial (Ibrahim et al., 2012). The BP, MDD, and MOA studies were randomized, controlled, crossover trials of intravenous ketamine versus saline. The RIL study was a randomized, controlled parallel arm trial of intravenous ketamine+oral riluzole versus intravenous ketamine+oral placebo (i.e., ketamine was open-label). The MDD and RIL studies included only participants with MDD, and the BP study included only participants with bipolar disorder. The MOA study included participants with both diagnoses, though only a few had bipolar disorder, as well as healthy controls who were excluded from the present analysis.

All four studies followed very similar (and, in some cases, identical) methodology. Briefly, participants had not received psychotropic medications for at least two weeks before randomization (three weeks for aripiprazole, five weeks for fluoxetine). All participants were drug-free for the entirety of their respective study except for participants in the BP study who received therapeutic lithium or valproate (Diazgranados et al., 2010; Zarate et al., 2012). The Structured Clinical Interview for Axis I Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) was used to establish psychiatric diagnoses, and these were subsequently confirmed by the clinical team.

For the present analysis, participants (n=108) were male and female, 18–65 years old, and in good physical health. All participants had been diagnosed with either MDD or bipolar disorder; had received a ketamine infusion; had data for the Montgomery-Asberg Depression Rating Scale (MADRS), Hamilton Depression Rating Scale (HAM-D), and Beck Depression Inventory (BDI) rating scales; and had non-zero ratings on at least one of the primary outcome measures for at least two of the included timepoints. The MADRS contains an SI item, but all three rating scales were used to compute the Negative Cognitions score (see below). Exclusion criteria included pregnancy, nursing, and any medical contraindication to receiving ketamine. All participants provided written informed consent to a clinical trial, and the study was approved by the NIH Combined Neuroscience Institute Review Board.

Measures

SI was operationalized as the MADRS suicidal thoughts item (scale of 0 to 6). Hopelessness was operationalized as item 2 from the BDI (“discouraged about future”, scale of 0 to 3). Psychological pain was operationalized using a Negative Cognitions score that was empirically derived in previous research (Ballard et al., 2018). The Negative Cognitions score was selected because of its conceptual similarity to the constructs of psychological pain and psychache, as it comprises items from the MADRS (“pessimistic thoughts”), HAM-D (“guilt”), and BDI (“thoughts of failure”, “guilt”, “feelings of punishment”, “disappointment in self”, “self-criticism”, “increased crying, “worthlessness”, and “reduced sexual interest”). The combination of hopelessness and pain was expressed as their product. Three other empirically derived scores—Anhedonia, Depressed Mood, and Impaired Sleep (Ballard et al., 2018)—were used in the secondary analyses. To improve interpretability, each target variable was scaled by the total points possible.

Design

Participants responded to the questionnaires at 40, 80, 120, and 230 minutes post-ketamine infusion, as well as at Days 1, 2, 3, 7, and 11 post-infusion, depending on the substudy. Two sets of analyses were performed. The short-term analyses, which included data from all four original studies (n=105), used data collected at 230 minutes, Day 1, Day 2, and Day 3 post-ketamine infusion. The long-term analyses, which only included data from the RIL study (n=45), used data collected at 230 minutes, Day 3, Day 7, and Day 11. These timepoints were selected because they were nearly evenly spaced and therefore appropriate for the analytic model described below. Only data from the active treatment arms (no placebo/saline) were included in this analysis.

Analytic Plan

A simple correlation matrix would not suffice for this analysis because cross-lagged correlations from longitudinal correlation matrices do not provide an appropriate basis for inferring causality (Rogosa, 1980). Because the research question posed by this study concerned within-subject longitudinal relationships among correlated constructs, the random intercept CLPM (RI-CLPM) was selected (Hamaker et al., 2015). The RI-CLPM controls for within-subject stability by using autoregressive paths and assumes that individuals vary around their own mean. In the RI-CLPM, a positive autoregressive parameter indicates that an individual who scores higher than their personal overall mean at one timepoint would be expected to score higher than their personal overall mean at the following timepoint (Hamaker et al., 2015). Evidence in support of our hypotheses would be the presence of both a strong cross-lagged relationship between hopelessness and psychological pain and later SI in combination with a weak cross-lagged relationship between SI and later hopelessness and psychological pain.

A multiple-group analysis was initially planned for the short-term data because the database comprised several sub-studies with nearly identical design. Ideally, the invariance of the RI-CLPM parameters would be established across groups. However, due to the small sample size relative to the number of parameters, the multiple-group models did not reliably converge. For this reason, a primary analysis was performed for the full sample, and sensitivity analyses were performed separately within each study. The results of the primary analysis run within each study are presented in Supplementary Tables S1 and S2.

Given the limitations presented by the sample size, the RI-CLPM was simplified by constraining to equality over time the lagged and autoregressive parameters. Although this is common practice (Hamaker et al., 2015), the effect on model fit of these constraints could not be determined because the model with freely estimated parameters would not converge. However, there is no theoretical reason to believe that these parameters should vary over time.

Some data were missing; these data were assumed to be missing at random and were not imputed. Current American Statistical Association guidelines were followed in reporting raw p-values and 95% confidence intervals for the estimated parameters and avoiding use of the concept of “statistical significance” (Wasserstein et al., 2019); this is especially important given the small sample size of this study. Structural equation modeling was performed in Mplus Version 8.4 (Hamaker, 2018), and processing of Mplus output was performed using MplusAutomation (Hallquist and Wiley, 2018) in R version 4.0.2. The model syntax, based on that provided by Hamaker (Hamaker, 2018), is provided in the Supplementary Materials.

Results

Demographic information is provided in Table 1. The intraclass correlation coefficient (ICC) for SI was calculated as part of an exploratory data analysis in order to describe the within-subject stability of the rating. The ICC of SI was 0.71 [0.66, 0.76] for the short-term data and 0.62 [0.51, 0.72] for the long-term data.

Table 1.

Participant Demographic information

Short-Term (n = 105) Long-Term (n = 45)*
Mean (SD) Mean (SD)
Age 43.12 (12.36) 47.96 (12.33)
Baseline MADRS Score 33.78 (4.38) 33.93 (4.61)
N (%) N(%)
Gender, Female 52 (49.52) 19 (42.22)
Race, White 92 (87.62) 42 (93.33)
MDD Diagnosis 74 (70.48) 45 (100)
BP Diagnosis 31 (29.52) 0
History of Suicide Attempt 38 (36.19) 17 (38)
Open in a new tab

MADRS: Montgomery-Asberg Depression Rating Scale; MDD: major depressive disorder; BP: bipolar disorder

*

Three participants contributed only long-term data; the remaining 42 are a subset of the short-term sample.

Short-term Follow-up

The RI-CLPM had adequate fit to the data (Table 2). The autoregressive parameters for both SI and hopelessness/psychological pain were moderate (95% CI SI: 0.026, 0.47; H/P: −0.001, 0.49), indicating that elevation above the participant’s own typical value at one timepoint was only weakly associated with similar elevation at the next timepoint. The cross-lagged parameters were of substantive interest, as support for the hypothesized model would require a strong correlation between hopelessness/psychological pain and later SI in combination with a weak correlation between SI and later hopelessness/psychological pain. However, in the short-term data, both parameters were weakly positive and did not differ from one another (t = −0.15, p = 0.89) (see Table 2 and Figure 1).

Table 2.

RI-CLPM Results

Short-Term (n = 105) Long-Term (n = 45)
Estimate (SE) 95% CI Test Estimate (SE) 95% CI Test
Model Fit Indices
Chi Square (DF = 17) 36.51 p = 0.0039 14.172 (p = 0.6549)
CFI 0.972 1
TLI 0.954 1
AIC 2733.714 1129.063
BIC 2805.371 1177.843
RMSEA 0.105 [0.057, 0.151] 0 [0, 0.112]
SRMR 0.06 0.064
Parameter Estimates
H&P (Autoregressive) 0.246 (0.126) [−0.001, 0.493] t = 1.95, p = 0.052 0.52 (0.169) [0.189, 0.851] t = 3.07, p = 0.002
SI (Autoregressive) 0.246 (0.112) [0.026, 0.466] t = 2.2, p = 0.028 0.24 (0.136) [−0.027, 0.507] t = 1.76, p = 0.078
H&P → SI (Lagged) 0.151 (0.119) [−0.082, 0.384] t = 1.27, p = 0.205 0.054 (0.122) [−0.185, 0.293] t = 0.45, p = 0.657
SI → H&P (Lagged) 0.169 (0.084) [0.004, 0.334] t = 2.03, p = 0.043 0.378 (0.153) [0.078, 0.678] t = 2.48, p = 0.013
Difference in lagged parameters −0.019 (0.128) [−0.27, 0.232] t = −0.15, p = 0.885 −0.323 (0.179) [−0.674, 0.028] t = −1.81, p = 0.071
Open in a new tab

Note: CFI = comparative fit index; TLI = Tucker-Lewis fit index; AIC = Aikake’s information criterion; BIC = Bayesian information criterion; RMSEA = root mean square error of approximation; SRMR = standardized root mean squared residual; SI = suicidal ideation; H&P = hopelessness and psychological pain. Both models had 27 parameters. Model fit indices refer to the fit of the RI-CLPM as described in the methods, where the autoregressive and lagged parameters (respectively) are constrained to equality over time. For the long-term model, fit indices were at the boundaries because they are based on the chi-square, which was smaller than the degrees of freedom, indicating very good fit or inability to reject the null. Parameter estimates are standardized. The difference in lagged parameters corresponds to the test of the hypothesis that the difference in lagged parameters is zero. Short-term refers to endpoints of 230 minutes, Day 1, Day 2, and Day 3 post-ketamine infusion, and Long-term refers to endpoints of 230 minutes, Day 3, Day 7, and Day 11 post-ketamine infusion.

Figure 1. Key parameter estimates from RI-CLPMs.

Figure 1.

Open in a new tab

Diagram has been simplified to show only the autocorrelation and lagged parameter estimates with 95% confidence intervals (CIs) and does not represent the full model of analysis.

Long-term Follow-up

The RI-CLPM had good fit to the data, though the chi-square was smaller than the degrees of freedom for the model, which prevented estimation of some fit indices (Table 2). In the long-term data, the autoregressive parameter for SI was very similar to that observed in the short-term data (95% CI: −0.027, 0.507). However, the autoregressive parameter for hopelessness / psychological pain indicated that elevations at one timepoint were related to later elevations (95% CI: 0.189, 0.851). The cross-lagged parameters did not support the hypothesis, given that hopelessness/psychological pain was not associated with later SI (95% CI: −0.185, 0.293), while SI moderately predicted later hopelessness/psychological pain (95% CI: 0.078, 0.678) (test of the difference: t = −1.81, p = 0.07).

Secondary Outcomes

All model fits were good for the secondary outcomes: anhedonia, depressed mood, and impaired sleep (Supplementary Table S3). For all three models, autoregressive parameters were moderately strong, but both cross-lagged parameters (secondary outcome predicting later SI and SI predicting later secondary outcome) did not differ from zero (Figure 2, Supplementary Table S4).

Figure 2. Key parameter estimates for secondary outcomes.

Figure 2.

Open in a new tab

Autocorrelation and lagged parameter estimates with 95% confidence intervals (CIs) are plotted for each secondary outcome variable. The secondary outcome variable (Anhedonia, Depressed Mood, or Impaired Sleep) and the dataset (Short-term or Long-term) are indicated above the panel. Arrow indicates the direction of the effect. A positive autocorrelation indicates that the value of a variable at timepoint t was positively correlated with the value of the same variable at timepoint t+1. A positive lagged correlation indicates that the value at timepoint t of the variable listed before the arrow was positively correlated with the value at timepoint t+1 of the variable listed after the arrow. None of secondary outcome variables were associated with SI at timepoint t+1. SI = suicidal ideation; AR = autoregressive.

Discussion

In this secondary analysis of ketamine clinical trial data, the interaction between psychological pain and hopelessness was not prospectively associated with the re-emergence of SI. In addition, none of the other depressive symptoms—including depressed mood, anhedonia, or impaired sleep—were associated with next-day SI, highlighting the limitations of these measures and the study design to identify antecedents of the re-emergence of SI after ketamine administration. Contrary to our hypotheses, SI was weakly associated with later hopelessness and psychological pain.

These negative results nevertheless highlight several important implications for understanding the trajectory of suicidal thoughts. First and most importantly, this was an analysis of ketamine trial data rather than a natural history tracking the development of suicidal thoughts. This suggests that psychological theory regarding the development of SI may not be applicable to the re-emergence of SI post-ketamine administration, particularly because ketamine may have independent effects on SI and depressive symptoms (Ballard et al., 2014). This is especially relevant in tracking outcomes after ketamine is administered to individuals at increased risk for SI and underscores the importance of repeated assessment of SI, depressive symptoms, and suicide risk factors in the days after ketamine administration. Because there may be little relationship between symptoms day-to-day, it is possible that SI may re-emerge quickly and with little warning.

The relationship between SI and next-day hopelessness and psychological pain warrants further mention, although results were weakly associated and require replication. Ketamine is associated with dramatic, but transient, relief from SI and depressive symptoms. Because SI itself can be a distressing experience, it is possible that its re-emergence after a few days without it could be upsetting, leading to psychological pain and pessimism about the future. Qualitative interviews with individuals who have received ketamine support a variety of viewpoints; while some individuals feel more able to cope with their SI after receiving ketamine, others describe themselves as feeling bereft when it returns. One participant noted, “…hopefully this is going to get better with longer treatment, but if it doesn’t it, you know, it makes me think that, what’s the point of living” (Lascelles et al., 2020). For treating clinicians, conversations with patients around the experience of re-emerging SI may be warranted.

While a ketamine trial is not directly comparable to everyday fluctuations in symptomatology, these findings parallel work in the ecological momentary assessment (EMA) literature. Specifically, repeated assessment of SI and other symptoms during the day using smartphone devices have also been used to attempt to predict SI in the short term. These analyses have demonstrated that SI often varies dramatically over the course of the day; while factors such as hopelessness, feeling like a burden, and loneliness were concurrently correlated with SI, none were associated with short-term changes in SI (Kleiman et al., 2017). Other EMA analyses have also shown limited ability to predict short-term changes in SI using constructs such as depression (Hallensleben et al., 2018), hopelessness, connectedness, or burdensomeness (Czyz et al., 2019). The dynamic variability of SI suggests that it may be difficult to predict short-term changes in SI regardless of setting. Notably, variability in SI has itself recently emerged as a key construct for predicting suicide risk (Oquendo et al., 2020). Future analyses should evaluate the relationship between ketamine and SI variability rather than its presence or absence.

This analysis was associated with several limitations. First, this was a secondary analysis of clinical trial data not collected for this purpose. Second, because no specific ratings of hopelessness or psychological pain were available—for instance, as might be obtained via the Beck Hopelessness Scale (Beck et al., 1974), the Mee-Bunney Psychological Pain Assessment Scale (Mee et al., 2011), or the Psychache Scale (Holden et al., 2001)—all assessments were proxy measures obtained from existing depression rating scales. Furthermore, while some of the measures were repeated, they were not consistently administered each day for the entirety of the clinical trials, which limited the number of datapoints that could be used. Third, this was a convenience sample, and no a priori sample size was calculated. As with most statistical approaches, no hard-and-fast rules exist for sample sizes in structural equation modelling, given that requirements are strongly influenced by study-specific information such as model complexity and strength of relationships (Wolf et al., 2013). Given that an underpowered analysis may yield unpredictable results, the surprising observation that SI was weakly associated with later hopelessness and psychological pain must be treated with caution, particularly because each of these psychological constructs is highly correlated. Given the small sample size, we were obliged to simplify the RI-CLPM with model constraints, and it is impossible to know whether the results might have been interpreted differently with a more complex model.

In conclusion, this analysis suggests that the interaction between hopelessness and psychological pain was not prospectively associated with the re-emergence of next-day SI post-ketamine. Future research, potentially using digital phenotyping approaches, could be used to tease apart response to interventions, emotional reactions to the re-emergence of symptoms, and everyday variability in SI. Such analyses will be valuable for appropriately treating and monitoring at-risk individuals.

Supplementary Material

1

Highlights.

  • Suicidal thoughts and behaviors are difficult to predict

  • Ketamine is associated with rapid, transient changes in suicidal thoughts

  • This study sought to identify antecedents of suicidal thoughts post-ketamine

  • Psychological pain and hopelessness were not linked with next-day suicidal thoughts

  • Suicidal thoughts were linked with next-day psychological pain and hopelessness

Acknowledgements

The authors thank the 7SE research unit and staff for their support. Ioline Henter (NIMH) provided invaluable editorial assistance.

Role of Funding Source

Funding for this work was supported by the Intramural Research Program at the National Institute of Mental Health, National Institutes of Health (IRP-NIMH-NIH; ZIAMH002927; NCT01204918, NCT00054704, NCT00088699). The NIMH had no further role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.

Footnotes

Author Disclosures

Declaration of Interest

Dr. Zarate is listed as a co-inventor on a patent for the use of ketamine in major depression and suicidal ideation; as a co-inventor on a patent for the use of (2R,6R)-hydroxynorketamine, (S)-dehydronorketamine, and other stereoisomeric dehydroxylated and hydroxylated metabolites of (R,S)-ketamine metabolites in the treatment of depression and neuropathic pain; and as a co-inventor on a patent application for the use of (2R,6R)-hydroxynorketamine and (2S,6S)-hydroxynorketamine in the treatment of depression, anxiety, anhedonia, suicidal ideation, and post-traumatic stress disorders. He has assigned his patent rights to the U.S. government but will share a percentage of any royalties that may be received by the government. All other authors have no conflict of interest to disclose, financial or otherwise.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

References

  1. Abramson LY, Alloy LB, Hogan ME, Whitehouse WG, Cornette M, Akhavan S, Chiara A, 1998. Suicidality and cognitive vulnerability to depression among college students: a prospective study. J Adolesc 21, 473–487. [DOI] [PubMed] [Google Scholar]
  2. Ballard ED, Ionescu DF, Vande Voort JL, Niciu MJ, Richards EM, Luckenbaugh DA, Brutsché N, Ameli R, Furey ML, Zarate CA Jr., 2014. Improvement in suicidal ideation after ketamine infusion: relationship to reductions in depression and anxiety. J Psychiatr Res 58, 161–166. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Ballard ED, Wills K, Lally N, Richards EM, Luckenbaugh DA, Walls T, Ameli R, Niciu MJ, Brutsche NE, Park L, Zarate CA Jr., 2017. Anhedonia as a clinical correlate of suicidal thoughts in clinical ketamine trials. J Affect Disord 218, 195–200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Ballard ED, Yarrington JS, Farmer CA, Lener MS, Kadriu B, Lally N, Williams D, Machado-Vieira R, Niciu MJ, Park L, Zarate CA Jr., 2018. Parsing the heterogeneity of depression: An exploratory factor analysis across commonly used depression rating scales. J Affect Disord 231, 51–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Beck AT, Steer RA, Kovacs M, Garrison B, 1985. Hopelessness and eventual suicide: a 10-year prospective study of patients hospitalized with suicidal ideation. Am J Psychiatry 142, 559–563. [DOI] [PubMed] [Google Scholar]
  6. Beck AT, Weissman A, Lester D, Trexler L, 1974. The measurement of pessimism: the hopelessness scale. J Consult Clin Psychol 42, 861–865. [DOI] [PubMed] [Google Scholar]
  7. Czyz EK, Horwitz AG, Arango A, King CA, 2019. Short-term change and prediction of suicidal ideation among adolescents: a daily diary study following psychiatric hospitalization. J Child Psychol Psychiatry 60, 732–741. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Diazgranados N, Ibrahim L, Brutsche NE, Newberg A, Kronstein P, Khalife S, Kammerer WA, Quezado Z, Luckenbaugh DA, Salvadore G, Machado-Vieira R, Manji HK, Zarate CA Jr., 2010. A randomized add-on trial of an N-methyl-D-aspartate antagonist in treatment-resistant bipolar depression. Arch Gen Psychiatry. 67, 793–802. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Ducasse D, Holden RR, Boyer L, Artéro S, Calati R, Guillaume S, Courtet P, Olié E, 2018. Psychological pain in suicidality: a meta-analysis. J Clin Psychiatry 79, 16r10732. [DOI] [PubMed] [Google Scholar]
  10. Franklin JC, Ribeiro JD, Fox KR, Bentley KH, Kleiman EM, Huang X, Musacchio KM, Jaroszewski AC, Chang BP, Nock MK, 2017. Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychol Bull 143, 187–232. [DOI] [PubMed] [Google Scholar]
  11. Grunebaum MF, Galfalvy HC, Choo TH, Keilp JG, Moitra VK, Parris MS, Marver JE, Burke AK, Milak MS, Sublette ME, Oquendo MA, Mann JJ, 2018. Ketamine for rapid reduction of suicidal thoughts in major depression: a midazolam-controlled randomized clinical trial. Am J Psychiatry 175, 327–335. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Hallensleben N, Spangenberg L, Forkmann T, Rath D, Hegerl U, Kersting A, Kallert TW, Glaesmer H, 2018. Investigating the dynamics of suicidal ideation. Crisis 39, 65–69. [DOI] [PubMed] [Google Scholar]
  13. Hallquist MN, Wiley JF, 2018. MplusAutomation: an R package for facilitating large-scale latent variable analyses in Mplus. Struct Equ Modeling 25, 621–638. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Hamaker E, 2018. How to run the RI- CLPM with Mplus, https://www.statmodel.com/download/RI-CLPM%20Hamaker%20input.pdf.
  15. Hamaker EL, Kuiper RM, Grasman RP, 2015. A critique of the cross-lagged panel model. Psychol Methods 20, 102–116. [DOI] [PubMed] [Google Scholar]
  16. Holden RR, Mehta K, Cunningham EJ, McLeod LD, 2001. Development and preliminary validation of a scale of psychache. Can J Behav Sci 33, 224–231. [Google Scholar]
  17. Ibrahim L, Diazgranados N, Franco-Chaves J, Brutsche N, Henter ID, Kronstein P, Moaddel R, Wainer I, Luckenbaugh DA, Manji HK, Zarate CA Jr., 2012. Course of improvement in depressive symptoms to a single intravenous infusion of ketamine vs add-on riluzole: results from a 4-week, double-blind, placebo-controlled study. Neuropsychopharmacology 37, 1526–1533. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Jollant F, Perreira F, Fiori LM, Richard-Devantoy S, Lutz PE, Belzeaux R, Turecki G, 2020. Neural and molecular correlates of psychological pain during major depression, and its link with suicidal ideas. Prog Neuropsychopharmacol Biol Psychiatry 100, 109909. [DOI] [PubMed] [Google Scholar]
  19. Katayama N, Nakagawa A, Umeda S, Terasawa Y, Kurata C, Tabuchi H, Kikuchi T, Mimura M, 2019. Frontopolar cortex activation associated with pessimistic future-thinking in adults with major depressive disorder. Neuroimage Clin 23, 101877. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Kleiman EM, Turner BJ, Fedor S, Beale EE, Huffman JC, Nock MK, 2017. Examination of real-time fluctuations in suicidal ideation and its risk factors: results from two ecological momentary assessment studies. J Abnorm Psychol 126, 726–738. [DOI] [PubMed] [Google Scholar]
  21. Klonsky ED, May AM, 2014. Differentiating suicide attempters from suicide ideators: a critical frontier for suicidology research. Suicide Life Threat Behav 44, 1–5. [DOI] [PubMed] [Google Scholar]
  22. Klonsky ED, May AM, 2015. The Three-Step Theory (3ST): a new theory of suicider rooted in the “ideation-to-action” framework. Int J Cogn Ther 8, 114–129. [Google Scholar]
  23. Klonsky ED, Saffer BY, Bryan CJ, 2018. Ideation-to-action theories of suicide: a conceptual and empirical update. Curr Opin Psychol 22, 38–43. [DOI] [PubMed] [Google Scholar]
  24. Lascelles K, Marzano L, Brand F, Trueman H, McShane R, Hawton K, 2020. Ketamine treatment for individuals with treatment-resistant depression: longitudinal qualitative interview study of patient experiences. BJPsych Open 7, e9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Mee S, Bunney BG, Bunney WE, Hetrick W, Potkin SG, Reist C, 2011. Assessment of psychological pain in major depressive episodes. J Psychiatr Res 45, 1504–1510. [DOI] [PubMed] [Google Scholar]
  26. Nugent AC, Ballard ED, Gould TD, Park LT, Moaddel R, Brutsche NE, Zarate CA Jr., 2018. Ketamine has distinct electrophysiological and behavioral effects in depressed and healthy subjects. Mol Psychiatry. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Oquendo MA, Galfalvy HC, Choo TH, Kandlur R, Burke AK, Sublette ME, Miller JM, Mann JJ, Stanley BH, 2020. Highly variable suicidal ideation: a phenotypic marker for stress induced suicide risk. Mol Psychiatry Jun 23 [online ahead of print]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Pigeon WR, Pinquart M, Conner K, 2012. Meta-analysis of sleep disturbance and suicidal thoughts and behaviors. J Clin Psychiatry 73, e1160–1167. [DOI] [PubMed] [Google Scholar]
  29. Rogosa D, 1980. A critique of cross-lagged correlation. Psychol Bull 88, 245–258. [Google Scholar]
  30. Shneidman ES, 1993. Suicide as psychache. J Nerv Ment Dis 181, 145–147. [DOI] [PubMed] [Google Scholar]
  31. Smith JM, Alloy LB, Abramson LY, 2006. Cognitive vulnerability to depression, rumination, hopelessness, and suicidal ideation: multiple pathways to self-injurious thinking. Suicide Life Threat Behav 36, 443–454. [DOI] [PubMed] [Google Scholar]
  32. Wasserstein RL, Schirm AL, Lazar NA, 2019. Moving to a world beyond “p < 0.05”. Am Stat 73, 1–19. [Google Scholar]
  33. Wilkinson ST, Ballard ED, Bloch MH, Mathew SJ, Murrough JW, Feder A, Sos P, Wang G, Zarate CA Jr., Sanacora G, 2018. The effect of a single dose of intravenous ketamine on suicidal ideation: a systematic review and individual participant data meta-analysis. Am J Psychiatry 175, 150–158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Wolf EJ, Harrington KM, Clark SL, Miller MW, 2013. Sample size requirements for structural equation models: an evaluation of power, bias, and solution propriety. Educ Psychol Meas 76, 913–934. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Zarate CA Jr., Brutsche NE, Ibrahim L, Franco-Chaves J, Diazgranados N, Cravchik A, Selter J, Marquardt CA, Liberty V, Luckenbaugh DA, 2012. Replication of ketamine’s antidepressant efficacy in bipolar depression: a randomized controlled add-on trial. Biol Psychiatry 71, 939–946. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Zarate CA Jr., Singh JB, Carlson PJ, Brutsche NE, Ameli R, Luckenbaugh DA, Charney DS, Manji HK, 2006. A randomized trial of an N-methyl-D-aspartate antagonist in treatment-resistant major depression. Arch Gen Psychiatry. 63, 856–864. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS1800302-supplement-1.docx (30.7KB, docx)

RESOURCES