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Suicidal ideation (SI) is a common mental health problem. Variability in intensity of SI over time has been linked to suicidal behavior, yet little is known about the temporal course of SI.
The primary aim was to identify prototypical trajectories of SI in the general population and, secondarily, to examine whether receiving Web-based self-help for SI, psychiatric symptoms, or sociodemographics predicted membership in the identified SI trajectories.
We enrolled 236 people, from the general Dutch population seeking Web-based help for SI, in a randomized controlled trial comparing a Web-based self-help for SI group with a control group. We assessed participants at inclusion and at 2, 4, and 6 weeks. The Beck Scale for Suicide Ideation was applied at all assessments and was included in latent growth mixture modeling analysis to empirically identify trajectories.
We identified 4 SI trajectories. The high stable trajectory represented 51.7% (122/236) of participants and was characterized by constant high level of SI. The high decreasing trajectory (50/236, 21.2%) consisted of people with a high baseline SI score followed by a gradual decrease to a very low score. The third trajectory, high increasing (12/236, 5.1%), also had high initial SI score, followed by an increase to the highest level of SI at 6 weeks. The fourth trajectory, low stable (52/236, 22.0%) had a constant low level of SI. Previous attempted suicide and having received Web-based self-help for SI predicted membership in the high decreasing trajectory.
Many adults experience high persisting levels of SI, though results encouragingly indicate that receiving Web-based self-help for SI increased membership in a decreasing trajectory of SI.
Suicidal ideation (SI) is a common mental health problem. The lifetime prevalence of SI in Western countries has been reported to be around 10% [
Traditionally, longitudinal studies have reported the prevalence of self-reported SI at several time points or provided the mean change in SI over time for a whole study cohort or in predefined categories based on, for instance, diagnosis [
By applying data from a longitudinal Dutch randomized controlled trial comparing a group following a Web-based self-help program for suicidal thoughts with a waitlist control group (Netherlands Trial Register NTR1689), we had the opportunity to examine prototypical patterns of SI in an adult sample from the general population seeking Web-based help for SI. Promising results from this randomized controlled trial have previously been published showing that SI was significantly more reduced in the Web-based self-help program receivers than in the control participants [
Our primary aim was to identify prototypical trajectories of SI, thereby increasing current knowledge on individual variability of SI. Secondarily, we examined whether baseline sociodemographics, clinical symptoms, or the Web-based self-help program was associated with membership in the identified SI trajectories.
Mean change in suicidal ideation as assessed by the Beck Scale for Suicide Ideation (BSS), overall and by randomization group.
Full details of the methods of the randomized controlled trial have previously been described [
We recruited participants from the general population through newspaper advertisements and banners on the Internet that directed interested people to a website where they obtained information about the study and were able to register. Inclusion in the study required a minimum age of 18 years, access to the Internet and an email address, being fluent in Dutch, having mild to moderate SI (defined as a score between 1 and 26 on the Beck Scale for Suicide Ideation, BSS) [
Because this study was conducted in a vulnerable population, we used safety procedures [
The Web-based self-help program was based on elements from cognitive behavioral therapy, dialectical behavioral therapy, problem-solving therapy, and mindfulness-based cognitive therapy, which have all been shown to reduce suicidality [
Each module contained theory and core exercises. Module 1 aimed at helping participants recognize how often they repeat suicidal thoughts and learning to manage this worrying or ruminating repetition better. Module 2 focused on learning to tolerate and regulate intense emotions. The theory section explained how to recognize an upcoming crisis and tapped into dealing with the urge to self-harm. Core exercises introduced different ways of coping with intense emotions, such as behavioral activation (eg, seeking distraction) and acceptance (waiting until the feelings subside). Participants were also encouraged to make a crisis plan. Modules 3 to 5 dealt with identifying automatic thoughts, recognizing common thinking patterns (all-or-nothing thinking, overgeneralization, or mind reading), and cognitively restructuring the three most important identified negative automatic thoughts. Module 6 was dedicated to preventing relapse and discussed the possibility of future setbacks and disappointments.
The control group received access to a website with information on suicidality, that is, how common it is and its risk factors, and provided a list of common places to seek treatment for suicidality. The control group was provided with access to the self-help program at the 6-week follow-up.
Our primary measure, which we used to identify latent trajectories of SI, was the BSS questionnaire, which we distributed to participants at baseline, at weeks 2 and 4 of the intervention, and finally at the sixth and last week of the intervention. Furthermore, we administered questions on the following at baseline, and subsequently applied and examined them as possible predictors of trajectory membership: sex, age, living with partner (yes/no), paid employment (yes/no), having children (yes/no), random allocation group (control/Web-based self-help intervention), and currently receiving other help such as psychiatric or psychological therapy (yes/no). We also examined clinical factors such as having attempted suicide before baseline (item from the BSS), depression symptoms measured by the BDI, and levels of hopelessness as measured by the Beck Hopelessness Scale [
We applied latent growth mixture modelling (LGMM) to estimate trajectories of SI. This data-driven statistical method identifies subgroups in a sample based on shared growth parameters (ie, intercept and slope). As such, in LGMM it is assumed that multiple subpopulations exist in a sample; however, no assumptions are made about the number of subpopulations or their specific growth parameters. Hence, individuals are classified into possible unobserved subgroups based on common profile patterns and, subsequently, between-group differences can be examined [
Goodness of fit statistics for 1- to 6-class solutions and
No. of classes | Fit estimatesa | Entropyc | |||||
AICd | BICe | adj.BICf | Vuong-Lo- Mendell-Rubin likelihood ratio test | Lo-Mendell- Rubin adjusted likelihood ratio test | Bootstrap likelihood ratio test | ||
1 | 5798 | 5825 | 5800 | ||||
2 | 5742 | 5783 | 5745 | <.01 | <.01 | <.01 | .69 |
3 | 5709 | 5764 | 5714 | .23 | .24 | <.01 | .77 |
4 | 5673 | 5742 | 5679 | .06 | .07 | <.01 | .85 |
5 | 5647 | 5730 | 5654 | .24 | .26 | <.01 | .86 |
6 | 5630 | 5727 | 5638 | .08 | .10 | <.01 | .87 |
aLower values of AIC, BIC, and adj.BIC indicate better model fit.
b
cEntropy estimates ranges from 0 to 1 and assess the accuracy with which models classify individuals into their most likely class; higher scores represent greater classification accuracy.
dAkaike information criteria.
eBayesian information criteria.
fSample size-adjusted BIC.
We obtained the most parsimonious model with the 4-class solution, where fit estimates (AIC, BIC, and adj.BIC) were low, the bootstrap likelihood ratio test performed with a significant
Of the 4 identified trajectories, 3 had high intercepts (BSS>14), indicating that individuals in these latent classes had high intensity or frequency of SI at baseline (see
Baseline characteristics of members in each suicidal ideation trajectory.
Characteristics | Latent trajectorya | |||||
High decreasing |
High increasing |
High stable |
Low stable |
|||
41 (12.3) | 36 (12.0) | 41 (14.3) | 41 (13.8) | .66b | ||
.96c | ||||||
Women | 30 (65) | 8 (73) | 85 (66) | 33 (65) | ||
Men | 16 (35) | 3 (27) | 43 (34) | 18 (35) | ||
.58c | ||||||
No | 27 (60) | 9 (82) | 78 (61) | 31 (63) | ||
Yes | 18 (40) | 2 (18) | 49 (39) | 18 (37) | ||
.04c | ||||||
Control group | 15 (33) | 6 (55) | 68 (53) | 31 (61) | ||
Intervention group | 31 (67) | 5 (45) | 60 (47) | 20 (39) | ||
.25c | ||||||
No | 21 (47) | 2 (18) | 52 (42) | 25 (50) | ||
Yes | 24 (53) | 9 (82) | 73 (58) | 25 (50) | ||
.07c | ||||||
No | 19 (42) | 9 (82) | 67 (53) | 21 (43) | ||
Yes | 26 (58) | 2 (18) | 60 (47) | 28 (57) | ||
.03c | ||||||
No | 20 (44) | 9 (82) | 88 (65) | 29 (57) | ||
Yes | 26 (57) | 2 (18) | 45 (35) | 22 (43) | ||
<.01c | ||||||
No | 21 (47) | 2 (18) | 78 (61) | 36 (74) | ||
Yes | 24 (53) | 9 (82) | 49 (39) | 13 (27) | ||
Beck Depression Inventory | 26 (9.9) | 34 (12.0) | 29 (8.3) | 22 (8.6) | <.01b | |
Beck Hopelessness Scale | 15 (3.4) | 15 (3.4) | 15 (3.5) | 12 (3.6) | <.01b |
aNumbers of members in each class diverge slightly from those in
bAnalysis of variance
cPearson chi-square test.
Odds ratios (95% CI) from multivariable logistic regression analyses describing the association between baseline characteristics and membership in suicidal ideation trajectories using the high stable trajectory as the reference.
Characteristics | Low stable | High increasing | High decreasing | |||
Control group | 1 | 1 | 1 | |||
Intervention group | 0.82 (0.31–2.13) | 0.66 (0.11–3.78) | 3.15 (1.19–7.67)* | |||
No | 1 | 1 | 1 | |||
Yes | 1.19 (0.48–2.97) | 0.18 (0.01–4.25) | 1.30 (0.52–3.24) | |||
No | 1 | 1 | 1 | |||
Yes | 1.79 (0.68–4.70) | 0.57 (0.08–4.08) | 3.12 (1.27–7.67)* | |||
No | 1 | 1 | 1 | |||
Yes | 0.74 (0.24–2.26) | 8.64 (0.16–452.7) | 2.72 (1.10–6.70)* | |||
Beck Depression Inventory | 0.95 (0.89–1.01) | 1.06 (0.95–1.19) | 0.95 (0.90–1.01) | |||
Beck Hopelessness Scale | 0.78 (0.67–0.91) |
0.87 (0.68–1.11) | 0.96 (0.81–1.15) |
*
**
Odds ratios (95% C) from multivariable logistic regression analyses describing the association between baseline characteristics and membership in suicidal ideation trajectories using the low stable trajectory as the reference.
Characteristics | High increasing | High decreasing | |
Control group | 1 | 1 | |
Intervention group | 0.8 (0.12–5.25) | 3.84 (1.22–12.12)* | |
No | 1 | 1 | |
Yes | 0.15 (0.01–3.48) | 1.09 (0.36–3.31) | |
No | 1 | 1 | |
Yes | 0.32 (0.04–2.36) | 1.74 (0.58–5.21) | |
No | 1 | 1 | |
Yes | 11.7 (0.26–516.8) | 3.68 (1.05–13.0)* | |
Beck Depression Inventory | 1.12 (0.99–1.26) | 1.0 (0.93–1.08) | |
Beck Hopelessness Scale | 1.11 (0.86–1.45) | 1.24 (1.01–1.52)* |
*
Trajectories of suicidal ideation as assessed by Beck Scale for Suicide Ideation (BSS) scores.
This study aimed to examine prototypical trajectories of SI in an adult population seeking Web-based treatment for suicidal thoughts. The results of the LGMM confirmed heterogeneity by identifying 4 distinct trajectories of SI in this population. A notable finding was that those experiencing a decrease in SI (members of the high decreasing class) differed in characteristics from those with a more stable level of SI (both high stable and low stable) during the study period. Those receiving the Web-based intervention (vs the control group) and having a history of attempted suicide were more than 3 times as likely to be members of the high decreasing class as to be members of both stable classes. Members of the high decreasing class were also more likely than members of the high stable class to be living with a partner, and they had a higher level of hopelessness at baseline than did members of the low stable class. Overall, the findings of this study yield important and new information about developmental patterns of SI and especially how these patterns associate with the Web-based self-help intervention.
This study has demonstrated that patterns of SI vary greatly, which is not detected using traditional analyses. While traditional analyses showed an overall small significant mean effect size in SI (
We also identified predictors of membership in trajectories. Most important, membership in the high decreasing trajectory, compared with the 2 stable trajectories, was significantly associated with having received the Web-based intervention program, indicating that the program had a reducing effect on SI. This is consistent with earlier publications on this sample, which showed a small but significant overall mean effect size (a reduction of 4.6 points on the BSS) [
The high follow-up response rate strengthens this study, as this makes the estimation of SI trajectories more precise. Furthermore, we measured SI with a validated scale (BSS), as opposed to a single-item question on SI, which was applied in some of the other studies of heterogeneity in SI [
The analyses of trajectories of SI have provided clinically interesting information. In particular, it was notable that being assigned to the Web-based self-help program, having a history of suicidal behavior, having a partner, and having lower baseline levels of hopelessness were associated with experiencing a large decrease in SI during the 6-week study period, even though this applied to a small proportion of the sample. A discouraging finding was that a large proportion of the Web-based help seekers experienced persistently high levels of SI, and future research should address whether this group might benefit more from tailored Web-based programs or from face-to-face help. Recently, this Web-based self-help program to reduce SI was found to be cost effective too [
sample size-adjusted Bayesian information criteria
Akaike information criteria
Beck Depression Inventory
Bayesian information criteria
Beck Scale for Suicide Ideation
latent growth mixture modelling
odds ratio
suicidal ideation
The study was approved by the Medical Ethics Committee of the VU University Medical Centre (registration number 2008/204).
Financial support: A postdoctoral scholarship from Copenhagen Mental Health Center funded the corresponding author. This study was funded by the Netherlands Organisation for Health Research and Development (ZonMw), The Hague, project number 120510003. The funder had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The authors report no financial or other relationship relevant to the subject of this paper. BvS and AK are authors of the Web-based self-help program described in this paper. BvS and AK receive royalties from an adapted paper version of the self-help program described in this paper under the title “Piekeren over zelfdoding” (in Dutch), published by Boom, Amsterdam (2012).