Background
Every year, over 800,000 individuals worldwide die by suicide and between 10 and 20 million individuals attempt suicide [
1]. In many cases suicidal thoughts are antecedents of a suicide attempt and completed suicide [
2]. Among suicide ideators, about one third go on to act on them with a suicide attempt, and 60% of these transitions occur within the first year after onset of suicidal thoughts [
3]. Although suicidal behavior is strongly associated with mental disorders, no linear relationship exists; the vast majority of people with mental disorders do not experience suicidal behavior [
4]. Thus, psychiatric disorders as risk factors for suicidal behavior have only limited predictive power [
5]. Therefore, we need to better understand the motivational processes that lead to suicidal thoughts and why some individuals cross the threshold to act on them. This is particularly important for clinical interventions that address the reduction of suicide ideation as an antecedent to a suicide attempt.
One approach that elaborates that motivational view is the internal suicide debate hypothesis [
6]. The hypothesis involves the assumption that suicidal individuals are often entangled in a struggle over whether to live or die and weigh up between reasons for living (RFL) and reasons for dying (RFD). Linehan et al. [
7] further examined the life-oriented aspect of this debate and introduced the Reasons for Living Inventory (RFLI). Prospective studies showed that individuals with few reasons for living were at increased risk for developing suicidal thoughts [
8] and attempting suicide [
9]. A recent study of Cwik et al. [
10] strikingly illustrated, that RFL moderated the relationship between depression and suicide ideation. Participants who reported more RFL experienced less suicide ideation even at the highest severity of depression as compared to participants with only a small number of RFL. In line with these results, Gutierrez et al. [
11] showed that a low score on the “RFL-Survival and Coping Beliefs”-subscale was associated with an increased suicide risk. However, in this study internal risk factors (e.g. hopelessness and repulsion by life) were more useful in identifying individuals with an increased suicide risk compared to protective factors measured by the RFLI.
Nevertheless, Gutierrez et al. [
11] highlight the importance of assessing both ends of the suicidality continuum, reasons for living and dying, in order to get a more detailed picture of suicide risk and to decide about suitable intervention. For example, a person with an increased suicide risk but a strong sense of responsibility to his or her family and fear of suicide might benefit from outpatient therapy. Without these protective factors, hospitalization might be more appropriate. Therefore, covering both facets of the internal ambivalence in suicidal individuals might be essential for obtaining a more comprehensive evaluation of suicide risk. Moreover, interventions addressing risk factors while simultaneously increasing reasons for living should be more effective than those only concentrating on risk factors. For a systematic evaluation of the motivational drivers involved in the suicidal process, more specifically a person’s attraction to life and death, Jobes and Mann [
12] developed the “Reasons for living (RFL) and Reasons for dying (RFD) Assessment”, which is part of the Suicide Status Form III [
13]. It is a self-report assessment for measuring quantitative and qualitative characteristics of the internal suicide debate that prompts participants to write down up to five individual reasons for staying alive (RFL) vs. wanting to die (RFD) (see Table
1).
Table 1
Typical Reasons for living and Reasons for dying
My husband | No more pain |
Working in the bookstore | Feeling alone |
Music | To stop hurting others |
I think things will work out | |
Harris et al. [
14] investigated the RFL and RFD in 1016 participants classified as high suicidal vs. non-suicidal. Participants with a greater wish to die than to live and a high total-score in the Suicide Behaviors Questionnaire – Revised [
15] were categorized as high suicidal and vice versa for the non-suicidal group. They found that the non-suicidal group produced significantly more RFL and fewer RFD than high suicidal respondents. To date, there is no research on the number of RFL and RFD in suicide attempters. The current study intended to close this gap and investigated the quantitative RFL and RFD responses in suicide attempters and their influence on current and future suicidality.
Aims of the study
1.
The first aim of the study was to compare the number of RFL and RFD in individuals with a recent suicide attempt. We assumed that individuals would report significantly more RFD than RFL immediately after a suicide attempt.
2.
The second aim was to examine the influence of the number of RFL and RFD at baseline on concurrent suicide ideation at baseline as well as on suicide ideation at 6 months (T2) and 2 years (T4) after the index suicide attempt. Here, we hypothesized that a higher number of RFD would indicate a higher degree of suicide ideation, whereas a higher number of RFL would have a protective effect on current and future suicide ideation.
3.
Third, we wanted to investigate whether the number of RFD would mediate the relationship between depression and suicide ideation.
4.
Finally, we aimed to explore whether the number of RFL and RFD would have a predictive value on the occurrence of a repeated suicide attempt during a one-year (T1-T3) and a two-year follow-up (T1-T4).
Methods
Participants
The sample consists of participants who were admitted at the emergency unit of the Bern University General Hospital following an attempted suicide. The present study, which was part of a larger randomized controlled trial [
16], included 60 patients who gave written informed consent and received routine psychiatric treatment (inpatient, day patient, and individual outpatient care). Exclusion criteria were insufficient mastery of the German language, serious cognitive impairment, psychotic disorder, and residency outside the hospital catchment area. Table
2 presents baseline characteristics and clinical diagnoses of the patients. Participants were Caucasians, had an average age of 39 years, and half of them were female. Twenty-five percent were married and 32% had children. Sixty percent were diagnosed with an affective disorder, 47% with a neurotic and stress-related disorder, and 33% a substance abuse disorder. The mean number of diagnoses was 2 (
M = 2.1,
SD = .93, range 1–4). Twenty-two percent reported one prior suicide attempt; 35% had a history of multiple (two or more) prior suicide attempts.
Table 2
Characteristics of the participants at baseline (N = 60)
Age | 39.15 | 14.58 | | |
Male sex | | | 30 | 50.00 |
Relationship (yes) | | | 21 | 35.00 |
Children (yes) | | | 19 | 31.66 |
Employment |
- Unemployed, disability pension, sick leave | | | 26 | 43.33 |
- Employed, in training, in education | | | 34 | 56.66 |
Previous suicide attempts |
- none | | | 26 | 43.30 |
- 1 | | | 13 | 21.70 |
- 2 | | | 10 | 16.70 |
- > 2 | | | 11 | 18.30 |
Diagnoses |
- F1: Mental and behavioural disorders due to psychoactive substance use | | | 20 | 33.33 |
- F3: Mood (affective) disorders | | | 36 | 60.00 |
- F4: Neurotic, stress-related and somatoform disorders | | | 28 | 46.66 |
- F5: Behavioural syndromes associated with physiological disturbances and physical factors | | | 1 | 1.66 |
- F6: Disorders of adult personality and behaviour | | | 12 | 20.00 |
BDI sum | 18.32 | 12.25 | | |
BSS mean | 9.05 | 9.15 | | |
Number of reasons for living (RFL) | 3.45 | 1.35 | | |
Number of reasons for dying (RFD) | 1.90 | 1.55 | | |
Measures
Socio-demographic questionnaire
The Sociodemographic Questionnaire (DEMO) [
17] is a 31-item questionnaire that assesses personal, sociodemographic, and health-related data, including information on suicidal behavior. The DEMO asks for the frequency of suicide ideation and self-harm in the last 6 months as well as for the number of suicide attempts in the last 6 months and during lifetime.
Beck depression inventory
The Beck Depression Inventory (BDI) [
18] is a 21-item self-report measure to assess the severity of a patient’s current level of depression including affective, cognitive, motivational, behavioral, and somatic components. Items are scored on a 4-point Likert scale (0 = nonexistent to 3 = severe) and are summed up. A score from 18 or above indicates significant depressive symptoms. The German version has demonstrated good validity [
19] and for the current study, Cronbach alpha was .88.
Beck scale for suicide ideation
The Beck Scale for Suicide Ideation (BSS) [
20] is a 21-item self-report instrument and was used to assess the intensity of the patient’s attitudes, behaviors, and plans related to suicidal behavior. The items are scored on a 3-point Likert Scale and are summed up except of the last two items. They assess the number of previous suicide attempts before the index suicide attempt and the strength of the desire to die during the index suicide attempt. The higher the respondent’s total score, the higher is their suicide risk. The German version has demonstrated a very good internal consistency with a Cronbach alpha of .94 [
21] and for the current study, Cronbach alpha was .93.
Reasons for Living and Dying from the Suicide Status Form (SSF-III) [
13]. Participants were instructed to write down up to five RFL and RFD respectively on the SSF-III (see Table
1). For current analyses, we were interested in the numbers of RFL and RFD responses.
Attrition analysis
All patients took part in a single clinical interview at baseline, which included a structured suicide risk assessment using the “Suicide Status Form” [
12]. The median delay time between the suicide attempt and the interview was 17.5 (interquartile range 9.0–34.5) days. They filled out the DEMO) [
17], the BDI [
18], the BSS [
20], and the SSF-III [
13] at baseline (T1) and after 6 (T2), 12 (T3), and 24 (T4) months. Six months (T2) after baseline 71.7% of the participants completed the questionnaires; 12 months (T3) after baseline the response rate was 60% of the baseline sample and at the two-year follow-up (T4), 63.3% of the baseline sample took part. Complete data over all included measurement points was obtained by 46.7% of the baseline sample. Data on repeated suicide attempts were primarily assessed with the DEMO [
17]. Additionally, we complemented self-reported data by searching medical records and contacting involved health professionals in order to complete data regarding suicidal behavior. Within 12 months after baseline, one patient died by suicide and three died of natural causes.
Overall attrition was significantly associated with a higher number of RFL at baseline (r = .26, p = .040), stronger psychological pain at the time of the suicide attempt (r = .29, p = .025), and not being in outpatient treatment between T2 and T3 (r = −.33, p = .049). Attrition at T2 was associated with fewer suicide attempts (r = −.34, p = .007), stronger psychological pain at the time of the suicide attempt (r = .27, p = .033), and fewer outpatient and inpatient treatments before baseline (r = − .35, p = .008, r = −.34, p = .007, resp.). Attrition at T3 was associated with stronger psychological pain at the time of the suicide attempt (r = .26, p = .041) and more psychotherapy sessions during the previous 6 months before the index suicide attempt (r = .27, p = .040). Attrition at T4 was associated with a higher number of RFL at T1 (r = .26, p = .048), a lower number of psychotherapy sessions in the 6 months prior to T3 (r = .40, p = .016). Under the assumption of missing at random, we used multiple imputations for missing data (see data analysis section).
Statistical analysis
Under the assumption of missing at random, we computed multiple imputations for all variables included in the analyses based on Markov Chain Monte Carlo simulations with the Bayesian estimator in Mplus version 7.4 [
22]. A total of 40 imputed datasets were generated and results are reported on pooled analyses of these datasets. Sensitivity analyses yielded similar results using the imputed and the non-imputed datasets. Pearson correlation were used for two continuous variables, tetrachoric correlations for two binary, biserial correlations for one continuous and one binary or ordered polytomous variable, and polychoric correlations for a binary and an ordered polytomous variable. To analyze predictors of the BSS score and repeated suicide attempts, we used robust linear and logistic regression analyses. In the multiple regression analyses, we entered all correlations with a
p-value <.09 simultaneously.
We conducted cross-sectional path analyses at baseline to investigate whether the number of RFD mediated the relationship between the BDI score and BSS score at baseline. Furthermore, we conducted longitudinal analyses with BDI at baseline, number of RFD at T2, and BSS at T3. This temporal sequence of the variables suggests a directional link from the predictor to the outcome variables via the mediator. It accounts for the implication of the temporal relation with depression occurring before the RFD and the RFD occurring before suicide ideation and thus the notion that the depression at baseline affects the number of RFD 6 months later and the RFD affect the level of suicide ideation at the 12-month follow-up [
23].
Results
Numbers of reasons for living and reasons for dying and socio-demographic factors
After the index suicide attempt at baseline participants reported significantly more RFL (M = 3.45, SE = 1.35) than RFD (M = 1.90, SE = 0.55, t(59) = 5.71, p < .001), which corresponds to a strong effect (d = 1.00). Therefore, our hypothesis that patients immediately after a suicide attempt had more RFD than RFL was rejected. Even though significance level was just not reached, participants with at least one prior suicide attempt produced more RFD (M = 2.24, SE = 0.28) than participants with no prior suicide attempt (M = 1.46, SE = 0.25, t(58) = − 1.96, p = .054, d = 0.53). There was no difference regarding RFL between those with and without prior suicide attempt (M = 3.38, SE = 0.22 vs. M = 3.54, SE = 0.27, t(58) = .44, p = .660, d = 0.12).
Table
3 presents the zero-order correlations of socio-demographic variables, RFL and RFD at baseline and 6 month (T2) later, BDI at baseline, BSS scores at T1 - T4, and repeated suicide attempts. RFL and RFD responses at baseline did not correlate (
r = −.05, 95% BCa CI [−.31, .24],
p = .697). The number of RFL at baseline and at T2 were not significantly related to socio-demographic and clinical sample characteristics or any other variables (all
p > .05). However, RFD at baseline correlated with BDI at baseline (
r = .56, 95% CI [.37, .75],
p < .001) and BSS at baseline (
r = .70, 95% CI [.54, .86],
p < .001), BSS at T2 (
r = .53, 95% CI [.31, .76],
p < .001), and BSS at T4 (
r = .29, 95% CI [.04, .53],
p = .021).
Table 3
Correlations between sociodemographic variables, depression and suicide-related variables
Male Sex a | .13 | | | | | | | | | | | | | | |
Partner a | - .28 t | .06 | | | | | | | | | | | | | |
Children a |
.49
| - .06 | - .29 | | | | | | | | | | | | |
Previous SA (0–2) | - .07 | - .19 | .14 | - .27 | | | | | | | | | | | |
RFL T1 | .03 | .02 | .21 | - .02 | - .13 | | | | | | | | | | |
RFD T1 | .18 | .08 | - .03 | - .16 | .25 t | - .05 | | | | | | | | | |
RFLT2 | - .24 | - .11 | .15 | - .27 | .26 t | .23 | .19 | | | | | | | | |
RFD T2 | - .25 t | - .13 | .32 t |
- .41
| .19 | - .04 |
.51
|
.39
| | | | | | | |
BDI T1 | - .06 | - .25 | .08 |
- .35
|
.28
| - .19 t |
.56
| - .08 |
.48
| | | | | | |
BSS T1 | .07 | .05 | .30 t |
- .45
|
.31
| - .10 |
.70
| - .04 |
.52
|
.63
| | | | | |
BSS T2 | - .19 | - .11 |
.45
|
- .37
| .29 t | - .08 |
.53
| .23 |
.72
|
.55
|
.78
| | | | |
BSS T3 | - .10 | .15 |
.37
| - .16 | .19 | - .05 | .14 | - .10 |
.45
|
.32
|
.37
|
.50
| | | |
BSS T4 | .09 | - .06 | - .05 | - .24 |
.35
| - .13 |
.29
| .02 |
.34
|
.43
|
.41
|
.37
|
.50
| | |
Repeated SA 0–12 months a | .04 | - .12 | .22 | .00 | .17 | - .18 | .34t | - .12 | .34 t |
.51
|
.48
|
.52
|
.71
|
.54
| |
Repeated SA 0–24 months a | - .06 | - .19 | - .08 | - .15 | .27 | - .05 | .23 | - .05 | .14 |
.37
|
.34
| .29 |
.36
|
.55
|
.87
|
Prediction of suicide ideation at baseline, after six months and after two years
Table
4 presents the results of the simple and multiple regression analyses for predicting the BSS score at baseline, the six-month (T2), and two-year follow-up (T4). Simple regression analyses showed that being in a relationship was significantly associated with a higher BSS score at baseline and BSS at T2. Having children at baseline was significantly related to a lower BSS score at baseline and at T2. RFD at baseline showed the strongest association with BSS score at baseline with an explained variance of 50%. More suicide attempts prior to the baseline, a higher BDI at baseline, and more RFD at baseline consistently predicted a higher BSS score at baseline, at T2, and at T4 with declining effect sizes across time. RFD at baseline still explained 9% of the variance of the BSS score at T4. In contrast, RFL were not associated with suicide ideation.
Table 4
Cross-sectional and longitudinal predictors of suicide ideation and repeated suicide attempts
BSS score baseline |
Age | .08 | .12 | .527 | .005 | | | | |
Male sex a | .08 | .26 | .746 | .002 | | | | |
Partner a | .46 | .22 | .040 | .048 | .38 | .14 | .005 | |
Children a | −.69 | .22 | .002 | .104 | −.33 | .14 | .017 | |
Previous SA (0–2) | .31 | .13 | .018 | .074 | .05 | .08 | .534 | |
RFL t1 | −.10 | .15 | .519 | .010 | | | | |
RFD t1 | .70 | .06 | .000 | .493 | .52 | .09 | .000 | |
BDI t1 | .63 | .08 | .000 | .395 | .27 | .10 | .009 | .642 |
BSS score six-month |
Age | −.19 | .12 | .110 | .040 | | | | |
Male sex a | −.17 | .27 | .528 | .008 | | | | |
Partner a | .66 | .21 | .001 | .100 | .33 | .19 | .071 | |
Children a | −.56 | .23 | .015 | .069 | .05 | .19 | .805 | |
Previous SA (0–2) | .26 | .12 | .029 | .070 | .04 | .09 | .646 | |
RFL t1 | −.08 | .14 | .568 | .008 | | | | |
RFD t1 | .53 | .09 | .000 | .285 | −.01 | .12 | .909 | |
BDI t1 | .55 | .10 | .000 | .308 | .12 | .13 | .343 | |
BSS t1 | .78 | .06 | .000 | .613 | .68 | .15 | .000 | .655 |
BSS score 24-month |
Age | .09 | .13 | .474 | .012 | | | | |
Male sex a | −.09 | .28 | .744 | .006 | | | | |
Partner a | −.07 | .28 | .793 | .004 | | | | |
Children a | −.34 | .23 | .149 | .027 | | | | |
Previous SA (0–2) | .28 | .14 | .039 | .086 | .19 | .15 | .193 | |
RFL t1 | −.13 | .16 | .428 | .019 | | | | |
RFD t1 | .29 | .14 | .035 | .086 | −.08 | .19 | .664 | |
BDI t1 | .43 | .11 | .000 | .185 | .27 | .15 | .067 | |
BSS t1 | .41 | .12 | .001 | .174 | .25 | .21 | .220 | .261 |
Repeated suicide attempts 0–12 months |
Age | .04 | .23 | .856 | .009 | | | | |
Male sex a | −.20 | .39 | .612 | .014 | | | | |
Partner a | .37 | .42 | .388 | .037 | | | | |
Children a | −.01 | .42 | .990 | .004 | | | | |
Previous SA (0–2) | .15 | .21 | .477 | .030 | | | | |
RFL t1 | −.18 | .19 | .331 | .036 | | | | |
RFD t1 | .34 | .18 | .051 | .122 | −.15 | .33 | .658 | |
BDI t1 | .51 | .19 | .006 | .264 | .35 | .25 | .156 | |
BSS t1 | .48 | .15 | .001 | .232 | .23 | .36 | .312 | .316 |
Repeated suicide attempts 0–24 months |
Age | −.06 | .19 | .743 | .013 | | | | |
Male sex a | −.30 | .36 | .413 | .029 | | | | |
Partner a | −.12 | .37 | .740 | .009 | | | | |
Children a | −.25 | .38 | .498 | .018 | | | | |
Previous SA (0–2) | .23 | .18 | .193 | .060 | | | | |
RFL t1 | −.05 | .18 | .766 | .008 | | | | |
RFD t1 | .23 | .17 | .179 | .058 | | | | |
BDI t1 | .37 | .18 | .034 | .143 | .25 | .23 | .267 | |
BSS t1 | .34 | .16 | .028 | .120 | .19 | .20 | .354 | .163 |
As a next step, we computed multiple regression analyses to investigate the unique contribution of all significant predictors in the simple regression analyses controlling for the other predictors. Concurrent associations at baseline confirmed the unique contributions of being in a relationship, having children, a higher number of RFD, and a higher level of depression for predicting suicide ideation. However, previous suicide attempts were no longer significant. Again, RFD at baseline were the strongest predictor; all variables together explained 64% of the variance of suicide ideation at baseline (BSS T1).
We examined longitudinal associations of the predictor variables at baseline on BSS score at T2 controlling for BSS at baseline. Multiple regression analyses showed that only BSS score at baseline remained a significant predictor and had a unique contribution to the BSS at T2. The explained variance was again 65%. Regarding the long-term associations after 2 years (T4), no baseline predictor had a unique contribution to the BSS at T4. The amount of explained variance of the BSS score at T4 declined to 26%.
Table
5 presents the results of the path models testing whether RFD mediated the association between depression (BDI) and suicide ideation (BSS). We found a significant indirect effect (
STD b = .29,
p < .0001) of the level of depression on the level of suicide ideation via the number of RFD. The direct relationship between depression and suicide ideation remained significant, but the standardized regression coefficient declined from .63 to .34. Thus, a partial mediation was confirmed. The model explained 57% of the variance of suicide ideation at baseline.
Table 5
Results of the mediation analyses
Outcome BSS t1 |
Simple regression |
BDI t1 -- > BSS t1 | .63 | .08 | .000 | .395 |
Mediation model including RFD t1 |
Direct paths |
BDI t1 -- > BSS t1 | .34 | .10 | .001 | |
BDI t1 -- > RFD t1 | .56 | .08 | .000 | |
RFD t1 -- > BSS t1 | .51 | .09 | .000 | |
Indirect path |
BDI t1 -- > BSS t1 via RFD t1 | .29 | .06 | .000 | .572 |
Outcome BSS t3 |
Simple regression |
BDI t1 -- > BSS t3 | .32 | .14 | .022 | .107 |
Mediation model including RFD t2 |
Direct paths |
BDI t1 -- > BSS t3 | .13 | .15 | .373 | |
BDI t1 -- > RFD t2 | .48 | .12 | .000 | |
RFD t2 -- > BSS t3 | .38 | .15 | .010 | |
Indirect path |
BDI t1 on BSS t3 via RFD t2 | .19 | .08 | .024 | .223 |
As a next step, we repeated these analyses using longitudinal data to test whether RFD at T2 mediated the relationship between the BDI at baseline and BSS at T3. Results confirmed a significant indirect effect (STD b = .19, p = .024) even though smaller than the cross-sectional indirect effect. The direct effect of depression at baseline on suicide ideation 12 month later disappeared, confirming a full mediation. The model explained 22% of the variance of suicide ideation at 12-month follow-up.
Prediction of suicide reattempts within one and two years after baseline
Table
4 reports the results of the logistic regression analyses to predict suicide reattempts. Within the 12-month period after baseline, 23.3% (
n = 10) of the participants reported another suicide attempt. In line with the previous analyses, BSS and BDI at baseline predicted suicide reattempts after 12 months (T1-T3) in the simple regression analyses. The number of RFD at baseline just missed the level of significance (
p = .051). In contrast to the prediction of suicide ideation, having a partner, having children or previous suicide attempts before baseline did not predict suicide reattempts. Multiple regression analyses explained 32% of the variance in suicide reattempts within 1 year but no single predictor remained significant. Within the two-year period from baseline, 36.7% (
n = 16) of the participants reported another suicide attempt. BDI and BSS at baseline, but not RFD at baseline predicted significantly suicide reattempts after 2 years (T1 – T4) in the simple regression analyses. The multiple regression model explained 16% of the variance and again no single predictor remained statistically significant.
Conclusion
Several conclusions for research and clinical practice can be drawn from these findings. First, we found no strong evidence for the assumption that the RFL and RFD are two poles of a suicidality continuum. They rather represented two different dimensions, which were differentially related with suicidality. In this sample, the number of RFL did not correlate with suicide risk and, therefore, was not confirmed as a protective factor against suicide ideation or suicide reattempts. Therefore, the common clinical assumption that a higher number of RFL is linked with a reduced suicide risk should be considered with caution.
Second, findings of this study suggest that the number of RFD can be considered as a motivational driver of the suicidal process and individuals with a high number of RFD are very prone for a suicidal crisis. In regard of suicide risk management and treatment, individual reasons of a person, which serve as motives to end their life or for a recent suicide attempt, should be carefully assessed and treated. Psychological interventions in suicidal crisis should give priority to the reduction or foster a cognitive defusion from RFD, which could serve as motivational drivers in the suicidal process than the elaborating RFL.
Acknowledgements
We thank Anja Gysin-Maillart and Konrad Michel, who kindly provided the data for our analysis.
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