Main findings

We drew data from a large case register of patients receiving secondary mental healthcare in a defined catchment area over a prolonged period (2007–2015) linked with national mortality data and we tested the extent to which structured risk assessment items (individual risk factors and overall scores) predicted suicide. First, as expected, we identified a high number of suicides in a population of patients in secondary mental healthcare (approximately 100.28/100,000 person-year), approximately tenfold higher than in the general population (10.9/100,000 person-year) [22]. Second, we found that although a number of risk factors were significantly associated with suicide in the bivariate analyses (namely, being male, previous suicide attempts, previous use of violent methods, plans to end life, suicidal ideation, distress, lack of control over life, impulsivity, disengagement from services/non-compliance with medication and recent hospital discharge), only hopelessness and having a significant loss remained independent and statistically significant predictors of suicide in the multivariable regression models. Third, overall risk assessment performed poorly to predict suicide in a large sample of mental health service users, which was in line with our expectations and recent literature [13,14,15].

Comparison with previous literature

Of relevance, we did not find a protective effect of completing suicide risk assessment on reducing suicide rates as previously suggested [10], which was in line with further reviews of the NICE guidelines [30]. It might seem intuitive to speculate that those patients with a risk assessment documented are deemed at a higher risk of suicide by the treating team and they are more likely to receive a higher level of input and caution in management. It remains unanswerable what may have happened if these ‘high risk’ individuals had not been administered a risk assessment and to research this would raise ethical issues. However, recording of risk assessment is, to some degree, circular and more likely in those patients who will be followed-up by mental health services [31]. In addition, risk assessment in this cohort may have been completed due to concerns raised regarding other clusters of risk, such as violence to others and/or self-neglect [24]. Moreover, risk assessment completion rates may have been affected by the patient’s legal status in some cases, which was not evaluated in this study. For instance, those receiving care under restriction, hence subject to the UK Mental Health Act 1983 (amended 2007) [32] may be more likely to have a risk assessment documented. In this regard, our findings are of major relevance from a human rights perspective, since these individuals may have been ‘forced’ to undertake an assessment which appears to have a limited value, which would also go against the 2015 UK Code of Practice [33].

In terms of risk factors, we replicated the association of being male [1, 34], previous suicide attempts [35], previous use of violent methods [5], plans to end life and suicidal ideation [36], hopelessness [37, 38], distress, lack of control over life and impulsivity [39], having a significant loss [40], disengagement from services/non-compliance with medication and recent hospital discharge [4] with suicide. Consistent with previous models of suicide [41, 42], only hopelessness and having a significant loss remained significant. However, it should be noted that childhood trauma, which was not evaluated by our risk assessment questionnaire, was found to have greater effects on suicidality than depression and related variables [43], hence it should become part of routine clinical suicide risk assessment.

Over four decades ago, hopelessness was defined as ‘the cognitive element of negative expectations’ [37], which was also demonstrated to be the strongest predictor of suicide in outpatients [38], and this we replicated in our results. Hence, our findings agree, in part, with Mann’s diathesis-stress model of suicide [42] regarding the role of hopelessness, although impulsivity [39] was not significantly associated with suicide in our cohort. It should be noted, however, that impulsivity, as measured by the SLaM risk assessment, might refer to a different construct. On the other hand, we did find that having a significant loss was a predictor of suicide independently of other factors, which, in addition to the role of hopelessness, was consistent with the classic theory of ‘suicide as psychache’ [41]. Of note, the conceptualization of suicide as the consequence of ‘mental pain or psychache’ has been recently reconsidered [44] in light of decades of relatively unsuccessful neurobiological research [45] based on Mann’s model of suicide [42]. Indeed, over 90% of suicide attempters report ‘mental pain’ [46], which is frequently the consequence of a bereavement [40], which is of particular concern after surviving the suicide of a love one [47]. Moreover, ‘mental pain’ appears to be a contributor to suicide independently of depression [48], which is in full agreement with our results. Indeed, the relationship between suicide and ‘mental illness’ (from a psychiatric perspective) may be weaker than previously thought, especially in Western countries [44]. In keeping with this, neither medication compliance nor (psychiatric) diagnosis were associated with suicide in our large cohort of mental health service users, which may provide further support for a non-medical approach to suicide [49]. Hence, those patients receiving secondary mental healthcare at risk of suicide may particularly benefit from psychological therapies, as recommended by the UK NICE guidelines for depression [50], although not frequently offered [51].

In addition, overall risk assessment showed poor predictive validity, which was unsurprising, given the rarity of the outcome. In particular, high sensitivity was reached at the price of low specificity (i.e., a very high number of false positives to identify most of suicides) and vice versa, i.e., reducing the number of false positives (high specificity) occurred at the expenses of too many false negatives (low sensitivity), thus preventing high-risk patients from care and treating ‘healthy’ people unnecessarily, which was in full agreement with early literature [11, 12].

In keeping with this, for the most optimal cut-off point (4–5), a very low positive predictive value (1%) and very high negative predictive value (99%) emerged from the analyses. In other words, in this ‘low-risk’ group (those with less than four risk factors), there would be still 20 suicides (approximately one quarter of those who ended their lives). On the other hand, 6988 individuals (50.8% of the total sample) would be classified as ‘high-risk’ patients, although only 61 of these subjects took their lives. The question arises. Is it, therefore, worth managing so many patients as ‘suicidal’ to prevent a few deaths? More specifically, in times of financial constraints, should so many patients receive high levels of care such as unnecessary admissions to hospital?

These findings were consistent with a 2017 literature review on ‘the limitations of epistemic uncertainty’ with regard to risk assessment, whose overall poor performance appears to be due to the so-called ‘aleatory uncertainty’. In short, risk factors change ‘by chance’, which is unpredictable [18]. The concept of risk, therefore, requires a reformulation. Specifically, while suicide risk does not appear to be predictable, a more prevention-orientated approach may result in better clinical outcomes [52].

However, our findings concerning the association of hopelessness and having a significant loss with suicide, which as a whole provide some support for the ‘mental pain’ model of suicide [41], which was discussed above, still suggest that suicide may still be, to some degree, predictable.

Future research

While we do recommend that risk assessment should remain part of our routine clinical practice, a more narrative (free-text) approach should be taken [53] to better capture aspects such as ‘mental pain’, which, based on our findings, seems to be more useful in terms of clinical risk assessment. In particular, rather than categorising patients as ‘low–medium–high’ risk, the wide range of contributing factors to risk should be detailed in relation to the individual’s mental health problems and the social context and how these factors may change dynamically over time, thus increasing or decreasing risk for a given individual, which is what matters clinically [52]. Patient information from electronic records can be easily, safely and securely de-identified to generate large datasets for secondary research [54], such as the SLaM CRIS [20, 21]. Specifically, naturalistic language processing (NLP) tools appear to be promising research instruments to extract statistically analysable clinical information from narrative electronic records, hence determining risk from free-text notes [55]. NLP techniques may assess suicide risk using information from unstructured questions with higher precision than the classic risk assessment scales [56], thus potentially capturing the presence of ‘mental pain’.

Specifically, future studies should examine whether risk assessment changes over time, particularly self-ratings shortly before suicide may increase the predictive value of risk assessment. In this regard, mobile phone and web-based text messaging may represent a useful tool to self-monitor suicide risk [57], particularly to follow-up people attempting suicide [58] and to assess risk shortly before suicidal events, including suicides. For instance, the classic suicide note may have been substituted by a message left on this new media, which clinicians should discuss with patients and carers when assessing self-harm [59]. In addition, free-text-based risk assessment, which can be researched through NLP techniques [55], may be more accurate than psychometric scales [56]. Future research should, therefore, switch the focus from long-term risk factors to short-term risk algorithms, which are more relevant to the clinician [60]. However, the evidence of the use of communication technologies in health care and public health, which is known as mobile health (mHealth) [61], on suicide prevention is limited [62].

Strengths and limitations

The use of a large case register linked with national mortality data allowed us to investigate the role of risk assessment in predicting suicide in a large sample of patients who were receiving secondary mental healthcare within a defined geographic catchment and time period. Since most people living in South-East London requiring secondary mental healthcare receive this from NHS resources, our sample is likely to be representative. In addition, participants were followed-up for up to 9 years and, in addition to risk assessment ratings, a number of covariates were taken into account.

However, the study has some limitations to be borne in mind when drawing conclusions from the results. First, all participants were mental health service users residing in South-East London, which is an inner urban area. Hence, our findings may not generalise to people with mental health problems under primary care or those who live in rural areas. Second, the vast majority of SLaM patients (almost 90%) did not have a structured risk assessment completed and those who did may have been deemed ‘at-high-risk’ by their treating teams. In other words, it could be still speculated that assessing risk in all patients receiving care may reduce risk. Third, although only the last suicide risk assessment was considered, risk factors may have changed from the time of risk assessment to death. Also, risk assessment scores may have been affected by survival, hence those who survived for longer (and therefore received care for a more prolonged period of time) may have been rated differently. Finally, other factors such as patient’s legal status at the time of risk assessment or a history of childhood trauma, which were not evaluated in this study, may have affected both risk assessment completion rates and ratings, and the main outcome measure of this study, namely suicide.

Implications and conclusions

Our results, therefore, support the notion that neither individual risk factors nor a combination of them, i.e., risk assessment, can adequately predict suicide in a population of patients receiving mental healthcare. Suicide is a very uncommon outcome even in a high-risk group such as patients receiving secondary mental healthcare. Our study suggests that risk assessment cannot predict suicide in the clinical setting due to its very low occurrence, which is in full agreement with recent meta-analyses [13,14,15], although hopelessness and having a significant loss were linked with suicide, consistent with the classic ‘mental pain’ model of suicide [41, 44, 46, 48].

Meanwhile, further research on suicide prevention [62,63,64] is warranted. In particular, means restriction remains the first-line strategy to prevent both high-risk groups such as patients receiving mental healthcare [17] and the general population [65] from suicide.