Focussing treatment in patients displaying suicidal behaviour
E.L. Karman S1290908
Master Thesis Clinical Psychology Dr. Hendrik Koopman
Institute of Psychology University Leiden November 5, 2015
Table of Contents
Abstract ... 3
1 Introduction ... 4
1.1 Biopsychosocial model of suicide ... 5
1.2 Stress-diathesis model ... 6 1.3 Research Question ... 7 2 Methods ... 12 2.1 Participants ... 12 2.2 Procedure ... 13 2.3 Measures ... 13 2.4 Statistical Analysis ... 15 3 Results ... 16 4 Discussion ... 18
4.1 Suicide attempt and MDD diagnosis ... 18
4.2 Factors associated with suicide and depression ... 19
4.3 Alcohol use and childhood abuse ... 19
4.4 Mastery ... 20
4.5 Social network ... 21
4.6 Family history of depression ... 22
4.7 Limitations ... 23
4.8 Future Research ... 24
4.9 Implications ... 25
Table 1: Demographics of the study sample (N = 1983) ... 31
Table 2: Construct Variances (In Parentheses on the Diagonal Axis) and Relations ... 32
Abstract
This study investigated the relationships of various factors believed to affect suicidal behaviour. Based on the results of previous studies, depression, social network, family history of depression, mastery, childhood abuse, and alcohol use were considered relevant to suicidal behaviour. The research utilized data collected by the Netherlands Study of Depression and Anxiety (NESDA), a longitudinal study examining the long-term course of depression and anxiety. Data was included from 1,983 participants using clinical interviews, structured assessments and diagnoses. By creating a structural equation model, the study was able to focus on factors which best correlate with suicidal behaviour as a means to focus treatment direction. The relationship between the listed factors and depression was also closely examined in order to rule out any omitted-variable bias. In line with our hypotheses, social network, mastery, and family history of depression all related with both suicidal behaviour and depression. Despite our expectations, neither alcohol use nor childhood abuse showed a statistically significant relation with either suicidal behaviour or depression. Our results emphasize the need to illuminate depression, mastery, social network, and family history as a focus of treatment and prevention for suicidal behaviour as well as further examination of the role of alcohol use and childhood abuse.
1 Introduction
Suicide continues to be one of the leading causes of death with a death occurring once every 40 seconds. As high as this number is, it does not take into account the number of suicide attempts which is 20 times as high (World Health Organization [WHO], 2014). According to CBS Statistics Netherlands (2013a), the suicide rate in the Netherlands has increased from 559 in 1950 to 1,753 in 2012. In 2011, the suicide rate in the Netherlands was 9.9 per 100,000 in the population with mostly male victims (CBS Statistics Netherlands, 2012). From 2008 to 2012 alone, the total suicide rate in the Netherlands has gone up 30% (CBS Statistics Netherlands, 2013b). These statistics emphasize the impact this issue has on individuals and society as a whole. The increasing numbers indicate that something more should be done to address suicidal behaviour in identifying it and treating it.
Acknowledgement that suicide is a rising cause of death prompts researchers to examine the
reasons behind suicidal behaviour as well as measures which can reduce the number of suicide attempts. While there has been an established relationship between diagnosis of depression and suicidal behaviour, not all who suffer from depression commit suicide. In the same vein, not all who commit suicide suffer from depression (Gvion & Apter, 2012). While depression has been demonstrated to be strongly connected to suicidal behaviour, the previous statement indicates that factors aside from depression are also important to consider when examining an individual’s propensity for suicidal behaviour. By streamlining understanding of suicidal behaviour to a focus on mental illness, important factors may be missed, to the detriment of many lives. It has been noted there is a lack of suicide risk training, particularly in the primary care network (Saini, While, Chantler, Windfuhr, & Kapur, 2014). Examination of additional factors will expand the focus for mental health practitioners, crisis hotline employees, and general practitioners in addressing patients who contact them with suicidal thoughts. Suicide intervention and prevention programs can easily be developed in a well-rounded manner by addressing multiple factors affecting suicide. The current research examines multiple variables, both risk and protective factors, and help solidify their link to suicidal behaviour. These variables are examined as a whole to inform whether all variables when taken together are still useful in determining risk of
suicidal behaviour. The findings will add to the literature informing common aspects linked to increased and decreased suicidal behaviour to focus assessment and treatment in all areas of care.
While a variety of factors may influence an individual’s vulnerability to mental health issues, the increasing number of them, particularly combined with few protective factors, may weaken a person’s resiliency. The biopsychosocial model of suicide clearly illustrates factors stemming from various sources need to be considered when examining risk of suicide. Adding to this, the stress-diathesis model indicates the greater the number of biopsychosocial factors negatively influencing a person’s life, the less likely they will be able to cope appropriately when high-stress issues occur.
1.1 Biopsychosocial model of suicide
It is important to recognize that suicide is a final act as a result of an interaction of numerous variables (Gvion & Apter, 2012). These variables can be described as biological, psychological, and social in nature. The theoretical model outlines biopsychosocial factors are linked to one another and each requires attention when addressing health issues. In this way, suicide is not only determined by biological factors, but is influenced by psychological and social factors as well. While the model makes conceptual sense, there has been difficulty putting it into practice (Smith, 2002). While generally accepted that attention needs to be paid to biological, psychological, and social factors affecting a patient’s wellbeing, the task of addressing all factors is often daunting for many physicians (Weston, 2005). When it comes to suicide risk, physicians are often unaware of the true risk of their patients (Holi et al., 2008; Prinstein, Spirito & Grapentine, 2001), which may be due to lack of training, lack of time, or lack of validity in patient’s reports. The biopsychosocial model is also well supported as it relates to depression (Schotte, Bossche, Doncker, Claes & Cosyns, 2006; Smith, 2006; Suls & Rothman, 2004; Weston, 2005). Generally, overweight patients are directed by their physicians to diet and exercise, as well as being prescribed medication to address issues such as high blood pressure. In this way, various types of factors are addressed in order to improve the individual’s well-being. Similarly with mental health issues, such as depression, it is necessary to evaluate numerous
variables, not only biological factors which can be narrowing when discussing health issues. In the current study, biological factors were examined through family history, psychological factors included childhood abuse, mastery, depression, and social factors were social support and alcohol use.
Often physicians will diagnose a patient with depression and treat depression with medication. While this may significantly reduce suicide risk among some patients, medication primarily targets biological factors. Without treatment for underlying psychological and social factors in tandems, medication can become a temporary solution for many patients as other factors may remain in existence. Often the transition from suicidal ideation to attempt occurs within one year (Kessler, Borges & Walters, 1999) and reliance on client report alone is dangerous as they often conceal their thoughts and behaviours (Denmark, Hess & Becker, 2012). For these reasons, it is important to take the biopsychosocial model into consideration as it relies on more than just client report, but an examination of the patient’s environment as well.
1.2 Stress-diathesis model
The observation that even under extreme levels of stress not all individuals engage in suicidal behaviour has led to the development of the stress-diathesis model of suicide (Van Heeringen, 2012). This model recognizes that while proximal factors such as job loss, divorce, and death can cause high levels of stress for an individual, distal factors influence the vulnerability of said individual to react in various ways. In other words, not everyone reacts to the same stressor in the same manner as not everyone has the same vulnerability levels. When individuals have a predisposition for suicidal behaviour, proximal stressors can push that individual over the edge (Sarchiapone, Vladimir, Cuomo & Roy, 2007). The interaction between vulnerability and stress essentially determines what the outcome is for the individual in dealing with the stressor (Ingram & Luxton, 2005). As a result, it is essential to examine both ongoing proximal stressors in an individual’s life, as well as their vulnerabilities in order to obtain an accurate conceptualization of their suicide risk. The stress-diathesis model of suicide portrays a theoretical framework from
which to consider vulnerabilities. A person’s vulnerabilities may stem from various biopsychosocial sources.
The above theories emphasize the importance of examining a variety of factors, rather than focussing on genetics alone. Recognizing multiple factors is essential as the more factors involved enhances a person’s vulnerability to stress. Being able to understand the level of vulnerability a person has to suicidal behaviour, will allow mental health practitioners to address those factors in prevention of action on those thoughts when proximal stress events occur.
1.3 Research Question
Factors chosen for the current research followed from the biopsychosocial and stress-diathesis models to test a model which illustrates their relationship to suicidal behaviour. Due to the strength of the connection between suicidal behaviour and depression, this study focuses on both in order to facilitate a thorough analysis of the risk and protective factors for suicidal behaviour while recognizing the heavy impact they may also have on depression. While mental health difficulties are a relevant precursor to suicidal behaviour, additional factors have been shown to be significant as well. Often depression is thought to lead to suicidal behaviour; however, not all who suffer from depression commit suicide (Gvion & Apter, 2012). As additional factors continue to be a reality for many patients, it is important to address them in addition to depression. The current research aims to examine multiple factors within one model to ascertain which factors will be most important for health practitioners in their practice.
Suicide and Depression
Suicide has been commonly associated not only with Major Depressive Disorder, but other mood disorders as well (Galfalvy et al., 2006). Depression can be a lethal disorder in terms of the health risks it can lead to, including suicidal behaviour exhibited by sufferers. Often depressed individuals experience suicidal ideation, even if they never act on their suicidal thoughts. Mood disorder has been demonstrated to be the most common disorder among those who commit suicide (Beautrais, 2003; Gvion & Apter, 2012; Lewinsohn, Sanchez & Le, 2001).
Understanding the relation between mood disorders and suicidal behaviour can be facilitated by the stress-diathesis model. Depression takes a toll on the body and mind and eventually the stress can become so great that an individual feels unable to cope. At that point, even a seemingly minor amount of stress can become overwhelming to the point where they consider suicide as an option to end their suffering. Long-term stress, such as struggling with depression, particularly with no treatment or support, can become too much for one person to handle. As depression and suicide are closely interconnected, it is essential to examine them together to analyze whether other factors are simply associated with one or the other, or whether both have common risk and protective factors which are important to examine.
H1: Diagnosis of depression is associated with a higher rate of suicidal behaviour.
Social Support
Social factors within the biopsychosocial model include influences at various levels (e.g. individual, societal, etc.); however, one of the most powerful is the individual support one receives from those directly impacting their life. Joiner’s (2005) interpersonal-psychological theory of suicide asserts that those who contemplate suicide perceive themselves to be burdensome and feel socially alienated. Loneliness and lack of social support have been linked to higher rates of suicidal behaviour among various age groups (Hall-Lande, Eisenberg, Christenson & Neumark-Sztainer, 2007; Masuda, Kurahashi & Onari, 2013; Prinstein et al., 2001; Spruijt & de Goede, 1997). Not only does having strong social support act as a protective factor in suicidal behaviour, but it is also noted to be a highly malleable factor (Kleiman & Lui, 2013) which has high potential for treatment focus. Theoretically, social support would potentially lower a person’s experience of overwhelming amounts of stress as they would have a social outlet to use as a resource to deal with stress.
H2: Low level of social support is associated with a higher rate of suicidal behaviour.
Level of social support has long been known to be related to an individual’s health prognosis. Those who experience low levels of social and emotional support are at higher risk for depression (Wilkinson & Marmot, 2003). Further research examining loneliness and lack of social connectedness has determined a link with higher levels of depression (Grav, Hellzèn, Romild &
Stordal, 2011; Hall-Lande et al., 2007; Marcotte, Marcotte & Bouffard, 2002; Seeds, Harkness & Quilty, 2010; Stice, Ragan & Randall, 2004). Furthermore, positive changes in social support have been linked with improvement in depression (Lachman and Agrigoroaei, 2010; Zautra,et al, 2012) and therefore demonstrates implications for treatment focus.
H3: Low level of social support is associated with a diagnosis of depression.
Alcohol Use
Acute alcohol use has been associated with suicidal behaviour and a history of alcohol use has been noted a risk factor for suicide (Haw, Houston, Townsend & Hawton, 2001; Sher, 2006a). Alcohol use has been cited as a coping strategy some use to deal with the stress around them, similar to suicidal behaviour. As those who have attempted suicide also have been noted to have an alcohol disorder (Lewinsohn, Rohde, & Seely, 1998), alcohol use was considered a factor in the current study.
H4: Higher level of alcohol use is associated with a higher rate of suicidal behaviour.
While the direction of the relationship is continuously being examined, research has demonstrated that a higher level of alcohol use is strongly associated with a diagnosis of depression (Boden & Fergusson, 2011; Davis, Uezato, Newell & Frazier, 2008; Worley et al, 2012). Mulford and Miller (1960) put forward a motivation for alcohol use which they coined “personal-effect” motivation, or drinking to cope with stress. However, within treatment studies demonstrate that changes in depression are negatively related with changes in alcohol use (Worley et al, 2012) which implies alcohol use can be modified and subsequently positively influence depressive symptoms.
H5: Higher level of alcohol use is associated with a diagnosis of depression.
Childhood Abuse
Exposure to negative events during childhood has been shown to be associated with suicidal behaviour later in life (Dube et al., 2001, Duke, Pettingell, McMorris, & Borowsky, 2010). The frequency of the abuse has shown an additive effect, namely, the more the abuse, the more the risk of violent behaviour, including suicidal behaviour (Duke et al., 2010). The severity and type
of abuse is also positively related to the number of attempts one makes (Dube et al., 2001; Hadland et al., 2012; Mandelli, Carli, Roy, Serretti & Sarchiapone, 2011). For those who experienced childhood abuse, they may be unable to cope with high levels of stress and resort to drastic measures such a suicidal behaviour to address such stress.
H6: Experience of childhood abuse is associated with a higher rate of suicidal behaviour
A basic influence of psychological development is the treatment of a child by their parents. Be it physical, sexual, emotional, or neglect, an individual’s mental health is affected by the trauma they experience in their formative years. Experience of abuse in childhood can negatively affect children’s development and is associated with depression and other mental health disorders (Mandelli et al., 2011; Sarchiapone et al., 2009; Seeds, Harkness, & Quilty, 2010). The social factor of experiencing childhood abuse could potentially increase a person’s vulnerability to mental health issues in the future.
H7: Experience of childhood abuse is associated with a diagnosis of depression.
Family History of Depression
Family background is essential information to collect on patients as family history of mood disorders is highly related with suicidal behaviour (Bottlender, Jäger, Strauß & Möller, 2000; Galfalvy et al., 2006; Lizardi et al., 2009; Sorenson et al., 2009) which may be due to genetics or modelling behaviour, or a combination of both. Biologically and socially, family history is responsible for a person’s genetic makeup, but also their development. A family member’s experience of depression is believed to relate to an individuals expression of suicidal behaviour. H8: Family history of depression is associated with a higher rate of suicidal behaviour.
Family history of depression is one of the primary risk factors for depression of their offspring (Hirschfeld & Weissman, 2002) as children and grandchildren of those with depression have a higher risk of being diagnosed (Lieb, Isensee, Höfler, Pfister, Wittchen, 2002; Weissman et al., 2005). Genetics is an influential biological factor involved in a person’s mental health, as many have prior vulnerabilities.
Mastery
Through experience of negative events in their life, over time, some individuals feel they have little or no control over their environment and as a result are unable to develop positive coping strategies and have poor problem solving skills (Lauer, de Man, Marquez & Ades, 2008). This external locus of control has been associated with higher levels of suicidal behaviour (Lauer et al., 2008; Evans, Owens & Marsh, 2005). High levels of mastery would allow an individual to be able to deal with high levels of stress in appropriate ways. Psychologically, if an individual feels they are unable to cope with overwhelming stress, they may then feel suicide is the only way to deal with their stress.
H10: Low level of mastery is associated with a higher rate of suicidal behaviour.
Mastery develops over time and influences the sense of control an individual feels over their life. Those with a high level of mastery feel they have control over the happenings in their life, while those with low mastery tend to attribute consequences to external forces (Pearlin & Schooler, 1978). A lower level of mastery is associated with increased psychological problems as individuals are more responsive to stress (Rotter, 1966). Depression results as they perceive events in their life as unpredictable and uncontrollable (Jaswal & Dewan, 1997; Zawawi & Hamaideh, 2009); however, helping individuals improve their level of mastery reduces levels of depression and other health issues (Lachman and Agrigoroaei, 2010; Zautra,et al, 2012). As a psychological factor, high levels of mastery allows the individual to feel confident in their abilities to deal with life which leads to lower levels of depression. For those who feel they have little control in their life, feelings of helplessness and depression may result – particularly when probed by high levels of stress.
H11: Low level of mastery is associated with a diagnosis of depression.
The research question to be addressed by the current study is to create a structural equation model which examines the strength of connections between various factors related to suicidal behaviour. The hypotheses included in this study reflect the importance noted above of examining both distal and proximal factors associated with suicidal behaviour as well as biopsychosocial factors. See the model below for the factors included in the model.
Suicide Attempt MDD Diagnosis (Lifetime) Mastery Alcohol Use Social Network Childhood Abuse
Family History of Depression
0, e1 1 0, e2 1
Figure 1. SEM Model. This figure illustrates the factors included in predicting the model best outlining associations with suicide attempt and MDD diagnosis.
2 Methods 2.1 Participants
The current study focuses on data obtained from participants of the Netherlands Study of Depression and Anxiety (NESDA). This study is a longitudinal cohort study designed to examine the long-term course of depression and anxiety. Participants were gathered from mental health care, primary care, and community settings with a total of 2,981 participants. Those included in the current study are those who suffered from a current or past diagnosis of Major Depressive Disorder as well as those who did not present with a past or present diagnosis. The latter served as the control group. Exclusion criteria were those who suffered from a psychiatric disorder (other than depression) and if they did not demonstrate a fluency in Dutch. In addition, those cases with missing data were excluded from the analysis. Taking these exclusions into account, the number of participants within the current study was 1,983.
2.2 Procedure
An observational study design was utilized using the baseline data collected at the start of the longitudinal study. The study was approved by the Ethical Review Board of the VU University Medical Centre as well as the local boards of participating clinics. Informed consent was collected from all participants prior to participation. Participants were assessed using clinical interview and self-report measures at the start of the study to provide a baseline which served as the data utilized in the current study.
2.3 Measures Childhood Abuse
Childhood Trauma Questionnaire-Short Form (CTQ-SF)
The Childhood Trauma Questionnaire Short Form (CTQ-SF) is a retrospective 28-item self report measure designed to assess childhood abuse. The questionnaire takes approximately five minutes to administer and includes questions pertaining to sexual (sexual contact with a child younger than 18 years and an adult), physical (assaults on the child’s body by an adult which posed risk or injury), and emotional abuse (verbal assaults toward a child or demeaning or humiliating behaviour committed by an adult) as well as physical neglect (failure of caretakers to provide basic physical needs for the child) and emotional neglect (failure of caretakers to provide basic psychological and emotional needs for the child including love, nurturance and support). The questionnaire also includes a 3-item scale examining minimization and denial. Each scale of the CTQ-SF includes five items to address each construct. Responses to items are scored on a 5-point Likert scale (1= never true, 2 = rarely true, 3 = sometimes true, 4 = often true, 5 = very often true). For the current study, the Dutch version was used. As one item from the sexual abuse scale, “I believe I was molested”, was removed due to ambiguity in the Dutch version, the scores used for the purposes of this study will include a total of 24 items instead of 25 items. The current study determined childhood trauma to be present utilizing the recommended cut-off scores (absent = score of 25-40, present = score of 41-125). In the Dutch version, Cronbach’s alpha for the scales were described as .91 for physical abuse, .89 for emotional abuse, .95 for sexual abuse, .63 for physical neglect, and .91 for emotional neglect, meeting adequate internal consistency reliability (Thombs et al., 2009).
Alcohol Use
Alcohol Use Disorders Identification Test (AUDIT)
The Alcohol Use Disorders Identification Test (AUDIT) is a 10-item self-report measure designed to identify individuals who engage in harmful use of alcohol. The three domains assessed by the AUDIT are hazardous alcohol use (e.g. “how often do you have a drink containing alcohol?”), dependence symptoms (e.g. “how often in the last year have you needed a first drink in the morning to get yourself going after a heavy drinking session?”), and harmful alcohol use (e.g. “have you or someone else been injured because of your drinking”). For the purposes of this study, total scores greater than ‘8’ were deemed to indicate the presence of alcohol problems (Babor, Higgins-Biddle, Saunders & Monteiro, 2001). The Chronbach’s alpha for the AUDIT was described as .82, meeting adequate internal consistency reliability (Daeppen et al., 2000).
Mastery
Mastery Scale
The Pearlin and Schooler Mastery Scale is a 5-item self-report measure intended to determine an individual’s sense of control over factors that influence their life. The five items of the scale are measured by a likert scale (1= strongly disagree, 2 = disagree, 3 = no disagreement/agreement, 4 = agree, 5 = strongly agree) (Pearlin & Schooler, 1978). The cut off scores for low and high mastery are ≤ 16 and ≥ 20, respectively.
Family History
Family history information was collected using a grid which asked participants to outline their family members including siblings, parents and grandparents. Participants were then asked to mark which family members have suffered from depression and other psychological illnesses in the past. For the purposes of the current study, only information relating to parents’ experience of depression was included.
MDD Diagnosis
Depression diagnosis was determined based on DSM-IV criteria via clinical interview. For the purposes of the current study, participants who had been diagnosed at any point in their lifetime were included.
Social Network
Social network was reflected in the number of persons in each participant’s life with which they
had regular or important contact. Only persons above the age of 18 were included.
Suicide Attempt
Suicidal behaviour was reflected in participants self-report of whether they have engaged in a suicide attempt.
2.4 Statistical Analysis
The statistical procedure selected to analyze the data is Structural Equation Modelling (SEM) utilizing the student version of AMOS 5. The paths will be considered significant if p<.05 and the model is deemed to have adequate fit as determined by chi-square. As recommended by Schreiber et al (2006), CFI, TLI and RMSEA will be used to more accurately determine model fit. Prior to analysis, data will be examined for collinearity, non-normality and outliers. In addition, control variables (i.e. sex, age, and education level) will be tested using linear regression in SPSS as student AMOS 5 limits the number of variables to a point where controls would not be able to be tested using SEM. Demographic characteristics for the sample were examined. Assumption of normality was analyzed as well as potential outliers. This study focused on both depression and suicidal behaviour simultaneously in order to eliminate any omitted-variable bias. In this way, all factors are examined with both depression and suicide in order to assure no important variables were left out of the analysis and all factors can be assessed more thoroughly as to their relation to suicidal behaviour.
Figure 2. SEM Model. This figure illustrates the factors included the model with the standardized estimates.
3 Results
Within the study sample, 32% were male and 68% were female. In terms of past suicidal behaviour, 11% of the sample had made a suicide attempt in the past. Furthermore, 63% of the sample had a present or previous diagnosis of Major Depressive Disorder. Please refer to Appendix 1 for further detailed information regarding demographics of the study sample.
The model was analyzed using all variables and all independent variables were allowed to covary with each other. After further examining the results, the model was adapted by eliminating the covariant of childhood abuse and alcohol use to allow for degrees of freedom. The model fit is very good (χ² = 0.018, df = 1, p = .892; CFI = 1.00, TLI = 1.29, RMSEA = .00).
Figure 2 shows the standardized estimates of the structural model. The results support hypotheses 1 (MDD diagnosis – suicide attempt), 2 (social network – suicide attempt), 3 (social
network – MDD diagnosis ), 8 (family history – suicide attempt), 9 (family history – MDD diagnosis ), 10 (mastery – suicide attempt), and 11 (mastery – MDD diagnosis). The model
explains 19.6% of the variance of MDD diagnosis and 5.9% of the variance of suicide attempt.
Hypotheses 4 (alcohol use – suicide attempt), 5 (alcohol use – MDD diagnosis), 6 (childhood
abuse – suicide attempt), and 7 (childhood abuse – MDD diagnosis) were not supported. Further
analysis using linear regression was conducted to examine whether higher levels of problematic alcohol use would have a greater effect. Original cut-off scores were used based on the AUDIT manual which stated those with scores above eight would require intervention. The revised cut-off scores used were also based on the AUDIT manual which suggested that medium alcohol problems (scores 8-15) would require mild intervention and those with high alcohol problems (scores above 16) would require more intensive intervention. Further analysis examined those with high alcohol problems which also failed to show a statistically significant relation to suicide
attempt or MDD diagnosis.
Sex, education, and age were added as control variables to see if the relationships could be explained by demographic factors. Examination of the significance levels of the variables revealed adding sex, education, and age in the model did not have an additional effect on suicide. These results are included in Table 1.
In summary, MDD diagnosis and suicide attempt were found to be related with each other, as well as social network, mastery, and family history of depression. Taking the results into account, the new model created by this study is below:
Figure 3. SEM Model. This figure illustrates the final model.
4 Discussion
Use of a structural equation model examined factors as they relate with suicidal behaviour as well as how they relate to each other. In this way, a variety of biopsychosocial factors were able to be examined simultaneously. The model outlines the significant factors related to suicidal behaviour. After analysis, family history of depression, social support, mastery, and MDD
diagnosis were associated with suicide attempts. These were incorporated into a new model to
outline the factors necessary to include when identifying suicidal behaviour. Below, each factor in the model is explained, as well as those that were not included in the final model.
4.1 Suicide attempt and MDD diagnosis
Depression has long been known to be a powerful risk factor for suicidal behaviour. In this study too, MDD diagnosis and suicide attempt were found to be strongly related with each other. In fact, all factors in this study which were associated with one were associated with the other. Additionally, those that were not associated with one were also not associated with the other. This implies that depression and suicidal behaviour are inherently connected, which coincides
Suicide Attempt
MDD Diagnosis
Social Network
Family History of Depression
e1
1
e2
1
with prior research (Culp, Clyman, & Culp, 1995; Davidson, Wingate, Grant, Judah, & Mills, 2011; Gvion & Apter, 2012; Kessler, Borges, & Walters, 1999; Sanchez & Le, 2001). This supports the emphasis that already exists on examining symptoms of depression when one mentions suicidal ideations, and to check for suicidal ideation for those with depressive symptoms. Even though not all who are depressed are suicidal and vice versa (Gvion & Apter, 2012), as they are so closely connected, it is still important to discuss both with the individual. This study supports the conclusion that treating depression, when present, is essential in combating suicidal ideation; particularly as treating depression will make it easier for the individual to begin addressing other factors which would work towards reduction of suicidal thinking.
4.2 Factors associated with suicide and depression
Many factors have demonstrated links to both suicidal behaviour and depression. In this study, it was important to address factors for depression in addition to suicidal behaviour and examine variables which may influence either, both, or neither. Specifically, factors examined were alcohol use, experience of childhood abuse, level of mastery, family history of depression, and social network. It was proposed that all factors would be related with both suicidal behaviour and depression.
4.3 Alcohol use and childhood abuse
Despite our expectations, childhood abuse and alcohol use were not related with either depression or suicidal behaviour, which seems to contradict the findings of past studies. As those who were included in the study were adults, potentially, the results may indicate that the effects of childhood abuse do not directly affect those in adulthood. Rather, the experience of abuse as a child may influence other factors in one’s life. Further specification of the type of childhood abuse or different type of childhood trauma could also find evidence to support the link between childhood abuse and suicide behaviour. As for alcohol abuse, although studies referred to it as a factor associated with suicide, the current study was not able to replicate those findings. This may be due to other factors having a stronger association with suicide. Many studies suggest that an aspect which often relates alcohol use and suicidal behaviour is aggression (Sher, 2006b;
Modetso-Lowe, Brooks, & Ghani, 2006). Unfortunately, it was not possible to examine levels of aggression with the data available; however, other studies may find it useful to include aggression when examining alcohol and suicide in the future as they may moderate the effects of alcohol use and suicide to an extent. Additionally, both alcohol abuse and childhood abuse were examined using self-report questionnaires. Perhaps, alternative measures would better fit the participant population within the study.
4.4 Mastery
The current study adds to evidence which supports mastery is significantly related with MDD
diagnosis and suicide. The results of our study follow as participants with low levels of mastery
exhibited higher levels of suicidal behaviour and rate of depression while those with high levels of mastery demonstrated low levels of suicidal behaviour and a lower rate of depression. Not only are these results invaluable in having a greater understanding of mastery’s connection with depression and suicide, but they also indicate a directional focus for treatment. Increasing a person’s level of mastery has been demonstrated to improve overall health (Lachman and Agrigoroaei, 2010). A high level of mastery is related to a feeling of internal locus of control, meaning the individual feels the actions they take directly effect the environment around them. This is opposed to an external locus of control which attributes changes in the environment to random acts such as luck, chance or coincidence. For those with low mastery, their environment seems unpredictable and uncontrollable resulting in a feeling of helplessness (Jaswal & Dewan, 1997; Zawawi & Hamaideh, 2009). Altering an individual’s feeling of control in their lives could have great impact in reducing both depression symptoms and suicidal behaviours. Lazarus and Folkman (1984) define stress as a fissure between an individuals’ perception of a challenge placed before them and their expectation of their capability to meet the demands of that challenge. As the stress-diathesis model demonstrates, when the stressor appears is the time in which the vulnerabilities of the individual are tested. Suicide has been documented as a way in which individuals cope poorly in the presence of such stress (Lewis & Frydenburg, 2002). The assumption for mastery in the current study is that one who believes to have much control over their life will likely be more capable to cope well with stressors. Morgan, Harmon, and Maslin-Cole (1990) speak of mastery motivation, which they define as ‘a psychological force that
stimulates an individual to attempt independently, in a focused and persistent manner, to solve a problem or master a skill or task which is at least moderately challenging for him or her.’ A person with internal locus of control, will likely be more motivated to cope with stressors in their life. In this way, if individuals are treated to alter their perspective of their capabilities in dealing with proximal stressors, their mastery will increase and so will their resilience to other stressors in the future.
It is important to examine mastery further when developing risk assessments for suicide, but also preventative programs. Research has shown that mastery levels are adaptable (Zaatra et al., 2012; Huang & Ford, 2011) which can have a large impact in treatment for both depression and suicidal behaviour. If a person’s sense of control can increase their ability to cope with the situations around them, this has major influence for their well-being in general.
4.5 Social network
The present study also demonstrated social network to be significantly related with MDD
diagnosis and suicide. Many studies have come to the consensus that indeed a strong social
network is connected to a more positive level of mental health (Grav, Hellzen, Romild, & Stordal, 2011; Wilkinson & Marmot, 2003). In terms of suicidal behaviour, those with stronger social bonds reported less suicidal behaviour and depression. This connection may be due to the fact that those with strong relationships have people they feel they can rely on, whereas those with fewer connections may struggle with reaching out to those around them. Bearman & Moody (2004) demonstrated clearly that the number of people within an individual’s perceived social network was strongly related to the suicidal behaviour of that person. For Bearman & Moody (2004), this was especially true for females. In the current study, controlling for gender had no effect and evidence held that the strength of an individual’s social network was negatively related to a person’s suicidal behaviour for both men and women. A person with strong social bonds may be more likely to communicate issues they are dealing with which is considered a positive coping strategy. Support from both of one’s parents demonstrates lower rates of depression than children receiving support from one parent, or where the support is ambiguous (Marcotte, et al., 2002). Therefore, not only is it important to the individual to have members
within their sphere of influence, but also for those members to be a source of positive support (Kleiman & Riskind, 2013; Marcotte et al., 2002). It is not enough for there to merely to be accessible people, it is essential the individual utilize their support network (Kleiman & Riskind, 2013). In fact, it has been demonstrated that the act of support seeking has been associated with lowered rates of suicidal behaviour (Khurana & Romer, 2012). Knowledge that social bonds are a risk factor for suicidal behaviour reveals the importance for practitioners to be asking questions which probe this area. It is noteworthy that questioning friends or family of the individual may not provide the most accurate information as the best indicator is the individual’s personal perception which seems to matter in this area (Kleiman & Riskind, 2013).
Additionally, social network was related with MDD diagnosis as those who reported strong social bonds also tended not to have experienced a diagnosis of depression in their lifetime. Stereotypically, social support has been thought of as a women’s issue and that men do not require it as much; however, the current study supported that a person’s social network is negatively related with their history of depression for both men and women. A greater number of individuals within a person’s social sphere can positively affect their level of depression. In other studies, the impact of this has been a stronger level of emotional support and tangible support (Grav et al., 2011). Examination of the effects of health-promoting factors have demonstrated that promotion of social networks, along with other factors, has a positive effect on an individual’s general well-being in addition to depressive symptoms later in life (Berkman, Glass, Brissette, & Seeman, 2000; Lachman & Agrigoroaei, 2010). As such, social support is an adaptable aspect of human function which lends itself to be a crucial aspect to the treatment of depression and a protective factor against suicide.
4.6 Family history of depression
There is a significant relation between family history of depression and MDD diagnosis, as well as a between family history of depression and suicide attempt. These results imply having parents with depression makes it more probable that a person will struggle with depression over their lifetime and it also increases their risk of engaging in suicidal behaviour. In past studies, those who had one or both parents suffering from depression experienced earlier onset and a more
severe course of depression (Hirschfeld & Weissman, 2002; Lieb, Isensee, Hofler, Pfister, Wittchen, 2002; Weissman et al., 2005). These studies implicate genetics to be a strong factor in the hereditary nature of depression. In addition to the genetic component, modelling may also play a role in the development of depression in the children of those diagnosed with depression, particularly as those with depression often utilize poor coping mechanisms which may then be modelled to their children. Not only are the children more vulnerable to depression, they are also more likely to not have been shown the appropriate methods of dealing with stress.
Further investigation into the results indicated family history of depression is significantly related with mastery and social network. These results suggest family history of depression may negatively influence coping strategies to deal with depression and suicidal behaviour. This has been demonstrated in other studies as well (Lieb et al., 2002). The present study does not clarify whether the influence of family history of depression is due to genetic similarities with the parents or if these relations are largely explained by social circumstances. Further studies would have to be conducted to clarify the grounds of these relations.
4.7 Limitations
There are limitations to the current study which should be noted. Variables such as MDD
diagnosis, suicidal behaviour, social network and family history of depression were based
entirely on self-report which can be suspect to bias or false reporting and may not obtain an overall picture of the individual. Future studies may seek to incorporate collateral information and actuarial measures to obtain a more valid result. A major limitation of the study was the requirements of the statistical program to the inclusion of only eight factors and to exclude any participants with missing data. Further research should be sure to include all relevant variables to encompass a wider range of potential factors. Generalizations of this research outside of the Netherlands should be treated with caution as it inherently focused on those in the Netherlands who speak Dutch fluently, thus eliminating many immigrants and non-Dutch speakers.
4.8 Future Research
There has been demonstrated evidence which indicate both childhood abuse and problematic alcohol use would be related with depression and suicide; however, this study found no significant relation. This is not to say that childhood abuse and alcohol use would not affect depression and suicidal behaviour in some way. Both exemplify aspects that may damage or negatively influence coping strategies and both serve as a primer for the development of mental illness. It should be noted that a relatively high percentage of individuals scored positively for the presence of childhood abuse in this sample. As many participants unfortunately have experienced abuse in their childhood, future research may want to focus on the severity levels of the abuse experienced which may have more specific implications on depression and suicidal behaviour.
There have been various thoughts on how social support impacts depression levels and suicidal behaviour. It is important for further research to determine the mechanisms behind social support and the manner in which it affects various aspects of an individual’s mental and general health. In this way, encouragement of social bonds will have a more direct focus and can be adapted to programming and treatment in a purposeful manner.
Another aspect which is important to examine is the impact of a family history of suicidal behaviour as there is evidence that this is also impactful for individual’s pattern of suicidal behaviour (Lizardi et al., 2009). In fact, some research has shown that parental history of suicide impacts their offspring’s suicidal behaviour irrespective of any psychiatric issues (Sorensen et al., 2009). Unfortunately, this was not possible to include in the current study due to the limitation of the data collected.
While each of the above factors is important to identify, even more useful is understanding the integration of these factors. From the study, we can extrapolate that those who have a higher level of mastery, strong social support, no diagnosis of depression, and no history of family depression are not likely at risk for suicidal behaviour. However, future research should examine the minimum levels for an individual in each of these areas in order to determine the threshold
level for risk of suicide. Investigating the hierarchy of importance for these factors to determine which is most important to improve and by how much will allow practitioners additional information to treat those struggling with suicidal thoughts. Focussing on how the protective and risk factors balance each other would be of note as well (e.g. having strong social supports, yet a history of family depression).
As our study revealed 5.9% of suicide can be attributed to social network, family history of
depression, MDD diagnosis, and mastery, further research is needed to determine other factors
related to suicide. In any case, a multi-modal approach to treating various aspects similar to those addressed in the current study has been suggested in order to improve individual’s overall functioning, specifically in regards to their health (Lachman and Agrigoroaei, 2010). Research examining the success in treating multiple factors simultaneously will be an important follow up to the current study to determine whether the specific factors outlined can improve outcomes for a similar population.
4.9 Implications
Studies have shown that additive protective factors and an integrative treatment approach provides the best results in the well-being of individuals (Lachman and Agrigoroaei, 2010; O’Connor, 2003; Schutte, et al., 2006). Examination of multiple factors for various physical and mental illnesses is necessary in order to provide individuals well-rounded assessment and treatment which address multiple aspects of their functioning. Focussing on an individual’s family history, level of social support, level of mastery, and presence of depression, will identify not only whether they are at risk for suicidal behaviour, but also will point to important protective factors to be enhanced. This study, along with others of its kind help fuel the development of programming, treatment, and general public knowledge of the risk and protective factors related to suicide and depression. Furthering of the mechanisms involved in factors associated will strengthen the research in this area and assist in lessening the suffering and death of individuals worldwide. Specifically, this study was able to identify mastery, social support, family history of depression, and a diagnosis of depression as factors which can be considered together when examining suicidal behaviour. While they are all important factors on their own, together, they
provide the additive benefit of addressing biological, psychological, and social factors simultaneously to provide the most influence on suicidal behaviour. Treating depression may be one piece of the puzzle; however, strengthening their social network, increasing their level of mastery are concrete aspects which should also be addressed and improved upon to reduce the risk of suicidal behaviour.
Even though addressing various factors on their own has benefit for the individual, research has demonstrated an additive effect has significantly more strength in improving individual’s well-being (Lachman & Agrigoroaei, 2010). This study has demonstrated multiple factors which should be incorporated into suicide risk assessments as well as treatment for those at higher risk of suicide and depression to ensure many factors are addressed. Unfortunately, static factors such as family history are not changeable in treatment; however, the information itself provides much value and perhaps the effects of an individual with a family history of mental illness will be adaptable (e.g. coping mechanisms).
An important implication of this research is the development of preventative programs for patients who may be vulnerable to suicidal behaviour. These programs would address the biopsychosocial factors in an integrative format which would increase the patient’s resistance to vulnerabilities they already possess by providing them better coping strategies and increase their resistance to suicidal behaviour.
A further implication is recognition of patients at risk for suicidal behaviour. Mental health practitioners who are able to recognize a variety of factors present in their patients will firstly identify patients who could benefit from treatment intervention. Development of programs is essential; however, positively identifying those individuals who would most benefit from the treatment is ideal. Identification of low levels of mastery, low levels of social support, presence of depression, and a family history of depression, will assist in identifying those at risk of suicidal behaviour. From there, those individuals can be placed into preventative treatment in order to enhance factors which will protect them from acting on suicidal thoughts.
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Table 1: Demographics of the study sample (N = 1983) Variables n (%) Gender - Male 640 (32.3) - Female 1343 (67.7) Education
- Elementary not completed 27 (1.4)
- Elementary 98 (4.9) - Lower vocational 272 (13.7) - General intermediate 200 (10.1) - Intermediate vocational 328 (16.5) - General secondary 247 (12.5) - Higher vocational 513 (25.9) - College 25 (1.3) - University 273 (13.8)
Major Depressive Disorder
- Absent 743 (37.5) - Present 1240 (62.5) Alcohol use - Not problematic 1605 (80.9) - Problematic 378 (19.1) Childhood abuse - Absent 1225 (61.8) - Present 758 (38.2) Mastery - Low 851 (42.9) - Mid 435 (21.9) - High 697 (35.1)
Family history of depression
- Absent 430 (21.7)
- Present 1553 (78.3)
Suicide Attempt
- Absent 1760 (88.8)
Table 2: Construct Variances (In Parentheses on the Diagonal Axis) and Relations 1 2 3 4 5 6 7 1 Suicide attempt (0.09) *** 2 MDD diagnosis 0.14 *** (0.19) *** 3 Mastery -0.10 *** -0.36 *** (0.78) *** 4 Family history 0.05 * 0.15 *** -0.13 *** (0.17) *** 5 Childhood abuse 0.01 0.01 -0.04 -0.01 (0.23) *** 6 Social network -0.06 * -0.11 *** 0.24 *** -0.08 *** -0.03 (1.31) *** 7 Alcohol use -0.04 -0.01 -0.10 *** 0.03 0.00 -0.03 (0.13) *** *p < .05 (two-tailed) **p < .01 (two-tailed) ***p < .001 (two-tailed)
Table 3: Standardized Regression Weights and Model Fit of the Structural Model
*p < .05 (two-tailed) *** p <.001 (two-tailed)
Independent variable Dependent variable Model
Hypothesis 2 Social Network Suicide attempt -0.07 ***
Hypothesis 6 Childhood abuse Suicide attempt -0.01
Hypothesis 4 Alcohol use Suicide attempt -0.04
Hypothesis 8 Family history Suicide attempt 0.05 *
Hypothesis 10 Mastery Suicide attempt -0.10 ***
Hypothesis 3 Social network MDD diagnosis -0.11 ***
Hypothesis 7 Childhood abuse MDD diagnosis 0.01
Hypothesis 5 Alcohol use MDD diagnosis -0.01
Hypothesis 9 Family history MDD diagnosis 0.15 ***
Hypothesis 11 Mastery MDD diagnosis -0.36 ***
Hypothesis 1 MDD diagnosis Suicide attempt 0.14 ***
Model fit indices
0.02 df 1 p .892 CFI 1.00 TLI 1.03 RMSEA 0.00
