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Psychiatry International Journal of Social

DOI: 10.1177/0020764004040961 2004; 50; 142 International Journal of Social Psychiatry

Jukka Hintikka and Heimo Viinamaki Kaisa Haatainen, Antti Tanskanen, Jari Kylmaä, Kirsi Honkalampi, Heli Koivumaa-Honkanen,

Ftors Associated with Hopelessness: A Population Study

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FACTORS ASSOCIATED WITH HOPELESSNESS:

A POPULATION STUDY

KAISA HAATAINEN, ANTTI TANSKANEN, JARI KYLMA,KIRSI HONKALAMPI, HELI KOIVUMAA-HONKANEN, JUKKA HINTIKKA

& HEIMO VIINAMAKI

ABSTRACT

Background: Hopelessness is associated with depression and suicidality inclinical as well as in non-clinical populations. However, data on the prevalenceof hopelessness and the associated factors in general population are exiguous.Aims: To assess the prevalence and the associated factors of hopelessness in ageneral population sample.Methods: The random population sample consisted of 1722 subjects. The studyquestionnaires included the Beck Hopelessness Scale (HS), Beck DepressionInventory (BDI), Toronto Alexithymia Scale (TAS-20) and Life Satisfaction Scale(LS).Results: Eleven percent of the subjects reported at least moderate hopeless-ness. A poor financial situation (OR 3.64), poor subjective health (OR 2.87) andreduced working ability (OR 2.67) independently associated with hopelessness.Moreover, the likelihood of moderate or severe hopelessness was significantlyincreased in subjects dissatisfied with life (OR 5.99), with depression (OR4.86), with alexithymia (OR 2.37) and with suicidal ideation (OR 1.85).Conclusions: This study demonstrated a moderately high prevalence of hope-lessness at the population level. Hopelessness appears to be an important indi-cator of low subjective well-being in the general population that health carepersonnel should pay attention to.

Key words: hopelessness, population, risk

INTRODUCTION

In earlier studies, hopelessness has been found to be associated with depression (Beck et al.,1988b; Prezant & Neimeyer, 1988; Whisman et al., 1995; Nimeus et al., 1997), suicidality(Suominen et al., 1997; Malone et al., 2000; O’Connor et al., 2000) and physical sickness(Everson et al., 1997; Swindells et al., 1999). Furthermore, in non-clinical samples it hasbeen shown to be a predictor of depression (Rholes et al., 1985; Alford et al., 1995), and inclinical populations a predictor of long-term suicidality (Beck et al., 1985, 1990; Fawcett etal., 1987; Young et al., 1996).

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In general, baseline hopelessness, even without clinically verified depression, may predict afuture suicide attempt (Young et al., 1996). When persons prone to hopelessness becomedepressed, they experience higher levels of suicidal intent than do other depressed patients(Beck et al., 1985). There is also evidence that hopelessness might even be a more importantrisk factor for suicidality than depression (Kovacs et al., 1975; Beck et al., 1985, 1990, 1993;Salter & Platt, 1990). However, it should be noted that not all depressed patients are hopeless(Greene, 1989; Cannon et al., 1999), and hopelessness is not always a predictor of suicidalintent, either (Mendonca & Holden, 1996; Nimeus et al., 1997).

At the population level, data on hopelessness among adult subjects are limited. To ourknowledge, few studies have been carried out in community-based population samples(Tanaka et al., 1996; Pillay & Sargent, 1999), and only a single study in a general population(Greene, 1981). According to this, hopelessness was associated with low socio-economicstatus and increasing age. However, this study was conducted as long as two decades ago,and its sample size (N ¼ 400), as well as the number of risk factors studied were relativelysmall.

The purpose of our study was to assess the prevalence and the mean level of hopelessnessand to identify associated factors in a random sample of the Finnish population. Sociodemo-graphic background variables and psychiatric symptom scales were used to study theserelationships.

MATERIAL AND METHODS

Study population

The study was conducted in the district of Kuopio, which is located in the central-easternpart of Finland. Our population sample included 2945 subjects living in that area, aged25–64 years, randomly selected from the National Population Register. Study questionnaireswere mailed in May–June 1999. A total of 1767 questionnaires were returned. Due to incom-plete data, 45 subjects were excluded from the analysis. Thus, the final sample (n ¼ 1722)included 735 (43%) men and 987 (57%) women, giving a response rate of 58.5%. The meanage of the responding subjects was 45.9 (SD ¼ 10:5) years; men were older than women(46.7, SD ¼ 10:1 years vs. 45.3, SD ¼ 10:7 years, p ¼ 0:008). The subjects were mainlymarried or cohabiting (73.0%), were living in an urban area (74.4%) and were white-collarworkers (75.4%). The complete study design has been described in detail elsewhere (Honka-lampi et al., 2001). Approval for the study was obtained from the Ethics Committee ofKuopio University Hospital and the University of Kuopio.

Hopelessness

The level of hopelessness was assessed by using the Beck Hopelessness Scale (HS), which is a20-item, self-administered rating scale designed to measure an adult’s negative expectanciesconcerning oneself and one’s future life. The Hopelessness Scale is based on three dimensionsof hopelessness: affective (e.g. lack of hope), motivational (giving up) and cognitive (lack offuture expectations) (Beck et al., 1974). The total score of HS ranges from 0 to 20, and thelevel of hopelessness increases with increasing scores. If a response was missing for one or

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two items, the missing item was replaced with an arithmetic mean, while in the case of moremissing items the scale was regarded as incomplete data.

Based on the original cut-off points, the subjects were classified into four groups: no hope-lessness at all (scores 0–3), mild hopelessness (scores 4–8), moderate hopelessness (scores9–14) and severe hopelessness (scores 15–20) (Beck & Steer, 1988). The alpha reliability coeffi-cient (Cronbach’s alpha) for the scale was 0.87 in our study.

Depression

Depression was assessed using the 21-item Beck Depression Inventory (BDI) (Beck et al.,1961). The items of BDI contain four statements each, and reflect the intensity of a particulardepressive symptom. If a response was missing for one or two items, the missing item wasreplaced with an arithmetic mean, while in the case of more missing items the scale wasregarded as incomplete data.

BDI was used as a continuous variable or as a class variable with four groups and the fol-lowing cut-off scores: no depression (scores <10), mild depression (scores 10–18), moderatedepression (scores 19–29) and severe depression (scores 30–63) (Beck et al., 1988a). In themultiple logistic regression analysis the BDI scores were dichotomised (depressive: scores5 10 vs. not depressive: scores <10). Cronbach’s alpha was 0.91.

Suicidal ideation

Suicidal ideation refers to cognitions that can vary from transient thoughts about worthless-ness of life and death wishes to concrete plans for killing oneself and obsessive preoccupationwith self-destruction (Diekstra & Garnefski, 1995). The BDI suicidality item (item 9) can beused in screening for suicidal ideation (Hintikka et al., 2001).

In this study, the answer alternatives (1) ‘I have thoughts of harming myself but I wouldnot carry them out’, (2) ‘I feel I would be better off dead’ and (3) ‘I would kill myself if Icould’ indicated the presence of suicidal ideation, and the answer alternative (0) ‘I don’thave any thoughts of harming myself ’ the absence of it. Item 9 was not included in thetotal score of BDI in the multivariate analysis to avoid overlapping of suicidality item inBDI and suicidal ideation.

Life satisfaction

Life satisfaction was estimated by means of a four-item scale (Koivumaa-Honkanen et al.,2000). The scale comprised the following questions: (1) ‘Do you feel that your life at presentis very interesting (score 1), fairly interesting (score 2), fairly boring (score 4) or very boring(score 5)?’ (2) ‘Do you feel that your life at present is very happy (score 1), fairly happy (score2), fairly unhappy (score 4) or very unhappy (score 5)?’ (3) ‘Do you feel that your life atpresent is very easy (score 1), fairly easy (score 2), fairly hard (score 4) or very hard (score5)?’ (4) ‘Do you feel that at the present moment you are very lonely (score 5), fairly lonely(score 4) or not at all lonely (score 1)?’ The item responses ‘cannot say’ as well as missingdata were scored as 3 in every question. Thus, the range of the sum score for life satisfactionwas 4–20, with increasing values indicating a decrease in life satisfaction.

Total score was used to classify the subjects into the satisfied (scores 4–6), the slightly dis-satisfied (scores 7–11) and the dissatisfied (scores 12–20) (Koivumaa-Honkanen et al., 2000).

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In the multiple logistic regression analysis life satisfaction was categorised into two classes(dissatisfied with life: scores 12–20 vs. others: scores 4–11). Cronbach’s alpha was 0.77.

Alexithymia

The prevalence of alexithymia was screened using the Finnish version (Joukamaa et al., 2001)of the 20-item Toronto Alexithymia Scale (TAS-20) (Bagby et al., 1994a, 1994b). TAS-20consists of three sub-factors: (1) difficulty in identifying feelings and distinguishing themfrom bodily sensations of emotions; (2) difficulty in describing feelings to others; and (3)an externally oriented style of thinking (Bagby et al., 1994a, 1994b). Each item was ratedon a five-point Likert scale, with total scores ranging from 20 to 100. If a response was miss-ing for one or two items, the missing item was replaced with an arithmetic mean, while in thecase of more missing items the scale was regarded as incomplete data.

The total scores of the TAS-20 were categorised according to the recommendations ofBagby and Taylor (1997); thus a score 5 61 indicated alexithymia, and 4 51 no alexithymia.Subjects with a TAS-20 score between 52 and 60 were categorised into the intermediate group(Honkalampi et al., 2001). In the multiple logistic regression analysis alexithymia was cate-gorised into two classes (alexithymic: scores 5 61 vs. others: scores 20–60). Cronbach’salpha was 0.86.

Background characteristics

The subjects reported data on the following factors of their sociodemographic back-ground (classification in parentheses): marital status (married ¼ 1; single, divorced orwidowed ¼ 0); years of education (high i.e. 5 9 ¼ 0; low i.e. <9 years ¼ 1); subjective eva-luation of working ability (good ¼ 0; reduced or unable to work ¼ 1); place of residence(urban ¼ 0; rural ¼ 1); subjective evaluation of financial situation (good or fairly good =0; fairly poor or poor ¼ 1); and subjective evaluation of general health (good or fairlygood ¼ 0; fairly poor or poor ¼ 1).

Statistical analysis

Subjects with moderate or severe hopelessness (HS score of 5 9; n ¼ 193) were comparedwith the others (HS score < 9; n ¼ 1529). The statistical methods used included Pearson’schi-squared test for categorical variables, the independent-samples t-test, Pearson’s two-tailed correlation analysis, analysis of variance for continuous variables and multiple logisticregression analysis (method: enter) to identify factors independently associated with hope-lessness (HS score 5 9). Data analysis was conducted with SPSS 10.0. All statistical testswere two-tailed.

RESULTS

A total of 149 subjects (8.7%) reported moderate and 44 subjects (2.6%) severe hopelessness.The mean score on the Hopelessness Scale was 3.9 (SD ¼ 3:6, ranging from 0 to 20;n ¼ 1722). The prevalence of hopelessness according to gender and age is shown in Table 1.

HAATAINEN ET AL.: FACTORS ASSOCIATED WITH HOPELESSNESS 145

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There was a trend of increasing prevalence of hopelessness with age. Among women, thosewho reported moderate or severe hopelessness were significantly older than the others(48.2, SD ¼ 10:1 years vs. 45.0, SD ¼ 10:7 years, t ¼ 2:947, d:f: ¼ 985, p ¼ 0:003). In men,the difference did not reach statistical significance (48.5, SD ¼ 9:3 years vs. 46.5, SD ¼

10.2 years, t ¼ 1:785, d:f: ¼ 733, p ¼ 0:075).Reduced working ability (subjective evaluation), a poor financial situation (subjective

evaluation) and poor subjective health (subjective evaluation) were significantly associatedwith hopelessness among all subjects. Hopelessness was significantly associated with beingsingle, divorced or widowed in men and with low education in women. Place of residencedid not have any association with hopelessness (Table 2).

The prevalence of hopelessness increased with increasing severity of depression. Moderateor severe hopelessness was found in 88.0% of the subjects with severe depression. Further-more, subjects with suicidal ideation, with dissatisfaction with life or with alexithymia hadan increased prevalence of moderate to severe hopelessness (Table 3).

All the background factors from Tables 1 and 2 that were found to be significantly asso-ciated with hopelessness were chosen as covariates in the multiple logistic regressionmodel. The risk of at least moderate hopelessness was significantly increased in subjects witha poor financial situation, with poor subjective health and with a reduced working abilitycompared with the respective reference groups (Table 4, model A).

Even though intercorrelations between satisfaction with life, depression, alexithymia andsuicidality were rather high (from 0.27 to 0.69), these psychiatric factors were deliberatelyforced into the samemultiple logistic regression model. In this model all the factors were inde-pendently associated with hopelessness (dissatisfaction with life OR 5.99, 95% CI 3.78–9.49;depression OR 4.86, 95% CI 2.95–8.02; alexithymia OR 2.37, 95% CI 1.46–3.84; suicidalideation OR 1.85, 95% CI 1.13–3.03) after adjusting for covariates shown in Table 4,model B. In addition, poor subjective health maintained its association with hopelessnesswhile the other factors did not.

Table 1Prevalence (%) of hopelessness according to gender and age in a general population sample (N ¼ 1722) of

eastern Finland

Level ofhopelessness(HS scores)

Mena

Age group (years)Womenb

Age group (years)

25–34 35–44 45–54 55–64 Total 25–34 35–44 45–54 55–64 Total

Not at all (0–3)Mild (4–8)Moderate (9–14)Severe (15–20)(N)

761671

(106)

682183

(190)

6027103

(260)

5135113

(179)

622693

(735)

732151

(195)

642575

(263)

583372

(307)

4143142

(222)

593182

(987)

a Linear-by-linear association between levels of hopelessness and age groups, �2¼ 13:84, d:f: ¼ 1, p < 0:0005

b Linear-by-linear association between levels of hopelessness and age groups, �2¼ 30:97, d:f: ¼ 1, p < 0:0005

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DISCUSSION

Our results give new information about factors associated with hopelessness in a generalpopulation. This information may help health care personnel to recognise hopelessnessmore effectively than earlier. Our study demonstrates three notable factors significantly asso-ciated with hopelessness. We found that the likelihood of moderate to severe hopelessnesswas about three-and-a-half-fold higher when the financial situation was poor, nearly three-fold higher when subjective health was poor and about two-and-a-half-fold higher whenworking ability was reduced. In contrast to the previous findings of Greene (1981), the posi-tive relationship between hopelessness and increasing age was not observed in our study in themultivariate model.

Further, life dissatisfaction, depressive symptoms, alexithymia and suicidal ideationproved to be the most potent factors associated with moderate to severe hopelessness. Allthese symptom scales measure separate aspects of one’s well-being. Moreover, as all these

Table 2Prevalence (%) of hopelessness (HS-score 5 9) in relation to gender and other sociodemographic factors in a

general population sample of eastern Finland

Men(N ¼ 735)

Women(N ¼ 987)

Total(N ¼ 1722)

Marital statusMarried or cohabitingSingle, divorced or widowed

9.819.5(p ¼ 0:001Þ

9.712.9(p ¼ 0:144Þ

9.715.3(p ¼ 0:002Þ

Education5 9 years< 9 years

10.816.7(p ¼ 0:059Þ

9.218.6(p ¼ 0:003Þ

9.817.6(p < 0:0005Þ

Subjective evaluation of working abilityGoodReduced or unable to work

5.522.6(p < 0:0005Þ

5.420.8(p < 0:0005Þ

5.421.6(p < 0:0005Þ

Place of residenceUrbanRural

11.214.2(p ¼ 0:252Þ

10.511.0(p ¼ 0:812Þ

10.812.4(p ¼ 0:337Þ

Subjective evaluation of financial situationGood or fairly goodFairly poor or poor

6.332.5(p < 0:0005Þ

7.525.3(p < 0:0005Þ

7.028.8(p < 0:0005Þ

Subjective evaluation of general healthGood or fairly goodFairly poor or poor

7.538.7(p < 0:0005Þ

7.435.4(p < 0:0005Þ

7.537.0(p < 0:0005Þ

HAATAINEN ET AL.: FACTORS ASSOCIATED WITH HOPELESSNESS 147

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psychiatric factors at the same time were significantly associated with hopelessness, hopeless-ness could be viewed as a cluster of different clinical manifestations, and accordingly a usefulindicator of low subjective well-being. Among sociodemographic factors, poor subjectivegeneral health only remained significantly associated with hopelessness as examining socio-demographic and psychiatric factors concurrently. To our knowledge, none of the previousstudies has in a general population explored the relationship between hopelessness andreports of life satisfaction, depressive symptoms, alexithymia and suicidal ideation.

This study shows reliable prevalence rates of hopelessness in a general population. In ourstudy, the prevalence of moderate to severe hopelessness was close to the figure of 11.5%reported by Greene (1981). Nevertheless, due to methodological differences, caution isneeded in comparing the results of these studies. In Greene’s study, the cut-off point wastwo points higher than the original one reported by Beck and Steer (1988), which was usedin our study. Thus, we can prudently assume that the prevalence of hopelessness in Irelandin the 1980s was higher than that in Finland at the end of the 1990s. The mean score of hope-lessness in our sample was also slightly lower than that of Irish people (3.9 vs. 4.5) (Greene,1981). In addition to the different points in time of the two studies, the results might alsoreflect cultural differences between Finland and Ireland. Moreover, the sample size inGreene’s study was relatively small.

Table 3Prevalence (%) of hopelessness (HS-score 5 9) in relation to depression, suicidal ideation, life satisfaction and

alexithymia in a general population sample of eastern Finland

Men(N ¼ 735)

Women(N ¼ 987)

Total(N ¼ 1722)

DepressionNoneMildModerateSevere

(BDI scores)(0–9)(10–18)(19–29)(30–63)

3.438.570.492.3(p < 0:0005Þ

2.924.265.183.3(p < 0:0005Þ

3.130.466.788.0(p < 0:0005Þ

Suicidal ideationNoYes

(BDI-item 9)6.9

40.7(p < 0:0005Þ

7.643.5(p < 0:0005Þ

7.342.0(p < 0:0005Þ

Life satisfactionSatisfiedSlightly dissatisfiedVery dissatisfied

(LS scores)(4–6)(7–11)(12–20)

1.14.3

51.9(p < 0:0005Þ

0.46.3

45.0(p < 0:0005Þ

0.75.548.2(p < 0:0005Þ

AlexithymiaNon-alexithymicIntermediate groupAlexithymic

(TAS-20 scores)(4 51)(52–60)(5 61)

4.419.343.0(p < 0:0005Þ

4.722.051.9(p < 0:0005Þ

4.620.547.3(p < 0:0005Þ

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Table 4Risk factors for hopelessness (5 9 scores) in multiple logistic regression models of a general population sample of eastern Finland

Model A Model BVariables Wald Odds

ratio95% CI a p-value Wald Odds

ratio95% CI a p-value

Poor financial situation (subjective)Poor general health (subjective)Reduced working ability (subjective)Single, divorced or widowedAge (years)Low educationMale gender

51.2123.5218.812.870.340.120.00

3.642.872.671.360.991.081.01

2.56–5.191.88–4.401.71–4.170.95–1.930.98–1.010.69–1.690.72–1.40

<0.0005<0.0005<0.0005<0.090<0.562<0.728<0.970

2.044.381.570.000.162.360.01

1.391.761.411.001.001.520.98

0.89–2.171.04–2.970.83–2.400.65–1.540.97–1.020.89–2.580.65–1.49

�NS�0.036�NS�NS�NS�NS�NS

Life dissatisfaction (LS scores 12–20)Depression (BDI scores 5 10)Alexithymia (TAS scores 5 61)Suicidal ideation (BDI item 9)

58.2138.3712.326.04

5.994.862.371.85

3.78–9.492.95–8.021.46–3.841.13–3.03

<0.0005<0.0005<0.0005�0.014

aCI ¼ Confidence interval

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The Beck Hopelessness Scale is occasionally considered to be less reliable for samples inwhich the level of hopelessness is expected to be low than it is for psychiatric patients(Durham, 1982; Young et al., 1992). We have explicit arguments to oppose this view. Thealpha reliability coefficient in our study was high, our sample size was the largest of itskind and the age range of the random population sample covered the entire period of adult-hood. The response rate in our study was satisfactory as we are dealing with a postal survey,and we suggest that our results give a reasonable estimate of the level of hopelessness and thefactors associated with it in an adult population.

We did not conduct any interviews, which can be conceived as a limitation. However, as wewere particularly interested in subjective approximations, we used self-report methods (HS,BDI, LS and TAS-20) and subjective assessments of health, working ability and financialsituation. On the other hand, as the subjects responded anonymously, we have no reasonto doubt that self-report assessments have been confounded by social desirability that haswidely been debated in several studies (Linehan & Nielsen, 1981, 1983; Holden et al., 1989;Ivanoff & Jang, 1991).

The information a cross-sectional study gives may be limited, since hopelessness may bedynamic, not static (Abramson et al., 1989; Beck et al., 1990; Young et al., 1996). Whetherhopelessness is more temporary than stable when a general population is under examinationshould be studied further. In conclusion, the present study broadens the picture of hopeless-ness and the factors associated with it. Hopelessness can be profiled as an important indicatorof low subjective well-being in the general population that should be recognised in everydaymental health work. Thus, as we will be facing subjects with a poor financial situation, poorsubjective health or reduced working ability, we are due to be aware of the possibility ofhopelessness.

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Kaisa Haatainen, MHSc, researcher, Department of Psychiatry, Kuopio University Hospital, Kuopio, Finland.

Antti Tanskanen, MD, senior lecturer, Department of Psychiatry, Kuopio University Hospital, Kuopio, Finland.

Jari Kylma, PhD, senior lecturer, Department of Nursing Science, University of Kuopio, Kuopio, Finland.

Kirsi Honkalampi, PhD, senior researcher, Department of Psychiatry, Kuopio University Hospital, Kuopio, Finland.

Heli Koivumaa-Honkanen, MD, senior lecturer, Department of Psychiatry, Kuopio University Hospital, Kuopio,Finland.

Jukka Hintikka, MD, senior lecturer, Department of Psychiatry, Kuopio University Hospital, Kuopio, Finland.

Heimo Viinamaki, MD, professor, Department of Psychiatry, Kuopio University Hospital, Kuopio, Finland.

Correspondence to Kaisa Haatainen, MHSc, Research and Development Unit 4977, Department of Psychiatry,Kuopio University Hospital, PO Box 1777, FIN-70211 Kuopio, Finland.Email: kaisa.haatainen@kuh.fi

152 INTERNATIONAL JOURNAL OF SOCIAL PSYCHIATRY 50(2)

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