The vast majority of research on suicide risk focuses on negative factors that increase the chances of an individual engaging in intentional self-harm (e.g., Beck, Kovacs, & Weismann, 1979; Joiner & Rudd, 1996).
The different approach to assessment suicide risk arose with the product and development of the Reasons for Living Inventory (RFL; Linehan, Goodstein, Nielsen,& Chiles, 1983). Linehan and colleagues chose to examine the cognitive factors that allow individuals desire to living in the face of hardship and adversity. They say that suicidal individuals lack coping characteristics possessed by normal individuals and have important role in understanding suicide risk. Their new scale allowed to therapist differentiated suicidal and normal individuals to be based on the content of their belief systems. This scale has a 48-item and six valid and reliable subscales: Survival and Coping Beliefs (SCB), Responsibility to Family (RF), Child Related Concerns (CRC), Fear of Suicide (FS), Fear of Social Disapproval (FSD), and Moral Objections (MO).
The RFL and its psychometric properties have been examined and supported in several studies (Kralik & Danforth, 1992; Osman et al., 1993; Osman, Gregg, Osman, & Jones, 1992; Osman, Jones, & Osman, 1991). Findings on sex differences with the RFL have varied. One study found no differences in scores across subscales (Osman et al., 1991), whereas women scored higher than men on some subscales, such as FS, RF, and MO, in others (Hirsch & Ellis, 1996; Osman et al., 1993; Osman et al., 1992; Osman et al., 1991).
The RFL has been used in a variety of studies with college students in the countries like United States and Australia as a means of examining protective factors (Hirsch & Ellis, 1996). Results of Dyck et al (1991) showed weak but significant negative correlations between total RFL score and hopelessness, and they belief that the RFL have a distinct construct have supported. In addition, Hirsch and Ellis (1996) found that suicide Ideators could be distinguished from normal based on their scores on the RFL. Connell and Meyer (1991) grouped college students into categories based on reported history of suicidality and found that the SCB, RF, and MO subscales adequately discriminated between groups. The clinical utility of the RFL has been demonstrated with both adult outpatient (Dyck, 1991) and psychiatric inpatient samples (Strosahl, Chiles, &Linehan, 1992). Dyck concluded that the RFL is less influenced by depression than a commonly used measure of hopelessness and may therefore be a better measure of suicide risk with depressed patients.
Strosahl and colleagues found that the SCB subscale of the RFL was the best at discriminating across of desire to suicide in a group of patients with a history of suicide. Range, Hall, and Meyers (1993) examined the factor structure, reliability, and validity of the RFL when used with adolescents. Their sample included 128 high school students between the ages of 14 and 17, plus a comparison sample of 153 college students under the age of 20. Their confirmatory factor analysis (CFA) failed to fit the data from either sample to the original RFL six-factor structure or to a five-factor solution (deleting CRC items).
However, Range et al. (1993) were able to derive two unique six-factor solutions accounting for 53.6% of the variance in high school student data and 49.8% of variance in college student data. The authors determined internal consistency reliability of all original RFL subscales except MO to be adequate in both samples (range of Cronbach = .77 to .91).
Westfield, Cardin, and Deaton (1992) based on original RFL scale produced an RFL-type measure specifically for the college student population. Similar original RFL scale they derived a six-factor solution. But they put college-related concerns factor in new scale and remove child-related concerns factor for a specific, increased importance placed on friends in addition to family. College Student Reasons for Living inventory included: SCB, College and Future-Related Concerns, MO, Responsibility to Friends and Family, FS, and FSD (Westfield et al., 1992). The psychometric properties of the College Student Reasons for Living inventory examined and accepted in the several studies (Rogers & Hanlon, 1996; Westfield, Bandura, Kiel, & Scheel, 1996).
Utility of the RFL with the adolescent population in the several studies examined. Cole (1989) based on five subscale (CRC was dropped) of six subscale RFL compared high school students and adolescences delinquents. They results were consistent with Linehan et al. (1983) but MO failed to significantly correlate with depression, hopelessness, or suicidality in the delinquent adolescences (Cole, 1989). In the other hand, the high school sample Ideators were distinguished from attempters based on their MO scores.
Results study of Pinto, Weismann, and Conwell (1998) Instead, exploratory components analysis yielded a five-factor solution accounting for 66.5% of the variance failed to replicate the original RFL factor structure with adolescent psychiatric inpatients.
Based on the available data, it appears that the theoretical base of RFL is adequate to adolescents. However, the results of past studies when the RFL is used with adolescents and college students suggested the need for a unique measure for adolescents (Osman et al., 1996).Therefore decided to develop a new measure, based on the underlying theory of the RFL, specifically for adolescents.
Improved ways of assessing the level suicide risk in the Iranian adolescents is necessary. Based on annual data for 2006 collected from Social Welfare organization, from 5 attempt for suicide three of them are adolescents between age 12 to 24 (Social Welfare organization 2006). In the all cities and state of Iran, Kermanshah have upper rate of suicide. The rate of completed suicides in the 15- to 24-year-old age group has deviated from a mean of 6.1 (per100, 000 population) for the 1387(2008) year in the Kermanshah city (Emam Khomeini hospital of treatment suicide). These data suggest that intentional self-harmful behavior and the potential for engaging in such behaviors are a serious concern for young people, parents, teachers and counselors and overall society in the Kermanshah city.
The RFL–A is a 32-item self-report measure designed specifically to assess adolescents’ adaptive reasons for not committing suicide. It is comprised of five factors: Future Optimism (FO), Suicide-Related Concerns (SRC), Family Alliance (FA), Peer Acceptance and Support (PAS), and Self-Acceptance (SA). Less relevant items (e.g., relating to concerns about the effects of suicide on one’s children) are not included in the RFL–A. The factor structure of the RFL–A is consistent with the multifaceted nature of adolescent suicidality (Osman et al., 1998). The authors also found support for convergent and construct validity. Important group differences on the RFL–A were identified. Specifically, boys had significantly higher SA scores, adolescents in the normal group scored higher on all subscales than an suicidal group, and a psychiatric no suicidal group scored higher than a psychiatric attempter group. The main purpose of this study was to confirm the factor structure of the RFL–A derived by Osman et al. (1998) in the Iranian adolescents (Kermanshah city).and we tested the hypothesis that: 1) the RFL–A can distinguish adolescent on suicide group from normal. 2) Finally, we hypothesized that the RFL–A would discriminate between suicide attempters and no attempters better than the Beck Hopelessness Scale (BHS; Beck, Weismann, Lester, & Trexler, 1974).
Participants (189 boys and 211 girls) were recruited from all Kermanshah high schools and patients between age 15 to 24 that because attempt to suicide be care in Farabi hospital. Boys (M age = 15.42, SD = .88) and girls (M age = 15.86, SD = 1.04) did not differ significantly in age, t (221) = .21, p = .83. Most of the participants were Kurd (94.4%), 3.1% were Lack, and 2.5% were Fars. Data collected from the total sample of participants were used to assess the factor structure of the RFL–A. To explore additional psychometric properties of the RFL–A, we collected complete data on the measures used in this study on a subsample (n = 96; 54boys and 42 girls) of participants (see Measures and Procedure section). We assigned these participants to two groups based on information obtained by author and a review of the medical records. In addition to the semi structured (i.e., clinical interviews).
Participants in the group suicide (13 boys and 25 girls) with a history of multiple suicide attempts who were admitted because of a recent (within 1–2 weeks prior to admission) suicide attempt (self-harm or injury with established intent to die) were assigned to the attempter group (n = 14). The method of attempts identified included drug or medication overdoses (n = 5), self-inflicted lacerations (n = 3), hanging (n = 8), attempts to use a gun (n = 3), car accidents (n= 2), and jumping from heights (n =3). Participants in the normal group (176 boys and 186 girls) who had no previous history of suicide attempts.
Measures and Procedure
Each participant completed a brief demographic questionnaire, the RFL–A, the Beck Suicide Scale Ideation (BSSI), and Oxford Happiness Inventory (Argyle et al, 1987).
Reasons for living inventory for adolescents (RFL-A; Osman et al., 1998). The RFL–A is a 32-item self-report measure designed specifically to assess adolescents’ adaptive reasons for not committing suicide. It is comprised of five factors: Future Optimism (FO), Suicide-Related Concerns (SRC), Family Alliance (FA), Peer Acceptance and Support (PAS), and Self-Acceptance (SA). less relevant items (e.g., relating to concerns about the effects of suicide on one’s children) are not included in the RFL–A. The factor structure of the RFL–A is consistent with the multifaceted nature of adolescent suicidality (Osman et al., 1998). The authors also found support for convergent and construct validity.
Beck Suicide Scale Ideation (BSSI; Beck et al., 1974). This 19-item scale is designed to assess prior suicide ideation and behavior, frequency of suicide ideation, threats of suicide, and likelihood of attempting
Suicide someday. The BSSI has been used in several investigations with adolescents and young adults. The BSSI was used as a measure of self-reported suicide likelihood in validating the RFL–A scales. In this study we use from BSSI to assess divergent validation.
Oxford Happiness Inventory (OHI; Argyle et al, 1987). The OHI contains 29 items designed to assess the happens. It also assesses four dimensions of suicidality: happens, hope and positive expectations about future events. Each OHI item is rated on a 4-point scale ranging from 1 (none or a little of the time) to 4 (most or all of the time). The SPS has good reliability and concurrent validity (Tatman, Greene, & Karr, 1993). We used this scale as a measure to assess convergent validation
Beck Hopelessness Scale (BHS; Beck et al., 1974).The BHS is a 20-item self-report instrument with a true–false response format. As in previous investigations, this scale has been used in several investigations to assess the extent of negative expectations about future events (see Joiner & Rudd, 1996; Marano, Cisler,& Lemuroid, 1993).
We collected data from each participant within 4 weeks of admission. Participation in the study was voluntary. During data collection, the second author or a practicum student in psychology (all trained in the administration of the research package) approached and asked each potential participant to volunteer to participate in the study. Next, the study was briefly explained, informed consent was obtained, and the questionnaire package was administered individually. Approval for conducting the study was obtained from the hospital administrator and the Medical Sciences University of Kermanshah. The protocol also included obtaining adolescent assent and significant other (legal guardians and parents) written informed consent before administering the questionnaire packet and reviewing the medical records.
Based goals of study used from below data analyses:
- For analyses material of scales used from classic test model
- Statically features of material of scales assess by descriptive statistics
- Reliability of items each scale assess by kornbakh coefficient and retest
- For assess factor validation and determine number factors of scale used from pc style
- For calculation divergent validation correlation between RFL-A and BSSI assessed.
- For calculation convergent validation correlation between RFL-A and OHI assessed.
- For calculation relationship between RFL-A and other variables like age, gender and education used from T-test and correlation.
- For calculation discriminate validation and comparison mean of two group (suicide and normal) used from T-test.
We examined the internal consistency reliability of the RFL–A total and scales for the combined sample before evaluating the validity of this new instrument. The alpha coefficients for the RFL–A scales were as
Follows: FA = .88, SRC = .92, SA = .91, PAS = .89, and FO = .90. The corrected item-total correlation for each scale was greater than .40. The alpha index for the RFL–A total scale was .93. These findings are consistent with those reported by Osman et al. (1998). And result of retest after 2 weeks on subsample (n=50) was .87. in the table 1 we can see mean, std. deviation, Corrected Item-Total Correlation and Cronbach’s Alpha if Item Deleted all question of RFL-A.
table 1 mean, std. deviation, Corrected Item-Total Correlation and Cronbach’s Alpha if Item Deleted RFL-A
Corrected Item-Total Correlation
Cronbach’s Alpha if Item Deleted
Corrected Item-Total Correlation
Cronbach’s Alpha if Item Deleted
Because we can use PC model and achieve this note that data correlation is not zero we should applied Bartlett Test Of Sphericity before PC model and then used PC to examine the five – factor oblique model reported by Osman et al(1998). However we see in the table 2 KMO is .92 and significant (.0001) and therefore we can do factor analysis in the sample group.
Because extraction factors fit with social and cultural structure of sample group , in the section explorative factor analysis we examine the one – factor, two – factor, three – factor, four – factor and five – factor solution model. In the end of this section appears that factor solution model have better and equated with data and were able to derive unique five-factor solutions accounting for 57.8% of the variance in adolescents data(Table 3).
Table 2.KMO and Bartlett’s Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
Bartlett’s Test of Sphericity
Table 3.Total Variance Explained
Extraction Sums of Squared Loadings
% of Variance
% of Variance
For a mixed sample of suicidal and normal adolescents. In addition, we specified and evaluated the fit of 5 competing models, a one- factor, two- factor, three- factor, four- factor and five factors for select best solution way in factor analyses. After do this models it is appears that best solution way for factor analyses is five factors. Table 4 present the RFL-An items internal consistency (alpha coefficients) and descriptive statistics (skewness and kurtosis) for each factor.
Table 4. Reasons for living inventory for adolescents, internal consistency and descriptive statistics
1.Family Alliance (FA)
2. Suicide-Related Concerns (SRC)
3. Self-Acceptance (SA)
4. Peer Acceptance and Support (PAS)
5. Future Optimism(FO)
Based on results PC model of factor analysis material of scale, number factors of RFL-A in the Iranian population was five factors. Because this scale for first time used in this population lower limit of load factors .35 determined (Hooman, 2001). Factors Structure, coefficient reliability and standard error of measurement each factor presented in Table 5 and in the Table 6 we can see Principal Component Analysis with Promax Rotation Method.
Table 5. Factors Structure, coefficient reliability and standard error of measurement five factor
Number of questions
Std. error of measurement
Peer Acceptance and Support
Table 6. Principal component analysis Structure Matrix
Because of the confirmation number factors and explorative factor analysis we used the confirmatory factor analysis and following indexes to evaluate the fit of each model:
1) A relative robust chi-square of 2 or less.
2) Bentler and Bonett normed fit index(NFI) of .90 or greater,
3) Bentler and bonnet non-normed fit index (NNFI) of .90 or greater, robust comparative fit index(R-CFI) of .90 or greater.
4) Root mean squared residual index (RMSR) of .05 or less (see Bentler, 1995; Bentler & Bonett, 1980; Marsh, Balla, & McDonald, 1988).
Results for the one, two, three, four and five factor solution model tested are presented in the Table 3. The five-factor model provided the best solution way model fit to the data. The Satorra-Bentler index (1.34) was less than 2, and NFI, NNFI, and R-CFI values were greater than .90. Also, the RMSR index was less than .05. These results suggest that the five factor solution way model can be reliably replicated in an adolescent sample.
Table 7.Confirmatory Factor Analysis of the Reasons for Living Inventory for Adolescents for five models
Discriminate, divergent and convergent validity
We conducted planned comparisons to determine divergent and convergent validity of scale and determine whether the RFL–A scales can distinguish adolescent based on suicide status. Results for achieve divergent and convergent validity in the Table 8 showed there was a positive correlation between, RFL–A and Oxford Happiness Inventory (OHI; Argyle et al, 1987) and negative correlation between this scale and Beck Suicide Scale Ideation (BSSI; Beck et al., 1974).
Table 8.Correlations between the RFL–A and Concurrent Validity Measures
Oxford Happiness Inventory
Beck Suicide Scale Ideation
Beck Hopelessness Scale
Note: RFL–A = Reasons for Living Inventory for Adolescents; FA = Family Alliance; SRC = Suicide-Related Concerns; SA = Self-Acceptance; PAS = Peer Acceptance and Support; FO = Future Optimism;.
*p < .001, **p < .005
For comparisons between the suicide (n = 38) and normal (n = 40) groups, the overall t-test was significant, t = .78, F (5, 168) = 26.04, p < .001; η2= .44. The normal group scored significantly higher than did the attempter group on all five RFL–A scales (all p values < .001). (See Table 9 and Table 10).
Pearson product–moment correlations were computed between the RFL–A total and scales, and the con-current validity measures (the BSSI, BHS and OHI scales). The results are presented in Table 8 for the total sample. The analyses showed that all of the RFL–A total and scale scores were negatively and significantly correlated with scores on BSSI items (range = –.44 to –.61). Similarly, negative and significant correlations were obtained between scores on the RFL–A total and scales and scores on the BHS. And also positive and significant correlations were obtained between scores on the RFL–A total and scales and scores on the OHI. These results showed that RFL-A have good discriminate, divergent and convergent validity and specially can discriminate Suicide Attempters from normal Adolescents.
Table 9.Independent Samples Test For comparisons between the suicide and normal group
Equal variances assumed
Equal variances not assumed
Table 10. Means and Standard Deviations on the Reasons for Living Inventory for Adolescents for normal and suicide attempters
Note: RFL–A = Reasons for Living Inventory for Adolescents; FA = Family Alliance; SRC = Suicide-Related Concerns; SA = Self-Acceptance; PAS = Peer Acceptance and Support; FO = Future Optimism.
The purpose of this study was to assess the reliability, validity, and standardization of the Reasons for Living Inventory for Adolescents (RFL–A; Osman et al., 1998) among Iranian Adolescents (Kermanshah city). Several tools have been developed to help counselors and psychologists in determining which adolescents are most likely to attempt to kill themselves and which group is at the greatest risk for suicide. The majority of research and existing measures in the felid of adolescents’ suicide focus on negative predictors of risk like depression, hopelessness and history of prior attempt for suicidal behavior. A major character of Linehan’s RFL (Linehan et al., 1983) is opposite the negative predictor approach that assesses potentially life-threatening crises, this approach allows for the assessment of adaptive reasons for living. Although this measure has been used with varying degrees of success with young adults and adolescents, it has certain limitations (e.g., Cole, 1989; Hirsch & Ellis, 1996; Osman et al., 1996; Pinto et al., 1998). Because these limitations Osman et al. (1998) created a psychometrically sound measure for adolescents based on the theoretical constructs underlying the RFL.
The results of this study add support to existing data (Osman et al., 1998) on the reliability and validity of the RFL–A. Our study also provides preliminary normative data for non suicide (normal) and suicide attempter adolescents in the Kurdish adolescents (city Kermanshah). Although no differences were found on subscale scores within the suicide attempter adolescents, girls in the attempter group scored lower on FA, PAS and SRC, suggesting a pattern of suicide and decrease reasons for living in the Kermanshah that opposite with world pattern (women 3 times more men have successful suicide). Perhaps girls who engage in serious suicidal behavior have lost their connections to family and friends, and may these lower scores indicate increase tolerance of pain (as one components of suicide). It is unclear why boys who have made an attempt would get higher scores in these subscales in the same group. This finding will need to be explored in future
The total RFL–A score was very useful in distinguishing between the non suicidal (normal), and suicide attempter groups. As was expected, adolescents in the non suicidal group had the highest total scores, and suicide attempter groups’ scored lowest. A significant amount of variance in scores on suicide probability were explained by the RFL–A. Low levels reasons for living appear to be indicators of greatest suicide risk. Scores on the RFL–A were also predictors of achieve scores in suicide ideation. Our analyses indicated that more hopeless and more suicide ideation of adolescents have limited optimism about the future, low levels of peer acceptance and support, and a weak sense of alliance with their families. These findings congruent with prior studies (Osman et al, 1998; Gutierrez et al, 2000).
In the several areas the RFL–A appears relate to adolescent suicide risk. For example, the SA subscale predicts depression, anger, alienation, and family problems (Gutierrez et al, 2000). The RFL–A can provide specific guidance to clinicians and counselors on where and when do interventions and assessment for improvement desire to life and decrease suicide in adolescents.
Additional support for the discriminative ability of the RFL–A comes from the results of the t scores and discriminate validity analyses. The RFL–A was found to be a significantly better than other scales that widely used tool for this purpose (Joiner & Rudd, 1996) can predicate suicide like hood. Results showed that the RFL–A and the theory underlying measures of adaptive functioning (e.g., Linehan et al., 1983; Osman et al., 1996; Westfield et al., 1992) is useful in assessing suicide risk and this scale more than original RFL (Linehan et al, 1983) have sensitivity, specificity, and predictive value to suicide adolescents. However, the developmentally appropriate RFL–A in the Iran especially in the Kermanshah city because higher statics of suicide is superior for use with adolescents.
A few limitations of this study must be discussed. The majority of participants were Kurdish, making it difficult to determine the racial and ethnic generalizability of the findings. Future studies should attempt to utilize more ethnically and racially diverse Participants like Turkmen, Fars, Lor and Turk people.
It has long been accepted that adolescent suicide risk is multiply determined (Brent, Moritz, Bridge, Perper, & Canobbio, 1996; Pfeiffer, Newcorn, Kaplan, Mizruchi, & Plutchik,1988). Much of the existing literature focuses on negative risk factors (Beck et al., 1974). Only focus on risk factors in the assess suicide is incomplete and inadequate. We are believed that an accurate picture of risk can only be constructed from protocols that include both measures of negative factors and protective elements. We results of our study showed that RFL–A as a reliable, valid, and clinically useful tool for assessing adolescent suicide risk in the Kermanshah city.
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