Examining Cultural Validity of the Problem-Solving Inventory (PSI) in Italy
Journal of Career Assessment Volume 17 Number 4 November 2009 478-494 {) 2009 SAGE Publications 1O.l177/1069072709339490 http://jca.sagepub.com hosted at http://online.sagepub.com
Laura Nota University ofPadua
P. Paul Heppner University ofMissouri
Salvatore Soresi University ofPadua
Mary 1. Heppner University ofMissouri
The problem-solving inventory (PSI) is the most widely used applied problem-solving measure in the United States. Although a great deal of validity and reliability information exists for the PSI, much of this data has been collected in the United States. The purpose of this study was to examine the PSI's psychometric estimates with a large sample of Italian high school students across geographically representative regions of Italy. Results revealed a similar but slightly dif ferent PSI factor structure in the Italian PSI, as well as sex differences (which have been rarely found in the U.S. samples) and different associations with intelligence. In addition to providing useful psychometric information for an Italian PSI, this study identifies the complexities of problem-solving appraisal cross-culturally. Finally, this investigation also serves to underscore the necessity to examine the cultural validity of assessment instruments used in the increasing number of cross-national studies: the widespread practice of simply translating inventories developed in one country and then using them in other cultural contexts can create significant methodological problems.
Keywords: instrument construction; problem solving appraisal; coping; cross-cultural validity and Italian sample.
U
nderstanding how people respond to difficult and often stressful problems has received a great deal of attention in applied psychology (see Lazarus & Folkman, 1984; Maier, 1970). People seek professional counseling because they are unable to solve difficult prob lems on their own. In many ways, however, there is still a lack of knowledge about how peo ple grapple with difficult life problems within different cultural contexts (see Heppner, 2008a; Wong & Wong, 2006). Moreover, it remains unclear how much of what is known about applied problem solving is culture specific. A rich line of research has developed around how people appraise their applied problem solving; that is, how they evaluate their problem-solving capacities, and in tum how such an Authors' Note: Correspondence concerning this article should be addressed to Mary 1. Heppner, Educational, School and Counseling Psychology, Columbia, MO 65211; e-mail:
[email protected]. 478
appraisal affects a range Witty, & Dixon, 2004).. Heppner & Petersen, 198. self-report measures ofaI tor analysis of the PSI I approach-avoidance styli 1982). In essence, people feelings of confidence wI sonal control as they diJ problem-solving appraisa (see Heppner, Lee, et aI., More specifically, the over the last 25 years. 80 investigations that th many indices ofpsycholc behavior, eating disorden received some support in Canada, and racial and Americans. The PSI has a ment instruments and beh cancer and acquired brain making and adjustment. behavioral domains sugge tive problem solving, bUi et aI., 2004). Although pl with problem-solving skil to substantially overlap \\ more details). In short, thl pIe, Dixon, Heppner, and behavior was predicted b) Although there has beel still important to recog:nil appraisal was conducted c more needs to be done to f in other countries and cultt: ness around the globe that in other cultures rather thal cated that in some cultures. of control in coping with 1 baum, & Blackburn, 1984: factors in East Asian cultuI Coping Scale (CCS) based In essence, the cultural applied problem solving an role of culture has been ig I
Journal of Career Assessment Volume 17 Number 4 November 2009 478-494 {, 2009 SAGE Publications 10.1177/1069072709339490 http://jca.sa~i>ub.com
hosted at hnp:/Ionline.sagepub.com
:d problem-solving measure y information exists for the )urpose of this study was to ltalian high school students ed a similar but slightly dif ces (which have been rarely Ice. In addition to providing !ntifies the complexities of In also serves to underscore rlents used in the increasing rlply translating inventories rltexts can create significant
'al; coping; cross-cultural
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problems has received
& Folkman, 1984; Maier,
table to solve difficult prob fknowledge about how peo llfal contexts (see Heppner, ,ow much of what is known
'praise their applied problem ties, and in tum how such an
to Mary 1. Heppner, Educational,
[email protected].
Nota et al. / Problem-Solving Appraisal in Italy
479
appraisal affects a range of psychological, physical, and vocational outcomes (see Heppner, Witty, & Dixon, 2004). This line of research has used the problem-solving inventory (PSI Heppner & Petersen, 1982; Heppner, 1988), which is often regarded as the most widely used self-report measures of applied problem solving (Nezu, Nezu, & Perri, 1989). The initial fac tor analysis of the PSI revealed three factors (a) problem-solving confidence (PSC), (b) approach-avoidance style (AAS), and (c) personal control (PC Heppner & Petersen, 1982). In essence, people who perceive themselves as effective problem solvers have greater feelings of confidence when solving problems, approach problems more, and feel more per sonal control as they differ significantly from those who see themselves as having poor problem-solving appraisal on a whole range of cognitive, affective, and behavioral variables (see Heppner, Lee, et aI., 2004). More specifically, the PSI has been studied in more than 130 empirical studies published over the last 25 years. For example, the empirical research indicates from more than 80 investigations that there is a pervasive link across populations between the PSI and many indices of psychological distress, such as depression, anxiety, hopelessness, suicidal behavior, eating disorders, alcohol abuse, and childhood traumas. These findings have also received some support in other countries, such as Italy, Turkey, Hong Kong, South Africa, Canada, and racial and ethnic populations within the United States such as African Americans. The PSI has also been related to physical health across a broad range of assess ment instruments and behavioral outcomes, including adapting to a physical illness such as cancer and acquired brain damage. In addition, the PSI is also related to vocational decision making and adjustment. Most importantly, the patterns in the cognitive, affective, and behavioral domains suggest that a positive problem-solving appraisal indicates more effec tive problem solving, but there are also some important exceptions (see Heppner, Lee, et aI., 2004). Although problem-solving appraisal should not be considered synonymous with problem-solving skills, problem-solving appraisal as measured by the PSI does seem to substantially overlap with problem-solving skills (see Heppner, Witty, et aI., 2004 for more details). In short, the PSI can be a powerful predictor of human behavior; for exam ple, Dixon, Heppner, and Rudd (1994) reported almost 70% of the variance in suicidal behavior was predicted by the PSI. Although there has been some cross-national research using the PSI, as noted above, it is still important to recognize that the majority of the research examining problem-solving appraisal was conducted on White college students and adults in the United States; much more needs to be done to examine the cross-cultural validity and usefulness of this measure in other countries and cultures. It is particularly important given the growing interconnected ness around the globe that instruments created in one cultural context be carefully validated in other cultures rather than simply translated and used. For example, researchers have indi cated that in some cultures, such as Japanese culture, there is an emphasis on different types of control in coping with stressful problems than in most Western countries (Weisz, Roth baum, & Blackburn, 1984). Not surprisingly, researchers also found quite different coping factors in East Asian cultures than western-based coping inventories such as the Collectivist Coping Scale (CCS) based on Asian values (Heppner et aI., 2006). In essence, the cultural context has been assumed or ignored for the most part in the applied problem solving and coping literature (Heppner, 2008a). More broadly, the powerful role of culture has been ignored in the vast majority of American psychological research
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JOulilal of Career Assessment
(Arnett, 2008). Researchers have tended to act in a culture-blind manner, assuming simila rities across cultural groups (Heppner, 2008b). This has definitely been the case with the U.S.-based problem-solving and coping research. Although researchers are beginning to con duct problem-solving and coping research in other countries, most often the instruments have been simply translated rather than examining their validity through factor analyses and other psychometric assessments. The vast majority of the studies call for tests of external validity, but there is a tendency for researchers to maximize internal validity and downplay general izability to other countries or cultures. "All of these issues create a psychological science that over simplifies and homogenizes our knowledge bases, rather than promoting a rich under standing how cultural experiences shape human behavior" (Heppner, 2008a, p. 12). Thus, even though the PSI has been used in several other countries, it remains vitally important to conduct vigorous psychometric studies of the kind in this investigation to examine its cross-cultural validity. The purpose of the current study was twofold: (a) to examine the psychometric properties of the PSI in an Italian culture, taking into account regional differences that may exist even within a single country (northern, middle, and southern Italy); (b) to further our understand ing of applied problem solving by examining problem-solving appraisal in a cross-national setting, thus promoting examination of the cultural validity of the PSI in another culture. Such research may eventually clarify the use of applied problem-solving constructs across diverse environments, and thus facilitate the development of more comprehensive and globally relevant theories about problem solving, coping, and human adjustment. Thus, the specific focus of the current investigation was to examine the psychometric properties of the PSI data in a large, geographically representative sample of Italian high school students, spe cifically with regard to factor structure, normative information, reliability, and validity estimates.
Method Participants The participants were 15,000 adolescents attending the last 2 years of high school. These 15,000 students were drawn from a larger data set of 60,000 students who had taken part in a vocational guidance project under the high patronage of the president of the Italian Republic called Progetto Magellano (Magellano Project). A total of 5,000 participants were from the north, middle, and south ofItaly, respectively. Each ofthe three regional samples consisted of 50% men and 50% women. These students attended high school: in Italy, all students who are awarded a high school diploma, which is earned after successfully passing a final examina tion at the end ofa 5-year course, can emoll at a university. In the sample 59.8% (n = 8,975) attended a lycee (Note: lycees have a 5-year duration and aim especially at preparing students for university education); 44.8% (n = 5,223) a technical school, and 5.3% (n = 802) a train ing school. The mean ages and standard deviations by region were as follows: north (M = 18.3, SD = 1.5), central (M = 18.3, SD = 1.5), and south (M = 18.3, SD = 1.5). The econ omy of the northern region is mainly industrial, whereas the central and southern regions are mainly agricultural.
Procedures
These data were collel collection with high schoc pants and they were infor results. Participants then I I-hr sessions were used
Instruments
PSI, Form B (Heppner ing three filler items; 1 = ual perceptions of his 01 skills. Higher scores indie problem solver. The PSI 1 derived from exploratory , The three factors are as foj The PSC refers to an in& when faced with a novel arise). The AAS is defm problem-solving activities alternative and compare t one is in control of his or 1 though I work on a probl( getting down to the real is the PSI has acceptable inte to high .80s) and good stal week period and .81 over 3 in this study were .92 for respectively. In addition, tJ well established based on 2004). The PSI was translated i speakers who are fluent it compared their two sepafll the Italian translations wen back-translation was comp Italian speaker who is flue English items. Four items I once again and then back semantic equivalence or n 2004). Standardized Magellanc sional interests, types of it learning strategies. Only t1
Nota et al. / Problem-Solving Appraisal in Italy
d manner, assuming simila itely been the case with the Ifchers are beginning to con st often the instruments have Igh factor analyses and other for tests of external validity, idity and downplay general a psychological science that han promoting a rich under lIJpner, 2008a, p. 12). Thus, it remains vitally important investigation to examine its
:the psychometric properties ferences that may exist even b) to further our understand appraisal in a cross-national f the PSI in another culture. ~m-solving constructs across )f more comprehensive and ilUman adjustment. Thus, the sychometric properties ofthe ian high school students, spe lion, reliability, and validity
2 years of high school. These ldents who had taken part in a ~sident of the Italian Republic DO participants were from the regional samples consisted of ,I: in Italy, all students who are :ully passing a final examina he sample 59.8% (n = 8,975) ,pecially at preparing students 1, and 5.3% (n = 802) a train were as follows: north (M = = 18.3, SD = 1.5). The econ ntral and southern regions are
481
Procedures These data were collected by psychologists in classroom settings as part of a larger data collection with high school students in Italy. Each ofthe measures was described to the partici pants and they were informed that they would receive a personalized report of their individual results. Participants then completed a battery of measures during group testing sessions. Two I-hr sessions were used for the administration so that participant fatigue was lessened.
Instruments PSI, Form B (Heppner, 1988) is a 35-item inventory with a six-point Likert scale (includ ing three filler items; 1 = strongly agree to 6 = strongly disagree); the PSI assesses individ ual perceptions of his or her problem-solving styles, rather than actual problem-solving skills. Higher scores indicate an individual's assessment of oneself as a relatively ineffective problem solver. The PSI has a total score (i.e., the sum of the three factors) and three factors derived from exploratory and confirmatory factor analyses (see Heppner, Witty, et aI., 2004). The three factors are as follows: (a) PSC (11 items), (b) AAS (16 items), and (c) PC (5 items). The PSC refers to an individual's belief and trust in one's own problem-solving ability (e.g., when faced with a novel situation, I have confidence that I can handle problems that may arise). The AAS is defined as a general tendency to approach or avoid a wide range of problem-solving activities (e.g., when making a decision, I weigh the consequences of each alternative and compare them against each other). The PC refers to individual's belief that one is in control of his or her own behaviors and emotions while solving problems (e.g., even though I work on a problem, sometimes I feel like I am groping or wandering, and am not getting down to the real issue; Heppner & Baker, 1997). Previous studies demonstrated that the PSI has acceptable internal consistency estimates (the a. coefficient ranging from low. 70s to high .80s) and good stability estimates (test-retest reliability coefficients) of .80 over a 2 week period and .81 over 3 weeks as well as 4 months. The a. coefficients for the sample used in this study were .92 for the PSI total, and .84, .89, and .67 for the PSC, AAS, and PC, respectively. In addition, the construct, convergent, and discriminant validity of the PSI was well established based on more than 120 studies (for a review, see Heppner, Witty, et aI., 2004). The PSI was translated into Italian by using the following process: first, two native-Italian speakers who are fluent in English independently translated each of the items. They then compared their two separate translations to achieve a shared Italian version of each. Next, the Italian translations were back-translated by a professional Italian-English translator. Once back-translation was complete, the professional Italian-English translator and another native Italian speaker who is fluent in English compared each back-translated item to the original English items. Four items required revisions. Each of these items was translated into Italian once again and then back-translated and compared to the original English version until semantic equivalence or meaning of the items was achieved (see Mallinckrodt & Wang, 2004). Standardized Magellano Universita (Soresi, 2000) battery consists of five tests: profes sional interests, types of interests, cultural interests, aptitudes and general intelligence, and learning strategies. Only the fourth and fifth tests were used in this study.
482
Journal of Career Assessment
Aptitudes and general intelligence, which consists of 100 items that assess, on one hand, the general intelligence (l00 items), such as the ability to think and reason regardless of the content to be learned, as well as five fundamental specific abilities: verbal (20 items), mechanical reasoning (20 items), abstract (20 items), spatial (20 items), and numerical (20 items). Learning strategies, which consists of 85 statements concerning how students approach studying, including learning strategies and motivation for pursuing a university education. The self-report asks participants to rate on a five-point scale how much each statement describes their usual way of thinking and behaving (1 = does not describe me at all; 5 = describes me very well). A total of 10 different learning strategies are evaluated: time man agement (eight items; e.g., "Before I start I think of all the things I have to study and decide how much time to devote to each subject"); anxiety control (eight items; e.g., "Although I have studied and feel I am prepared, I get very nervous in oral tests"); motivation (eight items; e.g., "In this moment the most important thing to me is success in school"); informa tion analysis (eight items; e.g., "I find it difficult to repeat what I study using my own words"); study strategies (eight items; e.g., "When I study I usually do graphs and schemes to fix ideas in my memory"); self-control oflearning (eight items; e.g., "I go through subjects that I studied a long time before"); notes (eight items; e.g., "I make notes of what the teacher says and then I try to organize and make schemes of them as soon as I can "); idea selection (eight items; e.g., "I find it difficult to single out the most important information from what I read"); attitude (eight items; e.g., "I don't study with enthusiasm, even if the subject might interest me"); concentration (eight items; e.g., "While I study I often get up from the desk to phone friends, read the paper, watch TV, etc."); and five filler items. Scale scores were obtained by summing item responses corresponding to each of the 10 factors, after reversing the scores of negatively worded item.
Career decision making. The standardized Magellano Universita (Soresi, 2000) battery has a biographic data sheet. The students were first asked to complete a data form designed to obtain information regarding their age, gender, school attended, and their decision-making status, specifically if they had already made a choice with regard to university (yes or no). The number of students who indicated they were undecided was 5,608, and the number who had decided to attend either a 3-year or 5-year university course was 9,392. In addition, if the participants had already made a decision, they were also asked to indicate whether they decided to attend a 5-year university course or a 3-year university course. The number of stu dents who chose to attend a 3-year course was 1,891, whereas 7,501 chose to attend a 5-year course.
Results As a preface to the results and discussion, we will be presenting some comparisons of PSI data with previously collected samples primarily in the United States, as well as in some other countries. In doing so, we are not contrasting the Italian sample to the U.S. samples or other cross-national samples for the purpose of comparing Italians to any type of "gold standard." Rather, we will make the comparisons to highlight differences and similarities in the data to
promote greater underst context.
Confirmatory Factor.
To examine the constrl three correlated factors fc sample, a confirmatory fi package (Joreskog & SOl indices were used: the chi approaching 1 indicate ad approaches 1, the greater 1 imation (RMSEA; the mOl to be; Bollen, 1989). For the north, the fit inc = 461; GFI = 0.80; AGFI data. For the center, the fit df= 461; GFI = 0.79; AG the data. For the south, tl 22,053.7; df = 461; GFI = good fit with the data. For factors (X 2 = 62,481.0; df there was no good fit with
Exploratory Factor An
Thus, we conducted eX1 well as by the three region distribution was normal (i. & Algina, 1986), scores " oblimin rotations. The nun three factors. Table 1 prese pIe, tJ. coefficients, and the Using an inc1usionary cr criteria of cross-loading les tors. The first scale very cl< ically, nine of the original originally from the AAS S( were all original PSC items the original scale title PSC . make plans to solve a prabl my ability to solve new and have confidence that I can tional AAS items indicated
Nota et al. I Problem-Solving Appraisal in Italy 483
promote greater understanding of problem-solving appraisal within the Italian cultural context.
ns that assess, on one hand, :md reason regardless of the rbilities: verbal (20 items), ) items), and numerical (20
Confirmatory Factor Analyses
ling how students approach !ling a university education. how much each statement not describe me at all; 5 = ies are evaluated: time man :s I have to study and decide Ight items; e.g., "Although I al tests"); motivation (eight uccess in school"); informa ~hat I study using my own lally do graphs and schemes s; e.g., "I go through subjects ake notes ofwhat the teacher )on as I can"); idea selection 1ant information from what I ;m, even if the subject might often get up from the desk to ler items. Scale scores were the 10 factors, after reversing
rersita (Soresi, 2000) battery )mplete a data form designed ed, and their decision-making .ard to university (yes or no). IS 5,608, and the number who : was 9,392. In addition, if the (ed to indicate whether they ty course. The number of stu 7,501 chose to attend a 5-year
ling some comparisons of PSI itates, as well as in some other e to the U.S. samples or other ) any type of"gold standard." and similarities in the data to
/
/
To examine the construct validity of the PSI, and to determine whether the model with three correlated factors found with the U.S. participants would fit this data with an Italian sample, a confirmatory factor analyses was initially conducted using Lisrel 8.30 software package (Joreskog & Sorbom, 1999). To test the adaptation of the model, the following indices were used: the chi-square test; the goodness of fit index ([GFI] in this case, values approaching 1 indicate adequate adjustment); the adjusted GFI ([AGFI] the more the index approaches 1, the greater the adequacy of the model); the root mean square error of approx imation (RMSEA; the more it approaches 0, the more satisfactory it indicates the adjustment to be; Bollen, 1989). For the north, the fit indices for the model with three correlated factors (X 2 = 20,495.6; df = 461; GFI = 0.80; AGFI = 0.77; RMSEA = 0.093) indicated there was no good fit with the data. For the center, the fit indices for the model with three correlated factors (X 2 = 20,821.1; df = 461; GFI = 0.79; AGFI = 0.76; RMSEA = 0.094) indicated there was no good fit with the data. For the south, the fit indices for the model with three correlated factors (X 2 = 22,053.7; df = 461; GFI = 0.78; AGFI = 0.75; RMSEA = 0.097) indicated there was no good fit with the data. For the total sample, the fit indices for the model with three correlated factors (X 2 = 62,481.0; df= 461; GFI = 0.79; AGFI = 0.76; RMSEA = 0.095) indicated there was no good fit with the data.
Exploratory Factor Analyses Thus, we conducted exploratory factor analyses with the total sample (N = 15,000), as well as by the three regions (n = 5,000 for each region). Following confirmation that item distribution was normal (i.e., skewness and kurtosis values between + 1 and -1; Crocker & Algina, 1986), scores were analyzed using principal components analyses followed by oblimin rotations. The number of eigenvalues greater than 1 was 5. A scree test suggested three factors. Table 1 presents the factor loadings of the three factor model for the total sam ple, l1 coefficients, and the amount of variance accounted for by each factor. Using an inclusionary criterion of items with factor loadings over.40 and the exclusionary criteria of cross-loading less than .30, 26 of the original 32 items loaded on the original fac tors. The first scale very closely resembled the PSC scale and consisted of 12 items. Specif ically, nine of the original items loaded on the PSC scale along with three other items originally from the AAS scale. The eight highest factor loadings (.68 to .48) on this scale were all original PSC items indicating the scale remained conceptually a PSC scale, and thus the original scale title PSC was retained. The highest loading items continued to be: When I make plans to solve a problem, I am almost certain that I can make them work (.68); I trust my ability to solve new and difficult problems (.65); and When faced with a novel situation, I have confidence that I can handle problems that may arise (.65). However, the three addi tional AAS items indicated that in the perceptual processes of this sample, these approach
484
Journal of Career Assessment
Table 1
Items, Component Loading, and Commonalty Estimates Contributing to the
Three-Factor Problem-Solving Inventory for the Italian Sample Factor Loadings 27 Items (ex
= .87)
Factor 1: Problem-solving confidence (12 items; ex = .85) 19. When I make plans to solve a problem, I am almost certain that I can make them work 24. When faced with a novel situation, I have confidence that I can handle problems that may arise 27. I trust my ability to solve new and difficult problems 23. Given enough time and effort, I believe I can solve most problems that confront me 33. After making a decision, the outcome I expected usually matches the actual outcome 10. I have the ability to solve most problems even though initially no solution is immediately apparent 5. I am usually able to think up creative and effective alternatives to solve a problem 12. I make decisions and am happy with them later 20. I try to predict the overall results of carrying out a particular course of action 28. I have a systematic method for comparing alternatives and making decisions
35. When I become aware ofa problem, one of the first things I do is to try to find out exactly what the
problem is 6. After I have tried to solve a problem with a certain course of action, I take time and compare the actual outcomes to what I thought should have happened Factor 2: Approach-avoidance style (nine items; ex = .81) 17. I generally go with the first idea that comes to mind 13. When confronted with a problem, I tend to do the first thing that I can think of to solve it 14. Sometimes I do not stop and take time to deal with my problems, but just kind of muddle ahead 15. When deciding on an idea or possible solution to a problem, I do not take time to consider the chances of each alternative being successful 16. When confronted with a problem, I stop and think about it before deciding on a next step 30. When confronted with a problem, I do not usually examine what sort of external things in my environment may be contributing to my problem 2. When I confronted with a complex problem, I do not bother to develop a strategy to collect information so that I can define exactly what the problem is
F2
F3
M
SD
112
.68
-.09
-.15
2.65
1.12
.52
.65
-.12
-.28
2.73
1.18
.56
.65 .65
-.07 -.04
-.30 -.09
2.49 2.14
1.20 1.07
.61
.65
.02
-.02
2.67
1.01
043
.63
-.04
-.20
2.30
1.17
049
.58
.01
-.11
2.31
1.11
.39
.58 .55
-.03 .01
-.07 .07
2.36 2.66
1.04 1.21
.35 .28
048
-.00
.04
3.32
1.33
.22
048
.27
.22
1.68
.93
.35
047
.24
.28
2.34
1.18
.34
-.14 -.20
.82 .81
-.06 -.09
2.82 3.11
1.49 1.52
.64 .62
-.14
.79
-.13
2.98
1.53
.62
-.01
.63
-.04
2.96
1.46
040
.27
.57
.25
1.98
1.06
048
-.02
.53
-.07
2.78
1.36
.28
.10
.49
-.04
2.26
1.41
.29
Fl
044
(continued)
27 Items (ex
= .87)
4. After I have solved a f went right and what WI 1. When a solution to a p not examine why it die
Factor 3: Emotional control ( 32. Sometimes I get so ch! unable to consider mar problem 25. Even though I work on like I am groping or Wl down to the real issues 34. When confronted with whether I can handle t1J 11. Many of the problems I to solve 3. When my first efforts to uneasy about my ability Note: N = 15,000.11 2 = com style; F3 = emotional control.
items were related to COl action; I use a systematic Nine items loaded on ~ 16 items that loaded on t1 on the PC scale. The two scale: I generally act on when confronted with a (.81). In essence, the scal a problem and was again The third scale consisl original items loaded on 1 on the PSC scale. The twl scale: There are times wh natives for solving a partie feel like I'm groping or w. items loading on this seal larity to the other items in' When confronted with a . many of the problems J fal ceptualized as one 's abili~ and not become overwheb
Nota et al. I Problem-Solving Appraisal in Italy
485
Factor Loadings
:ontributing to the tHan Sample
27 Items (ex.
= .87)
4. After I have solved a problem, I do not analyze what went right and what went wrong 1. When a solution to a problem was unsuccessful, I do not examine why it didn't work
~s
F3
M
SD
Tt 2
-.15
2.65
1.12
.52
-.28
2.73
1.18
.56
-.30 -.09
2.49 2.14
1.20 1.07
.61
.44
-.02
2.67
1.01
.43
-.20
2.30
1.17
.49
-.11
2.31
1.11
.39
-.07 .07
2.36 2.66
1.04 1.21
.35 .28
.04
3.32
1.33
.22
.22
1.68
.93
.35
.28
2.34
1.18
.34
-.06 -.09
2.82 3.11
1.49 1.52
.64 .62
-.13
2.98
1.53
.62
-.04
2.96
1.46
.40
.25
1.98
1.06
.48
-.07
2.78
1.36
.28
-.04
2.26
1.41
.29
(continued)
Factor 3: Emotional control (five items; ex. = .76) 32. Sometimes I get so charged up emotionally that I am unable to consider many ways of dealing with my problem 25. Even though I work on a problem, sometimes I feel like I am groping or wandering, and am not getting
down to the real issues 34. When confronted with a problem, I am unsure of whether I can handle the situation 11. Many of the problems I face are too complex for me to solve 3. When my first efforts to solve a problem fail, I become uneasy about my ability to handle the situation Note: N = 15,000. 112 = communality estimates; F I style; F3 = emotional control.
0
Fl
F2
F3
M
.09
.48
-.00
2.76
1.52
.26
.04
.44
-.03
2.13
1.51
.21
.02
.05
-.72
3.95
1.50
.54
.11
.15
-.67
3.53
1.43
.56
.13
.10
-.63
3.42
1.42
.49
.14
.15
-.58
2.76
1.34
.45
.18
.16
-.54
3.17
1.56
.43
SD
Tt
= problem-solving confidence; F2 = approach-avoidance
items were related to confidence (e.g., I try to predict the results of a particular course of action; I use a systematic method to compare alternatives and make decision) . Nine items loaded on the second scale; specifically, this scale consisted of8 ofthe original 16 items that loaded on the AAS scale, along with one additional item that originally loaded on the PC scale. The two highest loading items continued to be ones from the original AAS scale: I generally act on the first idea that comes to mind in solving a problem (.82); and when confronted with a problem, I tend to do the first think I can think of to solve it (.81). In essence, the scale remained conceptually one reflecting approach or avoidance of a problem and was again labeled AAS. The third scale consisted of five items; specifically, this scale consisted of three of the original items loaded on the PC scale, and two other items that were both originally loaded on the PSC scale. The two items with the highest factor loadings were from the original PC scale: There are times when I become so emotionally charged that I can no longer see alter natives for solving a particular problem (.72); Even though I work on a problem, sometimes I feel like I'm groping or wandering and not getting down to the real issue (.67). The two new items loading on this scale were originally from the PSC scale; both have conceptual simi larity to the other items in this scale suggesting a lack of emotional control. These items were: When confronted with a problem, I am unsure of whether I can handle the situation; and many of the problems I face are too complex for me to solve. This scale was originally con ceptualized as one's ability to have enough PC to proceed with the problem-solving process and not become overwhelmed by the emotion of the situation. The addition of the two PSC
486
Journal of Career Assessment
items, in conjunction with the three PC items, all seemed to suggest in this Italian sample that the scale best reflected emotional control and feelings of being unable to handle situations that they perceive as too complex. Because of the greater theme on emotional control, this scale was labeled emotional control.
PSI Means and Problem-Solvin~
M
Comparing the PSI Factor Structure across Regions The factor structures were compared across the different combinations of the three regions by using congruence coefficients (Tucker, 1951). The congruence coefficient is similar to a correlation coefficient in that it compares the two sets of factor loadings and is most appro priate to use when determining differences between factors. Values higher than .95 are indi cative of factorial similarity, whereas values lower than .90 are assumed to point to differences in the factor structure (Van de Vijver & Leung, 1997). Results indicate that for all of the comparisons the congruence coefficients were .99. Thus, it appears there was very strong factorial similarity across the regions of Italy on the three factors of the PSI.
North (N = 5,000)
Male 29.1
Female 31.0
Center (N = 5,000)
Male 29.0
Female 30.7
South (N = 5,000)
28.5
Male Female 26.7
Total sample (N = 15,000) Male 28.8 Female 30.4
Reliability Estimates
Note: PSI = problem-solving
The reliability estimates of the current study on the Italian version of the PSI indicate the instrument to have satisfactory internal reliability. An estimate of internal consistency revealed Cl coefficients of .87 for the entire inventory, and .85, .81, and .76 for the three fac tors (PSC, AAS, and PC respectively). No differences were found across geographic regions on these estimates (all ps
