Sarah R. Baker* Department of Psychology, Keele University, Staffordshire, ST5 5BG, UK

Transcription

1 Personality and Individual Differences 35 (2003) A prospective longitudinal investigation of social problemsolving appraisals on adjustment to university, stress, health, and academic motivation and performance Sarah R. Baker* Department of Psychology, Keele University, Staffordshire, ST5 5BG, UK Received 2 November 2001; received in revised form 26 April 2002; accepted 23 July 2002 Abstract A prospective longitudinal design was used to examine the predictive relations between social problem-solving appraisals and subsequent adjustment, stress, health, motivation and performance in a sample of university students during their three years at university. Controlling for gender, age and prior academic aptitude, self-perceived problem-solving abilities, measured on entry to university, had direct beneficial effects on psychosocial adjustment to university, perceived stress levels, selfdetermined motivational orientations, and academic performance during students second year of study. Additionally, social problem-solving appraisals, adjustment to university and intrinsic motivation towards accomplishment predicted higher marks over the course of students 3 years at university, controlling for university entry qualifications. Gender differences emerged in perceived stress, selfdetermination profiles, and academic performance, with women displaying higher scores than men. More specific analysis of problem-solving appraisals indicated that different dimensions (e.g. control, confidence) had different long-range adaptational outcomes. Results are discussed with reference to models of social problem-solving (D Zurilla, 1986, 1990) and self-determination (Deci & Ryan, 1985, 1991) and implications for interventions based on problem-solving training for stress management are considered. # 2003 Elsevier Ltd. All rights reserved. Keywords: Social problem-solving appraisals; Adjustment; Motivation; Performance; Stress; Students * Tel.: ; fax: address: s.r.baker@keele.ac.uk (S.R. Baker) /03/$ - see front matter # 2003 Elsevier Ltd. All rights reserved. PII: S (02)

2 570 S.R. Baker / Personality and Individual Differences 35 (2003) Introduction Self-appraised social problem solving ability is concerned with the way in which individuals perceive and cope with problems encountered in everyday life. This conceptualisation of problem solving appraisal is derived from the original problem solving model of D Zurilla and Goldfried (1971) which defined the problem solving process as a set of five interacting components: (1) problem orientation, (2) problem definition and formulation, (3) generation of alternatives, (4) decision making, and (5) verification. The first component problem orientation refers to the motivational part of the problem solving process which includes generalised beliefs, appraisals, and expectations about problems and an individual s own problem solving abilities. The remaining four components include the actual problem solving skills required to define and resolve problems effectively. One of the main assumptions of this and more contemporary formulations of the social problem-solving process (D Zurilla, 1986, 1990) is that problem solving is a general coping strategy, which facilitates and maintains general competence and adaptation. There has been much convergent evidence in support of this hypothesis. Social problem-solving appraisals have been linked to indices of psychological distress including depression and anxiety (Elliott, Herrick, MacNair, & Harkins 1994; Elliott, Sherwin, Harkins, & Marmarosh, 1995; Heppner, Hibel, Neal, Weinstein, & Rabinowitz, 1982; Nezu, 1985, 1986), stress (Baker & Williams, 2001; Nezu & Perri, 1989; Nezu & Ronan, 1985, 1988), and adjustment (Heppner & Anderson, 1985), as well as behavioural health outcomes such as, health complaints and symptoms (Elliott, 1992; Elliott & Marmarosh, 1994). In addition, effective and ineffective self-appraised problem solvers have been found to differ in relation to expectancies for control (Nezu, 1985), self-concept (Heppner, Reeder, & Larson, 1983), and irrational beliefs (Heppner et al., 1983), whilst effective selfappraised problem solving has been associated with rational decision-making styles (Chartrand, Rose, Elliott, Marmarosh, & Caldwell, 1993) and the use of problem-focussed coping strategies (MacNair & Elliott, 1992). Further investigations of the social problem-solving process indicate that different components (problem orientation & problem-solving skills) may contribute to different adaptational outcomes. Self-appraised problem solving confidence and personal control, which are presumed to reflect the motivational or problem orientation component of the problem solving model (c.f. Elliott et al., 1995; Nezu, & Perri, 1989) have been linked to indices of subjective distress (Elliott, Shewchuk, Richeson, Pickelman, & Franklin, 1996), and state and trait affectivity (Chartrand et al., 1993; Elliott et al., 1994, 1995). In contrast, approach-avoidance appraisals, representing specific cognitive-behavioural strategies as reflected in the problem solving skills component of the social problem solving model, have been linked to rational decision-making strategies (Chartrand et al., 1993), assertion skills (Elliott, Godshall, Herrick, Witty, & Spruell, 1991), and problem solving coping techniques (MacNair & Elliott, 1992), but have been found to be unrelated to self-report indices of distress or affect (Elliott et al., 1994, 1995a, 1995b, 1996). Although many studies in the social problem-solving field have used undergraduate students as convenient participants, there has been little research that has examined specifically the role of social problem-solving appraisals in relation to adaptational and academic outcomes in educational settings. Yet, transition to university is a time when individuals are faced with many new interpersonal, social, and academic demands. There is extensive evidence that such a time is

3 S.R. Baker / Personality and Individual Differences 35 (2003) stressful for many individuals, and that adjustment during this period is linked to the way individuals cope with that stress which impacts on physical and psychological health (Aspinwall & Taylor, 1992; van Rooijen, 1986), and academic motivation and performance (Sharma, 1973; Zitzow, 1984). Within both the educational and psychology literatures, many factors thought to influence adjustment to university and health-related and academic outcomes have been investigated including demographics (Halamandaris & Power, 1999; van Rooijen, 1986), university entry qualifications and intellectual ability (Aspinwall & Taylor, 1992; Sternberg & Kaufman, 1998), personality variables such as the Big Five factors neuroticism and extraversion (DeRaad, 1996; Halamandaris & Power, 1997, 1999), motivational orientations (Vallerand & Bissonnette, 1992; Vallerand, Blais, Briere, & Pelletier, 1989; Vallerand, Pelletier, Blais, Briere, Senecal, & Vallieres, 1992), and learning approaches (Minnaert & Janssen, 1992). The few studies that have included a measure of social problem solving have found effective self-appraised problem-solving to be associated with more adaptive study habits and attitudes (Elliott, Godshall, Shrout, & Witty, 1990), and prospectively with lower psychological distress (Chang & D Zurilla, 1996), lower levels of stress associated with starting university (D Zurilla & Sheedy, 1991), and better academic performance (GPA) in the first year of college after accounting for prior academic aptitude (D Zurilla & Nezu, 1990; D Zurilla & Sheedy, 1992; Rodriguez-Fornells & Maydeu- Olivares, 2000). Although existing research suggests that self-appraised social problem-solving ability may be an important tool in accounting for individual differences in adaptational outcomes in tertiary educational settings, in the majority of these studies, the variance accounted for by problem-solving was rather modest. It may be, as suggested by D Zurilla and Sheedy (1991), that the time-frame over which these studies were conducted was too short (i.e. 6 weeks to 3 months) to allow students sufficient time to cope successfully with initial adjustment problems over the course of their first year and the transition into their second year of college. Particularly as previous research suggests that social problem solving facilitates effective problem resolution and adjustment over time (D Zurilla, 1986, 1990). Thus, more effective problem solvers ought to be able to effectively solve their adjustment problems and patterns between study variables are more likely to emerge in the longer-term. The only way in which to disentangle potential relationships between social problem solving and key outcome variables is to collect data from a sample of students over the entire course of their time at university. Another limitation of previous studies is that they have examined the impact of social problem solving on key outcome variables, such as adjustment and academic performance, in relative isolation, rather than investigating the complexities of such variables simultaneously. Furthermore, there has been no research examining the influence of social problem solving on academic motivation; yet, it is known that motivational orientations play a significant role in educational outcomes (Deci & Ryan, 1985, 1991 for reviews). In general, this research suggests that intrinsic motivation, that is doing an activity voluntarily for its own sake and the pleasure and satisfaction derived from participation, has a positive influence on academic performance. In contrast, extrinsic motivation, that is engaging in activities for external rewards and as a means to an end, has been associated with lower academic attainment. Similarly, other research has found amotivation, whereby individuals are neither intrinsically or extrinsically motivated but rather they perceive no contingencies between their behaviour and outcomes, to be negatively related to educational outcomes such as, perceptions of competence and dropout rates (Vallerand & Bissonnette,

4 572 S.R. Baker / Personality and Individual Differences 35 (2003) ; Vallerand et al., 1989). In the light of these relationships, it is perhaps surprising that there has been little research examining the role of different motivational orientations in longer-term academic performance in university settings, nor the potential impact of individual difference factors on such motivational orientations. Given the influence of social problem-solving appraisals on initial university adjustment and performance (e.g. D Zurilla & Sheedy, 1992), there is a need to assess the potential impact of such appraisals on different motivational orientations and their longer-term consequences. The present study was designed to overcome some of the problems discussed above by utilising a longitudinal prospective design that allowed an examination of the temporal relations between social problem-solving appraisals and future adjustment, motivational orientations, stress, health, and performance whilst controlling for the influence of demographics (age, gender), initial academic aptitude, and prior health. The first goal of the study was to examine the degree to which measures of social problem-solving appraisals, obtained on entry to university, predicted adjustment, motivational orientations, stress and health in individuals second year of study, and overall academic performance whilst at university. A second goal was to assess whether levels of adjustment, stress, health and motivational orientations predicted overall academic performance. An additional aim was to explore these key outcome variables in relation to different dimensions of problem solving reflecting the problem orientation and problem-solving skill components of the social problem-solving model. Thus, the study incorporated three stages. Stage 1 involved the assessment of social problem-solving appraisals, and baseline measures of physical and psychological health within two weeks of students arrival at university. Stage 2 assessed motivational orientations, adjustment to university, academic performance, stress and health during students second year of study. Stage 3 involved the assessment of overall academic performance during students three years at university obtained after they had finished their studies. 2. Methods 2.1. Participants Participants at Stage 1 were 104 first year joint-honours Psychology undergraduates (81 women, 23 men) enrolled at a medium-sized campus-based university during the period Ages ranged from 18 to 36 years (M=19.39, SD=2.90). For the second and third stages of the study, 91 of the original respondents took part (71 women, 20 men), with a mean age of (SD=3.08) Response rates Time 1. Of the 156 questionnaires distributed at Time 1, 132 (84.6%) were returned. Of these, 28 (21 women, seven men) subsequently left the course during their first two years at University. For these students, no Time 2 or Time 3 data were available and they were dropped from the study. Therefore, the final sample at Time 1 consisted of 104 students (81 women, 23 men). A comparison of entry qualifications, age, social problem solving, and health scores for those respondents who dropped out compared to those who finished their studies and completed Time 2 measures, yielded no significant differences on any measure.

5 Time 2. Of the 104 original participants who received Time 2 questionnaires, 13 (10 women, three men) did not complete the second questionnaire (response rate=87.5%). Comparisons on age, Time 1 measures, entry qualifications, and academic performance revealed no significant differences between those participants who did not complete the second assessment compared to those that did. Time 3. Of the 91 respondents who completed questionnaires at Time 1 and 2, overall academic performance data (1st, 2nd and 3rd year marks) were available for all participants Procedure Questionnaires were distributed to all first-year psychology students during the first 2 weeks following arrival at the university. Participants were given the questionnaire during scheduled classes after having been informed about the nature and aims of the study, and assuring them that all responses were confidential. Participants completed the questionnaire during the class, and when completed returned them to a collection box. Respondents were asked to provide their student identification numbers in order to allow matching of questionnaires with Time 2 measures and academic performance data. All participants received course participation credits for taking part in the first stage of the study. During the second semester of students second year of study (17 months from Time 1), a second questionnaire was distributed to all students who responded to the first questionnaire. Questionnaires were distributed and completed in scheduled classes. As at Time 1, respondents were asked to provide their student identification numbers, and again assured that all responses were confidential. Participants received no incentives (course credits or payments) for taking part in the second stage of the study. Following the second semester of students third year of study (14 months from Time 2), participants entry qualifications and academic performance data were obtained from the departmental database Time 1 measures S.R. Baker / Personality and Individual Differences 35 (2003) Social problem-solving appraisals. Self-appraised social problem solving was measured using the Cassidy-Long Problem-Solving Questionnaire (Cassidy & Long, 1996). This questionnaire was originally developed in order to assess more fully the multidimensional nature of problem-solving appraisals as identified in the social problem-solving model (D Zurilla, 1986, 1990) by incorporating dimensions both from the commonly used Problem Solving Inventory (PSI; Heppner, 1988), as well as additional dimensions identified in the problem-solving literature (e.g. Nezu, 1987). Original factor analysis of the questionnaire (Cassidy & Long, 1996) indicated six factors; three replicating those from the PSI (problem-solving confidence, control, approach-avoidance style), although the analysis revealed that the latter was two separate factors, avoidance style and approach style, and two further factors, problem-solving helplessness and creative style. In line with previous research (Elliott et al., 1995; Nezu & Perri, 1989), it is reasoned that the problemsolving confidence (a self-assurance and trust in one s ability to solve problems) and personal control dimensions (a sense of control over emotions and behaviours in problem solving situations) reflect aspects of the problem orientation component of the social problem solving model (D Zurilla, 1986, 1990), whilst approach (a general tendency to approach problem situations and

6 574 S.R. Baker / Personality and Individual Differences 35 (2003) confront them head on) and avoidance style (a general tendency to avoid problem situations and put off dealing with them) represent facets of the problem-solving skills component. In addition, it is tentatively reasoned, as outlined by Cassidy and Long (1996), that problem-solving creativity, which measures planning and consideration of alternative solutions, represents aspects of the problem-solving skills component, whilst problem-solving helplessness reflects a general problem orientation. Each item has a true/?/false response format and is scored on a 0 2 scale with a higher score indicating more effective problem-solving on each of the dimensions, with the exception of the helplessness and avoidance factors which are reverse scored (i.e. the higher the score, the lower the amount of perceived helplessness and avoidance). The problem-solving questionnaire is scored for each of the six sub-scales and the total questionnaire. The internal reliability of the problem-solving measure, as measured in the present sample, was high =0.80. Psychological and physical health. The 12-item General Health Questionnaire (GHQ-12; Goldberg, 1972) was used to assess psychological health. Respondents rate how much they agree with each statement, with a higher score indicating greater self-reported psychological distress. Cronbach s alpha for the GHQ-12 in this study was Participants perceptions of their current physical health or healthiness were measured with a 16-item rating scale using items from Cassidy s Healthiness Rating Scale and Frequency of Ill Health Scale (Cassidy, 2000). The scale consisted of items such as Do you regularly take non-prescription painkillers? and Do you suffer from colds?. Respondents rated each item from 1 (never) to 5 (a lot), with a higher score indicating worse self-reported physical health. The internal reliability of the physical health measure in the present study (=0.56) was not as high as one might hope, although it is above the 0.50 that Nunnally (1967) ascertains is sufficient for research purposes Time 2 measures Adjustment to university. To assess adjustment to university, two outcome measures were used in order to increase the reliability of the information provided. The first measure, the College Adaptation Questionnaire (CAQ; Crombag, 1968; Vlaander & van Rooijen, 1981) consists of 18 statements scored on a 7-point scale, which measure individuals psychological, social and interpersonal adaptation to university life. Ten of the items reflect poor adjustment (e.g. I find it hard to get used to life here ) and 18 items reflect good adjustment (e.g. I am glad that I came to study here ). The score for the CAQ is the sum of the item scores after reflection of the 10 items indicating poor adjustment. Previous studies have reported the CAQ to be highly reliable, =0.83 (van Rooijen, 1986). The second measure, self-reported adjustment (SRA), was assessed using items from a previous study on college students adjustment and performance (Aspinwall & Taylor, 1992). Three items asked students to rate their academic, social and overall adjustment (e.g. Overall, how well do you think you ve adjusted to University? ) on a 7-point scale (1=not at all well, 7=extremely well). Next, students were asked to rate their overall adjustment to the university compared to an average second-year undergraduate on a 7-point scale (1=much less adjusted, 7=much more adjusted), and their overall satisfaction with the university. Self-reported adjustment is the sum of the five item scores, with higher scores indicating more successful adjustment to university. Cronbach s alpha indicated the scale to be highly reliable, =0.83. Academic motivation. To assess students motivation to succeed at university, two outcome measures were used. The first, the academic motivation scale (AMS; Vallerand et al., 1992) is a

7 28-item measure of motivation based on the theoretical model of motivation postulated by Deci and Ryan (1985). The scale has seven sub-scales assessing three types of intrinsic motivation (intrinsic motivation to know, to accomplish things, and to experience stimulation), three types of extrinsic motivation (external, introjected, and identified regulation), and amotivation. Respondents are asked to rate each item on a 7-point scale (1=does not correspond at all, 7=corresponds exactly) to the extent to which it corresponds to the reasons why they are at university. The AMQ is scored for each of the seven sub-scales with higher scores indicating greater intrinsic, extrinsic and amotivation. Previous studies using the AMQ reveal high internal (=0.81) and test-retest reliability (r=0.79) (Vallerand et al., 1989, 1992). The second measure, self-reported motivation (SRM), included one item from Mallinckrodt (1988) to assess drop-out intention, I am certain I will obtain my degree from the university scored on 7-point scale (1=strongly disagree, 7=strongly agree), and three items from Aspinwall and Taylor (1992) to assess expectation of success (e.g. I expect to do well at university ) and educational aspiration. For the latter, respondents indicated the lowest level of degree classification that they would be satisfied with ranging from a third-class degree to a first-class degree. Self-reported motivation is the sum of the four item scores, with higher scores indicating higher academic motivation. This four item measure of motivation showed satisfactory reliability, =0.67. Academic performance. Two measures of academic performance were obtained from the departmental database. The first, entry qualifications (EQ) represented respondents A-level point average gained prior to their entry to university and was obtained to control for respondents previous academic performance. The second measure represented respondents grade point average (GPA) for the four modules taken in their first year at university. Psychological and physical health. Health was assessed as at Time 1. Stress. Perceived stress was assessed using two measures; the Perceived Stress Scale (PSS; Cohen, Kamarck, & Mermelstein, 1983) and a modified version of the Daily Hassles Index (DHI; Schafer, 1998) The PSS-4 consists of four items rated on a 4-point scale (0=never, 4=very often), with a higher score indicating greater perceived stress. Previous studies indicate the scale has good reliability, =0.73 (Aspinwall & Taylor, 1992). The second stress measure included 20 items from the Daily Hassles Index, which is designed to assess academic, social, financial and interpersonal stress in university students. Respondents indicated on a 5-point scale (1=never, 4=very often) how often each event was a source of stress (e.g. managing own finances and taking exams/tests ). The measure, scored so that higher scores indicated greater self-perceived stress, was highly reliable as measured in the present study, = Time 3 measures S.R. Baker / Personality and Individual Differences 35 (2003) Two measures of academic performance were obtained from the departmental database. Entry qualifications (EQ) were assessed as at Time 2 in order to control for respondents initial level of academic achievement. Second, overall academic performance (OAP) was assessed as respondents average mark for the 12 modules taken in Years 1 3.

8 576 S.R. Baker / Personality and Individual Differences 35 (2003) Overview of analysis In order to assess the relationships between social problem-solving appraisals, psychosocial adjustment, academic motivation, health, stress and academic performance, a series of multiple regression analyses were performed in two stages, summarised in the path diagram shown as Fig. 1. Those variables with an arrow pointing to it acted as dependent variables in a separate regression analysis, whilst variables from which the arrow originates were used as an independent variable (cf. Wong & Csikszentmihalyi, 1991). It should be noted, as can be seen in Fig. 1, that measures of adjustment, stress, health, motivation, and performance whilst studying acted as dependent variables in the first stages of the analyses, but as independent variables in the second stages when predicting performance. Stage 1 of the analyses assessed the role of problem-solving appraisals (measured at Time 1) in predicting adjustment, academic motivation, stress, health, and academic performance (measured at Time 2). In all analyses, age and gender were entered as the first step to control for demographics. Indeed, preliminary analyses revealed that there were gender differences on a number of Time 1 and 2 measures. In Step 2, entry qualification score was entered in order to control for Fig. 1. Path diagram indicating hypothesised relationships between social problem-solving appraisals, adjustment, motivation, stress and health while studying, and academic performance.

9 S.R. Baker / Personality and Individual Differences 35 (2003) academic performance prior to arrival at the university. Self-appraised problem solving was then entered as the third step. For those analyses involving health as the dependent variable, the baseline (Time 1) score on the relevant questionnaire was entered as a separate step prior to the social problem-solving measure, in order to control for prior health status. In Stage 2 of the analyses, to assess predictors of overall academic performance (measured at Time 3), two sets of hierarchical regressions were performed. First, to assess whether social problem-solving appraisals significantly predicted overall performance. Second, to assess whether measures of adjustment, academic motivation, stress, health, and academic performance at Time 2 predicted overall academic performance. In both sets of analyses, age, gender and entry qualifications were entered in the first and second steps in order to control for demographics and prior academic achievement. In all Stage 1 and 2 analyses, where total problem-solving appraisal scores were significant predictors, further exploratory regression analyses were conducted entering each of the six problem-solving subscales (e.g. control, confidence) in a stepwise incremental fashion. 3. Results 3.1. Descriptive statistics and correlations The means, standard deviations and ranges for all study variables are presented in Table 1, and intercorrelations between social problem solving appraisal dimensions in Table 2. As can be seen in Table 2, in general, the problem-solving appraisal dimensions were significantly related to one another, with the exception of avoidance style. Table 3 presents the inter-correlations between all study variables. As can be seen, problem-solving appraisals correlated positively with adjustment to university (CAQ and SRA) and intrinsic motivation (to know and experience stimulation), and negatively with the amotivation subscale of the AMQ, both measures of perceived stress (PSS-4, DHI), and the GHQ-12. With regard to academic performance, problem-solving appraisals were not significantly related to either GPA or OAP. Of the Time 2 measures, only GPA was significantly related to overall academic performance. Entry qualification scores, a measure of students aptitude prior to university, were positively related to the external regulation subscale of the AMQ and negatively correlated with the intrinsic motivation (to accomplish) subscale. In addition, scores were positively related to both academic performance measures taken during students university careers (GPA, OAP). Interrelationships between the two adjustment (SRA and CAQ), health (GHQ and Physical health) and stress (PSS and DHI) outcome measures were significant, whilst between the two motivation measures only the relationship between self-reported motivation and two of the AMQ subscales (IMTA and EMIN) was significant Self-appraised social problem solving as a predictor of adjustment to university, academic motivation, stress, health, and academic performance while studying To assess whether social problem-solving appraisals measured at the start of students academic career predicted adjustment to university, academic motivation, stress, health, and academic performance in their second year of study, a series of hierarchical multiple regression analyses

10 578 S.R. Baker / Personality and Individual Differences 35 (2003) Table 1 Means, standard deviations, and ranges of all study variables at Time 1, 2 and 3 Variable Mean SD Range N Time 1 Total SPSA Helplessness Control Avoidance Approach Creativity Confidence GHQ Physical health Time 2 Adjustment CAQ SRA Academic motivation AMQ IMTK IMTA IMES EMID EMIN EMER AMOT SRM Health GHQ Physical health Stress PSS DHI Academic performance GPA Time 3 OAP EQ AMQ=Academic Motivation Questionnaire; IMTK, IMTA, IMES=intrinsic motivation-to know, to accomplish, to experience stimulation; EMID, EMIN, EMER=extrinsic motivation-identified regulation, introjected regulation, external regulation; AMOT=amotivation; GPA=Grade Point Average; EQ=entry qualifications; PSS=Perceived Stress Scale; CAQ=College Adjustment Questionnaire; DHI=Daily Hassles Index; SRM=self-reported motivation; SRA=self-reported adjustment; GHQ=general health questionnaire; SPSA=social problem-solving appraisals.

11 S.R. Baker / Personality and Individual Differences 35 (2003) Table 2 Intercorrelations between the social problem-solving appraisal dimensions Variable Helplessness 0.50** ** ** 2. Control ** ** 3. Creativity 0.44** 0.23* 0.41** 4. Confidence ** 5. Avoidance Approach Higher scores indicate more effective problem-solving on each of the dimensions, with the exception of the helplessness and avoidance factors whereby the higher the score, the lower the amount of perceived helplessness and avoidance. * P<0.05. ** P<0.01. were carried out. The results of these analyses are presented in Table 4, which shows R 2, R 2 change, and F values for the final models. Problem-solving had significant effects on a number of Time 2 measures, after controlling for age, gender and entry qualifications; adjustment to university, academic motivation, perceived stress, and academic performance. Total problem-solving scores accounted for an additional 14 and 11% of variance in self-reported adjustment (Fchange (1, 86)=14.49, P<0.001) and CAQ scores (Fchange (1, 86)=11.02, P<0.001), 7 and 12% in extrinsic motivation (identified regulation) (Fchange (1, 86)=7.49, P< 0.01) and amotivation (Fchange (1, 86)=9.97, P <0.01) respectively, 5 and 7% in PSS (Fchange (1, 86)=4.83, P<0.05) and DHI (Fchange (1, 86)=8.75, P<0.01) respectively, and 7% in academic performance scores (GPA) (Fchange (1, 86)=7.18, P<0.01). Examination of the direction of the beta values indicates that individuals with higher problem-solving appraisals report better psychosocial adjustment to university life, are more self-determined (as measured by the extrinsic motivation-identification scale), are less amotivated, and have lower levels of stress while studying, and have higher average marks in their first year of study when compared to those with lower self-appraised problemsolving. It is important to note significant predictors other than problem solving in these regression analyses. Gender was a significant predictor in the final models for self-reported stress (DHI), extrinsic motivation (identified regulation) and GPA, with the positive beta values indicating that women reported high levels of stress and self-determination, and had higher average first year marks compared to men. In terms of academic performance, in addition to gender, both age and entry qualifications had significant effects. Together, demographics and entry qualifications accounted for 16% of the variance in student s GPA, with older students, women, and those with higher entry qualifications prior to university having higher average marks after their first year of study. In relation to the health measures, the only significant predictor of physical health whilst studying was prior physical health scores measured at Time 1, accounting for an additional 19% of the variance after controlling for demographics and EQ. Prior psychological health, as measured by the GHQ, was not a significant predictor of psychological well-being while studying.

12 Table 3 Intercorrelations between the study variables a Variable SPS 0.35** 0.39*** 0.29** * ** * 0.35** 0.23* CAQ 0.74*** 0.34** 0.22* *** *** 0.46*** * SRA 0.48*** 0.42*** 0.32** 0.25* *** *** 0.44*** ** AMQ- IMTK 0.60*** 0.76*** 0.22* *** ** AMQ- IMTA 0.61*** 0.28** 0.41*** * 0.24* * 6. AMQ- IMES * * AMQ- EMID 0.32** 0.45*** 0.21* AMQ- EMIN 0.38*** * AMQ * * EMER 10. AMQ- AMOT ** 0.30** 0.28** SRM PSS 0.30** 0.23* 0.21* DHI ** GHQ 0.21* Physical health GPA 0.89*** 0.23* 17. OAP 0.30** 18. EQ a See Table 1 for abbreviations. * P<0.05. ** P<0.01. *** P< S.R. Baker / Personality and Individual Differences 35 (2003)

13 S.R. Baker / Personality and Individual Differences 35 (2003) Table 4 Hierarchical regression analyses predicting adjustment to university life, academic motivation, health, stress, GPA, and overall academic performance from social problem-solving appraisals a Dependent variables R 2 R 2 change F Beta values SPS Age Gender EQ Prior health Adjustment CAQ * 0.34*** SRA ** 0.38*** Motivation AMQ b - EMID ** 0.28** *** - AMOT * 0.33** SRM Stress PSS * 0.23* DHI ** 0.30** * 0.16 Health GHQ Physical health *** *** Performance GPA *** 0.26** 0.25* 0.32** 0.39*** OAP *** 0.22* *** 0.46*** a See Table 1 for abbreviations. b Significant subscales only. * P<0.05. ** P<0.01. *** P< Self-appraised social problem solving as a predictor of overall academic performance To examine whether social problem-solving appraisals measured on arrival at university predicted overall academic performance achieved at the end of students academic careers, a hierarchical regression analysis was conducted. As can be seen in Table 4, after controlling for demographics and entry qualifications, the relation between self-appraised problem-solving and academic performance was significant. Problem solving appraisals accounted for an additional 5% of the variance in students average marks over their three years of study. In addition, both gender and entry qualifications had a significant effect on academic performance, accounting for an additional 9 and 14% of the variance respectively. Examination of the beta values indicates that individuals with higher self-appraised problem-solving, women, and students with higher entry qualifications had higher overall marks.

14 582 S.R. Baker / Personality and Individual Differences 35 (2003) Adjustment, academic motivation, stress and health as predictors of overall academic performance To examine whether the variables measured during students second year of study (Time 2) predicted overall academic performance at the end of their university careers, a series of hierarchical multiple regressions were conducted. After controlling for demographics and entry qualifications, only intrinsic motivation (to accomplish), self-reported adjustment, and academic performance during their first year of study (GPA) had a significant effect on students overall marks; intrinsic motivation (to accomplish) (R 2 change=0.05, (Fchange (1, 74)=4.62, P<0.05), GPA (R 2 change=0.58, (Fchange (1, 74)=263.40, P<0.001), self-reported adjustment (R 2 change=0.06, (Fchange (1, 74)=5.68, P<0.05). Examination of the beta values indicate that students with higher intrinsic motivation accomplishment scores (beta=0.22, P<0.05), higher levels of self-reported adjustment to university (beta=0.24, P<0.05), and a higher GPA in their first year of study (beta=0.86, P<0.001) had higher overall marks at the end of their university careers Relations among adjustment, academic motivation, stress, GPA, overall academic performance and social problem solving appraisal dimensions To further clarify the relationships between different problem-solving appraisal dimensions, Time 2 measures and overall academic performance, further exploratory regression analyses were conducted using the problem-solving appraisal subscales. For those measures that showed a significant relationship with total problem-solving scores (see Table 4), a further stepwise regression analysis was conducted entering each of the six problem-solving subscales in an incremental fashion to assess which dimensions contributed most to the relation between problem-solving appraisals and adjustment, motivation, stress, and academic performance. The results of these Table 5 Stepwise multiple regression analyses predicting adjustment to university life, academic motivation, stress, GPA and overall academic performance from problem-solving appraisal subscales a Independent Dependent variables variables b CAQ SRA AMQ- EMID AMQ- AMOT PSS DHI GPA OAP beta R 2 ch beta R 2 ch beta R 2 ch beta R 2 ch beta R 2 ch beta R 2 ch beta R 2 ch beta R 2 ch Helplessness 0.33** 0.10 Control 0.23* ** 0.06 Creativity 0.27* 0.11 Confidence 0.34** * ** * 0.05 Approach 0.19* 0.04 Avoidance 0.22* 0.05 a See Table 1 for abbreviations. b Only significant results shown. * P<0.05. ** P<0.01.

15 S.R. Baker / Personality and Individual Differences 35 (2003) analyses are shown in Table 5. As can be seen, problem-solving creativity and confidence were significant predictors of self-reported adjustment to university, accounting for an additional 15% of the variance after controlling for demographics and entry qualifications (R 2 =0.20, F(5, 90)=4.12, P<0.01). Problem-solving confidence was also a significant predictor of adjustment to university (CAQ), extrinsic motivation (identified regulation), and perceived stress (PSS) accounting for an additional 11% (R 2 =0.13, F(4, 90)=3.24, P<0.05), 7% (R 2 =0.18, F(4, 90)=4.60, P<0.01) and 5% (R 2 =0.11, F(5, 90)=2.72, P<0.05) of the variance respectively. Examination of the beta values indicates that those individuals who had greater confidence in their ability to solve problems reported better adjustment to university, greater self-determination (as measured by the identified regulation subscale), and lower levels of stress while studying than did individuals with less problem-solving confidence. In addition, individuals who were more creative in solving problems reported better adjustment to university compared to less creative problem-solvers. Self-reported stress (DHI) was also associated with greater feelings of helplessness in problem situations (R 2 =0.21, F(4, 90)=5.53, P=0.001). With regard to amotivation, problem-solving control and avoidance had significant effects, accounting for an additional 12% of the variance (R 2 =0.13, F(5, 90)=2.64, P<0.05), with feelings of uncontrollability and the tendency to avoid problems associated with greater amotivation while studying. After controlling for demographics and entry qualifications, two problem-solving appraisal dimensions were associated with academic performance; problem-solving control with GPA (R 2 =0.22, F(4, 90)=6.01, P<0.001), and approach with overall academic performance (R 2 =0.27, F(4, 90)=7.91, P<0.001), both contributing 4% of the variance to their respective measures. Examination of the beta values indicates that those individuals with greater feelings of control in problem situations had higher marks in their first year of study, whilst the tendency to approach problem situations was associated with higher overall marks over students three years of study. 4. Discussion The results of the study suggest that social problem-solving appraisals were an important predictor of individuals psychosocial adjustment to university, perceived stress levels, motivational orientations (identified extrinsic motivation and amotivation), and academic performance whilst studying, and overall academic performance over the course of students university careers. In relation to overall academic performance, gender, entry qualifications, intrinsic motivation (to accomplish), and levels of adjustment, in addition to social problem-solving appraisals, were all important in predicting performance over the course of students time at university. Additionally, different dimensions of self-appraised problem solving were related to different adaptational and academic outcomes. Within a social problem-solving framework (D Zurilla, 1986, 1990), social problem solving is a process that enables individuals to effectively identify and implement coping strategies to deal with problems and demands encountered in daily living. In this way, problem solving should act to increase general competence and adaptation and reduce levels of stress by facilitating more effective problem resolution, and minimising the emotional effects of problem situations. The present findings are consistent with this hypothesis, and with previous studies in educational settings (Chang & D Zurilla, 1996; D Zurilla & Sheedy, 1991). That is, effective self-appraised

16 584 S.R. Baker / Personality and Individual Differences 35 (2003) problem solving, measured on entry to university, was associated with better subsequent psychosocial adjustment and lower levels of perceived stress. Furthermore, social problem-solving appraisals had a direct effect on academic motivation; effective self-appraised problem solving was linked to greater identified extrinsic motivation and lower levels of amotivation. In accordance with Deci and Ryan s (1985, 1991) self-determination framework, these data suggest that individuals who had greater self-perceived problem-solving abilities had a more self-determined profile, therefore were more likely to undertake academicrelated behaviours (e.g. extra reading) because they were valued and judged as intrinsically important, rather than for the attainment of external rewards (e.g. teacher approval), and that they were less amotivated, compared to individuals with lower self-perceived problem-solving abilities. That is, they were more likely to perceive contingencies between their behaviours (e.g. more time spent studying) and academic outcomes (e.g. better grades). Although no previous studies have examined specifically relations between social problem-solving appraisals and motivational orientations, the present data are in line with differences reported in the literature between self-appraised effective and ineffective problem solvers on a number of dimensions which might characterise intrinsically motivated behaviours; enjoyment of cognitive activities (Heppner et al., 1983), more adaptive study habits and attitudes (Elliott et al., 1990), and higher expectancies for control (Nezu, 1985), as well as those potentially associated with amotivated behaviours namely, a general tendency toward passivity, and shirking of responsibilities and decision-making (Maydeu-Olivares & D Zurilla, 1996). In relation to academic performance, effective social problem-solving appraisals predicted higher grades, findings that support and extend those of previous studies with American and Spanish students (D Zurilla & Nezu, 1990; D Zurilla & Sheedy, 1992; Rodriguez-Fornells & Maydeu-Olivares, 2000). After controlling for prior academic aptitude, problem-solving appraisals were found to have a direct positive effect on academic performance not just in students first year as reported in previous studies but throughout their university careers. However, although the variance accounted for by social problem solving in academic performance scores was more than that reported in these previous studies ( %), it was still rather modest (5 7%). There are a number of possible reasons for this. It may be that in addition to exerting a direct effect, social problem solving appraisals had an indirect impact on performance via other factors. There are a number of factors identified in the relevant literature that may potentially moderate this relationship (e.g. personality; Halamandaris & Power, 1997, 1999). Of those factors included in the present study, motivational orientation, gender, entry qualifications and psychosocial adjustment were all associated with academic performance; women, and those individuals who reported better adjustment to university, were more intrinsically motivated toward accomplishment, and had higher academic entry qualifications obtained significantly higher marks during their three years at university. It may be, for example, that effective problem-solvers had better levels of adjustment to university life or were more intrinsically motivated toward their academic studies, which in turn, led to better academic performance. Such an explanation would be supported by relationships observed between social problem solving appraisals and both psychosocial adjustment and academic motivation. It is also consistent with previous research in a range of educational settings that supports the notion that better adjustment and more intrinsically motivated behaviours are linked to greater academic success (e.g. Deci & Ryan, 1985, 1991). However, what is not possible to ascertain from the present study is the cause and effect relationship between social problem solving appraisals and motivational orientations. Since the

17 S.R. Baker / Personality and Individual Differences 35 (2003) motivation measure was not administered at Time 1, it is not possible to determine whether individuals displayed the same pattern of motivational orientations prior to arrival at university, or whether these patterns developed in response to social problem solving skills and abilities. Moreover, whilst social problem solving appraisals in the present study have been shown to influence students academic motivation and performance, it is highly likely that reciprocal relationships also exist. That is, changes in motivation over time as a result of experiences whilst studying, as well as ongoing performance, may impact on the implementation and effectiveness of social problem solving skills. Other factors are also more than likely to influence these relationships. For example, women students had higher identified extrinsic motivation scores and better academic performance than did men in this study. These data are in line with previous studies which have found that women were generally more motivated toward academic activities (Karsenti & Thibert, 1994), displayed a more self-determined motivational profile (Vallerand & Bissonnette, 1992), and tended to have higher levels of desire to finish university and persistence behaviour than men (Allen, 1999). It is not clear whether these differences were related to social problem-solving appraisals; although there were no gender differences in self-appraised social problem solving, previous studies have indicated such differences do exist (D Zurilla, Maydeu- Olivares, & Kant, 1998). Given the difference in sample size between men and women in the present study, reflecting the gender imbalance of British psychology courses, these data should be interpreted with caution until further research has explored these potential differences further. Furthermore, future research needs to assess the influence of other factors not measured in this study. For example, personality variables such as neuroticism and extraversion, social support, and study habits, have all been shown to impact on key adaptational and educational outcomes (e.g. DeRaad, 1996; Elliott et al., 1990; Halamandaris & Power, 1997, 1999). It is possible that such factors may have influenced the pattern of results observed here given that the data were not in all cases consistent with the hypothesised relations depicted in Fig. 1, for example in relation to self-reported health. Additionally, whilst there are a number of strengths in the design and conclusions that can be drawn from prospective longitudinal studies such as this, the only way in which to assess the complexities of the interrelationships between social problem-solving appraisals and key outcome variables, including both direct and moderating pathways, is via structural equation modelling. Due to the number of participants this was beyond the scope of the present study. Additional data is currently being collected from two cohorts of students giving data over a 5-year time-span, which should enable a more detailed investigation of these relationships. In addition, key adaptational outcomes are being measured at different time points throughout students three years at university, which will allow an examination of the potential differential effects of social problem-solving appraisals on stress, adjustment and motivation in relation to new demands and problems experienced over students entire university careers. An additional aim of the study was to explore the different dimensions of problem solving appraisals and their relation to different long-term outcomes. It was reasoned that the problemsolving confidence, personal control, and problem-solving helplessness dimensions would be associated with measures of subjective well-being (adjustment and stress), whilst the dimensions of problem-solving creativity, and approach and avoidance style would associated with behaviourally-based outcomes such as academic performance, but unrelated to subjective indices of distress. These predictions were based on the premise that problem-solving confidence, personal control, and problem-solving helplessness represent facets of the problem orientation component