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Rasch analysis and item reduction of the hypomanic personality scale
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Personality and Individual Differences 44 (2008) 1772–1783 www.elsevier.com/locate/paid
Rasch analysis and item reduction of the hypomanic personality scale David M. Meads a,*, Richard P. Bentall b a
Galen Research, Enterprise House, Manchester Science Park, Lloyd Street North, Greater Manchester M16 6SE, United Kingdom b School of Psychology, University of Wales, Bangor, United Kingdom
Received 25 June 2007; received in revised form 2 February 2008; accepted 11 February 2008
Abstract The aim of the current study was to reduce the number of items in the 48-item hypomanic personality scale (HPS) and determine whether a unidimensional scale of the hypomanic trait could be derived. Previously collected HPS data from University students (n = 318) were applied to the Rasch model (one-parameter item response theory). Overall scale and individual item fit statistics were used to judge fit to the model and item maps employed to determine coverage of the trait. Cronbach’s Alpha and correlations with other questionnaires pre- and post-item reduction were evaluated. Rasch analysis indicated that the original HPS was not unidimensional, had significant redundancy and differential item functioning by age and gender. An iterative process of item reduction produced a 20-item HPS (HPS-20) that retained the concepts of the original HPS and had excellent fit to the Rasch model (v2 p = 0.27). Unidimensionality of the HPS20 was confirmed. The traditional psychometric properties of the HPS-20 and coverage of the underlying hypomanic construct were similar to the original. It was possible to derive a unidimensional measure of the hypomanic trait. Further use of the HPS-20 is encouraged as it may increase understanding of the risk factors for affective disorders. Ó 2008 Elsevier Ltd. All rights reserved. Keywords: Hypomanic; Personality; Item reduction; Rasch; Item-response theory; Questionnaire
*
Corresponding author. Tel.: +44 0 161 226 4446; fax: +44 0 161 226 4478. E-mail addresses: [email protected], [email protected] (D.M. Meads), [email protected] (R.P. Bentall). 0191-8869/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2008.02.009
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1. Introduction People experiencing hypomania are characterised by optimism, happiness, extraversion, sociability, and increased energy but can also be irritable, impulsive, risk-taking, irresponsible and controlling (Eckblad & Chapman, 1986). It has been suggested that individuals exhibiting hypomanic personality traits may be at an increased risk of developing bipolar disorders (Kwapil et al., 2000), which has been estimated the fifth most important cause of disability and third most important mental illness worldwide (World Health Organization, 2001). The hypomanic personality scale (HPS; Eckblad & Chapman, 1986) is one of the most commonly used questionnaires to assess hypomanic personality traits and has been used to identify those most at risk for bipolar disorders (Meyer, 2002). The HPS is a self-report questionnaire capturing sociability, high ambition and self-esteem, positive affect, increased energy levels, and selfperceived individuality and creativity. A number of studies have provided encouraging evidence of the construct validity of the HPS. In the development study, Eckblad and Chapman (1986) found that high scorers on the HPS had more mood disorders and hypomanic episodes, more psychotic-type symptoms, higher rates of substance abuse and lower psychosocial functioning compared with low scoring controls. These findings were corroborated by Kwapil et al. (2000) and similar results were found by Klein, Lewinsohn, and Seeley (1996). Using the German version of the HPS, Meyer and Hautzinger (2003) also found a group scoring highly on the HPS had a significantly higher lifetime risk of manic episodes (20.8%) and hypomanic episodes (41.7%) than a low scoring control group (1.3% and 6.6%, respectively). High scorers on the HPS have also been found to share similar traits and biases to individuals with bipolar disorder (Bentall & Thompson, 1990; Johnson, Ruggero, & Carver, 2005). Perhaps most importantly, the study by Kwapil et al. (2000), which followed-up HPS high scorers after 12 years, found that the HPS scores predicted the onset of bipolar disorders. A disorder prevalence of 25% was reported for the (high scoring) risk group compared to 0% in the (low scoring) control group. The authors also found that 36% of the high scorers had experienced a major depressive episode in the follow-up period compared to 10% of the control group. Despite this encouraging evidence about the utility and validity of the HPS, very little work has been conducted assessing its dimensionality. Research on the dimensionality of questionnaires in this field has been generally limited to the application of factor analysis (e.g. Eckblad & Chapman, 1986; Hantouche, Angst, & Akiskal, 2003; Meyer et al., 2007). 1.1. Rasch model Item response theory (IRT) is a general statistical theory about item (question) and scale (questionnaire) performance and how that performance relates to the factor(s) that are measured by the items in the scale. The simplest logistic latent trait IRT model is the Rasch one-parameter model (Rasch, 1960). Rasch analysis places questionnaire response data for each individual and each question on the same spectrum of person severity and item severity (i.e. every person and item is given a location). The Rasch model assumes that the probability a particular individual will respond in a certain way to a particular item is a logistic function of the relative distance between the item location
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and the person location and only a function of this. In the case of dichotomous items this is formally expressed by pi ðhÞ ¼
eðhbi Þ 1 þ eðhbi Þ
where pi ðhÞ is the probability that persons with severity h will affirm item i, and b is the item severity parameter. For the HPS to conform to the Rasch model, the probability that an individual would affirm an item on the scale must be a function of the level of hypomanic trait exhibited by the individual and the level of hypomanic trait represented by the item being completed and only a function of these factors. For the scale and items to be working consistently, there should be evidence that those people who (according to their scores on the whole scale) possess a high level of the hypomanic trait tend to have a high probability of affirming items representing low levels of the trait. Assuming that the data fit, the Rasch model transforms them from ordinal scores into interval level measurement with the logit (log odds unit) as the unit of measurement. The use of the Rasch model informs whether items and scales can be considered unidimensional. Once unidimensionality is confirmed it is then justifiable to claim that the items measure one construct and it is acceptable to add the scores of these items together to obtain a total score for that construct. The use of Rasch analysis in the development and analysis of tests and questionnaires is increasing in psychology and psychiatry (e.g. Betemps & Baker, 2004; Merrell & Tymms, 2005; Pallant & Tennant, 2007; Schultz-Larsen, Lomholt, & Kreiner, 2007). Several authors (Nijsten, Unaeze, & Stern, 2006; Prieto, Alonso, & Lamarca, 2003; Wright, 1996, 1999) have argued that the use of Rasch in assessing questionnaire scaling properties is preferred to the use of classical test theory (CTT) and factor analysis. Factor analysis does not necessarily provide a conceptual linear assessment of the construct, even if there is a high loading onto one factor (Wright, 1999; Waugh & Chapman, 2005), and may provide misleading evidence that a scale is working well when it is not (Waugh & Chapman, 2005). 1.2. Aims and objectives The HPS may be a useful tool for gaining an understanding of the aetiology of and risk factors for affective disorders. However, the limited research conducted into the dimensionality of the scale and the underlying hypomanic construct together with the scale’s length (48-items) may act as barriers to its increased use. The aim of the research was to apply the Rasch model to HPS data to determine whether a unidimensional measure of hypomania could be derived and to reduce the number of items to produce a short and more easily administered scale.
2. Methods 2.1. Data source The data used for the analysis had been previously collected as part of a PhD project. 318 undergraduate students at the University of Manchester completed a battery of online question-
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naires as part of their course requirements. Two hundred and nineteen (68.9%) were female and 99 (31.1%) male. The mean age of the sample was 21.5 years (SD = 4.0, range 18.0–48.0). The following measures were completed. 2.2. HPS The HPS comprises 48 statements with dichotomous response options (‘True’ [scored 1] or ‘Not True’ [scored 0]). Scores range 0–48, with high scores indicating greater levels of hypomania. The HPS has been found to have adequate inter-relatedness of items (Cronbach’s Alpha = 0.87 Eckblad & Chapman, 1986) and test–retest reliability (r = 0.81 Eckblad & Chapman, 1986). 2.3. BDI The Beck Depression Inventory (BDI; Beck, Ward, & Mendelson, 1961) is a 21-item self-report rating inventory measuring characteristic attitudes and symptoms of depression. Scores range from 0 to 3 on each item (total range 0–63). 2.4. SDS The Crowne–Marlowe Scale for Social Desirability (SDS; Crowne & Marlowe, 1960) is a questionnaire with true/false response options that assesses levels of social desirability or need for approval. The 10-item short-form was employed in this study (Strahan & Gerbasi, 1972). 2.5. RSQ Nolen-Hoeksema’s Response Style Questionnaire (RSQ; Nolen-Hoeksema, 1991, amended by Thomas & Bentall, 2002) is a 48-item self-report measure of stable coping behaviours in response to feelings of depression. People respond on a four-point scale (0–3). The RSQ has 23-items covering rumination, 11-items covering distraction techniques or behaviours, 10-items covering dangerous activities and 4-items relating to problem solving. The Dangerous activity scale includes items such as ‘Drink alcohol excessively’ and ‘Try to initiate new relationships with strangers’. Table 1 shows questionnaire scores for the sample. Only 5 (1.7%) of the sample scored 36 or higher on the HPS which was the threshold for high risk used by Eckblad and Chapman (1986).
Table 1 Questionnaire scores HPS N Mean (SD) Median Min–max
299 17.6 (8.2) 17.0 3.0–38.0
BDI 318 10.9 (8.7) 9.0 0.0–41.0
SDS 318 5.4 (2.0) 5.0 0.0–11.0
RSQ Rumination
Adaptation
Dangerous activities
318 45.8 (11.3) 46.0 23.0–71.0
318 27.7 (6.6) 27.0 14.0–47.0
318 9.0 (3.1) 8.0 6.0–20.0
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2.6. Traditional analyses Correlations (Pearson’s product-moment) between the HPS and the BDI, SDS, RSQ, and age were examined pre- and post-item reduction. The HPS correlated at 0.19 with the BDI in the study by Thomas and Bentall (2002) thus correlations in this study were anticipated to be low. Ideally, correlations between the HPS and SDS should be low to give confidence that the hypomania trait being assessed is not inflated due to social desirability. The RSQ dangerous activities scale should exhibit higher correlations with the HPS since the trait of hypomania is associated with the participation in risky and potentially dangerous activities. Cronbach’s Alpha was calculated for the HPS before and after item reduction. 2.7. Rasch analysis Rasch analyses were conducted using the Rasch Unidimensional Measurement Model (RUMM2020; Andrich, Lyne, Sheridan, & Ludo, 2003) software. The adequacy of the fit of the HPS to the Rasch model was evaluated using the item-trait interaction v2 fit statistic. In addition, the fit of the items were evaluated through individual item v2 fit statistics. A significant v2 p value of <0.01 was taken to indicate significant misfit while a p value of 0.01–0.05 was taken to indicate borderline misfit. When the data fit the model, the overall distribution statistics for item fit and Person fit should have a mean of approximately 0 and a standard deviation of approximately 1. The analysis provides an estimate of the level of divergence of each person from the model and provides residual scores for each item. Any items with a residual of greater than ±2.5 exhibit misfit to the Rasch model. When data has been shown to fit the Rasch model a test must be conducted to ensure an absence of multidimensionality. This test involves conducting an independent t-test comparison of person locations estimated using two different subset of items in the final scale (Smith, 2002). Finally, the RUMM programme also allows the opportunity to evaluate differential item functioning (DIF; Holland & Wainer, 1993). DIF occurs when the responses to an item are affected by factors that are external to the questionnaire, such as age and gender and may mean, for example, that males are more likely to affirm an item than females. As Rasch analysis places each individual and each item on the same underlying logit scale it is possible to observe (in the form of item maps) the extent to which the underlying trait expressed by the respondents is captured by the HPS. In addition to revealing item redundancy, the item maps also reveal the order of items in terms of severity; this is important because it is informative about which items and factors represent more or less of the latent trait being captured. 2.8. Item reduction process Items were considered candidates for removal from the scale if they exhibited significant misfit (v2 p < 0.01), or had excessive residual values (> ± 2.5). Items were also considered for removal if they exhibited significant DIF (ANOVA p < 0.01) by age or gender. Throughout this process the item map was consulted to identify redundant items. Since it was desirable to maintain the scope of measurement offered by the original scale, items at the extremes of the severity levels were only removed as a last resort.
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Item removal was an iterative process, with items being removed one at a time followed by consultation of the fit statistics. The concept-retention method (Beaton, Wright, & Katz, 2005) was also employed such that, wherever possible, all factors represented in the long-form of the scale would also be represented in the short-form. The success of the item reduction process was judged by comparing pre- and post-reduction alpha coefficients, correlations with other assessments and logit coverage.
3. Results 3.1. Rasch analysis Rasch analysis of the 48-item HPS indicated that it did not fit the model (overall v2 p < 0.001). The residual mean value for the items was 0.003 with a SD of 1.66. Since the SD is much higher than the expected value of 1 there is evidence that the items do not fit the model. The residual mean for persons was 0.038 with a SD of 0.932 indicating that respondents did not misfit the model. Two items (item 20: ‘I am no more self-aware than the majority of people’ and item 38: ‘When I feel very excited and happy, I almost always know the reason why’) had significant misfit and another two had borderline misfit. Fig. 1 shows the item characteristic curve (ICC) for the item 38, which gives an indication of misfit. The six class intervals (observed scores of groups each of around 50 people with similar levels of hypomania) do not trace the S-shaped curve of expected responses. The model predicts that those exhibiting low levels of hypomania (Class 1) should have a far lower probability (point A) of affirming this item than was observed (point B). In addition, as the trajectory of the class intervals are flat as levels of hypomania increase (left to right on the x axis), the item does not discriminate well between groups of individuals. There is little difference in observed scores on this item (from point B to C) between those with the lowest (Class 1) and highest (Class 6) levels of hypomania (the difference should be that between A and D). This item was removed.
Fig. 1. Misfit in ‘When I feel very excited and happy, I almost always know the reason why’.
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Fig. 2. DIF in ‘I find it easy to get people sexually interested in me’.
Several items also exhibited DIF by age and gender. Fig. 2 shows DIF by gender for the item ‘I find it easy to get people sexually interested in me’. At every level of trait females are more likely to affirm this statement. The difference between observed scores on this item is shown by the difference between points A and B which are the observed scores for males and females who exhibited moderate levels of hypomania. This item was also removed from the scale. Several of the items addressing intensity and fluctuation in emotions and mood exhibited DIF with females being more likely to affirm these items. It was considered necessary to retain some of these items however as they capture crucial hypomanic facets. The item map in Fig. 3, shows that the HPS has a reasonable coverage of the underlying trait and respondents but that there are some respondents at the mild end of the spectrum that are not covered by the HPS. According to the map item 36 (‘I think I would make a good nightclub comedian’) represents the greatest level of hypomanic trait (is the most severe item) and items 12 (‘I often feel excited and happy for no apparent reason’) and 33 (‘I do most of my best work during brief periods of intense inspiration’) capture the lowest level of trait (are the mildest). The logit distance (3.40 logits) between the locations of these extreme items represents the scope of construct covered by the HPS. Fig. 3 suggests that there is a good deal of redundancy in the HPS since items are bunched around the centre of the logit scale, many capturing similar levels of trait; this suggests that there is considerable scope for item reduction. Misfitting items were deleted, as were redundant items leaving a 20-item scale. The reduced scale exhibited excellent fit to the model (overall v2 p = 0.27) with no significant item misfit. The mean residual for items was 0.17 with a SD of 0.98 and for persons 0.07 with a SD of 0.85. The SD for items is much closer to 1 after item reduction indicating better fit. Local independence of items was confirmed with the t-test of person locations, confirming that the shortened HPS is a unidimensional assessment of hypomania. The logit distance between the most severe and mildest items (3.12) is similar to that of the original measure indicating that although the scale has fewer than half the items it retains the scope
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Fig. 3. Item map of 48-item HPS.
of trait coverage. The final item map (Fig. 4) shows the HPS-20 items (item numbers in parentheses) in severity order. 3.2. Traditional psychometrics The mean score of the 20-item HPS was 8.2 (±4.3; range 0.0–19.0) and the mean per item score was 0.41 which was slightly higher than that of the 48-item HPS (0.37). As with the original HPS, the reduced version had no end effects as only 1 person scored 0 and none scored the maximum total. In terms of identifying high scorers, of the 35 people scoring in the top decile on the 48-item HPS, 30 also appeared in the top decile of scorers on the 20-HPS. Nine individuals in the upper decile on the 20-item HPS do not appear in the upper decile on the original version of the measure. These slight changes in the ordering of the sample in terms of hypomanic trait level are to be expected given the number of items that have been removed. The 20-item also resulted in reduced missing data as 11 fewer cases have missing responses when the shortened HPS was used. The alpha of the reduced scale is 0.80 which indicates adequate inter-relatedness of items. This is lower than the alpha value obtained by the 48-item HPS (0.87) but this value would have been inflated due to significant item redundancy. The 48- and 20-item versions of the HPS correlated at 0.94 (n = 299). Correlations between the HPS and comparator questionnaires pre- and post-item reduction, shown in Table 2, are similar.
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(25) A hundred years after I’m dead, my achievements will probably have been forgotten I am so good at controlling others that sometimes it scares me I am frequently in such high spirits that I can’t concentrate on any one thing for too long I am considered to be a kind of ‘Hyper’ person I often have moods where I feel so energetic and optimistic that I feel I could outperform almost anyone at anything In unfamiliar surroundings I am often so assertive and sociable that I surprise myself / (48) I like to have others think of me as a normal kind of person (32) I am usually in an average sort of mood, not too high and not too low / (7) I often get into moods where I feel like many of the rules of life don’t apply to me (27) (23) (35) (16) (19)
(24) I very frequently get into moods where I wish I could be everywhere and do everything at once (42) I have often felt happy and irritable at the same time / (8) Sometime ideas and insights come to me so fast I cannot express them all / (3) I seem to have an uncommon ability to persuade and inspire others (44) I frequently find that my thoughts are racing (10) There are times when I am so restless that it impossible for me to sit still / (45) When I feel an emotion, I usually feel it with extreme intensity (39) Many people would consider me to be amusing but kind of eccentric / (9) I seem to be a person whose mood goes up and down easily (12) I often feel excited and happy for no apparent reason / (33) I do most of my work during brief periods of intense inspiration
Fig. 4. Item map of HPS-20.
Table 2 HPS correlations with other scales pre- and post-item reduction Age BDI SDS RSQ Rumination Adaptation Dangerous activities a
48-item HPS
20-item HPS
0.11 0.22a 0.27a
0.11 0.30a 0.32a
0.32a 0.17a 0.41a
0.36a 0.11 0.39a
Correlation is significant at the 0.01 level (2-tailed).
4. Conclusions This study is one of the few to apply modern test theory in the form of Rasch analysis to a mania-related scale. The use of Rasch has enabled the derivation of a significantly shortened HPS that will lend itself more readily to inclusion in studies of the general population. The HPS-20 retains
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the scope of the original scale both in terms of the level of trait captured and the ideas covered. The indicators of hypomanic personality included by Eckblad & Chapman in the original scale are also present in the reduced version. This study shows that it is possible to conduct item reduction employing both concept-retention and more statistical-based methods. As the HPS-20 data fit the Rasch model, individual item scores can justifiably be summed to obtain an overall score of hypomania. The use of Rasch has also enabled the identification and removal of poor items which should improve the precision of the scale. The analysis has made it possible to see the relative severity of the items; this in turn provides information on what factors represent greater levels of hypomania and what items capture more of the hypomanic trait. There has been little research conducted into whether personality traits such as the Hyperthymic–hypomanic trait are normally distributed in the general population or whether they are an either/or factor (taxonic). Research by Meyer and Keller (2003) did not find evidence for the existence of a taxonomic structure of hypomania, instead concluding that the trait is dimensional and part of normal experience; this is corroborated by the findings of the current study. This idea of a spectrum of experience and behaviour stems from Eysenck’s research on the biological basis of normal personality variation and his proposal that mental illnesses are merely extremities of variable dimensions of behaviour (Eysenck, 1947, 1960). Work exploring this theory has been conducted in schizophrenia (Claridge, 1985, 1997 and in bipolar disorders (e.g. Klein et al., 1996; Birmaher & Axelson, 2006). According to this theory hypomania may represent the lower extremities of a continuum of affective disorder. This could be tested by combining HPS-20 data from the general population and those diagnosed with cyclothymia or bipolar II disorder and applying it to the Rasch model. If the HPS-20 still fit the Rasch model when these data were combined and worked in the same way for both groups then this would represent further evidence of the existence of a continuum of affective disorders. Several limitations of the present study need to be acknowledged. First, the data was obtained from a student sample and therefore may have inherent socioeconomic and cultural biases. Second, there is only limited evidence (from the expected correlations with other hypomania-related measures) of the validity of the scale. Future investigations comparing diagnosed bipolar spectrum patients and controls should address this issue. In addition, it is possible that the choice of item response theory model (one-parameter) may have affected the makeup of the final scale. It would be interesting to determine whether this is the case by applying the two-parameter model to the same data. Finally, it will be important to confirm in future studies that the HPS-20 is as capable of predicting future affective disorder as the original HPS. These limitations not withstanding, the reduced scale has obvious psychometric and practical advantages over the original HPS, and we encourage other investigators to use it appropriately in investigations of the psychological processes involved in mania and related states.
Acknowledgement The authors would like to thank Sara Melo who collected and supplied the data which made the research possible.
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Personality and Individual Differences 44 (2008) 1772–1783 www.elsevier.com/locate/paid
Rasch analysis and item reduction of the hypomanic personality scale David M. Meads a,*, Richard P. Bentall b a
Galen Research, Enterprise House, Manchester Science Park, Lloyd Street North, Greater Manchester M16 6SE, United Kingdom b School of Psychology, University of Wales, Bangor, United Kingdom
Received 25 June 2007; received in revised form 2 February 2008; accepted 11 February 2008
Abstract The aim of the current study was to reduce the number of items in the 48-item hypomanic personality scale (HPS) and determine whether a unidimensional scale of the hypomanic trait could be derived. Previously collected HPS data from University students (n = 318) were applied to the Rasch model (one-parameter item response theory). Overall scale and individual item fit statistics were used to judge fit to the model and item maps employed to determine coverage of the trait. Cronbach’s Alpha and correlations with other questionnaires pre- and post-item reduction were evaluated. Rasch analysis indicated that the original HPS was not unidimensional, had significant redundancy and differential item functioning by age and gender. An iterative process of item reduction produced a 20-item HPS (HPS-20) that retained the concepts of the original HPS and had excellent fit to the Rasch model (v2 p = 0.27). Unidimensionality of the HPS20 was confirmed. The traditional psychometric properties of the HPS-20 and coverage of the underlying hypomanic construct were similar to the original. It was possible to derive a unidimensional measure of the hypomanic trait. Further use of the HPS-20 is encouraged as it may increase understanding of the risk factors for affective disorders. Ó 2008 Elsevier Ltd. All rights reserved. Keywords: Hypomanic; Personality; Item reduction; Rasch; Item-response theory; Questionnaire
*
Corresponding author. Tel.: +44 0 161 226 4446; fax: +44 0 161 226 4478. E-mail addresses: [email protected], [email protected] (D.M. Meads), [email protected] (R.P. Bentall). 0191-8869/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2008.02.009
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1. Introduction People experiencing hypomania are characterised by optimism, happiness, extraversion, sociability, and increased energy but can also be irritable, impulsive, risk-taking, irresponsible and controlling (Eckblad & Chapman, 1986). It has been suggested that individuals exhibiting hypomanic personality traits may be at an increased risk of developing bipolar disorders (Kwapil et al., 2000), which has been estimated the fifth most important cause of disability and third most important mental illness worldwide (World Health Organization, 2001). The hypomanic personality scale (HPS; Eckblad & Chapman, 1986) is one of the most commonly used questionnaires to assess hypomanic personality traits and has been used to identify those most at risk for bipolar disorders (Meyer, 2002). The HPS is a self-report questionnaire capturing sociability, high ambition and self-esteem, positive affect, increased energy levels, and selfperceived individuality and creativity. A number of studies have provided encouraging evidence of the construct validity of the HPS. In the development study, Eckblad and Chapman (1986) found that high scorers on the HPS had more mood disorders and hypomanic episodes, more psychotic-type symptoms, higher rates of substance abuse and lower psychosocial functioning compared with low scoring controls. These findings were corroborated by Kwapil et al. (2000) and similar results were found by Klein, Lewinsohn, and Seeley (1996). Using the German version of the HPS, Meyer and Hautzinger (2003) also found a group scoring highly on the HPS had a significantly higher lifetime risk of manic episodes (20.8%) and hypomanic episodes (41.7%) than a low scoring control group (1.3% and 6.6%, respectively). High scorers on the HPS have also been found to share similar traits and biases to individuals with bipolar disorder (Bentall & Thompson, 1990; Johnson, Ruggero, & Carver, 2005). Perhaps most importantly, the study by Kwapil et al. (2000), which followed-up HPS high scorers after 12 years, found that the HPS scores predicted the onset of bipolar disorders. A disorder prevalence of 25% was reported for the (high scoring) risk group compared to 0% in the (low scoring) control group. The authors also found that 36% of the high scorers had experienced a major depressive episode in the follow-up period compared to 10% of the control group. Despite this encouraging evidence about the utility and validity of the HPS, very little work has been conducted assessing its dimensionality. Research on the dimensionality of questionnaires in this field has been generally limited to the application of factor analysis (e.g. Eckblad & Chapman, 1986; Hantouche, Angst, & Akiskal, 2003; Meyer et al., 2007). 1.1. Rasch model Item response theory (IRT) is a general statistical theory about item (question) and scale (questionnaire) performance and how that performance relates to the factor(s) that are measured by the items in the scale. The simplest logistic latent trait IRT model is the Rasch one-parameter model (Rasch, 1960). Rasch analysis places questionnaire response data for each individual and each question on the same spectrum of person severity and item severity (i.e. every person and item is given a location). The Rasch model assumes that the probability a particular individual will respond in a certain way to a particular item is a logistic function of the relative distance between the item location
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and the person location and only a function of this. In the case of dichotomous items this is formally expressed by pi ðhÞ ¼
eðhbi Þ 1 þ eðhbi Þ
where pi ðhÞ is the probability that persons with severity h will affirm item i, and b is the item severity parameter. For the HPS to conform to the Rasch model, the probability that an individual would affirm an item on the scale must be a function of the level of hypomanic trait exhibited by the individual and the level of hypomanic trait represented by the item being completed and only a function of these factors. For the scale and items to be working consistently, there should be evidence that those people who (according to their scores on the whole scale) possess a high level of the hypomanic trait tend to have a high probability of affirming items representing low levels of the trait. Assuming that the data fit, the Rasch model transforms them from ordinal scores into interval level measurement with the logit (log odds unit) as the unit of measurement. The use of the Rasch model informs whether items and scales can be considered unidimensional. Once unidimensionality is confirmed it is then justifiable to claim that the items measure one construct and it is acceptable to add the scores of these items together to obtain a total score for that construct. The use of Rasch analysis in the development and analysis of tests and questionnaires is increasing in psychology and psychiatry (e.g. Betemps & Baker, 2004; Merrell & Tymms, 2005; Pallant & Tennant, 2007; Schultz-Larsen, Lomholt, & Kreiner, 2007). Several authors (Nijsten, Unaeze, & Stern, 2006; Prieto, Alonso, & Lamarca, 2003; Wright, 1996, 1999) have argued that the use of Rasch in assessing questionnaire scaling properties is preferred to the use of classical test theory (CTT) and factor analysis. Factor analysis does not necessarily provide a conceptual linear assessment of the construct, even if there is a high loading onto one factor (Wright, 1999; Waugh & Chapman, 2005), and may provide misleading evidence that a scale is working well when it is not (Waugh & Chapman, 2005). 1.2. Aims and objectives The HPS may be a useful tool for gaining an understanding of the aetiology of and risk factors for affective disorders. However, the limited research conducted into the dimensionality of the scale and the underlying hypomanic construct together with the scale’s length (48-items) may act as barriers to its increased use. The aim of the research was to apply the Rasch model to HPS data to determine whether a unidimensional measure of hypomania could be derived and to reduce the number of items to produce a short and more easily administered scale.
2. Methods 2.1. Data source The data used for the analysis had been previously collected as part of a PhD project. 318 undergraduate students at the University of Manchester completed a battery of online question-
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naires as part of their course requirements. Two hundred and nineteen (68.9%) were female and 99 (31.1%) male. The mean age of the sample was 21.5 years (SD = 4.0, range 18.0–48.0). The following measures were completed. 2.2. HPS The HPS comprises 48 statements with dichotomous response options (‘True’ [scored 1] or ‘Not True’ [scored 0]). Scores range 0–48, with high scores indicating greater levels of hypomania. The HPS has been found to have adequate inter-relatedness of items (Cronbach’s Alpha = 0.87 Eckblad & Chapman, 1986) and test–retest reliability (r = 0.81 Eckblad & Chapman, 1986). 2.3. BDI The Beck Depression Inventory (BDI; Beck, Ward, & Mendelson, 1961) is a 21-item self-report rating inventory measuring characteristic attitudes and symptoms of depression. Scores range from 0 to 3 on each item (total range 0–63). 2.4. SDS The Crowne–Marlowe Scale for Social Desirability (SDS; Crowne & Marlowe, 1960) is a questionnaire with true/false response options that assesses levels of social desirability or need for approval. The 10-item short-form was employed in this study (Strahan & Gerbasi, 1972). 2.5. RSQ Nolen-Hoeksema’s Response Style Questionnaire (RSQ; Nolen-Hoeksema, 1991, amended by Thomas & Bentall, 2002) is a 48-item self-report measure of stable coping behaviours in response to feelings of depression. People respond on a four-point scale (0–3). The RSQ has 23-items covering rumination, 11-items covering distraction techniques or behaviours, 10-items covering dangerous activities and 4-items relating to problem solving. The Dangerous activity scale includes items such as ‘Drink alcohol excessively’ and ‘Try to initiate new relationships with strangers’. Table 1 shows questionnaire scores for the sample. Only 5 (1.7%) of the sample scored 36 or higher on the HPS which was the threshold for high risk used by Eckblad and Chapman (1986).
Table 1 Questionnaire scores HPS N Mean (SD) Median Min–max
299 17.6 (8.2) 17.0 3.0–38.0
BDI 318 10.9 (8.7) 9.0 0.0–41.0
SDS 318 5.4 (2.0) 5.0 0.0–11.0
RSQ Rumination
Adaptation
Dangerous activities
318 45.8 (11.3) 46.0 23.0–71.0
318 27.7 (6.6) 27.0 14.0–47.0
318 9.0 (3.1) 8.0 6.0–20.0
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2.6. Traditional analyses Correlations (Pearson’s product-moment) between the HPS and the BDI, SDS, RSQ, and age were examined pre- and post-item reduction. The HPS correlated at 0.19 with the BDI in the study by Thomas and Bentall (2002) thus correlations in this study were anticipated to be low. Ideally, correlations between the HPS and SDS should be low to give confidence that the hypomania trait being assessed is not inflated due to social desirability. The RSQ dangerous activities scale should exhibit higher correlations with the HPS since the trait of hypomania is associated with the participation in risky and potentially dangerous activities. Cronbach’s Alpha was calculated for the HPS before and after item reduction. 2.7. Rasch analysis Rasch analyses were conducted using the Rasch Unidimensional Measurement Model (RUMM2020; Andrich, Lyne, Sheridan, & Ludo, 2003) software. The adequacy of the fit of the HPS to the Rasch model was evaluated using the item-trait interaction v2 fit statistic. In addition, the fit of the items were evaluated through individual item v2 fit statistics. A significant v2 p value of <0.01 was taken to indicate significant misfit while a p value of 0.01–0.05 was taken to indicate borderline misfit. When the data fit the model, the overall distribution statistics for item fit and Person fit should have a mean of approximately 0 and a standard deviation of approximately 1. The analysis provides an estimate of the level of divergence of each person from the model and provides residual scores for each item. Any items with a residual of greater than ±2.5 exhibit misfit to the Rasch model. When data has been shown to fit the Rasch model a test must be conducted to ensure an absence of multidimensionality. This test involves conducting an independent t-test comparison of person locations estimated using two different subset of items in the final scale (Smith, 2002). Finally, the RUMM programme also allows the opportunity to evaluate differential item functioning (DIF; Holland & Wainer, 1993). DIF occurs when the responses to an item are affected by factors that are external to the questionnaire, such as age and gender and may mean, for example, that males are more likely to affirm an item than females. As Rasch analysis places each individual and each item on the same underlying logit scale it is possible to observe (in the form of item maps) the extent to which the underlying trait expressed by the respondents is captured by the HPS. In addition to revealing item redundancy, the item maps also reveal the order of items in terms of severity; this is important because it is informative about which items and factors represent more or less of the latent trait being captured. 2.8. Item reduction process Items were considered candidates for removal from the scale if they exhibited significant misfit (v2 p < 0.01), or had excessive residual values (> ± 2.5). Items were also considered for removal if they exhibited significant DIF (ANOVA p < 0.01) by age or gender. Throughout this process the item map was consulted to identify redundant items. Since it was desirable to maintain the scope of measurement offered by the original scale, items at the extremes of the severity levels were only removed as a last resort.
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Item removal was an iterative process, with items being removed one at a time followed by consultation of the fit statistics. The concept-retention method (Beaton, Wright, & Katz, 2005) was also employed such that, wherever possible, all factors represented in the long-form of the scale would also be represented in the short-form. The success of the item reduction process was judged by comparing pre- and post-reduction alpha coefficients, correlations with other assessments and logit coverage.
3. Results 3.1. Rasch analysis Rasch analysis of the 48-item HPS indicated that it did not fit the model (overall v2 p < 0.001). The residual mean value for the items was 0.003 with a SD of 1.66. Since the SD is much higher than the expected value of 1 there is evidence that the items do not fit the model. The residual mean for persons was 0.038 with a SD of 0.932 indicating that respondents did not misfit the model. Two items (item 20: ‘I am no more self-aware than the majority of people’ and item 38: ‘When I feel very excited and happy, I almost always know the reason why’) had significant misfit and another two had borderline misfit. Fig. 1 shows the item characteristic curve (ICC) for the item 38, which gives an indication of misfit. The six class intervals (observed scores of groups each of around 50 people with similar levels of hypomania) do not trace the S-shaped curve of expected responses. The model predicts that those exhibiting low levels of hypomania (Class 1) should have a far lower probability (point A) of affirming this item than was observed (point B). In addition, as the trajectory of the class intervals are flat as levels of hypomania increase (left to right on the x axis), the item does not discriminate well between groups of individuals. There is little difference in observed scores on this item (from point B to C) between those with the lowest (Class 1) and highest (Class 6) levels of hypomania (the difference should be that between A and D). This item was removed.
Fig. 1. Misfit in ‘When I feel very excited and happy, I almost always know the reason why’.
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Fig. 2. DIF in ‘I find it easy to get people sexually interested in me’.
Several items also exhibited DIF by age and gender. Fig. 2 shows DIF by gender for the item ‘I find it easy to get people sexually interested in me’. At every level of trait females are more likely to affirm this statement. The difference between observed scores on this item is shown by the difference between points A and B which are the observed scores for males and females who exhibited moderate levels of hypomania. This item was also removed from the scale. Several of the items addressing intensity and fluctuation in emotions and mood exhibited DIF with females being more likely to affirm these items. It was considered necessary to retain some of these items however as they capture crucial hypomanic facets. The item map in Fig. 3, shows that the HPS has a reasonable coverage of the underlying trait and respondents but that there are some respondents at the mild end of the spectrum that are not covered by the HPS. According to the map item 36 (‘I think I would make a good nightclub comedian’) represents the greatest level of hypomanic trait (is the most severe item) and items 12 (‘I often feel excited and happy for no apparent reason’) and 33 (‘I do most of my best work during brief periods of intense inspiration’) capture the lowest level of trait (are the mildest). The logit distance (3.40 logits) between the locations of these extreme items represents the scope of construct covered by the HPS. Fig. 3 suggests that there is a good deal of redundancy in the HPS since items are bunched around the centre of the logit scale, many capturing similar levels of trait; this suggests that there is considerable scope for item reduction. Misfitting items were deleted, as were redundant items leaving a 20-item scale. The reduced scale exhibited excellent fit to the model (overall v2 p = 0.27) with no significant item misfit. The mean residual for items was 0.17 with a SD of 0.98 and for persons 0.07 with a SD of 0.85. The SD for items is much closer to 1 after item reduction indicating better fit. Local independence of items was confirmed with the t-test of person locations, confirming that the shortened HPS is a unidimensional assessment of hypomania. The logit distance between the most severe and mildest items (3.12) is similar to that of the original measure indicating that although the scale has fewer than half the items it retains the scope
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Fig. 3. Item map of 48-item HPS.
of trait coverage. The final item map (Fig. 4) shows the HPS-20 items (item numbers in parentheses) in severity order. 3.2. Traditional psychometrics The mean score of the 20-item HPS was 8.2 (±4.3; range 0.0–19.0) and the mean per item score was 0.41 which was slightly higher than that of the 48-item HPS (0.37). As with the original HPS, the reduced version had no end effects as only 1 person scored 0 and none scored the maximum total. In terms of identifying high scorers, of the 35 people scoring in the top decile on the 48-item HPS, 30 also appeared in the top decile of scorers on the 20-HPS. Nine individuals in the upper decile on the 20-item HPS do not appear in the upper decile on the original version of the measure. These slight changes in the ordering of the sample in terms of hypomanic trait level are to be expected given the number of items that have been removed. The 20-item also resulted in reduced missing data as 11 fewer cases have missing responses when the shortened HPS was used. The alpha of the reduced scale is 0.80 which indicates adequate inter-relatedness of items. This is lower than the alpha value obtained by the 48-item HPS (0.87) but this value would have been inflated due to significant item redundancy. The 48- and 20-item versions of the HPS correlated at 0.94 (n = 299). Correlations between the HPS and comparator questionnaires pre- and post-item reduction, shown in Table 2, are similar.
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(25) A hundred years after I’m dead, my achievements will probably have been forgotten I am so good at controlling others that sometimes it scares me I am frequently in such high spirits that I can’t concentrate on any one thing for too long I am considered to be a kind of ‘Hyper’ person I often have moods where I feel so energetic and optimistic that I feel I could outperform almost anyone at anything In unfamiliar surroundings I am often so assertive and sociable that I surprise myself / (48) I like to have others think of me as a normal kind of person (32) I am usually in an average sort of mood, not too high and not too low / (7) I often get into moods where I feel like many of the rules of life don’t apply to me (27) (23) (35) (16) (19)
(24) I very frequently get into moods where I wish I could be everywhere and do everything at once (42) I have often felt happy and irritable at the same time / (8) Sometime ideas and insights come to me so fast I cannot express them all / (3) I seem to have an uncommon ability to persuade and inspire others (44) I frequently find that my thoughts are racing (10) There are times when I am so restless that it impossible for me to sit still / (45) When I feel an emotion, I usually feel it with extreme intensity (39) Many people would consider me to be amusing but kind of eccentric / (9) I seem to be a person whose mood goes up and down easily (12) I often feel excited and happy for no apparent reason / (33) I do most of my work during brief periods of intense inspiration
Fig. 4. Item map of HPS-20.
Table 2 HPS correlations with other scales pre- and post-item reduction Age BDI SDS RSQ Rumination Adaptation Dangerous activities a
48-item HPS
20-item HPS
0.11 0.22a 0.27a
0.11 0.30a 0.32a
0.32a 0.17a 0.41a
0.36a 0.11 0.39a
Correlation is significant at the 0.01 level (2-tailed).
4. Conclusions This study is one of the few to apply modern test theory in the form of Rasch analysis to a mania-related scale. The use of Rasch has enabled the derivation of a significantly shortened HPS that will lend itself more readily to inclusion in studies of the general population. The HPS-20 retains
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the scope of the original scale both in terms of the level of trait captured and the ideas covered. The indicators of hypomanic personality included by Eckblad & Chapman in the original scale are also present in the reduced version. This study shows that it is possible to conduct item reduction employing both concept-retention and more statistical-based methods. As the HPS-20 data fit the Rasch model, individual item scores can justifiably be summed to obtain an overall score of hypomania. The use of Rasch has also enabled the identification and removal of poor items which should improve the precision of the scale. The analysis has made it possible to see the relative severity of the items; this in turn provides information on what factors represent greater levels of hypomania and what items capture more of the hypomanic trait. There has been little research conducted into whether personality traits such as the Hyperthymic–hypomanic trait are normally distributed in the general population or whether they are an either/or factor (taxonic). Research by Meyer and Keller (2003) did not find evidence for the existence of a taxonomic structure of hypomania, instead concluding that the trait is dimensional and part of normal experience; this is corroborated by the findings of the current study. This idea of a spectrum of experience and behaviour stems from Eysenck’s research on the biological basis of normal personality variation and his proposal that mental illnesses are merely extremities of variable dimensions of behaviour (Eysenck, 1947, 1960). Work exploring this theory has been conducted in schizophrenia (Claridge, 1985, 1997 and in bipolar disorders (e.g. Klein et al., 1996; Birmaher & Axelson, 2006). According to this theory hypomania may represent the lower extremities of a continuum of affective disorder. This could be tested by combining HPS-20 data from the general population and those diagnosed with cyclothymia or bipolar II disorder and applying it to the Rasch model. If the HPS-20 still fit the Rasch model when these data were combined and worked in the same way for both groups then this would represent further evidence of the existence of a continuum of affective disorders. Several limitations of the present study need to be acknowledged. First, the data was obtained from a student sample and therefore may have inherent socioeconomic and cultural biases. Second, there is only limited evidence (from the expected correlations with other hypomania-related measures) of the validity of the scale. Future investigations comparing diagnosed bipolar spectrum patients and controls should address this issue. In addition, it is possible that the choice of item response theory model (one-parameter) may have affected the makeup of the final scale. It would be interesting to determine whether this is the case by applying the two-parameter model to the same data. Finally, it will be important to confirm in future studies that the HPS-20 is as capable of predicting future affective disorder as the original HPS. These limitations not withstanding, the reduced scale has obvious psychometric and practical advantages over the original HPS, and we encourage other investigators to use it appropriately in investigations of the psychological processes involved in mania and related states.
Acknowledgement The authors would like to thank Sara Melo who collected and supplied the data which made the research possible.
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