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Development and validation of the Pachinko/Pachi-Slot Playing Ambivalence Scale

Development and validation of the Pachinko/Pachi-Slot Playing Ambivalence Scale aria11832013@yahoo.co.jp Yoshino Hospital, 2252, Background: A scale aimed at measuring ambivalence among people with Zushi-tyo, Machida City, pachinko/pachi-slot playing disorder, the Pachinko/Pachi-Slot Playing Ambivalence Tokyo 1940203, Japan Full list of author information Scale (PPAS), was developed and its reliability and validity ascertained. is available at the end of the Methods: A total of 522 participants (average year: 48.0) who were residing in Tokyo article Metropolitan Area, and had played pachinko within the previous year completed ques- tions relating to demographics, four gambling-related scales (including South Oaks Gambling Screen) and two general ambivalence scales (including Ambivalence over Emotional Expressiveness Questionnaire). Results: Internal consistency (α = 0.87) and test–retest reliability (r = 0.66) were con- firmed. The PPAS’s score was associated with each related scale’s score (r = 0.37–0.62). Conclusions: The PPAS was shown to be consistent with previous scales and useful in clinical settings. Keywords: Gambling disorder, Pachinko/pachi-slot playing disorder, Ambivalence scale, DSM5, Severity Background The lifetime prevalence of gambling disorders around the world has been reported to be about 1.5% (Gowing et  al. 2015), similar to that of schizophrenia and bipolar disorder. Not only gambling disorder promotes depression and suicide (Petry and Kiluk 2002), but it has been linked to social problems such as child abuse and severe indebtedness (Grant et al. 2010). Therefore, the development of intervention guidelines based on appropriate diagnostic and assessment measures has become a pressing issue. Existing gambling disorder assessment scales can broadly be divided into: (a) scales for evaluating treatment effectiveness by measuring principal symptoms such as a craving and (b) diagnostic scales providing a comprehensive assessment of problems; for exam- ple, in cognition, behavior, and interpersonal relationships. The former type includes the Gambling Symptom Assessment Scale (G-SAS) (Kim et  al. 2009) and the Yale-Brown Obsessive Compulsive Scale-modified for Pathological Gambling (PG-YBOCS) (Pallanti et al. 2005). The latter type includes assessment instruments such as the Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) (American Psychiatric Association 2013), the South Oaks Gambling Screen (SOGS) (Lesieur and Blume 1987), the Alberta © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 2 of 14 Gaming Research Institute (AGRI) Short Version (Volberg and Williams 2011), the Prob- lem Gambling Severity Index (PGSI) (Ferris and Wynne 2001), and the Lie–Bet Screen (Johnson et al. 1997). These diagnostic scales (b) enable assessment of problem severity, based on several different pathological concepts in a given case. In other words, these scales focus not on a single pathological concept but on multiple pathological concepts such as psychopharmacology of substance use disorder, psychodynamics, and interper- sonal model (Stinchfield 2013). For example, the nine items of DSM5 consist of four different pathological concepts, namely psychopharmacology, psychodynamics, inter - personal and socio-economics model. Similarly, Lie–Bet Screen consists of two con- cepts, interpersonal model and psychopharmacology. On the other hands, scales, which focus on a single pathological concept, have been developed. For example, the Gambling Functional Assessment-Revised measures psychopharmacological dependency, namely positive and negative reinforcement such as resistance and withdrawal (Weatherly et al. 2011); whereas Gamblers’ Beliefs Questionnaire measures cognitive distortions such as neglecting of randomness (Steenbergh et al. 2002). Although various useful scales for gambling disorders have been developed, it is not clear if these scale measure core symptoms that explain the basic mechanism of gam- bling disorder. The importance of the concept of ambivalence, being that “alcoholics simultaneously want to quit and do not want to quit,” has been raised in substance addiction research (Walker et  al. 2011), because it has been found to be a predictor of relapse in drink- ing behavior (including heavy drinking) and drug abuse (Lipkus et  al. 2001; Oser et  al. 2010), and of relapse in ex-smokers (Menninga et  al. 2011). Additionally, ambivalence regarding alcoholism is an important determinant of drinking behavior in the same way that craving for alcohol is (Dawn et al. 2014). In many instances, ambivalence acts as an inhibitory factor in recovery (Armitage 2003). Bleuler, who first coined the concept of ambivalence, encompassed two different ideas. He pointed out that ambivalence can be a symptom of pathology because two oppo- site psychological phenomena continue to exist in parallel, or it can have the common meaning of tying different psychological phenomena together via consistent values (Bleuler 1914/1997; Hitomi 2011). Therefore, in the assessment of ambivalence, these two aspects must be covered. The former is a psychopathological finding, which reveals failure of solution to conflicts, such as “parallel existence of expectation, emotion, and reason” (Bleuler 1914/1997, p. 136). On the other hand, the latter reveals a self-oriented, rational response after conflictive behaviors, such as regret. When assessing ambivalence, one either assesses structural ambivalence by differen - tiating and measuring two conflicting factors such as feelings, thoughts and behaviors, or subjective ambivalence by assessing the psychological state that arises when two conflicting factors coexist (Priester and Petty 1996). For example, Drinking Ambiva - lence Scale (DAS) (Dawn et  al. 2014) measures structural ambivalence; whereas, General Ambivalence Scale (Thompson et  al. 1995) and a six-item ambivalence scale for smoking (Lipkus et  al. 2001) focus on subjective ambivalence. However, Conner and Sparks (2002) report there is a significant correlation between two assessment methods. Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 3 of 14 Currently, no scale has been developed for this concept in gambling. Thus, in this study, we developed a scale to measure ambivalence towards gambling behavior. In Japan, pachinko/pachi-slot playing disorder accounts for nearly 90% of all gambling dis- orders (Toyama et  al. 2014; Komoto 2014). Pachinko and pachi-slot constitute private gambling involving use of a device similar to a recreational arcade game. There are many pachinko/pachi-slot parlors in every downtown area in Japan. Therefore, we first devel - oped the Pachinko/Pachi-Slot Playing Ambivalence Scale (PPAS), and tested its reliabil- ity and validity. Improving classification (severity/subtype) and prediction of prognosis are not the only reasons for the incorporation of ambivalence into the diagnosis and treatment of gambling disorder. A better understanding of ambivalence by those pro- viding support to people with gambling disorders may enhance their understanding of the recovery process that may face frequent relapses. In addition, for the gambler, better understanding could provide an opportunity to think about the cravings that drive his/ her urge to gamble (Komoto and Sato 2014). Methods Participants Initial survey Using an online survey company, we recruited members registered as internet-shopping customers residing in Tokyo, in Saitama, Chiba, or in Kanagawa Prefectures, who had played pachinko or pachi-slot within the previous year. A total of 522 people agreed to participate in the survey, comprising the ambivalence scale and an impression manage- ment subscale (Paulhus 1991). Of the 522 participants, 446 (85.4%) were men and most were in their 40 s (35.8%) or 50  s (28.0%). The majority of the participants were individuals who had at least gradu - ated from college (77.4%), lived with a family (not be single) (72.8%), and had an annual household income of ¥4–10 million (60.4%; the so-called “middle economical class” in Japan). Retest survey We used the same online survey company and asked the 522 from the initial survey to participate again in the survey. Sixty-six participants (12.6%) of the original sample (n = 522) agreed to answer the retest questionnaire. Measures Playing frequency, duration, and expenditure The frequency of playing pachinko/pachi-slot and expenditure (i.e., “money lost”) over the previous 12  months were measured. Responses regarding frequency were rated on a 9-point scale from 1 (less than once a year) to 9 (more than 4 times a week). Playing duration was measured through average playing duration per day, on an 8-point scale, from 1 (less than 1 h) to 8 (8 h or more). Expenditure on playing was measured through the average amount of money lost per month, on a 7-point scale from 1 (I do not lose) to 7 (more than ¥200,000). A response indicating the lowest expenditure in this regard was allocated 1 point. Responses to “I do not lose” were merged with those to “less than ¥10,000,” with either option assigned 1 point. Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 4 of 14 The Pachinko/Pachi‑Slot Playing Ambivalence Scale (PPAS) Several congresses were held by three psychiatrists and four researchers specializing in psychology, education, neuroscience, and sociology to develop items of the PPAS. All psychiatrists were specialists of addictive disorders. Three researchers were experienced researchers of universities, and one researcher of sociology was also a specialist of statis- tics. During this process, the six-item ambivalence scale for smoking (Lipkus et al. 2001) and other existing ambivalence-related scales were used for reference (Dawn et al. 2014; King and Emmons 1990; Lipkus et al. 2005; Nagano et al. 2001). This six-item ambiva - lence scale for smoking consisted of the following six self-descriptive assessments: (1) “I have strong feelings both for and against smoking”; (2) “I have conflicting thoughts and feelings about smoking; sometimes I think that smoking is good, while at other times I think that it is bad”; (3) “My gut feeling and my thoughts do not seem to agree on whether I should smoke”; (4) “I find myself feeling torn between wanting and not want - ing to smoke”; (5) “My gut feeling about whether to smoke agrees perfectly with what my mind tells me” (a reversed question); and (6) “I have equally strong reasons for want- ing and not wanting to smoke.” Although this scale has good internal consistency and prognosis-predictive ability, some items are abstract, with terms such as “good,” “bad,” and “gut.” Therefore, we created the PPAS, with more concrete and clear expressions and consisting of two factors and nine items, as follows: three items concerning “regret” (e.g. “After losing money playing pachinko/pachi-slot, I wished that I had spent it on some- thing delicious to eat.”) and six items concerning “parallel expectations, emotions, and reasons” (e.g. “When I was playing pachinko or pachi-slot, I felt both happy and dis- tressed or “In my mind, I want to quit playing pachinko/pachi-slot and at the same time, I want to play.”). The rating was on a 4-point scale, as follows: (1) “Not true,” (2) “Maybe not true,” (3) “Maybe true,” and (4) “True.” The total score range was 9–36. Participants were asked to consider the questions regarding their gambling behavior only in the previous 12 months. Factor analysis of the PPAS We conducted an exploratory factor analysis (EFA) of nine items of the PPAS. Because all factors were considered dependent upon each other, the factor solution was sought after Promax rotation, which is an oblique rotation. The number of factors was deter - mined through the scree plot (Cattell 1966). To create subscales of the PPAS, we extracted items for each subscale if they yielded a loading of >0.3 on a particular factor, but of <0.3 on other factors. Thereafter, using maximum likelihood estimation, some factor structures including one derived from the EFA were confirmed through confirmatory factor analysis (CFA) among the same group of 522 participants. The fit of each data model was examined through the goodness of fit index (GFI), adjusted goodness of fit index (AGFI), compara - tive fit index (CFI) and root mean square error of approximation (RMSEA). According to conventional criteria, GFI > 0.9, AGFI > 0.9, CFI > 0.95, and RMSEA < 0.08 indicate an acceptable fit (Schermelleh-Engel et al. 2003). Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 5 of 14 Additionally Cronbach’s alpha for the hypothesized subscales was calculated to exam- ine the internal reliability of the PPAS. The acceptable standards for alpha values are ranging from 0.70 to 0.95. (Tavakol and Denneck 2011). Scales used to test concurrent validity To examine concurrent validity, we used both the general ambivalence and gambling scales. General ambivalence scales The Short Interpersonal Reactions Inventory (SIRI)—Japa - nese version (Grossarth-Maticek and Eysenck 1990; Nagano et al. 2001). This scale is a self-administered scale, with its reliability for use in Japan having been confirmed. Participants were required to answer “Yes”/“No” items related to the “ambiv - alent object-dependent type” characterized by an ambivalent attitude. We selected only the most representative three items to shorten a questionnaire. The items were as fol - lows: “I alternate to a great degree between positive and negative evaluation of people and situations”; “With people I love, I oscillate between them at a great distance to sti- fling dependence, and from stifling dependence to excessive distancing”; “As soon as someone becomes emotionally close to me, I tend to place contradictory demands on them, such as ‘Don’t ever leave me’ and ‘Get away from me.’” The score range for these items was from 3 to 6. Ambivalence over Emotional Expressiveness Questionnaire (AEQ) (King and Emmons 1990).The AEQ is a self-administered scale consisting of 28 items, used to assess ambiva - lence in emotional expressiveness in interpersonal relations. Since there is no Japanese version, the scale’s reliability and validity have not been confirmed for use in Japan. To shorten a questionnaire, we selected the following four items, referring to Cronbach’s alpha, which were rated on a 5-point scale, e.g. 0 (strongly disagree) to 4 (strongly agree): “Often I find that I cannot tell others how much they really mean to me”; “I want to tell someone people when I love them, but it is difficult to find the right words”; “After expressing anger at someone, it bothers me for a long time”; and “I feel guilty after hav- ing expressed anger at someone.” The possible range of the scale scores varied from 0 to Measures of gambling disorder In all of the gambling disorder’s items, the word “gambling” was replaced with the word “pachinko/pachi-slot playing.” The Diagnostic and  Statistical Manual of  mental Disorders‑5 (DSM‑5) Nine items were adapted from the Japanese version of the nine DSM-5 criteria for gambling disor- der (American Psychiatric Association 2013). The original DSM-5 wording was changed to make the items relevant to the questionnaire context and easier for respondents to understand. For example, “In a 12-month period…” became “In the last 12  months….” Moreover, the criteria regarding experiences of emotions and problems were expressed in a “Yes”/”No” question format. Upon scoring, a “Yes” response was assigned one point, so that the total possible score range was 0–9. We used the DSM-5 severity levels and simply Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 6 of 14 translated the number of criteria met into points; in other words, mild severity was 4–5 points, moderate was 6–7 points, and severe was 8–9 points. The South Oaks Gambling Screen (SOGS) We translated 19 of the SOGS’s 20 items (Lesieur and Blume 1987) into Japanese. We omitted translating the item concerning the writing of bad checks to cover gambling debt, as it is not relevant in the Japanese context. The answers were scored on the basis of Lesieur and Blume’s (1987) method. Scores were determined by adding up the number of questions which show an “at risk” response. Nineteen questions were scored 0 or 1. Therefore the score range was 0–19. The Problem Gambling Severity Index (PGSI) The PGSI is a 9-item scale requiring the respondent to think about the past 12 months (Ferris and Wynne 2001), with questions such as, “Have you bet more than you could really afford to lose?,” using a scale of 1 (“never”) to 4 (“almost always”). The score range was 9–36. The Alberta Gaming Research Institute (AGRI) Short Screen The AGRI Short Screen is a 5-item scale requiring the respondent to think about the past 12  months (Volberg and Williams 2011) and reply with “Yes” or “No” to questions such as, “Would you say you have been preoccupied with gambling?” (as adapted for this study). A score of 1 was assigned to each “Yes” answer. The score range was 0–5. A gambling dependency diagnosis status Participants were asked the question, “During the past year, have you ever been told by a medical or treatment support facility that you suffer from gambling dependence?,” to which they were to respond “Yes,” “No,” or “Don’t wish to answer.” A score of 1 was assigned for “Yes,” and 0 for “No”; “Don’t wish to answer” was treated as missing data. The score range was 0–1. Social desirability In order to check for the possibility of responses having been biased by the respondents’ desire for social approval, we included the 12-item Impression Management subscale from the Balanced Inventory of Desirable Responding. Respondents were asked to rate each item (e.g., “I sometimes tell lies if I have to.”) on a scale of 1–4, with 1 indicating “Not true” and 4 indicating “Very true” (Paulhus 1991; Tani 2008). The score range was 12–48. Procedure Data for the initial and retest surveys were collected via self-administered online ques- tionnaires at an interval of approximately two weeks in February 2015. Statistical analysis To determine validity, we observed the correlations between the PPAS and the scales presented in the preceding sub-sections, playing frequency, the gambling dependency diagnosis status, and social desirability by using Pearson’s correlation coefficients. To Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 7 of 14 test for reliability, we observed the correlations between the initial data and the retest data. Significance was set at p < 0.05. Ethics The study procedures were carried out in accordance with the Declaration of Helsinki. The Institutional Review Board of Ochanomizu University approved the study. All sub - jects were informed about the study and all provided informed consent. Participant data were treated as strictly confidential and anonymous. Results Playing frequency and expenditure With regard to playing frequency, 23.2% of the participants played 2–3 times per week, followed by 21.5%, who played 2–3 times per month. Moreover, 21.0% had played ≤4 times within the past year and 5.4% had played ≥4 times per week. Most of the par- ticipants (n = 150, 28.7%) played for 2–3 h, followed by 22.6%, who played for 3–4 h. In total, 8.0% played for ≥6 h. With regard to monthly expenditure, 28.0 and 26.2% of the participants reported losing less than ¥10,000 and ¥20,000–¥50,000, respectively. How- ever, 6.3% reported never losing and 5.3% reported a loss of ¥100,000 or more. PPAS The mean total score (SD) of PPAS was 21.3 (6.25). More “Very true” or “True” responses were given for “regret” (26.4–33.1%), as compared to “paralleling” (5.7–18.2%). EFA The entire log-transformed items of the PPAS were entered into an EFA. This sug - gested a two-factor structure. Factor 1 was loaded by three items (1–3), which expressed “regret” for gambling. Regret is a conflictive reaction after an inconsistent behavior, because feeling regret meant that gamblers recognized that the food, goods, and friend- ship were more important to them than gambling was. Factor 2 was loaded by six items that expressed coexistence of opposite thoughts, feelings and motivations, e.g. “a desire to gamble and a desire to quit gambling”. A two-factor structure was suggested in PPAS (Table 1). CFA Three models were tested. The first model to be examined was a one-factor model in which all nine items were predicted to load onto a single factor generally reflecting the ambivalence of disordered gamblers. The analysis showed that the single-factor solution was not a good fit for the data. All fitted indices were less than the acceptable value of 0.9. The second model to be examined was the two-factor model, which was extracted in the EFA. Although this model was a better fit than the one-factor model, the fit was not adequate, as the AGFI value was less than 0.9. Moreover, the RMSEA value fell outside the accepted value, further suggesting that the two-factor model was not the best fit for the data. Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 8 of 14 Table 1 Exploratory factor analysis (EFA) for the PPAS Please rate these statements thinking about the past 12 months Factor 1 2 1. After losing money playing pachinko or pachi-slot, I wished that I had spent it on 0.947 −0.082 something delicious to eat Regret 2. After losing money playing pachinko or pachi-slot, I wished that I had used it to 0.888 0.03 buy something I wanted 3. After losing money playing pachinko or pachi-slot, I wished that I had used the 0.862 0.006 money to go out with my sweetheart or a friend 4. When I am playing pachinko/pachi-slot, thoughts run through my mind that I −0.026 0.771 could get rich, but also that I could go bankrupt 5. When I am playing pachinko/pachi-slot, thoughts run through my mind that the −0.059 0.749 people I care about might praise me for playing, or that they might reproach me for playing Parallel 6. When I was playing pachinko or pachi-slot, I felt both happy and distressed 0.057 0.749 7. In my mind, I want to quit playing pachinko/pachi-slot and at the same time, I 0.205 0.547 want to play 8. The reason I play pachinko/pachi-slot is to win and also to lose −0.116 0.523 9. The reason I play pachinko/pachi-slot changes with the moment 0.126 0.491 N = 522 (principal component analysis with promax rotation) Italics mean each two factor group. Factor 1 consists of item 1–3, and factor 2 consists of item 4–9 The third model was the four-factor model, which was assumed logically. The par - allel factor, which was one factor of the two-factor model, could be divided into three sub-factors, namely, parallel expectation (items 4–5; e.g. “when I am playing pachinko/ pachi-slot, thoughts run through my mind that I could get rich, but also that I could go bankrupt.”), parallel emotion (items 6–7; e.g. “In my mind, I want to quit plying pachinko/pachi-slot and at the same time, I want to play.”), and parallel reasons (items 8–9; e.g. “The reason I play pachinko/pachi-slot is to win and also to lose.”). The analy - ses showed that this four-factor model was a good fit for the data, as all fit indices were greater than 0.9 (GFI  =  0.967; AGFI  =  0.929; CFI  =  0.975). Furthermore, the RMSEA value was in the accepted range (0.074). Three models were tested and four-factor model was a best fit for the data, as all fit indices were greater than 0.9 Table 2. Reliability Internal consistency (Cronbach’s alpha) Internal consistency coefficients (Cronbach’s alpha) for the overall scale and each factor were as follows: α = 0.87 for the total score, α = 0.92 for “regret,” α = 0.79 for “parallel expectations,” α = 0.80 for “parallel emotions,” and α = 0.48 for “parallel reasons.” Table 2 CFA of the PPAS χ2 Degrees of  GFI AGFI CFI RMSEA freedom 4-factor model 81.058 21 0.967 0.929 0.975 0.074 2-factor model 186.299 26 0.921 0.863 0.934 0.109 1-factor model 713.293 27 0.703 0.505 0.718 0.221 Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 9 of 14 Test–retest reliability (n = 66) Pearson’s correlation coefficients for the initial and retest scores were 0.66 for the total score, 0.62 for “regret,” 0.42 for “parallel expectations,” 0.56 for “parallel emotions,” and 0.50 for “parallel reasons.” All were significant at p < 0.01. Validity Correlations with related scales Scales related to the PPAS showed significant positive correlations with the PPAS and with each of its subscales. Total score and sub score of PPAS correlated with other gambling- and ambivalent- related scales Table 3. Next, we divided the participants into four groups according to the DSM-5 severity score (none, mild, moderate, and severe) and compared the mean PPAS scores across severity groups. For the procedure, we performed a one-way analysis of variance on the means for the four groups and found a significant between-group effect [F(3, 518) = 78.58, p < 0.001]. Differences between the mean values were then assessed using the Bonferroni comparison procedure. The results showed that the scores increased with severity. Mean total score of PPAS correlated with severity assessed by DSM5 Table 4. Correlations with a gambling dependency diagnosis status The correlations of a gambling dependency diagnosis status with the PPAS and its sub - scales were as follows: 0.21 for the total score, 0.09 for “regret,” 0.21 for “parallel expec- tations,” 0.16 for “parallel emotions,” and 0.24 for “parallel reasons.” The correlation for “regret” was significant at p < 0.05, and the rest at p < 0.01. Table 3 The PPAS’s correlations with related scales SIRI AEQ-G SOGS DSM-5 AGRI PGSI Mean total score 0.37 0.43 0.58 0.62 0.54 0.43 Regret 0.18 0.33 0.38 0.4 0.36 0.27 Parallel expectations 0.39 0.32 0.53 0.54 0.46 0.44 Parallel emotions 0.34 0.38 0.58 0.61 0.53 0.43 Parallel reasons 0.27 0.28 0.33 0.41 0.34 0.22 All correlation coefficients were significant at p < 0.01 Table 4 A comparison of PPAS total scores by DSM5-severity group Severity N Mean SD SE Mean at 95% CI Mnimum Maximum classification value value Lower limit Upper limit None 349 18.9a 5.66 0.303 18.3 19.5 9 36 Mild 84 25.4b 3.98 0.435 24.5 26.2 12 34 Moderate 57 25.8bc 3.91 0.518 24.8 26.8 18 36 Severe 32 28.7c 4.62 0.816 27 30.4 18 36 Total 522 21.3 6.25 0.274 20.7 21.8 9 36 Means followed by the same letter do not differ significantly (p = 0.05) Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 10 of 14 Correlations with playing frequency and expenditure (convergent validity) There were significant positive correlations (p < 0.01) between the total PPAS score and “frequency” (0.20), “playing duration” (0.17), and “money lost” (0.37). Discriminant validity Correlations with the social desirability scale Significant negative correlations (p < 0.01) were found between social desirability and the total PPAS score (−0.30), “regret” (−0.20), “parallel expectations (−0.33), “parallel emotions” (−0.22), and “parallel reasons” (−0.18). Correlations with demographic factors No significant differences were found in the total PPAS score according gender, education level (higher or lower than college-graduate level) and family structure (single or not single). Similarly, no significant results were found for the correlation between household income and the total PPAS and subscale scores. Significant negative correlations were found between age group and the total PPAS score and each sub score (p < 0.05). No significant differences were found in the total PPAS score according gender Table  5. No significant differences were found in the total PPAS score according education level Table 6. No significant differences were found in the total PPAS score according family struc - ture Table 7. Significant negative correlations were found between age group and the PPAS score (p  <  0.05). On the other hand, no significant results for the correlation were found between household income and the PPAS Table 8. Discussion The PPAS’s reliability The scale’s reliability was confirmed. Despite the low Cronbach’s alpha value for “parallel reasons,” at 0.48, those for the total scores and other three factors’ scores were 0.79–0.92, Table 5 The PPAS’s difference concerning demographic factors (gender) t-test/mean score Male (n = 446) Female (n = 76) Total 21.4 20.4 Regret 8.48 8.24 Parallel expectations 3.79 3.63 Parallel emotions 4.79 4.53 Parallel reasons 4.37 4.04 Table 6 The PPAS’s difference concerning demographic factors (education) t-test/mean score Over colleage (n = 404) Under high school (n = 118) Total 21.3 21.2 Regret 8.48 8.31 Parallel expectations 3.76 3.79 Parallel emotions 4.74 4.79 Parallel reasons 4.31 4.34 Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 11 of 14 Table 7 The PPAS’s difference concerning demographic factors (family structure) t-test With a family (n = 380) Single (n = 142) Total score 21.1 21.8 Regret 8.33 8.74 Parallel expectations 3.69 3.96 Parallel emotions 4.74 4.78 Parallel reasons 4.31 4.33 demonstrating the scale’s high internal consistency. Moreover, the test–retest correlation coefficients were 0.64 for the overall scale and between 0.42 and 0.62 for the subscales. Regarding parallel reasons, item 9 has a wider concept beyond ambivalence. Namely, changing the reason is not always associated with ambivalent attitude. Therefore the fac - tor “parallel reasons” demonstrated the relative low internal consistency. The PPAS’s validity Construct validity Results revealed that the four factors model reflected the classical distinctions drawn by Bleuler in defining regret. Concurrent validity There were significant positive correlations (0.37–0.62) between the total PPAS score and those of the related general scales (SIRI, AEQ) and gambling scales (SOGS, DSM-5, AGRI Short Screen, PGSI). Moreover, the correlations for the parallel factors tended to be higher than those for the regret factor. Additionally, there were small but significant positive correlations between the gambling dependency diagnosis status and the PPAS’s total score and its paralleling-factor scores. Thus, the PPAS’s concurrent validity was confirmed. Convergent validity The PPAS scores showed small to medium positive correlations with playing frequency and expenditure. In particular, stronger correlations were observed with money lost than with playing frequency. This confirmed the PPAS’s convergent validity. This may reflect ambivalent gambling leads to the unintentional repetitive incurrence of losses. Table 8 The PPAS’s correlations with  demographic factors (household income and  age group) Correlation test Household income Age group* Total score −0.05 −0.2 Regret −0.04 −0.15 Parallel expectations −0.08 −0.3 Parallel emotions −0.05 −0.09 Parallel reasons −0.01 −0.09 * Significant correlation: p < 0.05 Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 12 of 14 Discriminant validity No significant correlation was found between PPAS scores and demographic factors, except being younger. This may be a reflection of the instability in the self-identity of young people. For that reason, when researching young people, one needs to be cautious about their overestimation of themselves. Meanwhile, a negative correlation with social desirability was found. A possible explanation for these results is that ambivalent peo- ple are susceptible to anxiety because they become introspective in response to reality. To avoid anxiety, a denial mechanism serves to protect them from a negative self-image and, as a result, they tend to answer based on unrealistic images of themselves. In sum, some of the responses to the scale may be biased. On the other hand, similar results have been reported for the SOGS, suggesting that this may be a limitation of self-adminis- tered scales (Kuentzel et al. 2008). Therefore, depending on the situation, use of a social desirability scale may be necessary when using the PPAS. The utility of the PPAS While this study showed that some caution may be required when using the PPAS, its reliability and validity were ascertained. Further, the PPAS’s scores showed that the degree of ambivalence correlated with the scores of the DSM5 as the comprehensive severity-assessment scale. Therefore, this study revealed that ambivalence as measured by the PPAS may reflect a core aspect of the condition of a gambling disorder patient. Namely, the PPAS can be considered a useful measure for the assessment for gambling disorders. Limitations and suggestions for further research The recruitment of participants for this study was limited to people registered with an online survey company. As a result, the sample may have been biased and not repre- sentative of the general population of pachinko or pachi-slot players in Japan. However, the study’s sample may be considered appropriate, overall, because it consisted mainly of married, middle-class, middle-aged men, which is consistent with the characteristics of most Japanese people who are diagnosed with gambling disorder (Komoto 2014; Toyama et al. 2014). Moreover, participation was limited to people who had played pachinko or pachi-slot only within the previous year. Next, we selected PPAS’s items by not statistic method but specialists’ conferences. As result, inclusion criteria of scale items somewhat became arbitrary. Additionally, to better understand the efficacy of ambivalence to pre - dict prognosis, longitudinal studies are needed. While acknowledging these limitations, the further development and validation of this ambivalence scale for gambling disorder, for use in clinical settings, is recommended. Abbreviations AEQ: Ambivalence over Emotional Expressiveness Questionnaire; AGFI: adjusted goodness of fit index; AGRI: Alberta Gaming Research Institute; AIC: Akaike Information Criterion; CFI: comparative fit index; DSM-5: Diagnostic and Statistical Manual of Mental Disorders-5; GFI: goodness of fit index; G-SAS: Gambling Symptom Assessment Scale; PGSI: Problem Gambling Severity Index; PG-YBOCS: Yale-Brown Obsessive Compulsive Scale-modified for Pathological Gambling; PPAS: Pachinko/Pachi-Slot Playing Ambivalence Scale; RMSEA: root mean square error of approximation; SIRI: Short Interper- sonal Reactions Inventory; SOGS: South Oaks Gambling Screen. Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 13 of 14 Authors’ contributions All authors designed the study, had advises during the study and reviewed the completed manuscript. YK proposed the study concept and wrote the manuscript. HI monitored data collection. KA and Ash performed the statistical analysis. All authors read and approved the final manuscript. Author details 1 2 Yoshino Hospital, 2252, Zushi-tyo, Machida City, Tokyo 1940203, Japan. Graduate School of Humanities and Sciences, 3 4 Ochanomizu University, Bunkyō, Japan. The Nikkoso Research Foundation for Safe Society, Tokyo, Japan. Department 5 6 of Psychology, Ochanomizu University, Bunkyō, Japan. Naruse Mental Clinic, Machida City, Japan. NPO Recovery 7 8 Support Network, Tokyo, Japan. Tokyo University of Science Suwa, Chino, Japan. Japan Women’s University, Kawasaki, Japan. Competing interests Kikunori Shinohara is on the board of trustees of Nichiyukyo (Japan Pachinko Pachi-Slot industry association). Consent for publication and availability of data and materials All subjects were informed about the study and all provided informed consent. Participant data were treated as strictly confidential and anonymous. Ethical approval and consent to participate This study was approved by the Ethical Review Board for Research in the Humanities at Ochanomizu University (Approval No. 2014-106). Funding sources This study is wholly funded by the Nikkoso Research Foundation for a Safe Society. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Received: 3 September 2016 Accepted: 3 May 2017 References American Psychiatric Association (APA). (2013). Substance-related and addictive disorders: Gambling Disorder. Diagnostic and statistical manual of mental disorders fifth edition (DSM-5) (pp. 585–589). Washington, DC: American Psychiatric Publishing. Armitage, C. J. (2003). Beyond attitudinal ambivalence: Eec ff ts of belief homogeneity on attitude–intention–behavior relations. European Journal of Social Psychology, 33(4), 551–563. Bleuler, E. (1914/1997). Die Ambivalenz [Ambivalence]. In K. Hitomi (Ed.), Selected writings of Eugen Bleuler (pp. 135–157). (K. Hitomi, Trans.). Tokyo: Gakuju Shoin. Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1(2), 245–276. Conner, M., & Sparks, P. (2002). Ambivalence and attitudes. European Review of Social Psychology, 70, 141–156. Dawn, W. F., Clayton, N., & Alexander, P. (2014). Drinking motives as moderators of the effect of ambivalence on drinking and alcohol-related problems. Addictive Behavior, 39(1), 133–139. Ferris, J., & Wynne, H. (2001). The Canadian problem gambling index (Final report). https://www.problemgambling.ca/EN/ Documents/ProblemGamblingSeverityIndex.pdf. Accessed August 18, 2016. Gowing, L. R., Ali, R. L., Allsop, S., Marsden, J., Turf, E. E., West, R., et al. (2015). Global statistics on addictive behaviours: 2014 status report. Addiction. doi:10.1111/add.12899. Grant, J. E., Schreiber, L., Odlaug, B. L., & Kim, S. W. (2010). Pathological gambling and bankruptcy. Comprehensive Psychia- try, 51(2), 115–120. doi:10.1016/j.comppsych.2009.04.002. Grossarth-Maticek, R., & Eysenck, H. J. (1990). Personality, stress and disease: Description and validation of a new inven- tory. Psychological Reports, 66(2), 355–373. Hitomi, K. (2011). Ambivalence. Bulletin of Center for Clinical Psychology Kinki University, 4, 133–136. (in Japanese). Johnson, E. E., Hamer, R., Nora, R. M., Tan, B., Eisenstein, N., & Engelhart, C. (1997). The Lie/Bet Questionnaire for screening pathological gamblers. Psychological Reports, 80(1), 83–88. Kim, S. W., Grant, J. E., Potenza, M. N., Blanco, C., & Hollander, E. (2009). The Gambling Symptom Assessment Scale (G-SAS): A reliability and validity study. Psychiatry Research, 166(1), 76–84. doi:10.1016/j.psychres.2007.11.008. King, L. A., & Emmons, R. A. (1990). Conflict over emotional expression: Psychological and physical correlates. Journal of Personality and Social Psychology, 58(5), 864–877. doi:10.1037/0022-3514.58.5.864. Komoto, Y. (2014). Factors associated with suicide and bankruptcy in Japanese pathological gamblers. International Journal of Mental Health and Addiction, 12(5), 600–606. doi:10.1007/s11469-014-9492-3. Komoto, Y., & Sato, T. (2014). Desire model for gambling disorder. Seishin Igaku, 56(7), 625–635. (in Japanese). Kuentzel, J. G., Henderson, M. J., & Melville, C. L. (2008). The impact of social desirability biases on self-report among col- lege student and problem gamblers. Journal of Gambling Studies, 24(3), 307–319. doi:10.1007/s10899-008-9094-8. Lesieur, H. R., & Blume, S. B. (1987). The South Oaks Gambling Screen (SOGS): A new instrument for the identification of pathological gamblers. American Journal of Psychiatry, 144(9), 1184–1188. Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 14 of 14 Lipkus, I. M., Green, J. D., Feaganes, J. R., & Sedikides, C. (2001). The relationship between attitudinal ambivalence and desire to quit smoking among college smokers. Journal of Applied Social Psychology, 31(1), 113–133. doi:10.1111/j.1559-1816.2001.tb02485.x. Lipkus, I. M., Pollak, K. I., McBride, C. M., Schwartz-Bloom, R., Lyna, P., & Bloom, P. N. (2005). Assessing attitudinal ambiva- lence towards smoking and its association with desire to quit among teen smokers. Psychology and Health, 20(3), 373–387. doi:10.1080/08870440512331333988. Menninga, K. M., Dijkstra, A., & Gebhardt, W. A. (2011). Mixed feelings: Ambivalence as a predictor of relapse in ex-smok- ers. British Journal of Health Psychology, 16(3), 580–591. doi:10.1348/135910710X533219. Nagano, J., Sudo, N., Kubo, T., & Kono, S. (2001). Psychometric reliability and validity of a Japanese Version of the Short Interpersonal Reactions Inventory. Japanese Journal of Behavioral Medicine, 7(2), 104–116. (in Japanese). Oser, M. L., McKellar, J., Moos, B. S., & Moos, R. H. (2010). Changes in ambivalence mediate the relation between entering treatment and change in alcohol use and problems. Addictive Behaviors, 35(4), 367–369. doi:10.1016/j. addbeh.2009.10.024. Pallanti, S., DeCaria, C. M., Grant, J. E., Urpe, M., & Hollander, E. (2005). Reliability and validity of the pathological gambling adaptation of the Yale-Brown Obsessive-Compulsive Scale (PG-YBOCS). Journal of Gambling Studies, 21(4), 431–443. Paulhus, D. L. (1991). Measurement and control of response bias. In J. P. Robinson, P. R. Shaver, & L. S. Wrightsman (Eds.), Measures of personality and social psychological attitudes (pp. 17–59). New York: Academic Press. Petry, N. M., & Kiluk, B. D. (2002). Suicidal ideation and suicide attempts in treatment-seeking pathological gamblers. Journal of Nervous and Mental Disease, 190(7), 462–469. Priester, J. R., & Petty, R. E. (1996). The gradual threshold model of ambivalence: Relating the positive and nega- tive bases of attitude to subjective ambivalence. Journal of Personality and Social Psychology, 71(3), 431–449. doi:10.1037/0022-3514.71.3.431. Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Test of significance and descriptive goodness-of-fit-measures. Methods of Psychological Research Online, 8(2), 23–74. Dis- ponible en http://www.mpr-online.de. Steenbergh, T. A., Meyers, A. W., May, R. K., & Whelan, J. P. (2002). Development and validation of the Gamblers’ Beliefs Questionnaire. Psychology of Addictive Behaviors, 16(2), 143–149. Stinchfield, R. (2013). A review of problem gambling assessment instruments and brief screens. In D. C. S. Richard, A. Blaszczynski, & L. Nower (Eds.), The Wiley-Blackwell handbook of disordered gambling (pp. 165–203). Hoboken: John. Tani, I. (2008). Development of Japanese Version of Balanced Inventory of Desirable Responding (BIDR-J ). The Japanese Journal of Personality, 17(1), 18–28. (in Japanese). Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education., 2, 53–55. doi:10.5116/ijme.4dfb.8dfd. Thompson, M. M., Zanna, M. P., & Griffin, D. W. (1995). Let’s not be indifferent about (attitudinal) ambivalence. In R. E. Petty & J. A. Krosnick (Eds.), Attitude strength: Antecedents and consequences ( Vol. 4, pp. 361–386). Hillsdate, NJ: Erlbaum. Toyama, T., Nakayama, H., Takimura, T., Yoshimura, A., & Higuchi, S. (2014). Prevalence of pathological gambling in Japan: Results of national surveys of the general adult population in 2008 and 2013. Alcohol and Alcoholism, 49(suppl 1), i17. Volberg, R. A., & Williams, R. J. (2011). Developing a brief problem gambling screen using clinically validated samples of at-risk, problem and pathological gamblers. Edmonton: Alberta Gaming Research Institute. Walker, D., Stephens, R., Rowland, J., & Roffman, R. (2011). The influence of client behavior during motivational interview- ing on marijuana treatment outcome. Addictive Behaviors, 36(6), 669–673. doi:10.1016/j.addbeh.2011.01.009. Weatherly, J. N., Miller, J. C., & Terrell, H. K. (2011). Testing the construct validity of the gambling functional assessment— Revised. Behavior Modification, 35(6), 553–569. doi:10.1177/0145445511416635. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Asian Journal of Gambling Issues and Public Health Springer Journals

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Social Sciences; Social Sciences, general; Quality of Life Research; Sociology, general; Public Health; Psychology, general; Social Work and Community Development
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Abstract

aria11832013@yahoo.co.jp Yoshino Hospital, 2252, Background: A scale aimed at measuring ambivalence among people with Zushi-tyo, Machida City, pachinko/pachi-slot playing disorder, the Pachinko/Pachi-Slot Playing Ambivalence Tokyo 1940203, Japan Full list of author information Scale (PPAS), was developed and its reliability and validity ascertained. is available at the end of the Methods: A total of 522 participants (average year: 48.0) who were residing in Tokyo article Metropolitan Area, and had played pachinko within the previous year completed ques- tions relating to demographics, four gambling-related scales (including South Oaks Gambling Screen) and two general ambivalence scales (including Ambivalence over Emotional Expressiveness Questionnaire). Results: Internal consistency (α = 0.87) and test–retest reliability (r = 0.66) were con- firmed. The PPAS’s score was associated with each related scale’s score (r = 0.37–0.62). Conclusions: The PPAS was shown to be consistent with previous scales and useful in clinical settings. Keywords: Gambling disorder, Pachinko/pachi-slot playing disorder, Ambivalence scale, DSM5, Severity Background The lifetime prevalence of gambling disorders around the world has been reported to be about 1.5% (Gowing et  al. 2015), similar to that of schizophrenia and bipolar disorder. Not only gambling disorder promotes depression and suicide (Petry and Kiluk 2002), but it has been linked to social problems such as child abuse and severe indebtedness (Grant et al. 2010). Therefore, the development of intervention guidelines based on appropriate diagnostic and assessment measures has become a pressing issue. Existing gambling disorder assessment scales can broadly be divided into: (a) scales for evaluating treatment effectiveness by measuring principal symptoms such as a craving and (b) diagnostic scales providing a comprehensive assessment of problems; for exam- ple, in cognition, behavior, and interpersonal relationships. The former type includes the Gambling Symptom Assessment Scale (G-SAS) (Kim et  al. 2009) and the Yale-Brown Obsessive Compulsive Scale-modified for Pathological Gambling (PG-YBOCS) (Pallanti et al. 2005). The latter type includes assessment instruments such as the Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) (American Psychiatric Association 2013), the South Oaks Gambling Screen (SOGS) (Lesieur and Blume 1987), the Alberta © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 2 of 14 Gaming Research Institute (AGRI) Short Version (Volberg and Williams 2011), the Prob- lem Gambling Severity Index (PGSI) (Ferris and Wynne 2001), and the Lie–Bet Screen (Johnson et al. 1997). These diagnostic scales (b) enable assessment of problem severity, based on several different pathological concepts in a given case. In other words, these scales focus not on a single pathological concept but on multiple pathological concepts such as psychopharmacology of substance use disorder, psychodynamics, and interper- sonal model (Stinchfield 2013). For example, the nine items of DSM5 consist of four different pathological concepts, namely psychopharmacology, psychodynamics, inter - personal and socio-economics model. Similarly, Lie–Bet Screen consists of two con- cepts, interpersonal model and psychopharmacology. On the other hands, scales, which focus on a single pathological concept, have been developed. For example, the Gambling Functional Assessment-Revised measures psychopharmacological dependency, namely positive and negative reinforcement such as resistance and withdrawal (Weatherly et al. 2011); whereas Gamblers’ Beliefs Questionnaire measures cognitive distortions such as neglecting of randomness (Steenbergh et al. 2002). Although various useful scales for gambling disorders have been developed, it is not clear if these scale measure core symptoms that explain the basic mechanism of gam- bling disorder. The importance of the concept of ambivalence, being that “alcoholics simultaneously want to quit and do not want to quit,” has been raised in substance addiction research (Walker et  al. 2011), because it has been found to be a predictor of relapse in drink- ing behavior (including heavy drinking) and drug abuse (Lipkus et  al. 2001; Oser et  al. 2010), and of relapse in ex-smokers (Menninga et  al. 2011). Additionally, ambivalence regarding alcoholism is an important determinant of drinking behavior in the same way that craving for alcohol is (Dawn et al. 2014). In many instances, ambivalence acts as an inhibitory factor in recovery (Armitage 2003). Bleuler, who first coined the concept of ambivalence, encompassed two different ideas. He pointed out that ambivalence can be a symptom of pathology because two oppo- site psychological phenomena continue to exist in parallel, or it can have the common meaning of tying different psychological phenomena together via consistent values (Bleuler 1914/1997; Hitomi 2011). Therefore, in the assessment of ambivalence, these two aspects must be covered. The former is a psychopathological finding, which reveals failure of solution to conflicts, such as “parallel existence of expectation, emotion, and reason” (Bleuler 1914/1997, p. 136). On the other hand, the latter reveals a self-oriented, rational response after conflictive behaviors, such as regret. When assessing ambivalence, one either assesses structural ambivalence by differen - tiating and measuring two conflicting factors such as feelings, thoughts and behaviors, or subjective ambivalence by assessing the psychological state that arises when two conflicting factors coexist (Priester and Petty 1996). For example, Drinking Ambiva - lence Scale (DAS) (Dawn et  al. 2014) measures structural ambivalence; whereas, General Ambivalence Scale (Thompson et  al. 1995) and a six-item ambivalence scale for smoking (Lipkus et  al. 2001) focus on subjective ambivalence. However, Conner and Sparks (2002) report there is a significant correlation between two assessment methods. Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 3 of 14 Currently, no scale has been developed for this concept in gambling. Thus, in this study, we developed a scale to measure ambivalence towards gambling behavior. In Japan, pachinko/pachi-slot playing disorder accounts for nearly 90% of all gambling dis- orders (Toyama et  al. 2014; Komoto 2014). Pachinko and pachi-slot constitute private gambling involving use of a device similar to a recreational arcade game. There are many pachinko/pachi-slot parlors in every downtown area in Japan. Therefore, we first devel - oped the Pachinko/Pachi-Slot Playing Ambivalence Scale (PPAS), and tested its reliabil- ity and validity. Improving classification (severity/subtype) and prediction of prognosis are not the only reasons for the incorporation of ambivalence into the diagnosis and treatment of gambling disorder. A better understanding of ambivalence by those pro- viding support to people with gambling disorders may enhance their understanding of the recovery process that may face frequent relapses. In addition, for the gambler, better understanding could provide an opportunity to think about the cravings that drive his/ her urge to gamble (Komoto and Sato 2014). Methods Participants Initial survey Using an online survey company, we recruited members registered as internet-shopping customers residing in Tokyo, in Saitama, Chiba, or in Kanagawa Prefectures, who had played pachinko or pachi-slot within the previous year. A total of 522 people agreed to participate in the survey, comprising the ambivalence scale and an impression manage- ment subscale (Paulhus 1991). Of the 522 participants, 446 (85.4%) were men and most were in their 40 s (35.8%) or 50  s (28.0%). The majority of the participants were individuals who had at least gradu - ated from college (77.4%), lived with a family (not be single) (72.8%), and had an annual household income of ¥4–10 million (60.4%; the so-called “middle economical class” in Japan). Retest survey We used the same online survey company and asked the 522 from the initial survey to participate again in the survey. Sixty-six participants (12.6%) of the original sample (n = 522) agreed to answer the retest questionnaire. Measures Playing frequency, duration, and expenditure The frequency of playing pachinko/pachi-slot and expenditure (i.e., “money lost”) over the previous 12  months were measured. Responses regarding frequency were rated on a 9-point scale from 1 (less than once a year) to 9 (more than 4 times a week). Playing duration was measured through average playing duration per day, on an 8-point scale, from 1 (less than 1 h) to 8 (8 h or more). Expenditure on playing was measured through the average amount of money lost per month, on a 7-point scale from 1 (I do not lose) to 7 (more than ¥200,000). A response indicating the lowest expenditure in this regard was allocated 1 point. Responses to “I do not lose” were merged with those to “less than ¥10,000,” with either option assigned 1 point. Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 4 of 14 The Pachinko/Pachi‑Slot Playing Ambivalence Scale (PPAS) Several congresses were held by three psychiatrists and four researchers specializing in psychology, education, neuroscience, and sociology to develop items of the PPAS. All psychiatrists were specialists of addictive disorders. Three researchers were experienced researchers of universities, and one researcher of sociology was also a specialist of statis- tics. During this process, the six-item ambivalence scale for smoking (Lipkus et al. 2001) and other existing ambivalence-related scales were used for reference (Dawn et al. 2014; King and Emmons 1990; Lipkus et al. 2005; Nagano et al. 2001). This six-item ambiva - lence scale for smoking consisted of the following six self-descriptive assessments: (1) “I have strong feelings both for and against smoking”; (2) “I have conflicting thoughts and feelings about smoking; sometimes I think that smoking is good, while at other times I think that it is bad”; (3) “My gut feeling and my thoughts do not seem to agree on whether I should smoke”; (4) “I find myself feeling torn between wanting and not want - ing to smoke”; (5) “My gut feeling about whether to smoke agrees perfectly with what my mind tells me” (a reversed question); and (6) “I have equally strong reasons for want- ing and not wanting to smoke.” Although this scale has good internal consistency and prognosis-predictive ability, some items are abstract, with terms such as “good,” “bad,” and “gut.” Therefore, we created the PPAS, with more concrete and clear expressions and consisting of two factors and nine items, as follows: three items concerning “regret” (e.g. “After losing money playing pachinko/pachi-slot, I wished that I had spent it on some- thing delicious to eat.”) and six items concerning “parallel expectations, emotions, and reasons” (e.g. “When I was playing pachinko or pachi-slot, I felt both happy and dis- tressed or “In my mind, I want to quit playing pachinko/pachi-slot and at the same time, I want to play.”). The rating was on a 4-point scale, as follows: (1) “Not true,” (2) “Maybe not true,” (3) “Maybe true,” and (4) “True.” The total score range was 9–36. Participants were asked to consider the questions regarding their gambling behavior only in the previous 12 months. Factor analysis of the PPAS We conducted an exploratory factor analysis (EFA) of nine items of the PPAS. Because all factors were considered dependent upon each other, the factor solution was sought after Promax rotation, which is an oblique rotation. The number of factors was deter - mined through the scree plot (Cattell 1966). To create subscales of the PPAS, we extracted items for each subscale if they yielded a loading of >0.3 on a particular factor, but of <0.3 on other factors. Thereafter, using maximum likelihood estimation, some factor structures including one derived from the EFA were confirmed through confirmatory factor analysis (CFA) among the same group of 522 participants. The fit of each data model was examined through the goodness of fit index (GFI), adjusted goodness of fit index (AGFI), compara - tive fit index (CFI) and root mean square error of approximation (RMSEA). According to conventional criteria, GFI > 0.9, AGFI > 0.9, CFI > 0.95, and RMSEA < 0.08 indicate an acceptable fit (Schermelleh-Engel et al. 2003). Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 5 of 14 Additionally Cronbach’s alpha for the hypothesized subscales was calculated to exam- ine the internal reliability of the PPAS. The acceptable standards for alpha values are ranging from 0.70 to 0.95. (Tavakol and Denneck 2011). Scales used to test concurrent validity To examine concurrent validity, we used both the general ambivalence and gambling scales. General ambivalence scales The Short Interpersonal Reactions Inventory (SIRI)—Japa - nese version (Grossarth-Maticek and Eysenck 1990; Nagano et al. 2001). This scale is a self-administered scale, with its reliability for use in Japan having been confirmed. Participants were required to answer “Yes”/“No” items related to the “ambiv - alent object-dependent type” characterized by an ambivalent attitude. We selected only the most representative three items to shorten a questionnaire. The items were as fol - lows: “I alternate to a great degree between positive and negative evaluation of people and situations”; “With people I love, I oscillate between them at a great distance to sti- fling dependence, and from stifling dependence to excessive distancing”; “As soon as someone becomes emotionally close to me, I tend to place contradictory demands on them, such as ‘Don’t ever leave me’ and ‘Get away from me.’” The score range for these items was from 3 to 6. Ambivalence over Emotional Expressiveness Questionnaire (AEQ) (King and Emmons 1990).The AEQ is a self-administered scale consisting of 28 items, used to assess ambiva - lence in emotional expressiveness in interpersonal relations. Since there is no Japanese version, the scale’s reliability and validity have not been confirmed for use in Japan. To shorten a questionnaire, we selected the following four items, referring to Cronbach’s alpha, which were rated on a 5-point scale, e.g. 0 (strongly disagree) to 4 (strongly agree): “Often I find that I cannot tell others how much they really mean to me”; “I want to tell someone people when I love them, but it is difficult to find the right words”; “After expressing anger at someone, it bothers me for a long time”; and “I feel guilty after hav- ing expressed anger at someone.” The possible range of the scale scores varied from 0 to Measures of gambling disorder In all of the gambling disorder’s items, the word “gambling” was replaced with the word “pachinko/pachi-slot playing.” The Diagnostic and  Statistical Manual of  mental Disorders‑5 (DSM‑5) Nine items were adapted from the Japanese version of the nine DSM-5 criteria for gambling disor- der (American Psychiatric Association 2013). The original DSM-5 wording was changed to make the items relevant to the questionnaire context and easier for respondents to understand. For example, “In a 12-month period…” became “In the last 12  months….” Moreover, the criteria regarding experiences of emotions and problems were expressed in a “Yes”/”No” question format. Upon scoring, a “Yes” response was assigned one point, so that the total possible score range was 0–9. We used the DSM-5 severity levels and simply Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 6 of 14 translated the number of criteria met into points; in other words, mild severity was 4–5 points, moderate was 6–7 points, and severe was 8–9 points. The South Oaks Gambling Screen (SOGS) We translated 19 of the SOGS’s 20 items (Lesieur and Blume 1987) into Japanese. We omitted translating the item concerning the writing of bad checks to cover gambling debt, as it is not relevant in the Japanese context. The answers were scored on the basis of Lesieur and Blume’s (1987) method. Scores were determined by adding up the number of questions which show an “at risk” response. Nineteen questions were scored 0 or 1. Therefore the score range was 0–19. The Problem Gambling Severity Index (PGSI) The PGSI is a 9-item scale requiring the respondent to think about the past 12 months (Ferris and Wynne 2001), with questions such as, “Have you bet more than you could really afford to lose?,” using a scale of 1 (“never”) to 4 (“almost always”). The score range was 9–36. The Alberta Gaming Research Institute (AGRI) Short Screen The AGRI Short Screen is a 5-item scale requiring the respondent to think about the past 12  months (Volberg and Williams 2011) and reply with “Yes” or “No” to questions such as, “Would you say you have been preoccupied with gambling?” (as adapted for this study). A score of 1 was assigned to each “Yes” answer. The score range was 0–5. A gambling dependency diagnosis status Participants were asked the question, “During the past year, have you ever been told by a medical or treatment support facility that you suffer from gambling dependence?,” to which they were to respond “Yes,” “No,” or “Don’t wish to answer.” A score of 1 was assigned for “Yes,” and 0 for “No”; “Don’t wish to answer” was treated as missing data. The score range was 0–1. Social desirability In order to check for the possibility of responses having been biased by the respondents’ desire for social approval, we included the 12-item Impression Management subscale from the Balanced Inventory of Desirable Responding. Respondents were asked to rate each item (e.g., “I sometimes tell lies if I have to.”) on a scale of 1–4, with 1 indicating “Not true” and 4 indicating “Very true” (Paulhus 1991; Tani 2008). The score range was 12–48. Procedure Data for the initial and retest surveys were collected via self-administered online ques- tionnaires at an interval of approximately two weeks in February 2015. Statistical analysis To determine validity, we observed the correlations between the PPAS and the scales presented in the preceding sub-sections, playing frequency, the gambling dependency diagnosis status, and social desirability by using Pearson’s correlation coefficients. To Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 7 of 14 test for reliability, we observed the correlations between the initial data and the retest data. Significance was set at p < 0.05. Ethics The study procedures were carried out in accordance with the Declaration of Helsinki. The Institutional Review Board of Ochanomizu University approved the study. All sub - jects were informed about the study and all provided informed consent. Participant data were treated as strictly confidential and anonymous. Results Playing frequency and expenditure With regard to playing frequency, 23.2% of the participants played 2–3 times per week, followed by 21.5%, who played 2–3 times per month. Moreover, 21.0% had played ≤4 times within the past year and 5.4% had played ≥4 times per week. Most of the par- ticipants (n = 150, 28.7%) played for 2–3 h, followed by 22.6%, who played for 3–4 h. In total, 8.0% played for ≥6 h. With regard to monthly expenditure, 28.0 and 26.2% of the participants reported losing less than ¥10,000 and ¥20,000–¥50,000, respectively. How- ever, 6.3% reported never losing and 5.3% reported a loss of ¥100,000 or more. PPAS The mean total score (SD) of PPAS was 21.3 (6.25). More “Very true” or “True” responses were given for “regret” (26.4–33.1%), as compared to “paralleling” (5.7–18.2%). EFA The entire log-transformed items of the PPAS were entered into an EFA. This sug - gested a two-factor structure. Factor 1 was loaded by three items (1–3), which expressed “regret” for gambling. Regret is a conflictive reaction after an inconsistent behavior, because feeling regret meant that gamblers recognized that the food, goods, and friend- ship were more important to them than gambling was. Factor 2 was loaded by six items that expressed coexistence of opposite thoughts, feelings and motivations, e.g. “a desire to gamble and a desire to quit gambling”. A two-factor structure was suggested in PPAS (Table 1). CFA Three models were tested. The first model to be examined was a one-factor model in which all nine items were predicted to load onto a single factor generally reflecting the ambivalence of disordered gamblers. The analysis showed that the single-factor solution was not a good fit for the data. All fitted indices were less than the acceptable value of 0.9. The second model to be examined was the two-factor model, which was extracted in the EFA. Although this model was a better fit than the one-factor model, the fit was not adequate, as the AGFI value was less than 0.9. Moreover, the RMSEA value fell outside the accepted value, further suggesting that the two-factor model was not the best fit for the data. Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 8 of 14 Table 1 Exploratory factor analysis (EFA) for the PPAS Please rate these statements thinking about the past 12 months Factor 1 2 1. After losing money playing pachinko or pachi-slot, I wished that I had spent it on 0.947 −0.082 something delicious to eat Regret 2. After losing money playing pachinko or pachi-slot, I wished that I had used it to 0.888 0.03 buy something I wanted 3. After losing money playing pachinko or pachi-slot, I wished that I had used the 0.862 0.006 money to go out with my sweetheart or a friend 4. When I am playing pachinko/pachi-slot, thoughts run through my mind that I −0.026 0.771 could get rich, but also that I could go bankrupt 5. When I am playing pachinko/pachi-slot, thoughts run through my mind that the −0.059 0.749 people I care about might praise me for playing, or that they might reproach me for playing Parallel 6. When I was playing pachinko or pachi-slot, I felt both happy and distressed 0.057 0.749 7. In my mind, I want to quit playing pachinko/pachi-slot and at the same time, I 0.205 0.547 want to play 8. The reason I play pachinko/pachi-slot is to win and also to lose −0.116 0.523 9. The reason I play pachinko/pachi-slot changes with the moment 0.126 0.491 N = 522 (principal component analysis with promax rotation) Italics mean each two factor group. Factor 1 consists of item 1–3, and factor 2 consists of item 4–9 The third model was the four-factor model, which was assumed logically. The par - allel factor, which was one factor of the two-factor model, could be divided into three sub-factors, namely, parallel expectation (items 4–5; e.g. “when I am playing pachinko/ pachi-slot, thoughts run through my mind that I could get rich, but also that I could go bankrupt.”), parallel emotion (items 6–7; e.g. “In my mind, I want to quit plying pachinko/pachi-slot and at the same time, I want to play.”), and parallel reasons (items 8–9; e.g. “The reason I play pachinko/pachi-slot is to win and also to lose.”). The analy - ses showed that this four-factor model was a good fit for the data, as all fit indices were greater than 0.9 (GFI  =  0.967; AGFI  =  0.929; CFI  =  0.975). Furthermore, the RMSEA value was in the accepted range (0.074). Three models were tested and four-factor model was a best fit for the data, as all fit indices were greater than 0.9 Table 2. Reliability Internal consistency (Cronbach’s alpha) Internal consistency coefficients (Cronbach’s alpha) for the overall scale and each factor were as follows: α = 0.87 for the total score, α = 0.92 for “regret,” α = 0.79 for “parallel expectations,” α = 0.80 for “parallel emotions,” and α = 0.48 for “parallel reasons.” Table 2 CFA of the PPAS χ2 Degrees of  GFI AGFI CFI RMSEA freedom 4-factor model 81.058 21 0.967 0.929 0.975 0.074 2-factor model 186.299 26 0.921 0.863 0.934 0.109 1-factor model 713.293 27 0.703 0.505 0.718 0.221 Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 9 of 14 Test–retest reliability (n = 66) Pearson’s correlation coefficients for the initial and retest scores were 0.66 for the total score, 0.62 for “regret,” 0.42 for “parallel expectations,” 0.56 for “parallel emotions,” and 0.50 for “parallel reasons.” All were significant at p < 0.01. Validity Correlations with related scales Scales related to the PPAS showed significant positive correlations with the PPAS and with each of its subscales. Total score and sub score of PPAS correlated with other gambling- and ambivalent- related scales Table 3. Next, we divided the participants into four groups according to the DSM-5 severity score (none, mild, moderate, and severe) and compared the mean PPAS scores across severity groups. For the procedure, we performed a one-way analysis of variance on the means for the four groups and found a significant between-group effect [F(3, 518) = 78.58, p < 0.001]. Differences between the mean values were then assessed using the Bonferroni comparison procedure. The results showed that the scores increased with severity. Mean total score of PPAS correlated with severity assessed by DSM5 Table 4. Correlations with a gambling dependency diagnosis status The correlations of a gambling dependency diagnosis status with the PPAS and its sub - scales were as follows: 0.21 for the total score, 0.09 for “regret,” 0.21 for “parallel expec- tations,” 0.16 for “parallel emotions,” and 0.24 for “parallel reasons.” The correlation for “regret” was significant at p < 0.05, and the rest at p < 0.01. Table 3 The PPAS’s correlations with related scales SIRI AEQ-G SOGS DSM-5 AGRI PGSI Mean total score 0.37 0.43 0.58 0.62 0.54 0.43 Regret 0.18 0.33 0.38 0.4 0.36 0.27 Parallel expectations 0.39 0.32 0.53 0.54 0.46 0.44 Parallel emotions 0.34 0.38 0.58 0.61 0.53 0.43 Parallel reasons 0.27 0.28 0.33 0.41 0.34 0.22 All correlation coefficients were significant at p < 0.01 Table 4 A comparison of PPAS total scores by DSM5-severity group Severity N Mean SD SE Mean at 95% CI Mnimum Maximum classification value value Lower limit Upper limit None 349 18.9a 5.66 0.303 18.3 19.5 9 36 Mild 84 25.4b 3.98 0.435 24.5 26.2 12 34 Moderate 57 25.8bc 3.91 0.518 24.8 26.8 18 36 Severe 32 28.7c 4.62 0.816 27 30.4 18 36 Total 522 21.3 6.25 0.274 20.7 21.8 9 36 Means followed by the same letter do not differ significantly (p = 0.05) Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 10 of 14 Correlations with playing frequency and expenditure (convergent validity) There were significant positive correlations (p < 0.01) between the total PPAS score and “frequency” (0.20), “playing duration” (0.17), and “money lost” (0.37). Discriminant validity Correlations with the social desirability scale Significant negative correlations (p < 0.01) were found between social desirability and the total PPAS score (−0.30), “regret” (−0.20), “parallel expectations (−0.33), “parallel emotions” (−0.22), and “parallel reasons” (−0.18). Correlations with demographic factors No significant differences were found in the total PPAS score according gender, education level (higher or lower than college-graduate level) and family structure (single or not single). Similarly, no significant results were found for the correlation between household income and the total PPAS and subscale scores. Significant negative correlations were found between age group and the total PPAS score and each sub score (p < 0.05). No significant differences were found in the total PPAS score according gender Table  5. No significant differences were found in the total PPAS score according education level Table 6. No significant differences were found in the total PPAS score according family struc - ture Table 7. Significant negative correlations were found between age group and the PPAS score (p  <  0.05). On the other hand, no significant results for the correlation were found between household income and the PPAS Table 8. Discussion The PPAS’s reliability The scale’s reliability was confirmed. Despite the low Cronbach’s alpha value for “parallel reasons,” at 0.48, those for the total scores and other three factors’ scores were 0.79–0.92, Table 5 The PPAS’s difference concerning demographic factors (gender) t-test/mean score Male (n = 446) Female (n = 76) Total 21.4 20.4 Regret 8.48 8.24 Parallel expectations 3.79 3.63 Parallel emotions 4.79 4.53 Parallel reasons 4.37 4.04 Table 6 The PPAS’s difference concerning demographic factors (education) t-test/mean score Over colleage (n = 404) Under high school (n = 118) Total 21.3 21.2 Regret 8.48 8.31 Parallel expectations 3.76 3.79 Parallel emotions 4.74 4.79 Parallel reasons 4.31 4.34 Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 11 of 14 Table 7 The PPAS’s difference concerning demographic factors (family structure) t-test With a family (n = 380) Single (n = 142) Total score 21.1 21.8 Regret 8.33 8.74 Parallel expectations 3.69 3.96 Parallel emotions 4.74 4.78 Parallel reasons 4.31 4.33 demonstrating the scale’s high internal consistency. Moreover, the test–retest correlation coefficients were 0.64 for the overall scale and between 0.42 and 0.62 for the subscales. Regarding parallel reasons, item 9 has a wider concept beyond ambivalence. Namely, changing the reason is not always associated with ambivalent attitude. Therefore the fac - tor “parallel reasons” demonstrated the relative low internal consistency. The PPAS’s validity Construct validity Results revealed that the four factors model reflected the classical distinctions drawn by Bleuler in defining regret. Concurrent validity There were significant positive correlations (0.37–0.62) between the total PPAS score and those of the related general scales (SIRI, AEQ) and gambling scales (SOGS, DSM-5, AGRI Short Screen, PGSI). Moreover, the correlations for the parallel factors tended to be higher than those for the regret factor. Additionally, there were small but significant positive correlations between the gambling dependency diagnosis status and the PPAS’s total score and its paralleling-factor scores. Thus, the PPAS’s concurrent validity was confirmed. Convergent validity The PPAS scores showed small to medium positive correlations with playing frequency and expenditure. In particular, stronger correlations were observed with money lost than with playing frequency. This confirmed the PPAS’s convergent validity. This may reflect ambivalent gambling leads to the unintentional repetitive incurrence of losses. Table 8 The PPAS’s correlations with  demographic factors (household income and  age group) Correlation test Household income Age group* Total score −0.05 −0.2 Regret −0.04 −0.15 Parallel expectations −0.08 −0.3 Parallel emotions −0.05 −0.09 Parallel reasons −0.01 −0.09 * Significant correlation: p < 0.05 Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 12 of 14 Discriminant validity No significant correlation was found between PPAS scores and demographic factors, except being younger. This may be a reflection of the instability in the self-identity of young people. For that reason, when researching young people, one needs to be cautious about their overestimation of themselves. Meanwhile, a negative correlation with social desirability was found. A possible explanation for these results is that ambivalent peo- ple are susceptible to anxiety because they become introspective in response to reality. To avoid anxiety, a denial mechanism serves to protect them from a negative self-image and, as a result, they tend to answer based on unrealistic images of themselves. In sum, some of the responses to the scale may be biased. On the other hand, similar results have been reported for the SOGS, suggesting that this may be a limitation of self-adminis- tered scales (Kuentzel et al. 2008). Therefore, depending on the situation, use of a social desirability scale may be necessary when using the PPAS. The utility of the PPAS While this study showed that some caution may be required when using the PPAS, its reliability and validity were ascertained. Further, the PPAS’s scores showed that the degree of ambivalence correlated with the scores of the DSM5 as the comprehensive severity-assessment scale. Therefore, this study revealed that ambivalence as measured by the PPAS may reflect a core aspect of the condition of a gambling disorder patient. Namely, the PPAS can be considered a useful measure for the assessment for gambling disorders. Limitations and suggestions for further research The recruitment of participants for this study was limited to people registered with an online survey company. As a result, the sample may have been biased and not repre- sentative of the general population of pachinko or pachi-slot players in Japan. However, the study’s sample may be considered appropriate, overall, because it consisted mainly of married, middle-class, middle-aged men, which is consistent with the characteristics of most Japanese people who are diagnosed with gambling disorder (Komoto 2014; Toyama et al. 2014). Moreover, participation was limited to people who had played pachinko or pachi-slot only within the previous year. Next, we selected PPAS’s items by not statistic method but specialists’ conferences. As result, inclusion criteria of scale items somewhat became arbitrary. Additionally, to better understand the efficacy of ambivalence to pre - dict prognosis, longitudinal studies are needed. While acknowledging these limitations, the further development and validation of this ambivalence scale for gambling disorder, for use in clinical settings, is recommended. Abbreviations AEQ: Ambivalence over Emotional Expressiveness Questionnaire; AGFI: adjusted goodness of fit index; AGRI: Alberta Gaming Research Institute; AIC: Akaike Information Criterion; CFI: comparative fit index; DSM-5: Diagnostic and Statistical Manual of Mental Disorders-5; GFI: goodness of fit index; G-SAS: Gambling Symptom Assessment Scale; PGSI: Problem Gambling Severity Index; PG-YBOCS: Yale-Brown Obsessive Compulsive Scale-modified for Pathological Gambling; PPAS: Pachinko/Pachi-Slot Playing Ambivalence Scale; RMSEA: root mean square error of approximation; SIRI: Short Interper- sonal Reactions Inventory; SOGS: South Oaks Gambling Screen. Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 13 of 14 Authors’ contributions All authors designed the study, had advises during the study and reviewed the completed manuscript. YK proposed the study concept and wrote the manuscript. HI monitored data collection. KA and Ash performed the statistical analysis. All authors read and approved the final manuscript. Author details 1 2 Yoshino Hospital, 2252, Zushi-tyo, Machida City, Tokyo 1940203, Japan. Graduate School of Humanities and Sciences, 3 4 Ochanomizu University, Bunkyō, Japan. The Nikkoso Research Foundation for Safe Society, Tokyo, Japan. Department 5 6 of Psychology, Ochanomizu University, Bunkyō, Japan. Naruse Mental Clinic, Machida City, Japan. NPO Recovery 7 8 Support Network, Tokyo, Japan. Tokyo University of Science Suwa, Chino, Japan. Japan Women’s University, Kawasaki, Japan. Competing interests Kikunori Shinohara is on the board of trustees of Nichiyukyo (Japan Pachinko Pachi-Slot industry association). Consent for publication and availability of data and materials All subjects were informed about the study and all provided informed consent. Participant data were treated as strictly confidential and anonymous. Ethical approval and consent to participate This study was approved by the Ethical Review Board for Research in the Humanities at Ochanomizu University (Approval No. 2014-106). Funding sources This study is wholly funded by the Nikkoso Research Foundation for a Safe Society. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Received: 3 September 2016 Accepted: 3 May 2017 References American Psychiatric Association (APA). (2013). Substance-related and addictive disorders: Gambling Disorder. Diagnostic and statistical manual of mental disorders fifth edition (DSM-5) (pp. 585–589). Washington, DC: American Psychiatric Publishing. Armitage, C. J. (2003). Beyond attitudinal ambivalence: Eec ff ts of belief homogeneity on attitude–intention–behavior relations. European Journal of Social Psychology, 33(4), 551–563. Bleuler, E. (1914/1997). Die Ambivalenz [Ambivalence]. In K. Hitomi (Ed.), Selected writings of Eugen Bleuler (pp. 135–157). (K. Hitomi, Trans.). Tokyo: Gakuju Shoin. Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1(2), 245–276. Conner, M., & Sparks, P. (2002). Ambivalence and attitudes. European Review of Social Psychology, 70, 141–156. Dawn, W. F., Clayton, N., & Alexander, P. (2014). Drinking motives as moderators of the effect of ambivalence on drinking and alcohol-related problems. Addictive Behavior, 39(1), 133–139. Ferris, J., & Wynne, H. (2001). The Canadian problem gambling index (Final report). https://www.problemgambling.ca/EN/ Documents/ProblemGamblingSeverityIndex.pdf. Accessed August 18, 2016. Gowing, L. R., Ali, R. L., Allsop, S., Marsden, J., Turf, E. E., West, R., et al. (2015). Global statistics on addictive behaviours: 2014 status report. Addiction. doi:10.1111/add.12899. Grant, J. E., Schreiber, L., Odlaug, B. L., & Kim, S. W. (2010). Pathological gambling and bankruptcy. Comprehensive Psychia- try, 51(2), 115–120. doi:10.1016/j.comppsych.2009.04.002. Grossarth-Maticek, R., & Eysenck, H. J. (1990). Personality, stress and disease: Description and validation of a new inven- tory. Psychological Reports, 66(2), 355–373. Hitomi, K. (2011). Ambivalence. Bulletin of Center for Clinical Psychology Kinki University, 4, 133–136. (in Japanese). Johnson, E. E., Hamer, R., Nora, R. M., Tan, B., Eisenstein, N., & Engelhart, C. (1997). The Lie/Bet Questionnaire for screening pathological gamblers. Psychological Reports, 80(1), 83–88. Kim, S. W., Grant, J. E., Potenza, M. N., Blanco, C., & Hollander, E. (2009). The Gambling Symptom Assessment Scale (G-SAS): A reliability and validity study. Psychiatry Research, 166(1), 76–84. doi:10.1016/j.psychres.2007.11.008. King, L. A., & Emmons, R. A. (1990). Conflict over emotional expression: Psychological and physical correlates. Journal of Personality and Social Psychology, 58(5), 864–877. doi:10.1037/0022-3514.58.5.864. Komoto, Y. (2014). Factors associated with suicide and bankruptcy in Japanese pathological gamblers. International Journal of Mental Health and Addiction, 12(5), 600–606. doi:10.1007/s11469-014-9492-3. Komoto, Y., & Sato, T. (2014). Desire model for gambling disorder. Seishin Igaku, 56(7), 625–635. (in Japanese). Kuentzel, J. G., Henderson, M. J., & Melville, C. L. (2008). The impact of social desirability biases on self-report among col- lege student and problem gamblers. Journal of Gambling Studies, 24(3), 307–319. doi:10.1007/s10899-008-9094-8. Lesieur, H. R., & Blume, S. B. (1987). The South Oaks Gambling Screen (SOGS): A new instrument for the identification of pathological gamblers. American Journal of Psychiatry, 144(9), 1184–1188. Komoto et al. Asian J of Gambling Issues and Public Health (2017) 7:3 Page 14 of 14 Lipkus, I. M., Green, J. D., Feaganes, J. R., & Sedikides, C. (2001). The relationship between attitudinal ambivalence and desire to quit smoking among college smokers. Journal of Applied Social Psychology, 31(1), 113–133. doi:10.1111/j.1559-1816.2001.tb02485.x. Lipkus, I. M., Pollak, K. I., McBride, C. M., Schwartz-Bloom, R., Lyna, P., & Bloom, P. N. (2005). Assessing attitudinal ambiva- lence towards smoking and its association with desire to quit among teen smokers. Psychology and Health, 20(3), 373–387. doi:10.1080/08870440512331333988. Menninga, K. M., Dijkstra, A., & Gebhardt, W. A. (2011). Mixed feelings: Ambivalence as a predictor of relapse in ex-smok- ers. British Journal of Health Psychology, 16(3), 580–591. doi:10.1348/135910710X533219. Nagano, J., Sudo, N., Kubo, T., & Kono, S. (2001). Psychometric reliability and validity of a Japanese Version of the Short Interpersonal Reactions Inventory. Japanese Journal of Behavioral Medicine, 7(2), 104–116. (in Japanese). Oser, M. L., McKellar, J., Moos, B. S., & Moos, R. H. (2010). Changes in ambivalence mediate the relation between entering treatment and change in alcohol use and problems. Addictive Behaviors, 35(4), 367–369. doi:10.1016/j. addbeh.2009.10.024. Pallanti, S., DeCaria, C. M., Grant, J. E., Urpe, M., & Hollander, E. (2005). Reliability and validity of the pathological gambling adaptation of the Yale-Brown Obsessive-Compulsive Scale (PG-YBOCS). Journal of Gambling Studies, 21(4), 431–443. Paulhus, D. L. (1991). Measurement and control of response bias. In J. P. Robinson, P. R. Shaver, & L. S. Wrightsman (Eds.), Measures of personality and social psychological attitudes (pp. 17–59). New York: Academic Press. Petry, N. M., & Kiluk, B. D. (2002). Suicidal ideation and suicide attempts in treatment-seeking pathological gamblers. Journal of Nervous and Mental Disease, 190(7), 462–469. Priester, J. R., & Petty, R. E. (1996). The gradual threshold model of ambivalence: Relating the positive and nega- tive bases of attitude to subjective ambivalence. Journal of Personality and Social Psychology, 71(3), 431–449. doi:10.1037/0022-3514.71.3.431. Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Test of significance and descriptive goodness-of-fit-measures. Methods of Psychological Research Online, 8(2), 23–74. Dis- ponible en http://www.mpr-online.de. Steenbergh, T. A., Meyers, A. W., May, R. K., & Whelan, J. P. (2002). Development and validation of the Gamblers’ Beliefs Questionnaire. Psychology of Addictive Behaviors, 16(2), 143–149. Stinchfield, R. (2013). A review of problem gambling assessment instruments and brief screens. In D. C. S. Richard, A. Blaszczynski, & L. Nower (Eds.), The Wiley-Blackwell handbook of disordered gambling (pp. 165–203). Hoboken: John. Tani, I. (2008). Development of Japanese Version of Balanced Inventory of Desirable Responding (BIDR-J ). The Japanese Journal of Personality, 17(1), 18–28. (in Japanese). Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education., 2, 53–55. doi:10.5116/ijme.4dfb.8dfd. Thompson, M. M., Zanna, M. P., & Griffin, D. W. (1995). Let’s not be indifferent about (attitudinal) ambivalence. In R. E. Petty & J. A. Krosnick (Eds.), Attitude strength: Antecedents and consequences ( Vol. 4, pp. 361–386). Hillsdate, NJ: Erlbaum. Toyama, T., Nakayama, H., Takimura, T., Yoshimura, A., & Higuchi, S. (2014). Prevalence of pathological gambling in Japan: Results of national surveys of the general adult population in 2008 and 2013. Alcohol and Alcoholism, 49(suppl 1), i17. Volberg, R. A., & Williams, R. J. (2011). Developing a brief problem gambling screen using clinically validated samples of at-risk, problem and pathological gamblers. Edmonton: Alberta Gaming Research Institute. Walker, D., Stephens, R., Rowland, J., & Roffman, R. (2011). The influence of client behavior during motivational interview- ing on marijuana treatment outcome. Addictive Behaviors, 36(6), 669–673. doi:10.1016/j.addbeh.2011.01.009. Weatherly, J. N., Miller, J. C., & Terrell, H. K. (2011). Testing the construct validity of the gambling functional assessment— Revised. Behavior Modification, 35(6), 553–569. doi:10.1177/0145445511416635.

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