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Data were collected in an online survey, which was advertised as “Win three tickets for the Sziget Festival with your habits” and appeared on Hungarian general news and magazine websites. Participants were entered into a price drawing where three incentives (valued at €900) were offered. Participants could reach the survey between January and August 2014. Only individuals older than 18 years could take part. In total, 4177 people participated in the online questionnaire. Data were used if at least 80% of the items were completed, leaving 2875 valid responses. Despite our call, 170 participants were under 18 years old and were consequently excluded. This left 2705 participants’ data for analysis. Out of these, 1026 (36%) intentionally pulled their hair, 2289 (85%) bit their nails and 1198 (44%) intentionally picked their skin at least once during their life. Only those participants who reported to have done the given behaviour at least once were offered to fill out the appropriate grooming questionnaire.
TTM was assessed by the Massachusetts General Hospital Hairpulling Scale (MGH-HPS). The most widely used TTM instrument, the MGH-HPS is based on the Yale–Brown Obsessive–Compulsive Scale (Y-BOCS) [44]. The MGH-HPS has previously demonstrated strong test–retest reliability (r = 0.97) [45]. The questionnaire is self-administered, and participants rate severity, urge to pull, actual pulling, perceived control and associated distress from 0 (no symptom) to 4 (extreme symptom) on a five-point summative response scale. The items were translated and back-translated from English to Hungarian by three independent experts of both languages. The questionnaire provides an estimate of symptom severity in the past seven days. Internal consistency was high in the current sample (α = 0.92). Similar to the MGH-HPS, the Skin Picking Scale-Revised (SPS) was also modelled after the Y-BOCS [10]. The SPS contains eight factors covering impairment and symptom severity. The instrument demonstrated acceptable internal consistency in the current sample (α = 0.88). Considering the lack of clinically adapted nail-biting questionnaires in the literature and in order to comply with the previous questionnaires used in the current study (the MGH-HPS and SPS), we adapted the SPS to measure the severity of NB. The NB scale (NBS) performed acceptable internal consistency (α = 0.77) and can be found in the S1 File.
Impulsivity was measured by the modified Barratt Impulsiveness Scale (BIS, [46]). The 21-item questionnaire has three first-order factors: self-control, impulsive behaviour and impatience. Items are rated 1 to 4. The BIS achieved an acceptable level of internal consistency: α = 0.81. The Brief Symptom Inventory (BSI) is a 53-item self-report measurement designed to evaluate psychopathology in nine major fields of psychiatry: depression, anxiety, hostility, obsessive–compulsive tendencies, somatisation, phobic anxiety, psychoticism and paranoid ideation [47]. Besides the nine basic dimensions, the Global Severity Index calculates the sum of the scales and four extra items, then divides the sum by the total number of items to which the individual responded. The items are rated on a five-point summative response scale from 0 (not at all) to 4 (very much). The scale was validated in Hungarian [48] and yielded high internal consistency (α = 0.96). The Zanarini Rating Scale for Borderline Personality Disorder (ZAN-BPD) adapted the BPD criteria from the DSM-IV [49]. Initially developed for clinical use, the instrument was adopted to be used as a self-report measure with nine items. The ZAN-BPD reflects a one-week timeframe, and each of the nine criteria for BPD is rated to be present or absent. The scale had acceptable internal consistency (Cronbach’s α = 0.72). Contingent self-esteem (CSE) refers to the external sources of a person’s perceived self-worth, such as others’ love and evaluation of competence [50]. Sample items are “I feel worthwhile only when I have performed well” or “I tend to suppress my own needs and emotions to make others feel good”. The 26 items assessing CSE are measured on a scale from 1 to 4, with higher scores indicating increased likelihood to base one’s self-esteem on others’ evaluation. CSE contains two subscales, competence-based and relation-based self-esteem. The scale was translated to Hungarian in the same way as the MGH-HPS. Cronbach’s alpha was 0.93.
Confirmatory factor analysis with Mplus version 7.3 [51] was used to estimate the degree of fit for each grooming measure (TTM, SP and NB). Four models were tested. Model 1 consisted of correlating first-order factors (TTM, SP and NB defined as latent factors). Model 2 included a hierarchical factor structure representing the general grooming dimension as defined by the three first-order latent factors. Model 3 was a bifactorial model with the three first-order factors and the general latent factor defined by all grooming items. In this model, the correlation between the specific factors and the correlations between the specific factors and the global factor were fixed to zero [52]. Finally, Model 4 was bifactorial with correlating first-order factors. Due to the severe floor effect in the responses, items were treated as ordinal indicators, and the weighted least squares mean and variance (WLSMV) adjusted estimation method was used [53, 54]. A satisfactory degree of fit requires the comparative fit index (CFI) and the Tucker–Lewis index (TLI) to be higher than or close to 0.95, and the model should be rejected when these indices are less than 0.90 [53, 55]. The next fit index was the root mean square error of approximation (RMSEA). RMSEA below 0.05 indicates an excellent fit, a value around 0.08 indicates an adequate fit and a value above 0.10 indicates a poor fit. Closeness of the model fit using RMSEA (CFit of RMSEA) is a statistical test, which evaluates the statistical deviation of RMSEA from the value 0.05 [53]. A nonsignificant probability value (p > 0.05) indicates an acceptable model fit. Missing data was excluded listwise. The multiple indicators and multiple causes (MIMIC) modelling technique, a specification of structural equation modelling, was chosen for the present study [56]. We opted for this technique because MIMIC models can estimate the effect of indicators on latent variables when the direct effects of continuous variables on the latent variables are also included. In addition, MIMIC modelling is suitable to validate a construct via reflective modelling [57].
The study protocol was approved by the Institutional Review Board of Eötvös Loránd University and conforms to the Declarations of Helsinki. All participants were informed about the purpose of the study and provided written consent before filling out the questionnaire.
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