A new tool to assess the occurrence of personality traits:
the Phenomenological Personality Factor questionnaire

Natascia De Lucia1, Mauro Nelson Maldonato1, Valeria Cioffi2, Lucia Luciana Mosca2,
Elena Gigante
3, Nicole Nascivera2, Enrico Moretto2, Benedetta Muzii4, Mario Bottone1, Daniela Cantone5, Raffaele Sperandeo2

1Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, Naples, Italy; 2Postgraduate School of Integrated Gestalt Psychotherapy, Torre Annunziata (Naples), Italy; 3Postgraduate School of Integrated Gestalt Psychotherapy, Trapani, Italy; 4Department of Humanistic Studies, University of Naples “Federico II”, Naples, Italy; 5Department of Psychology, University of Campania “L. Vanvitelli”, Caserta, Italy.

Summary. Background. Personality traits are patterns of thoughts, feelings and actions that are usually assessed by means of psychometric questionnaires. In the present study we described the Phenomenological Personality Factor (PPF), a short questionnaire assessing the personality traits, taking into account the different interpretative models of personality. Methods. A sample of 554 healthy subjects (357 female; 197 males) aged 18-60 years were enrolled. Each participant was required to complete PPF, by indicating the presence/absence of the individual personality trait, and the Italian version of the Affective Neuroscience Personality Scale (ANPS). Results. The principal component analysis showed that seven factors explained the 35.07% of the total variance. Moreover, the correlation analysis revealed that the PPF components were significantly and positively associated with the ANPS scales. Conclusions. Our findings suggest that the PPF is a useful questionnaire to assess the personality traits, and the adaptive functioning, in healthy individuals.

Key words. Personality questionnaires, personality traits, principal component analysis.

Un nuovo strumento per valutare l’occorrenza dei tratti di personalità: il questionario Phenomenological Personality Factor.

Riassunto. Introduzione. I tratti di personalità rappresentano schemi di pensieri, sentimenti e azioni spesso valutati mediante questionari psicometrici. Nel presente studio noi descriviamo il questionario Phenomenological Personality Factor (PPF), un breve strumento sviluppato per valutare i tratti di personalità in soggetti sani, tenendo in considerazione i diversi modelli interpretativi della personalità. Metodi. Sono stati reclutati 554 soggetti sani (357 femmine; 197 maschi), di età compresa tra i 18 e i 60 anni. A ogni partecipante è stato chiesto di completare il PPF, indicando la presenza/assenza dello specifico tratto di personalità, e la versione Italiana dell’Affective Neuroscience Personality Scale (ANPS). Risultati. L’analisi delle componenti principali ha estratto sette fattori che spiegavano il 35,07% della varianza totale. Inoltre, l’analisi di correlazione ha mostrato che le componenti del PPF erano associate significativamente e positivamente con le scale dell’ANPS. Conclusioni. I nostri risultati suggeriscono che il PPF è un utile strumento per valutare l’occorrenza dei tratti di personalità, e il funzionamento adattivo, nei soggetti sani.

Parole chiave. Analisi delle componenti principali, questionario di personalità, tratti di personalità.

Introduction

Personality characteristics are distinctive and recurrent patterns of thoughts, feelings and actions that occur in response to particular situational demands1. Several psychometric questionnaires have been developed to assess and describe the personality and its dysfunctions. Some instruments derived from theoretical models that describe the personality as an organization of dimensions or factors2-4. Costa and McCrae5 constructed the NEO Personality Inventory (NEO-PI), based on the Five-Factors Model (FFM)2,6. According to this interpretative model, the personality is organized in specific behavioural, emotional and cognitive patterns, along five broad dimensions: neuroticism, introversion, openness, agreeableness and conscientiousness. Each dimension includes a cluster of specific traits, associated with distinct neural pathways, and is considered as enduring dispositions that underlie individuals’ cognitive and emotional tendencies7,8. The Eysenck Personality Inventory (EPQ)2,9, instead, assesses the personality according to a three-dimension model10, that includes the neuroticism (defined as an increased tendency to emotional reactivity), the extraversion (defined as the degree to which a person is outgoing and interactive with other people), and the psychoticism (referring to an underlying predisposition of personality to develop anomalies of psychiatric nature). Along this account, the personality would arise from the dynamic interaction of these biological systems with external situations. Similarly, the Temperament Personality Questionnaire (TPQ) and the Temperament Character Inventory (TCI) were developed4,11,12 to assess seven dimensions of personality, including four temperaments and three characters. The temperaments refer to novelty seeking (the tendency to response to novelty, danger and cue for reward, associated with low basal dopaminergic activity), harm avoidance (the tendency to avoid aversive stimuli, associated with high serotoninergic activity), reward dependence (the tendency to react actively to rewards, associated with low basal noradrenergic activities), and persistence, that manifest in unique emotional/behavioural patterns expressed in response to environmental stimuli. The characters refer to self-directedness, cooperativeness, and self-transcendence.

However, these instruments would seem to have some limitations. First, the numerous sets of items could impede an accurate assessment of personality since the risk of approximate and incomplete responses, especially in studies with large samples13,14. Second, these questionnaires tend to assess frequency and expressive intensity of personality traits, however this approach could not consider the subjective interpretation of the descriptors15,16.

More recently, the Affective Neuroscience Personality Scales (ANPS)17 has been derived from the affective neuroscience theory proposed by Panksepp18. According to this interpretative model, the personality traits are deeply correlated to functioning of the specific neural and biological circuits18. The emotions would represent complex mental processes developed during the phylogenetic evolution to ensure the survival of individual in critical situations, and integrated emotional systems with specific subcortical regions. Panksepp18 identified seven primary motivation-emotional systems, deeply rooted in subcortical areas of the human brain: seeking (or expectancy), lust, care (or nurturing), play (or social joy), rage (or anger), fear and panic (or sadness). These organizations were then distinguished in a positive emotional system, that included the seeking, lust, care, and play, and a negative emotional valence/punishment system that included the rage, fear and panic, according to the specific emotional value18. The seeking motivation system provides energy for obtaining resources to fulfil goals and strive for solutions to everyday problems (i.e., the search for food); it refers to a feeling of being able to accomplish almost anything. The lust motivation system represents the evolutionary older emotion as it is involved in the reproducing and transferring one’s own genome, and it is closely entwined with the care emotional system19. The care system urges to take attention on family including offspring and the close relatives and friends, and it refers to feeling affection, empathy, and soft-hearted toward people in need. The play system expresses a crucial emotion for regulating the social bondings20 and shaping physical activities21, and it refers to being funny, generally happy and joyful, and having humour and laughter. The negative emotional system, instead, would help to move away from danger conditions. Indeed, the rage system is involved in the protection of life resources, as escaping bodily restraint, and it describes feelings of frustration, easy irritation leading to verbal or physical anger. The fear tends to keep away from bodily harm and physical pain, by triggering freezing or flight responses to cope with dangerous situations, and it describes feelings of anxiety, worrying, ruminating about past decisions associated to losing sleep. Finally, the panic system aims to preserve the social contact avoiding the separation from caregivers and loved ones, and it refers to feelings of lonely and distress for dropped relationships17,22.

However, to exclusively consider the emotional functioning, as the ANPS, could impede a deep comprehension of the personality traits and its dysfunctions. Thus, a novel approach that integrates the study of the personality as organization of dimension or factors with the study of the emotional functioning would seem to be needed.

In the present study we tried to overcome these limitations by developing a short questionnaire comprising a smaller quantity of items, compared to the available personality questionnaires. Therefore, we aimed to describe the Phenomenological Personality Factor (PPF) questionnaire, and present its psychometric characteristics by administering the PPF to a sample of healthy Italian people. Therefore, this study would contribute to the examination of item characteristics, the factor structure, and the reliability of intensity and perceived impact dimensions of a scale used in previous research either in an idiographic format or without having determined psychometric properties.

Materials and methods

Participants

Participants for the present study were recruited from voluntary students attending the undergraduate psychology courses offered at the University of Naples “Federico II”. To qualify for the present study, participants had to meet the following inclusion criteria: 1) age comprised between 18 and 60 years; 2) lack of significant neurological and/or psychiatric disorders, as reported by the clinical assessment; 3) no history of alcohol or substance abuse or medications with significant effects on emotion or cognition.

A total of 554 healthy subjects (HS) satisfied the inclusion criteria, comprising 357 (64.5%) females and 197 (35.5%) males. Demographic data of the sample are reported in table 1.




All the participants gave their informal consent to participate in the study. This study was conducted in accordance with the Ethical standards of Helsinki Declaration.

Procedure

In order to devise the PPF, a working group of five experts in clinical psychology produced a pool of items that reflected difficulties within the seven emotional systems proposed by Panksepp’s affective neuroscience theory18. These items were written, re-written and edited until consensus among the authors was reached. An initial pool of 180 items was developed. For each item, participants were required to assess whether it applied to themselves, by indicating on a scale ranging from 0 to 1 point, where 0 means absence of the personality trait, and 1 presence of the personality trait.

It has been observed that the frequency and intensity may produce difficulties in the interpretation of the items15,16. Thus, in order to overcome this limitation, we decided to present descriptors with dichotomous responses (presence or absence the phenomenon) in order to avoid frequency (e.g., number of behaviour occurrence, such as “sometimes”, “often”, or “rarely”) and intensity (e.g., severity of behaviour, such as “enough”, “little”, or “very”) of the phenomenon.

The items are organized into three distinct areas23: emotional characteristics, dissociative phenomena, and psychopathological traits. Emotional characteristics area is focused to detect non-pathological psychic phenomenon, such as the emotional experiences and behaviours, physical sensations, and the impact of cortical functions on emotional systems; the dissociative phenomena area referred to presence of dissociative phenomena in the three dimensions of depersonalization-derealization, dissociated mental states and dissociative amnesia; psychopathological traits area referred to the presence or absence of a pathological phenomenon.

Moreover, participants were asked to complete the Italian version of the ANPS17 Italian validation by Pascazio et al.24 to assess the association between personality areas identified by the model and the six basic emotional processes, as depicted in the Affective Neuroscience theory18,25. ANPS is a self-report questionnaires consisting of 110 items, each scored on a 4-point Likert-type scale where 0 means maximum agreement and 3 means maximum disagreement. The original version also includes two further categories, Spirituality (defined “for a hypothesized higher-order affective human attribute”)17, and Faking (developed to focus the evidence of social desirability). In the present study we decided to exclude these additional systems since they were designed to reflect individual tendency to a self-image impression management, and do not refer to emotional endophenotypes24. Therefore, the final score ranged 0-440.

Statistical analyses

To assess the factorial structure of the PPF and identify the underlying dimensions of emotion regulation, we performed a principal component analysis (PCA), with Oblimin rotation and Kaiser normalization. To this statistical purpose, we considered the factors with eigenvalues >1.5. Bartlett’s test of sphericity and Kaiser-Meyer-Olkin (KMO) test were used to assess the sampling adequacy and the suitability of the respondent data for factor analysis.

Then, to explore the possible associations between scores on PPF and ANPS, we computed the Pearson’s correlation coefficients among the seven components extracted by the principal components analysis and the ANPS subscales.

Results

Bartlett’s test of sphericity was significant and KMO measure was >0.5, suggesting that the factorability was assumed (table 2).




Results from data processing showed that the PCA extracted seven factors (table 3), explaining the 35.07% of the total variance (table 4).










The PPF’s first factor was labelled “Confidence”, and includes 12 items describing the belief into own capacities to take part into the world and social relationships; high scores suggested limited confidence to successfully participate to world. The second component was labelled “Grandness”, and includes 8 items reflecting the ideal representation of self; high scores suggested marked grandness. The third component was labelled “Reflectively”, and comprises 6 items describing the tendency to carefully consider everything happen with scrupulousness and prudence; high scores implied disproportionate reflectively. The fourth component was labelled “Self-determination” and includes 10 items reflecting the belief to find everyday solutions by means of own resources only; high scores suggested low self-determination. The fifth component was labelled “Spirituality” and includes 7 items describing the presence of a deep openness toward a spiritual meaning of life; high scores suggested high spirituality. The sixth component was labelled “Sociality” and includes 6 items reflecting the tendency to extroversion and to socialization; high scores implied elevated motivation to create social relationships. The seventh component was labelled “Assertive behaviour”, and includes 6 items describing the ability to identify and state own thoughts, wishes, and emotions honestly, directly, adequately to other rights; high scores suggested marked assertive behaviour. The inspection of the correlation matrix among the components revealed weak associations between the first factor (Confidence) and the fourth factor (Self-determination), between the first factor and the seventh factor (Assertive behaviour), and between the fourth factor (Self-determination) and the seventh factor (Assertive behaviour; table 5).

Results from the correlation analysis exploring the possible associations between the seven components extracted by the principal components analysis and the ANPS subscales showed significant positive associations of the seven PPF factors and the subscales of ANPS (table 6). In particular, the Confidence factor was significantly and positively correlated to fear, care, rage, and panic subscales of the ANPS (all comparisons p<.05); grandness factor was significantly correlated to rage, play, and panic ANPS subscales (all comparisons p<.05); reflectively was correlated to fear (p<.05); self-determination was correlated to fear, rage, and panic (all comparisons p<.05); spirituality was correlated to seeking, care, panic, and lust (all comparisons p<.05); sociality was correlated to care, and play (all comparisons p<.05); assertive behaviour was correlated to seeking, play, and lust (all comparisons p<.05).

Discussion and conclusions

Traditionally, the personality and its dysfunctions have been conceived according to a heterogeneous theoretical model that identifies personality disorders within specific numbers of clinical criteria26. However, this approach would seem to have some limitations27,28. Indeed, the number of the clinical criteria useful to confirm a clinical diagnosis would seem to derive from non-psychometric procedures. Moreover, different diagnostic categories would seem to include clinic signs rather heterogeneous, and the different diagnosis would seem to have excessive comorbidity29-31.

Conversely, in the last years, revamped interest has been focused on the empirical models of personality traits32 that try to describe the temperament and the general tendency of thinks, feelings and behaviours33-36, and the characteristics of personality dysfunctions27. Indeed, the model based on personality traits could overcome the limits of the heterogeneous categories of personality disorders28, but they could be not able to describe the maladaptive personality characteristics37-39. Indeed, it is common opinion among clinicians40,41 that the description of personality disorders in category types is crucial for comprehension of disorders suggesting the necessity to preserve it. First, the personality traits model assesses a range of personality functioning without include the dis-adaptive functioning of the subject42. Second, the diagnostic categories of personality disease describe the personality characteristics that are flatten by the actual dimensional models of personality43.

In the current study, we presented a novel and short psychometric instrument, labelled “Phenomenological Personality Factor” (PPF) questionnaire, derived from the psychological and neurobiological interpretative models of the personality44-47. Results from the principal component analysis revealed the occurrence of seven components, thus confirming the same structure derived from the study in psychopathological individuals23. Indeed, these authors23 presented a procedure that aimed to combine explanatory and predictive modelling for the construction of new psychometric questionnaires based on psychological and neuroscientific theoretical grounding45,48. The PPF includes scores located along a continuum that allow to move from adaptive to dis-adaptive behaviours. Therefore, each factor of the PPF would include a wide range of values able to express the adaptive functioning within the specific category.

Our results even suggest that the psychometric characteristics of the PPF allow to consider this instrument as a useful method of dimensional analysis of the personality traits45,48, able to describe the empirical dimensions and to identify the dysfunctional phenomena23.

However, some limitations should be taken into account. We did not compare the PPF performance with questionnaires derived from theoretical models that describe the personality as an organization of dimensions or factors, thus future studies could consider to compare PPF with others instrument, for example the NEO Personality Inventory. Moreover, we did not explore the possible associations of the PPF factors with specific neurobiological mechanisms, thus further studies could address this issue. Notwithstanding these limitations, the PPF could represent a useful instrument to quickly assess the personality traits taking into account the adaptive functioning in healthy individuals.

Conflict of interests: the authors have no conflict of interests to declare.

References

1. Mischel W. Toward an integrative science of the person. Annu Rev Psychol 2004; 55: 1-22.

2. McCrae RR, Costa PT Jr. Personality trait structure as a human universal. Am Psychol 1997; 52: 509-16.

3. Eysenck HJ. The Scientific Study of Personality. London: Routledge & Kegan Paul, 1952.

4. Cloninger CR. A systematic method for clinical description and classification of personality variants. A proposal. Arch Gen Psychiatry 1987; 44: 573-88.

5. Costa PT, McCrae RR. The NEO Personality Inventory Manual. Odessa, FL: Psychological Assessment Resources, 1985.

6. Goldberg LR. An alternative “Description of Personality” the Big-Five Factor structure. J Per Soc Psychol 1990; 59: 1216-29.

7. McCrae RR, Costa PT. Personality in adulthood: a five-factor theory perspective. New York: Guilford Press, 2003.

8. DeYoung CG, Hirsh JB, Shane MS, Papademetris X, Rajeevan N, Gray JR. Testing predictions from personality neuroscience. Brain structure and the big five. Psychol Sci 2010; 21: 820-8.

9. Eysenck HJ, Eysenck S. Manual of the Eysenck personality inventory. London: London University Press, 1964.

10. Eysenck HJ. Manual of the Maudsley personality inventory. London: London University Press, 1959.

11. Cloninger CR, Svrakic DM, Przybeck TR. The tridimensional personality questionnaire: U.S. normative data. Psychol Rep 1991; 69: 1047-57.

12. Stallings MC, Hewitt LK, Cloninger CR, Heath AC, Eaves LJ. Genetic and environmental structure of the tridimensional personality questionnaire: three or four temperament dimensions? J Pers Soc Psychol 1996; 70: 127-40.

13. Gibbons RD, Weiss DJ, Kupfer DJ, et al. Using computerized adaptive testing to reduce the burden of mental health assessment. Psychiatric Services 2008; 59: 361-8.

14. Galesic M, Bosnjak M. Effects of questionnaire length on participation and indicators of response quality in a web survey. Public Opin Q 2009; 73: 349-60.

15. Wetzel E, Böhnke JR, Brown A. Response biases. In: Leong FTL, Bartram D, Cheung FM, Geisinger KF, Iliescu D (eds). The ITC international handbook of testing and assessment. New York: Oxford University Press, 2016.

16. Vispoel WP, Kim HY. Psychometric properties for the Balanced Inventory of desirable responding: dichotomous versus polytomous conventional and IRT scoring. Psychol Assess 2014; 26: 878-91.

17. Davis KL, Panksepp J, Normansell L. The Affective Neuroscience Personality Scales: normative data and implications. Neuropsychoanal 2003; 5: 57-69.

18. Panksepp J. Affective neuroscience: the foundations of human and animal emotions. New York: Oxford University Press, 1998.

19. Cerasa A. Re-examining the Parkinsonian Personality hypothesis: a systematic review. Pers Individ Differ 2018; 130: 41-50.

20. Pellegrini AD. Elementary-school children’s rough-and-tumble play and social competence. Dev Psych 1988; 24: 802-6.

21. Pellegrini AD, Smith PK. Physical activity play: the nature and function of a neglected aspect of play. Child Dev 1998; 69: 577-98.

22. Montag C, Elhai JD, Davis KL. A comprehensive review of studies using the Affective Neuroscience Personality Scales in the psychological and psychiatric sciences. Neurosci Biobehav Rev 2021; 125: 160-7.

23. Dolce P, Marocco D, Maldonato MN, Sperandeo R. Toward a machine learning predictive-oriented approach to complement explanatory modeling. An application for evaluating psychopathological traits based on affective neurosciences and phenomenology. Front Psychol 2020; 11: 446.

24. Pascazio L, Bembich S, Nardone IB, Vecchiet C, Guarino G, Clarici A. Validation of the Italian translation of the Affective Neuroscience Personality Scales. SAGE Journal 2015; 116: 97-115.

25. Montag C, Davis KL. Affective neuroscience theory and personality: an update. Personal Neurosci 2018; 10: 1e12.

26. American Psychiatric Association (APA). DSM-5. Manuale diagnostico e statistico dei disturbi mentali. tr. it. Milano: Raffaello Cortina Editore, 2014.

27. Krueger RF, Markon KE. The role of the DSM-5 personality trait model in moving toward a quantitative and empirically based approach to classifying personality and psychopathology. Annu Rev Clin Psychol 2014; 10: 477-501.

28. Widiger TA, Trull TJ. Plate tectonics in the classification of personality disorder: shifting to a dimensional model. Am Psychol 2007; 62: 71-83.

29. Clark LA. Assessment and diagnosis of personality disorder: perennial issues and an emerging reconceptualization. Annu Rev Psychol 2007; 58: 227-57.

30. Sharp C, Fonagy P. Practitioner review: borderline personality disorder in adolescence – recent conceptualization, intervention, and implications for clinical practice. J Child Psychol Psychitry 2015; 56: 1266-88.

31. Hopwood CJ, Wright AG, Ansell EB, Pincus AL. The interpersonal core of personality pathology. J Pers Dis 2013; 27: 270-95.

32. Roberts BW, Kuncel NR, Shiner R, Caspi A, Goldberg LR. The power of personality: the comparative validity of personality traits, socioeconomic status, and cognitive ability for predicting important life outcomes. Persp Psychol Sci 2007; 2: 313-45.

33. Markon KE, Krueger RF, Watson D. Delineating the structure of normal and abnormal personality: an integrative hierarchical approach. J Pers Soc Psychol 2005; 88: 139-57.

34. Kandler C, Bleidorn W, Riemann R, Spinath FM, Thiel W, Angleitner A. Sources of cumulative continuity in personality: a longitudinal multiple-rater twin study. J Pers Soc Psychol 2010; 98: 995-1008.

35. Bleidorn W, Hopwood CJ, Lucas RE. Life events and personality trait change. J Pers 2018; 86: 83-96.

36. Kotov R, Gamez W, Schmidt F, Watson D. Linking “big” personality traits to anxiety, depressive, and substance use disorders: a meta-analysis. Psychol Bull 2010; 136: 768-821.

37. Gore WL, Widiger TA. The DSM-5 dimensional trait model and five-factor models of general personality. J Abn Psychol 2013; 122: 816-21.

38. Thomas KM, Yalch MM, Krueger RF, Wright AG, Markon KE, Hopwood CJ. The convergent structure of DSM-5 personality trait facets and five-factor model trait domains. Assessment 2013; 20: 308-11.

39. Wright AG, Simms LJ. On the structure of personality disorder traits: conjoint analyses of the CAT-PD, PID-5, and NEO-PI-3 trait models. Pers Dis Theor Res Treat 2014; 5: 43-54.

40. Christensen AP, Golino H, Silvia P. A psychometric network perspective on the validity and validation of personality trait questionnaires. Eur J Per 2019; 34: 1095-108.

41. Hopwood CJ. Interpersonal dynamics in personality and personality disorders. Eur J Per 2018; 32: 499-524.

42. Morey LC, Hopwood CJ, Markowitz JC, et al. Comparison of alternative models for personality disorders, II: 6-, 8-and 10-year follow-up. Psychol Med 2012; 42: 1705-13.

43. Suzuki T, Samuel DB, Pahlen S, Krueger RF. DSM-5 alternative personality disorder model traits as maladaptive extreme variants of the five-factor model: an item-response theory analysis. J Abn Psych 2015; 124: 343-54.

44. Sperandeo R, Picciocchi E, Valenzano A, et al. Exploring the relationships between executive functions and personality dimensions in the light of “embodied cognition” theory: a study on a sample of 130 subjects. Acta Med Mediterr 2018; 34: 1271-9.

45. Maldonato MN. From neuron to consciousness: for an experience-based neuroscience. World Fut 2009; 65: 80-93.

46. De Lucia N, Grossi D, Mauro A, Trojano L. Closing-in in Parkinson’s disease individuals with dementia: an experimental study. J Clin Exp Neuropsych 2015; 37: 946-55.

47. Grossi D, De Lucia N, Trojano L. Closing-in is related to apathy in Alzheimer’s disease patients. J Alzh Dis 2015; 43: 849-55.

48. Maldonato MN, Sperandeo R, Dell’Orco S, et al. The relationship between personality and neurocognition among the American elderly: an epidemiologic study. Clin Pract Epidemiol Ment Health 2017; 13: 233-45.