Subjectifying the Personality State: Theoretical Underpinnings and an Empirical Example

Lazarus, Gal; Sened, Haran; Rafaeli, Eshkol

doi:10.1002/per.2278

Cited by 16 publications

(32 citation statements)

References 110 publications

(204 reference statements)

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“…Changes in personality characteristics barely track with specific life experiences Denissen et al, 2019), are similarly distributed across geographically diverse regions (Allik et al, 2017), but vary systematically across genders (Lee et al, 2020). Recently, research has also started to describe systematic patterns of short-term variations in personality as another aspect of individual differences (e.g., Danvers, Wundrack, & Mehl, 2020;Horstmann & Ziegler, 2020;Lazarus et al, 2020;Sosnowska et al, 2020). 2 The trait hierarchy Within the descriptive kind, a lot of research has been carried out on the relations between (subjectively perceived) trait scores with the aim to reduce personality variation among people to as few broad trait dimensions as possible.…”

Section: Descriptive Personality Sciencementioning

confidence: 99%

“…Finally, in some and maybe even many cases, links between phenomena and their plausible causes exist in such narrow circumstances as to be unique to individuals or only small subsets of them (e.g., Beck & Jackson, 2020), which further complicates connecting them with population-level variance in individual differences constructs (cf. Beltz et al, 2016;Dotterer et al, in press;Lazarus et al, 2020;. The more idiosyncratic the associations are, the less practical and even plausible it is to identify the specific causes of individual differences, at least as long as these are defined as dimensions along which individuals vary.…”

Section: Why Many Causes May Be Inherently Elusivementioning

confidence: 99%

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Descriptive, predictive and explanatory personality research: Different goals, different approaches, but a shared need to move beyond the Big Few traits

Mõttus¹,

Wood²,

Condon³

et al. 2020

Preprint

106

182

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We argue that it is useful to distinguish between three key goals of personality science – description, prediction and explanation – and that attaining them often requires different priorities and methodological approaches. We put forward specific recommendations such as publishing findings with minimum a priori aggregation and exploring the limits of predictive models without being constrained by parsimony and intuitiveness but instead maximising out-of-sample predictive accuracy. We argue that naturally-occurring variance in many decontextualized and multi-determined constructs that interest personality scientists may not have individual causes, at least as this term is generally understood and in ways that are human-interpretable, never mind intervenable. If so, useful explanations are narratives that summarize many pieces of descriptive findings rather than models that target individual cause-effect associations. By meticulously studying specific and contextualized behaviours, thoughts, feelings and goals, however, individual causes of variance may ultimately be identifiable, although such causal explanations will likely be far more complex, phenomenon-specific and person-specific than anticipated thus far. Progress in all three areas – description, prediction, and explanation – requires higher-dimensional models than the currently-dominant “Big Few” and supplementing subjective trait-ratings with alternative sources of information such as informant-reports and behavioural measurements. Developing a new generation of psychometric tools thus provides many immediate research opportunities.

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Section: Descriptive Personality Sciencementioning

confidence: 99%

Section: Why Many Causes May Be Inherently Elusivementioning

confidence: 99%

Descriptive, predictive and explanatory personality research: Different goals, different approaches, but a shared need to move beyond the Big Few traits

Mõttus¹,

Wood²,

Condon³

et al. 2020

Preprint

106

182

View full text Add to dashboard Cite

show abstract

“…We also encourage within‐individual variance designs that focus on estimating idiographic association patterns besides nomothetic ones (Beck & Jackson, 2020; Lazarus, Sened, & Rafaeli, 2020; Wright & Zimmermann, 2019). It is crucial that we understand how far our typical nomothetic models of variance can go in principle—that is how broad are the boundary conditions of possible causal effects.…”

Section: Explanatory Personality Sciencementioning

confidence: 99%

“…Recently, research has also started to describe systematic patterns of short–term variations in personality as another aspect of individual differences (e.g. Danvers, Wundrack, & Mehl, 2020; Horstmann & Ziegler, 2020; Lazarus, Sened, & Rafaeli, 2020; Sosnowska, Kuppens, Fruyt, & Hofmans, 2020). 2…”

Section: Descriptive Personality Sciencementioning

confidence: 99%

“…Beck & Jackson, 2020), which further complicates connecting them with population–level variance in individual differences constructs (cf. Beltz, Wright, Sprague, & Molenaar, 2016; Dotterer, Beltz, Foster, Simms, & Wright, in press; Lazarus, Sened, & Rafaeli, 2020; Woods et al, 2020; Wright & Zimmermann, 2019). The more idiosyncratic the associations are, the less practical and even plausible it is to identify the specific causes of individual differences, at least as long as these are defined as dimensions along which individuals vary.…”

Section: Explanatory Personality Sciencementioning

confidence: 99%

See 1 more Smart Citation

Descriptive, Predictive and Explanatory Personality Research: Different Goals, Different Approaches, but a Shared Need to Move beyond the Big Few Traits

et al. 2020

View full text Add to dashboard Cite

We argue that it is useful to distinguish between three key goals of personality science—description, prediction and explanation—and that attaining them often requires different priorities and methodological approaches. We put forward specific recommendations such as publishing findings with minimum a priori aggregation and exploring the limits of predictive models without being constrained by parsimony and intuitiveness but instead maximizing out–of–sample predictive accuracy. We argue that naturally occurring variance in many decontextualized and multidetermined constructs that interest personality scientists may not have individual causes, at least as this term is generally understood and in ways that are human–interpretable, never mind intervenable. If so, useful explanations are narratives that summarize many pieces of descriptive findings rather than models that target individual cause–effect associations. By meticulously studying specific and contextualized behaviours, thoughts, feelings and goals, however, individual causes of variance may ultimately be identifiable, although such causal explanations will likely be far more complex, phenomenon–specific and person–specific than anticipated thus far. Progress in all three areas—description, prediction and explanation—requires higher dimensional models than the currently dominant ‘Big Few’ and supplementing subjective trait–ratings with alternative sources of information such as informant–reports and behavioural measurements. Developing a new generation of psychometric tools thus provides many immediate research opportunities. © 2020 European Association of Personality Psychology

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Identifying the research priorities for schema therapy: A Delphi consensus study

Pilkington

Younan

Karantzas

2022

Clin Psychology and Psychoth

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Despite the popularity of schema therapy, there exist several important gaps in research on the schema therapy model and its effectiveness. The number of gaps makes it difficult to determine the research areas of the highest strategic priority to advance schema therapy. The objective of this study was to establish consensus among schema therapy clinicians and researchers on the priority areas for future schema therapy research. A panel of experts in schema therapy (43 clinicians and 13 researchers) participated in a Delphi consensus study. The research areas rated were developed by interviewing the founder of schema therapy, Jeffrey Young, conducting a focus group with the executive board of the International Society for Schema Therapy and screening recent reviews on schema therapy for recommendations for future research. The panel rated 81 research areas in terms of priority across three rounds. Nineteen research areas were rated by 75% of the panel as ‘Very high priority’ or ‘High priority’. These priorities reflected four broad themes: (1) schema therapy constructs and measures, (2) the theoretical assumptions underlying schema therapy, (3) schema therapy and theory in relation to different contexts and outcomes and (4) schema therapy effectiveness and mechanisms of change. The findings are important for establishing a clear research agenda for the future of schema therapy.

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Subjectifying the Personality State: Theoretical Underpinnings and an Empirical Example

Cited by 16 publications

References 110 publications

Descriptive, predictive and explanatory personality research: Different goals, different approaches, but a shared need to move beyond the Big Few traits

Descriptive, predictive and explanatory personality research: Different goals, different approaches, but a shared need to move beyond the Big Few traits

Descriptive, Predictive and Explanatory Personality Research: Different Goals, Different Approaches, but a Shared Need to Move beyond the Big Few Traits

Identifying the research priorities for schema therapy: A Delphi consensus study

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