Self Esteem Ninot

7/30/2019 Self Esteem Ninot

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Dynamical approach and self-esteem

Grgory NINOT

Professor (PhD)

Laboratory EA4206 Addictive, Performance and Health Behaviors

www.performance-sante.fr

[email protected]

Thanks to Didier Delignires, Marina Fortes, Christophe Gernigon, Jean Bilard, Grgory Moullec, Johana Monthuy-Blanc,

Jacques Birouste, Yannick Stephan, Christophe Maano


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1 - Theories of self-esteems functioning

2 - Perspectives in the dynamical approach

3 - Applications in psychology

Plan


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psychological variables

Inter-individual variability

QUESTIONNAIRE Date : ............Nom : ....................... Prnom : ....................... Age : ............. Sexe : .............

CONSIGNES

Dans ce questionnaire, vous trouverez 25 phrases qui expriment des sentiments, des opinions oudes ractions. Lisez attentivement chacune de ces phrases. Pour chaque phrase, encerclez une rponse

entre cela me ressemble Pas du tout (1), Trs peu (2), Un peu (3), Assez (4), Beaucoup (5), Tout fait (6)

Ef for cez-vous de rpondr e toutes les phrases. Sachez qu'aucune rponse n'est juste, elle doit

tre avant tout personnelle.

Cela me ressemble...Pasdutout

trspeu

Unpeu

Assez Beaucoup Tout fait

1. J'ai une bonne opinion de moi-mme -------------------------- -1- -2- --3-- ---4--- ----5---- --6--

2. Globalement, je suis satisfait de mes capacits physiques -- -1- -2- --3-- ---4--- ----5---- --6--

3. Je ne peux pas courir longtemps sans m'arrter --------------- -1- -2- --3-- ---4--- ----5---- --6--

4. Je trouve la plupart des sports faciles -------------------------- -1- -2- --3-- ---4--- ----5---- --6--

5. Je n'aime pas beaucoup mon apparence physique ------------ -1- -2- --3-- ---4--- ----5---- --6--

6. Je pense tre plus fort que la moyenne ------------------------- -1- -2- --3-- ---4--- ----5---- --6--

7. Il y a des tas de choses en moi que j'aimerais changer ------- -1- -2- --3-- ---4--- ----5---- --6--

8. Je suis content de ce que je suis et de ce que je peux fairephysiquement ------------------------------------------------------- -1- -2- --3-- ---4--- ----5---- --6--

9. Je serais bon dans une preuve d'endurance ------------------- -1- -2- --3-- ---4--- ----5---- --6--

10. Je trouve que je suis bon dans tous les sports ----------------- -1- -2- --3-- ---4--- ----5---- --6--

11. J'ai un corps agrable regarder -------------------------------- -1- -2- --3-- ---4--- ----5---- --6--

12. Je serais bon dans une preuve de force ----------------------- -1- -2- --3-- ---4--- ----5---- --6--

13. Je regrette souvent ce que j'ai fait ------------------------------ -1- -2- --3-- ---4--- ----5---- --6--

14. Je suis confiant vis--vis de ma valeur physique ------------- -1- -2- --3-- ---4--- ----5---- --6--

15. Je pense pouvoir courir longtemps sans tre fatigu --------- -1- -2- --3-- ---4--- ----5---- --6--

16. Je me dbrouille bien dans tous les sports --------------------- -1- -2- --3-- ---4--- ----5---- --6--

17. Personne ne me trouve beau ------------------------------------- -1- -2- --3-- ---4--- ----5---- --6--

18. Face des situations demandant de la force, je suis lepremier proposer mes services --------------------------------- -1- -2- --3-- ---4--- ----5---- --6--

19. J'ai souvent honte de moi ---------------------------------------- -1- -2- --3-- ---4--- ----5---- --6--

20. En gnral, je suis fier de mes possibilits physiques ------- -1- -2- --3-- ---4--- ----5---- --6--

21. Je pourrais courir 5 km sans m'arrter ------------------------- -1- -2- --3-- ---4--- ----5---- --6--

22. Je russis bien en sport ------------------------------------------- -1- -2- --3-- ---4--- ----5---- --6--

23. Je voudrais rester comme je suis -------------------------------- -1- -2- --3-- ---4--- ----5---- --6--

24. Je suis bien avec mon corps ------------------------------------- -1- -2- --3-- ---4--- ----5---- --6--

25. Je ne suis pas trs bon dans les activits d'endurance tellesque le vlo ou la course ------------------------------------------- -1- -2- --3-- ---4--- ----5---- --6--

Merci d'avoir rpondu ce questionnaire

Self-esteem :

Level (i.e. Baumeister, 1993)

2

4

6

8

1

0

0

behavior variables

a conscious self-assessment


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psychological constructsbehavior


Multidimensional models well-being (i.e. Diener, 1984)

Self-esteem : a conscious self-assessment

Level

motivation(i.e. Vallerand, 1997; Eliot, 2007)

perceived competence


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Fox et Corbin (1989) : Physical Sel f Percept ion Prof i le

Physical conditionSport

competenceAttractive body Physical strengh

Hierarchical model

Physical self-worth

Multidimensional

model

Global self-esteem


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Experimental design transversal

longitudinal

Multidimensional modelswell-beingmotivationperceived competence


Levelpsychological constructsbehavior


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Experimental designtransversal

longitudinal

Intrinsic dynamics (functioning overtime)? 3 hypotheses(Strelau, 2001)

Multidimensional modelswell-beingmotivationperceived competence


Levelpsychological constructsbehavior


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0

1

2

3

4

5

6

7

8

9

10

0

1

2

3

4

5

6

7

8

9

10

Homeostasis

0

1

2

3

4

5

6

7

8

9

10

Emotional state

0

1

2

3

4

5

6

7

8

9

10

Sociometer

0

1

2

3

4

5

6

7

8

9

10


Trait

Dispositional(i.e. Coopersmith, 1967;Epstein, 1979; Swann et al.,

1987)

State

Situational(i.e. Butleret al., 1994; Leary etal., 1995; Heartherton, 1991)

Steady state

Interactionist(i.e. Headey & Wearing,1991; Rosenberg, 1986)

Self-schema

Security base

0

1

2

3

4

5

6

7

8

9

10


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Nomothetical approach

Psychometric aspects- Long instruments ( > 25 items)

- Weak sensitivity (< likert 7)

- Classical rule neglects time (Prigogine, 1994)

- Level (attitudes + social stereotype)

Theoretical aspects

- Few repeated measures (< 6)

- Plenty of subjects required (n > 100)

- Gaussian statistics

Methodological aspects

no change of level

after 30 years o

(McCrae & Costa, 1994)

trait ?

0

1

2

3

4

5

6

7

8

9

10


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Plan


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Intra-individual variability

auto-correlation

yt = f(yt-1)

Dynamics (Nowak & Vallacher, 1998)

4

5

6

7

8

3

Days

y y + 7 days

Instability (Kernis et al., 1991; Showers et al., 1998; Nezlek, 2002)

standard deviation

range


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Nomothetic approach

- Neglecting time

- Level

Historicity (Nowak & Vallacher, 1998)

Level+ instability + dynamics

Rate = fruit of a complex system

Idiographic approach

Psychometric aspects

Theoretical aspects

Methodological aspects

- Few repeated measures

- Several subjects

- Gaussian statistics

Best witness of self = self

Time series analyses

Cellular automata (Nowak et al., 2000)

- Long instruments

- Weak sensitivity

Brief instrument (Robins et al., 2001)

High sensitivity (VAS)


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Example of protocol design

Globally, you have a good opinion of yourself

Not at all Absolutely

6,5 cm

- Measure error item

- Random presentation of items

Experimental design

- Self-assessment twice a day (7:00 9:00 AM and PM)

Time series analysis

- ACF, Autoregressive Integrated Moving Average, fractal analyses

Instrument

- Physical Self Inventory (6a)

5

6

7

8

9

10

avr mai

10

0

- Personal zone of comment


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0

1

2

3

4

5

6

7

8

9

10

0

1

2

3

4

5

6

7

8

9

10

0

1

2

3

4

5

6

7

8

9

10

0

1

2

3

4

5

6

7

8

9

10

0

1

2

3

4

5

6

7

8

9

10

Hypotheses of intrinsic dynamics of SE

Trait

Dispositional(Coopersmith, 1967; Epstein,1979; Swann et al., 1987)

State

Situational(Butleret al., 1994; Leary et al.,1995; Heartherton, 1991)

Steady state

Interactionist(Headey & Wearing, 1991Rosenberg, 1986)

0

1

2

3

4

5

6

7

8

9

10


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Dispositional theories of self-esteem : traitRandom fluctuations around a stable reference value

Fixed-point attractor

ARIMA

ACF NS (0,0,0) : yt = + t White noiseACF Fractal analys


0 100 200 300 400 500

10

0

I t i di id l i bilit


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0 100 200 300 400 500

Situational theories : state

Accumulation of uncorrelated displacements

Undetermined dynamics

p< .05 (0,1,0) : yt = yt-1 + t Brownian moti

ARIMAACF Fractal analys


10

0

I t i di id l i bilit


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0 100 200 300 400 500

Interactionist theories : steady state

Relaxation oscillations around a fixed point attractor

Fixed-point attractor

p< .05 (1,0,0) + cst : yt = + yt-1 + t Homeostas

ARIMAACF Fractal analys


10

0

Intra individual variability


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4

5

6

7

8

9

10

avr mai juin juil aot sept

B : Man, 29 years old




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ACF



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ACF



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4

5

6

7

8

9

10


A : Man, 32 years old




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F : Woman, 26 years old

4

5

6

7

8

9

10





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Instability (SD, Range, ADM)

- SE fluctuates more than measure error item (Ninot et al., 2004; 200

- Inter-individual difference (Kernis et al., 1993; Nezlek, 2002)

Historicity (ACF)

ACF :

- Short term historicity continuity of self(Tap, 1980; Tesseret al., 19

resistance to change (Vallacher & Nowak,2005; Vallacheret al., 2002; Knowles & Lin, 200

self-verification (Swann, 1990) personality (McCrae & John, 1992)


ARIMA ?



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ARIMA model obtained in adults (p < .001)

364

Ninot et al. (2005) JP

8

Observations

ARIMA (0,1,1)

Publication

n

6 months

8 / 8

728

48 / 48

8

1024

Delignires et a

(2004) NDPLS

4

1 year 512 days (17m

7 / 4824 / 24

Ninot et al. (2004) IDR



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y

ARIMA model obtained in 8 adults (p < .001)

51

Ninot et al. (in press a)

Experimental

4.15 hours

Ninot et al. (2004) IDR

41 / 48 (0,0,0) : yt = + t



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Moving average model ARIMA (0,1,1) without significant constant

yt = yt-1 -t-1+ t

Value at time t

Value at time t-1 Fraction of the

perturbation at

time t-1

Perturbation at time t

Mathematically: random variations around local value changing slowly

y



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A local equilibrium around a slowly varying reference value

Dynamical adjustment (Ninot et al., 2004, 2005; Delignires et al., 2004)

Random event(s)

y

t = y

t-1 -

(t-1) +

t

Adaptation to

perturbation

Preservation

Balance (0.0 1.0)

y

Without significant constant



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Dynamics

ARIMA :

- Same dynamics (whatever hierarchical level or subject) : (0,1- SE evolves slowly under influence of life events

- determines the balance between preservation and adaptatio

Instability

- Self-esteem > measure error item

- Inter-individual differences

Historicity

ACF :

- Short term historicity continuity of self



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0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 15 30 45 60 75 90

Lag

A

uto-correlation

Exemple of an ACF for self-esteem series

Intra-individual variability (Delignires et al., 2004, NLDPLS)


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1 1024

Observations1

Observations

1 1024

Observations

1

Observations

Spectral analysis: double logarithmic plot of power against frequency, Rescaled Range Analys

Dispersional Analysis, Scaled Windowed Variance Method (Eke et al., 2001)

Intra-individual variability (Delignires et al., 2004, NLDPLS)


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-3.5 -3 -2.5 -2 -1.5 -1 -0.5 0

log(Frquence)

log(Puissance)

-3.5 -3 -2.5 -2 -1.5 -1 -0.5 0

log(Frquence)

log(Puissance)

-3.5 -3 -2.5 -2 -1.5 -1 -0.5 0

log(Frquence)

log(Puissance)

-3.5 -3 -2.5 -2 -1.5 -1 -0.5 0

log(Frquence)

log(Puissance)

=1.17

=1.09=0.96

=1.13



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Dynamics

Fractal analyses 1/ f:- time series of SE and PS present fractal properties

- SE acts as a complex dynamical system, composed of

multiple, interconnected elements (Vallacher et al., 2002)

- Self-similar properties (auto-similarity): each level presents acomplexity similar to that observed at higher levels (MarksTarlow, 1999)



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- 1/fnoise

ubiquitous phenomenon in biological systems

(West & Shlesinger, 1990)

intrinsic properties of stability and resistance to perturbations

(Schmidt et al., 1991)

characteristic signature of adaptive, young and healthy syste

(Haussdorf et al., 1997)

Dynamics

Fractal analyses :

- Fractal properties of SE and physical self

- SE = complex dynamical system, interconnected elements

- Auto-similarity



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0 100 200 300 400

Trait State Steady state0 100 200 300 400 500 0 100 200 300 400 500

1

2

3

4

5

6

7

8

9

10

Oct

NovDe

cJanFe

bM

ar AprM

ay Jun Ju

lAu

gSe

pOct

NovDe

cJanFe

bM

ar AprM

ay Jun Ju

lAu

gSe

pOct

NovDe

c



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0 100 200 300 400

Trait State Steady state0 100 200 300 400 500 0 100 200 300 400 500

1

2

3

4

5

6

7

8

9

10

Oct

NovDe

cJanFe

bM

ar AprM

ay Jun Ju

lAu

gSe

pOct

NovDe

cJanFe

bM

ar AprM

ay Jun Ju

lAu

gSe

pOct

NovDe

c

Dynamicaladjustment :- Preservation vs. adaptatio

- Metastable state

- Disequilibrium equilibriu

Plan


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3 - Applications in psychology

Applications


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1 Dynamics of each element

Time

Instability = vulnerability ? (Ninot et al., 2006, JSS)


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More people place importance on physical competence an

attractiveness as determinants of self-worth, the more the

feelings of self-worth fluctuate (Kernis et al., 1993)

0

1

2

3

4

5

6

7

8

9

10

1 15 29 43 57 71 85 99 113 127 141 155

Sedentary adult (22 years old)

0

1

2

3

4

5

6

7

8

9

10

1 15 29 43 57 71 85 99 113 127 141

Triathlon athlete (22 years old

J 17 ld t i ti i

Prevention of withdrawal


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J., 17 years old, restrictive anorexia

J 17 ld t i ti i

Prevention of withdrawal


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J., 17 years old, restrictive anorexia

0

1

2

3

4

5

6

7

8

9

10

sept-06 d

Compliment

by father Exercise

Bring upFailure

school

ExerciseWeight loss

Weight

increase

Sept-06 Dec-06

Comparison of intrinsic dynamics (Moullec et al., submitted)


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Proportion of ARIMAs model (GSE, PSW, anxiety, depression)

Depressive patients(n = 14; 51.9 13.9)

7,8%

Young adult(n=21; 25.2 4.0)

58,2%

7,7%

15,4%

18,7%

Elderly(n=19; 60.8 10.7)

85,3%

2,0%

4,9%

8,6%

21,4%

31,4%

28,6%

10,0%

28,6%

32,1%

25,0%

12,5%

1,8%

COPD patients(n=11; 62.5 9.7)

Auto-regressive Moving average

(0,1,0)

AR (x,1,0)

AR (x,0,0)

AR (x,0,0) + c

(0,0,0)

MA (0,1,x)

Intra-individual prevision (Ninot et Fortes, 2007)


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1

2

3

4

5

6

7

8

9

10

OctNo

vDe

cJanFe

bM

ar AprM

ay Jun Ju

lAu

gSe

pOc

tNo

vDe

cJanFe

bM

ar AprM

ay Jun Ju

lAu

gSe

pOc

tNo

vDe

c

p

yt = f(yt-1) + t

p

(p < .001

Applications


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1 Dynamics of each element 2 Evolution of the model

PC

PSWGSE

SC AB PS

Time

GSE GSE

Causal flow (Fortes et al., 2004; Ninot et al., submitted)


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Bottom-up (Byrne, 1996; Harter, 1998)

PC SC AB PS

GSE

PSW

PC SC AB PS

GSE

PSW

Top-down (Brown, 1998)

Horizontal (Marsh & Young, 1998)

PC SC AB PS

GSE

PSW

PC SC AB

GSE

PSW

1 2

Reciprocal (Fiest et al., 1995)

PC SC AB PS

GSE

PSW

Applications (research report, Ninot, 2005)


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Case study

Man, 35 years, incomplete paraplegia, single, police agent

EG VPP

Numrosdepassation

aeurcoesur

1

2

3

4

5

6

7

8

9

0 10 20 30 40 50 60 70 80 90 100

GSE PSW

VAS

(0-10)

Bottom-up

PC SC AB PS

GSEPSW

Observations

1 D i f h l t 2 E l ti f th d l

Applications


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3 - Impacts on the model

2 - Evolution of the model

Constraint

Temps

PC

PSWGSE

SC AB PS

Method

Applications (Ninot et al., 2007, Disability & Rehabilitation)


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Results

Time

0

1

2

3

4

5

6

7

8

9

10

1 15 29 43 57 71 85 99 113 127 141 155

VAS

score

respiratory rehabilitation

Method

12 weeks including 4 weeks of respiratory rehabilitation

23 COPD patients

1 Dynamics of each element 2 Evolution of the model

Applications


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c - Impacts on the model

2 Evolution of the model

4 - Relation with biological variable10

5

0

100

50

0

Temps

Constraint

PC

PSWGSE

SC AB PS

Applications (Monthuy-Blanc et al., in preparation)

BMI relatively low and stable Brutal decrease


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0

1

2

3

4

5

6

7

8

9

10

Septembre Self-esteem instability Change of the dynamics

Time effect

BMI relatively low and stable Brutal decrease

of BMI

Documents

Self Esteem Ninot