2. Save the text file and then open it in SPSS.
3. Name the variables subject, begin, end, move, and case.
4. Sort the data by move in an ascending way: Data > Sort Cases.
5. Highlight all rows containing irregular units and delete them.
6. Sort the data by case and begin: Data > Sort Cases.
7. From the menus choose: Transform > Recode into Different Variables. Se-
lect the variable subject. Enter partner as an output variable name. Click Old
and New Values. Recode all movements of person A in “1” and of person B
in “2”. (A_rh_Structure_RX = 1, A_lh_Structure_RX = 1, B_rh_Structure_RX
= 2, B_lh_Structure_RX = 2)
8. Copy the variable partner. Name the new variable copy_partner.
9. Shift the values in the variable copy_partner one cell down. (Cut the values,
than paste them one cell down).
332
10. From the menus choose: Transform > Compute Variable. Enter the name
of the new variable into the box Target variable: partner_turn. Compute:
partner – copy_partner. The values “1” and “-1” indicate now the partner,
who takes the turn. “1” denotes that partner B takes turn and “-1” that part-
ner A takes turn. In the “0” cases there was no switch between the partner’s
moves.
Turn-taking is defined as a beginning of a movement unit relative to the move-
ment of the partner. In an overlapping turn-taking partner A begins to move dur-
ing the movement of partner B (or vice versa). In a subsequent turn-taking the
movement of partner A (or partner B) starts after the end of a partner’s move-
ment. So the turn-takings (TT) of partner A are calculated to the following for-
mula: TT_A = Begin_A – End_B, and for partner B accordingly: TT_B = Be-
gin_B – End_A. To compute these relations with SPSS both subtraction values
must be in a same row. To achieve this proceed as follows accordingly:
11. Copy the variable end. Name the new variable copy_end. Shift the values in
copy_end one cell down (cut the values, then paste them one cell down).
12. Copy the variable case. Name the new variable copy_case. Shift the values
in copy_case one cell down. For the further procedure the values must be
(convert to) numerical.
13. Calculate the turn-taking. From the menus choose: Transform > Compute
Variable. Enter the name of the new variable: turn_taking. Compute:
(begin – copy_end) / 1000. Select the function IF. Activate the field Include
if case satisfies condition: case - copy_case = 0. Continue and click on OK.
Now you have the overlapping time between two movements in seconds.
Negative values represent the overlapping time of two movements and posi-
tive values represent the time interval between the end of a movement and
the begin of the subsequent partner’s move.
14. Delete the first and the last row.
15. To filter the valid turn-takings from the menus choose: Transform > Re-
code into Same Variable. Choose the turn_taking variable. Select the func-
tion: If. Activate the field Include if case satisfies condition: Give the for-
mula: partner_turn = 0 and click on Next. Click Old and New Values. Re-
code All other values to System missing values.
333
Now only the values for the switches between the partner’s moves are left in the
turn-taking variable.
334
16. For graphic presentation of the turn-taking choose from the menus: Graphs
> Legacy Dialogs > Histogram. Choose the variable turn_taking. Check the
box Display normal curve and click OK.
17. If you need to adjust the scaling: open the diagram editor with double-click
on the histogram.
18. Double-click on the scaling values opens a new edit window:
335
18.4.3 Procedure for calculating Interactive Overlap
The advantage of this procedure is that it is less hypothesis-bound. All units are
considered. As an example, this method provides information how how much
time both partners spent with the (same) behaviour. The only disadvantage is
that no precise data about the time between the end of a unit and the beginning
of the next unit can be obtained. To achieve the interactive overlap values, pro-
ceed as follows:
1. Open the file in ELAN.
2. From the menu choose Tier -> Create Annotations from Gaps
Select the source tier. It can be on Activation, Atructure, or Focus level, or
any other level you want to explore. Choose Specific value. Name it: rest.
Click OK. Repeat this for all relevant tiers. Close the window.
3. If you have coded only a part from the video (e. g. only the first 5 minutes),
delete the rest-units for the first and after the last movement unit, or adjust
their length to the length of the coded part. Otherwise there will be two long
rest-units at the beginning and the end of the coded section.
4. Choose Tier -> Create Annotations from Overlaps (Classic)
Select the 2 source tiers.
336
Name the destination tier, e.g. A_rh_B_rh_equal_overlap (A and B refer to the
participants).
Select a linguistic type: Notes.
Select the options: Concatenate the values of overlapping annotations and
Only process if the overlapping annotations have the same value.
Click Finish.
5. Repeat the previous steps for the relations A_left hand – B_left hand, A_right
hand – B_left hand, and A_left hand – B_right hand.
337
6. For better clarity, you can delete the rest-units in the source tiers.
Choose Tier -> Remove Annotations or Value.
Select the source tiers. Choose: Annotations where value is ... rest. Click OK.
7. The overlap of the movement units represents the overlapping turn takings.
The overlap of the rest units represents the subsequent turn takings.
8. Under View -> Annotation Statistics you can see the values of occurrences
and duration, from which you can calculate the proportion of overlapping and
subsequent turn takings to the movements of each participant.
9. The option Create Annotations from Overlaps is also available for multiple
file processing. If you analyze more than one file, do step 1 – 4 for all files
separately and then choose File -> Multiple File Processing -> Annotations
from Overlaps.
10. Select files from domain > New Domain… > Add Folder… /Add File…
Select the tiers to overlap (see 5.) and go to Next.
Choose the option And their annotation values are equal and go to Next.
Enter the name of the destination tier (see 5.) and select Notes – free values
for a linguistic type. Go to Next.
Select the option: Concatenate the values of overlapping annotations.
Click Finish.
338
18.4.4 The Formal Matching category
The Formal Matching is assessed as (i) same value, or (ii) different value. To
achieve these values, proceed as follows:
First, determine the complete overlap. This procedure determines how often and
how long simultaneous movement generally occurs in the interaction. Specific
values of the gestures are not considered at this point. Since the coding in Mod-
ule 1 is done separately for both hands, now several steps are necessary to merge
the movements of the right and left hand.
1. Use the function Create annotations from overlaps and choose the tiers
A_rh_Focus right-hand-tier of Person A and of Person B. Possible tier-name:
rh_rh.
2. (see above) Choose left-hand-tier of Person A and Person B. Possible tier-
name: lh_lh.
3. Use the function Merge tiers and merge the two new tiers of Step 1 and 2.
The results are all annotations of the movements, which happened
simultaneously with the same hand. Possible tier-name: homo_overlap.
4. (See Step 1 and 2) Choose right-hand-tier of Person A and left-hand-tier of
Person B. Possible tier-name: rh_lh.
5. Choose left-hand-tier of Person A and right-hand-tier of Person B. Possible
tier-name: lh_rh.
6. (See Step 3) Merge the tiers of Step 4 and 5. The results are all annotations of
movements, which happened simultaneously with the contralateral hand.
Possible tier-name: hetero_overlap.
7. Merge the tiers homo_overlap and hetero_overlap. The results are all
annotations of movements, which happened simultaneously. Possible tier-
name: complete_overlap.
Determine the overlaps of units with the same Structure or StructureFocus
value
To analyze the actual quality of simultaneous movements, all overlaps in the
same gestural category should be established.
Repeat Steps 1 to 7 by using the option Only process if the overlapping anno-
tations have the same value.
339
It is necessary to give these new tiers other names so that they differ from the
tiers coded before. Possible tier-name: SV_rh_lh (SV for same value).
Determine the overlaps of units with different Structure or StructureFocus
values
To get an additional variable that gives information about the degree of quality
of simultaneous movements, all overlaps in different gestural categories can be
identified.
1. Export the tiers complete_overlap and SV_overlap into the program Microsoft
Excel.
2. Substract SV_overlap from complete_overlap.
In this way all overlaps of movement occurring simultaneously in a different
gestural category can be gathered. Possible tier-name: DV_overlap (DV for dif-
ferent value). The three values complete_overlap, SV_overlap and DV_overlap
can be put into a procentual relation to each other now.
Determine overlaps for specific values
To get more distinguished information about the SV_overlap, the program
ELAN provides the possibility to identify overlaps for specific values. It can be
detected in which values overlaps occur often and in which they occur rarely.
Furthermore, this function can be used for analysis, focussing on one value only,
e.g. irregular on body.
1. Accomplish Steps 1 to 7 using the option: Only process if the overlapping
annotations have the same value.
2. Additionally use the option: Only if the value is: ... and enter the gestural
category you want to analyze.
References
Ambady, N., & Rosenthal R. (1992): Thin slices of expressive behavior as pre-
dictors of´interpersonal consequences: A meta-analysis. Psychological Bulletin,
111, S.256-274.
Beebe, B., Gerstman, L., & Carson, B. (1982). Rhythmic Communciation in the
Mother-Infant Dyad. In: Davis M. Interaction Rhythms. New York: Human Sci-
ences Press, 79-100.
340
Bernieri, F.J. (1988). Coordinated movement and rapport in teacher-student in-
teractions. Journal of Nonverbal Behavior, 12, 120-138.
Bernieri, F.J., & Rosenthal, R. (1991). Interpersonal coordination: behaviour
matching and interactional synchrony. In R. S. Feldmann & B. Rimé (Eds.),
Fundamentals of nonverbal behaviour (pp. 401-432). Cambridge, England:
Cambridge University Press.
Bernieri, F.J., Davis, J., Rosenthal, R., & Knee, C. (1994). Interactional syn-
chrony and rapport: Measuring synchrony in displays devoid of sound and facial
affect. Personality and Social Psychology Bulletin, 20(3), 303-311.
Borkenau, P., & Ostendorf, F. (1993). NEO-Fünf-Faktoren-Inventar (NEO-FFI)
nach Costa und McCrae. Göttingen: Hogrefe.
Bouhuys, A.L., & Sam, M.M. (2000). Lack of coordination of nonverbal behav-
iour between patients and interviewers as a potential risk factor to depression
recurrence: vulnerability accumulation in depression. Journal Affective Disor-
ders ; 57: 189-200.
Chartrand, T.L., & Bargh, J.A. (1999). The chameleon effect: The perception-
behavior link and social interaction. Journal of Personality and Social Psychol-
ogy, 76, 893-910.
Condon, W.S., & Ogston, W.D. (1966). Sound film analysis of normal and
pathological behaviour patterns. The Journal of Nervous and Mental Disease;
143(4), 338-347.
Condon, W.S., & Brosin, H.W. (1969). Micro Linguistic-Kinesic Events in
Schizophrenic Behaviour. In: McQuown, N. A. (ed.): The natural history of an
interview. Chicago: University of Chicago, 812-837.
Davis, M. (1982). Interaction Rhythms: Periodicity in Communicative Behavior.
New York: Human Sciences Press.
Davis, M. (1986). Nonverbal Behavior Research and Psychotherapy. In:
Stricker, G., Keisner, R. H. (eds.): From Research to Clinical Practice. New
York: Plenum Press.
Denissen, J. (2005). Understanding and being understood: The impact of intelli-
gence and dispositional valuations on social relationships (doctoral dissertation,
Humboldt-University, 2005), from http://edoc.hu-berlin.de/dissertationen/ denis-
sen-jacobus-josephusadrianus-2005-07-08/PDF/Denissen.pdf
341
Dvoretska, D., Denissen, J., & Lausberg, H. (2013). Kinesic Turn Taking and
Mutual Understanding in Interactive Dyads. Conference Proceedings, TiGeR
2013, 06 / 2013, Tilburg.
Kestenberg, J. (1965a). The role of movement patterns in development I. The
Psychoanalytic Quarterly, 24(1), 1-36.
Kestenberg, J. (1965b). The role of movement patterns in development II. The
Psychoanalytic Quarterly, 24(4), 515-63.
Kestenberg, J. (1967). The role of movement patterns in development III. The
Psychoanalytic Quarterly, 26(3), 356-409
Kestenberg, J, & Sossin, M. (1979). The Role of Movement Patterns in Devel-
opment II. New York: Dance Notation Bureau.
La France, M., &. Broadbent, M. (1976). Group rapport: Posture sharing as a
nonverbal indicator. Group and Organization Studies, 1, 328-333.
La France, M. (1982). Posture Mirroring and Rapport. In: Davis, M. Interaction
rhythms: Periodicity in Communicative Behavior. New York: Human Sciences
Library.
Lakin, J.L., Jefferis, V.E., Cheng, C.M., & Chartrand, T.L. (2003): The chame-
leon effect as social glue: evidence for the evolutionary significance of noncon-
scious mimicry. Journal of Nonverbal Behaviour, 27, S. 145-162.
Lausberg, H. (2007). When we speak, we gesture – How gesture reflects and
affects individual and interactive cognitive processes. Unpublished paper pre-
sented at the Scientific Colloquium of the Center of Lifespan Psychology, Max
Planck Institute for Human Development, Berlin.
Lausberg, H., & Kryger, M. (2011). Gestisches Verhalten als Indikator thera-
peutischer Prozesse in der verbalen Psychotherapie: Zur Funktion der Selbstbe-
rührungen und zur Repräsentation von Objektbeziehungen in gestischen Darstel-
lungen. Psychotherapie-Wissenschaft, 1, 41-55.
Lausberg, H. (2011). Das Gespräch zwischen Arzt und Patientin: Die bewe-
gungsanalytische Perspektive. Balint Journal 12, 15-24.
Provine, R.R. (1986). Yawning as a stereotyped action pattern and releasing
stimulus. Ethologie, 72, 109-122.
342
Provine, R.R. (1992). Contagious laughter: Laughter is a sufficient stimulus for
laughs and smiles. Bulletin of the Psychonomic Society, 30, 1-4.
Sacks, H, Schegloff, E.A., & Jefferson, G. (1974). A simplest systematics for
the Organisation of Turn Taking for Conversation. Languages, 50, 696-735.
Scheflen, A.E. (1964). The significance of posture in communication systems.
Psychiatry, 27, 316-331.
Scheflen, A.E. (1973). Communicational Structure: Analysis of a Psychotherapy
Transaction. Bloomington: Indiana University.
Weilhammer, K., & Rabold, S. (2005). Durational Aspects in Turn Taking. Psy-
chonomic Bulletin and Review 12(6).
343