Life recovery models: Cross overs between Kobe
and Great East Japan Earthquake
recovery stories
Shigeo TATSUKI1
1
Professor, Department of Sociology, Doshisha University, Kyoto, Japan
statsuki@mail.doshisha.ac.jp

ABSTRACT

Recovery of individual lives has never been a major post-recovery agenda until the
1995 Kobe Earthquake. The author has been involved in social research projects that
aimed to identify life recovery facilitating factors and its mechanism, and in the
advocacy of individual life recovery policy and programs. Based on these activities, theSeven Critical Element Model (SCEM) of life recovery was formed. The seven
facilitating factors consist of housing, social ties, community involvement,
physical/mental stress management, preparedness, livelihood, and relations togovernment. After the 2011 Great East Japan Earthquake, the author has been closely
working with the life recovery department of Natori city, Miyagi prefecture. This paper
reports the results of the 2015 population survey of Natori survivors (1,533 households,
3,513 individuals) and compares these results with Kobe Earthquake life recovery
surveys. It discusses the cross over between the two mega-disaster recovery findings,
and examines what can be utilized in order to formulate life recovery policies andprograms for future disasters.
Keywords: life recovery, Kobe Earthquake, Great East Japan Earthquake, Seven
Critical Elements model

1. INTRODUCTION
Life recovery as opposed to livelihood recovery is a relatively new and more holistic
construct. Although livelihood has been promoted by income assistance programs of the1998 Act Concerning Support for Reconstructing Livelihood of Disaster Victims, life
recovery has been interpreted in more vague terms. It had not been clearly spelled out
until Kobe city conducted the fifth year review on 1995 Kobe Earthquake recovery. As
a part of the review, a series of grass-roots recovery assessment workshops with
impacted citizens were held in order to identify factors that would help each participant
to feel that “I am no longer a disaster victim.” Out of this review, the Seven Critical
Elements Model (SCEM) of life recovery was formed. The seven facilitating elements
consist of housing, social ties, community involvement, physical/mental stressmanagement, preparedness, livelihood, and relations to government (Tatsuki, 2007).
After the 2011 Great East Japan Earthquake (GEJE), the author’s team has been closely
working with the life recovery support department of Natori city, Miyagi prefecture.
Our team collaborated with the Natori city administration to conduct the 2013 Natori

October 2015, Kathmandu, Nepal

grass-roots assessment workshops on life recovery, which later confirmed that SCEM
was also applicable to Natori people’s life recovery (Tatsuki, 2015a). The team and thecity then jointly designed the questionnaire and the city administered a population
survey on life recovery to all impacted citizens. The first purpose of this paper is to
examine if SCEM is empirically capable of predicting a large proportion of life
recovery variance as reported by Natori people. Second, it aims to identify thesimilarities and differences between the 1995 Kobe Earthquake and the 2011 GEJE in
terms of which critical elements were relatively more important to determine life
recovery in each respective event. Third, it tries to portray the unique aspects of life
recovery processes of the 2011 GEJE impacted citizens that were not found or reported
before.

2. METHOD
2.1 Subjects
The research subjects of the survey were all 1,533 households and their 3,513 members
over the age of 18 that were registered by Natori city as temporary housing residents.
The subject households included 1) those who were residing in Natori city prior to the
GEJE and 2) those who were residing outside (mostly in Fukushima) and had moved toNatori after the 311 Fukushima disaster. They were residing in two types of temporary
housing accommodation: conventional prefabricated temporary housing (PTH) complex
units or newly introduced designated temporary housing (DTH) units, which werenothing but private rental units paid for by the prefectural government. Provision of
DTH has become mainstream national policy since the GEJE, with 57,825
apartment/housing units rented and 47,839 prefabricated temporary housing units were
newly constructed in East Japan prefectures. As of December 2014, 55 % of temporary
housing households resided in DTH and 45 % in PTH in Natori city.
2.2 Instrument
The life recovery scale measures the degree to which one feels that he/she is no longer adisaster victim.
The scale is a 5 point Likert scale consisting of 6 life
readjustment/fulfillment, 7 life satisfaction and 1 future prospect items whose
unidimensionality and reliability (i.e., Cronbach’s α > .80) have been established in
Hyogo Life Recovery Surveys in 1999, 2001, 2003 and 2005 (Tatsuki, 2007).
Demographic variables included age, gender, family size, disability/vulnerability status,and house damage. With regard to SCEM, housing was measured by temporary
housing type (PTH or DTH) and concerns/worries about current and future housing
issues, social ties by the number of people having social conversation/contact pre andpost disaster, community involvement by a community outlook scale that measures thedegree of neighbors’ engagement in community affairs, physical/mental stressmanagement by a physical and psychological stress scale, preparedness by concerns for
future disaster risk, livelihood by financial impact and leeway scales as well as
occupation pre and post disaster, relations to government by a communitarian/liberal
attitude scale as well as levels of awareness on and attention to local government PR
information. In addition, 1 impact alleviation and 2 event evaluation items were used tomeasure life recovery process variables which were known to intervene between SCEM
and life recovery outcomes (Tatsuki, 2007).

New Technologies for Urban Safety of Mega Cities in Asia

2.3 Procedures
The survey questionnaire package consisted of a 2-page household questionnaire and 6
sets of a 4-page household member questionnaire. Both household and its member
questionnaires were included in an official Natori city envelope and were sent to all
registered temporary housing households during the second week of January in 2015.
Each household was asked to answer one household questionnaire and each household
member was asked to respond to an individual member questionnaire. A returnenvelope addressed to Natori city office was included in each package. Postcards
reminding the return of questionnaires were sent on January 26th. Furthermore, new setsof questionnaires were mailed again on February 19th to those households that had not
returned the questionnaires by February 5th. All those responses that arrived at the cityby the first week of March in 2015 were used for the analysis.
In order to compare the current study results with 2001 Hyogo Life Recovery Survey
results, a general linear model (GLM) was used to test and estimate the effects ofdemographic, SCEM and life recovery process variables on life recovery. SPSS version
23 was used for the statistical analyses.

3. RESULTS AND DISCUSSION
3.1 Demographics and house damage
1,107 (702 PTH and 831 DTH) households returned the household questionnaire(72.2 % response rate) and 1,971 (820 PTH and 1,151 DTH) residents returned thehousehold member questionnaire (56.1 % response rate). The average ages of the
respondents were 54.4 and 56.1 for males and females, respectively. The average ages
by temporary housing type was 59.8 and 52.1 for PTH and DTH, respectively
suggesting that nearly half of PTH residents were over the age of 60 while the majorityof DTH residents were working age, possibly with school age children.
Table 1: House damage by 2015 Natori and 2001 Hyogo Life Recovery Survey

Full Damage
Large Scale Half Damage
Half Damage
Partial Damage
No Damage
Missing
Total

2015 Natori Life
Recovery Survey
N1503( 76.3% )58( 2.9% )( 4.1% )
80

330
1971

( 16.7% )( 100.0% )2001 Hyogo Life
Recovery Survey
N
195( 16.2% )
231
554
223

( 19.2% )( 46.1% )( 18.5% )1203( 100.0% )Table 1 compares proportions of house damage categories between the two life
recovery surveys. While 2001 Hyogo Life Recovery Survey sampled those who wereresiding in the most severely earthquake-hit areas and therefore their house damages
varied widely from no damage to full damage, 2015 Natori Survey subjects wereheavily (almost 5 times higher) concentrated in the full damage category (those who did
not answer house damage were mainly those who moved from Fukushima) because
Natori survey specifically focused on those who lost their houses due to the 311 tsunami
and following Fukushima nuclear power plant disaster and were residing in temporary
housing units at the time of the survey. The damage comparison suggests that house
Life recovery models: What cross over between Kobe and Great East Japan Earthquake
recovery stories

October 2015, Kathmandu, Nepal

damage effects need to be partialed out before comparing SCEM effects on life
recovery between the two surveys.
Table 2: Multiple regression (GLM) analysis of house damage and SCEM effects on lifre recovery
Hazard Exposure and Seven Critical Elements for Life Recovery

Parameter
Model Intercept

Model 1B
51.438 ***Model 2B
51.454 ***Model 3B
48.161 ***.544 **-0.1662.058 *

1.384 **
-0.0082.173 **

1.305 ***
.067
2.039 *

HOUSE DAMAGE
Full House Damage
Large Scale Half House Damage
Half House Damage
No Answer

0a

0a

0a

HOUSING
Temporal Housing Type Prefabricated Temporary Housing (PTH)
Designated Temporary Housing (DTH)
Temporary Housing Type by Person with Disability PTM*No Disability
PTM*Disability
DTH*No Disability
DTH*Disability
Temporary Housing Type by Single Elderly Household PTH*Any Household Other Than Single Elderly Person Household
PTH*Single Elderly Person Household
DTH*Any Other Than Single Elderly Person Household
DTH*Single Elderly Person Household
Temporary Housing Type by Household with/without Physically Vulnerable Person PTH*Household with Physically Vulnerable Person
PTH*Household without Physically Vulnerable Person
PTH*Household with or without Physically Vulnerable Person Unknown
DTH*Household with Physically Vulnerable Person
DTH*Household without Physically Vulnerable Person
DTH*Household with or without Physically Vulnerable Person Unknown
Concerns about Housing Issues Scale Concerns/Worries about Public Housing (factor score)
Concerns/Worries about Current Temporary Living Arrangements (factor score)-0.870 *0a-0.746 (p =.107)
0a5.014 *
0a-.765
0a4.136 **
0a
-3.492 **0a-1.0290a
1.303
1.772 **
0a-1.252 *.084-0.420 *-0.337 *0a-.406 **-.338 *

1.819 **
2.728 ***
0.873

1.532 *
2.650 ***
0.759

1.516 *
2.812 ***
.820

0a-1.759 **-2.979 ***-1.626 ***0a-1.555 **-2.834 ***-1.593 ***0a-1.600 **-3.024 ***-1.522 ***0a2.832 ***
1.471
0.870

0a
2.980 ***
1.472
0.936

0a
2.908 ***
1.310
1.182

0a
-3.430 ***-0.737-0.4330a-3.588 ***-0.849-0.4570a-3.309 ***
-.840
-.742

0a
-3.133 ***0a-3.212 ***0a-3.425 ***Residents do not socialize but neghborhood representatives seem to be more or less active-3.320 ***-3.403 ***-3.632 ***Residents socialize to a certain degree and some greet each other
Residents socialize very often and participate well in community events-1.968 ***-1.966 ***-2.201 ***

0a

0a

0a

4.886 ***
2.463 ***

4.739 ***
2.299 ***

4.373 ***
2.231 ***

0a-2.656 ***0a-2.621 ***0a-2.598 ***SOCIAL TIES
Number of Neighbors/Relatives/Friends having social conversation with before 311 None
1 to 45 to 9more than 10
Number of Neghbors/Relatives/Friends having social conversation with after 311 None
1 to 45 to 9more than 10
Number of People meeting in hobby/circle/social gatherings before 311 None
1 to 45 to 9more than 10
Number of People meeting in hobby/circle/social gatherings after 311 None
1 to 45 to 9more than 10
COMMUNITY INVOLVEMENT
Residents do not socialize with each other and live by themselves

PHYSICAL/MENTAL STRESS MANAGEMENT
Subjective Evaluation on one's health condition GoodOK
Bad
Physical and Mental Stress Scale Physical and Mental Stress (factor score)
PREPAREDNESS
Concerns for Future Disaster Risks Low concerns for future disaster risk (optimal scaling score)

0.513 ***

0.496 **

-0.819 ***0.934 *
1.775
0.077
-1.945 **-0.849 ***0.909 (p =.103)
1.891
0.100
-1.673 **-.720 ***
.988 *
1.826-.025-1.724 **.474 **

0a-3.582 ***3.076 ***
1.907 **
-2.960 ***2.316 ***
-3.475 ***0a-3.547 ***3.074 ***
1.808 **
-2.807 ***2.168 ***
-3.306 ***0a-1.991 ***-4.402 ***-1.008 *-1.100 ***.098 ***-5.060 ***-0.316
0.541 ***
4.004 ***
.547 (.534)-0.327 (p =.103)
0.535 ***
3.944 ***
.548 (.534)-.362 *
.332 ***
3.885 ***
.555 (.538)

LIVELIHOOD
Financial Impact Score Household Financial Impact (optimal scaling score)
Financial Leeway Score Household financial Leeway (optimal scaling score)
Financial Leeway Score by Age Financial Leeway by Age less than 18
Financial Leeway by Age between 19 and 64
Financial Leeway by Age between 65 and 74
Financial Leeway by Age 75 and over
Occupation Proprietor (before)
Proprietor (present)
Retired (before)
Retired (present)
Unemployed (before)
Unemployed present
RELATION TO GOVERNMENTRECOVERY PROCESS

Relation to Government Scale Communitarian vs. Liberal Attitude Score (optimal scaling score)Attention to Local Government Public Relation Information Scale Low Attention to Local Government Public Relation Information (optimal scaling score)
Recovery Process Score (factor score)R 2 (df adjusted R 2)*** p <.01, ** p <.05, * p <.10

3.2 Effects of seven critical elements on life recovery
3.2.1 Model fit
Table 2 summarizes multiple regression (GLM) analysis results. It compares results of3 models where varying degree of housing parameters were successively added. In
Model 1, only temporary housing type (PTH or DTH) was entered. Concerns andworries about current and future housing issues were entered in Model 2, and finally
temporary housing type by social vulnerability (e.g., household with person withdisability, single elderly, or physically vulnerable person) interactions were added inModel 3. Although the interpretation of the housing variable parameters will be
discussed in the later section, it should be noted that the final Model 3 predicted highest
55.5 % of the total variance in observed life recovery scores (R 2 =.555, adjusted

New Technologies for Urban Safety of Mega Cities in Asia

R2=.538) compared with Model 1 (R2=.547, adjusted R2=.534) and Model 2 (R2=.548,
adjusted R2=.534). Figure 1 illustrates an observed by Model 3 predicted values plot at
16%
14%
12%

Observed

10%
8%
6%
4%

Predicted

2%0%Standardized Residual

Observed

Predicted

Standardized Residual
2001 Hyogo Life Recovery Survey N=1203

Figure 1: Observed by Model 3 predicted (top center) bystandardized residuals (bottom center) plot.

2015 Natori Life Recovery Survey N=1312

Figure 2: Comparisons of each SCEM parameter effectsize (partial η2) on life recovery between 2015 Natoriand 2001 Hyogo Life Recovery Surveys.

the top center which shows a linear fit. At the bottom center of Figure 1, standardized
residuals by predicted values were plotted, which showed that residuals were evenly
scattered against low to high predicted values without any particular patterns. Those
two plots displayed that the final Model 3 showed a good fit (R2=.555), which iscomparable to 2001 Hyogo Life Recovery Survey (R2=.470 (Tatsuki and Hayashi,2001) or R2=.593 (Tatsuki and Hayashi, 2002)), to the observed life recovery scores andtherefore affirmed the first research question − whether SCEM is capable of a large
proportion of life recovery score variance among Natori impacted people − of thecurrent paper.
3.2.2 Parameter effects on life recovery
Partial regression parameter estimates for house damage and each of SCEM were listed
at the last 3 columns of Table 2. Because the effects of other parameters were partialed
out when interpreting a given parameter, the effects of other parameters such as housedamage categories were controlled. This made it possible to compare SCEM
parameters between Natori and Hyogo Life Recovery Survey results despite that Natoristudy subjects were heavily skewed toward heavy house damages.
With regard to effects of housing parameter, Model 1 and 2 demonstrated that PTH on
average tended to have negative impacts on life recovery in comparison to DTH. This
seems to support the validity of the newly introduced DTH policy for prefecture
government’s renting privately owned housing units and designating them for disastersurvivors’ use as temporary housing units. It should be noted that Model 3 PTH
parameter became positive suggesting PTH rather than DTH tended to positively
promote life recovery. This reversal of effect direction from negative to positive could
be interpreted as the result of multicollinearity that were caused by entering 14
additional housing parameters (social vulnerability and temporary housing typeinteractions) into Model 3.
For such SCEM parameters as social ties, community involvement, physical/mental
stress management, preparedness and livelihood as well as intervening life recovery
process, their effect directions were similar to 2001 Hyogo Life Recovery Survey
results. With regard to social ties, those who used to socialize with more than 5neighbors/relatives/friends in daily conversations or in social gatherings before theLife recovery models: What cross over between Kobe and Great East Japan Earthquake
recovery stories

October 2015, Kathmandu, Nepal

disaster showed better life recovery. However, this threshold value increased to morethan 10 in order for socialization or social gathering to have positive impacts on betterrecovery after the disaster. While social ties are an ego-centric and personal social
capital indicator, community involvement measures levels of communal social capitalthat are shared by a network of people in a community as a whole. On this ground,
better life recovery was predicted only by those who reported that one lived in acommunity where “residents socialize very often and participate well in community
events.” With regard to a subjective evaluation of one’s own health, a measure ofphysical/mental stress management, those who reported “Good” or “OK” showedsignificant positive impacts on life recovery in comparison with those who answered“Bad.” These findings were further supported by more reliable measures of the 6 item
physical and mental stress scale scores. Preparedness was measured by how optimistic
one was to future disaster losses and the better recovery was predicted by the optimistic
attitudes to disaster risks. The similar effect was also observed in 2001 Hyogo Life
Recovery Survey. These results seem to support an old saying “danger past and God
forgotten.” Disaster’s impacts on household finance and the current financial leeway
were very strong livelihood predictors of life recovery. Those “younger” elderly
between 65 and 74 years old who showed less financial leeway were the least recovered
among all ages. With regard to occupation, the proprietors, the retired and theunemployed on average showed significantly lower life recovery scores. Finally, anintervening life recovery process measure, a composite of 1 impact alleviation and 2
event evaluation items, showed significant positive impacts upon life recovery as has
been demonstrated in 2003 and 2005 Hyogo Surveys (Tatsuki, 2007).
The 2015 Natori Life Recovery Survey like the 2001 Hyogo Life Recovery Survey
showed the tendency that the respondent’s attitude toward government (relation to
government) mattered. Unlike the Hyogo Survey, however, the less communitarian andmore self-reliance (liberal) oriented Natori temporary housing residents tended to show
better recovery. Nature of pre-disaster government-people relationships seems being
different between Natori and Hyogo areas and this difference needs to be further
examined in future studies.
The second research question of the current paper was to identify the similarities anddifferences between the 1995 Kobe Earthquake and the 2011 GEJE in terms of which
critical elements were relatively more important to determine life recovery in each
respective event. Figure 2 directly answers to this question. It compares effect sizes ofthe seven critical elements upon life recovery as measured by partial η2 between 2015
Natori and 2001 Hyogo Life Recovery Surveys. The direct comparison of η2 values in
two surveys should be supported because goodness-of-fit estimates were comparable in
2 studies (R2=.555 for Natori and R2=.470 (Tatsuki and Hayashi, 2001) or R2=.593(Tatsuki and Hayashi, 2002) for Hyogo surveys). Figure 2 illustrates that the top 3 mostpowerful influences upon life recovery were physical/mental stress management,
livelihood, and social ties in both surveys. Between-comparisons of effect sizes foreach parameter, however, indicated that livelihood as well as community involvement
mattered more in Natori survey while physical/mental stress management, social ties
and housing (housing variance was much smaller in Natori Survey because all subjects
lived in temporary housing units) were more valued in Hyogo survey. This may suggest
relative importance of livelihood assistance programs for Natori impacted citizens.
3.3 Designated versus prefabricated temporary housing

New Technologies for Urban Safety of Mega Cities in AsiaAt the onset of the GEJE, National government needed to provide more than hundred
Household with/withou
PWD

51.00

Household without Pers
with Disability
Household with Personwith Disability

51.00Life Recovery Score

Life Recovery Score

50.50

50.00

50.00

49.00

の平均値

の平均値

48.00

49.50

F1, 1287 =3.593, p =.058

F2, 1280 =3.238, p =.040
47.00

49.00
Prefabricated Temporary Housing

Prefabricated Temporary Housing Designated Temporary Housing

Designated Temporary Housing

Temporary Housing Type

Temporary Housing Type

Figure 3: Life recovery score by temporary housing type

Life Recovery Score

53.00

Household with/withou
Physically Vulnerable
Person52.00

Household with Physica
Vulnerable Person
Household without
Physically Vulnerable
PersonNA

Figure 4: Life recovery score by temporary housing typeby household with/without person with disability

51.00

50.00

の平均値

49.00

48.00

F4, 1287 =2.065, p =.083

F2, 1287 =2.702, p =.067

47.00
Prefabricated Temporary Housing Designated Temporary Housing

Temporary Housing Type

Figure 5: Life recovery score by temporary housing typeby household with/without physically vulnerable person

Figure 6: Life recovery score by temporary housing typeby single elderly household or not

thousand temporary housing units urgently nearby the disaster area. Because it was
impossible to construct such a large number of prefabricated temporary housings in alimited time, National government allowed prefectural governments to rent out privately
owned housings and to use them as temporary housing units to the disaster victims. For
the first time in Japanese disaster management history, the impacted citizens had tomake decisions whether to dwell in conventional prefabricated temporary housing
complex units or in designated private rental housing units that were situated in widelydispersed locations. Japanese disaster research has been mainly focusing on life
recovery assistance for prefabricated temporary housing inhabitants who live in a close
proximity and not much is known about “diaspora” survivors. The third researchquestion of the present paper was to portray the unique aspects of life recovery
processes of DTH residents in comparison with those who were residing in PTH units.
Our research team decided to work with the life recovery support department of Natori
city in early May of 2011 with the concerns that DTH dwellers would have much harder
time for them to form mutual support networks, and to obtain necessary public
information and assistance, due to the fact that they resided in widely dispersed areas
inside and outside of the city/township of their original residence. As was briefly
discussed in the previous section and also shown in Figure 3, however, life recovery
scores of DTH residents on average tended to be higher than PTH residents (F 1, 1287
=3.593, p =.058). This seems to support in general the validity of the newly introduced
DTH policy. Geographical dispersion seemed not to matter much among the surveyed
average Natori impacted citizens. This finding partly supported earlier finings made by
Life recovery models: What cross over between Kobe and Great East Japan Earthquake
recovery stories

October 2015, Kathmandu, Nepal

ethnographic interviews with impacted Natori DTH residents (Tanaka and Shigekawa,
2014, 2015; Tatsuki, 2015a) which identified 3 groups of DTH households (Tatsuki,
2015a, p. 943):
1) Younger, self-reliant and upward mobile families, 2) families with individuals
such as PWD and frail elderly that required reasonable accommodations in theireveryday functioning, and 3) vulnerable households that would have been
benefited from group living conditions in prefabricated housing complexes but
failed to submit applications in time.
Figure 3 seems to imply that DTH was a better choice for “1) younger, self-reliant and
upward mobile families” according to the classification made by Tanaka and Shigekawa(2014).
In order to examine life recovery situations among the next two categories of“households with persons with disability” and/or “vulnerable households”, Model 3
tested temporary housing type by social vulnerability (PWD, physically vulnerable andsingle elderly household) interactions. Figure 4 and 5 showed that those householdswith PWD or physically vulnerable members respectively were better recovered at PTH
while any other households’ showed higher life recovery average at DTH. Similarly,
Figure 6 demonstrates that such vulnerable households as single elderly households
seemed to “have been benefited from group living conditions” in PTH showed betterrecovery at PTH than at DTH.
In conclusion, the current study affirmed 1) that SCEM was capable of a large
proportion of life recovery measure variance among Natori impacted people; 2) that the
top 3 most powerful influences upon life recovery were physical/mental stressmanagement, livelihood, and social ties in both 2015 Natori and 2001 Hyogo Life
Recovery Surveys while livelihood as well as community involvement mattered more in
Natori survey; and that 3) DTH was better suited to “younger, self-reliant and upward
mobile families” while those households with social vulnerabilities were benefitted
from PTH group living conditions.

ACKNOWLEDGEMENTS
This research project was supported by a grant from JST, RISTEX as “Optimal life recovery assistancefor disaster survivors living in designated temporary housing in a widely dispersed area” (Principal
Investigator, Shigeo Tatsuki).

REFERENCES
Tanaka, S. and Shigekawa, K., 2014, Housing recovery processes of the temporary housing dwellers forthe 2011 great east japan earthquake: Natori city case study, Proc. of the 3rd Int. Conf. on Urban Disaster
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Tanaka, S. and Shigekawa, K., 2015, Life Recovery Process Analysis of Designated Temporary Housing
Dwellers, (Japanese), Proc. of the 36th Institute of Social Safety Science Meeting, 55-56.
Tatsuki, S. and Hayashi, H., 2001, General Linear Model analyses of life recovery factors in the 2001
Kobe Panel Survey data. Proceedings of U.S.- Japan Cooperative Research in Urban Earthquake
Disaster Mitigation Third Grantees’ Meeting, 557-574.
Tatsuki, S. and Hayashi, H., 2002, Seven Critical Element Model of Life Recovery: General Linear
Model Analysis of the 2001 Kobe Panel Survey data. Proceedings of 2nd Workshop for Comparative
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New Technologies for Urban Safety of Mega Cities in Asia

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Life recovery models: What cross over between Kobe and Great East Japan Earthquake
recovery stories