Motiv Emot (2008) 32:81–89
DOI 10.1007/s11031-008-9087-z

ORIGINAL PAPER

Actual environments do affect motivation and psychologicaladjustment: A test of self-determination theory in a natural setting
Frederick L. Philippe Æ Robert J. VallerandPublished online: 11 April 2008
Ó Springer Science+Business Media, LLC 2008

Abstract This study examined the impact of the actual
environment on changes in psychological adjustment overtime. According to Self-Determination Theory (SDT; Deci
and Ryan, Intrinsic motivation and self-determination inhuman behavior, 1985a, Plenum, New York; J Res Pers 19:
109–134, 1985b; Psychol Inq 11:227–268, 2000), environments that are objectively supportive of autonomy should
facilitate psychological adjustment through their impact
on people’s subjective perceptions of autonomy and selfdetermined motivation. The present study tested thishypothesis using a prospective design with nursing homes
residents. Results from structural equation modeling showedthat actual autonomy-supportive nursing home environments were positively associated with residents’ perceptionsof autonomy that in turn predicted self-determined motivation in major life domains. Self-determined motivation, inturn, predicted increases in psychological adjustment over a
one-year period. Theoretical implications of the present
findings are discussed in line with SDT.
Keywords Self-determination theory 
Autonomy support  Psychological adjustment

Introduction
Mrs. Brown was a very active senior citizen. Her friends
and neighbors described her as a very dynamic and

F. L. Philippe  R. J. Vallerand (&)
Laboratoire de Recherche sur le Comportement Social,Département de Psychologie, Université du Québec à Montréal,Station ‘‘Centre-ville’’, P.O. Box 888, Montreal, QC,
Canada H3C 3P8
e-mail: vallerand.robert_j@uqam.ca

outgoing person, always in a good mood, and as possessing
a very good sense of humor. However, she has recently
moved to a nursing home where she has started to act very
differently. Indeed, the nursing home staff now describes
her as unhappy with little interest for interpersonal relationships. Why is it that certain environments make us feelenergized, optimistic, and strong, while others may lead us
to feel anxious and depressed? Based on Self-D etermination Theory (SDT; Deci and Ryan 1985a, 2000), thepresent research tested the hypothesis that environments
trigger a motivational sequence that influences people’s
perceptions of autonomy and self-determined motivation inlife that in turn affect psychological adjustment.

Self-determination theory (SDT)
According to SDT, the psychological need of autonomy is
crucial for personal development, as it energizes a wide
variety of adaptive behaviors and psychological processes(Deci and Ryan 1985a). Autonomy refers to being selfinitiating in regulating one’s actions, to being able to makeindependent choices that are not constrained by others, andhaving sufficient opportunity for self-expression (Deci and
Ryan 1991; Koestner and Losier 1996, 2002). SDT posits
that exposure to autonomy-supportive environments leads
to the fulfillment of the need for autonomy (Deci and Ryan
1985a, 2002). An autonomy-supportive environment refers
to environmental conditions that promote and facilitate
one’s possibility for being self-initiating and choosing
one’s own actions. A large body of research suggests thatperceived autonomy-supportive environments facilitate
one’s perceptions of autonomy. For instance, Grolnick
et al. (1991) found that parental autonomy support (asperceived by children) regarding education was positively

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related to their perceptions of autonomy toward education.
Similarly, Baard et al. (2004) and Deci et al. (2001) haveshown that employees’ perceptions of autonomy support
from their managers were related to the employees’ perceptions of autonomy. Finally, Vallerand et al. (1997) also
found that students’ perceptions of teacher, parent, andschool administration autonomy support were related to
students’ greater perceptions of autonomy. However, itappears that no research has looked at the relationshipbetween actual autonomy support and perceptions ofautonomy.
SDT further proposes the existence of different types ofmotivation that fall into two broad categories: Self-determined motivation and nonself-determined motivation (seealso Vallerand 1997; Vallerand and O’Connor 1989). Selfdetermined motivation pertains to a behavior that is
engaged in out of pleasure (intrinsic motivation) or out ofchoice and valued as being important (self-determined
extrinsic motivation). Conversely, nonself-determined
motivation refers to a behavior that is engaged in becauseof an external or internal pressure to do so (nonselfdetermined extrinsic motivation) or when one displays arelative lack of motivation (amotivation). According to
SDT, environments that support the need for autonomy bypromoting choices and initiatives will facilitate the person’s self-determined motivation, as people are more likely
to be self-determined when they can freely choose theiractions (Deci et al. 2001; Koestner et al. 1984). On theother hand, environments that are controlling, that impose
strict rules, and/or that constrain self-expressivity are likely
to lead to nonself-determined motivation (Deci and Ryan
1987). Much research in different life contexts has
indicated that when perceptions of autonomy increase,self-determined motivation increases along, while whenperceptions of autonomy are diminished, so does selfdetermined motivation (e.g., Vallerand et al. 1997). Similarfindings have also been obtained in experimental research(e.g., Zuckerman et al. 1978).
Finally, SDT posits that motivation toward one’s
important life domains will be conducive to different
levels of psychological adjustment. More specifically, selfdetermined motivation should facilitate psychologicaladjustment, while nonself-determined motivation should be
conducive to psychological dysfunction (Deci 1980; Ryanet al. 1995; Ratelle et al. 2004). Such an assertion is again
supported by several research findings which reveal thatthe most positive psychological consequences are derived
from the most self-determined types of motivation, while
the least self-determined forms of motivation usually produce the most negative consequences. Such results havebeen obtained with a variety of variables related to mental
health such as life satisfaction, general positive emotions,creativity, feelings of hope in life, vitality, and the absence

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of suicidal ideation (for reviews, see Deci and Ryan 1985a;
Ryan 1995; Vallerand 1997) and with different age groups
ranging from children (e.g., Gottfried 1985) to the elderly(e.g., O’Connor and Vallerand 1994; Vallerand andO’Connor 1989; Vallerand et al. 1995).
Overall, support for an integrative sequence would
appear to exist, as a number of experimental and correlational studies have independently tested each specificpart of the sequence ‘‘Autonomy-Supportive Environments ? Perceptions of Autonomy ? Self-Determined
Motivation ? Psychological Adjustment’’ (see Vallerand1997). Some studies have tested some types of similar
sequence. For instance, Grouzet et al. (2004) have shownthat perceived autonomy toward a task was conducive toself-determined motivation that was, in turn, conducive toconsequences such as levels of concentration and deliberate future intentions to perform the task. Similarly, Deciet al. (2001) found that perceived autonomy support atwork was conducive to need satisfaction that was, in turn,conducive to psychological consequences. Finally, Vallerand et al. (1997) also assessed an extended sequence as
they showed that perceived autonomy support (fromparents, teachers, and school administration) positively
predicted perceived school autonomy that was conducive
to self-determination motivation at school and that was, inturn, predictive of intentions to dropout and actual dropout
one year later. Although these studies share some overlaps
with the present research, they also differ on at least one
significant point. All three studies assessed only autonomy
support as perceived by the participants themselves. In thepresent research, we used an objective measure of autonomy-supportive environments. Such an addition is criticalas people’s perceptions of need satisfaction have beenshown to differ as a function of their motivational orientation (Deci and Ryan 1985b; Vallerand 1997). Therefore,
participants might perceive autonomy support only because
they are autonomously oriented (e.g., Grolnick and Ryan
1987). Measuring autonomy-supportive environments
objectively thus appears essential. Therefore, one goal of
the present research was to examine the role of actualautonomy-supportive environments on people’s perceptions of autonomy.
A second goal of the present research was to test theentire motivational sequence from actual autonomy-supportive environments to psychological adjustment within
the confines of the same study. Indeed, to the best of ourknowledge, no study has tested all of the elements of the
proposed sequence. This constitutes a critical assessmentof SDT to test all the indirect effects of the variables
involved in this sequence (e.g., the indirect effect ofobjective autonomy-supportive environments on psychological adjustment)—something that is not feasible whenassessing only parts of this sequence (Asher 1976). Thus, aMotiv Emot (2008) 32:81–89

second goal of the present research was to test the entire
motivational sequence. In addition, this sequence was tested in a partly prospective design over a one-year period.
Finally, the third goal of the present research aimed at
examining this prospective integrative sequence in a reallife setting, namely nursing homes for the elderly. In linewith principles of SDT and past research, it was hypothesized that nursing home environments that objectively
support the autonomy of their residents should allow themto experience perceptions of autonomy that should be
associated, one year later, to residents’ self-determined
motivation toward important life domains. Most research
has looked at the association between perceptions ofautonomy and self-determined motivation using crosssectional designs (e.g., Grouzet et al. 2004; Vallerand et al.
1997). This type of design makes it difficult to determine
whether perceptions of autonomy lead to self-determined
motivation or vice versa. In the present research, we
addressed this issue by inserting a one-year time interval
between the assessments of residents’ perceptions ofautonomy and self-determined motivation.1 Finally, as
much research has shown (e.g., O’Connor and Vallerand
1994; Reis et al. 2000; Ryan and Connell 1989), selfdetermined motivation should, in turn, predict increases in
psychological adjustment (i.e., lower depression and higher
levels of life satisfaction, meaning of life, and self-esteem)
over that one-year period.

MethodParticipants
A total of 126 elderly were recruited from 11 seniornursing homes. Overall, participants were aged between 65
and 96 years (M = 80.48 years SD = 7.12 years). At
Time 2 (one year later), 43 participants were deceased,
could not be located, or refused to participate in the second
part of the study. Final sample size was composed of 83
participants (a 35% attrition rate). Participants who werelost to follow-up did not differ on the model variables fromparticipants who took part in both phases of the study,
except for life satisfaction. Participants who did not participate at Time 2 had reported lower levels of life
1

Another approach would have been to measure residents’ selfdetermined motivation twice––at Times 1 and 2. However, the lengthof the scale was a clear obstacle with such a type of population,
especially knowing that the attrition rate is high and that the sample
size is usually small. We wanted the maximum number of participants
to take part in the second phase of the study. Therefore, we decided touse a short questionnaire at Time 1 and opted for the method of a oneyear time interval between residents’ perceptions of autonomy andself-determined motivation assessments.

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satisfaction at Time 1 (M = 4.38, SD = 1.33) than those
who participated in the two phases of the study (M = 5.08,
SD = 1.42), F (1, 124) = 7.12, p \ .05, g = .05.
Baseline measures (Time 1)
Actual autonomy support in nursing homes
The degree of actual autonomy support provided by eachnursing home was obtained from an interview of a trained
research assistant with the head nurse of each nursing
home. The interview focused on how much choice andautonomy residents had concerning their daily activities
and how much initiative they could take. These wereassessed with thirteen aspects including (1) how free participants were to be visited, (2) feelings of freedom
provided by the institution appearance and design (e.g.,space availability, esthetic appearance, length of the exterior view), (3) availability of outdoor peripheral areas, (4)private vs. common bedrooms, (5) availability to choose
from different activities and leisure, 6) choice of lunch
time, (7) choice of lunch place, (8) supportive relationships
with the staff, (9) possibility to engage freely in various
common tasks, (10) freedom to decorate and arrange one’s
apartment appearance (or room) and nursing home, (11)freedom to leave for vacations, (12) freedom to take care ofan animal, and (13) levels of residents’ opportunities toshow initiatives. These aspects have been derived from past
research on autonomy support and from pilot interviews
with old adults living in nursing homes. The trained
research assistant wrote all information provided by thehead nurse on a spreadsheet with separate columns for each
aspect for each nursing home. Three psychologists highly
familiar with SDT independently rated the degree ofself-determination provided by each nursing home oneach aspect on a nine-point scale (1 = Not supportive ofautonomy at all, 9 = Extremely supportive of autonomy).
One-way random effect intraclass correlation was r = .96(the comparison point is the average measure of the threeraters). The mean autonomy-support score for nursing
homes was 5.18 (SD = 1.09) and ranged from 3.30 to 6.93.
Perceptions of autonomy
Four items derived from past research (Reid et al. 1977;
Wolk and Telleen 1976) assessed residents’ feelings ofchoice and freedom. These items were (1) ‘‘How often can
you yourself decide what your everyday behaviors aregoing to be?’’, (2) ‘‘Residents in this home can solve
problems by taking the initiative on their own’’, (3) ‘‘Residents in this home have free access to the rooms anddifferent facilities of the center’’, (4) ‘‘The people whowork in this home give me the freedom to do what I choose

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to and do not force me to do things’’. These four items were
responded to on a 7-point Likert scale (a = .71).
Psychological adjustment
To assess psychological adjustment, participants wereadministered four different scales. The first one was a
short version of the Beck Depression Inventory (BDI;
Beck et al. 1961) composed of three items rated on a
4-point scale (ranging from 0 to 3) pertaining to feeling of
failure (e.g., ‘‘I feel I am a complete failure as a person’’),disappointment in oneself, and hopelessness. Adequate
validity and reliability for this short scale have beenreported and high correlations have been reported between
the short-version and the full-version of the BDI. Alphacoefficient in this study was .68. The second scale was theSatisfaction With Life Scale (SWLS; Diener et al. 1985).
This scale contains five items and assesses global life
satisfaction. A sample item is ‘‘if I could live my life over,I would change almost nothing’’. Alpha coefficient in thisstudy was .87. The third scale was an adapted 5-item
version from Reker et al. (1987) tapping meaning in life
(MLS; Meaning of Life Scale). A sample item is ‘‘Ibelieve my life has meaning now’’. Alpha coefficient inthis study was .81. The fourth scale to be used was the5-item short scale of the Rosenberg’s Self-Esteem scale(RSS; Rosenberg 1965). A sample item is ‘‘I feel that I ama person of worth, at least on an equal plane with others’’.
Alpha coefficient was .76 in this study. Participants indicated their degree of agreement on all the items on a
7-point Likert scale ranging from 1––Do not agree at all
to 7––Extremely agree (except for those of the BDI
ranging from 0 to 3). A composite score labeled psychological adjustment was constructed by reversing the scoresof the BDI, and by computing the mean scores of all thez-score items of the four scales. Alpha coefficient for thiscomposite index was .88.
Questionnaire at Time 2––one year later
The elderly motivation scale (EMS)The EMS (Vallerand and O’Connor 1989, 1991; Vallerandet al. 1995) is a 72-item scale that assesses motivational
styles when engaging in various daily activities in six life
domains: health, religion, biological needs, interpersonal
relationships, current events, and leisure activities. Threequestions per life domain ask participants why they engage
in a particular activity related to this life domain. For
instance, for the health domain, the three questions were(1) ‘‘why do you engage in various activities related toyour health’’, (2) ‘‘Why do you follow your nutrition/diet’’,(3) ‘‘Why do you take appointment with your doctor’’.

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These six domains and related questions have beendeveloped from semi-structural interviews with old adults
with the goal of highlighting their daily needs and activities(Vallerand et al. 1995; Vallerand and O’Connor 1989,
1991). For each of the three questions per domain, participants are asked to rate the same four items corresponding
to each of four types of motivation: (1) ‘‘I don’t know, I
don’t see what it does for me’’ (Amotivation; a = .94), (2)‘‘Because I am supposed to do it’’ (Nonself-Determined
Extrinsic Motivation; a = .61), (3) ‘‘Because I choose to
do it for my own good’’ (Self-Determined Extrinsic Motivation; a = .71), (4) ‘‘For the pleasure of doing it’’(Intrinsic Motivation; a = .90). These ratings were madeon a Likert scale ranging from 1 (Not at all) to 7 (Exactly).
The EMS has shown adequate construct, convergent, andpredictive validity (O’Connor and Vallerand 1994; Vallerand et al. 1995; Vallerand and O’Connor 1989, 1991),
reliability (O’Connor and Vallerand 1994; Vallerand et al.
1995; Vallerand and O’Connor 1989, 1991), and test-retest
stability (Vallerand and O’Connor 1991). Finally, a selfdetermination index (SDI) was constructed by weighting
each type of motivation according to a continuum of selfdetermination, in line with SDT (Deci and Ryan 2000).
More specifically, a weight of +2 was awarded to theintrinsic motivation subscale and a weight of +1 was
assigned the self-determined extrinsic motivation subscale
since these constructs correspond to self-determined
motivation, with intrinsic motivation representing thehighest level. A weight of -1 was allocated to the nonselfdetermined extrinsic motivation subscale and a weight of-2 was awarded to the amotivation subscale since these
constructs correspond to nonself-determined motivation,with amotivation representing the highest level. Scores foreach subscale were then multiplied by its corresponding
weight and all product terms were added to yield an SDI toaccount for global self-determined motivation. Thisweighting technique has been used and reported by several
authors (e.g., Blais et al. 1990; Vallerand and Bisonnette
1992; Ratelle et al. 2005; Richard and Schneider 2005;
Vallerand et al. 1997; also see Vallerand 1997 and Vallerand and Ratelle 2002 on this topic). Alpha for the SDI
was .64 in this study.

Psychological adjustment
To examine psychological adjustment at Time 2, participants were asked to complete the same four scales thatwere administered at Time 1. Alphas were .65, .83, .83, and.80 for the BDI, SWLS, MLS, and RSS, respectively.
Alpha for this composite index was .90 at Time 2. All
scales were completed at both Times 1 and 2 by residents
during an interview with a trained research assistant.

Motiv Emot (2008) 32:81–89

Results
Table 1 reports the means, standard deviations, and correlations of all study variables. In order to test the
hypothesized sequence, a path analysis with observed
variables was conducted with LISREL 8 (Jöreskog andSörborm 2003).2 The covariance matrix derived from theraw data served as the database for the path analysis andthe method of estimation was Maximum Likelihood. Paths
were drawn according to the proposed model and a positive
covariance was estimated between the two exogenous
variables (autonomy-supportive nursing homes and psychological adjustment at Time 1). In addition, a direct path2

Because we wanted to assess the influence of nursing homes’autonomy support on the motivational sequence at the between levelof the nursing homes, we were interested in the between covariance ofthe model variables. We expected that the variance in nursing homes
autonomy support between the nursing homes would lead toperceptions of autonomy at the mean average of the residents livingin each nursing homes that would in turn lead to residents’ mean
average of self-determined motivation and residents’ mean average ofincreases in psychological adjustment. Variation at the within level,that is variation among residents of a same nursing home, was also
plausible because of individual differences—not all participants wereequally self-determined or equally psychologically adjusted whenentering their respective nursing home. Thus, these variations were
expected and they were predicted to vary in the same direction of the
hypothesized between level model (it was not the present researchgoal to examine differences between the nursing homes level[between level] and the residents level [within level]). Results fromtwo separate path analyses using between and within (pooled)covariance matrices showed that model fit indices were excellent for
both between and within models (ps [ .35; RMSEA = 0.00, CFI[ .95, SRMR \ .05), thus suggesting that there was variance to bemodeled at both levels (between and within). However, the between
level model had to be computed from 11 nursing homes(groups = n = 11). Therefore, not all parameter estimates weresignificant at p \ .05 (they were at pone-tailed \ .10) (see Hox andMaas 2001 for an estimation of the bias in parameter estimates with asmall group sample size in a multilevel structural equation analysis).
Because both covariance matrices fit adequately the hypothesizedmodel, it was hypothesized that they should vary in the same
direction, but independently from each other. If such was the case,they could thus be combined on this basis. To test this model ofinvariance, we examined concurrently the entire model composed of
the between and within covariances using a multilevel structural
equation modeling technique (see Hox 2002; Stapleton 2006). In thisanalysis, both matrices (between and within) are modeled together
according to the hypothesized model and are expected to vary
independently and to be equal—that is, each parameter estimate andmeasurement error at the within level is constrained to be equal to its
corresponding one at the between level. Fit indices for this model
were excellent, v2(10) = 11.69, p = .31, CFI = .96, GFI = .97,
RMSEA = .042, thus suggesting that the same hypothesized model
held at both the between and within levels. Because both matrices
were independent and adequately and equally fit the model, we thus
computed a path analysis with the whole variance (i.e., without
separating between and within variances) in order to evaluate thesignificance of the parameter estimates and provide mediation
analyses with a sufficient power to detect them. The details of thispath analysis are presented in the Results section.

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from psychological adjustment at Time 1 to perceptions ofautonomy was drawn, as these two variables were expected
to covary at Time 1.3 Results of the path analysis revealed
an excellent fit to the data. The chi-square value was
non-significant, v2 (df = 4, N = 83) = 5.63, p = .23, andother fit indices were excellent: NNFI = .96, CFI = .98,
RMSEA = .068, GFI = .97, SRMR = .072, and NFI =.95. As shown in Fig. 1, all estimated direct paths weresignificant at p \ .01. Inspection of the correlation residuals revealed that all were below .10 and were nonsignificant, indicating that additional paths would not
improve the model fits (Kline 2005).4
Statistical tests were conducted in order to determine
the significance of the mediators sequence. In order to test
this, the whole model sequence was broken down in two
parts in order to assess each part of the chain composed of apredictor, a mediator, and an outcome. In line with recent
simulation studies with respect to mediation analyses(Mackinnon et al. 2002; Shrout and Bolger 2002), we
focused on the significance of the association between thepredictor and the mediator and that of the mediator and theoutcome—that is, Baron and Kenny’s (1986) step 2 and
3—and tested the significance of the whole mediation
sequence with Sobel Tests.5 If the Sobel Test is significant,the mediation effect is significant. As shown in Fig. 1, allpaths were significant. In other words, the associations
3

The hypothesized path between psychological adjustment andperceptions of autonomy is equivalent to a covariance (see Hershberger
2006; Kline 2005 on equivalent models). However, because psychological adjustment at Time 1 is used as a control variable to remove
shared variance with psychological adjustment at Time 2, it needs to bemodeled as an exogenous variable in the model (psychologicaladjustment at Time 1 is not predicted by any variable). Hence, it is
not well advised to have a covariance between an exogenous andendogenous variable in a structural equation model (because themeasurement error of an exogenous variable is fixed to 1.00 for
identification purposes). Thus, it has been replaced with a direct path. It
should be understood that psychological adjustment at Time 1 is notmeant to be seen as predicting perceptions of autonomy, but is only
correlated with it (a covariation). However, such a covariation is in linewith past research that has shown that psychological adjustment isassociated with greater perceptions of autonomy (Deci et al. 2001).
4
Controlling for residents’ daily required number of care hours or
residents’ health level as rated by head nurses did not change theresults. An alternative model was also tested. This alternative model
tested the sequence ‘‘Actual Autonomy-Supportive Environment ? Perceptions of Autonomy ? Changes in Psychological
Adjustment ? Self-Determined Motivation’’. Results revealed poor
fit indices for this model, v2 (df = 4, n = 83) = 8.53, p = .07,
RMSEA = .119, thus suggesting that the original hypothesized model
should be preferred. Other potential alternative models were nottheoretically or methodologically possible, thus they were not tested.
5
Baron and Kenny’s classical step 1—that is, to assess thecorrelation between the predictor and the outcome—was dropped assimulation studies have shown that this step is not a necessary
condition (Mackinnon et al. 2002), particularly with distal effect(such as in a prospective study) and with small sample sizes (Shrout
and Bolger 2002).

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Motiv Emot (2008) 32:81–89

Table 1 Means, standard deviations, and correlations of the model variables
Mean

SD

1

2

3

4

Nursing homes autonomy support (1)

5.18

1.09

–

Psychological adjustment Time 1 (2)a

0.00

0.75

.11

–

Residents’ perceptions of autonomy (3)

6.23

1.02

.46***.51***–

Self-determined motivation (4)

10.82

3.67

-.03

.25*

.31**

–

Psychological adjustment Time 2 (5)a

0.00

0.79

-.06

.53***.35**.62***

Note: n = 83, * p \ .05, ** p \ .01, *** p \ .001
aAverage of z-scores

between predictors and mediators and mediators and outcomes were significant. In addition, results from Sobel
Tests (controlling for the exogenous covariable psychological adjustment at Time 1) revealed that the mediation‘‘Actual Autonomy-Supportive Environments ? Perceptions of Autonomy ? Self-Determined Motivation’’ wassignificant, z = 2.39, p \ .01 (bootstrap 95% confidence
intervals: .033; .20). The effect size of this mediation effectwas calculated using Shrout and Bolger’s (2002) procedures which consist of the ratio of the indirect effect over
the total effect, thus resulting in a ratio of the effect proportion mediated (PM) ranging from 0 to 1 (with upperbound set to 1.00). The effect proportion for the above
mediation was PM = 0.76, thus indicating that 76% of thetotal effect between actual autonomy-supportive environments and self-determined motivation was mediated byperceptions of autonomy. Results also showed that themediation ‘‘Perceptions of Autonomy ? Self-Determined
Motivation ? Psychological Adjustment (T2)’’ was alsosignificant, z = 2.62, p \ .001 (bias-corrected 95% confidence intervals: .001; .24) and PM = 1.00, thus indicatingthat full mediation had occurred. Finally, in line withrecently recommended statistical procedures to test a threepath mediated effect (see Taylor et al. 2008), results fromthe joint significance test (pb1 \.05 and pb2 \.05 and pb3 \.05, where b is the parameter estimate of each path in thesequence) showed that the indirect effect from nursing
homes’ autonomy-support to psychological adjustment(T2) was significant at p\.05 (bootstrapped bias-corrected
95% confidence intervals: [.002; .024]). These results support the hypothesized motivational sequence from actualautonomy-supportive environments to increases in psychological adjustment in nursing homes residents.

Discussion
The present study was designed to examine the role of theenvironment in changes in psychological adjustment over a
one-year period. More specifically, this study aimed at
testing for the first time within the confines of the same

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study the integrative motivational sequence ‘‘Actual
Autonomy-Supportive Environments ? Perceptions ofAutonomy ? Self-Determined Motivation ? Changes in
Psychological Adjustment’’. The findings provide support
for the above sequence.
These findings lead to a number of implications. First,
the present study is one of the first field studies to show the
impact of objective autonomy-supportive environments on
subjective perceptions of autonomy. The results showedstrong support for the association of these variables, as themore autonomy supportive the actual environment, thegreater the perceptions of autonomy. These findings support SDT claims that the actual environment plays animportant role in providing people with opportunities tofulfill their needs (Deci and Ryan 2002). Second, results
also provided support for SDT, as subjective perceptions ofautonomy predicted self-determined motivation in major
life domains one year later. This finding replicates pastfindings (e.g., Pelletier et al. 2001; Vallerand et al. 1997;
Zuckerman et al. 1978) that showed that satisfaction of thebasic need for autonomy was in turn conducive to selfdetermined motivation in a number of activities. However,the present research extends those findings in two ways.
First, the present study is one of the few studies to show theexistence of this relationship with older adults, as paststudies have typically used samples of students (e.g.,
Grouzet, et al. 2004). This test thus provides an external
validity to the hypotheses derived from SDT. Second, thepresent results showed that subjective perceptions ofautonomy mediated 76% of the total effect of the relationship between the objective autonomy-supportive
environment and self-determined motivation in major life
domains. These findings are in line with past research andsupport SDT’s assertion that actual environments caneither facilitate or thwart one’s need for autonomy and thus
have an important indirect impact on one’s motivational
processes.
A third implication of the present research is that thefindings support SDT’s claims to the effect that selfdetermined motivation in one’s life is expected to contribute to psychological adjustment. Results also showedMotiv Emot (2008) 32:81–89

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Fig. 1 Path analysis of themodel variables. All direct paths
are significant at p \ .01.
Standardized coefficients arepresented

that self-determined motivation completely mediated therelationships between perceptions of autonomy and changes in psychological adjustment over a one-year period.
The present research extends results of past studies (e.g.,
Niemiec et al. 2006; Grolnick and Ryan 1989; Sheldon andKasser 1998) that obtained this relationship. Indeed, past
research has typically employed a cross-sectional design.
The fact that we replicated these findings using a prospective design provides additional support for SDT’s
claims that self-determined motivation plays a crucial rolein the increases in psychological adjustment over time (seealso Ratelle et al. 2004 on this issue). Furthermore, theresults of the present research are particularly interesting,as these were obtained with older adults, a population forwhom psychological adjustment has been shown to be
critical for life longetivity and physical health (e.g., Joppand Rott 2006; O’Connor and Vallerand 1998).
Finally, the present research is the first to assess thecomplete motivational sequence from actual autonomysupportive environment to changes in psychologicaladjustment within the confines of the same study. This
provides support for SDT. Indeed, it strongly suggests that
actual autonomy-supportive environments do have anindirect effect on people’s psychological adjustment overtime through the motivational sequence posited by SDT,
that is perceptions of autonomy and self-determined
motivation.
A number of limitations should be underscored from thepresent research. First, the sample size was small, thus it
limits the representativeness of this sample for the generalelderly population and the types of statistics that can be
conducted. Indeed, because of the sample size, it was notpossible to conduct a full multilevel structural equation
modeling. In addition, small sample sizes might also yieldhigh sampling error, biased parameter estimates, and typically have low power to detect significant effect. However,it did not appear to be the case in the present study as the

RMSEA was low, correlation residuals were non significant, and parameter estimates were relatively high.
Nevertheless, the present findings should be interpretedwith caution. Future research is needed in order to replicate
the present results with a larger sample size and a larger
number of nursing homes. A second limitation concerns themeasurement time points. Self-determined motivation was
only measured once. Thus, no conclusion can be drawn
with respect to its longitudinal evolution. Third, all participants were already in nursing homes at the time of thestudy. Thus, we cannot rule out the possibility that residents influenced their environment. However, because
additional statistical analyses revealed that the number ofyears spent in the nursing homes was unrelated to themodel variables, this possibility does not seem tenable.
In any event, future research might examine how exposition to a new living environment can influence peoples’
perceptions of autonomy. Finally, it should be noted thatthe perceptions of autonomy measure was developed specifically for the present study and it might also assess
residents’ perceptions of autonomy support. One should
thus be cautious in using this scale as a standard measure ofperceptions of autonomy. Future research is needed inorder to develop and validate measures that assess bothconstructs independently in field settings.
In sum, the present findings provide support for the
integrative sequence ‘‘Actual Autonomy-Supportive Environment ? Perceptions of Autonomy ? Self-Determined
Motivation ? Changes in Psychological Adjustment’’. In
line with SDT, it thus appears that environments can have along-term impact on one’s psychological adjustment,
through one’s perceptions of autonomy of the environmentand self-determined motivation. Future research is neededin order to explore if other aspects of the actual environment (e.g., environments that promote SDT’s other needsof competence and relatedness) can also have implications
for motivation and psychological adjustment.

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