Cognitive-affective responses to online positive-
psychological interventions: The effects of
optimistic, grateful, and self-compassionate
Johannes Bodo Heekerens
| Kathrin Heinitz
Department of Education and
Psychology, Division of Methods and
Evaluation, Freie Universitat Berlin,
Department of Education and
Psychology, Division of Work and
Organizational Psychology, Freie
Universitat Berlin, Berlin, Germany
School of Social Sciences, Chair of
Educational Psychology, University of
Mannheim, Mannheim, Germany
Johannes Bodo Heekerens, Department
of Education and Psychology, Division of
Methods and Evaluation, Freie
Universitat Berlin, Berlin, Germany.
Friedrich Naumann Foundation
Growing evidence suggests that online positive-
psychological interventions effectively increase well-
being, and a wealth of evidence describes cognitive-
affective responses to such interventions. Few studies,
however, have directly compared responses across pop-
ular exercises such as the best-possible-self interven-
tion, the gratitude letter, or self-compassionate writing.
In addition, current evidence is ambiguous regarding
the effects of potential moderator variables such as trait
gratitude and emotional self-awareness. To address
these issues, we randomized 432 German adults to
perform either optimism, gratitude, self-compassion, or
control writing interventions in an online setting. Par-
ticipants reported trait gratitude and trait emotional
self-awareness before the interventions, as well as
momentary optimism, gratitude, self-compassion, posi-
tive affect, and current thoughts immediately after
the interventions. Results indicate higher momentary
optimism after the best-possible-self intervention and
higher momentary gratitude after the gratitude letter
than after the control task. There were no differences
Received: 19 July 2021 Revised: 18 November 2021 Accepted: 18 November 2021
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use,
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© 2022 The Authors. Applied Psychology: Health and Well-Being published by John Wiley & Sons Ltd on behalf of International Associ-
ation of Applied Psychology.
Appl Psychol Health Well-Being. 2022;1–24. wileyonlinelibrary.com/journal/aphw 1
when comparing the best-possible-self intervention
with the gratitude letter. Both interventions increased
the number of positive self-relevant thoughts. The self-
compassion condition showed no effects. Moderation
analysis results indicate that neither emotional self-
awareness nor trait gratitude moderated the interven-
tion effects. Future studies should compare responses
across different positive-psychological interventions
using more comprehensive exercises to ensure larger
gratitude, online, optimism, positive psychology intervention,
Growing evidence suggests that positive-psychological interventions, which are intentional
activities designed to cultivate positive emotions, behaviors, and cognitions (Sin &
Lyubomirsky, 2009), effectively increase well-being (see Bolier et al., 2013; Sin &
Lyubomirsky, 2009, for two independent meta-analyses). Numerous studies have successfully
delivered positive-psychological interventions online (see Stone & Parks, 2018, for a review).
However, there is still limited understanding of the cognitive-affective responses to these inter-
ventions and how such responses are similar or different across interventions (Lyubomirsky &
In this study, we focus on three positive-psychological interventions that are popular among
researchers and practitioners: first, the best-possible-self (BPS) intervention (King, 2001), which
has been repeatedly shown to increase positive affect and optimism and to decrease pessimism
(see Heekerens & Eid, 2020; Loveday et al., 2016; Malouff & Schutte, 2016, for reviews and
meta-analyses); second, the gratitude letter exercise (Seligman et al., 2005), which has been
repeatedly shown to increase gratitude and psychological well-being (see Davis et al., 2016, for
a meta-analysis); and third, self-compassionate writing (Shapira & Mongrain, 2010), a fre-
quently used component of comprehensive interventions that focus on the cultivation of com-
passion, which might increase compassion, self-compassion, and mindfulness, as well as
alleviate depressive and anxious symptoms (see Kirby, 2017; Kirby et al., 2017, for a review and
meta-analysis). The magnitude of the effects of brief stand-alone positive-psychological inter-
ventions is typically small to medium and decreases over time (Bolier et al., 2013) and may even
be smaller when using online formats (e.g., Heekerens & Eid, 2020). In practice, this problem
may be resolved by embedding positive-psychological interventions in comprehensive well-
being programs (e.g., Heintzelman et al., 2020). In this study, we chose to examine the effects of
stand-alone online interventions because this allows to investigate the cognitive-affective
responses to these interventions.
2HEEKERENS ET AL.
Cognitive-affective intervention effects
Positive-psychological interventions have been proposed to target positive emotions and cogni-
tions, which in turn increase well-being (Lyubomirsky & Layous, 2013). In line with this,
meta-analytic evidence shows that different positive interventions successfully induce positive
affect (e.g., Davis et al., 2016; Heekerens & Eid, 2020). One experimental study has shown that
increases in positive emotions during a 8-weeks loving-kindness meditation program predicted
later increases in personal resources and life satisfaction (e.g., Fredrickson et al., 2008). Simi-
larly, one study showed that the effects of two one week positive-psychological interventions
on happiness and depressive symptoms were partially mediated through changes in positive
emotions during the trial (Gander et al., 2020). In addition, specific positive-psychological
interventions are assumed to promote adaptive cognitions (Seligman et al., 2005). For exam-
ple, the BPS intervention is theorized to build positive future expectations, the gratitude letter
should allow to adopt a grateful outlook, and self-compassionate writing has been proposed to
induce a mindful awareness that allows to overcome negative thoughts and feelings involved
in personal suffering (see Gross, 1998; Quoidbach et al., 2015, for detailed conceptual frame-
works). In line with this, meta-analytic evidence shows that individuals report higher levels of
optimism after writing about their best-possible future (Heekerens & Eid, 2020; Malouff &
Schutte, 2016), higher levels of gratitude after writing a gratitude letter (Davis et al., 2016),
and higher levels of self-compassion after a self-compassionate writing task (Kirby
et al., 2017). In addition, results from one waitlist-controlled study suggest that a 12-week
comprehensive positive intervention program successfully promoted specific cognitions and
emotions (e.g., hope, self-compassion, and gratitude) that were targeted during the weekly
online or in-person sessions of the program and that this change partially accounted for
increased subjective well-being after the program (Heintzelman et al., 2020). Moreover, one
experiment that manipulated the instructions for a positive-psychological intervention such
that the focus was either on cognitions (“describe”) or emotions (“re-experience”) or both sug-
gests that focusing on cognitions had a stronger effect on happiness (Gander et al., 2017; also
see Wellenzohn et al., 2016). However, there is also evidence that some positive interventions
have effects that are theoretically more closely linked to other interventions. For example,
results from one experimental study suggest that not only variations of the best-possible
self-intervention but also different gratitude interventions increase optimism and decrease
hopelessness (Huffman et al., 2014). In addition, experimental results indicate that a brief
self-compassion intervention not only increases self-compassion and mindfulness but also
self-efficacy and optimism (Smeets et al., 2014). Thus, the specificity of effects remains
Differential intervention effects
Another line of research has addressed the question for which groups of people positive-
psychological interventions show optimal effects (see Fritz & Lyubomirsky, 2018, for a recent
review). Specifically, current conceptual frameworks suggest that the effectiveness of positive-
psychological interventions depends on the interplay between features of the activity and partic-
ipant characteristics (Lyubomirsky & Layous, 2013; Schueller, 2011). In other words, effects are
expected to vary due to interactions between persons and situations (see Cronbach &
Snow, 1977, for an early discussion). In this study, we focus on emotional self-awareness and
COGNITIVE-AFFECTIVE RESPONSES TO ONLINE PPI 3
trait gratitude as moderators of cognitive-affective responses to positive-psychological interven-
tions because preliminary evidence indicates that these variables may play a role in differentiat-
ing intervention effects between participants. We did not investigate trait optimism as a
moderator of the best-possible-self intervention because previous research found that interven-
tion effects are equal among participants with varying levels of trait optimism (Harrist
et al., 2007; Meevissen et al., 2011; Peters et al., 2010).
Emotional self-awareness describes how frequently individuals generally pay attention to
their own emotions (see Eid et al., 2003; Lischetzke et al., 2012; Swinkels & Giuliano, 1995,
for a deeper discussion). The BPS intervention should be particularly helpful for individuals
low in emotional self-awareness because such individuals prefer not to approach strong emo-
tions and writing about goals provides self-regulatory benefits without an exploration of
unpleasant emotions (King, 2001). On the contrary, the self-compassion intervention should
yield better results for individuals high in emotional self-awareness because the intervention
offers the opportunity to explore and alleviate negative emotions, which reconciles with the
needs of highly emotionally self-aware individuals (Austenfeld & Stanton, 2004). Congruently,
two studies found that students who reported more active attempts to acknowledge their
emotions reported larger reductions in depressive symptoms and hostility after writing about
negative emotions, compared with writing about their best possible future (Austenfeld
et al., 2006; Austenfeld & Stanton, 2008). The moderation effect, however, has not yet been
investigated using outcomes that are more characteristic of the BPS and self-compassion
interventions and more closely relate to well-being such as optimism, self-compassion, and
Trait gratitude describes how frequently, intensely, and deeply individuals generally experi-
ence grateful affect (McCullough et al., 2002) and has been shown to relate to reports of state
gratitude in daily life (McCullough et al., 2004). The gratitude intervention should be more
effective for individuals higher in trait gratitude because of characteristic interpretive biases in
appraising situations that explain the relation between trait and state gratitude (see Wood
et al., 2008, for a conceptual model). Specifically, individuals higher in trait gratitude have been
shown to make more positive help-related benefit appraisals (Wood et al., 2008), which should
apply to the situation of writing a gratitude letter and result in higher levels of state gratitude
among individuals higher in trait gratitude after the intervention. In line with this, initial
evidence suggests that individuals high in trait gratitude expected gratitude interventions to be
easier, more socially accepted, and more effective (Kaczmarek et al., 2015). In addition, one
study reported that individuals higher in trait gratitude reported larger increases in positive
affect after writing about someone to whom they felt grateful (Watkins et al., 2003, study 4).
Other researchers, however, found that participants lower in trait gratitude reported higher pos-
itive affect (Harbaugh & Vasey, 2014), as well as higher happiness and life satisfaction (Rash
et al., 2011) following gratitude-based interventions. One study suggests that individuals higher
in openness and extraversion reported higher happiness and lower depressive symptoms after
writing and delivering a gratitude letter than individuals lower in openness and extraversion
(Senf & Liau, 2012). A later study investigating personality traits as moderators of the effects of
a 10-week multicomponent online well-being program, however, did not find comparable
effects (Wang et al., 2017). Taken together, studies on stable between-person differences as
moderators of the effects of positive-psychological interventions have yielded few replicable
effects and current evidence regarding trait gratitude as a moderator appears particularly
4HEEKERENS ET AL.
Aims of the present study
The aims of the present study were to investigate cognitive-affective responses to online
positive-psychological interventions and to explore differential effect patterns. Specifically, we
hypothesize the following:
1. Participants in the optimism condition report higher optimism, in the gratitude condition
higher gratitude, and in the self-compassion condition higher self-compassion after the
intervention compared with the control condition (effects on cognitions).
2. Participants in all positive-psychological intervention conditions report higher positive affect
after the intervention compared with participants in the control condition (effect on affect).
3. Participants low in emotional self-awareness report stronger effects in the optimism condi-
tion (compared to the control group), participants high in trait gratitude report stronger
effects in the gratitude condition (compared to the control group), and participants high in
emotional self-awareness report stronger effects in the self-compassion condition (compared
to the control group).
Participants were recruited online through the German platform respondi, offering them 5€
for their participation. We included German natives who were at least 18 years old and who
passed all our quality checks, including assessments of whether participants read the instruc-
tions and questions carefully (Merkle & Kaczmirek, 2016). We excluded 10 participants, 3 in
the control condition, 1 in the optimism condition, and 5 in the self-compassion condition,
due to insufficient text quality as indicated by meaningless or defiant input. The final sample
comprised 425 adults of whom 106 were assigned to the control condition, 110 to the opti-
mism condition, 105 to the gratitude condition, and 104 to the self-compassion condition. A
sample size of 425 is sufficient to detect an effect size of f=.16 of a one-way ANOVA con-
sisting of four groups with a power of .80 (α=0.05). Text quality was assessed by two inde-
pendent raters and deviating ratings were discussed until a consensus was reached. The mean
age of participants was 43.26 years (SD =12.67, range =18–75), and 57.2% were female. The
sample comprised 7.8% students and individuals undergoing vocational training, 73.4%
employees and freelancers, 3.5% jobseekers, and 15.3% others, including retirees and house-
wives. Data were collected in March 2018.
Participants accessed our study through a link. On the first page, they were informed that the
purpose of the study was to examine effects of writing on emotions as well as to the voluntary
nature of participation and data protection. On the second page, participants answered ques-
tions regarding emotional self-awareness and trait gratitude. Afterwards, participants were ran-
domly assigned to either perform one of the positive interventions or the control condition. We
designed the survey such that participants had to spend at least 15 min on the writing task.
COGNITIVE-AFFECTIVE RESPONSES TO ONLINE PPI 5
After implementation, participants listed 10 current thoughts and rated the self-reference and
valence of each thought. Next, participants reported momentary optimism, gratitude, self-com-
passion, and affective state. They indicated how much they liked the intervention, how much
they have benefitted from the intervention, and how difficult the intervention was for them.
Finally, participants answered socio-demographic questions, indicated their level of experience
with self-help techniques, and whether they have been undergoing or currently undergo psy-
Participants were randomly assigned to one of four online interventions. The randomization
sequence was computer generated, and nobody had access to the sequence at any time of the
experiment. As in previous studies, participants in the optimism condition were instructed to
write about their ideal future (based on King, 2001), participants in the gratitude condition
wrote a letter about experiences for which they feel grateful towards the person who did the
kind act for them (based on Lyubomirsky et al., 2011; Seligman et al., 2005), and participant in
the self-compassion condition reflected upon their shortcomings from the perspective of a com-
passionate other (based on Shapira & Mongrain, 2010). Participants in the control condition
were instructed to write about their previous week (based on Layous et al., 2013; Odou & Vella-
Brodrick, 2013). We chose the control condition because the format is comparable to the posi-
tive interventions; however, the content should have been emotionally neutral on average. All
participants were informed that their input is anonymous and were asked not to worry about
grammar and spelling. All instructions were provided in German. Full texts are provided in
Appendix S1. The ethics committee of the department of education and psychology at Freie
Universität Berlin approved the study (No 177/2018).
We assessed momentary optimism using an adaption of the German version of the Life Orien-
tation Test Revised (LOT-R; Carver et al., 2010; Glaesmer et al., 2011). We only included the
three items capturing optimism. Participants were asked about their momentary experience
(e.g., “At the moment, I'm optimistic about my future”; see Appendix S2 for all selected
items). The scale is anchored at 1 (strongly disagree) and 5 (strongly agree). McDonald's Omega
(calculated using the R package MBESS; Kelley, 2007; McDonald, 1991) for optimism was .88,
95% CI [.85, .91].
Momentary gratitude was assessed using items borrowed from the Gratitude Questionnaire-6
(GQ-6; McCullough et al., 2002). Specifically, we used three items that make sense
when assessing gratitude in the present moment (e.g., “At the moment, I have something in
life to be thankful for”; see Appendix S2 for all selected items). Trait gratitude was assessed
6HEEKERENS ET AL.
with the full scale and using the original wording (e.g., “I am grateful to a wide variety of
people”). The German item versions were derived by a translation and back translation
process (Proyer, 2007). The scale is anchored at 1 (strongly disagree) and 7 (strongly agree).
McDonald's Omega for momentary gratitude was .91, 95% CI [.89, .93] and for trait gratitude
.79, 95% CI [.76, .83].
We assessed momentary self-compassion using an adaption of the German short version of the
Self Compassion Scale (SCS; Hupfeld & Ruffieux, 2011; Raes et al., 2011). We included ten items
that we reworded to reflect current self-compassion, and participants were asked about their
momentary experience (e.g., “At the moment, I give myself the caring and tenderness I need”;
also see Breines & Chen, 2012). Prior to the analysis, we excluded the item “I can imagine that
feelings of inadequacy are shared by most people”from all analyses because the item was
negatively correlated with all other items in the scale, demonstrating that the German transla-
tion of the item was ambiguous (see Wieland et al., 2017, for a discussion). The scale is
anchored at 1 (strongly disagree) and 4 (strongly agree). McDonald's Omega for self-compassion
was .81, 95% CI [.77, .84].
Positive affect was assessed using the short version A of the Multidimensional Mood Question-
naire (MDBF; Hinz et al., 2012; Steyer et al., 1994). The scale includes each four items referring
to positive-negative mood (e.g., “happy”), alert-tired mood (e.g., “rested”), and calm-agitated
mood (e.g., “restless”). Participants were asked how they feel “at the moment”. The scale is
anchored at 1 (not at all) and 5 (very). McDonald's Omega for positive affect was .93, 95% CI
Positive self-relevant thoughts
We assessed positive self-relevant thinking using the thought listing approach (Cacioppo
et al., 1979). Participants were asked to list 10 current thoughts, and afterwards, they were to
indicate whether each thought was self-relevant or not and whether each thought was positive,
neutral, or negative. The average number of thoughts falling into each category (e.g., positive
thought) was assessed by adding them up and dividing them by the total number of reported
thoughts. Previous studies have established that the data obtained using the thought listing
approach meet common psychometric standards (see Cacioppo et al., 1997; Glass &
Arnkoff, 1994, for reviews). For example, the number of negative thoughts has been shown to
relate to lower self-evaluations, providing evidence for criterion-related validity (Cacioppo
et al., 1979). Another study found that the responses of participants who rated how comfortable
they would feel in a hypothetical situation were similar whether or not participants completed
the measure, indicating that the technique is not reactive (Fichten et al., 1988). However,
clinical intervention studies demonstrated that the number of positive and negative thoughts
can be changed through targeted action (Heimberg, 1994).
COGNITIVE-AFFECTIVE RESPONSES TO ONLINE PPI 7
We assessed emotional self-awareness using the Attention to Feelings Scale (Lischetzke
et al., 2001). The scale includes six items referring to individual differences in attention to one's
feelings (e.g., “I think about my feelings.”). It is anchored at 1 (almost never) and 4 (almost
always). McDonald's Omega for emotional self-awareness was .94, 95% CI [.93, .95].
Demographics and quality check items
Participants were asked to indicate gender, age, and current job status. Additionally, we asked
how often they use self-help techniques such as books or mobile application on the topic of
happiness offering the answer options “never,”“sometimes (once or twice a year),”“regularly
(once or twice a month),”and “often (once or twice a week).”Afterwards, participants were
asked whether or not they currently receive or have been receiving psychotherapeutic treat-
ment. In addition, participants were asked how much they liked the exercise, how much they
benefited from the exercise, and how difficult the exercise was for them (based on
Schueller, 2011). Items were assessed separately to allow for more nuanced interpretations of
the results. The scale is anchored at 1 (strongly disagree) and 7 (strongly agree). Furthermore, we
used two quality check items to make sure that participants have read the instructions carefully
(as recommended by Merkle & Kaczmirek, 2016). First, we included an instructional manipula-
tion check and asked participants to respond “blue”to the question “Which color matches your
text?”as part of the intervention description. The question and the instructed response “blue”
were displayed after the intervention, together with the answer options “red,”“green,”
“yellow,”and “purple.”Second, we displayed a 5-point rating scale anchored at 1 (not at all)
and 5 (very) together with the item “sad”and asked participants “Please choose the answer
option ‘very’to show that you have read the instructions.”
We tested our hypotheses with three multiple group structural equation models (SEM). For
the main analysis, we used MPLUS version 8.1 (Muthén & Muthén, 1998-2017) applying
robust maximum likelihood (MLR) estimation. Specifically, we used multiple group analyses
to test our hypotheses because this approach allowed us to test the expected group differ-
ences in latent means (Hypotheses 1 and 2) and differential effects (Hypothesis 3) within
one statistical framework. Data were analyzed in two steps. In the first step, we defined
three models with two correlated factors in the optimism condition (positive affect and
optimism), the gratitude condition (positive affect and gratitude), and the self-compassion
condition (positive affect and self-compassion) to assess model fits either assuming different
or equal factor loadings and intercepts across the intervention and control groups. This was
done to test the assumption of measurement invariance across groups. Comparing latent
means and regression coefficient across groups require that strong (scalar) measurement
invariance is given (e.g., Millsap, 2011, that means that the factor loadings and intercepts do
not differ between groups). The models look like the models depicted in Figure 1 if the
regression coefficients are replaced with covariance (correlations) between the factors. Each
model contained three observed indicator variables loading on a common latent variable for
8HEEKERENS ET AL.
each construct under investigation. The observed indicator variables for positive affect and
self-compassion reflect parcels
that were formed by aggregating randomly allocated items
(as recommended by Matsunaga, 2008), whereas the indicator variables for optimism and
gratitude reflect single items. Results indicate appropriate fit indices for the restricted (with
the assumption of measurement invariance) optimism intervention model, χ2(60, N=216) =
68.24, p=.218, CFI =.99, RMSEA =0.04, 95% CI [0.00, 0.07], SRMR =.06, the gratitude inter-
vention model, χ2(60, N=211) =89.49, p=.008, CFI =.97, RMSEA =0.07, 95% CI [0.04,
0.10], SRMR =.08, and the self-compassion intervention model, χ2(60, N=210) =67.15, p =
.246, CFI =.99, RMSEA =0.03, 95% CI [0.00, 0.07], SRMR =.06 (as indicated by CFI > .97,
RMSEA < .05, and SRMR < .08; Hooper et al., 2008; Hu & Bentler, 1999). Importantly, scaled
χ2difference tests (Satorra & Bentler, 2010) showed that assuming measurement invariance did
not significantly worsen model fit for the three models, χ2diff =19.30, df diff =12, p=.082,
χ2diff =15.67, df diff =12, p=.207, and, χ2diff =19.44, df diff =12, p=.079, respectively (see
FIGURE 1 (a) Emotional self-awareness: optimism condition (n=110). (b) Trait gratitude: gratitude
condition (n=105). (c) Emotional self-awareness: self-compassion condition (n=104). Note: Multiple group
structural equation models comparing participants in the optimism, gratitude, and self-compassion condition
with participants in the control condition. We displayed the models that freely estimate the regression
coefficients to provide additional information although none of the differences between intervention and control
groups reach statistical significance. Unstandardized parameter estimates with standard errors in brackets and
standardized solutions for the latent regression part in bold. PA_A, PA_B, PA_C =observed variables (parcels)
for positive affect; Opt_A, Opt_B, Opt_C =observed variables (items) for optimism; Grat_A, Grat_B,
Grat_C =observed variables (items) for gratitude; SC_A, SC_B, SC_C =observed variables (parcels) for self-
compassion; ESA_A, ESA_B, ESA_C =observed variables (parcels) for emotional self-awareness; TG_A, TG_B,
TG_C =observed variables (parcels) for trait gratitude; PA =common latent state variable for positive affect;
Grat =common latent state variable for gratitude; Opt =common latent state variable for optimism; SC =
common latent state variable for self-compassion; ESA =common latent state variable for emotional self-
awareness; TG =common latent state variable for trait gratitude.
COGNITIVE-AFFECTIVE RESPONSES TO ONLINE PPI 9
Cheung & Rensvold, 2002 for a discussion). Because strong measurement invariance is given,
hypotheses 1 and 2 can be analyzed with respect to the latent means. Moreover, to analyze
Hypothesis 3, we regressed our outcome variables on the proposed moderators and freely
estimated the regression coefficients (see Figure 1). To test the proposed multivariate modera-
tion effects, we compared the resulting models with models assuming equal regression coeffi-
cients across conditions. If the model with equal regression coefficient does not fit the data
worse than the model with freely estimated regression coefficient, then there will be no signifi-
cant moderation effect. If, however, the model with freely regression coefficient fits the data
better, there will be a significant moderation, and the intervention effect will depend on the
value of the moderator variable. Variance-covariance matrices for our models are shown in
Preliminary, exploratory, and additional analyses were done with R version 3.6.2 (R Core
Team, 2019). For computerized text analysis, we used the German version of the Linguistic
Inquiry and Word Count (LIWC) program version 2015 (see Hirsh & Peterson, 2009;
Pennebaker, 2011; Tausczik & Pennebaker, 2010; Wolf et al., 2008, for a deeper discussion).
Prior to the main analysis, we conducted a MANOVA to test whether participants in the posi-
tive intervention conditions and the control condition differ regarding emotional self-aware-
ness, trait gratitude, and age. Results indicate no difference between conditions, Pillai's Trace =
0.02, F(3,421) =0.76, p=.656, η2
adj =0.01 (using Serlin's correction as recommended by
Grissom & Kim, 2012; Serlin et al., 1982). In addition, Pearson's Chi-squared test results suggest
no difference regarding gender, χ2(3, N=425) =2.63, p=.452, ω=0.08, 95% CI [0.00, 0.13],
experience with self-help, χ2(9, N=425) =8.02, p=.532, ω=0.14, 95% CI [0.00, 0.15], and
therapy status, χ2(6, N=425) =3.87, p=.694, ω=0.10, 95% CI [0.00, 0.12] (using the R pack-
age MBESS to calculate confidence intervals; Kelley, 2007). Taken together, results indicate no
group differences before the interventions.
Tests of hypotheses
Effects on cognition
According to our first hypothesis, we expected that participants report higher optimism after
the optimism intervention, higher gratitude after the gratitude intervention, and higher self-
compassion after the self-compassion intervention. Before testing this hypothesis on the level of
latent means, we will present the results with respect to the observed means because this is usu-
ally done in this area of research. Table 1 presents the results with respect to the total scale
scores. It reveals that average observed optimism was significantly higher in the optimism com-
pared with the control condition, 3.92 versus 3.55 on a scale ranging from 1 to 5, d=0.38, 95%
CI [0.11, 0.65] (effect size and confidence interval calculated using the R package MBESS;
Cohen, 1988; Kelley, 2007), and average gratitude was significantly higher in the gratitude con-
dition, 6.04 versus 5.58 on a scale ranging from 1 to 7, d=0.40, 95% CI [0.12, 0.67]. There was
10 HEEKERENS ET AL.
no significant difference in average self-compassion in the self-compassion condition, 3.39
versus 3.43, d=-0.05, 95% CI [0.32, 0.22].
Table 2 presents the (unstandardized) latent mean differences between the optimism, grati-
tude, and self-compassion conditions and the control condition. Based on the latent mean
scores and there 95 % confidence intervals, the statistical conclusions were the same as for the
observed means. The latent mean differences with respect to the control condition were 0.36,
95% CI [0.11, 0.61] for the optimism, 0.51, 95% CI [0.14, 0.87] for the gratitude, and 0.05, 95%
CI [0.24, 0.15] for the self-compassion condition. The estimates reported here are derived from
the three multi group models (A–C) computed in the second step of our analysis after esta-
blishing measurement invariance.
TABLE 1 Manifest means, standard deviations, and intercorrelations for PA, Opt, Grat, SC, ESA, TG, and
PST in the control (n=106), optimism (n=110), Gratitude (n=105), and self-compassion (n=104) conditions
Measure PA Opt Grat SC ESA TG PST M SD
Control and optimism condition
1. PA - .50
2. Opt .64
3. Grat .17 .48
.08 5.91 1.16
4. SC .67
- .01 .32
5. ESA .19 .06 .10 .11 - .18 .06 2.86 0.72
6. TG .27
- .12 5.26 1.04
7. PST .34
- 3.96 3.04
M3.29 3.55 5.58 3.43 2.76 5.08 2.32
SD 0.85 0.97 1.23 0.70 0.70 0.93 2.16
Gratitude and self-compassion condition
1. PA - .60
2. Opt .63
3. Grat .39
.18 5.68 1.22
4. SC .65
5. ESA .08 .05 .08 .06 - .17 .08 2.87 0.72
6. TG .46
- .17 5.34 0.91
7. PST .16 .24
.13 .08 .14 - 2.20 2.03
M3.43 3.71 6.04 3.42 2.76 5.14 3.73
SD 0.87 0.93 1.07 0.70 0.77 0.98 2.91
Note: The first section shows Pearson correlations for the control condition below the diagonal and for the optimism condition
above the diagonal. Manifest means and standard deviations for the control condition are presented in the rows and for the
optimism condition in the columns. The second section shows Pearson correlations for the gratitude condition below the
diagonal and for the self-compassion condition above the diagonal. Means and standard deviations for the gratitude condition
are presented in the rows and for the self-compassion condition in the columns.
Abbreviations: ESA, emotional self-awareness; Grat, gratitude; Opt, optimism; PA, positive affect; PST, positive, self-relevant
thoughts; SC, self-compassion; TG, trait gratitude.
COGNITIVE-AFFECTIVE RESPONSES TO ONLINE PPI 11
Effect on affect
According to our second hypothesis, we expected that participants report higher positive affect
after all positive interventions. Table 1 reveals that average observed positive affect measured
on the total scale ranging from 1 to 5 was 3.48 in the optimism, 3.43 in the gratitude, and 3.30
in the self-compassion condition compared with 3.29 in the control condition. Standardized
TABLE 2 Latent mean differences, standard deviations, and latent covariances and correlations for PA, Opt,
Grat, and SC in the control (n=106), optimism (n=110), gratitude (n=105), and self-compassion (n=104)
Measure (A) optimism condition
1. PA 2. Opt 3. ESA M, SD
1. PA 0.36
0.03 (0.05) 0.06 0.190, 88
2. Opt 0.47
0.04 (0.07) 0.07 0.36, 0.93
3. ESA 0.09 (0.06)
0.04 (0.07) 0.06 - 0.10, 0.09 [0.08,
(B) Gratitude condition
1. PA 2. Grat 3. TG M,SD
1. PA - 0.43
2. Grat 0.17 (0.12) 0.18 - 1.00
3. TG 0.24
- 0.10, 0.16
1. PA 2. SC 3. ESA M, SD
1. PA 0.34
0.09 (0.06) 0.18 0.01, 0.11
2. SC 0.36
-0.09 (0.06) 0.19 0.05 0.10
3. ESA 0.09 (0.06)
0.05 (0.05) 0.11 - 0.12, 0.10
Note: Within each section, we displayed the latent covariances and correlations for the control condition below the diagonal
and for the intervention condition above the diagonal. Covariance estimates with standard errors in brackets and standardized
solutions in bold. The latent means in the control condition were set to zero. Latent mean differences and standard deviations
in the intervention condition are presented in the columns along with the corresponding confidence intervals. All models
assume measurement invariance across conditions
Abbreviations: ESA, emotional self-awareness; Grat, gratitude; Opt, optimism; PA, positive affect; SC, self-compassion; TG, trait
12 HEEKERENS ET AL.
differences were d=0.22, 95% CI [-0.05, 0.48], d=0.16, 95% CI [0.12, 0.43], and d=0.01,
95% CI [0.26, 0.28], respectively.
Accordingly, Table 2 shows that the (unstandardized) latent mean differences between the
optimism, gratitude, and self-compassion conditions, and the control condition was 0.19, 95%
CI [0.03, 0.40], 0.14, 95% CI [0.07, 0.36], and 0.01, 95% CI [0.20, 0.21], respectively. None
of the mean differences was significantly different from 0.
According to our third hypothesis, we expected that the effects of the optimism and self-
compassion interventions depend on trait emotional self-awareness and that the effects of
the gratitude condition depend on trait gratitude. This hypothesis assumes interactions
between the intervention conditions and the personality variables. Because interaction is a
symmetrical concept, these proposed interactions would imply that the regression slopes
between the dependent latent variables and the potential latent moderator variables differ
between the intervention and control groups. If there are no differences between the inter-
vention and control groups in the regression coefficients, there will be no moderation
(interaction) effect. To test our hypothesis, we compared two multiple group models against
each other. The first model is depicted in Figure 1. It freely estimates the regressions
between the proposed moderators and the outcome variables in the intervention and the
control conditions. According to our hypothesis and assuming a linear moderation effect, the
size of the negative regressions in the optimism condition should be larger than in the
control condition because we expected individuals lower in emotional self-awareness to bene-
fit more (or individuals higher in emotional self-awareness to benefit less or even experience
adverse effects). Results for Model (a) in Figure 1 reveal that the size of the (unstandardized)
regression for positive affect was actually smaller in the optimism compared with the control
condition, B =0.06 versus B =0.21. For optimism, the coefficients were B =0.07 ver-
sus B =0.08. To test whether these differences were statistically significant, we calculated
a second model under the assumption of equal regression coefficients across groups
(i.e., assuming that the relation between emotional self-awareness and the outcomes is the
same in the optimism and the control condition). A scaled χ2difference test showed that the
fit of the second model was not significantly worse than the fit of the first model, χ2diff =1.00,
df diff =2, p=.606, indicating that there is not any significant moderation effect. We repeated
the steps to test the expected moderation effects in the gratitude and self-compassion condi-
tions. According to our hypothesis, the size of the positive regressions in the gratitude condition
should be larger than in the control condition because we expected individuals high in trait
gratitude to benefit more. Results for Model (b) in Figure 1 and Table 2 reveal that the coeffi-
cients for positive affect were B =0.43 versus B =0.26 and for gratitude B =0.89 versus 0.95.
The differences were not statistically significant, χ2diff =2.59, df diff =2, p=.274, showing that
there is no significant moderation effect. Finally, we assumed that the size of the negative
regressions in the self-compassion condition should be smaller than in the control condition
because we expected individuals high in emotional self-awareness to benefit more. Results for
Model (c) in Figure 1 and Table 2 reveal that the coefficients for positive affect were B =0.20
versus B =0.21 and for gratitude B =0.19 versus 0.10. The differences were not statisti-
cally significant, χ2diff =3.07, df diff =2, p=.215, indicating that there is no significant
COGNITIVE-AFFECTIVE RESPONSES TO ONLINE PPI 13
Exploratory and additional analyses
We also investigated intervention effects on positive self-relevant thinking (Mongrain &
Anselmo-Matthews, 2012), explored variables that potentially influence the effectiveness of our
interventions (person-activity fit; Proyer et al., 2015; Schueller, 2011), and used text analysis to
further investigate emotional and cognitive processing during the writing process (Guastella &
Positive self-relevant thoughts
Univariate analysis of variance results indicates significant differences in positive self-relevant
thoughts across groups, F(3,421) =13.51, p=.000, η2=0.09, 90% CI [0.05,0.13].
Table 1 reveals that participants in the control condition self-rated on average 23% of their
thoughts as both positive and self-relevant compared with 39% in the optimism condition, 37%
in the gratitude condition, and 22% in the self-compassion condition. Post hoc comparisons
reveal significant differences between the optimism and the control conditions, diff =1.63, 95%
CI [0.73, 2.54, the gratitude and the control conditions, diff =1.41, 95% CI [0.50, 2.33], the opti-
mism and the self-compassion conditions, diff =1.75, 95% CI [0.84, 2.66], and the gratitude and
the self-compassion conditions, diff =1.53, 95% CI [0.61, 2.45]. There were no significant differ-
ences between the self-compassion and the control conditions, diff =0.12, 95% CI [1.04,
0.80], as well as the optimism and gratitude conditions, diff =0.22, 95% CI [0.69, 1.13].
Results first show that participants liked the positive interventions better than the daily activi-
ties control. Specifically, the average score for liking on a scale ranging from 1 to 7 was 4.91 in
the control condition compared with 5.36 in the optimism condition, d=0.31, 95% CI [0.04,
0.58], 5.47 in the gratitude condition, d=0.38, 95% CI [0.11, 0.65], and 5.40 in the self-
compassion condition, d=0.36, 95% CI [0.09, 0.63].
Second, participants in the optimism and
gratitude conditions reported that they had benefited more than participants in the control con-
dition, 4.70 versus 4.25, d=0.28, 95% CI [0.02, 0.55] and 5.42 versus 4.25, d=0.77, 95% CI
[0.49, 1.04], respectively. There was no significant difference between the self-compassion and
the control condition, 4.58 versus 4.25, d=0.22, 95% CI [0.05, 0.49]. Third, participants per-
ceived the self-compassion intervention as more difficult than the control intervention, 2.83 ver-
sus 2.28, d=0.34, 95% CI [0.06, 0.61], whereas there were no significant differences between
the optimism and the control condition, 2.53 versus 2.28, d=0.15, 95% CI [0.12, 0.42], and
the gratitude and the control condition, 2.65 versus 2.28, d=0.23, 95% CI [0.04, 0.50].
Participants on average wrote 341 words in the control condition, which exceeded the aver-
age word counts in the optimism condition, 245, d=0.51, 95% CI [0.24, 0.78], the gratitude
condition, 247, d=0.56, 95% CI [0.29, 0.84], and the self-compassion condition, 196, d=
0.96, 95% CI [0.68, 1.25]. The data contained four extreme values (optimism condition:
14 HEEKERENS ET AL.
2, gratitude condition: 1, control condition: 1) identified as values that fall above 3 standard
deviations above the third quartile or participants who wrote more than 931 words (mean for
all: 257.69, median for all: 224). Statements about the significance of group differences do not
differ between the results obtained from the complete data and results obtained after remov-
ing outliers, which were 332 versus 226 words, d=0.73, 95% CI [0.45, 1.00], in the optimism
condition, 332 versus 240 words, d=0.63, 95% CI [0.35, 0.90], in the gratitude condition,
and 332 versus 196 words, d=0.98, 95% CI [0.70, 1.27], in the self-compassion condition
(also see Aguinis et al., 2005; Dickerhoof, 2007). Text analysis results using the LIWC pro-
gram show that participants in the optimism and gratitude conditions used more positive
emotion words than participants in the control condition. As the table in Appendix S4
reveals, the average amount of positive emotion words was 27% in the control condition com-
pared with 55% in the optimism condition, d=1.28, 95% CI [0.99, 1.57] and 63% in the grat-
itude condition, d=1.78, 95% CI [1.46, 2.10]. Participants in the self-compassion condition
did not use significantly more positive emotion words than control participants, 31% versus
27%, d=0.22, 95% CI [0.06, 0.49]. However, the use of positive emotion words was posi-
tively associated with positive affect after the self-compassion writing session, r=.26, p=
.007, whereas there was virtually no association in the control condition, r=.01, p=.905.
In addition, participants in the gratitude and self-compassion conditions used more negative
emotion words compared with the control condition, 16% versus 10%, d=0.63, 95% CI [0.36,
0.91] and 36% versus 10%, d=1.80, 95% CI [1.48, 2.13], respectively. Participants in the opti-
mism condition did not use more negative emotion words, 10% versus 10%, d=0.08, 95% CI
[0.18, 0.35]. Interestingly, the use of negative emotions words was negatively associated
with positive affect in the control condition, r=.28, p=.004, but not in the optimism con-
dition, r=.06, p=.513. One reason for this may be that the word count program we used
did not count negated emotional expressions (e.g., “I will not be afraid”). Moreover, partici-
pants in the optimism, gratitude, and self-compassion conditions used more insight words
compared with control participants, 30% vs. 18%, d=0.99, 95% CI [0.71, 1.28], 24% versus
18%, d=0.50, 95% CI [0.23, 0.78], and 30% versus 18%, d=0.87, 95% CI [0.58, 1.15], respec-
tively. Participants in the gratitude and self-compassion conditions also used more causal
words, 16% versus 11%, d=0.56, 95% CI [0.29, 0.84] and 20% versus 11%, d=0.90, 95% CI
[0.61, 1.18], respectively. There was no significant difference between the optimism and the
control condition, 12% versus 11%, d=0.10, 95% CI [0.17, 0.37]. However, the use of causal
words among BPS participants was positively associated with gratitude ratings after the
intervention, r=.19, p=.049, whereas the association was negative in the control condition,
r=.27, p=.005. Finally, in line with the observation that participants in the optimism
and gratitude conditions reported more positive self-relevant thoughts, text analysis results
show that participants in the optimism and gratitude conditions used more positive emotion
words to describe their thoughts compared with control participants, 11% versus 8%, d=
0.62, 95% CI [0.34, 0.89] and 16% versus 8%, d=0.55, 95% CI [0.28, 0.83], respectively. There
was no significant difference in the self-compassion condition, 7% versus 8%, d=-0.06, 95%
CI [0.33, 0.21].
The aim of the present study was to investigate cognitive-affective responses to online positive-
psychological interventions and to explore differential effect patterns. Such knowledge is
COGNITIVE-AFFECTIVE RESPONSES TO ONLINE PPI 15
fundamental to the effective use and further development of positive-psychological interven-
tions, which seems desirable considering their widespread application in digital formats
(see Diefenbach, 2018; Hone et al., 2014, for reviews).
In line with earlier studies, we found that the BPS intervention increased optimism
(Heekerens & Eid, 2020) and that the gratitude letter increased gratitude immediately after the
writing tasks (Davis et al., 2016). This finding provides further evidence that online positive-
psychological interventions can facilitate specific adaptive cognitions (Quoidbach et al., 2015;
also see Lyubomirsky & Layous, 2013). As in one previous study, effects on optimism and grati-
tude did not differ when comparing the BPS intervention group with the gratitude exercise
group (Huffman et al., 2014). Other than expected differences in positive affect between the
intervention conditions and the control task did not reach statistical significance. This is sur-
prising given that numerous studies have demonstrated increases in positive affect following
the BPS intervention (Heekerens & Eid, 2020), the gratitude letter exercise (Davis et al., 2016),
and self-compassionate writing (Kirby et al., 2017). More so, and at odds with earlier studies
(e.g., Shapira & Mongrain, 2010), the self-compassionate writing showed no other beneficial
effect on cognitions. One reason for small or absent effects in our study is that we used very
brief interventions (15 min writing) that were administered once. In addition, the self-
compassion exercise may have lacked explicit instructions to acknowledge experienced difficult
events or emotions, which may be necessary to develop self-compassionate responses. The
instructions we used made participants perceive the self-compassionate exercise as less helpful
and more complicated than the gratitude letter exercise and the best-possible-self intervention.
It could have been helpful if participants had the opportunity to ask questions regarding the
instructions (Dreisoerner et al., 2020). Particularly self-compassion interventions may require
multiple administrations to be effective (e.g., 15 min daily meditation practice over the course
of 8 weeks; Fredrickson et al., 2008; or 2 h weekly group sessions over the course of 8 weeks;
Neff & Germer, 2013). In addition, our results indicate an increase in positive self-relevant
thoughts immediately after the BPS intervention and the gratitude letter exercise (Mongrain &
Anselmo-Matthews, 2012), which aligns well with the increase observed in levels of optimism
and gratitude following these interventions.
At odds with earlier studies, we found that the cognitive-affective responses to the gratitude let-
ter did not differ depending on the level of baseline trait gratitude. This finding neither supports
one experiment finding that individuals higher in trait gratitude report more positive emotions
following gratitude interventions (Watkins et al., 2003, study 4), nor one experiment finding
that individuals lower in trait gratitude report more positive emotions (Harbaugh &
Vasey, 2014). In addition, we found that differences in baseline trait of emotional self-awareness
do not affect cognitive-affective responses to the BPS intervention, which contradicts results
from two experiments showing that individuals low in emotional processing particularly
benefitted from the BPS intervention (Austenfeld et al., 2006; Austenfeld & Stanton, 2008). Rea-
sons for the divergent results include differences in the frequency of intervention exposure
16 HEEKERENS ET AL.
(single vs. repeated administrations) or the outcomes under investigation (optimism and posi-
tive affect vs. negative affect). For example, individuals who generally pay little attention to
their own emotions may require longer interventions to derive an additional self-regulatory
advantage and succeed in regulating negative affective states.
We examined participants' writing and asked them to list 10 current thoughts after the interven-
tions with the aim of exploring cognitive-affective processing. As expected, participants in the
optimism and gratitude conditions used more positive emotion and insight words than partici-
pants in the control condition (Heekerens & Heinitz, 2019; Owens & Patterson, 2013). It might
be that these interventions allow participants to draw connections between their present life
and future dreams or reflect their relationships with meaningful others, which may facilitate
self-exploration and understanding (King, 2002). Evidence from the expressive writing para-
digm suggests that participants who used more positive emotion and insight words while writ-
ing about traumatic experiences gained most from the writing sessions (see Pennebaker, 2011,
for a review). Building on this, results from the current study suggest that positive-psychological
interventions may accomplish the same, providing a vital alternative to reactivating negative
experiences to increase psychological health (King, 2001). Interestingly, participants in the grat-
itude condition also used more negative emotion words in their writings compared with control
participants. This finding highlights that some positive-psychological interventions do require
participants to confront unpleasant emotions while experiencing positive emotions at the same
time (Killam & Kim, 2014). In addition, participants in the gratitude condition used more nega-
tive emotion words in their writings compared with control participants and although partici-
pants in the BPS intervention did not show an increased use of negative emotion words, the use
of such words was unrelated to positive affect, whereas in the control condition a negative rela-
tionship was observed. This finding suggests that some positive-psychological interventions do
require participants to confront unpleasant emotions and that positive-psychological interven-
tions might help to facilitate an adaptive integration of negative emotional states, probably
through simultaneously experiencing positive emotions (Killam & Kim, 2014).
Limitations and future research
Several limitations and proposals for future research should be mentioned. First, there was only
one occasion of measurement after the intervention and our design did not permit conclusions
regarding follow-up effects. Future studies should apply longitudinal designs and test how
positive-psychological interventions differentially affect various outcomes over time (Maxwell &
Cole, 2007). Second, our study revealed that the interaction effects are very small, and in most
analyses much smaller, than typically found in moderator regression analyses (Champoux & Pet-
res, 1987; Chaplin, 1991). Therefore, the sample size of our study was too small to detect such
small interaction effects with sufficient power. Future studies can use the sizes of these estimated
interaction effects to calculate the appropriate size in a priori power analyses (see Aguinis
et al., 2005, for a deeper discussion). Third, the self-reports we used limit our results to conscious
aspects of the constructs under investigation. Although there is compelling evidence that the sub-
jective indicators we used are meaningful (e.g., Oswald & Wu, 2010), future studies should also
COGNITIVE-AFFECTIVE RESPONSES TO ONLINE PPI 17
evaluate positive-psychological interventions based on more objective metrics (e.g., real-time
measures; Alexandrova, 2005; Kahneman, 2000). Fourth, participants' motivation to complete
the interventions might primarily stem from the payment they received. Research shows that
motivation influences the effectiveness of positive-psychological interventions and effect sizes are
likely larger in samples of individuals who actively seek to become happier (Lyubomirsky
et al., 2011; Parks et al., 2012). Fifth, although our results support the notion that positive-
psychological interventions can affect specific outcomes (e.g., optimism or gratitude), longitudi-
nal mediation studies are needed to establish whether increases in these variables explain subse-
quent increases in well-being (see Heekerens & Heinitz, 2019; Heekerens et al., 2019, for
examples). Such studies should also investigate the role of positive self-relevant thinking
(Mongrain & Anselmo-Matthews, 2012) and provide text analyses to deepen our understanding
of cognitive and emotional processing during the writing sessions (Pennebaker, 2011).
The first author of this study received a scholarship from the Friedrich Naumann Foundation
for Freedom and is deeply grateful for the financial and personal support.
CONFLICT OF INTEREST
The authors declare that they have no conflict of interest.
Theauthorsdeclarethatthecurrentstudymeetsethical standards and was approved by the Ethics Com-
mittee of the Freie Universität Berlin. All participants signed informed consent prior to participation.
JH and BM designed the experiments. JH conceived and performed the experiments. JH, ME,
and BM analyzed the data. ME and KH contributed to reagents/materials/analysis tools. JH
wrote the paper.
Parceling in structural equation modeling refers to a technique that aggregates individual items into “parcels”
and uses those parcels, instead of items, as the indicators of latent constructs (Matsunaga, 2008). In this study,
we randomly aggregated the 12 items of the MDMQ (affect) and the 10 items of the SCS (self-compassion) into
each three parcels.
For reasons of simplicity, we report ANOVA results here. We additionally performed sensitivity analyses for
thought ratings using negative binomial regressions. Statements about the significance of group differences do
not differ between the results of the more advanced methods and the normal approximations.
Again, we reported standardized mean difference and confidence intervals here because we assumed normal
approximations due to our comparably large sample. Sensitivity analyses were conducted for all tests. Specifi-
cally, group differences for rating scales were tested using probit regressions and for text analyses (percentages)
using zero inflated beta regressions. Statements about the significance of group differences do not differ
between the results of the more advanced methods and the normal approximations.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available on request from the corresponding
author, JH. The datasets are not publicly available because they contain information that could
compromise the privacy of research participants.
18 HEEKERENS ET AL.
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Additional supporting information may be found in the online version of the article at the pub-
How to cite this article: Heekerens, J. B., Eid, M., Heinitz, K., & Merkle, B. (2022).
Cognitive-affective responses to online positive-psychological interventions: The effects of
optimistic, grateful, and self-compassionate writing. Applied Psychology: Health and
24 HEEKERENS ET AL.