Reward and Threat Sensitivity as Mediators of Positive and Negative Affect Treatment
Phase: NA
Conditions: Depression, Anxiety
Sponsor: University of California, Los Angeles

Affect Treatment for Depression and Anxiety Trial Protocol 1 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Trial Protocol for 
“Reward and Threat Sensitivity as Mediators of Positive and 
Negative Affect Treatment” 
 
Last updated February 5th, 2025 

Affect Treatment for Depression and Anxiety Trial Protocol 2 
 
Trial Registration 
The trial was officially registered on clinicaltrials.gov on January 10th, 2022. The registry 
name is “Affect Treatment for Depression and Anxiety” (Clinical Trials ID#: NCT05203861). This 
study is funded by the National Institute of Health (R33MH115138). Dr. Michelle G. Craske is the 
contact principal investigator (PI), and Drs. Alicia Meuret and Thomas Ritz are additional PIs of 
the study. Correspondence concerning this protocol should be addressed to Michelle G. Craske, 
Department of Psychology, University of California, Los Angeles, 405 Hilgard Avenue, Los 
Angeles, CA 90077 (email: mcraske@mednet.ucla.edu), or to Alicia E. Meuret, Department of 
Psychology, Southern Methodist University, Dallas, P.O. Box 750442, Dallas, TX 75275 (e-mail: 
ameuret@smu.edu). 
 
Public Title: “Affect Treatment for Depression and Anxiety” 
Scientific Title: “Reward and Threat Sensitivity as Mediators of Positive and Negative Affect 
Treatment” 
 
Roles and Responsibilities 
The Executive Committee of the three PIs (Drs. Craske, Meuret, and Ritz) will be chaired 
by Dr. Craske. The Executive Committee will hold weekly teleconference calls. Monthly calls will 
include key investigators as needed, including our biostatistician (Dr. Rosenfield), Consultants 
(Drs. Pizzagalli and Hollon) as well as research staff. In these monthly meetings, we will address 
issues of data collection, budget, recruitment, treatment delivery, data management and analysis, 
and training and ongoing review to maintain interrater reliability. Also, we will discuss human 
subjects’ issues, especially the recruitment of minority participants. 
The Executive Committee will review all publications and presentations derived from data 
garnered in this grant in order to ensure its quality. Assignment of publications and other academic 
products of this project will be decided on by the Executive Committee, with lead roles equitably 
rotated among the three PIs. Disagreements will be resolved by majority decision. At the end of 
the trial, each site will receive a cleaned and checked data file; however, all publications and 
presentations derived from that data in the future will be vetted within the Executive Committee 
prior to release. 
 
Background and Significance 
Affective neuroscience has identified two core systems that regulate thoughts and 
behaviors. The first is the approach or appetitive system, which motivates actions towards goals 
and rewards, and produces positive emotions such as enthusiasm and pride. The second is the 
withdrawal or defensive system, which motivates avoidance of aversive outcomes or 
punishments, and is linked with negative emotions. Despite the fundamental role played by both 
appetitive and defensive systems in depression and anxiety, treatment has focused largely upon 
decreasing withdrawal (and negative affect) rather than increasing approach (and positive affect). 
This study will test mechanisms of a novel, pilot-tested treatment specifically designed to target 
deficits in the appetitive system. This goal is aligned with the NIMH Research Domain Criteria 
(RDoC) initiative, in which the appetitive positive valence system is a critical dimension of 
psychopathology. 
Low positive affect is increasingly recognized as a critical transdiagnostic feature of many 
mental health disorders1, 2. In the context of depression and anxiety, low positive affect is not only 
correlate but also a risk factor for onset3-7 and is associated with poorer longitudinal course8. 
Furthermore, low positive affect is associated with suicidal ideation and the related construct of 
anhedonia (or markedly diminished interest or joy in usual activities) is a predictor of suicide 
ideation and attempt9, 10, even when controlling for other cognitive and affective symptoms of 
depression11, 12. Patients with depression view the restoration of positive mood as their primary 
treatment goal, over reducing negative symptoms13. Yet, treatments to date have not reliably 
improved positive affect. The goal of the current study was to test replicability of a novel treatment 
for positive affect and to evaluate processes underlying therapeutic effects. 
Meta-analyses of evidence-based psychotherapies for depression (primarily cognitive– 
behavioral therapy and mindfulness-based cognitive therapy) yield low to moderate effects sizes 

Affect Treatment for Depression and Anxiety Trial Protocol 3 
 
for change in positive affect, with significant heterogeneity across studies14. Re-analyses of prior 
RCTs show that cognitive therapy and antidepressant medication normalized elevations in 
negative affect but had little effect on positive affect15 and were less successful in raising positive 
affect than decreasing negative affect16. Even Behavioral Activation therapy, which aims to 
increase positive affect through response contingent positive reinforcement from rewarding 
activities17 has limited effects on positive affect in the few studies in which such effects have been 
reported18, 19. This is perhaps not surprising since little attention has been given to how to conduct 
behavioral activation in a manner that maximizes rewarding, positive emotional experiences20. 
Pharmacological treatments have mixed effects and may even worsen positive emotions or 
responses to rewarding stimuli21-24, although newer pharmacological approaches such as kappa- 
opioid antagonists and ketamine are showing promising effects25, 26. 
As noted by Dunn (2012)27 little attention has been given to how to conduct behavioral 
activation, or psychological treatments in general, in a manner that maximizes positive emotional 
experience. We hypothesize therapeutic strategies which specifically target the mechanisms 
underlying low positive affect will lead to greater improvement in positive affect than extant 
treatments. 
Low positive affect is a core feature of anhedonia (or diminished interest or joy in usual or 
pleasurable activities), and both low positive affect and anhedonia can be viewed as expressions 
of an underlying dysregulated reward system. The reward system affects the ability to anticipate 
or predict expected rewards; associates relative values and costs with rewards; determines the 
effort required to obtain rewards; integrates this information to decide whether it is worthwhile to 
obtain rewards and when to become motivated to perform the necessary actions to obtain 
rewards28. While there are many aspects of the reward system, including action selection/decision 
making, habit responding29 and satiation, we focus on three frequently emphasized 
components30: 1) anticipation-motivation for reward, 2) initial responsiveness to reward 
attainment, and 3) reward learning.31,28 The anticipation-motivation component drives adaptive 
behaviors towards rewarding stimuli (e.g., planning and looking forward to a vacation) and is 
related to the effort expended to receive reward. It is dominated by “wanting.” The initial attainment 
component refers to the pleasure or hedonic impact of rewarding stimuli (e.g., the pleasure whilst 
on vacation) and is dominated by “liking.” The learning component typically involves Pavlovian or 
instrumental associations and predictions about future rewards based on past experiences. 
Thomsen and colleagues31 relate wanting, liking, and learning of reward to the appetitive, 
consummatory, and satiety phases of the pleasure cycle. Their model recognizes that each 
component serves a particular survival function, is associated with different behavioral outputs, 
and is supported by different brain networks (albeit with some overlapping areas). 
Individuals who are depressed show deficits in anticipation-motivation, initial 
responsiveness to attainment and learning of reward across multiple indices.32, 33 Furthermore, 
there is compelling evidence for linkages between reward hyposensitivity and low positive affect, 
mostly in the context of depression-related anhedonia.34-37 
Anticipation-Motivation. (1) Self-report: Dysphoric individuals expect to feel less positive 
emotions in future positive events38, 39 and report less positive emotion in anticipation of monetary 
rewards37 compared to healthy controls, although the evidence is not entirely robust.40 (2) 
Behavior: Trait anhedonia among healthy individuals correlates with choosing easy tasks for a 
small reward over harder tasks for larger rewards, indicative of less motivation (i.e., expenditure 
of effort) to gain reward.41 Also, depressed individuals make fewer high reward/high effort choices 
than healthy controls,42 and importantly, the motivational effort they expend to obtain rewards 
decreases with higher anhedonia.42, 43 (3) Psychophysiology: Monetary incentives have 
consistently been shown to be associated with cardiac acceleration.44-47Dysphoric individuals 
show less reliable acceleration of heart rate than healthy controls when performing memory or 
mental arithmetic tasks that are linked to monetary rewards48-50. (4) Neurophysiology: Depressed 
individuals show reduced activation in reward circuitries in anticipation of reward.36,51—57 
Importantly, reduced ventral striatum responsivity to incentive stimuli and reward expectancy- 
prediction error is particularly related to anhedonic symptoms57—59. 
Initial Responsiveness to Reward Attainment. (1) Self-report: Evidence for deficits in self- 
rated liking of reward as a function of depression is mixed. Some data fail to show deficits in liking 
of reward.60—62 However, a meta-analysis of methodologically rigorous studies concluded that 

Affect Treatment for Depression and Anxiety Trial Protocol 4 
 
there was evidence for blunted self-reported positive emotion to positive stimuli in laboratory tasks 
in depressed individuals.63 Importantly, lower levels of self-reported positive emotions to positive 
stimuli are more strongly related to anhedonia than to depression.64,65 (2) Attention Bias: 
Depressed individuals show less attention to positive stimuli than controls as measured via 
response latency times in dot probe tasks and eye tracking.64, 66-68 Attention to positive information 
is associated with positive affect but has not been linked to anhedonia per se.69 (3) 
Psychophysiology: Anhedonia is associated with reduced cardiac acceleration while viewing 
pleasant pictorial stimuli70 or during imagery of pleasant scripts.71 (4) Neurophysiology: In 
depressed samples, ventral striatum and lateral global pallidus hypoactivity to positive stimuli72—
74 is strongly associated with symptoms of anhedonia.72,74-77 These effects were specific to 
anhedonia above and beyond negative symptoms of anxiety or depression.76,77 
Reward Learning. (1) Behavior: The propensity to develop a response bias to stimuli that 
are more frequently rewarded is less likely to develop over time as a function of higher depressive 
symptoms.78-80 Importantly, impairments in response bias formation among clinically depressed 
individuals correlate with self-reported anhedonia.78-79,81 Furthermore, reduced reward learning 
predicted elevated anhedonia symptoms one month later78 and depressed adults with poor (as 
compared to relatively intact) reward learning were almost 8 times more likely to remain 
symptomatic at the end of SSRI or psychotherapy.79 (2) Neurophysiology: Depressed individuals 
and remitted individuals show reduced activation in reward circuitries during reward learning82-83, 
and poor reversal learning after unexpected reward delivery in depressed individuals is 
associated with deficits in the ventral striatum.84 The monetary incentive delay task also reveals 
lower activation in the dorsal caudate (an area connected with feedback driven contingency 
learning) in depressed individuals.74 There is some evidence for blunted ventral striatal responses 
to Pavlovian83 and instrumental conditioning tasks85 in depression with neural responses 
correlating with self-reported anhedonia.82,85 
 
Given the evidence cited, a treatment that specifically targets three cardinal sub-domains 
of reward sensitivity within the RDoC Positive Valence Systems, Anticipation-Motivation, Initial 
Responsiveness to Reward Attainment, and Reward Learning, may be particularly potent for low 
positive affect. As noted, existing psychological treatments mostly target negative affect and while 
behavioral activation is designed to increase engagement in pleasant activities, little attention has 
been given to optimization of positive emotions during the planning and conduct of such 
activities.27,86 Drawing from affective neuroscience and experimental psychopathology, we 
developed a treatment that specifically targets reward hyposensitivity, coined Positive Affect 
Treatment (PAT).87 In our previous randomized controlled trial88, PAT was compared to cognitive 
behavior therapy that targeted reductions in negative affect (termed Negative Affect Treatment, 
NAT) for individuals with moderate to severe depression or anxiety. PAT resulted in higher 
positive affect, lower negative affect and less severe depression and anxiety at six months. 
 
Specific Aims 
The goal is to evaluate whether Positive Affect Treatment (PAT) leads to significantly 
higher positive affect, lower interviewer-rated anhedonia, and lower symptoms of depression and 
anxiety (outcome measures) than cognitive behavioral therapy that focuses on negative affect 
(called Negative Affect Treatment, NAT). A second goal is to evaluate whether PAT leads to 
greater (1) reward anticipation-motivation, (2) initial reward responsiveness or (3) reward learning 
(reward targets) compared to NAT. A third goal is to evaluate whether changes in reward targets 
correlate with changes in outcome measures (i.e., self-reported positive affect, interview-rated 
anhedonia, and symptoms of depression and anxiety). Targets will be assessed before, twice 
during, posttreatment, and one-month follow-up, using physiological, behavioral, cognitive and 
subjective/experiential measures. Participants will be individuals who score above clinical cut-
offs on (1) low positive affect, (2) depression or anxiety, and (3) functioning. 
Aim 1: Treatment Efficacy and Target Engagement. Hypotheses: a) Clinical Outcome 
(comprised of PANAS-P, DASS Total, and in interview-rated anhedonia) improves more in PAT 
than in NAT, b) each of the three reward targets show significantly greater target engagement 
(improvement) in PAT than NAT, and c) threat sensitivity target will improve more in NAT than in 
PAT. 

Affect Treatment for Depression and Anxiety Trial Protocol 5 
 
Aim 2: Specificity of Target Engagement with Respect to Threat versus Reward. 
Hypotheses: i) PAT leads to significantly greater improvements in reward anticipation-
motivation, initial responsiveness to reward attainment, or reward learning than NAT, and ii) 
PAT leads to significantly greater changes in reward sensitivity than threat sensitivity relative to 
NAT. 
Aim 3: Mediation. Hypothesis: Reward sensitivity targets and the threat sensitivity target 
will mediate treatment condition (PAT vs. NAT) differences in the improvement in clinical 
outcomes. 
Aim 4: Trimming of Target Measures.  
 
Methods 
Trial Design 
This will be a multi-site, assessor-blinded, parallel, 2-arm, stratified (medicated, y/n), 
randomized (1:1) clinical superiority trial, for help-seeking adults with moderate to severe 
depression or anxiety, functional impairment, and low positive affect. 
 
Participants 
Participants will be recruited in the U.S. A brief study description will be distributed via lab 
websites, social media, clinicaltrials.gov, and brochures to local agencies. A 3-stage standardized 
screening process will begin with online screening of demographic, medical and symptomatic 
eligibility criteria. Eligible persons then will complete a more in-depth phone screen by study staff 
who detailed study procedures. The third stage will involve a SCID-5 Research Version90 (for 
exclusion criteria) conducted by reliability-certified advanced research associates, with 
consensus diagnosis overseen by experienced clinicians. Cross-site consistency for diagnostic 
interviews will be maintained by (1) annual joint teleconference among interviewers and PIs to 
discuss diagnostic issues, and (2) cross-site consistency checks, in which 20% of the audio or 
video-taped interviews at each site will be randomly selected to be blindly rated by interviewers 
of the other site. 
Inclusion criteria will consist of (1) aged 18 to 65 years old, (2) English-speaking, (3) low 
positive affect indexed by < 24 on the Positive Affect Subscale of the Positive and Negative Affect 
Schedule (PANAS-P),89 or 1SD below the population mean90 (4) Depression, Anxiety and Stress 
Scales91 scores of ≥ 11 for depression, ≥ 6 for anxiety or ≥ 10 for stress to represent moderate to 
severe symptom severity,92 (5) ≥5 on any Sheehan Disability Scale subscale to represent clinically 
significant impairment93 and (6) willingness to refrain from initiating psychosocial/pharmacological 
treatment until study completion. 
Exclusion criteria will consist of (1) Patient report of serious medical conditions - such as 
history of serious, uncontrolled medical illness, or instability (including significant cardio- 
pulmonary disease, organic brain syndrome, seizure disorder, cerebrovascular disease, thyroid 
dysfunction, and diabetes), (2) active suicidal ideation, (3) lifetime bipolar disorder, psychosis, 
mental retardation, or organic brain damage (4) substance abuse in last 6 months or dependence 
in the last 12 months (5) 11 or more cigarettes per week or nicotine equivalent (6) history of 
marijuana, cocaine, or stimulant use 5-7 times per week or more before 15 years old (e.g., 
amphetamine, cocaine, methamphetamine) (7) pregnancy (8) bupropion, dopaminergic or 
neuroleptic medication use in the past 6 months, (9) Heterocyclics and SSRIs are permitted if 
stabilized (3 months), and PRN benzodiazepines and beta-blockers are permitted but 
discouraged on laboratory assessment visits, (10) refusal to be video/audio taped. 
 
Interventions 
Positive Affect Treatment 
Positive Affect Treatment (or PAT) includes three core elements. The first is behavioral 
activation to rewarding experiences augmented by imaginal recounting and reinforcement of 
positive mood effects. The second is cognitive exercise focusing on identifying positive aspects 
of experience, taking responsibility for positive outcomes, and imagining future positive events. 
The third is the cultivation and savoring of positive experiences through exercises of appreciative 
joy, gratitude, generosity, and loving-kindness. The behavioral activation with imaginal 

Affect Treatment for Depression and Anxiety Trial Protocol 6 
 
recounting is continuous throughout the fifteen weekly therapy sessions, while cognitive 
exercises are the focus of sessions 8-11, and cultivating positive emotions is the focus of sessions 
12-14. Session 15 is relapse prevention. 
Behavioral activation with imaginal recounting. Behavioral activation targets the 
anticipation and motivation for reward by designing rewarding activities and response to 
attainment of reward through engagement in rewarding activities. Detailed labeling of positive 
emotions experienced during the activities facilitates reward attainment. Changes in mood are 
closely monitored from before to after each activity to reinforce the positive mood-inducing effects, 
and in so doing, targets reward learning (i.e., instrumental learning by which engaging in a specific 
activity increases positive mood). To deepen and savor the rewarding aspects of the experience 
each behavioral activity is followed by intensive, first-person perspective and present tense 
imaginal recounting through visualization and reimagining of assigned activities, including specific 
sensations, thoughts, emotions, and situational details. Other processes are likely taking place 
as well since the guided memory recounting involves shifting attention away from negative 
portions and toward positive portions of the behavioral experience. To that degree, it serves as 
a type of attentional control (shifting attention from one aspect of a situation to another). Such 
attentional control has been shown to be effective as a form of emotion regulation.94 The imaginal 
recounting resembles other memory specificity interventions for emotional disorders that have led 
to short-term significant improvements in overgeneral memory, depression, hopelessness, 
problem solving, anticipatory pleasure, and behavioral intention to engage in activities.95-99 In 
Positive Affect Treatment, the primary goal of imaginal recounting is to enhance the hedonic 
impact of reward and to improve the skill of appreciating and liking a rewarding event. Additionally, 
imaginal recounting involves sustained attention to positive stimuli, which has shown to lead to 
subsequent preferences for positive stimuli, albeit in nonclinical samples.100 Increased preference 
for positive material is posited to, in turn, decrease interest in negative information.101 
Furthermore, training positive attentional preferences may enhance attentional vigilance for and 
orienting toward positive information that eventually shifts more elaborate attention mechanisms 
toward positive meanings and facilitates encoding of positive information in daily experiences. 
Cognitive Exercises. PAT involves a set of cognitive training skills for attending to positive 
stimuli. Unlike cognitive therapy for depression which challenges negative cognitions, cognitive 
techniques in PAT aim to identify and savor positive aspects of experiences such as taking 
responsibility for positive outcomes or imagining and appreciating future positive events. Hence, 
the PAT cognitive skill set does not address negative thoughts or errors in thinking that may have 
contributed to negative assumptions and beliefs. Instead, all discussion focuses on attending to 
positive features of situations in the past, present, and future. Targeting attention is expected to 
impact mood as described with respect to the attentional mechanisms involved in imaginal 
recounting (i.e., increases in positive affect, increases in preference for positive stimuli, decreased 
interest in negative stimuli, and eventual shift toward more positive meanings101). Hence, even 
though there is little direct attempt to change appraisals, underlying meanings and appraisals may 
shift in a more positive direction indirectly as a function of the cognitive training exercises. 
The first cognitive skill, Finding the Silver Linings, trains clients to recognize and 
appreciate the positive features in everyday situations, even situations with a partly negative 
valence. The repeated practice of identifying multiple positive elements in everyday situations is 
presumed to enhance preference for, attentional vigilance to, and encoding of positive 
information.101 The second skill, Taking Ownership, involves repeated practice identifying one’s 
own behavioral contributions to positive outcomes in daily lives (reward learning) and savoring 
positive emotions of pride, mastery, and excitement (anticipating reward). Accomplishments can 
be read out loud in front of a mirror to deepen the experience. Taking ownership counters the 
depressive attributional bias to attribute positive outcomes to external factors and is consistent 
with experimental evidence for training a positive attributional bias.102 By asking clients to consider 
ways in which they may have contributed to a positive outcome, this skill may influence self- 
appraisals. The third skill, Imagining the Positive, is based on evidence for repeated practice 
imagining positive events to increase positive mood and positive interpretation bias.103-105 Clients 
are guided to repeatedly imagine as many positive aspects as possible about an upcoming event, 
including positive emotions such as excitement, joy, and curiosity, to facilitate the wanting of 
reward. 

Affect Treatment for Depression and Anxiety Trial Protocol 7 
 
Cultivate and Savor Positive Experiences Exercises. The final set of skills is designed to 
cultivate and savor positive experiences and include daily practices of the mental and physical 
act of giving. Practices in Loving-Kindness (i.e., mentally sending happiness, health, peace, and 
freedom from suffering) is described as an act of training one’s emotional experience toward 
warmth and tenderness106. It encourages the focus of awareness on loving and kind concern of 
other living beings, oneself, and the world.107 Even brief practices of Loving-Kindness108 have 
been shown to increase positivity toward self and others, improvements in positive affect and 
personal resources (e.g., personal relationship with others, physical health, self-acceptance, 
satisfaction).109 Preliminary evidence from proof-of-concept clinical trials in individuals with 
schizophrenia,110 post-traumatic stress disorder111, and more recently dysthymia112 show 
increases in positive emotions and an improved sense of self and others. Acts of Generosity (i.e., 
engaging in an act of generosity without expecting return) have been linked to improvements in 
positive mood.113,114 In a reciprocal cycle, prosocial behaviors have been shown to increase 
positive mood, which in turn, increases prosocial behaviors115. Furthermore, there is some 
evidence that the positive mood effects of prosocial behavior toward others are greatest for those 
with depression, at least in adolescent samples116. 
Other skills involve daily practices of the mental act of wishing good to self and others 
through Appreciative Joy (i.e., wishing happiness, joy, and fortune) and of generating a sense of 
gratefulness through the practice of Gratitude. Cultivating Gratitude (by creating gratitude lists, 
gratitude contemplation, or the behavioral expression of gratitude) leads to changes in positive 
mood, greater resourcefulness, and general well-being in studies with nonclinical participants117-
120. It is speculated that practicing Gratitude leads to an increased value of help from others,120,121 
which leads to seeking more social support and strengthening social bonds.122 This “broaden and 
build” approach123 is thought to add to resiliency.124 Appreciative Joy is a practice that involves 
feeling happiness for people with success, good fortune, or happiness. Similar to practices of 
Loving-Kindness, Appreciative Joy has been associated with increases in positive mood, positive 
thinking, interpersonal relations, empathic accuracy, and improvements in psychological distress, 
although study quality is often problematic.125,126 In a small study, Appreciative Joy alone was 
found to increase positive mood in a healthy sample.127 
Positive mood is rated before and after each exercise to assess and understand the 
mood- inducing effects. In so doing, the exercises across the three treatment modules also 
target the learning of reward (i.e., by engaging in this practice, mood improves). 
Negative Affect Treatment 
NAT will target elements of elevated threat responding as well as loss and frustrative 
nonreward, using cognitive behavioral therapeutic strategies. 
Augmented Exposure. The first module involves designing, planning, and practicing 
exposures to feared or stressful situations, sensations, or objects to reduce threat responding. 
Inhibitory learning and consolidation are optimized by implicit and explicit violation of 
expectancies, practices for enhanced generalization, and post-exposure analysis.128,129 
Augmented exposure included the part of behavioral activation for depression that directly targets 
avoidance of stressful situations.130 Note that behavioral activation toward rewarding or 
pleasurable activities was excluded to retain a focus upon reducing negative affect. 
Cognitive Restructuring. The second module targeted threat as well as loss and frustrative 
nonreward, and involves exercises for reducing threat appraisal by identifying overestimations of 
probability and cost for negative outcomes (relevant to depression and anxiety), excessive self- 
attribution for negative outcomes (i.e., self-criticism, particularly relevant to depression), and by 
developing evidence-based estimations, problem-solving and alternative interpretations for 
negative outcomes.131,132 
Respiratory Training. The third module uses a handheld capnometer to reduce 
hypocapnia and excessive arousal by means of shallower and slower breathing combined with 
feedback of partial pressure of end-tidal carbon dioxide levels.133-135 Although respiratory training 
was originally developed for panic disorder, low partial pressure of CO2 have been found to 
predict poor outcomes from cognitive– behavioral therapy for mixed anxiety disorders.136 In 
addition, breathing-based interventions have been shown to be effective for depression137 and to 
reduce depressive symptoms in anxious patients.135 

Affect Treatment for Depression and Anxiety Trial Protocol 8 
 
Session 15 is relapse prevention. 
 
Therapist Training, Supervision, and Fidelity 
Therapists will be Ph.D. students in clinical psychology with experience in cognitive- 
behavioral therapies for depression or anxiety. They will attend an annual 2-day standardized 
training workshop at UCLA led by Drs. Craske and Meuret, for initial training and to ensure proper 
recalibrations of therapy applications, troubleshooting, and additional therapist training. They will 
attend weekly supervision at their respective sites with the study PIs (Craske, Meuret). 
Supervision will include detailed feedback on videotaped treatment sessions and monthly cross- 
site supervision video calls with the supervising PIs, Dr. Steve Hollon (study consultant), and all 
study therapists to facilitate cross-site consistency. Additional consultation from Dr. Hollon will be 
provided as needed. In the event of symptom worsening throughout treatment, the PIs will consult 
and seek advice from an independent clinician at the UCLA site (Scott Fears, MD) regarding study 
withdrawal and referral where appropriate. 
Treatment fidelity ratings (using our established adherence scales) will be measured by 
independent ratings of 15% of all sessions by independent assessors at one site reviewing the 
treatment sessions from the other site. Inter-rater reliability will be assessed on 10% of the 
adherence-rated sessions. Disparities across sites in competency and adherence will be 
addressed via additional joint supervision from Drs. Craske and Meuret. To minimize therapist 
effects, therapists will be assigned to PAT and NAT. 
 
Outcome Measures 
Given our goal of evaluating components of reward sensitivity as targets of treatment 
outcome (Aims 2 and 3), it is essential that our primary outcome measures are distinct from 
measures of reward sensitivity. For this reason, we will not select the Snaith–Hamilton Pleasure 
Scale [SHAPS]138, the Fawcett-Clark Pleasure Scale [FCPS]),139 the Chapman Physical and 
Social Anhedonia Scale [PAS])140 or the TEPS141 as outcome measures as they purport to 
measure the underlying components of reward sensitivity, particularly the attainment of reward 
 (SHAPS, FCPS, PAS, and TEPS) and the approach-motivation for reward (PAS, TEPS). 
Instead, our three primary outcome measures will include (1) self-reported positive affect, (2) 
interviewer- rated anhedonia, and (3) symptoms of depression and anxiety. . . 
Primary Outcome Measures. 
Self-Rated Positive Affect: Positive Affect Subscale (PANAS-P)89 Positive and Negative 
Affective Schedule (PANAS) is a widely used measure comprised of 20-items assessing positive 
affect and negative affect. Self-rated levels of positive affect will be assessed using the Positive 
Affect Subscale ("during the past week"). The PANAS-P directly measures expressed levels of 
positive affect without reliance upon constructs of reward sensitivity. We have validated the use 
of PANAS-Positive in our previous trial.142 The PANAS has high internal consistency and temporal 
stability. Correlational data support its convergent and discriminant validity. Confirmatory factor 
analyses support the construct validity of the PANAS.90 
Depression and Anxiety Stress Scales (DASS-21)145 The 21-item DASS measures 
depression, anxiety (e.g., difficulty breathing, heart palpitations), and stress (e.g., difficulty 
relaxing, irritability). The DASS has strong construct validity146-147 and good-to-excellent internal 
consistency147. It has clinical severity ranges from normal to extremely severe. Significant 
changes on the DASS were observed in our pilot trial of PAT.87 The DASS total score will be 
analyzed. 
Secondary Outcome Measures. 
Interviewer-Rated Anhedonia. Given the importance of heterogeneous measurements 
with respect to their error and method variance,143 independent assessor ratings of our primary 
outcome are a methodological advantage. We will use a method currently employed in another 
investigation of threat and reward sensitivity (R01MH100117, PI-Craske). Independent 
interviewers will rate the three diagnostic screener items from the SCID-5 interview (‘loss of 
interest,’ ‘loss of pleasure,’ and ‘low drive’) that load most heavily onto the anhedonia factor.144 
All three items will be rated by an independent assessor using a 4-point rating scale (from “absent” 
to “severe”). In 294 community participants, the three items showed good internal consistency 

Affect Treatment for Depression and Anxiety Trial Protocol 9 
 
(alpha = .72). 73% of participants identified by interviewers as high in anhedonia were also high 
in anhedonia by self-report, X2(1) = 60.1, p < .001. Assessors will be certified and trained to 
acceptable levels of inter-rater reliability. 
Sheehan Disability Scale (SDS)148 The SDS will be used to assess the degree of 
impairment in daily functioning in (a) work activities, (b) social life and leisure activities, and (c) 
family life and home responsibilities (0-10 point scales). 
Beck Scale for Suicidal Ideation. The Beck Scale for Suicidal Ideation will be used to 
assess suicidal ideation, from baseline to one-month follow-up. 
Self-Rated Positive Affect: Basic Positive Emotions Scales and Serenity (PANAS-X) 
 
Measures of Reward Sensitivity and Threat Sensitivity (Target engagement measures) 
Target measures of 1) reward anticipation-motivation, 2) response to reward attainment, 
3) reward learning, and 4) threat sensitivity are depicted in Table 1. 
 
Table 1. Self-report, behavioral, cognitive, and physiological measures of reward anticipation- 
motivation, response to reward attainment and reward learning at baseline, week 5, week 10, 
posttreatment-assessment, and one-month follow-up. 
 
 
Baseline 
 
 
 
 
 
Post 1MFU 
Week 
0 
1-4 
5 
6-9 
10 
11-15 
16 
20 
Reward Sensitivity (Target) 
Reward Anticipation-Motivation 
 
 
 
 
 
 
 
 
B: Effort Expenditure for Rewards Task 
(EEfRT) 
X 
 
X 
 
X 
 
X 
X 
P: Monetary Incentive Task (MIT) 
X 
 
X 
 
X 
 
X 
X 
S: Behavioral Inhibition and Activation 
Scale-Reward-Drive Subscale (BAS-
RD) 
X 
 
X 
 
X 
 
X 
X 
S: Dimensional Anhedonia Rating 
Scale (DARS-A-M) 
X 
 
X 
 
X 
 
X 
X 
Response to Reward Attainment 
 
 
 
 
 
 
 
 
C: Modified Attentional Dot Probe Task 
[positive cues] 
X 
 
X 
 
X 
 
X 
X 
P: International Affective Picture 
System (IAPS) Task [positive stimuli] 
X 
 
X 
 
X 
 
X 
X 
S: Temporal Experience of Pleasure 
Scale-Consummatory Subscale 
(TEPS-C) 
X 
 
X 
 
X 
 
X 
X 
S: Dimensional Anhedonia Rating 
Scale (DARS-C) 
X 
 
X 
 
X 
 
X 
X 
Reward Learning 
 
 
 
 
 
 
 
 
B: Probabilistic Reward Task (PRT) 
X 
 
X 
 
X 
 
X 
X 
Threat Sensitivity (Target) 
S: Anxiety Sensitivity Index (ASI) 
X 
 
X 
 
X 
 
X 
X 
S: Probability and Cost Questionnaire 
X 
 
X 
 
X 
 
X 
X 
S: Behavioral Inhibition Scale (BIS) 
X 
 
X 
 
X 
 
X 
X 
P: Mental Arithmetic Task 
X 
 
X 
 
X 
 
X 
X 
P: International Affective Picture 
System (IAPS) Task [negative stimuli] 
X 
 
X 
 
X 
 
X 
X 
C: Modified Attentional Dot Probe Task 
[negative cues] 
X 
 
X 
 
X 
 
X 
X 
B=behavioral, C=cognitive, P=physiological, S=subjective/experiential 
 
Reward Anticipation-Motivation 
Behavioral Index: Effort Expenditure for Rewards Task (EEfRT)41 The EEfRT is a 
behavioral measure for reward motivation (i.e., willingness to work for reward). Trait anhedonia140 

Affect Treatment for Depression and Anxiety Trial Protocol 10 
 
correlates with choosing easy tasks for small rewards over harder tasks for larger rewards in 
healthy controls41 and the effort individuals with depression expend to obtain rewards correlates 
negatively with anhedonia.42,43,149 Dopamine agonists produce a dose-dependent increase in 
willingness to work for EEfRT rewards, and depressed individuals showed reduced striatal 
response (caudate nucleus) using EEfRT, relative to healthy controls.150 The task is a computer 
game with monetary incentive which varies effort (hard vs easy), probability (12%, 50%, 88%) 
and amount of reward ($1.00 for easy trials, $1.24-$4.30 for hard tasks), for maximum earning of 
$16. The dependent variable is ratio of hard-effort choices for each probability of reward. 
Physiological Index: Heart rate acceleration during Monetary Incentive Task (MIT) Heart 
rate normally accelerates in tasks that require effort to obtain monetary rewards.44-47 Dysphoric 
individuals show less heart rate acceleration to the prospect of reward in MIT tasks48-50 and striatal 
hyporesponsiveness during MIT is linked to deficits of reward anticipation in various conditions, 
including depression.151,152 In this forced-choice reaction time task, participants react to a target 
stimulus presented after an incentive cue but before the reward is given. The incentive cue 
comprises an image of two quarters which indicate the maximum reward that can be earned on 
a trial. The target stimulus consists of a series of five arrows. The participant must indicate 
whether the middle arrow is pointing to the right or the left. Participants receive a maximum 
reward ($0.50) for a correct and fast response. Total maximum earning is $16. The dependent 
variable is heart rate acceleration from initial practice trial to initial reward trial, as the initial 
reward trial of this task has been shown to generate the strongest cardiac acceleration in non-
dysphoric individuals.44,45 The unrewarded practice trial serves as a baseline that holds constant 
for nonspecific factors (such as physical activity, visual processing) except for the prospect of 
reward. 
Self-report Index: Behavioral Activation Scale (Reward Drive Subscale; BAS-RD). The 
Behavioral Inhibition and Activation Scale (BIS/BAS)153 is a 24-item self-rated measure of habitual 
behavioral inhibition and activation sensitivities (i.e., avoidance and approach motives), which are 
hypothesized to reflect the negative and positive valence systems, respectively. The BAS Reward 
Drive subscale is a measure of effort valuation/willingness to work. Significant correlations have 
been established between the BAS-Reward Drive subscale and measures of positive affect.153 
BAS-Reward Drive is purported to reflect individual differences in ventral–striatal-related 
circuitry.153 
Self-report Index: Dimensional Anhedonia Rating Scale-Reward Anticipation-Motivation 
(DARS-A-M). DARS is a 17-item self-report questionnaire designed to assess anhedonia in MDD. 
Respondents provide their own examples of rewarding experiences across the domains of 
hobbies, social activities, food/drink, and sensory experience. They subsequently answer a set of 
standardized questions with the timeframe of “right now” to evaluate four domains of reward 
sensitivity within each domain: interest, motivation, effort, and enjoyment of reward. DARS shows 
good convergent and divergent validity and reliability of the subscales are high across studies 
(Cronbach's α = 0.75-0.92).154 Items related to desire, motivation, and effort will be summed to 
create an index of reward anticipation-motivation (DARS-A-M). The summation was ad hoc, 
but ratings showed high internal consistency (alpha=.94). 
 
Response to Reward Attainment 
Cognitive Index: Modified Probe Detection Task (DOTPROBE). Attentional biases for 
emotional information are observed for depression and anxiety.155,156 Less attention is directed to 
positive information as a function of low positive affect,69,157 depression,64,67 and social anxiety. 158 
Depressed individuals spend more time gazing at negative stimuli and less time gazing at positive 
stimuli159 and meta-analyses indicate greater disengagement from positive stimuli within dot 
probe attention tasks as a function of depression.160 While there are likely to be multiple 
explanations, including reward devaluation, the end result is less time attending to positive stimuli, 
which can be considered a weaker response to attainment of reward. There is good evidence for 
test-retest reliability for positive bias using the dot probe task in healthy controls.161 Stimuli 
comprise standardized male and female disgust, sad, happy, and neutral faces.162 Each emotional 
face is paired with a neutral face from the same person (e.g., sad–neutral). Neutral trials serve as 
a baseline to compute engagement bias and disengagement bias scores.163,164 
The task trials instruct participants to attend to a small line that will appear on the right or 

Affect Treatment for Depression and Anxiety Trial Protocol 11 
 
left side of the screen, which is either horizontal or vertical. The first line that appears is the “cue.” 
The cue disappears, and two images appear on the screen. One of them is a random blur, and 
the other is a sad, happy, or neutral face (presented for 500ms or 1000ms, randomized). The 
images disappear, and then another line appears on either side of the screen, which is again 
either horizontal or vertical. This second line that appears is the “target.” The participant must 
indicate with a keypress whether the cue and target lines were identical or different. The 
dependent variable is engagement bias for happy and disengagement bias for sad faces. 
Engagement bias trials are when the cue does not appear on the same side (i.e., distal) as the 
emotional image. Disengagement bias trials are when the cue appears on the same side (i.e., 
proximal) as the emotional image. According to Rudaizky et al. 165 the calculation of these indices 
is as follows: 
Reaction time (RT) index for engagement bias: (Cue appears distal to the emotional face 
in the pair of emotional face and random blur image: RT for target distal to emotional face minus 
RT for target proximal to emotional face) minus (Cue appears distal to neutral face in the pair of 
neutral face and random blur image: RT for target distal to neutral face minus RT for target 
proximal to neutral face). 
Reaction time (RT) index for disengagement bias: (Cue appears proximal to emotional 
face in the pair of emotional face and random blur image: RT for target distal to emotional face 
minus RT for target proximal to emotional face) minus (Cue proximal to neutral face in pair of 
neutral face and random blur image: RT for target distal to neutral face minus RT for target 
proximal to neutral face). 
Physiological Index: Heart rate acceleration to International Affective Picture Systems 
(IAPS) positive stimuli. The IAPS is a well-established paradigm for studying psychophysiology 
of emotion.166 Heart rate acceleration within 6 seconds of stimulus presentation is typically 
stronger with increasing pleasure of pictorial material.166 Compared to controls, participants with 
anhedonia showed less heart rate acceleration with increasing pleasantness of images,166 and 
positive stimuli elicit greater activation of the vmPFC and less activation of the striatum in 
individuals with anhedonia.167 Following the previously used paradigm with anhedonia 
patients166, 21 IAPS images (7 positive, 7 neutral, and 7 negative, selected using normative IAPS 
valence and arousal ratings) will be presented randomly, followed by repeated presentation as 
participants rate pleasure, arousal, and dominance using the Self-Assessment Manikin.168 
Maximum heart rate acceleration during the 6 seconds of positive image presentation relative to 
the last 2 seconds before picture onset will be assessed and compared to acceleration to 
neutral images. 
Self-report Index: Temporal Experience of Pleasure Scale-Consummatory Subscale 
(TEPS-C)141 The TEPS Consummatory subscale measures initial response to reward attainment, 
with high test-retest reliability in college students.141 Scores on the consummatory subscale 
correlate with measures of positive affect141 and Met carriers of the COMT gene had higher TEPS- 
consummatory scores and greater left PFC activation following reward consumption.169 
Self-report Index: Dimensional Anhedonia Rating Scale-Consummatory Pleasure 
(DARS- C). DARS is a 17-item self-report questionnaire designed to assess anhedonia in MDD. 
Respondents provide their own examples of rewarding experiences across the domains of 
hobbies, social activities, food/drink, and sensory experience. They subsequently answer a set of 
standardized questions with the timeframe of “right now” to evaluate four domains of reward 
sensitivity within each domain: interest, motivation, effort, and consummatory pleasure of reward. 
DARS shows good convergent and divergent validity and reliability of the subscales are high 
across studies (Cronbach's α=0.75-0.92)154. Items related to enjoyment will be summed to create 
an index of response to reward consumption (DARS-C). 
 
Reward Learning 
Behavioral Index: Probabilistic Reward Task (PRT)78 This task measures propensity to 
modulate behavior as a function of prior reinforcements, with good test-retest reliability in college 
students.78 Poor learning in Reward Tasks is associated with deficits in the ventral striatum.84 
Reduced reward learning in MDD correlated with self-reported anhedonia,79,81 and predicted poor 
antidepressant response two months later.79 Participants determine, via button press, whether a 

Affect Treatment for Depression and Anxiety Trial Protocol 12 
 
short (11.5 mm) or a long (13 mm) “mouth” was presented on a previously mouthless cartoon 
face. Correct identification is rewarded with money on 40% of trials. Total maximum earning is 
$16. The dependent variable is response bias (measured as accuracy) toward the more frequently 
rewarded stimulus. 
 
Threat Sensitivity 
 
Self-report Index: Anxiety Sensitivity Index (ASI)183 The 16-item ASI is designed to assess 
the beliefs that unexplained somatic sensations are dangerous and may cause deleterious 
physical, psychological, or social consequences beyond any immediate physical discomfort. 
The index has shown good internal consistency (a=.82)184, test–retest reliability (r=.71–.75)183, 
and criterion validity by significantly discriminating between patients with anxiety disorders and 
college students, as well as patients with agoraphobia and patients with other anxiety 
disorders183. 
 
Self-report Index: Probability and Cost Questionnaire185 The Probability and Cost 
Questionnaire was derived from that described by Foa, Franklin, Perry & Herbert (1996)185. The 
survey contains 20 items, each consisting of an example of a negative social event. Half of 
these items directly involved their own social performance (e.g., "During a job interview or 
evaluation, you will freeze") and half did not (e.g., "You will be ignored by someone you know"). 
Participants first rated each item based on how likely they believed it was to occur to them 
within the next year. They then rated each item based on how bad or distressing the outcomes 
would be for them if it did occur. All ratings were done on a likert scale ranging from 0 (not at all 
likely) to 8 (extremely likely). 
 
Self-report Index: Behavioral Inhibition Scale (BIS)153 The 7-item BIS measures self-
reported threat sensitivity via reactions to anticipation of punishment. Test-retest reliability after 
8-weeks in college students was r=.66153. BIS correlates positively with PANAS-Negative and 
neuroticism177 and improves following CBT for depression178 and anxiety179. 
 
Physiological Index: Mental Arithmetic Task186 A standard mental arithmetic task was 
used that had been used previously in cardiovascular reactivity research and has shown to elicit 
stress and anxiety186. The task was preceded by a 3-min baseline and followed by a 3-min 
recovery period. Participants were asked to add and subtract 12 lines of 12 single or double-
digit numbers on a computer screen while listening to background noises (voices of people 
having indistinguishable conversations in a large room) through in-ear headphones. Four of the 
lines were highlighted in blue, four in yellow, and four in red. At the end of the task, the 
experimenter asked the participants the final number and solution. To increase social evaluate 
threat, participants were told that most people made it towards the end of the red zone of lines. 
Physiological Index: Heart rate acceleration to International Affective Picture Systems 
(IAPS) negative stimuli. Maximum heart rate acceleration during the 6 seconds of negative 
image presentation relative to the last 2 seconds before picture onset will be assessed and 
compared to acceleration to neutral images. 
Cognitive Index: Modified Probe Detection Task (DOTPROBE) negative cues. This task 
measures attention bias to negative as well as positive cues. Preferential allocation of attention 
to negative stimuli is associated with negative affect155, predicts outcomes from CBT for anxiety 
disorders180 and changes significantly with CBT for anxiety disorders181-182. 
 
 
Reliability of Target Measurement 
Cross-site consistency in procedures for the behavioral and physiological measurement of 
the anticipation, motivation, attainment, and learning of reward sensitivity will be maintained in the 
following ways. First, detailed protocol manuals outline the procedures, including verbatim 
instructions to experimenters and participants. Second, experimenters will undergo standardized 
training involving: (a) use of physiological equipment, experimental procedures, data collection, 
and (b) implementation of the laboratory paradigms. Training will include one full protocol rehearsal 
per experimenter and an observation certification check, in which experimenters will be observed 
by Dr. Ritz, who will rate adherence to procedures at both sites (SMU and UCLA). Experimenters 
will have to pass the adherence check before being certified. Adherence checks will be repeated 
annually to minimize site or experimenter drift, combined with annual joint 1-day laboratory 

Affect Treatment for Depression and Anxiety Trial Protocol 13 
 
protocol adherence meetings. Dr. Ritz will be primarily responsible for overseeing and maintaining 
within and cross-site consistency in these paradigms and measures and will address disparities 
across sites as they arise. In addition, Dr. Pizzagalli (study consultant) will review methods, 
procedures, and ongoing data collection for the Probabilistic Reward Task and will be available 
as needed for troubleshooting. 
We will complete cross-site quality checks of behavioral and physiological data, including 
consultation from Dr. Diego Pizzagalli for the PRT annually. 
 
Sample Size 
Our target sample size is n = 100. 
We will use PinT 2.12 (Power in Two-Level Models170) to calculate the minimum effect 
size (ES) detectable with power >.80 unless otherwise noted. We assume a conservative estimate 
of 25% missing data. Data from our pilot study provided estimates for covariances and error 
variances that are needed by PinT. Since the Benjamini-Hochberg correction cannot be directly 
implemented in power analysis calculations, we will use the more conservative Bonferroni 
correction for our power analyses. Since MMLM analyses have greater power than the single 
outcome MLM analyses,171 for each Aim, we will calculate the power for the more conservative 
univariate MLM analysis. For hypotheses regarding clinical outcomes, we have greater than .80 
power to detect an ES difference between PAT and NAT as small as d = .35. For hypotheses 
regarding target engagement, we have greater than .80 power to detect an ES difference between 
PAT and NAT as small as d = .39. For hypotheses regarding covariation between target measures 
and clinical outcome measures, we have .80 power to detect covariation between a target and 
PANAS-P as small as d = .44. 
 
Ethics and Dissemination 
Trial conduct will be overseen by a data and safety monitoring board comprised of four 
researchers from three universities with extensive experience in treatments for depression and 
anxiety. The trial was approved by internal review boards of the respective data collection sites 
(UCLA and SMU) December, 2021. Written informed consent will be obtained from all 
participants by research personnel at UCLA and SMU. Any potential changes to the protocol will 
be submitted as amendments to the IRB and discussed with the data monitoring board at 
meetings. This study will follow the Consolidated Standards of Reporting Trials (CONSORT) 
reporting guideline. 
Individuals will be assigned a subject number upon entering the study. The study staff will 
place the participant’s name and contact information on a code sheet next to their subject number. 
This code sheet will be stored on a password-protected computer in a locked laboratory with 
restricted access. Paperwork with identifying information will be shredded. Only coded identifiers 
will be used for data archiving. Personally identifying information will be kept in a secure location, 
password-protected, and stored completely separate from any subject data that will be processed 
or analyzed for the research. 
Results will be communicated and disseminated through publication in scientific journals, 
conferences, and other common research outlets. Any use of the study data would require strong 
contributions in the conceptualization of the paper to constitute authorship. 
 
Randomization and Masking 
Participants will be randomized 1:1 to PAT vs. NAT via centralized, computer-generated 
allocation sequences with variable-sized permuted block sizes, stratified by medication status (2 
strata; y/n). Randomization will be managed by the study statistician (D.R.). Because of the nature 
of the study, only outcome assessors were masked to group allocation. Study coordinators 
enrolled participants and assigned them to interventions according to the randomization table. 
 
Statistical Methods 
 
We will use intent-to-treat multilevel models (MLM) to analyze our longitudinal data. 
Multivariate multilevel models (MMLM) will be used when there are multiple measures for the 
outcome being analyzed (i.e., for the clinical outcomes, the three reward targets, and the threat 

Affect Treatment for Depression and Anxiety Trial Protocol 14 
 
sensitivity target). We will investigate various growth curve models for our MLMs (e.g., linear, 
quadratic, logarithmic, square root) and use the best fitting model (lowest BIC) for our analyses. 
For purposes of this data analysis, the word “target” refers to a conceptual group of potential 
mediators (i.e., the Reward Anticipation/Motivation, Reward Attainment, and Reward Learning 
targets, and the Threat Sensitivity target), while the individual measures which comprise a target 
are referred to simply as “measures”. Whenever an MMLM shows a significant difference between 
PAT and NAT, we will follow the MMLM analysis with univariate MLM analyses of each of the 
measures comprising the target of that MMLM to determine which individual measures are 
engaged more by PAT than by NAT. 
 
Aim 1: Treatment Efficacy and Target Engagement.   
1a. We will first use MMLM to determine whether our multivariate Clinical Outcome (comprised of 
PANAS-P, DASS Total, and interviewer-rated anhedonia) improves more in PAT than in NAT. 1b. 
Using MMLM, we will determine if each of the three reward targets show significantly greater 
target engagement (improvement) in PAT than NAT. 1c. We will use MMLM to evaluate the 
hypothesis that the threat sensitivity target will be engaged more in NAT than in PAT. 
 
Aim 2: Specificity of Target Engagement with Respect to Threat versus Reward.  
The relative effects of PAT vs. NAT on reward sensitivity vis-à-vis threat sensitivity will be directly 
tested using an MMLM in which the measures of the threat sensitivity target and the measures of 
each of the three reward targets (in a separate analysis for each of the 3 targets in turn) are 
nested within assessments. We will code a dummy variable to contrast the threat sensitivity 
measures to the reward sensitivity measures. A significant 3-way interaction between the 
contrast dummy variable, treatment condition, and time will indicate that the effect of PAT vs. 
NAT is different for the reward sensitivity measures compared to the threat sensitivity measures. 
This analysis will be performed three times, each comparing the measures of one of the three 
reward targets to the measures of the threat sensitivity target.  
 
Aim 3: Mediation.  
We expect that our reward sensitivity targets and the threat sensitivity target will mediate 
treatment condition (PAT vs. NAT) differences in the improvement in clinical outcomes. We will 
evaluate each of the three reward sensitivity targets, and the threat sensitivity target, as a 
mediator of treatment group differences, with each target analyzed in a separate set of analyses.  
For the analysis of each target as a mediator, we will first investigate each individual 
measure of the target as a single mediator of treatment group differences in clinical outcome 
improvements using our MMLM model from Aim 1. We will follow those analyses with a 
multimediator analysis for each target in which all of the individual measures of the respective 
target are included as simultaneous mediators (e.g., for the reward anticipation/motivation target, 
we have 4 individual measures of treatment condition differences in clinical outcome: BAS-drive, 
DARS anticipation/motivation, EEfRT task, Monetary Incentive Task). This analysis will tell us 
which individual measures are significant mediators of group differences in clinical outcome 
improvement over and above the other measures in the analysis. We expect that the reward 
sensitivity measures will be more engaged in PAT vs. NAT (these are the “a” paths in the 
longitudinal mediation analysis). On the other hand, we expect the threat sensitivity measures to 
be more engaged in NAT than in PAT. We will use the distribution of products test RMediation to 
test for significant mediation.  
 
We will first test cross-lag mediation in which the individual measures of the target at each 
assessment (“t”) will be used to predict the multivariate clinical outcome at the next assessment 
(“t+1”), controlling for clinical outcome at the previous assessment (“t”), in a longitudinal 
mediation analysis (these will be the “b” paths in the mediation analysis).  
 
If the cross-lag mediation analysis fails to detect any significant cross-lag mediation, we 
will repeat the analyses using a concurrent mediation analysis, in which the individual measures 
of the target at assessment “t” are used as predictors of clinical outcomes at assessment “t”. 
 
In all mediation analyses, the time-varying mediators (the individual measures of the 
target) will be disaggregated into their between-subjects components and their within-subjects 
components. Since the relations among the between-subjects components and clinical outcome 

Affect Treatment for Depression and Anxiety Trial Protocol 15 
 
are confounded by potential individual differences between participants, we will only examine 
mediation by the within-subjects components of the individual mediators. 
 
Aim 4: Trimming of Target Measurement.  
To create an optimized mediation model, we will investigate a model in which all the significant 
individual measures of each target in Aim 3 are included in a single multi-mediator analysis. 
Models will be optimized by dropping non-significant mediator measures.  
This multi-mediator model will first be evaluated as a cross-lag mediation analysis (each 
measure at time “t” predicting outcome at time “t+1”, controlling for outcome at time “t”), as in Aim 
3. If the cross-lag mediation analysis fails to detect any significant cross-lag mediation, we will 
repeat the analyses using a concurrent mediation analysis (as in Aim 3). 
 
Safety Monitoring 
Study staff will be available 24 hours to respond to urgent issues. All staff will be able to 
provide information about local emergency facilities. The therapist or Ph.D. level project 
coordinator will generally be the first person to respond to a participant with a problem. They will 
handle some events immediately. If they are not able to manage the emergency event, they will 
contact the PIs, who will also be available 24 hours by cell phone to assist with participant 
management or crisis intervention. In addition, a DSMB will oversee safety and other related 
issues pertinent to the ongoing study (see Data Safety Monitoring Plan). 
A Data Safety and Monitoring Board (DSMB) will be a committee of four members that 
oversee clinical and ethical issues pertaining to the clinical trial. Dr. Bruce L. Kagan, M.D., Ph.D., 
who will serve as the chair, is a Professor of Clinical Psychiatry at the UCLA Semel Institute for 
Neuroscience and Human Behavior Brain Research Institute. Dr. Robert DeRubeis, Ph.D., is a 
Professor of Psychology at the University of Pennsylvania. Drs. Sherwood Brown, M.D., Ph.D., 
and Robin Jarret, Ph.D., are Professors of Psychiatry at the UT Southwestern Medical Center in 
Dallas. All members have extensive research and clinical expertise in mood disorders. All 
members are independent of the sponsor and do not hold competing interests. 
Regarding our data sharing efforts, we will submit the Data Monitoring Agreement and 
complete annual enrollment and submission of raw data to the NIMH Data Sharing repository. 
According to the NIMH definition, an adverse event is “Any untoward or unfavorable 
medical occurrence in a human subject, including any abnormal sign, symptom, or disease, 
temporally associated with the subject’s participation in the research, whether or not considered 
related to the subject’s participation in the research.” The following adverse events will be 
monitored: deaths, suicide attempts, study dropout, psychiatric hospitalizations, and clinical 
deterioration, defined as emergent suicidal ideation or suicidal plan, development of serious 
substance abuse, or the emergence of a new psychiatric or medical diagnosis or behavior posing 
a significant risk to the subjects of others. Adverse events will be presented at the annual DSMB 
meeting. DSMB committee members will independently evaluate whether each event qualified as 
a serious adverse event using the following criteria: 1) Serious/Not serious: Is the event serious 
or places subjects or others at greater risk than previously known or recognized? 2) 
Expected/Unexpected: Is the event unexpected (not described in the protocol or consent or 
exceeds severity/frequency of expected event) 3) Causality: Is the event-related or possibly 
related to research procedures? If an event qualifies as a serious adverse event, then the serious 
adverse event will be reported to IRB. 

Affect Treatment for Depression and Anxiety Trial Protocol 16 
 
CONSENT TO PARTICIPATE IN RESEARCH  
for Treatment Participants 
 
Affect Treatment for Depression and Anhedonia 
 
Michelle G. Craske, Ph.D., (Department of Psychology at the University of California, Los Angeles) 
is conducting a research study. You were selected as a possible participant in this study because 
of your responses to a preliminary screening, which indicated that you may experience elevated 
symptoms of anxiety, depression, or stress.  
 
Your participation in this study is voluntary. You should read all of the information below and ask 
questions about anything that you do not understand, before deciding whether or not to participate. 
Research designs often require that the full intent of the study not be explained during participation. 
Although we have described the general nature of the tasks that you will be asked to perform, there 
may be some details that are not revealed for the sake of accurate data collection. For scientific 
reasons, this consent form does not include complete information about the study hypotheses and 
the research questions being tested. You will be fully debriefed following your participation in the 
research. Similarly, after the study, we will provide you with an explanation of the study, which will 
include relevant background information. You will also be given an opportunity to ask any 
questions you might have about the hypothesis and the procedures used in the study.   
 
Why is this study being done? 
 
The purpose of the study is to examine which individuals with symptoms of anxiety, depression, 
and stress are more likely to benefit from two different versions of therapy. Each of these therapies 
includes components and therapeutic strategies that have been demonstrated to be effective for 
these problem areas. One therapy focuses on enhancing and increasing positive coping and life 
strategies, whereas the other therapy focuses on decreasing or eradicating negative coping and 
life strategies. Both versions involve examining thoughts and modifying behaviors 
 
What will happen if I take part in this research study? 
 
If you volunteer to participate in this study, we would ask you to do the following things: 
 
You already should have gone through two screening procedures, which were designed to 
determine if the study is appropriate for you. Screening procedures include answering initial 
eligibility questions, a diagnostic interview dealing with anxiety, depression, and other 
psychological problems, use of illegal drugs and medical history. This interview can last up to 2 
hours. In addition, a medical evaluation will be encouraged if you have not had a full medical 
examination in the last 12 months, at your cost.  If you are seeing another mental health provider 
(e.g., psychiatrist) we may ask you to sign a release of information (optional) so that we can 
contact the other provider regarding your care. If it is determined that the study is not appropriate 
for you, your participation will end at that point, and we can provide you with a list of referrals.  
 
Treatments 
 
During participation in the study, you will receive 15 weekly treatment sessions and one pre-
therapy session with a trained therapist. You will be randomly assigned, or by chance, to one of 
two treatments. One therapy focuses on enhancing and increasing positive coping and life 
strategies, whereas the other therapy focuses on decreasing or eradicating negative coping and 
life strategies. Both versions involve examining thoughts, modifying behaviors, and focusing on 
breathing.  
  
All of the treatments will be conducted by fully trained clinical psychology doctoral students, with 
the aid of a senior research staff, and supervised by licensed, clinical psychologists with extensive 

Affect Treatment for Depression and Anxiety Trial Protocol 17 
 
experience. All of the treatment sessions will be audio- and videotaped. This is done in order to 
monitor reliability and consistency among the therapists. Video data will also be analyzed to 
investigate markers of behavioral activation. Remote sessions will be offered through an encrypted 
video-conferencing platform via Zoom. When appropriate in-person therapy sessions may be 
offered.  
 
 
Individuals taking dopaminergic medications (e.g., Ritalin, Wellbutrin, amphetamines, 
methylphenidate, L-dopa) or Bupropion cannot participate in the study while still on medication. 
Heterocyclics and SSRIs need to be stabilized (3 months), as does fluoxetine (3 months) – that 
means that your dose should be the same, or that you should be medication-free, for that number 
of weeks (differing by medication) before enrolling in the study. PRN (when required) use of 
benzodiazepines and beta blockers are permitted, but they should not be used on assessment 
days, and ideally not within 2 weeks leading up to the assessments. If you are on medications, you 
will be asked to remain on a consistent dose/ regimen of your medication until after completion of 
the 15-week treatment, post-treatment assessment, and follow-up assessment. You should always 
consult with your primary provider before making changes to medication, dose, or discontinuation 
of current medication Also, you will be asked to inform us if you seek other forms of medical or 
psychological treatment for depression, anxiety, or stress before completion of the 15-week 
treatment study. 
 
All 15 treatment sessions must be completed within 19 weeks. In addition, you may be removed 
from the study if you miss more than three treatment sessions without notifying study staff within 24 
hours of your scheduled session. Further, we expect all participants to notify study staff within 24 
hours before missing a physiological assessment. These assessments often require up to 5 
researchers, and cancellations without notice are very inconvenient. We will work hard to schedule 
your appointments when convenient for you, so please let us know at least 24 hours in advance for 
any changes or cancellations.  
 
If you delay starting therapy for six or more weeks following your diagnostic interview, you will need 
to complete the diagnostic assessment and lab tasks again. 
 
Remote Assessments: 
 
You will be asked to complete a set of online questionnaires during weeks 0, 5, 10, post-treatment 
and at one-month follow-up. In addition, you will be asked to complete a brief interview during 
these time-points. 
 
In-person Assessments 
 
You will be asked to complete laboratory assessments with our research staff. You will be asked to 
come into the laboratory to complete a 3-hour laboratory assessment, which is split into two days. 
The first portion will be a 2-hour appointment (day 1), and the second portion will be 1-hour 
appointment (day 2). During these assessments, your behavior and your physical responses 
(pCO2, respiration rate, pulse, and heart rate) will be monitored and recorded while you are asked 
to attempt computer tasks. Your physiological responses will be measured by electrodes that are 
taped on your skin. Your weight will also be collected to analyze these physiological responses. 
We will also analyze inflammatory markers such as C-reactive protein via your saliva.  
 
 
The first diagnostic interview, laboratory assessment, behavioral assessment, and questionnaires 
will be administered at baseline, prior to starting treatment. The laboratory assessment, behavioral 
assessment and questionnaires will also be administered after 5 weeks into treatment, 10 weeks 
into treatment, at the completion of treatment, and at a one-month follow-up.  
 
Upon completing the treatment phase of the study, you will be asked to complete one diagnostic 

Affect Treatment for Depression and Anxiety Trial Protocol 18 
 
evaluation with one of our research staff. The diagnostic evaluation will cover anxiety, depression, 
and other psychological disorders. This evaluation will be occurring after treatment and is expected 
to last approximately one hour. There will also be a one-month follow up assessment that will 
mirror the pre and post treatment assessments. 
 
There is an additional, optional procedure in which you can elect to participate as a participant in 
this study. This optional procedure is to provide two blood samples—one at pre and one and post-
intervention. You will receive a $25 Amazon gift card at each timepoint if you choose to undergo 
this procedure. If you choose to complete this procedure, 1/8th of a teaspoon of blood drawn by a 
self-administered device (i.e. TASSO-M20). The TASSO device sticks to your skin with a light 
adhesive and forms a vacuum while a lancet pricks the surface of the skin. You have an option to 
complete the blood draw at your home or at UCLA. If you decide to complete the blood draw 
procedure at your home, we will collect your home address. Your sample will be used to look at 
differences in immune system functioning. The blood draw is for research purposes only, and you 
will not receive the results. Any leftover study blood samples may be stored for future research 
studies. Samples will only be released for use in future studies after approval by the Principal 
Investigator and other regulatory bodies, as appropriate.  
 
How long will I be in the research study? 
 
Overall, your involvement in the study will last approximately five months (approximately one month 
for initial assessment, four months for treatment, a post-treatment assessment approximately one 
week after the completion of treatment), and a follow-up assessment (approximately one month 
after the completion of treatment). 
 
Are there any potential risks or discomforts that I can expect from this study? 
 
There are no known risks associated with the initial diagnostic evaluation or any of the follow-up 
assessments beyond any discomfort you might experience talking about your medical and 
psychological history. 
 
During the treatment phase of the study, you may experience anxiety from being asked to face 
things that cause you distress or from being asked to confront situations and feelings that you find 
anxiety provoking. 
 
The laboratory sessions can induce symptoms such as discomfort or mild physical symptoms in 
some people. During one of the laboratory tasks you will see some images that can be disturbing 
and make you upset. You may ask to stop the task at any time. Furthermore, the paste and collars 
of the electrodes may cause minor skin irritations in some participants. The assessment of the 
physiological measures (pCO2, respiration rate, pulse, heart rate, etc.) is non-invasive and 
therefore is of minimal risk. All medical supplies (nasal cannulas, electrodes) are sterile to reduce 
the risk of infection.   
 
Blood draw risks: 
 
While neither the public nor the controlled-access databases developed for this project will contain 
information that is traditionally used to identify you, such as your name, address, telephone 
number, or social security number, people may develop ways in the future that would allow 
someone to link your genetic or medical information in our databases back to you. For example, 
someone could compare information in our databases with information from you (or a blood 
relative) in another database and be able to identify you (or your blood relative). It also is possible 
that there could be violations to the security of the computer systems used to store the codes 
linking your genetic and medical information to you. 
 
     Because this is a research study, there may be some unknown risks that are currently 
unforeseeable. You will be informed of any significant new findings.      

Affect Treatment for Depression and Anxiety Trial Protocol 19 
 
 
     Please also note: Any specimens (e.g., blood, saliva) obtained for the purpose of this study will 
become the property of the University of California. Once you provide the specimens you will not 
have access to them. The University may share your specimens in the future with other 
researchers or outside institutions. Information that identifies you will not be shared with anyone 
outside of UCLA. The specimens will be used for research and such use may result in inventions or 
discoveries that could become the basis for new products or diagnostic or therapeutic agents. In 
some instances, these inventions and discoveries may be of potential commercial value and may 
be patented and licensed by the University. You will not receive any money or other benefits 
derived from any commercial or other products that may be developed from use of the specimen. 
 
 
You have the right to refuse to answer any question that you do not wish to answer, and to refuse 
any task that you do not wish to do. You can stop your participation in the study at any time without 
penalty. 
 
Are there any potential benefits if I participate? 
 
You will receive a diagnostic evaluation and treatment at no cost to you. At the completion of each 
physiological session, you will be compensated monetarily. Findings from this study may help 
clinicians provide more effective treatments for psychological disorders. Research has shown that 
these treatment approaches are likely to be of benefit to those who show symptoms similar to 
yours. It is important to note that individuals respond differently to therapy, and so it is not possible 
to know in advance if the treatment will be helpful in your particular case. However, potential 
benefits may include significant reductions in your symptoms of anxiety, depression, or stress. 
 
Also, you will be provided with additional or alternative treatment referrals at any point in time along 
the study if you make such a request. 
 
What other choices do I have if I choose not to participate? 
 
Your participation in the study is voluntary. Refusal to participate will involve no penalty or loss of 
benefits to which you would be otherwise entitled. You may discontinue participation at any time 
without penalty or loss of benefits to which you may be otherwise entitled. 
 
Medication or therapy (e.g., cognitive-behavioral therapy) from other providers are alternatives to 
participating in this study. If you would like, we will provide you with a referral list.  
  
Will I be paid for participating? 
 
You will be compensated $75 at the completion of the second laboratory session (day 2), and you 
will also be able to earn up to $70 on certain tasks during the laboratory sessions. The maximum 
amount that can be earned for the five laboratory assessments is $560. You will be reimbursed for 
parking or Uber/Lyft. If you choose to undergo the optional blood draw procedure, you will be paid 
$25 at the completion of each blood draw procedure.  
 
Are there any costs for taking part in this study? 
 
You will receive diagnostic evaluations and treatment for free. If in-person therapy sessions are offered, 
you will be responsible for paying parking during your treatment visits.  
 
What happens if I believe I am injured because I took part in this study? 
 
It is important that you promptly tell the researchers if you believe that you have been injured by 
taking part in this study. You can tell the researcher in person or call her at the number listed 
below.  

Affect Treatment for Depression and Anxiety Trial Protocol 20 
 
 
Michelle Craske, Ph.D. 
UCLA Anxiety Disorders Research Center  
Department of Psychology  
Franz Hall - Box 951563 
Los Angeles, CA 90094-1563 
(310) 825-8403 
 
If you are injured as a result of being in this study, UCLA will provide necessary medical treatment. 
The costs of the treatment may be covered by the University of California, or billed to you and your 
insurer just like other medical costs, depending on a number of factors. The University does not 
normally provide any other form of compensation (payment) for injury. For more information about 
this you may call the UCLA Office of the Human Research Protection Program at 310-825-5344 or 
send an email to mirb@research.ucla.edu.  
 
 
If you are having thoughts of suicide, please contact the National Suicide Prevention 
Lifeline at 1-800-273-8255, or call 911 if you are in immediate danger. 
 
Will information about me and my participation be kept confidential? 
 
The researchers will make every attempt to protect your confidentiality, or privacy, and to make 
sure that your personal identity does not become known. The investigator has obtained a 
Confidentiality Certificate from the Department of Health and Human Services to further help us 
protect your privacy. The Certificate protects us from being forced to disclose or provide 
information that may identify you in any federal, state, local, criminal, administrative, legislative or 
any other procedures. However, information will be disclosed upon request of DHHS for purposes 
of audit or evaluation. You need to be aware that the Confidentiality Certificate does not prevent 
you from voluntarily releasing information. However, if an employer or insurer finds out about your 
participation in the study and obtains your consent to receive research information, then we will not 
be able to withhold the requested information. Accordingly, it is important that you and your family 
actively protect your own privacy.  
 
Finally, you need to be aware that the investigator will need to disclose information including 
reporting to authorities to prevent harm to yourself or others. In the event that you tell the research 
or clinical staff that you are thinking about suicide, or if you answer yes to a question to having 
thoughts about suicide, the research staff will ask you more questions about the thoughts.  
Depending on how intense the thoughts are or how much you feel like hurting yourself, the 
research staff may provide you with referrals for treatment; work with you to contact your personal 
physician, trusted family member, or therapist to discuss your thoughts of harming yourself; or work 
with you on a plan that may include getting you to a hospital for safety.  
 
This signed consent form will be stored in a locked file that will be accessible only to a very small 
number of the authorized people involved in this project. The research will carefully follow the 
coding, storage, and data sharing plan explained below.  
 
Some identifiable information about you will be replaced with a code. A list linking the code and 
your identifiable information will be kept separate from the research data. All research data and 
records will be maintained in a secure location at the pertaining sites, UCLA and SMU. Only 
authorized individuals will have access to it. Some research data and records will be stored 
electronically on a secure network with password protection.  
 
All of the diagnostic evaluations and treatment sessions will be video- and/or audio-taped and later 
reviewed by research staff for educational purposes (supervision) and to determine whether the 
assessments and treatment have been delivered appropriately (quality assurance). The data and 
video/audiotapes will be stored in a secure location for five years after the study has been 

Affect Treatment for Depression and Anxiety Trial Protocol 21 
 
completed, and then they will be destroyed. 
 
If you are ineligible for the study, we will still need to enter some of your screening information in 
our database. However, the diagnostic interviews and any other screening information will be 
shredded, and there will be no personal identifiers between your data that is in the database and 
yourself. 
 
Emergency contact: We ask you to provide us with your emergency contact. We will contact your 
emergency contact only if we have consistently failed to reach you using a variety of channels 
(phone, email) and if we are concerned about your safety. We will disclose to your emergency 
contact only that you are participating in a UCLA research study and that we have been trying to 
reach you but failed to do so. We will disclose that we are concerned about your safety if that is the 
case. We will not disclose the nature of the study or any other information you have provided to us.  
 
Use of data and specimens for future research 
 
Data sharing can benefit science by allowing researchers with a broad set of perspectives to 
analyze the same data, and by allowing the analysis of large datasets that are combined across 
many smaller studies. Because we believe that the data being collected from you are valuable, 
they may be shared with other researchers or included in national or international efforts to create 
large databases of scientific information.  
 
Identifying information will be removed from the study data, so no identifying information is included 
in the data that are shared with other investigators. When we share this data, you will not be asked 
for additional informed consent. You will not be informed of any information learned from the 
collected data, either by us or by any other group that utilizes shared data. 
 
What are my rights if I take part in this study? 
 
• 
You can choose whether or not you want to be in this study, and you may withdraw your 
consent and discontinue participation at any time. 
• 
Whatever decision you make, there will be no penalty to you, and no loss of benefits to which 
you were otherwise entitled.   
• 
You may refuse to answer any questions that you do not want to answer and still remain in the 
study. 
 
The investigator may withdraw you from this research if things happen that make your removal 
necessary. The decision may be made either to protect your health and safety, or because it is part 
of the research plan that people who develop certain conditions may not continue to participate.   
 
Who can I contact if I have questions about this study? 
 
If you have any questions or concerns about the research, please feel free to contact  
Michelle G. Craske, Ph.D., Professor of Psychology, Director of the Anxiety and Depression 
Research Center at UCLA, Franz Hall 3170, who can be reached at (310) 825-8403. 
 
UCLA Office of the Human Research Protection Program (OHRPP): 
If you have questions about your rights while taking part in this study, or you have concerns or 
suggestions and you want to talk to someone other than the researchers about the study, 
please call the OHRPP at (310) 825-7122 or write to:  
 
UCLA Office of the Human Research Protection Program:  
11000 Kinross Avenue, Suite 211, Box 951694  
Los Angeles, CA 90095-1694 
 
 

Affect Treatment for Depression and Anxiety Trial Protocol 22 
 
  
SIGNATURE OF RESEARCH SUBJECT 
 
I understand the procedures described above.  My questions have been answered to my 
satisfaction, and I agree to participate in this study.  I have been given a copy of this form. 
 
Please initial next to one of the following responses. Your decision will not affect your participation 
in the current study. 
_____ I agree to provide blood samples at pre and post-intervention. 
_____ I do not want to provide blood samples at pre and post-intervention. 
Please initial next to one of the following responses. Your decision will not affect your participation 
in the current study. 
_____ I agree to be contacted about other research studies conducted by Michelle Craske, Ph.D. 
_____ I do not agree to be contacted about other research studies conducted by Michelle Craske, 
Ph.D. 
 
________________________________________ 
Name of Subject 
 
________________________________________                          __________________ 
Signature of Subject                                                                          Date 
 
Emergency Contact: 
Name: _______________________________ Relationship: ________________________ 
Phone Number: ________________________ 
 
SIGNATURE OF INVESTIGATOR 
 
In my judgment the subject is voluntarily and knowingly giving informed consent and possesses the 
legal capacity to give informed consent to participate in this research study. 
 
 
  
Name of Person Obtaining Consent 
 Contact Number 
 
 
  
Signature of Person Obtaining Consent 
 
Date 

Affect Treatment for Depression and Anxiety Trial Protocol 23 
 
References 
 
1. 
Villanueva, C. M., Silton, R. L., Heller, W., Barch, D. M., & Gruber, J. (2021). Change is on 
the horizon: call to action for the study of positive emotion and reward in psychopathology. 
Current Opinion in Behavioral Sciences, 39, 34-40. 
https://doi.org/10.1016/j.cobeha.2020.11.008 
2. 
Trøstheim M, Eikemo M, Meir R, et al. Assessment of Anhedonia in Adults With and 
Without Mental Illness: A Systematic Review and Meta-analysis. JAMA Netw Open. 
2020;3(8):e2013233. doi:10.1001/jamanetworkopen.2020.13233 
3. 
Kendall, A. D., Zinbarg, R. E., Mineka, S., Bobova, L., Prenoveau, J. M., Revelle, W., & 
Craske, M. G. (2015). Prospective associations of low positive emotionality with first 
onsets of depressive and anxiety disorders: Results from a 10-wave latent trait-state 
modeling study. Journal of abnormal psychology, 124(4), 933–943. 
https://doi.org/10.1037/abn0000105 
4. 
Sewart AR, Zbozinek TD, Hammen C, Zinbarg RE, Mineka S, Craske MG. Positive Affect 
as a Buffer Between Chronic Stress and Symptom Severity of Emotional Disorders. 
Clinical Psychological Science. 2019;7(5):914-927. doi:10.1177/2167702619834576 
5. 
Prenoveau, J. M., Zinbarg, R. E., Craske, M. G., Mineka, S., Griffith, J. W., & Epstein, A. 
M. (2010). Testing a hierarchical model of anxiety and depression in adolescents: a tri- 
level model. Journal of anxiety disorders, 24(3), 334–344. 
https://doi.org/10.1016/j.janxdis.2010.01.006 
6. 
Naragon-Gainey, K., Prenoveau, J. M., Brown, T. A. & Zinbarg, R. E. A comparison and 
integration of structural models of depression and anxiety in a clinical sample: Support for 
and validation of the tri-level model. J. Abnorm. Psychol. 125, 853–867 (2016). 
7. 
Khazanov, G. K., & Ruscio, A. M. (2016). Is low positive emotionality a specific risk factor 
for depression? A meta-analysis of longitudinal studies. Psychological Bulletin, 142, 991– 
1015. http://dx.doi.org/10 .1037/bul0000059 
8. 
Morris, B. H., Bylsma, L. M., & Rottenberg, J. (2009). Does emotion predict the course of 
major depressive disorder? A review of prospective studies. The British Journal of Clinical 
Psychology. 48(Pt 3), 255–273. https://doi.org/10.1348/014466508X396549 
9. 
Ducasse, D., Loas, G., Dassa, D., Gramaglia, C., Zeppegno, P., Guillaume, S., Olié, E., & 
Courtet, P. (2018). Anhedonia is associated with suicidal ideation independently of 
depression: A meta-analysis. Depression and Anxiety. 35(5), 382–392. 
https://doi.org/10.1002/da.22709 
10. Winer, E. S., Nadorff, M. R., Ellis, T. E., Allen, J. G., Herrera, S., & Salem, T. (2014). 
Anhedonia predicts suicidal ideation in a large psychiatric inpatient sample. Psychiatry 
Research. 218(1-2), 124–128. https://doi.org/10.1016/j.psychres.2014.04.016 
11. Fawcett, J., Scheftner, W. A., Fogg, L., Clark, D. C., Young, M. A., Hedeker, D., & 
Gibbons, R. (1990). Time-related predictors of suicide in major affective disorder. The 
American Journal of Psychiatry. 147(9), 1189–1194. 
https://doi.org/10.1176/ajp.147.9.1189 
12. Ballard, E. D., Wills, K., Lally, N., Richards, E. M., Luckenbaugh, D. A., Walls, T., Ameli, 
R., Niciu, M. J., Brutsche, N. E., Park, L., & Zarate, C. A., Jr (2017). Anhedonia as a 
clinical correlate of suicidal thoughts in clinical ketamine trials. Journal of Affective 
Disorders. 218, 195–200. https://doi.org/10.1016/j.jad.2017.04.057 
13. Demyttenaere, K., Donneau, A. F., Albert, A., Ansseau, M., Constant, E., & van 
Heeringen, K. (2015). What is important in being cured from depression? Discordance 
between physicians and patients (1). Journal of Affective Disorders. 174, 390–396. 
https://doi.org/10.1016/j.jad.2014.12.004 
14. Boumparis, N., Karyotaki, E., Kleiboer, A., Hofmann, S. G. & Cuijpers, P. The effect of 
psychotherapeutic interventions on positive and negative affect in depression: A 
systematic review and meta-analysis. Journal of Affective Disorders. 202, 153–162 (2016). 

Affect Treatment for Depression and Anxiety Trial Protocol 24 
 
15. DeRubeis, R. J., Hollon, S. D., Amsterdam, J. D., Shelton, R. C., Young, P. R., Salomon, 
R. M., O'Reardon, J. P., Lovett, M. L., Gladis, M. M., Brown, L. L., & Gallop, R. (2005). 
Cognitive therapy vs medications in the treatment of moderate to severe depression. 
Archives of General Psychiatry. 62(4), 409–416. https://doi.org/10.1001/archpsyc.62.4.409 
16. Dunn BD, German RE, Khazanov G, Xu C, Hollon SD, DeRubeis RJ. Changes in Positive 
and Negative Affect During Pharmacological Treatment and Cognitive Therapy for Major 
Depressive Disorder: A Secondary Analysis of Two Randomized Controlled Trials. Clinical 
Psychological Science. 2020;8(1):36-51. doi:10.1177/2167702619863427 
17. Martell, C., Dimidjian, S. & Herman-Dunn, R. Behavioral activation for depression: A 
clinician’s guide. (2010). 
18. Dichter, G. S., Felder, J. N., Petty, C., Bizzell, J., Ernst, M., & Smoski, M. J. (2009). The 
effects of psychotherapy on neural responses to rewards in major depression. Biological 
Psychiatry. 66(9), 886–897. https://doi.org/10.1016/j.biopsych.2009.06.021 
19. Moore, R. C., Chattillion, E. A., Ceglowski, J., Ho, J., von Känel, R., Mills, P. J., Ziegler, M. 
G., Patterson, T. L., Grant, I., & Mausbach, B. T. (2013). A randomized clinical trial of 
Behavioral Activation (BA) therapy for improving psychological and physical health in 
dementia caregivers: results of the Pleasant Events Program (PEP). Behaviour Research 
and Therapy. 51(10), 623–632. https://doi.org/10.1016/j.brat.2013.07.005 
20. Forbes, C. N. New directions in behavioral activation: Using findings from basic science 
and translational neuroscience to inform the exploration of potential mechanisms of 
change. Clin. Psychol. Rev. 79, (2020). 
21. Landén, M., Högberg, P. & Thase, M. E. Incidence of sexual side effects in refractory 
depression during treatment with citalopram or paroxetine. J. Clin. Psychiatry. 66, 100– 
106 (2005). 
22. McCabe, C., Mishor, Z., Cowen, P. J. & Harmer, C. J. Diminished Neural Processing of 
Aversive and Rewarding Stimuli During Selective Serotonin Reuptake Inhibitor Treatment. 
Biol. Psychiatry. 67, 439– 445 (2010). PMCID: PMC2828549 
23. Nierenberg, A. A. et al. Residual symptoms in depressed patients who respond acutely to 
fluoxetine. Prim. Care Companion J. Clin. Psychiatry. 1, 124 (1999). 
24. Price, J., Cole, V. & Goodwin, G. M. Emotional side-effects of selective serotonin reuptake 
inhibitors: Qualitative study. Br. J. Psychiatry. 195, 211–217 (2009). 
25. Thomas, R. K., Baker, G., Lind, J. & Dursun, S. Rapid effectiveness of intravenous 
ketamine for ultraresistant depression in a clinical setting and evidence for baseline 
anhedonia and bipolarity as clinical predictors of effectiveness. J. Psychopharmacol. 32, 
1110–1117 (2018). 
26. Krystal AD, Pizzagalli DA, Smoski M, Mathew SJ, Nurnberger J Jr, Lisanby SH, Iosifescu 
D, Murrough JW, Yang H, Weiner RD, Calabrese JR, Sanacora G, Hermes G, Keefe RSE, 
Song A, Goodman W, Szabo ST, Whitton AE, Gao K, Potter WZ. A randomized proof-of- 
mechanism trial applying the 'fast-fail' approach to evaluating κ-opioid antagonism as a 
treatment for anhedonia. Nat Med. 2020 May;26(5):760-768. doi: 10.1038/s41591-020- 
0806-7. Epub 2020 Mar 30. PMID: 32231295. 
27. Dunn BD. (2012). Helping depressed clients reconnect to positive emotion experience: 
current insights and future directions. Clinical Psychology & Psychotherapy, 19(4):326-40. 
PMID: 22674611 
28. Der-Avakian A, Markou A. (2012). The neurobiology of anhedonia and other reward 
related deficits. Trends in Neuroscience, 35: 68–77. PMID: 22177980 
29. Miendlarzewska, E.A., Bavelier, D., & Schwartz, S. (2016). Influence of reward motivation 
on human declarative memory. Neuroscience and Biobehavioral Reviews, 61, 156-176. 
30. Morris SE, Cuthbert BN. (2012). Research Domain criteria: cognitive systems, neural 
circuits, and dimensions of behavior. Dialogues in Clinical Neuroscience, 14(1):29–37. 
PMID: 22577302 

Affect Treatment for Depression and Anxiety Trial Protocol 25 
 
31. Thomsen KR, Whybrow PC, Kringelbach ML. (2015). Reconceptualizing anhedonia: novel 
perspectives on balancing the pleasure networks in the human brain. Frontiers in 
Behavioral Neuroscience. PMCID: PMC4356228 
32. Treadway MT, Zald DH. (2011). Reconsidering anhedonia in depression: lessons from 
translational neuroscience. Neuroscience & Biobehavioral Reviews. 35(3), 537-55. PMID: 
20603146 
33. Pizzagalli DA. (2014). Depression, stress, and anhedonia: toward a synthesis and 
integrated model. Annual Review of Clinical Psychology.10, 393-423. PMID: 24471371 
34. Henriques JB, Davidson RJ. (2000). Decreased responsiveness to reward in depression. 
Cognition & Emotion, 14, 711-724. 
35. Jazbec S, McClure E, Hardin M, Pine DS, Ernst M. (2005). Cognitive control under 
contingencies in anxious and depressed adolescents: an antisaccade task. Biological 
Psychiatry, 58(8), 632-639. PMID: 16018983 
36. Pizzagalli DA, Sherwood RJ, Henriques JB, Davidson RJ. (2005). Frontal brain asymmetry 
and reward responsiveness: a source-localization study. Psychological Science. 16(10), 
805-813. PMID: 16181444 
37. McFarland BR, Klein DN. (2009). Emotional reactivity in depression: diminished 
responsiveness to anticipated reward but not to anticipated punishment or to nonreward or 
avoidance. Depression and Anxiety, 26(2), 117-122. PMID: 18972567 
38. Yuan JW, Kring AM. (2009). Dysphoria and the prediction and experience of emotion. 
Cognition and Emotion, 23(6), 1221-1232. 
39. Hoerger, M., Quirk, S. W., Chapman, B. P., & Duberstein, P. R. (2012). Affective 
forecasting and self-rated symptoms of depression, anxiety, and hypomania: Evidence for 
a dysphoric forecasting bias. Cognition & Emotion, 26, 1098-1106. PMID: 22397734 
40. Knutson B, Bhanji JP, Cooney RE, Atlas LY, Gotlib IH. (2008). Neural responses to 
monetary incentives in major depression. Biological Psychiatry, 63(7), 686-692. PMID: 
17916330 
41. Treadway MT, Buckholtz JW, Schwartzman AN, Lambert WE, Zald DH. (2009). Worth the 
‘EEfRT’? The effort expenditure for rewards task as an objective measure of motivation 
and anhedonia. PLoS One, 4(8): e6598. PMID: 19672310 
42. Treadway MT, Bossaller NA, Shelton RC, Zald DH. (2012). Effort-based decision-making 
in major depressive disorder: a translational model of motivational anhedonia. Journal of 
Abnormal Psychology.121, 553–558. PMID: 22775583 
43. Yang XH, Huang J, Zhu CY, Wang YF, Cheung EF, Chan RC, Xie GR. (2014). 
Motivational deficits in effort-based decision making in individuals with subsyndromal 
depression, first-episode and remitted depression patients. Psychiatry Research, 
220(3):874-82. PMID: 25262638 
44. Brenner SL, Beauchaine TP, Sylvers PD. A comparison of psychophysiological and self- 
report measures of BAS and BIS activation. Psychophysiology. 2005 Jan;42(1):108-15. 
doi: 10.1111/j.1469-8986.2005.00261.x. 
45. Iaboni F, Douglas VI, Ditto B. Psychophysiological response of ADHD children to reward 
and extinction. Psychophysiology. 1997 Jan;34(1):116-23. doi: 10.1111/j.1469- 
8986.1997.tb02422.x. 
46. Richter M, Gendolla GH. Incentive value, unclear task difficulty, and cardiovascular 
reactivity in active coping. Int J Psychophysiol. 2007 Mar;63(3):294-301. doi: 
10.1016/j.ijpsycho.2006.12.002. 
47. Tranel DT, Fisher AE, Fowles DC. Magnitude of incentive effects on heart rate. 
Psychophysiology. 1982 Sep;19(5):514-9. doi: 10.1111/j.1469-8986.1982.tb02578.x. 
48. Brinkmann K, Schüpbach L, Joye IA, Gendolla GH. (2009). Anhedonia and effort 
mobilization in dysphoria: reduced cardiovascular response to reward and punishment. 
International Journal of Psychophysiology, 74(3):250-8. PMID: 19808061 

Affect Treatment for Depression and Anxiety Trial Protocol 26 
 
49. Brinkmann K, Franzen J. (2013). Insensitivity to varying levels of reward in dysphoria. 
Biological Psychology, 94(2):263-71 
50. Franzen J, Brinkmann K. (2015) Blunted cardiovascular reactivity in dysphoria during 
reward and punishment anticipation. International Journal of Psychophysiology. 95(3):270- 
7. PMID: 25462217 
51. Smoski MJ, Felder J, Bizzell J, Green SR, Ernst M, Lynch TR, Dichter GS. (2009). fMRI of 
alterations in reward selection, anticipation, and feedback in major depressive disorder. 
Journal of Affective Disorders, 118(1-3):69-78. PMID: 19261334 
52. McCabe C, Cowen PJ, Harmer CJ. (2009). Neural representation of reward in recovered 
depressed patients. Psychopharmacology.205(4):667-77. doi: 10.1007/s00213-009-1573- 
9. PMID: 19529923 
53. Steele JD, Kumar P, Ebmeier KP. (2007). Blunted response to feedback information in 
depressive illness. Brain, 130(9):2367-74. PMID: 17586866 
54. Forbes EE, Hariri AR, Martin SL, Silk JS, Moyles DL, Fisher PM, Brown SM, Ryan ND, 
Birmaher B, Axelson DA, Dahl RE. (2009). Altered striatal activation predicting real-world 
positive affect in adolescent major depressive disorder. The American Journal of 
Psychiatry, 166(1):64-73. PMID: 19047324 
55. Chentsova-Dutton Y, Hanley K. (2010). The effects of anhedonia and depression on 
hedonic responses. Psychiatry Research, 179: 176–180. PMID: 20478624 
56. Forbes EE, Christopher May J, Siegle GJ, Ladouceur CD, Ryan ND, Carter CS, Birmaher 
B, Axelson DA, Dahl RE. (2006). Reward-related decision-making in pediatric major 
depressive disorder: an fMRI study. Journal of Child Psychology and Psychiatry, and allied 
disciplines, 47(10):1031-40. PMCID: PMC2129133 
57. Greenberg T, Chase HW, Almeida JR, Stiffler R, Zevallos CR, Aslam HA, Deckersbach T, 
Weyandt S, Cooper C, Toups M, Carmody T, Kurian B, Peltier S, Adams P, McInnis MG, 
Oquendo MA, McGrath PJ, Fava M, Weissman M, Parsey R, Trivedi MH, Phillips ML. 
(2015). Moderation of the Relationship Between Reward Expectancy and Prediction Error- 
Related Ventral Striatal Reactivity by Anhedonia in Unmedicated Major Depressive 
Disorder: Findings From the EMBARC Study. The American Journal of Psychiatry, 
172(9):881–91. PMID: 26183698 
58. Stoy M, Schlagenhauf F, Sterzer P, Bermpohl F, Hägele C, Suchotzki K, Schmack K, 
Wrase J, Ricken R, Knutson B, Adli M, Bauer M, Heinz A, Ströhle A. (2011). 
Hyporeactivity of ventral striatum towards incentive stimuli in unmedicated depressed 
patients normalizes after treatment with escitalopram. Journal of Psychopharmacology. 
26(5), 677-688. PMID: 21926423 
59. Ubl B, Kuehner C, Kirsch P, Ruttorf M, Diener C, Flor H. (2015). Altered neural reward and 
loss processing and prediction error signalling in depression. Social Cognitive and 
Affective Neuroscience, pii: nsu158. PMID: 25567763 
60. Berlin I, Givry-Steiner L, Lecrubier Y, Puech AJ. (1998). Measures of anhedonia and 
hedonic responses to sucrose in depressive and schizophrenic patients in comparison 
with healthy subjects. European Psychiatry. 1998;13:303–309. PMID: 19698645 
61. Dichter, G.S., Felder, J.N., Smoski, M. (2010). The Effects of Brief Behavioral Activation 
Therapy for Depression on Cognitive Control in Affective Contexts: an fMRI investigation; 
Journal of Affective Disorders, 126(1-2):236-244. PMID: 20421135 
62. Swiecicki L, Zatorski P, Bzinkowska D, Sienkiewicz-Jarosz H, Szyndler J, Scinska A. 
(2009). Gustatory and olfactory function in patients with unipolar and bipolar depression. 
Progress in Neuro-Psychopharmacology & Biological Psychiatry. 33(5), 827-834. PMID: 
19345708 
63. Bylsma LM, Morris BH, Rottenberg J. (2008). A meta-analysis of emotional reactivity in 
major depressive disorder. Clinical Psychology Review, 28(4), 676-691. PMID: 18006196 
64. Peckham AD, McHugh RK, Otto MW. (2010). A meta-analysis of the magnitude of biased 
attention in depression. Depression and Anxiety, 27(12), 1135-1142. PMID: 21049527 

Affect Treatment for Depression and Anxiety Trial Protocol 27 
 
65. Clepce M, Gossler A, Reich K, Kornhuber J, Thuerauf N. (2010). The relation between 
depression, anhedonia and olfactory hedonic estimates--a pilot study in major depression. 
Neuroscience Letters, 471(3):139-43. PMID: 20097263 
66. Armstrong, T., Olatunji, B. O. (2009). What they see is what you get: Eye tracking of 
attention in the anxiety disorders. Psychological Science Agenda, 23, 3. 
67. Fritzsche A, Dahme B, Gotlib IH, Joormann J, Magnussen H, Watz H, Nutzinger DO, von 
Leupoldt A. (2010). Specificity of cognitive biases in patients with current depression and 
remitted depression and in patients with asthma. Psychological Medicine. 40(5), 815-826. 
68. Soltani S, Newman K, Quigley L, Fernandez A, Dobson K, Sears C. (2015). Temporal 
changes in attention to sad and happy faces distinguish currently and remitted depressed 
individuals from never depressed individuals. Psychiatry Research. 230(2), 454-463. 
69. Tamir M, Robinson MD. (2007). The happy spotlight: positive mood and selective attention 
to rewarding information. Personality and Social Psychology Bulletin. 33(8),1124-1136. 
70. Fitzgibbons L, Simons RF. (1992). Affective response to color-slide stimuli in subjects with 
physical anhedonia: a three-systems analysis. Psychophysiology, 29(6):613-20. PMID: 
1461952 
71. Fiorito ER, Simons RF. (1994). Emotional imagery and physical anhedonia. 
Psychophysiology, 31(5):513-21. PMID: 7972606 
72. Epstein J, Pan H, Kocsis JH, Yang Y, Butler T, Chusid J, Hochberg H, Murrough J, 
Strohmayer E, Stern E, Silbersweig DA. (2006). Lack of ventral striatal response to 
positive stimuli in depressed versus normal subjects. The American Journal of Psychiatry, 
163(10), 1784-1790. PMID: 17012690 
73. Tremblay LK, Naranjo CA, Graham SJ, Herrmann N, Mayberg HS, Hevenor S, Busto UE. 
(2005). Functional neuroanatomical substrates of altered reward processing in major 
depressive disorder revealed by a dopaminergic probe. Archives of General Psychiatry, 
62(11), 1228-36. PMID: 16275810 
74. Pizzagalli DA, Holmes AJ, Dillon DG Goetz EL, Birk JL, Bogdan R, Dougherty DD, 
Iosifescu DV, Rauch SL, Fava M. (2009). Reduced caudate and nucleus accumbens 
response to rewards in unmedicated subjects with Major Depressive Disorder. American 
Journal of Psychiatry, 166, 702–710. PMID: 19411368 
75. Keedwell PA, Andrew C, Williams SC, Brammer MJ, Phillips ML. (2005) The neural 
correlates of anhedonia in major depressive disorder. Biological Psychiatry, 58(11), 843- 
853. PMID: 16043128 
76. Wacker J, Dillon DG, Pizzagalli DA. (2009). The role of the nucleus accumbens and rostral 
anterior cingulate cortex in anhedonia: integration of resting EEG, fMRI, and volumetric 
techniques. NeuroImage, 46(1), 327-337. PMID: 19457367 
77. Chung YS, Barch D. (2015). Anhedonia is associated with reduced incentive cue related 
activation in the basal ganglia. Cognitive, Affective & Behavioral Neuroscience, 15(4): 
749–767. PMCID: 5141384 
78. Keedwell PA, Andrew C, Williams SC, Brammer MJ, Phillips ML. (2005) The neural 
correlates of anhedonia in major depressive disorder. Biological Psychiatry, 58(11), 843- 
853. PMID: 16043128 
79. Wacker J, Dillon DG, Pizzagalli DA. (2009). The role of the nucleus accumbens and rostral 
anterior cingulate cortex in anhedonia: integration of resting EEG, fMRI, and volumetric 
techniques. NeuroImage, 46(1), 327-337. PMID: 19457367 
80. Brailean AM, Koster EH, Hoorelbeke K, De Raedt R. (2014). Attentional modulation by 
reward and punishment cues in relation to depressive symptoms. Journal of Behavior 
Therapy and Experimental Psychiatry. 45(3), 351-359. 
81. Pizzagalli DA, Iosifescu D, Hallett LA, Ratner KG, Fava M. (2008). Reduced hedonic 
capacity in major depressive disorder: evidence from a probabilistic reward task. Journal 
of Psychiatric Research, 43, 76–87. PMID: 18433774 

Affect Treatment for Depression and Anxiety Trial Protocol 28 
 
82. Whitton AE, Treadway MT, Pizzagalli DA. (2015). Reward processing dysfunction in major 
depression, bipolar disorder and schizophrenia. Current Opinion in Psychiatry, 28(1):7-12. 
PMCID: PMC4277233 
83. Kumar P, Waiter G, Ahearn T, Milders M, Reid I, Steele JD. (2008). Abnormal temporal 
difference reward-learning signals in major depression. Brain, 131: 2084–2093. PMID: 
18579575 
84. Robinson OJ, Cools R, Carlisi CO, Sahakian BJ, Drevets WC. (2012). Ventral striatum 
response during reward and punishment reversal learning in unmedicated major 
depressive disorder. American Journal of Psychiatry, 169: 152–159. PMID: 22420038 
85. Gradin, V. B., Kumar, P., Waiter, G., Ahearn, T., Stickle, C., Milders, M., Reid I, Hall J, 
Steele, J. D. (2011). Expected value and prediction error abnormalities in depression and 
schizophrenia. Brain, 134(6), 1751-1764. PMID: 21482548 
86. Taylor CT, Lyubomirsky S, Stein, MB. (2016) Upregulating the positive affect system in 
anxiety and depression: Outcomes of a positive activity intervention. Depression and 
Anxiety, 00:1–14. PMID: 28060463 
87. Craske, M.G., Meuret, A.E., Ritz, T., Treanor, M., & Dour, H. (2016). Treatment for 
anhedonia: neuroscience driven approach. Depression and Anxiety, 33, 927-938. 
88. Craske, M. G., Meuret, A. E., Ritz, T., Treanor, M., Dour, H., & Rosenfield, D. (2019). 
Positive affect treatment for depression and anxiety: A randomized clinical trial for a core 
feature of anhedonia. Journal of Consulting and Clinical Psychology, 87(5), 457–471. 
89. Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief 
measures of positive and negative affect: the PANAS scales. Journal of Personality and 
Social Psychology, 54(6), 1063. 
90. Crawford JR, Henry JD. (2004). The positive and negative affect schedule (PANAS): 
construct validity, measurement properties and normative data in a large non-clinical 
sample. British Journal of Clinical Psychology, 43, 245-265. 
91. Lovibond, S. H., & Lovibond, P. F. (1995). Manual for the Depression Anxiety Stress 
Scales (2nd ed.). Sydney, Australia: Psychology Foundation of Australia. 
92. Brown TA, Chorpita BF, Barlow DH. (1998). Structural relationships among dimensions of 
the DSM-IV anxiety and mood disorders and dimensions of negative affect, positive affect, 
and autonomic arousal. Journal of Abnormal Psychology, 107(2):179-92. PMID: 9604548 
93. Willams, J.B.W. (2000) Mental health status, functioning, and disabilities measures. 
American Psychiatric Association (Eds), Handbook of Psychiatric Measures (93-100). 
Washington, DC: American Psychiatric Association. 
94. Gross JJ. The emerging field of emotion regulation: An integrative review. Review of 
General Psychology. 1998;2(3):271–299. https://doi.org/10.1037/1089-2680.2.3.271 
95. Barry TJ, Sze WY, & Raes F. A meta-analysis and systematic review of Memory 
Specificity Training (MeST) in the treatment of emotional disorders. Behaviour Research 
and Therapy. 2019; 116:36–51. https://doi.org/10.1016/j.brat.2019.02.001 
96. Hallford DJ, Sharma MK, & Austin DW. Increasing anticipatory pleasure in major 
depression through enhancing episodic future thinking: a randomized single-case series 
trial. Journal of Psychopathology and Behavioral Assessment. 2020. 
https://doi.org/10.1007/s10862-020-09820-9 
97. Hallford DJ, Farrell H, & Lynch E. Increasing anticipated and anticipatory pleasure through 
episodic thinking. Emotion. 2020. https://doi.org/10.1037/emo0000765 
98. McMakin DL, Siegle GJ, & Shirk SR. Positive Affect Stimulation and Sustainment (PASS) 
module for depressed mood: A preliminary investigation of treatment-related effects. 
Cognitive Therapy and Research. 2011; 35(3), 217–226. https://doi.org/10.1007/s10608- 
010-9311-5 
99. Pictet A, Jermann, F, & Ceschi, G. When less could be more: Investigating the effects of a 
brief internet-based imagery cognitive bias modification intervention in depression. 

Affect Treatment for Depression and Anxiety Trial Protocol 29 
 
Behaviour Research and Therapy. 2016; 84, 45–51. 
https://doi.org/10.1016/j.brat.2016.07.008 
100. Wadlinger HA, & Isaacowitz DM. Looking happy: The experimental manipulation of a 
positive visual attention bias. Emotion. 2008; 8(1):121–126. https://doi.org/10.1037/1528- 
3542.8.1.121 
101. Wadlinger HA., & Isaacowitz DM. Fixing our focus: training attention to regulate emotion. 
Personality and Social Psychology Review : An Official Journal of the Society for 
Personality and Social Psychology, Inc. 2011; 15(1): 75–102. 
https://doi.org/10.1177/1088868310365565 
102. Peters KD, Constans JI, Mathews A. Experimental modification of attribution processes. 
Journal of Abnormal Psychology. 2011; 120(1):168–173. https://doi.org/10.1037/a0021899 
103. Holmes D, Murray SJ, Perron A & Rail G. Deconstructing the evidence-based discourse in 
health sciences: truth, power and fascism. International Journal of Evidence-Based 
Healthcare. 2006;4(3): 180–186. https://doi.org/10.1111/j.1479-6988.2006.00041.x 
104. Holmes EA, Mathews A, Mackintosh B, Dalgleish T. (2008). The causal effect of mental 
imagery on emotion assessed using picture-word cues. Emotion, 8(3), 395-409. PMID: 
18540755 
105. Pictet, Arnaud, Coughtrey, A. E., Mathews, A., & Holmes, E. A. (2011). Fishing for 
happiness: the effects of generating positive imagery on mood and behaviour. Behaviour 
Research and Therapy, 49(12), 885–891. https://doi.org/10.1016/j.brat.2011.10.003 
106. Garland EL., Fredrickson B, Kring AM., Johnson DP, Meyer PS, & Penn DL. Upward 
spirals of positive emotions counter downward spirals of negativity: insights from the 
broaden-and-build theory and affective neuroscience on the treatment of emotion 
dysfunctions and deficits in psychopathology. Clinical Psychology Review. 
2010;30(7):849–864. https://doi.org/10.1016/j.cpr.2010.03.002 
107. Hofmann SG, Grossman P, & Hinton DE. Loving-kindness and compassion meditation: 
potential for psychological interventions. Clinical Psychology Review. 2011; 31(7):1126– 
1132. https://doi.org/10.1016/j.cpr.2011.07.003 
108. Hutcherson CA, Seppala EM, Gross, JJ. Loving-kindness meditation increases social 
connectedness. In Emotion. 2008;8(5):720–724. https://doi.org/10.1037/a0013237 
109. Fredrickson BL, Cohn MA, Coffey KA, Pek J, Finkel, SM. (2008). Open hearts build lives: 
positive emotions, induced through loving- kindness meditation, build consequential 
personal resources. Journal of Personality and Social Psychology, 95:1045-1062. PMID: 
18954193 
110. Mayhew, SL, Gilbert P. Compassionate mind training with people who hear malevolent 
voices: a case series report. Clinical Psychology & Psychotherapy,. 2008;15(2):113–138. 
https://doi.org/10.1002/cpp.566 
111. Kearney DJ., Malte, CA, McManus C, Martinez ME, Felleman B, Simpson TL. Loving- 
kindness meditation for posttraumatic stress disorder: a pilot study. Journal of Traumatic 
Stress. 2013;26(4):426–434. https://doi.org/10.1002/jts.21832 
112. Hofmann SG., Petrocchi N, Steinberg J, Lin M, Arimitsu K, Kind S, Mendes A, Stangier U. 
Loving-Kindness Meditation to Target Affect in Mood Disorders: A Proof-of-Concept Study. 
Evidence-Based Complementary and Alternative Medicine. 2015. 
https://doi.org/10.1155/2015/269126 
113. Nelson, SK, Layous K, Cole SW, Lyubomirsky S. Do unto others or treat yourself? The 
effects of prosocial and self-focused behavior on psychological flourishing. Emotion 
(Washington, D.C.). 2016;16(6):850–861. https://doi.org/10.1037/emo0000178 
114. Rowland L, Curry OS. A range of kindness activities boost happiness. The Journal of 
Social Psychology. 2019;159(3):340–343. 
https://doi.org/10.1080/00224545.2018.1469461 

Affect Treatment for Depression and Anxiety Trial Protocol 30 
 
115. Snippe E, Jeronimus BF, Aan Het Rot M, Bos EH, de Jonge P, Wichers M. The 
Reciprocity of Prosocial Behavior and Positive Affect in Daily Life. Journal of Personality. 
2018;86(2):139–146. https://doi.org/10.1111/jopy.12299 
116. Schacter HL, Margolin G. When it feels good to give: Depressive symptoms, daily 
prosocial behavior, and adolescent mood. Emotion (Washington, D.C.). 2019;19(5):923– 
927. https://doi.org/10.1037/emo0000494 
117. Froh, JJ, Kashdan TB, Ozimkowski KM, & Miller N. Who benefits the most from a gratitude 
intervention in children and adolescents? Examining positive affect as a moderator. The 
Journal of Positive Psychology. 2009;4(5):408–422. 
https://doi.org/10.1080/17439760902992464 
118. Geraghty, AWA, Wood AM, Hyland ME. Dissociating the facets of hope: Agency and 
pathways predict dropout from unguided self-help therapy in opposite directions. Journal 
of Research in Personality. 2010a;44(1):155–158. 
https://doi.org/https://doi.org/10.1016/j.jrp.2009.12.003 
119. Geraghty AWA., Wood AM, Hyland ME. Attrition from self-directed interventions: 
investigating the relationship between psychological predictors, intervention content and 
dropout from a body dissatisfaction intervention. Social Science & Medicine. 
2010b;71(1):30–37. https://doi.org/10.1016/j.socscimed.2010.03.007 
120. Wood, AM, Froh JJ, Geraghty, AWA. Gratitude and well-being: a review and theoretical 
integration. Clinical Psychology Review. 2010;30(7):890–905. 
https://doi.org/10.1016/j.cpr.2010.03.005 
121. Maltby J, Wood AM, Day L, Kon TWH, Colley A, Linley PA. Personality predictors of levels 
of forgiveness two and a half years after the transgression. Journal of Research in 
Personality. 2008;42(4): 1088–1094. 
122. Wood AM, Joseph S, Maltby J. Gratitude uniquely predicts satisfaction with life: 
Incremental validity above the domains and facets of the five factor model. Personality and 
Individual Differences. 2008; 45(1):49–54. 
https://doi.org/https://doi.org/10.1016/j.paid.2008.02.019 
123. Fredrickson BL. The role of positive emotions in positive psychology. The broaden-and- 
build theory of positive emotions. The American Psychologist, 2001;56(3):218–226. 
https://doi.org/10.1037//0003-066x.56.3.218 
124. Emmons, R. A., & McCullough, M. E. (2003). Counting blessings versus burdens: an 
experimental investigation of gratitude and subjective well-being in daily life. Journal of 
Personality and Social Psychology, 84(2), 377–389. https://doi.org/10.1037//0022- 
3514.84.2.377 
125. Shonin E, Van Gordon W, Compare A, Zangeneh M, Griffiths MD. Buddhist-derived 
loving-kindness and compassion meditation for the treatment of psychopathology: A 
systematic review. Mindfulness. 2015;6(5);1161–1180. https://doi.org/10.1007/s12671- 
014-0368-1 
126. Zeng X, Chiu CPK, Wang R, Oei TPS, Leung, FYK. The effect of loving-kindness 
meditation on positive emotions: a meta-analytic review. Frontiers in Psychology. 2015; 
6:169. https://www.frontiersin.org/article/10.3389/fpsyg.2015.01693 
127. Zeng X, Wang R, Oei TPS, Leung FYK. Heart of joy: a randomized controlled trial 
evaluating the effect of an appreciative joy meditation training on subjective well-being and 
attitudes. Mindfulness. 2019;10(3):506–515. 
128. Craske, M.G., Hermans, D., & Vervliet, B. (2018). State of the art and future directions for 
extinction as a translational model for fear and anxiety. Philosophical Transactions B: 
Biological Sciences, 373(1742), 20170025. doi: 10.1098/rstb.2017.0025 
129. Craske, Treanor, Zbozinek & Vervliet (in press) 
130. Martell, C. R., Dimidjian, S., & Herman-Dunn, R. (2010). Behavioral activation for 
depression: A clinician’s guide . The Guilford Press, New York, NY. 

Affect Treatment for Depression and Anxiety Trial Protocol 31 
 
131. Beck, A. T. (1972). Cognition, anxiety, and psychophysiological disorders. In C. 
Spielberger (Ed.), Anxiety: Current trends in theory and research (pp. 343–354). New 
York, NY: Academic Press. http://dx.doi.org/10 
.1016/B978-0-12-657402-9.50008-9 
132. Disner, S. G., Beevers, C. G., Haigh, E. A. P., & Beck, A. T. (2011). Neural mechanisms of 
the cognitive model of depression. Nature Reviews Neuroscience, 12, 467– 477. 
http://dx.doi.org/10.1038/nrn3027 
133. Meuret, A. E., Ritz, T., Wilhelm, F. H., Roth, W. T., & Rosenfield, D. (2018). 
Hypoventilation therapy alleviates panic by repeated induction of dyspnea. Biological 
Psychiatry: Cognitive Neuroscience and Neuroimaging, 3, 539 –545. 
http://dx.doi.org/10.1016/j.bpsc.2018.01.010 
134. Meuret, A. E., Rosenfield, D., Seidel, A., Bhaskara, L., & Hofmann, S. G. (2010). 
Respiratory and cognitive mediators of treatment change in panic disorder: Evidence for 
intervention specificity. Journal of Consulting and Clinical Psychology, 78, 691–704. 
http://dx.doi.org/10.1037/ a0019552 
135. Meuret, A. E., Wilhelm, F. H., Ritz, T., & Roth, W. T. (2008). Feedback of end-tidal pCO2 
as a therapeutic approach for panic disorder. Journal of Psychiatric Research, 42, 560 – 
568. http://dx.doi.org/10.1016/j 
.jpsychires.2007.06.005 
136. Davies, C. D., & Craske, M. G. (2014). Low baseline pCO2 predicts poorer outcome from 
cognitive behavioral therapy: Evidence from a mixed anxiety disorders sample. Psychiatry 
Research, 219, 311–315. http://dx .doi.org/10.1016/j.psychres.2014.06.003 
137. Sharma, A., Barrett, M. S., Cucchiara, A. J., Gooneratne, N. S., & Thase, M. E. (2017). A 
Breathing-based meditation intervention for patients with major depressive disorder 
following inadequate response to antidepressants: A randomized pilot study. The Journal 
of Clinical Psychiatry, 78, e59 – e63. http://dx.doi.org/10.4088/JCP.16m10819 
138. Snaith RP, Hamilton M, Morley S, Humayan A, Hargreaves D, Trigwell P (1995). A scale 
for the assessment of hedonic tone the Snaith- Hamilton Pleasure Scale. The British 
Journal of Psychiatry, 167, 99–103. 
139. Fawcett, J., Clark, D. C., Scheftner, W. A., and Gibbons, R. D. (1983). Assessing 
anhedonia in psychiatric patients. The pleasure scale. Archives of General Psychiatry, 40, 
79–84. PMID: 6849623 
140. Chapman LJ, Chapman JP, Raulin ML. (1976). Scales for physical and social anhedonia; 
Journal of Abnormal Psychology, 85: 374–382. PMID: 956504 
141. Gard, D.E., Germans Gard, M.K., Kring, A.M., & John, O.P. (2006). Anticipatory and 
consummatory experience of pleasure: A scale development study. Journal of Research in 
Personality, 40, 1086-1102. 
142. Craske MG, Meuret AE, Ritz T, Treanor M, Dour H, Rosenfield D. Positive affect treatment 
for depression and anxiety: A randomized clinical trial for a core feature of anhedonia. J 
Consult Clin Psychol. 2019 May;87(5):457-471. doi: 10.1037/ccp0000396. PMID: 
30998048. 
143. Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the 
multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81-105. PMID: 13634291 
144. Prenoveau, J.M., Zinbarg, R.E., Craske, M.G., Mineka, S., Griffith, J.W., & Epstein, A. 
(2010). Testing a hierarchical model of anxiety and depression in adolescents: a trilevel 
model. Journal of Anxiety Disorders, 24, 334-344. PMID: 20171054 
145. Lovinbond P.F. & Lovindbond S.H. (1995). The structure of negative emotional states: 
Comparison of the depression anxiety stress scales (DASS) with the Beck Depression and 
Anxiety Inventories. Behaviour Research and Therapy, 33(3), 335-343. 
146. Shea TL, Tennant A, Pallant JF. (2009). Rasch model analysis of the Depression, Anxiety 
and Stress Scales (DASS). BMC Psychiatry, 9(1), 21. PMID: 19426512 

Affect Treatment for Depression and Anxiety Trial Protocol 32 
 
147. Antony M, Bieling PJ, Cox BJ, Enns MW, Swinson RP. (1998). Psychometric properties of 
the 42-item and 21-item versions of the Depression Anxiety Stress Scales in clinical 
groups and community a sample. Psychological Assessment; 10:176–181. PMCID: 
PMC2709995 
148. Sheehan DV, Harnett-Sheehan K, Raj BA. The measurement of disability. International 
Clinical Psychopharmacology 1996;11:89–95 
149. Sherdell L, Waugh CE, Gotlib IH. (2012). Anticipatory pleasure predicts motivation for 
reward in major depression. Journal of Abnormal Psychology. 121, 51–60. PMID: 
21842963 
150. Borsini, A., Wallis, A.S.J., Zunszain, P. et al. Characterizing anhedonia: A systematic 
review of neuroimaging across the subtypes of reward processing deficits in depression. 
Cogn Affect Behav Neurosci 20, 816–841 (2020). https://doi.org/10.3758/s13415-020- 
00804-6 
151. Knutson, B., Bhanji, J.P., Cooney, R.E., Atlas, L.Y., Gotlib, I.H. (2008). Neural responses 
to monetary incentives in major depression. Biol. Psychiatry. 63, 686–692. 
152. Stoy M, Schlagenhauf F, Sterzer, P., Bermpohl, F., Hägele, C., Suchotzki, K., Schmack, 
K., Wrase, J., Ricken, R., Knutson, B., Adli, M., Bauer, M., Heinz, A., & Ströhle A.J. 
(2012). Hyporeactivity of ventral striatum towards incentive stimuli in unmedicated 
depressed patients normalizes after treatment with escitalopram. Journal of 
Psychopharmacology. 26(5):677-88. doi: 10.1177/0269881111416686. 
153. Carver CS, White TL. (1994). Behavioral inhibition, behavioral activation, and affective 
responses to impending reward and punishment: The BIS/BAS scales. Journal of 
Personality and Social Psychology, 67:319-333. 
154. Rizvi, S.J., Quilty, L.C., Sproule, B., Cyriac, A., Bagby, R.M. et al. (2015). Development 
and validation of the Dimensional Anhedonia Rating Scale (DARS) in a community sample 
and individuals with major depression. Psychiatry Research, 229(1-2): 109-119. 
10.1016/j.psychres.2015.07.062 
155. Taylor CT, Amir N. (2010). Attention and emotion regulation. Guilford Press, New York. 
156. Bar-Haim Y, Lamy D, Pergamin L, Bakermans-Kranenburg MJ, van IMH.(2007). Threat- 
related attentional bias in anxious and nonanxious individuals: a meta-analytic study. 
Psychological Bulletin.;133(1):1-24. PMID: 17201568 
157. Joormann J, Talbot L, Gotlib IH. (2007). Biased processing of emotional information in 
girls at risk for depression. The Journal of Abnormal Psychology, 116(1), 135-143. PMID: 
17324024 
158. Taylor CT, Bomyea J, Amir N. (2010). Attentional bias away from positive social 
information mediates the link between social anxiety and anxiety vulnerability to a social 
stressor. Journal of Anxiety Disorders. 24(4), 403-408. PMID: 20207102 
159. Kellough, J. L., Beevers, C. G., Ellis, A. J., & Wells, T. T. (2008). Time course of selective 
attention in clinically depressed young adults: an eye tracking study. Behaviour research 
and therapy, 46(11), 1238–1243. https://doi.org/10.1016/j.brat.2008.07.004 
160. Winer, E. S., & Salem, T. (2016). Reward devaluation: Dot-probe meta-analytic evidence 
of avoidance of positive information in depressed persons. Psychological bulletin, 142(1), 
18–78. https://doi.org/10.1037/bul0000022 
161. Britton JC, Bar-Haim Y, Clementi MA, Sankin LS, Chen G, Shechner T, Norcross MA, 
Spiro CN, Lindstrom KM, Pine DS. (2013). Training-associated changes and stability of 
attention bias in youth: Implications for Attention Bias Modification Treatment for pediatric 
anxiety. Developmental cognitive neuroscience, 4:52-64. PMCID: PMC3606014 
162. Matsumoto D, Ekman P. Japanese and Caucasian facial expressions of emotion 
(JACFEE) [Slides]. San Francisco, CA: Intercultural and Emotion Research Laboratory, 
Department of Psychology, San Francisco State University; 1988. 

Affect Treatment for Depression and Anxiety Trial Protocol 33 
 
163. Amir N, Taylor CT, Donohue MC. (2011). Predictors of response to an attention 
modification program in generalized social phobia. Journal of Consulting and Clinical 
Psychology.;79(4):533-541. PMID: 21707134 
164. Koster EH, Crombez G, Verschuere B, De Houwer J. (2004). Selective attention to threat 
in the dot probe paradigm: differentiating vigilance and difficulty to disengage. Behaviour 
Research and Therapy, 42(10), 1183-1192. PMID: 15350857 
165. Daniel Rudaizky, Julian Basanovic & Colin MacLeod (2014) Biased attentional 
engagement with, and disengagement from, negative information: Independent cognitive 
pathways to anxiety vulnerability?, Cognition and Emotion, 28:2, 245-259, DOI: 
10.1080/02699931.2013.815154 
166. Lang PJ, Greenwald MK, Bradley MM, Hamm AO. (1993). Looking at pictures: affective, 
facial, visceral, and behavioral reactions. Psychophysiology, 30(3):261-73. PMID: 
8497555 
167. McGuire JT, Kable JW. (2010). Medial prefrontal cortical activity reflects dynamic re- 
evaluation during voluntary persistence. Nature Neuroscience. 18(5),760-6. 
168. Bradley MM, Lang PJ. (1994). Measuring emotion: the Self-Assessment Manikin and the 
Semantic Differential. Journal of Behavior Therapy and Experimental Psychiatry, 25(1):49- 
59. PMID: 7962581 
169. Kaz AC, Sarapas C, Bishop JR, Patel SR, Shankman SA. (2015). The mediating effect of 
prefrontal asymmetry on the relationship between the COMT Val(158)Met SNP and trait 
consummatory positive affect. Cognition and Emotion, 29:867-81. PMID: 25195915158. 
170. Snijders, T.A., & Bosker, R. J. (1993). Standard errors and sample sizes for two-level 
research. Journal of Educational Statistics, 18, 237-259. 
171. Hox, J. (2010). Multilevel analysis: Techniques and applications (2nd ed.). Lawrence 
Erlbaum Associates Publishers, Utrecht. 
172. Hamer, R.M., & Simpson, P.M. (2009). Last observation carried forward versus mixed 
models in the analysis of longitudinal psychiatric clinical trials. American Journal of 
Psychiatry, 166, 639-641. PMID: 19487398 
173. Heck, R. H., Thomas, S. L., & Tabata, L. N. (2014). Multilevel and Longitudinal Modeling 
with IBM SPSS. Routledge, New York: NY. 
174. Enders, C.K. (2011). Missing not at random models for latent growth curve analyses. 
Psychological Methods, 16, 1-16. PMID: 21381816 
175. Benjamini, Y., & Yekutieli, D. (2001). The control of the false discovery rate in multiple 
testing under dependency. Annals of Statistics. 29, 1165-1188. 
176. Wang, L., and Maxwell, S. E. (2015). On disaggregating between-person and within- 
person effects in longitudinal data using multilevel models. Psychological Methods, 20, 63- 
83. 
177. Campbell-Sills, L., Liverant, G., & Brown, T.A. (2004). Psychometric evaluation of the 
Behavioral Inhibition/Behavioral Activation Scales in a large sample of outpatients with 
anxiety and mood disorders. Psychological Assessment, 16, 244-54. PMID: 15456380 
178. Tang TZ, DeRubeis RJ, Hollon SD, Amsterdam J, Shelton R, Schalet B. (2009). 
Personality change during depression treatment: a placebo-controlled trial. Archives of 
General Psychiatry, 66 (12), 1322-1330 
179. Hedman E, Andersson G, Lindefors N, Gustavsson P, Lekander M, Ruck C, Andersson E, 
Ljotsson B. (2014). Personality Change following Internet-Based Cognitive Behavior 
Therapy for Severe Health Anxiety. PLoS ONE 9(12): e113871. doi:10.1371/journal.pone. 
0113871 
180. Barry T J, Vervliet B, Hermans D. (2015) An integrative review of attention biases and 
their contribution to treatment for anxiety disorders. Frontiers in Psychology, 6, Article 968. 
doi: 10.3389/fpsyg.2015.00968 
181. Niles, A., Mesri, B., Burklund, L., Lieberman, M., & Craske, M.G. (2013). Attentional bias 
and emotional reactivity as predictors and moderators of behavioral treatment for social 
phobia. Behaviour Research and Therapy, 51(10), 669-679. 
182. Hadwin JA, Richards HJ (2016) Working Memory Training and CBT Reduces Anxiety 
Symptoms and Attentional Biases to Threat: A Preliminary Study. Frontiers in Psychology, 
7, Article 47. doi: 1 O. 3389/fpsyg .2016. 0004 7 

Affect Treatment for Depression and Anxiety Trial Protocol 34 
 
183. Reiss, S., Peterson, R., Gursky, D., & McNally, R. (1986). Anxiety sensitivity, anxiety 
frequency, and the prediction of fearfulness. Behavior Research and Therapy, 24, 1–8. 
184. Telch, M. J., Shermis, M. D., & Lucas, J. A. (1989). Anxiety sensitivity: Unitary personality 
trait or domain-specific appraisals? Journal of Anxiety Disorders, 3, 25–32. 
185. Foa, E. B., Franklin, M. E., Perry, K. J., & Herbert, J. D. (1996). Cognitive biases in 
generalized social phobia. Journal of Abnormal Psychology, 105(3), 433–
439. https://doi.org/10.1037/0021-843X.105.3.433 
186. Vögele, C., Steptoe, A., 1992. Emotional coping and tonic blood pressure as determinants 
of cardiovascular responses to mental stress. J. Hypertens. 10 (9). 
https://doi.org/10.1097/00004872-199209000-00024