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. Author manuscript; available in PMC: 2024 Oct 1.
Published in final edited form as: J Obsessive Compuls Relat Disord. 2023 Sep 1;39:100840. doi: 10.1016/j.jocrd.2023.100840

Psychometric properties of a daily obsessive-compulsive symptom scale for ecological momentary assessment

Rebecca C Cox 1,2, Kelly A Knowles 2,3, Sarah C Jessup 2, Alexandra M Adamis 2, Bunmi O Olatunji 2
PMCID: PMC10552676  NIHMSID: NIHMS1930380  PMID: 37808900

Abstract

Despite growing interest in ecological momentary assessment (EMA) in psychopathology and clinical observation of day-to-day fluctuations in obsessive-compulsive disorder (OCD) symptoms, there is not a standardized EMA measure of such symptoms that can guide systematic research. In the absence of such a measure, prior EMA research in OCD has utilized heterogeneous approaches to sampling momentary and daily OCD symptoms, which limits the ability to compare results between studies. The present study sought to examine the psychometric properties of a daily OCD symptom (d-OCS) measure that assesses common OCD symptom themes (e.g., contamination, checking, intrusive thoughts) in a sample of adults with OCD (n = 20), psychiatric controls (n = 27), and healthy controls (n = 27). Participants completed the d-OCS 3 times per day for 1 week. The d-OCS distinguished those with OCD from psychiatric controls and healthy controls. The d-OCS demonstrated good internal consistency, adequate test-retest reliability, and good convergent validity. These findings offer initial psychometric support for the use of the d-OCS in EMA research examining day-to-day fluctuations in symptoms of OCD. Additional investigation is needed to examine the discriminant validity of the d-OCS and generalize these findings to more diverse samples.

Keywords: daily, momentary, OCD, assessment, obsessions, compulsions

Obsessive-compulsive disorder (OCD) affects an estimated 2.3% of the population at some point in their lifetime (Ruscio et al., 2010) and has profound, negative effects on quality of life. Individuals with OCD often experience significant functional impairment across various life domains, including decreased physical, emotional, and social functioning, and increased financial difficulties (Eisen et al., 2006; Moritz et al., 2005). Further, considerable research has found support for the heterogeneous nature of OCD in terms of diversity of symptoms, subtype, severity, and clinical presentation (Mataix-Cols et al., 2005; Olatunji et al., 2019). Given the detrimental effects of OCD on quality of life, as well as the vast heterogeneity within the disorder itself, it is critical that OCD research employs sensitive, psychometrically sound measures to advance our understanding of the etiology and maintenance of OCD symptoms. Indeed, accurate measurement of OCD symptoms over time has important implications for the development and implementation of evidence-based treatments.

There are several psychometrically sound clinical tools to assess obsessive-compulsive disorder (OCD) symptom severity. For example, the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) (Goodman et al., 1989) is widely acknowledged as the gold-standard by researchers and clinicians alike and measures obsession and compulsion severity over the past week. Severity ratings on the Y-BOCS are assessed by the time spent, interference, distress, resistance, and degree of control over both obsessions and compulsions. OCD symptoms are also commonly assessed by the Obsessive-Compulsive Inventory-Revised (OCI-R) (Foa et al., 2002) and the Dimensional Obsessive-Compulsive Scale (DOCS) (Abramowitz et al., 2010), both of which are self-report measures that assess OCD symptoms over the past month. The OCI-R measures distress related to obsessions and compulsions across six domains (i.e., washing, checking, ordering, obsessing, hoarding, neutralizing), whereas the DOCS distills symptom severity into four theme-based dimensions: contamination, responsibility for harm or mistakes, unacceptable thoughts, and incompleteness (or “not-just-right” feelings). All three assessment measures (Y-BOCS, OCI-R, and DOCS) have demonstrated good reliability, validity, sensitivity to change and diagnostic sensitivity (Abramowitz et al., 2010; Foa et al., 2002; Goodman et al., 1989), and provide valuable insight into individual differences in OCD symptoms over a given week or month. However, OCD patients often experience day-to-day fluctuations in symptoms and these measures are not designed to capture briefer fluctuations in symptom severity, representing a notable knowledge gap in the literature. Indeed, the predictors of moment-to-moment or day-to-day fluctuations of individual differences in OCD symptoms remain unclear.

Ecological momentary assessment (EMA) may be a useful method for filling this gap in the measurement of real-time changes in symptoms of OCD. EMA involves the rapid, repeated assessment of phenomena in real time and in naturalistic settings using technologies such as smartphones, electronic diaries, or passive physiological sensors (Shiffman et al., 2008; Stone & Shiffman, 1994). EMA is well-suited for capturing dynamic processes such as daily OCD symptom fluctuation, as EMA is less vulnerable to recall bias and has stronger ecological validity than traditional retrospective measures (Shiffman et al., 2008). As such, EMA methods have been increasingly and successfully leveraged in the study of anxiety disorders, yielding novel insights into the predictors, patterns, and consequences of daily fluctuations in anxiety symptoms (Walz et al., 2014). However, there is a paucity of research applying EMA to the study of OCD. Though some studies have leveraged daily diaries asking participants to log OCD symptoms as they occur (Nota et al., 2014; Purdon et al., 2007) or nightly interview of symptom severity during the day (Naftalovich et al., 2021), such approaches are limited in their psychometric validity (i.e., unstandardized, vulnerable to retrospective bias, respectively). Other studies have modified existing OCD symptom severity measures for EMA. For example, two studies used a modified version of the YBOCS administered to adults with OCD hourly for 3 days (Herman et al., 1998) and 4 times/day for 6–10 days (MacLaren Kelly et al., 2019). Two studies have used a modified version of the OCI-R (Gloster et al., 2008) in patients with OCD administered four times/day for one week and in an unselected sample completed once/day twice weekly for 4 weeks (Macatee et al., 2013). Finally, one study developed an original set of items to assess the presence and severity of momentary OCD symptoms in a treatment-seeking sample of adults with OCD 10 times/day for 4 days (Rupp et al., 2019). However, in the latter case, the items are limited in scope in the range of OCD symptoms assessed.

To date, there is no commonly used measure of daily OCD symptoms with demonstrated validity. This represents a key gap in the literature that is important to address to advance our understanding of dynamic processes in OCD. Macatee and colleagues (2013) did develop a 15-item scale with items from other validated OCD symptom measures modified for daily assessment and includes checking, contamination, ordering, and obsessing symptoms. Similar versions of this measure have been used in two prior studies of clinical and non-clinical samples (Gloster et al., 2008; Macatee et al., 2013). Although this scale that is designed for daily assessment of OCD symptoms is promising, the psychometric properties of the measure are unknown. To address this gap in the literature, we examined the performance and psychometric properties of the daily OCD symptom scale developed by Macatee et al. (2013; hereafter referred to as the d-OCS). Given that this measure consists of items from validated OCD symptom questionnaires assessing common OCD symptom themes (e.g., contamination, checking, intrusive thoughts; Burns et al., 1996; Foa et al., 2002; Hodgson & Rachman, 1977; Radomsky & Rachman, 2004; Thordarson et al., 2004; Watson & Wu, 2005), evidence of good psychometric properties could bolster the use of the scale as the ‘gold standard’ for EMA. Specifically, we examined the performance and psychometric properties of the d-OCS in a sample of adults with OCD, psychiatric controls, and healthy controls. In addition, we examined the extent to which the d-OCS can distinguish between these three groups.

Methods

Participants

The sample consisted of undergraduate students and community adults with and without OCD (N = 80) who participated prior to and during the COVID-19 pandemic.1 Participants who met criteria for moderate to high suicide risk (n = 2) or psychotic symptoms (n = 1) were withdrawn immediately and given appropriate referral information. An additional three participants withdrew prior to the second laboratory session due to scheduling issues or no longer being interested in study participation. Seventy-four participants completed both study sessions.

Twenty participants (27%) met criteria for OCD, and 27 participants (36.5%) were identified as healthy controls (i.e., met criteria for no psychiatric disorders). An additional 27 (36.5%) participants were identified as psychiatric controls (i.e., met criteria for a psychiatric disorder other than OCD). Sixty participants (75%) participated in data collection in person prior to the onset of the COVID-19 pandemic, and 20 participants (25%) participated in data collection virtually during the pandemic (see Procedure). Demographics by diagnostic group are reported in Table 1 and comorbidity information for the OCD and psychiatric control groups are reported in Supplemental Table 1.

Table 1.

Items on the Daily Obsessive-Compulsive Disorder Symptom Scale (d-OCS).

1. I checked things quite a bit.
2. I felt compelled to arrange my possessions until it felt “just right.”
3. I sometimes had to wash or clean myself simply because I felt contaminated.
4. I found it difficult to control my own thoughts.
5. I had to check things (e.g., gas or water taps, doors, etc.) several times.
6. I felt compelled to arrange objects so that they were balanced and evenly spaced.
7. I was concerned about contamination (touching dirty things, germs, or chemicals).
8. I was upset by unpleasant thoughts that came into my mind against my will.
9. I had to do things several times before I thought they were properly done.
10. I worried about germs.
11. I spent time straightening and arranging objects in my home.
12. I washed my hands quite a bit.
13. I got nasty thoughts and had difficulty in getting rid of them.
14. I washed and cleaned quite a bit.
15. I was concerned about germs and disease.
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Note. d-OCS items were compiled and first reported by Macatee & colleagues (2013).

Measures

Diagnostic status

The MINI International Neuropsychiatric Interview (MINI) (Sheehan et al., 1998) is a well-validated and widely used semi-structured diagnostic interview that assesses for 17 DSM disorders. The MINI was used to determine diagnostic status. The MINI and the YBOCS (see below) were administered by bachelor- and master-level trainees who were trained and supervised by the last author, who is a licensed clinical psychologist. Questions about diagnostic status were determined by group consensus.

OCD symptoms

The daily OCD symptoms scale (Macatee et al., 2013) is a 15-item scale that includes items from other validated OCD symptom measures modified for daily assessment and includes checking, contamination, ordering, and obsessing subscales. Items on the daily OCD symptoms scale are rated on a Likert scale from 0 (not at all) to 4 (extremely), and higher scores indicate a higher severity of daily OCD symptoms. See Table 1 for d-OCS items. We instructed participants to complete the scale considering the extent to which they experienced symptoms since the previous assessment.

The Obsessive-Compulsive Inventory-Revised (OCIR; (Foa et al., 2002) is an 18-item self-report measure of OCD symptoms in the past month. The OCIR consists of 5 subscales measuring specific categories of OCD symptoms (washing, checking, ordering, neutralizing, obsessing; the hoarding subscale was not examined, and hoarding items were not included in the total score for the purposes of this study). Items on the OCIR are rated on a Likert scale from 0 (not at all) to 4 (extremely), and higher scores indicated higher OCD symptom severity. The OCIR demonstrated adequate internal consistency (α = .87) in the present study.

The Yale-Brown Obsessive-Compulsive Scale (YBOCS) (Goodman et al., 1989) is a 10-item clinician-rated interview of OCD symptoms. The YBOCS assesses OCD symptom severity independent of symptom content and includes separate subscales for obsessions and compulsions. Higher scores indicate higher OCD symptom severity.

A neutralization task (Cougle et al., 2011) was used as a behavioral measure of OCD symptoms. Participants were asked to think of a loved one, then write the sentence “[Name of loved one] will be in a car accident” on a piece of paper. The experimenter then left the room for 1 minute. Upon returning, the experimenter recorded neutralizing responses (e.g., visualizing the accident with a different outcome, destroying the paper, changing the sentence, etc.). The outcome on the neutralization task was coded 0 (did not neutralize) or 1 (neutralized).

Mood and anxiety measures

The Perseverative Thinking Questionnaire (PTQ) (Ehring et al., 2011) is a 15-item self-report measure of transdiagnostic repetitive negative thinking. Items are rated on a Likert scale from 1 (never) to 4 (almost always), and higher scores indicate higher RNT. The PTQ demonstrated good internal consistency in the present study (α = .97).

The Depression, Anxiety, and Stress Scales-Short Form (Lovibond & Lovibond, 1995) is a 21-item self-report measure of symptoms of depression, anxiety, and stress over the past week. Only the 7-item depression and 7-item anxiety subscales were used in the present analysis. Items on the DASS are rated on a Likert scale from 0 (did not apply to me at all) to 3 (applied to me very much, or most of the time), and higher scores indicate higher symptoms of depression and anxiety. The depression and anxiety subscales demonstrated good and adequate internal consistency in the present study (α = 0.91 and 0.84), respectively.

The Anxiety Sensitivity Index (ASI) (Reiss et al., 1986) is a 16-item self-report measure of fear of fear, or anxiety about the consequences of anxiety. Items on the ASI are rated on a Likert scale from 0 (very little) to 4 (very much), and higher scores indicate higher anxiety sensitivity. The ASI demonstrated good internal consistency in the present study (α = .91).

Procedure

Data collection occurred over 9 consecutive days. All study procedures were approved by the university Institutional Review Board. This study was not preregistered. Materials and analysis code for this study are available by emailing the corresponding author.

Prior to COVID-19 pandemic

On day 1, participants attended a laboratory session that included informed consent and administration of the MINI and YBOCS. On days 2 through 8, participants received a prompt via email to complete the d-OCS at 8:00am, 2:00pm, and 8:00pm2. They were instructed to complete each assessment within two hours of receipt. 83%, 90% and 86% of responses were completed within two hours of receipt in the morning, afternoon, and evening, respectively. To minimize missing data, we did not exclude responses that were completed outside of the two-hour window3. Participants were sent a reminder email if an assessment had not been completed after 1 hour. On day 9, participants returned to the laboratory to complete the OCIR, PTQ, DASS, ASI and neutralization task.

During COVID-19 pandemic

Following the onset of the COVID-19 pandemic, data collection was halted until June 25, 2020, on which date virtual data collection was initiated. Measures on day 1 and day 9 were collected via Zoom. The suicide module of the MINI was not completed virtually. d-OCS administration was unchanged.

Data analysis

We conducted statistical analysis in SPSS version 29. We examined the distributions of momentary d-OCS responses across all times of day in the OCD, psychiatric control, and healthy control groups.

To examine the effect of time of day on OCD symptoms, we calculated time since wake for each momentary assessment by calculating duration of time elapsed between the time-stamped clock hour that a given assessment was completed and the participants sleep offset on that day in decimal format (numbers to the right of the decimal are minutes divided by 60). For example, if a participant woke up at 08:00 and completed the 3 assessments for that day at 08:05, 14:30, and 21:00, the times since wake, in decimal format, would be .08, 6.5, and 13.0. We placed a minimum limit of 0 (i.e., participant completed first assessment immediately upon reported sleep offset). We then calculated bivariate correlations between time since wake and d-OCS scores in the OCD, psychiatric control, and health control groups.

We conducted a 3-level linear mixed model analysis of variance (ANOVA) to examine differences between the OCD, psychiatric control, and healthy control groups on d-OCS scores and variability by time of day and day (level 1 = moment, level 2 = day, level 3 = participant). We calculated partial η2 in R version 4.3.0 to evaluate effect sizes for model main effects and simple main effects using standard thresholds (.01 = small, .06 = medium, .14 = large).

We tested the internal consistency of the d-OCS and d-OCS subscales by calculating Cronbach’s alpha at each administration. We tested the test-retest reliability of the d-OCS by computing correlation coefficients between scores in the morning, afternoon, and evening of days 1 and 7 and the day-average scores between days 1 and 7. We tested the convergent validity of the d-OCS and its subscales by calculating bivariate correlations with established OCD symptom measures (OCIR, YBOCS) and other measures related to mood and anxiety (PTQ, DASS, ASI) and a point biserial correlation with the neutralization task.

Results

Descriptive statistics and known group validity

Descriptive statistics and demographics are reported in Table 2. Examination of distributions of momentary d-OCS scores revealed positively skewed score distributions in OCD, psychiatric controls, and healthy controls, with the latter two groups demonstrating a modal score of 0 (Figure 1). There was a small, significant correlation between time of day and momentary d-OCS scores in the OCD group, such that higher scores were reported later in the day. There was no significant correlation between time of day and d-OCS scores in the psychiatric control group or healthy control group (Figure 2).

Table 2.

Descriptive statistics by diagnostic group

OCD (n=20) Psychiatric controls (n=27) Healthy controls (n=27) All (n=74)
Age 25.85 (10.19) 22.44 (4.63) 24.44 (6.87) 24.09 (7.31)
Sex
Male 4 (20%) 8 (29.6%) 8 (29.6%) 20 (27%)
Female 16 (80%) 19 (70.4%) 19 (70.4%) 54 (73%)
Race
White 12 (60%) 12 (44.4%) 17 (63.0%) 41 (55.4%)
African American/Black 2 (10%) 3 (11.1%) 3 (11.1%) 9 (10.8%)
Asian/Asian American 2 (10%) 8 (29.6%) 7 (25.9%) 17 (23%)
Hispanic/Latino 2 (10%) 2 (7.4%) 0 (0%) 4 (5.4%)
Other 2 (10%) 2 (7.4%) 0 (0%) 4 (5.4%)
d-OCS 12.59 (10.10) 6.00 (6.55) 2.94 (3.41) 6.7 (7.75)
YBOCS Obsessions 9.60 (1.70) 5.78 (2.75) 4.37 (3.05) 6.29 (3.33)
YBOCS Compulsions 10.10 (2.15) 7.11 (3.75) 4.70 (3.65) 7.09 (3.89)
YBOCS total 19.70 (2.79) 12.89 (6.01) 9.07 (6.29) 13.38 (6.78)
OCIR checking 3.70 (2.74) 2.22 (1.93) 1.11 (1.19) 2.22 (2.20)
OCIR ordering 4.85 (3.77) 3.67 (3.05) 2.44 (2.56) 3.54 (3.21)
OCIR neutralizing 4.65 (4.22) 1.85 (2.20) 1.07 (2.21) 2.32 (3.20)
OCIR washing 4.20 (3.14) 1.51 (1.83) 1.70 (2.27) 2.31 (2.63)
OCIR obsessions 4.50 (3.47) 3.04 (2.88) 1.33 (2.14) 2.81 (3.06)
OCIR total 26.40 (10.85) 16.22 (9.18) 9.70 (8.13) 16.59 (11.32)
DASS Anxiety 5.50 (3.76) 3.63 (3.68) 2.30 (3.92) 3.65 (3.95)
DASS Depression 6.60 (4.30) 4.56 (4.68) 1.81 (2.20) 4.11 (4.25)
PTQ 34.0 (12.77) 29.48 (14.76) 16.19 (13.48) 25.85 (15.57)
ASI 26.40 (12.74) 24.19 (12.62) 19.26 (11.10) 22.97 (12.31)
Neutralized (%) 12 (60%) 13 (48.1%) 13 (48.1%) 38 (52.8%)
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Note. d-OCS=daily OCD symptom scale; YBOCS=Yale-Brown Obsessive-Compulsive Scale; OCIR=Obsessive-Compulsive Inventory-Revised; DASS=Depression, Anxiety, and Stress Scale; PTQ=Perseverative Thinking; ASI=Anxiety Sensitivity Index.

Figure 1.

Figure 1.

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Distributions of momentary daily OCD symptom scale (d-OCS) scores in OCD (panel A), psychiatric controls (panel B), and healthy controls (panel C).

Figure 2.

Figure 2.

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Momentary daily OCD symptom scale (d-OCS) scores across the day in OCD (panel A), psychiatric controls (panel B), and healthy controls (panel C), where 0 is self-reported wake time. R = correlation coefficient. Gray band = 95% confidence interval.

There was a large, significant effect of group on d-OCS, F(2, 67.97) = 11.25, p < .001, partial η2 = .25, such that the OCD group reported significantly higher d-OCS scores (M = 12.59, SD = 10.10) compared to the psychiatric control (M = 6.21, SD = 6.58, t = 3.07, p < .01) and healthy control groups (M = 3.16, SD = 3.54, t = 4.72, p < .001) (Figure 3). There was also a small, significant effect of time of day, F(1, 945.05) = 11.37, p < .001, partial η2 = .01, such that d-OCS scores were highest later in the day. There was not a significant effect of day, F(1, 68.53) = .08, p = .78, partial η2 < .001.

Figure 3.

Figure 3.

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Group differences in average daily OCD symptom scale (d-OCS) scores between OCD, psychiatric controls, and healthy controls. Boxes represent the lower and upper quartile, and lines represent the maximum and minimum. Thick black circles represent means, and thick black lines represent medians.

Reliability

The d-OCS demonstrated adequate to good internal consistency in the morning, afternoon, and evening in the OCD group. Internal consistency was similar though somewhat attenuated in the psychiatric and healthy control groups and in the total combined sample (see Table 3). The d-OCS subscales (i.e., checking, contamination, ordering, and obsessing) also demonstrated adequate to good internal consistency in the morning, afternoon, and evening across the full sample. Similar to the full d-OCS, d-OCS subscale internal consistencies were strongest in the OCD group and attenuated in the psychiatric and healthy control groups, which the latter group exhibiting the most attenuation of internal consistency (see Supplemental Table 2).

Table 3.

Cronbach’s α and test-retest reliability coefficients for the daily OCD symptom scale (d-OCS).

OCD (n=20) Psychiatric controls (n=27) Healthy controls (n=27) All (n=74)
Cronbach’s alpha mornings .87–.94 .87–.95 .75–.89 .91–95
Cronbach’s alpha afternoons .90–.94 .87–.95 .75–.88 .91–.94
Cronbach’s alpha evenings .88–.90 .89–.96 .78–.91 .90–.94
Day 1 morning & day 7 morning 77** .66** .48* .69**
Day 1 afternoon & day 7 afternoon .86** 72** 74** .84**
Day 1 evening to day 7 evening .58* .60** .75** .68**
Day 1 average to day 7 average .86** .70** .82** .82*
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*

p < .05

**

p < .01

In the OCD group, the d-OCS demonstrated adequate test-retest reliability between days 1 and 7 in the morning and afternoon, whereas test-retest reliability was diminished between days 1 and 7 in the evening. When collapsing to the day level, the d-OCS again demonstrated adequate test-retest reliability between days 1 and 7 in the OCD group. Test-retest reliability was similar though slightly attenuated in the psychiatric and healthy control groups and in the total combined sample (see Table 3).

Convergent validity

The d-OCS demonstrated large, significant associations with OCIR total score, OCIR washing and obsessions subscales, DASS anxiety subscale, DASS depression subscale, and ASI (p < .001). The d-OCS demonstrated medium, significant associations with the YBOCS total score and obsessions and compulsions subscales, the OCIR, checking, and ordering subscales, and PTQ (p < .01). The d-OCS demonstrated a small, significant association with the OCIR neutralizing subscale (p < .05). The d-OCS was not significantly associated with neutralizing on the neutralizing task (p = .36) (Table 4). The d-OCS checking, contamination, ordering, and obsessing subscales generally demonstrated similar patterns of association as the total score. However, the d-OCS obsessing subscale demonstrated a relatively larger correlation with DASS anxiety and depression subscales, PTQ, and ASI than did the d-OCS total score (see Supplemental Table 3).

Table 4.

Descriptive statistics and correlations for study measures (n = 74).

Measure 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.
1. d-OCS --
2. YBOCS Obsessions .46** --
3. YBOCS Compulsions .42** .75** --
4. YBOCS total .47** .93** .96** --
5. OCIR checking .48** .34** .45** .43** --
6. OCIR ordering .44** .27* .32** .32** .43** --
7. OCIR neutralizing .24* .51** .45** .51** .46** .18 --
8. OCIR washing .65** .44** .46** .48** .32** .23* .31** --
9. OCIR obsessions .57** .41** .38** .42** .40** .18 .35** .34** --
10. OCIR total .70** .57** .60** .63** .76** .61** .64** .63** .68** --
11. DASS Anxiety .60** .48** .46** .50** .36** .26* .31** .40** .62* .64** --
12. DASS Depression .51** .28* .23 .27* .35** .07 .22 .36** .44** .44** .40** --
13. PTQ .45** .42** .48** .48** .40** .12 .44** .32** .59** .64** .67** .58** --
14. ASI .50** .42** .49** .49** .27* .23* .26* .35** .54** .56** .79** .34** .65** --
15. Neutralized .11 .13 .24* .20 .16 .21 .20 .18 .20 .20 .07 .004 −.07 .09 --
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Note. d-OCS=daily OCD symptom scale; YBOCS=Yale-Brown Obsessive-Compulsive Scale; OCIR=Obsessive-Compulsive Inventory-Revised; DASS=Depression, Anxiety, and Stress Scale; PTQ=Perseverative Thinking; ASI=Anxiety Sensitivity Index.

*

p < .05

**

p < .01

Discussion

The present study examined the performance and psychometric properties of the d-OCS, a measure of daily OCD symptoms, in an EMA study of adults with OCD, psychiatric controls, and healthy controls. Results revealed that the d-OCS performed well at distinguishing those with OCD from psychiatric controls and healthy controls. To our knowledge, no study to date has examined the ability of any OCD EMA measure to distinguish between clinical samples, and the present findings suggest the d-OCS has adequate construct validity. Relatedly, we found a small but significant time-of-day effect, such that scores on the d-OCS increased slightly from morning to evening. However, in probing this association in each group, we found the correlation between time of day and d-OCS scores was only significant in the OCD group, indicating a unique performance of the d-OCS in its relevant diagnostic group in regards to variability within day. This distinct pattern of symptoms in the OCD group highlights the importance of EMA measures to capture symptom variability over short time frames. Such variability, which is masked by retrospective measures, may offer insight into and greater precision in symptom subtyping, prediction of symptom increases, or treatment delivery.

We also found the d-OCS demonstrated adequate reliability. Specifically, the d-OCS total score demonstrated adequate to good internal consistency at all time points (morning, afternoon, evening) on every study day in all groups. Thus, there does not appear to be variation in individual item performance at different administration times. The subscales also demonstrated adequate to good internal consistency at all time points in the total sample, the OCD group, and the psychiatric control group; however, the internal consistency of the subscales was notably attenuated in the healthy control group. We also found adequate test-retest reliability in the OCD group at the day-level between days 1 and 7 and at the moment-level in the morning and afternoon between days 1 and 7, whereas the test-retest reliability was attenuated in the evening. Thus, the internal consistency and test-retest reliability of the d-OCS is largely similar to that observed for the OCIR (Foa et al., 2002) and YBOCS (López-Pina et al., 2015).

Across the full sample, the d-OCS was found to correlate moderately to strongly with other measures of OCD symptoms, including the YBOCS and OCIR (rs = .47–.70), suggesting good convergent validity. Notably, however, the d-OCS was also moderately to strongly correlated with other relevant measures of anxiety, depression, perseverative thinking, and anxiety sensitivity (rs = .45–.60), broadening its convergent validity beyond OCD symptom measures. These correlations appear to be strengthened by the d-OCS obsessing subscale, which is consistent with the transdiagnostic nature of repetitive negative thinking (Ehring et al., 2011). Although we did not include any measures theoretically irrelevant to OCD in the present study, limiting the ability to fully assess discriminant validity, we might expect stronger correlations with OCD symptoms than with other symptom measures. A full examination of the discriminant validity of the d-OCS would require the inclusion of specific symptom measures less relevant to OCD, such as externalizing symptoms. In addition, the d-OCS did not correlate with a behavioral task designed to assess neutralizing symptoms. However, only one OCD symptom measure (YBOCS compulsions) was significantly and weakly associated with performance on the neutralization task. Thus, it is possible that the neutralization task was not an accurate behavioral indicator of OCD symptoms within the present sample. Notably, neutralization was observed at high frequencies across all groups within our sample (Table 2), suggesting that this task might lack specificity to OCD. The development of reliable, generalizable behavioral assessments of OCD symptoms continues to be a priority in multimodal research on OCD.

EMA is growing more popular as an assessment technique in psychological research due to increased ease of implementation (e.g., the accessibility of smartphones), yet it is still underutilized in the study of OCD. The use of EMA may provide additional insight into the temporal patterns of OCD symptoms. In fact, there is also growing interest in how different treatments may result in changes in the daily lives of patients with OCD (Landman et al., 2020). However, less attention has been paid to the psychometric properties of instruments used in EMA research, which are frequently adapted from validated measures but have not themselves been carefully evaluated. In addition to concerns about accurate measurement, the use of EMA might lead to measurement reactivity, as increasing awareness of symptoms often changes behavior (Barta et al., 2012). Indeed, patients receiving treatment for OCD are often asked to self-monitor compulsive behaviors for homework in order to increase awareness and decrease engagement in compulsions (Kozak & Foa, 1997). These challenges to accurate measurement will need to be examined in future studies. However, the potential of EMA using the d-OCS to improve understanding of the temporal relationships between obsessions, compulsions, and daily stressors is an exciting future direction for clinical OCD research.

The present study examined the performance and psychometrics of the d-OCS, a daily measure of OCD symptoms, in an EMA study of adults with OCD, psychiatric controls, and healthy controls. Although the findings suggest that the d-OCS has promising psychometric properties, the findings must be considered within the context of the study limitations. First, the sample size in each group was relatively small, which may have limited the ability to detect statistically significant time of day effects in the psychiatric and healthy control groups. Likewise, it is possible that low reliability estimates on individual study days and/or moments may be due to correlation attenuation. Second, the relative sex and racial homogeneity of the sample limits the ability to generalize these findings to diverse groups. Third, as discussed above, EMA prompts were sent on a fixed schedule identical for all participants, which may have introduced bias in responding. Fourth, one week is a relatively short sampling period for EMA, and a longer sampling period would provide more robust data. Fifth, we did not include any comparator EMA OCD measures to examine which, if any, measure may outperform another, and future research is needed to validate the other measures previously used for daily OCD symptom assessment (Herman et al., 1998; Rupp et al., 2019). Sixth, it will be important to replicate these findings after the conclusion of the COVID-19 pandemic, which may have inflated OCD symptom severity in the 25% of the sample who participated during the pandemic. Given these limitations, future research is needed to replicate and extend these findings in larger and more diverse samples and without the influence of the COVID-19 pandemic in order to bolster confidence in the use of the d-OCS as the gold standard for EMA research in OCD.

Supplementary Material

1

  • Examined psychometrics of ecological momentary assessment OCD symptom scale (dOCS)

  • dOCS distinguished between OCD and psychiatric and healthy controls

  • dOCS demonstrated good internal consistency, good convergent validity

  • dOCS demonstrated adequate test-retest reliability

  • Initial psychometric support for use of dOCS to examine daily OCD symptoms

Acknowledgments

The authors would like to acknowledge Allison Booher, Yunfeng Deng, Max Luber, Angelee Parmar, Maria Sanin, and Yunshu Yang for their assistance with data collection.

Funding

This work was supported by the National Institute of Mental Health of the National Institutes of Health [F31MH113271]. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Declaration of Interest

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Given their role as an Editorial Board Member, Bunmi Olatunji had no involvement in the peer-review of this article and had no access to information regarding its peer-review.

CRediT author statement

Rebecca C. Cox: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Visualization, Writing-original draft; Kelly A. Knowles: Writing-original draft; Sarah C. Jessup: Investigation, Writing-original draft; Alexandra M. Adamis: Writing-original draft; Bunmi O. Olatunji: Resources, Supervision, Writing-review and editing.

1

The primary analyses from the parent study and detailed description of study methods have been published elsewhere (Cox & Olatunji, 2022).

2

Participants were also asked to keep a sleep diary as part of study procedures. These data have been reported elsewhere (Cox & Olatunji, 2022) and are not included in the present study.

3

Results did not differ when excluding responses that were completed outside of the 2-h window.

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NIHMS1930380-supplement-1.docx (29.5KB, docx)

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