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Rendering promise: Enhancing motivation for change in hoarding disorder using virtual reality
Journal of Obsessive-Compulsive and Related Disorders 25 (2020) 100519
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Rendering promise: Enhancing motivation for change in hoarding disorder using virtual reality
T
Gregory S. Chasson∗, C. Elizabeth Hamilton, Alexandria M. Luxon, Andrew J. De Leonardis, Sage Bates, Nisha Jagannathan Illinois Institute of Technology, 201 Tech Central, 3424 South State Street, Chicago, IL, 60616, USA
A R T I C LE I N FO
A B S T R A C T
Keywords: Hoarding Virtual reality Treatment Motivation
Treatment ambivalence is commonly associated with hoarding disorder (HD), representing a public health challenge. One possible innovative approach to reducing problematic treatment ambivalence leverages virtual reality (VR) technology as a motivational strategy. For this pilot study, 23 adults with HD were immersed in a VR environment depicting rooms in their own homes without existing clutter. At pre-VR immersion, participants completed diagnostic interviews; self-reported on HD symptoms and correlates, as well as valid measures of motivation for change; and described a cluttered series of rooms on a floor of their home that was then rendered in a VR environment minus the clutter. After immersing participants for 10 min in the VR environment and asking them to explore the rendering, they completed the measures of motivation again, plus items about acceptability of the VR protocol. The VR immersion was rated as acceptable by participants in many ways and with no indication that it was unacceptable. Pre-to post-immersion results indicate an increase in some indices of motivation, as well as in confidence to change. This pilot study provides preliminary support for the VR immersion as a motivation strategy and warrants further investigation.
1. Introduction Standard pharmacotherapy and cognitive-behavioral treatment (CBT) approaches developed for obsessive-compulsive disorder—of which hoarding behavior was considered a subtype until Hoarding Disorder (HD) was codified as a distinct diagnosis in the DSM-5 (American Psychiatric Association, 2013)—have not been particularly effective for treating HD (Muroff, Bratiotis, & Steketee, 2011). For this reason, specialized CBT for HD has been developed and tested. Two treatment trials examining CBT of HD found statistically significant reductions in hoarding symptoms and have demonstrated promise for helping individuals with HD (Steketee, Frost, Tolin, Rasmussen, & Brown, 2010; Tolin, Frost, & Steketee, 2007). Although CBT for HD has shown promise, one of the biggest concerns noted in the trials was considerable participant treatment ambivalence characterized by avoidance of treatment altogether or a lack of engagement in treatment once initiated (Steketee et al., 2010; Tolin et al., 2007). Thus, although specialized psychosocial treatments for HD are emerging and showing promise, there is need for strategies to engage those with HD in help-seeking behavior.
Innovative solutions for treatment ambivalence in this clinical population are sorely needed. One such solution may include leveraging the power of imagery to facilitate motivation to change HD behaviors by evoking implicit motives (e.g., for affiliation, power, achievement) (Rawolle, Schultheiss, Strasser, & Kehr, 2017). Using imagery via presenting physical pictures has been experimentally linked to motivation by evoking such implicit motives (e.g., Shantz & Latham, 2009), and mental imagery takes this a step further to describe visual mental representations of a desired future goal state (e.g., a baseball player mentally evoking an image of hitting a homerun before the at-bat). Mental imagery has also been causally linked to improved motivation via arousing implicit motives (Rawolle et al., 2017). The correlational association between imagery and motivation also has an extensive research base across many decades and areas (e.g., nursing, Kwekkeboom & Bratzke, 2016; sport psychology, Martin, Moritz, & Hall, 1999; pain management, Posadzki, Lewandowski, Terry, Ernst, & Stearns, 2012; sexual health, Nims, 1975). Thus, there seems to be basic experimental and correlational support for imagery as a motivation strategy, as well as a rationale for translating this technique to a clinical challenge like HD. It may be the case that using imagery via virtual reality (VR)
∗
Corresponding author. Department of Psychology, Illinois Institute of Technology, 201 Tech Central,3424 South State Street,Chicago, IL, 60616, USA. E-mail addresses: [email protected] (G.S. Chasson), [email protected] (C. Elizabeth Hamilton), [email protected] (A.M. Luxon), [email protected] (A.J. De Leonardis), [email protected] (S. Bates), [email protected] (N. Jagannathan). https://doi.org/10.1016/j.jocrd.2020.100519 Received 26 November 2019; Received in revised form 18 January 2020; Accepted 24 January 2020 Available online 28 January 2020 2211-3649/ © 2020 Elsevier Inc. All rights reserved.
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2. Methods
Planner 5D to create a VR rendering of one floor of the participant's home, but without clutter. With respect to cost of the whole set-up, including subscription to the interior decorator library of objects, smart phone, headset, and joystick, the total cost at the time of writing is less than $300. For an example of the software user interface, please see Supplemental Fig. 1 or contact the corresponding author. The software program has a VR mode that displays a navigable, first-person, eye-level view of the rooms. For an example of a rendering of a cluttered room using a picture from the Clutter Image Rating scale (Frost, Steketee, Tolin, & Renaud, 2008), please see Supplemental Fig. 2 or contact the corresponding author. Prior to the VR immersion, participants completed a battery of preimmersion measures. Next, participants were seated in a swivel chair in the middle of a room without obstacles and fitted with a headset holding a Galaxy Samsung S7 phone with Android software running the VR mode of Planner 5D. The VR immersion lasted for 10 min and was supervised by a research assistant. Wearing the headset, participants were instructed to look around the rooms created for them, turning their head and body in the swivel chair to rotate their view within the virtual environment. Participants were instructed on how to use a small handheld Bluetooth joystick to move through the environment. They were advised that if they experienced any dizziness or vertigo during the VR immersion they could discontinue early at any time without penalty (n = 1). Supplemental Video 1 (https://youtu.be/ oUV0AxcRF9I) simulates movement through an example virtual home rendering. Following the 10-min VR immersion, participants completed brief post-immersion measures. Supplementary video related to this article can be found at https:// doi.org/10.1016/j.jocrd.2020.100519
2.1. Participants
2.3. Measures
The sample included 23 non-treatment seeking community adults with diagnosed HD. Participants were predominantly female (70%) with an average age of 56.70 years (SD = 15.26; range 22–76). Current comorbidities included major depressive disorder (n = 6), attentiondeficit/hyperactivity disorder (n = 6), obsessive-compulsive disorder, generalized anxiety disorder or alcohol use disorder (n = 3), and agoraphobia, specific phobia, posttraumatic stress disorder, binge eating disorder, tobacco use disorder or insomnia disorder (n = 1). A data collection error resulted in missing information on participant ethnicity for all but 11 participants. However, among that subset of 11 individuals, 73% self-identified as White, 18% as African American, and 9% as American Indian/Alaska Native.
Structured Clinical Interview for DSM-5 Disorders – Research Version (SCID; First, Williams, Karg, & Spitzer, 2015). The SCID is a semistructured diagnostic interview used to assess for a wide range of psychopathology. The instrument is based on diagnostic criteria that have demonstrated adequate reliability (Regier et al., 2013). This interview was used to assess for psychological comorbidities among participants. Structured Interview for Hoarding Disorder (SIHD; Nordsletten et al., 2013). The SIHD is a brief diagnostic interview eliciting information about clutter, difficulty discarding, excessive acquisition, and quality of life in HD. It has demonstrated excellent psychometric properties (Nordsletten et al., 2013). The SIHD was used for establishing the presence of HD diagnoses. Saving Inventory-Revised (SI-R; Frost, Steketee, & Grisham, 2004). The SI-R contains 23 Likert items providing a total score and three subscales reflecting components of HD: Clutter, Difficult Discarding, and Acquisition. The SI-R has demonstrated good internal consistency, the ability to differentiate between individuals with and without HD, test-retest reliability, and convergent and discriminant validity (Frost et al., 2004). The clinical cutoff for the total score is 41, Clutter is 17, Difficulty Discarding is 17, and Acquisition is 9 (Frost et al., 2004). This measure was administered at pre-immersion to characterize the severity of HD. University of Rhode Island Change Assessment (URICA; McConnaughy, Prochaska, & Velicer, 1983). The 32-item URICA was administered at pre- and post-immersion and consists of statements about personal change rated on a 5-point Likert scale, from strongly disagree (score of 1) to strongly agree (score of 5). Items are averaged within four subscales representing the stages of change: Pre-Contemplation, Contemplation, Action, and Maintenance. The scale with the highest loading represents the individual's current stage of change. The scale also yields a Treatment Readiness score, derived from the subscales (i.e., sum the means of Contemplation, Action, and Maintenance and then subtract Pre-contemplation) that provides an overall score of motivation for treatment. The URICA was found to be highly reliable in
technology helps reduce help-seeking ambivalence (i.e., enhancing motivation to change) in adults with HD. To this end, the current study pilot tested a novel virtual reality (VR) technology designed to leverage the power of imagery as a motivational tool to increase motivation to change among adults with HD. Specifically, individuals with HD were immersed in a virtual environment that was tailored for each participant, permitting them to walk through a rendering of their own home but with the existing clutter removed. In doing so, individuals would theoretically be motivated to take appropriate steps to change by experiencing a positive depiction of their home (i.e., uncluttered). Moreover, an increase in motivation could occur despite any emotional comfort associated with clutter in this clinical population (Frost, Hartl, Christian, & Williams, 1995), particularly given that participation is voluntary and does not involve actual removal of any possessions, thus preserving the individual's autonomy and self-determination. The current study pilot tested this novel use of VR to enhance motivation to change in those with HD. The study evaluated whether such a technology-laden technique would be acceptable to participants with HD, especially given that many such individuals tend to be older adults (Frost, Steketee, Williams, & Warren, 2000). The study also aimed to uncover preliminary evidence of improvements in motivation to change HD behavior among individuals who participated in this VR immersion. Participants completed pre- and post-immersion self-report batteries. It was hypothesized that participants would find the VR immersion acceptable and report an increase in motivation to change HD behaviors from pre-to post-immersion.
2.2. Procedures and apparatus Participants were recruited via flyers in a large Midwestern city and were remunerated with $75 for participation. They had to be age 18 or older, speak and read English, meet DSM-5 criteria for a diagnosis of HD, and report having a current room in the home with impairing or distressing clutter. Individuals with animal hoarding, current or past psychosis, current mania, developmental disorders, dementia, epilepsy or a seizure disorder, or history of traumatic brain injury (other than mild concussion) were excluded from the study. Approval for this study was obtained from the Institutional Review Board of Illinois Institute of Technology. Prospective participants were screened over the phone by a graduate or undergraduate research assistant. Overall, 35 prospective participants were screened. Most instances of ineligibility were the result of the individual reporting uncluttered living space or not meeting diagnostic criteria for HD. After providing informed consent, participants underwent diagnostic interviews to confirm an HD diagnosis and comorbid conditions. Participants then worked closely with an undergraduate research assistant using a free digital interior design software program called 2
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an adult psychotherapy sample, with Cronbach alphas for the four subscales ranging from 0.88 to 0.89 (McConnaughy et al., 1983). There is precedent for using the URICA to measure treatment motivation in adults with HD and for the measure's sensitivity to change over time in this population (Chasson et al., 2015). Treatment Motivation Questionnaire (TMQ; Ryan, Plant, & O'Malley, 1995). The TMQ was administered at pre- and post-immersion and is a 26-item scale with subscales measuring Internal Motivation for treatment, External Motivation for treatment, Confidence in treatment, and interpersonal Help-Seeking. Items are rated on a 7-point Likert scale from not at all true to very true and averaged within subscale. Internal motivation for treatment has been associated with increased treatment success in a number of populations including those seeking treatment for diabetes, weight loss, alcohol abuse, smoking cessation, and general adult outpatient psychotherapy (Ferron, Elbogen, Swanson, Swartz, & McHugo, 2011). External Motivation at post-immersion did not achieve adequate internal stability (α = 0.43). Therefore, this subscale was dropped from data analysis. Treatment Acceptability Questionnaire (TAQ; Hunsley, 1992). A 14item adaptation of the TAQ was administered at post-immersion and assesses the acceptability of psychological treatments. The original version has demonstrated good internal consistency and test-retest reliability over a 3-week period (Hunsley, 1992). Items were modified and supplemented for this population and uniqueness of the VR immersion. Previous research with similarly modified items of the TAQ has highlighted its utility for measuring acceptability (Chasson, Carpenter, Ewing, Gibby, & Lee, 2014). A copy of the modified instrument is available from the corresponding author, and item content as well as details about item anchors can be found in the note at the bottom of Table 2.
Table 1 Pre- and post-immersion descriptive data.
SI-R total Clutter Difficulty Discarding Acquisition URICA Precontemplation Contemplation Action Maintenance TMQ Internal Motivation Help-Seeking Confidence in Treatment
Pre-Immersion
Post-Immersion
M(SD) Cronbach α
M(SD)
Cronbach α
51.48(12.73) 19.09(6.33) 18.70(4.45) 13.70(4.95)
.91 .81 .74 .73
– – – –
– – – –
1.73(0.71) 3.64(0.99) 3.73(0.80) 2.74(1.07)
.80 .87 .81 .87
1.56(0.72) 3.91(1.02) 3.78(0.77) 2.93(1.27)
.82 .93 .82 .92
4.57(1.56) 4.28(2.15) 4.35(1.78)
.92 .97 .88
4.86(1.61) 4.40(2.32) 5.14(1.65)
.93 .98 .91
Note. N = 23. SI-R=Saving Inventory–Revised. URICA=University of Rhode Island Change Assessment Scale. TMQ = Treatment Motivation Questionnaire. TMQ External Motivation subscale was removed due to poor reliability.
neutral, nor did responses on whether the VR immersion was motivating to change or motivating to complete a de-cluttering exercise. Results for Treatment Readiness are presented in Fig. 1. There was a significant increase in overall Treatment Readiness from pre-to post-VR immersion on the URICA; t(22) = 2.36, p = .028, Cohen's d = 0.24. This effect in Treatment Readiness resulted from (a) the significant decrease in URICA Precontemplation after the immersion; t (22) = −2.25, p = .035, Cohen's d = 0.24, and (b) a significant increase in URICA Contemplation after immersion; t(22) = 2.40, p = .026, Cohen's d = 0.27. Changes in scores on the Action and Maintenance subscales of the URICA were not significant, t(22) = 0.38, p = .71 and t(22) = 1.13, p = .27, respectively. Finally, as depicted in Fig. 2, there was a significant increase in TMQ Confidence from pre-to post-immersion, t(22) = 2.71, p = .013, Cohen's d = 0.46, suggesting an increase in the belief that hoarding treatment, if engaged, would be successful in helping them reduce hoarding behaviors. Changes in scores on the TMQ Internal Motivation and Help Seeking subscales were not significant, t(22) = 0.98, p = .34 and t(22) = 0.44, p = .67, respectively.
2.4. Data analysis For the first hypothesis, TAQ data were analyzed using one-sample t-tests comparing average sample ratings of each acceptability item to its respective middle anchor score of 4 (with the score of 4 serving as the criterion in a one-sample t-test; Field, 2017), which reflects neutral acceptability. For the second hypothesis, motivation to change hoarding behaviors from pre-to post-VR immersion were tested using a series of paired samples t-tests on the loadings for each of the four stages of change scales on the URICA, and the four subscales on the TMQ. Given that this was a pilot study of a novel technique with minimal potential for harm, the analysis did not include control for inflated Type I error.
4. Discussion This pilot study suggests promise for an innovative application of VR to enhance motivation to change in those with HD. The first hypothesis—that participants would find the VR immersion acceptable—was largely supported. Most acceptability indicators suggested a positive participant view of the experience, with some neutral ratings, and no clear negative ratings. Given that VR immersion might be aversive for a population that typically presents to treatment later in life (Frost et al., 2000), these findings are encouraging and mitigate concerns about feasibility of the technique. This feasibility is also supported by the low cost of the technology. Findings regarding shifts in motivation to change hoarding behaviors from pre-to post-immersion were mixed but generally promising. From pre-to post-immersion, a pattern of significant reductions in Precontemplation and increases in Contemplation, yielding higher levels of Treatment Readiness overall, is an important pattern in this treatment ambivalent population. This pattern, coupled with the finding that participants reported an increase in the confidence that hoarding intervention might help, could suggest this VR immersion may help to impel individuals with HD to seek treatment. The mechanisms for any change in motivation are unclear, but could be related to the impact of imagery on motivation. Indeed, experimental evidence suggests that imagery improves motivation (Rawolle et al., 2017). Nonetheless, some findings with the TMQ did not suggest a shift in
3. Results Descriptive data for the sample at pre- and post-immersion are provided in Table 1. All participants in the sample scored in the clinically significant range for total HD symptoms, amount of clutter, difficulty discarding, and excessive acquisition. For the current sample, Cronbach alphas for the total scores and subscales of the study measures are provided in Table 1. Missing data for key variables were minimal and spread across five different participants. One participant did not complete some items on the URICA, two participants did not complete some items on the TMQ, and two did not complete a couple of items on the TAQ. Missing data were handled with stochastic regression imputation for any missing computed scores for the scales. Results for treatment acceptability are presented in Table 2. Significant findings indicated that participants liked the VR immersion and rated it as safe and helpful. Moreover, they rated the VR immersion as not upsetting, and not provoking feelings of anger, shame, or embarrassment. Mean responses on items about the length and difficulty of the VR immersion, whether participants would be likely to recommend it to a friend, whether they judged it as having a positive impact, and whether it provoked feelings of sadness did not differ significantly from 3
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Table 2 Treatment acceptability questionnaire descriptive data and results.
VR Length VR Difficulty Likely to Recommend VR VR Feel Safe VR Helpful Like VR Experience VR Experience Has Positive Impact on Your Life Find VR to be Upsetting VR Make You Sad About Clutter/Saving VR Make You Angry About Clutter/Saving VR Make You Ashamed About Clutter/Saving VR Make You Embarrassed About Clutter/Saving VR Motivating to Seek Changes in Clutter/Saving VR Help Motivate You to Complete De-Clutter Exercise
M(SD)
M difference from Neutral Criterion of 4 (95% CI)
4.44(1.62) 3.96(1.40) 4.87(2.26) 6.52(1.04)** 4.91(1.72)* 5.13(2.01)* 4.61(1.90) 2.65(2.19)** 3.10(2.02) 2.05(1.69)** 2.40(2.04)** 2.62(2.06)** 4.38(1.99) 4.48(2.09)
.44 (−.27, 1.13) -.04 (−.65, .56) .87 (−.11, 1.85) 2.52 (2.09, 2.95) .91 (.15, 1.67) 1.13 (.16, 2.00) .61 (−.21, 1.43) −1.35 (−2.29, −.40) -.91 (−1.83, .02) −1.95 (−2.72, −1.18) −1.60 (−2.55, −.65) −1.38 (−2.32, −.44) .38 (−.52, 1.29) .48 (−.47, 1.43)
Note: N = 23. p-values based on one-sample t-tests using the neutral anchor rating of 4 as the criterion. VR Length = What did you think of the length of the VR experience (1 = too little to 7 = too much)? VR Difficulty = How hard was the VR experience (1 = too easy to 7 = too hard)? Likely to Recommend VR=How likely would you be to recommend this VR experience to a friend or loved one with HD (1 = not likely to 7 = very likely)? VR Feel Safe = How safe did you feel during the VR experience (1 = very unsafe to 7 = very safe)? VR Helpful = How helpful was this VR experience (1 = very unhelpful to 7 = very helpful)? Like VR Experience = How much did you like the VR experience (1 = disliked a lot to 7 = liked a lot)? Positive Impact = How much did this VR experience have a positive impact on your life (1 = no positive impact to 7 = major positive impact)? Experimenters Effective = How effective were the experimenters in helping you (very ineffective – very effective)? Like the Experimenters = How much did you like the experimenters (1 = not at all to 7 = a lot)? Find VR to be Upsetting = How much did you find the overall VR experience to be upsetting (1 = not at all to 7 = a lot)? VR Make You Sad = How much did the VR exercise make you sad about your clutter or saving tendencies (1 = not at all to 7 = a lot)? VR Make You Angry = How much did the VR exercise make you angry about your clutter or saving tendencies (1 = not at all to 7 = a lot)? VR Make You Ashamed = How much did the VR exercise make you ashamed about your clutter or saving tendencies (1 = not at all to 7 = a lot)? VR Make You Embarrassed = How much did the VR exercise make you embarrassed about your clutter or saving tendencies (1 = not at all to 7 = a lot)? VR Motivating to Seek Changes = How much did the VR exercise motivate you to seek changes in your saving and clutter tendencies (1 = not at all to 7 = a lot)? VR Help Motivate You to Complete De-Clutter Exercise = If you and a professional were set to de-clutter a small part of your home as an exercise, do you think participating in the VR experience would help motivate you to complete that de-cluttering exercise (1 = not at all to 7 = a lot)?. * = p < .05, ** = p < .01.
Fig. 1. Change in University of Rhode Island Change Assessment Scale (URICA) Treatment Readiness subscale from before to after VR immersion (error bar represents 1 standard error).
Motivation subscale items. It may be the case that such negative perceptions and interpretations are less likely to change from pre-to postimmersion, as the VR paradigm was not intended to target this type of content. Second, previous precedent suggests that the URICA is sensitive to change in this clinical population (Chasson et al., 2015), including the data presented in the current study. There is no such precedent for the TMQ in this clinical population, suggesting the TMQ requires further investigation in adults with HD. Although speculative at this time, it may be the case that the URICA is particularly sensitive to detecting change from such a time-limited VR immersion. The lack of change from pre-to post-immersion on indices that reflect action steps or change behaviors (i.e., URICA Action and TMQ
motivation, as Internal Motivation scores were not statistically significant from pre-to post-immersion. Although the explanation for this discrepancy between motivation indices (i.e., TMQ Internal Motivation vs. URICA Treatment Readiness) is ultimately unclear, it may be the result of measurement in at least two possible ways. First, item content of the TMQ Internal Motivation subscale often reflects a negative internal state or interpretation (e.g., “I won't feel good about myself if I don't get some help” and “I feel so guilty about my problem that I have to do something about it.“). In contrast, the URICA Pre-Contemplation and Contemplation subscale items—which largely accounted for the change in Treatment Readiness overall in this study—do not reflect negative internal states or interpretation as much as the TMQ Internal 4
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Fig. 2. Change in Treatment Motivation Questionnaire (TMQ) Confidence from before to after VR immersion (error bar represents 1 standard error).
Ethical standard
Help Seeking subscales) is not surprising. This study enrolled a nontreatment-seeking sample of adults with confirmed HD, which has been associated with considerable treatment ambivalence (Steketee et al., 2010; Tolin et al., 2007). The VR immersion in this study was timelimited and carried out only once. Future research would benefit from examining a more robust immersion, both in terms of time spent navigating the rendering (e.g., longer duration or repeated immersions over time) and in the extensiveness of the details and manipulability of the rendered stimuli (e.g., picking up and moving objects was not possible with the current immersion). A subsequent step would also include measuring treatment engagement in a trial that combines repeated VR immersion with evidence-based treatment approaches for hoarding, such as CBT. Limitations of the current study include an error in data collection of participants’ ethnicities, lack of a control group, a reliance on selfreport measures with no direct measures of behavioral change (e.g., a discarding task to see if motivation changes translate to behavior change), a limited sample size, and a lack of follow-up data collection to determine if the VR immersion had a lasting association with increased motivation. Due to missing ethnicity data, only a subset of the sample could be characterized on this key demographic variable, limiting conclusions about generalizability of findings. Poor psychometric properties for the TMQ External Motivation subscale precluded analyses. Future research would benefit from examining this type of motivation in the context of VR immersion for HD. In addition, it is important to acknowledge that effect sizes were modest, but this is not surprising given the minimal immersion time (i.e., 10 min) and that the VR experience only occurred once. A dose effect could emerge in future investigations in which longer and more frequent immersions enhance the effect size proportionally. As a way of promoting multimethod assessment (i.e., beyond a reliance on self-report), future research would also benefit from including analogue discarding tasks. This would also provide an opportunity to see if VR immersion of this type changes not just motivation, but actual discarding behavior, which is a core target of HD treatment (Steketee et al., 2010; Tolin et al., 2007). It would also be useful to measure treatment engagement and motivation at longer intervals after VR immersion to determine if increases in motivation are maintained over time. Lastly, a limited sample size precluded examining subgroup differences (e.g., gender, age) in the VR experience and outcome. Limitations and future research steps notwithstanding, the results of the current study are promising and suggest that a simple and cost effective VR immersion may be useful for facilitating treatment motivation in a clinical population that is notably treatment ambivalent.
The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.
Data transparency statement This manuscript is based on data collection that has never been used for publishing elsewhere and has not currently been submitted elsewhere. This is the first submission from this data collection (piecemeal or in its entirety).
Author contribution All authors contributed in a significant way to the manuscript and all authors have read and approved of the final version of the manuscript.
CRediT authorship contribution statement Gregory S. Chasson: Conceptualization, Methodology, Formal analysis, Data curation, Resources, Writing - original draft, Writing review & editing, Visualization, Supervision, Project administration. C. Elizabeth Hamilton: Conceptualization, Methodology, Investigation, Data curation, Writing - review & editing, Visualization, Supervision. Alexandria M. Luxon: Methodology, Investigation, Writing - review & editing. Andrew J. De Leonardis: Investigation, Writing - review & editing. Sage Bates: Investigation, Writing - review & editing. Nisha Jagannathan: Investigation, Writing - review & editing.
Declaration of competing interest The authors declare no conflicts of interest.
Acknowledgment We would like to thank Josh Guberman, Natalie Herrmann, Pranathi Merneedi, Regina Minnis, and Yadid Gutierrez Huerta for their assistance with this project. 5
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Appendix A. Supplementary data
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Supplementary data to this article can be found online at https:// doi.org/10.1016/j.jocrd.2020.100519. References American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Association. Chasson, G. S., Carpenter, A., Ewing, J., Gibby, B., & Lee, N. (2014). Empowering families to help a loved one with Hoarding Disorder: Pilot study of Family-As-Motivators training. Behaviour Research and Therapy, 63, 9–16. https://doi.org/10.1016/j.brat. 2014.08.016. Chasson, G. S., Hollern, E. A., Luxon, A. M., Bean, Y. F., Taylor, C. L., Divecha, P. N., et al. (2015). November. Preliminary results of a randomized waitlist controlled trial of FamilyAs-Motivators Training for hoarding disorder. Chicago, IL: 49th annual Association for Behavioral and Cognitive Therapies conference. Ferron, J. C., Elbogen, E. B., Swanson, J. W., Swartz, M. S., & McHugo, G. J. (2011). A conceptually based scale to measure consumers' treatment motivation. Research on Social Work Practice, 21(1), 98–105. https://doi.org/10.1177/1049731509357629. Field, A. (2017). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications Ltdhttps://www.amazon.com/Discovering-Statistics-Using-IBM-SPSS/dp/ 1526436566/ref=dp_ob_title_bk. First, M., Williams, J., Karg, R., & Spitzer, R. (2015). Structured clinical interview for DSM5—research version. American Psychiatric Association. Frost, R. O., Hartl, T. L., Christian, R., & Williams, N. (1995). The value of possessions in compulsive hoarding: Patterns of use and attachment. Behaviour Research and Therapy, 33(8), 897–902. https://doi.org/10.1016/0005-7967(95)00043-w. Frost, R. O., Steketee, G., & Grisham, J. (2004). Measurement of compulsive hoarding: Saving inventory-revised. Behaviour Research and Therapy, 42(10), 1163–1182. https://doi.org/10.1016/j.brat.2003.07.006. Frost, R. O., Steketee, G., Tolin, D. F., & Renaud, S. (2008). Development and validation of the clutter image rating. Journal of Psychopathology and Behavioral Assessment, 30(3), 193–203. https://doi.org/10.1007/s10862-007-9068-7. Frost, R. O., Steketee, G., Williams, L. F., & Warren, R. (2000). Mood, personality disorder symptoms and disability in obsessive compulsive hoarders: A comparison with clinical and nonclinical controls. Behaviour Research and Therapy, 38(11), 1071–1081. Hunsley, J. (1992). Development of the treatment acceptability Questionnaire. Journal of Psychopathology and Behavioral Assessment, 14(1), 55–64. https://doi.org/10.1007/ BF00960091. Kwekkeboom, K. L., & Bratzke, L. C. (2016). A systematic review of relaxation,
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Short communication
Rendering promise: Enhancing motivation for change in hoarding disorder using virtual reality
T
Gregory S. Chasson∗, C. Elizabeth Hamilton, Alexandria M. Luxon, Andrew J. De Leonardis, Sage Bates, Nisha Jagannathan Illinois Institute of Technology, 201 Tech Central, 3424 South State Street, Chicago, IL, 60616, USA
A R T I C LE I N FO
A B S T R A C T
Keywords: Hoarding Virtual reality Treatment Motivation
Treatment ambivalence is commonly associated with hoarding disorder (HD), representing a public health challenge. One possible innovative approach to reducing problematic treatment ambivalence leverages virtual reality (VR) technology as a motivational strategy. For this pilot study, 23 adults with HD were immersed in a VR environment depicting rooms in their own homes without existing clutter. At pre-VR immersion, participants completed diagnostic interviews; self-reported on HD symptoms and correlates, as well as valid measures of motivation for change; and described a cluttered series of rooms on a floor of their home that was then rendered in a VR environment minus the clutter. After immersing participants for 10 min in the VR environment and asking them to explore the rendering, they completed the measures of motivation again, plus items about acceptability of the VR protocol. The VR immersion was rated as acceptable by participants in many ways and with no indication that it was unacceptable. Pre-to post-immersion results indicate an increase in some indices of motivation, as well as in confidence to change. This pilot study provides preliminary support for the VR immersion as a motivation strategy and warrants further investigation.
1. Introduction Standard pharmacotherapy and cognitive-behavioral treatment (CBT) approaches developed for obsessive-compulsive disorder—of which hoarding behavior was considered a subtype until Hoarding Disorder (HD) was codified as a distinct diagnosis in the DSM-5 (American Psychiatric Association, 2013)—have not been particularly effective for treating HD (Muroff, Bratiotis, & Steketee, 2011). For this reason, specialized CBT for HD has been developed and tested. Two treatment trials examining CBT of HD found statistically significant reductions in hoarding symptoms and have demonstrated promise for helping individuals with HD (Steketee, Frost, Tolin, Rasmussen, & Brown, 2010; Tolin, Frost, & Steketee, 2007). Although CBT for HD has shown promise, one of the biggest concerns noted in the trials was considerable participant treatment ambivalence characterized by avoidance of treatment altogether or a lack of engagement in treatment once initiated (Steketee et al., 2010; Tolin et al., 2007). Thus, although specialized psychosocial treatments for HD are emerging and showing promise, there is need for strategies to engage those with HD in help-seeking behavior.
Innovative solutions for treatment ambivalence in this clinical population are sorely needed. One such solution may include leveraging the power of imagery to facilitate motivation to change HD behaviors by evoking implicit motives (e.g., for affiliation, power, achievement) (Rawolle, Schultheiss, Strasser, & Kehr, 2017). Using imagery via presenting physical pictures has been experimentally linked to motivation by evoking such implicit motives (e.g., Shantz & Latham, 2009), and mental imagery takes this a step further to describe visual mental representations of a desired future goal state (e.g., a baseball player mentally evoking an image of hitting a homerun before the at-bat). Mental imagery has also been causally linked to improved motivation via arousing implicit motives (Rawolle et al., 2017). The correlational association between imagery and motivation also has an extensive research base across many decades and areas (e.g., nursing, Kwekkeboom & Bratzke, 2016; sport psychology, Martin, Moritz, & Hall, 1999; pain management, Posadzki, Lewandowski, Terry, Ernst, & Stearns, 2012; sexual health, Nims, 1975). Thus, there seems to be basic experimental and correlational support for imagery as a motivation strategy, as well as a rationale for translating this technique to a clinical challenge like HD. It may be the case that using imagery via virtual reality (VR)
∗
Corresponding author. Department of Psychology, Illinois Institute of Technology, 201 Tech Central,3424 South State Street,Chicago, IL, 60616, USA. E-mail addresses: [email protected] (G.S. Chasson), [email protected] (C. Elizabeth Hamilton), [email protected] (A.M. Luxon), [email protected] (A.J. De Leonardis), [email protected] (S. Bates), [email protected] (N. Jagannathan). https://doi.org/10.1016/j.jocrd.2020.100519 Received 26 November 2019; Received in revised form 18 January 2020; Accepted 24 January 2020 Available online 28 January 2020 2211-3649/ © 2020 Elsevier Inc. All rights reserved.
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2. Methods
Planner 5D to create a VR rendering of one floor of the participant's home, but without clutter. With respect to cost of the whole set-up, including subscription to the interior decorator library of objects, smart phone, headset, and joystick, the total cost at the time of writing is less than $300. For an example of the software user interface, please see Supplemental Fig. 1 or contact the corresponding author. The software program has a VR mode that displays a navigable, first-person, eye-level view of the rooms. For an example of a rendering of a cluttered room using a picture from the Clutter Image Rating scale (Frost, Steketee, Tolin, & Renaud, 2008), please see Supplemental Fig. 2 or contact the corresponding author. Prior to the VR immersion, participants completed a battery of preimmersion measures. Next, participants were seated in a swivel chair in the middle of a room without obstacles and fitted with a headset holding a Galaxy Samsung S7 phone with Android software running the VR mode of Planner 5D. The VR immersion lasted for 10 min and was supervised by a research assistant. Wearing the headset, participants were instructed to look around the rooms created for them, turning their head and body in the swivel chair to rotate their view within the virtual environment. Participants were instructed on how to use a small handheld Bluetooth joystick to move through the environment. They were advised that if they experienced any dizziness or vertigo during the VR immersion they could discontinue early at any time without penalty (n = 1). Supplemental Video 1 (https://youtu.be/ oUV0AxcRF9I) simulates movement through an example virtual home rendering. Following the 10-min VR immersion, participants completed brief post-immersion measures. Supplementary video related to this article can be found at https:// doi.org/10.1016/j.jocrd.2020.100519
2.1. Participants
2.3. Measures
The sample included 23 non-treatment seeking community adults with diagnosed HD. Participants were predominantly female (70%) with an average age of 56.70 years (SD = 15.26; range 22–76). Current comorbidities included major depressive disorder (n = 6), attentiondeficit/hyperactivity disorder (n = 6), obsessive-compulsive disorder, generalized anxiety disorder or alcohol use disorder (n = 3), and agoraphobia, specific phobia, posttraumatic stress disorder, binge eating disorder, tobacco use disorder or insomnia disorder (n = 1). A data collection error resulted in missing information on participant ethnicity for all but 11 participants. However, among that subset of 11 individuals, 73% self-identified as White, 18% as African American, and 9% as American Indian/Alaska Native.
Structured Clinical Interview for DSM-5 Disorders – Research Version (SCID; First, Williams, Karg, & Spitzer, 2015). The SCID is a semistructured diagnostic interview used to assess for a wide range of psychopathology. The instrument is based on diagnostic criteria that have demonstrated adequate reliability (Regier et al., 2013). This interview was used to assess for psychological comorbidities among participants. Structured Interview for Hoarding Disorder (SIHD; Nordsletten et al., 2013). The SIHD is a brief diagnostic interview eliciting information about clutter, difficulty discarding, excessive acquisition, and quality of life in HD. It has demonstrated excellent psychometric properties (Nordsletten et al., 2013). The SIHD was used for establishing the presence of HD diagnoses. Saving Inventory-Revised (SI-R; Frost, Steketee, & Grisham, 2004). The SI-R contains 23 Likert items providing a total score and three subscales reflecting components of HD: Clutter, Difficult Discarding, and Acquisition. The SI-R has demonstrated good internal consistency, the ability to differentiate between individuals with and without HD, test-retest reliability, and convergent and discriminant validity (Frost et al., 2004). The clinical cutoff for the total score is 41, Clutter is 17, Difficulty Discarding is 17, and Acquisition is 9 (Frost et al., 2004). This measure was administered at pre-immersion to characterize the severity of HD. University of Rhode Island Change Assessment (URICA; McConnaughy, Prochaska, & Velicer, 1983). The 32-item URICA was administered at pre- and post-immersion and consists of statements about personal change rated on a 5-point Likert scale, from strongly disagree (score of 1) to strongly agree (score of 5). Items are averaged within four subscales representing the stages of change: Pre-Contemplation, Contemplation, Action, and Maintenance. The scale with the highest loading represents the individual's current stage of change. The scale also yields a Treatment Readiness score, derived from the subscales (i.e., sum the means of Contemplation, Action, and Maintenance and then subtract Pre-contemplation) that provides an overall score of motivation for treatment. The URICA was found to be highly reliable in
technology helps reduce help-seeking ambivalence (i.e., enhancing motivation to change) in adults with HD. To this end, the current study pilot tested a novel virtual reality (VR) technology designed to leverage the power of imagery as a motivational tool to increase motivation to change among adults with HD. Specifically, individuals with HD were immersed in a virtual environment that was tailored for each participant, permitting them to walk through a rendering of their own home but with the existing clutter removed. In doing so, individuals would theoretically be motivated to take appropriate steps to change by experiencing a positive depiction of their home (i.e., uncluttered). Moreover, an increase in motivation could occur despite any emotional comfort associated with clutter in this clinical population (Frost, Hartl, Christian, & Williams, 1995), particularly given that participation is voluntary and does not involve actual removal of any possessions, thus preserving the individual's autonomy and self-determination. The current study pilot tested this novel use of VR to enhance motivation to change in those with HD. The study evaluated whether such a technology-laden technique would be acceptable to participants with HD, especially given that many such individuals tend to be older adults (Frost, Steketee, Williams, & Warren, 2000). The study also aimed to uncover preliminary evidence of improvements in motivation to change HD behavior among individuals who participated in this VR immersion. Participants completed pre- and post-immersion self-report batteries. It was hypothesized that participants would find the VR immersion acceptable and report an increase in motivation to change HD behaviors from pre-to post-immersion.
2.2. Procedures and apparatus Participants were recruited via flyers in a large Midwestern city and were remunerated with $75 for participation. They had to be age 18 or older, speak and read English, meet DSM-5 criteria for a diagnosis of HD, and report having a current room in the home with impairing or distressing clutter. Individuals with animal hoarding, current or past psychosis, current mania, developmental disorders, dementia, epilepsy or a seizure disorder, or history of traumatic brain injury (other than mild concussion) were excluded from the study. Approval for this study was obtained from the Institutional Review Board of Illinois Institute of Technology. Prospective participants were screened over the phone by a graduate or undergraduate research assistant. Overall, 35 prospective participants were screened. Most instances of ineligibility were the result of the individual reporting uncluttered living space or not meeting diagnostic criteria for HD. After providing informed consent, participants underwent diagnostic interviews to confirm an HD diagnosis and comorbid conditions. Participants then worked closely with an undergraduate research assistant using a free digital interior design software program called 2
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an adult psychotherapy sample, with Cronbach alphas for the four subscales ranging from 0.88 to 0.89 (McConnaughy et al., 1983). There is precedent for using the URICA to measure treatment motivation in adults with HD and for the measure's sensitivity to change over time in this population (Chasson et al., 2015). Treatment Motivation Questionnaire (TMQ; Ryan, Plant, & O'Malley, 1995). The TMQ was administered at pre- and post-immersion and is a 26-item scale with subscales measuring Internal Motivation for treatment, External Motivation for treatment, Confidence in treatment, and interpersonal Help-Seeking. Items are rated on a 7-point Likert scale from not at all true to very true and averaged within subscale. Internal motivation for treatment has been associated with increased treatment success in a number of populations including those seeking treatment for diabetes, weight loss, alcohol abuse, smoking cessation, and general adult outpatient psychotherapy (Ferron, Elbogen, Swanson, Swartz, & McHugo, 2011). External Motivation at post-immersion did not achieve adequate internal stability (α = 0.43). Therefore, this subscale was dropped from data analysis. Treatment Acceptability Questionnaire (TAQ; Hunsley, 1992). A 14item adaptation of the TAQ was administered at post-immersion and assesses the acceptability of psychological treatments. The original version has demonstrated good internal consistency and test-retest reliability over a 3-week period (Hunsley, 1992). Items were modified and supplemented for this population and uniqueness of the VR immersion. Previous research with similarly modified items of the TAQ has highlighted its utility for measuring acceptability (Chasson, Carpenter, Ewing, Gibby, & Lee, 2014). A copy of the modified instrument is available from the corresponding author, and item content as well as details about item anchors can be found in the note at the bottom of Table 2.
Table 1 Pre- and post-immersion descriptive data.
SI-R total Clutter Difficulty Discarding Acquisition URICA Precontemplation Contemplation Action Maintenance TMQ Internal Motivation Help-Seeking Confidence in Treatment
Pre-Immersion
Post-Immersion
M(SD) Cronbach α
M(SD)
Cronbach α
51.48(12.73) 19.09(6.33) 18.70(4.45) 13.70(4.95)
.91 .81 .74 .73
– – – –
– – – –
1.73(0.71) 3.64(0.99) 3.73(0.80) 2.74(1.07)
.80 .87 .81 .87
1.56(0.72) 3.91(1.02) 3.78(0.77) 2.93(1.27)
.82 .93 .82 .92
4.57(1.56) 4.28(2.15) 4.35(1.78)
.92 .97 .88
4.86(1.61) 4.40(2.32) 5.14(1.65)
.93 .98 .91
Note. N = 23. SI-R=Saving Inventory–Revised. URICA=University of Rhode Island Change Assessment Scale. TMQ = Treatment Motivation Questionnaire. TMQ External Motivation subscale was removed due to poor reliability.
neutral, nor did responses on whether the VR immersion was motivating to change or motivating to complete a de-cluttering exercise. Results for Treatment Readiness are presented in Fig. 1. There was a significant increase in overall Treatment Readiness from pre-to post-VR immersion on the URICA; t(22) = 2.36, p = .028, Cohen's d = 0.24. This effect in Treatment Readiness resulted from (a) the significant decrease in URICA Precontemplation after the immersion; t (22) = −2.25, p = .035, Cohen's d = 0.24, and (b) a significant increase in URICA Contemplation after immersion; t(22) = 2.40, p = .026, Cohen's d = 0.27. Changes in scores on the Action and Maintenance subscales of the URICA were not significant, t(22) = 0.38, p = .71 and t(22) = 1.13, p = .27, respectively. Finally, as depicted in Fig. 2, there was a significant increase in TMQ Confidence from pre-to post-immersion, t(22) = 2.71, p = .013, Cohen's d = 0.46, suggesting an increase in the belief that hoarding treatment, if engaged, would be successful in helping them reduce hoarding behaviors. Changes in scores on the TMQ Internal Motivation and Help Seeking subscales were not significant, t(22) = 0.98, p = .34 and t(22) = 0.44, p = .67, respectively.
2.4. Data analysis For the first hypothesis, TAQ data were analyzed using one-sample t-tests comparing average sample ratings of each acceptability item to its respective middle anchor score of 4 (with the score of 4 serving as the criterion in a one-sample t-test; Field, 2017), which reflects neutral acceptability. For the second hypothesis, motivation to change hoarding behaviors from pre-to post-VR immersion were tested using a series of paired samples t-tests on the loadings for each of the four stages of change scales on the URICA, and the four subscales on the TMQ. Given that this was a pilot study of a novel technique with minimal potential for harm, the analysis did not include control for inflated Type I error.
4. Discussion This pilot study suggests promise for an innovative application of VR to enhance motivation to change in those with HD. The first hypothesis—that participants would find the VR immersion acceptable—was largely supported. Most acceptability indicators suggested a positive participant view of the experience, with some neutral ratings, and no clear negative ratings. Given that VR immersion might be aversive for a population that typically presents to treatment later in life (Frost et al., 2000), these findings are encouraging and mitigate concerns about feasibility of the technique. This feasibility is also supported by the low cost of the technology. Findings regarding shifts in motivation to change hoarding behaviors from pre-to post-immersion were mixed but generally promising. From pre-to post-immersion, a pattern of significant reductions in Precontemplation and increases in Contemplation, yielding higher levels of Treatment Readiness overall, is an important pattern in this treatment ambivalent population. This pattern, coupled with the finding that participants reported an increase in the confidence that hoarding intervention might help, could suggest this VR immersion may help to impel individuals with HD to seek treatment. The mechanisms for any change in motivation are unclear, but could be related to the impact of imagery on motivation. Indeed, experimental evidence suggests that imagery improves motivation (Rawolle et al., 2017). Nonetheless, some findings with the TMQ did not suggest a shift in
3. Results Descriptive data for the sample at pre- and post-immersion are provided in Table 1. All participants in the sample scored in the clinically significant range for total HD symptoms, amount of clutter, difficulty discarding, and excessive acquisition. For the current sample, Cronbach alphas for the total scores and subscales of the study measures are provided in Table 1. Missing data for key variables were minimal and spread across five different participants. One participant did not complete some items on the URICA, two participants did not complete some items on the TMQ, and two did not complete a couple of items on the TAQ. Missing data were handled with stochastic regression imputation for any missing computed scores for the scales. Results for treatment acceptability are presented in Table 2. Significant findings indicated that participants liked the VR immersion and rated it as safe and helpful. Moreover, they rated the VR immersion as not upsetting, and not provoking feelings of anger, shame, or embarrassment. Mean responses on items about the length and difficulty of the VR immersion, whether participants would be likely to recommend it to a friend, whether they judged it as having a positive impact, and whether it provoked feelings of sadness did not differ significantly from 3
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Table 2 Treatment acceptability questionnaire descriptive data and results.
VR Length VR Difficulty Likely to Recommend VR VR Feel Safe VR Helpful Like VR Experience VR Experience Has Positive Impact on Your Life Find VR to be Upsetting VR Make You Sad About Clutter/Saving VR Make You Angry About Clutter/Saving VR Make You Ashamed About Clutter/Saving VR Make You Embarrassed About Clutter/Saving VR Motivating to Seek Changes in Clutter/Saving VR Help Motivate You to Complete De-Clutter Exercise
M(SD)
M difference from Neutral Criterion of 4 (95% CI)
4.44(1.62) 3.96(1.40) 4.87(2.26) 6.52(1.04)** 4.91(1.72)* 5.13(2.01)* 4.61(1.90) 2.65(2.19)** 3.10(2.02) 2.05(1.69)** 2.40(2.04)** 2.62(2.06)** 4.38(1.99) 4.48(2.09)
.44 (−.27, 1.13) -.04 (−.65, .56) .87 (−.11, 1.85) 2.52 (2.09, 2.95) .91 (.15, 1.67) 1.13 (.16, 2.00) .61 (−.21, 1.43) −1.35 (−2.29, −.40) -.91 (−1.83, .02) −1.95 (−2.72, −1.18) −1.60 (−2.55, −.65) −1.38 (−2.32, −.44) .38 (−.52, 1.29) .48 (−.47, 1.43)
Note: N = 23. p-values based on one-sample t-tests using the neutral anchor rating of 4 as the criterion. VR Length = What did you think of the length of the VR experience (1 = too little to 7 = too much)? VR Difficulty = How hard was the VR experience (1 = too easy to 7 = too hard)? Likely to Recommend VR=How likely would you be to recommend this VR experience to a friend or loved one with HD (1 = not likely to 7 = very likely)? VR Feel Safe = How safe did you feel during the VR experience (1 = very unsafe to 7 = very safe)? VR Helpful = How helpful was this VR experience (1 = very unhelpful to 7 = very helpful)? Like VR Experience = How much did you like the VR experience (1 = disliked a lot to 7 = liked a lot)? Positive Impact = How much did this VR experience have a positive impact on your life (1 = no positive impact to 7 = major positive impact)? Experimenters Effective = How effective were the experimenters in helping you (very ineffective – very effective)? Like the Experimenters = How much did you like the experimenters (1 = not at all to 7 = a lot)? Find VR to be Upsetting = How much did you find the overall VR experience to be upsetting (1 = not at all to 7 = a lot)? VR Make You Sad = How much did the VR exercise make you sad about your clutter or saving tendencies (1 = not at all to 7 = a lot)? VR Make You Angry = How much did the VR exercise make you angry about your clutter or saving tendencies (1 = not at all to 7 = a lot)? VR Make You Ashamed = How much did the VR exercise make you ashamed about your clutter or saving tendencies (1 = not at all to 7 = a lot)? VR Make You Embarrassed = How much did the VR exercise make you embarrassed about your clutter or saving tendencies (1 = not at all to 7 = a lot)? VR Motivating to Seek Changes = How much did the VR exercise motivate you to seek changes in your saving and clutter tendencies (1 = not at all to 7 = a lot)? VR Help Motivate You to Complete De-Clutter Exercise = If you and a professional were set to de-clutter a small part of your home as an exercise, do you think participating in the VR experience would help motivate you to complete that de-cluttering exercise (1 = not at all to 7 = a lot)?. * = p < .05, ** = p < .01.
Fig. 1. Change in University of Rhode Island Change Assessment Scale (URICA) Treatment Readiness subscale from before to after VR immersion (error bar represents 1 standard error).
Motivation subscale items. It may be the case that such negative perceptions and interpretations are less likely to change from pre-to postimmersion, as the VR paradigm was not intended to target this type of content. Second, previous precedent suggests that the URICA is sensitive to change in this clinical population (Chasson et al., 2015), including the data presented in the current study. There is no such precedent for the TMQ in this clinical population, suggesting the TMQ requires further investigation in adults with HD. Although speculative at this time, it may be the case that the URICA is particularly sensitive to detecting change from such a time-limited VR immersion. The lack of change from pre-to post-immersion on indices that reflect action steps or change behaviors (i.e., URICA Action and TMQ
motivation, as Internal Motivation scores were not statistically significant from pre-to post-immersion. Although the explanation for this discrepancy between motivation indices (i.e., TMQ Internal Motivation vs. URICA Treatment Readiness) is ultimately unclear, it may be the result of measurement in at least two possible ways. First, item content of the TMQ Internal Motivation subscale often reflects a negative internal state or interpretation (e.g., “I won't feel good about myself if I don't get some help” and “I feel so guilty about my problem that I have to do something about it.“). In contrast, the URICA Pre-Contemplation and Contemplation subscale items—which largely accounted for the change in Treatment Readiness overall in this study—do not reflect negative internal states or interpretation as much as the TMQ Internal 4
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Fig. 2. Change in Treatment Motivation Questionnaire (TMQ) Confidence from before to after VR immersion (error bar represents 1 standard error).
Ethical standard
Help Seeking subscales) is not surprising. This study enrolled a nontreatment-seeking sample of adults with confirmed HD, which has been associated with considerable treatment ambivalence (Steketee et al., 2010; Tolin et al., 2007). The VR immersion in this study was timelimited and carried out only once. Future research would benefit from examining a more robust immersion, both in terms of time spent navigating the rendering (e.g., longer duration or repeated immersions over time) and in the extensiveness of the details and manipulability of the rendered stimuli (e.g., picking up and moving objects was not possible with the current immersion). A subsequent step would also include measuring treatment engagement in a trial that combines repeated VR immersion with evidence-based treatment approaches for hoarding, such as CBT. Limitations of the current study include an error in data collection of participants’ ethnicities, lack of a control group, a reliance on selfreport measures with no direct measures of behavioral change (e.g., a discarding task to see if motivation changes translate to behavior change), a limited sample size, and a lack of follow-up data collection to determine if the VR immersion had a lasting association with increased motivation. Due to missing ethnicity data, only a subset of the sample could be characterized on this key demographic variable, limiting conclusions about generalizability of findings. Poor psychometric properties for the TMQ External Motivation subscale precluded analyses. Future research would benefit from examining this type of motivation in the context of VR immersion for HD. In addition, it is important to acknowledge that effect sizes were modest, but this is not surprising given the minimal immersion time (i.e., 10 min) and that the VR experience only occurred once. A dose effect could emerge in future investigations in which longer and more frequent immersions enhance the effect size proportionally. As a way of promoting multimethod assessment (i.e., beyond a reliance on self-report), future research would also benefit from including analogue discarding tasks. This would also provide an opportunity to see if VR immersion of this type changes not just motivation, but actual discarding behavior, which is a core target of HD treatment (Steketee et al., 2010; Tolin et al., 2007). It would also be useful to measure treatment engagement and motivation at longer intervals after VR immersion to determine if increases in motivation are maintained over time. Lastly, a limited sample size precluded examining subgroup differences (e.g., gender, age) in the VR experience and outcome. Limitations and future research steps notwithstanding, the results of the current study are promising and suggest that a simple and cost effective VR immersion may be useful for facilitating treatment motivation in a clinical population that is notably treatment ambivalent.
The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.
Data transparency statement This manuscript is based on data collection that has never been used for publishing elsewhere and has not currently been submitted elsewhere. This is the first submission from this data collection (piecemeal or in its entirety).
Author contribution All authors contributed in a significant way to the manuscript and all authors have read and approved of the final version of the manuscript.
CRediT authorship contribution statement Gregory S. Chasson: Conceptualization, Methodology, Formal analysis, Data curation, Resources, Writing - original draft, Writing review & editing, Visualization, Supervision, Project administration. C. Elizabeth Hamilton: Conceptualization, Methodology, Investigation, Data curation, Writing - review & editing, Visualization, Supervision. Alexandria M. Luxon: Methodology, Investigation, Writing - review & editing. Andrew J. De Leonardis: Investigation, Writing - review & editing. Sage Bates: Investigation, Writing - review & editing. Nisha Jagannathan: Investigation, Writing - review & editing.
Declaration of competing interest The authors declare no conflicts of interest.
Acknowledgment We would like to thank Josh Guberman, Natalie Herrmann, Pranathi Merneedi, Regina Minnis, and Yadid Gutierrez Huerta for their assistance with this project. 5
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Appendix A. Supplementary data
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