Resilience Factors and Selective Learning in Patients With Fibromyalgia
Study Details
Study Description
Brief Summary
Learning impairments (such as reduced selective learning or excessive generalization) in the context of pain can lead to disability. Learning deficits have been found in experimental studies in various pain populations. In current scientific discussions, the activation of resilience factors (in particular positive affect and optimism) is being considered to optimize learning experiences and to make therapeutic procedures more effective. Positive affect could promote selective learning since positive emotions broaden attention and focus and thus possibly improve inhibitory learning. There is first scientific evidence for improved safety learning through positive affect in non-clinical samples in the context of pain. In this research project, the influence of positive affect and optimism on selective learning will be investigated in a clinical sample of fibromyalgia patients. Data will be collected online and standardized questionnaires will be used.
The authors expect that (1) There will be a larger increase in positive affect and positive future expectations in the Best Possible Self condition than in the Typical Day condition. (2) Patients in the Best Possible Self condition will show elevated positive affect and positive future expectations after the intervention compared to patients in the Typical Day condition. (3) And crucially, patients in the Best Possible Self condition will show better selective learning than patients in the Typical Day group. Thus the investigators hypothesize that the blocking effect will be higher for patients with higher degrees of positive affect and optimism.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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N/A |
Detailed Description
Selective learning will be experimentally investigated by using the blocking procedure. The blocking effect is one mechanism that can provide information about selective learning. In this procedure, one event (A+) will be first paired with pain. Participants should learn the relation between this event and the occurrence of pain. After, another event (x), i.e. the blocking stimulus, is displayed with the first event A (AX+). The combination of both events will also be associated with pain. It will be tested, to which extent participants expect pain for the blocking stimulus alone. In case of "blocked", i.e. reduced pain expectation for X we can assume adaptive, selective learning.
In the planned study a fictitious diary of a fibromyalgia patient will be used as "cover story". Different events and the words "pain" or "no pain" will be visually presented together, indicating in which situation pain occurs and in which not. Participants will be asked to imagine that they are the practitioner trying to learn which situations are associated with pain. This learning experiment is based on a former study by Meulders and colleagues, in which selective learning was investigated by presenting fictitious diary entries, such as "Kim was walking her dog" or "the weather was bad today" (CS) and pairing the sentences in terms of the blocking procedure (see above). In the central test phase, in which events were presented without pain report, participants were asked to give their pain expectations for the different situations. Deficits in selective learning were found in fibromyalgia patients compared to healthy control. For the planned study this learning paradigm will be used with minor adaptations (translated to German, minor instruction adaptations, renamed scale ends, higher scale resolution). The learning experiment will take about 15 minutes.
Positive affect and optimism will be induced through the Best Possible Self (BPS) Intervention. Subjects will be randomly assigned to either the optimism condition or a control condition.
The whole study will be conducted online. Participants will be asked to switch from the experimental platform to the questionnaire platform at various times. In order to recreate the laboratory situation and to keep participants engaged, we implemented several videos in which the virtual investigator guides participants throughout the experiment.
The sample size should include 164 participants, assuming a small effect. A priori power analyses were calculated with the software program G*Power for ANOVA with repeated measures, within-between interaction with a small effect (f=0.1, Power 0.8, α=0.05).
Patients with fibromyalgia will be recruited via social media platforms like Facebook and Instagram, but also through advertisement in magazines, self-help groups as well as via flyers in medical offices and clinics.
Mainly ANOVA´s with repeated measures and t-tests are planned to be calculated. There will be four separate repeated measures (RM) ANOVA´s on positive and negative Affect and on positive and negative future expectations with Group (BPS/TD) as between-factor and Time (Pre/Post) as within-subjects factor. Planned contrasts will also be used to check whether the increase in
- positive affect and b) positive future expectations (and not a decrease in a) negative affect and b) negative future expectations) will be larger in the BPS group compared with the TD group.
Further, we will calculate ANOVA´s to test acquisition of pain expectancy in the different phases. The central analysis will be a 2 x 3 RM ANOVA with Group (BPS/TD) as between-subjects variable and Stimulus Type (B/Z/X) as within-subjects variable on pain expectancy ratings in the test phase of the learning experiment. Further, following the literature, the investigators might do responder analyses and use the change in a) positive affect and b) positive future expectations as predictors for selective learning (in order to have more power in statistical analyses, if necessary).
Transformations: Transformations of not normally distributed variables will be done.
Inference criteria: We will use the standard p < .05 criteria.
Data exclusion: Participants will be excluded from analyses, if they give Z>X ratings in the test phase or if they give the same rating throughout the whole experiment. Participants, who did not complete the BPS/TD writing exercise properly will be excluded from ANOVA´s with group factors.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: Best Possible Self Positive affect and optimism will be induced through the Best Possible Self (BPS) Intervention. In the optimism intervention, participants will be asked to imagine a future in which everything went well and in which all their wishes are fulfilled. This procedure is known to reliably generate positive affect and positive future expectations (Carrillo et al., 2019). Orientated at Flink et al. (2015) the BPS condition was adapted for a pain population. |
Behavioral: Best Possible Self
Participants are asked to think about their Best Possible Self for one minute, then describe it for 15 minutes (in writing) and, subsequently, imagine it for another 5 minutes as vividly as possible.
|
| Active Comparator: Typical Day In the control condition, participants are asked to describe and visualize a typical day (TD). We adapted the TD condition in order to take possible changes in participants´ TD due to the COVID-19 pandemic into account. |
Behavioral: Typical Day
Participants are asked to think about their Typical Day for one minute, then describe it for 15 minutes (in writing) and, subsequently, imagine it for another 5 minutes as vividly as possible.
|
Outcome Measures
Primary Outcome Measures
- Positive Affect [post-intervention (immediately after the intervention)]
Positive Affect will be measured with the Positive and Negative Affect Schedule (PANAS; Breyer & Bluemke, 2016). It will be tested if participants of the BPS group score higher in Positive Affect after the intervention than at baseline. Further, we will test if participants in the BPS condition score higher in Positive Affect than participants in the TD group.
- State Optimism/Positive Future Expectancies [post-intervention (immediately after the intervention)]
State Optimism/Positive Future Expectancies will be measured with the future expectancies scale (FEX; Hanssen et al., 2013; Peters, Vieler, & Lautenbacher, 2016). It will be tested if participants of the BPS group score higher in Optimism after the intervention than at baseline. Further, we will test if participants in the BPS condition score higher in Optimism than participants in the TD group.
- Pain expectancy/contingency awareness pre-rating phase [Pain-expectancy will be measured in the pre-rating phase before the intervention]
Numerical Rating Scale (NRS; 0-100; 0 = expect not all, 100 = expect very much) It will be tested to which extent participants expect pain for the different stimuli which are used in the experiment (A, B, X, Z).
- Pain expectancy/contingency awareness elemental acquisition phase [Pain-expectancy will be measured in the practice phase before the intervention]
Numerical Rating Scale (NRS; 0-100; 0 = expect not all, 100 = expect very much) It will be tested to which extent participants expect pain for the stimuli A+ and Z-.
- Pain expectancy/contingency awareness reminder of acquisition phase [post-intervention (immediately after the intervention)]
Numerical Rating Scale (NRS; 0-100; 0 = expect not all, 100 = expect very much) It will be tested to which extent participants expect pain for the stimuli A+ and Z-.
- Pain expectancy/contingency awareness compound acquisition phase [post-intervention (immediately after the intervention)]
Numerical Rating Scale (NRS; 0-100; 0 = expect not all, 100 = expect very much) It will be tested to which extent participants expect pain for the stimuli B+, AX+ and Z-.
- Pain expectancy/contingency awareness test phase [post-intervention (immediately after the intervention)]
Numerical Rating Scale (NRS; 0-100; 0 = expect not all, 100 = expect very much) It will be tested to which extent participants expect pain for X, B, and Z. In case of "blocked", i.e. reduced pain expectation for X in the test phase we can assume adaptive, selective learning.
- Positive Affect [immediately after the blocking procedure]
Positive Affect will be measured with the Positive and Negative Affect Schedule (PANAS; Breyer & Bluemke, 2016). It will be tested if affect is stable from immediate postvisualization to end of the experiment.
- State Optimism/Positive Future Expectancies [immediately after the blocking procedure]
State Optimism/Positive Future Expectancies will be measured with the future expectancies scale (FEX; Hanssen et al., 2013; Peters, Vieler, & Lautenbacher, 2016). It will be tested if state optimism is stable from immediate postvisualization to end of the experiment.
Secondary Outcome Measures
- Trait Optimism [pre-intervention (baseline)]
Trait Optimism will be measured with the revised version of the life-orientation-test (LOT-R; Scheier & Carver 1985).
- chronic pain [immediately after the blocking procedure]
Pain will be measured with the revised graded chronic pain scale (GCPS-R, von Korff et al., 2020).
- Depression [immediately after the blocking procedure]
Depression will be measured with the Patient Health Questionnaire (PHQ-9, Spitzer, Kroenke & Williams, 1999).
- Pain Catastrophizing [immediately after the blocking procedure]
Pain Catastrophizing will be measured with the Pain Catastrophizing Scale (PCS; Sullivan, Bishop, Pivik 1995). Answers are scored on a 5-point rating scale (0 = not at all; 4 = all the time).
- Negative Affect [post-intervention (immediately after the intervention)]
Negative Affect will be measured with the Positive and Negative Affect Schedule (PANAS; Breyer & Bluemke, 2016). It will be tested if participants´ scores in Negative Affect are influenced by the intervention.
- Negative Affect [immediately after the blocking procedure]
Negative Affect will be measured with the Positive and Negative Affect Schedule (PANAS; Breyer & Bluemke, 2016). It will be tested if Negative Affect is stable from immediate postvisualization to end of the experiment.
- Negative Future Expectancies [immediately after the blocking procedure]
Negative Future Expectancies will be measured with the future expectancies scale (FEX; Hanssen et al., 2013; Peters, Vieler, & Lautenbacher, 2016).It will be tested if participants´ score in Negative Future Expectancies are influenced by the intervention.
- Negative Future Expectancies [post-intervention (immediately after the intervention)]
Negative Future Expectancies will be measured with the future expectancies scale (FEX; Hanssen et al., 2013; Peters, Vieler, & Lautenbacher, 2016).It will be tested if participants´ score in Negative Future Expectancies are influenced by the intervention.
Other Outcome Measures
- Pain expectancy/contingency awareness practice phase [Pain-expectancy will be measured in the practice phase before the intervention]
Participants can train to give pain expectancy ratings for the stimuli C+ und D-, which are only used in the practice phase.
- Positive Affect [pre-intervention (baseline)]
Positive Affect will be measured with the Positive and Negative Affect Schedule (PANAS; Breyer & Bluemke, 2016). It will be tested if there are baseline differences between the BPS and TD group. Further, this outcome might be used as covariate.
- State Optimism/Positive Future Expectancies [pre-intervention]
State Optimism/Positive Future Expectancies will be measured with the future expectancies scale (FEX; Hanssen et al., 2013; Peters, Vieler, & Lautenbacher, 2016). It will be tested if there are baseline differences between the BPS and TD group. Further, this outcome might be used as a covariate.
- Negative Future Expectancies [pre-intervention (baseline)]
Negative Future Expectancies will be measured with the future expectancies scale (FEX; Hanssen et al., 2013; Peters, Vieler, & Lautenbacher, 2016).It will be tested if participants´ score in Negative Future Expectancies are influenced by the intervention.
- Negative Affect [pre-intervention]
Negative Affect will be measured with the Positive and Negative Affect Schedule (PANAS; Breyer & Bluemke, 2016). It will be tested if there are baseline differences between the BPS and TD group.
Eligibility Criteria
Criteria
Inclusion Criteria:
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self-reported fibromyalgia diagnosis
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access to a computer or laptop with audio output
Exclusion Criteria:
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dyslexia
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other impairments that affect cognitive performance (e.g. stroke or brain damages)
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Philipps University Marburg Medical Center | Marburg | Germany |
Sponsors and Collaborators
- Philipps University Marburg Medical Center
Investigators
- Principal Investigator: Winfried Rief, Professor, Philipps University Marburg Medical Center
Study Documents (Full-Text)
None provided.More Information
Publications
- Boselie JJ, Vancleef LM, Peters ML. Increasing Optimism Protects Against Pain-Induced Impairment in Task-Shifting Performance. J Pain. 2017 Apr;18(4):446-455. doi: 10.1016/j.jpain.2016.12.007. Epub 2016 Dec 27.
- Boselie JJLM, Vancleef LMG, Smeets T, Peters ML. Increasing optimism abolishes pain-induced impairments in executive task performance. Pain. 2014 Feb;155(2):334-340. doi: 10.1016/j.pain.2013.10.014. Epub 2013 Oct 19.
- Flink IK, Reme S, Jacobsen HB, Glombiewski J, Vlaeyen JWS, Nicholas MK, Main CJ, Peters M, Williams ACC, Schrooten MGS, Shaw W, Boersma K. Pain psychology in the 21st century: lessons learned and moving forward. Scand J Pain. 2020 Apr 28;20(2):229-238. doi: 10.1515/sjpain-2019-0180. Review.
- Flink IK, Smeets E, Bergboma S, Peters ML. Happy despite pain: Pilot study of a positive psychology intervention for patients with chronic pain. Scand J Pain. 2015 Apr 1;7(1):71-79. doi: 10.1016/j.sjpain.2015.01.005.
- Geschwind N, Meulders M, Peters ML, Vlaeyen JW, Meulders A. Can experimentally induced positive affect attenuate generalization of fear of movement-related pain? J Pain. 2015 Mar;16(3):258-69. doi: 10.1016/j.jpain.2014.12.003. Epub 2014 Dec 20.
- Harvie DS, Weermeijer JD, Olthof NA, Meulders A. Learning to predict pain: differences in people with persistent neck pain and pain-free controls. PeerJ. 2020 Jun 23;8:e9345. doi: 10.7717/peerj.9345. eCollection 2020.
- Meevissen YM, Peters ML, Alberts HJ. Become more optimistic by imagining a best possible self: effects of a two week intervention. J Behav Ther Exp Psychiatry. 2011 Sep;42(3):371-8. doi: 10.1016/j.jbtep.2011.02.012. Epub 2011 Mar 2.
- Meulders A, Boddez Y, Blanco F, Van Den Houte M, Vlaeyen JWS. Reduced selective learning in patients with fibromyalgia vs healthy controls. Pain. 2018 Jul;159(7):1268-1276. doi: 10.1097/j.pain.0000000000001207.
- Meulders A, Harvie DS, Bowering JK, Caragianis S, Vlaeyen JW, Moseley GL. Contingency learning deficits and generalization in chronic unilateral hand pain patients. J Pain. 2014 Oct;15(10):1046-56. doi: 10.1016/j.jpain.2014.07.005. Epub 2014 Jul 25.
- Meulders A, Meulders M, Vlaeyen JW. Positive affect protects against deficient safety learning during extinction of fear of movement-related pain in healthy individuals scoring relatively high on trait anxiety. J Pain. 2014 Jun;15(6):632-44. doi: 10.1016/j.jpain.2014.02.009. Epub 2014 Mar 17.
- Meulders A. Fear in the context of pain: Lessons learned from 100 years of fear conditioning research. Behav Res Ther. 2020 Aug;131:103635. doi: 10.1016/j.brat.2020.103635. Epub 2020 Apr 30. Review.
- Vlaeyen JWS, Linton SJ. Fear-avoidance and its consequences in chronic musculoskeletal pain: a state of the art. Pain. 2000 Apr;85(3):317-332. doi: 10.1016/S0304-3959(99)00242-0. Review.
- Vlaeyen JWS, Linton SJ. Fear-avoidance model of chronic musculoskeletal pain: 12 years on. Pain. 2012 Jun;153(6):1144-1147. doi: 10.1016/j.pain.2011.12.009. Epub 2012 Feb 8.
- Zbozinek TD, Craske MG. The Role of Positive Affect in Enhancing Extinction Learning and Exposure Therapy for Anxiety Disorders. Journal of Experimental Psychopathology. April 2017:13-39. doi:10.5127/jep.052615
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