Cold Hands, Warm Heart: Quality of Life, Wellbeing, and Mental Health in Raynaud’s Disease – An International Survey Study

Cold Hands, Warm Heart: Quality of Life, Wellbeing, and Mental Health in Raynaud’s Disease – An International Survey Study | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Cold Hands, Warm Heart: Quality of Life, Wellbeing, and Mental Health in Raynaud’s Disease – An International Survey Study View ORCID Profile Eleftheria Vaportzis doi: https://doi.org/10.1101/2025.06.06.25329136 Eleftheria Vaportzis 1 Department of Psychology, University of Bradford , Bradford, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Eleftheria Vaportzis For correspondence: E.Vaportzis{at}bradford.ac.uk Abstract Full Text Info/History Metrics Preview PDF Abstract Objectives The study assessed the quality of life, wellbeing, and mental health of people living with Raynaud’s disease (RD). It employed an RD-specific measure for quality of life, used a large international sample, and included meteorological variables in the analyses. It also compared outcomes between primary and secondary RD and people without an RD diagnosis. Methods A cross-sectional design was used. Participants (n = 720) completed a demographics questionnaire, The Raynaud-Specific Quality of Life Questionnaire (RQLQ), WHO-5 Wellbeing Index and DASS-21. Meteorological variables were recorded based on the participants’ location. Results Participants with secondary RD reported lower quality of life and wellbeing, and higher anxiety, depression, and pain, than participants with primary RD or without a diagnosis. Participants without a diagnosis reported worse mental health than groups with a diagnosis. Participants in tropical climates reported the lowest quality of life, and those in temperate climates had the lowest wellbeing. Pain and symptom severity were the strongest predictors of quality of life (accounting for 30% of the variance), while meteorological variables accounted for up to 2% of the variance. Conclusion RD negatively affects quality of life, wellbeing, and mental health, particularly for people living with secondary RD. Pain and symptom severity are key determinants. Meteorological factors contribute minimally. Tailored interventions focusing on symptoms management should be prioritised. Meteorological influences should be considered in healthcare planning alongside clinical and psychosocial factors. Pain and symptom severity strongly predict quality of life in Raynaud’s disease Individuals without a diagnosis report worse mental health than individuals with a diagnosis Warmer climates do not necessarily protect against reduced qualify of life in Raynaud’s disease Introduction Raynaud’s disease (RD) is a disorder of the peripheral vascular system characterised by episodes of pain, numbness, and colour changes in the extremities due to cold or stress. RD can be primary (pRD) or secondary (sRD) to an underlying condition such as scleroderma ( 1 ). The prevalence of pRD in the general population is around 5%, and although it varies by country ( 2 ), it carries a significant burden. It is estimated that pRD accounts for 80-90% of RD cases, and sRD accounts for 10-20% ( 3 ). Although some studies found the prevalence of RD to be higher in colder climates ( 4 ), other studies reported conflicting evidence ( 5 , 6 ). The impact of RD on quality of life depends on several factors, including the frequency, duration, and severity of episodes, as well as the presence of comorbidities ( 7 ). sRD is progressive and can lead to irreversible damage ( 8 ). While pRD is considered benign, the pain, functional disability, and unpredictability of episodes ( 9 ) lead individuals to make lifestyle changes ( 7 ). Available treatments require daily routine modifications, are often ineffective, have side effects ( 10 ), and negatively impact individuals’ quality of life and mental health ( 11 ). Research investigating the impact of RD on quality of life is limited and has not always employed appropriate measures. Past research measured health-related quality of life using 36-Item Short Form Health Survey (SF-36; 12, 13), the anxiety/depression dimension of EQ-5D ( 14 ), and measures of wellbeing (i.e., ONS4-Life Satisfaction; 15, 16). In the absence of RD-specific quality of life measures, Fábián et al. ( 17 ) developed and validated the Raynaud Specific Quality of Life Questionnaire (RQLQ). Using RQLQ, Fábián et al. ( 11 ) reported that people with sRD had significantly lower quality of life than those with primary RD. People with RD report higher levels of stress ( 15 ), anxiety ( 15 , 16 ), and depression ( 11 , 15 , 16 , 18 ) compared with the general population. Some studies found those with sRD being more severely affected than those with pRD ( 11 , 16 ), while others found no differences between the two types ( 15 ). Variations in findings may be explained by the different measures employed by these studies. A study with people with pRD reported that stress was not a significant predictor of RD episodes; however, they found a relationship between higher anxiety and a higher frequency of episodes at temperatures over 15.5° C ( 19 ). Surprisingly, this was the only study that investigated the role of temperature on psychological outcomes. Previous studies reported mixed outcomes between cold temperatures and RD. Maricq et al. ( 20 ) found that RD episodes were more likely to occur in colder climates. However, Pauling et al. ( 6 ) compared people with sRD in India and North America and reported that the difficulties they experienced in winter were not significantly different, despite the temperature difference between the two regions being more than 20°C. Additionally, a New Zealand study found that RD was more prevalent in the warmer region of the country ( 5 ). The relationship between temperature and RD remains underexplored and warrants further investigation. The revised Wilson and Cleary model provides a theoretical model to understand better health-related quality of life in people living with chronic disease ( 21 ). According to this model, there are four main determinants of overall quality of life including biological function (e.g., abnormal vasoconstriction), symptoms (e.g., pain), functional status (e.g., ability to hold small objects), and general health perceptions (e.g., perception of RD severity). Characteristics of the individual (e.g., age, gender) and their environment (e.g., average temperatures) influence all determinants and quality of life. The current study was guided by the revised Wilson and Cleary model and aimed to conduct a survey-based assessment of quality of life, wellbeing, and mental health in people living with RD. The study addressed gaps in the literature by employing an RD-specific measure for quality of life, using a large international sample, and including meteorological variables in the analyses. Methods Recruitment A cross-sectional survey was designed, following guidelines by Kelley et al. ( 22 ). Eligibility criteria included having a diagnosis or suspecting they have RD, being over 18 years old, and being fluent in English. The survey was distributed in hard copy and online via JISC between March and April 2025. Data collection continued until two consecutive days passed without any new completions. Participants were recruited through social media and relevant charities and organisations. Ethics approval was granted by the Humanities, Social, and Health Sciences Research Ethics Panel at the University of Bradford (E1301). Survey design Demographics Demographic questions include participants’ age, gender, ethnicity, employment, smoking habits, and location. Based on participants’ location, the following meteorological variables were recorded: average temperature and temperature variation on the day the survey was completed and the preceding four weeks, along with precipitation, humidity, dew point, wind, and air pressure for the same four-week period. The Universal Thermal Scale was used to classify participants’ locations from coldest to warmest based on the average temperatures in the preceding four weeks ( 23 ). Participants’ climate regions were classified using the Köppen–Geiger climate classification ( 23 ). The wind chill was calculated using the following formula ( 24 ): Where: T = temperature in °C V = wind speed in mph Raynaud’s diagnosis Participants were asked if they had been diagnosed with RD, and if yes, whether they had pRD or sRD. If participants had no diagnosis, they completed Raynaud’s quiz ( 25 ) (e.g., ‘Are your fingers or toes often cold, even indoors on a warm day and air conditioning?’) Participants provided Yes/No answers. At least one Yes suggests that the person may have RD. Total scores can range between 0 and 5. Raynaud’s severity Following previous studies ( 17 , 19 ), pain severity was assessed using three questions from SF-36. These items were modified for RD. Participants were asked to report the following questions for the past 4 weeks: ‘How often did you experience pain as a result of your Raynaud’s?’ (1 = Never – 4 = Often); ‘How intense was the pain that you experienced as a result of your Raynaud’s?’ (1 = No pain – 4 = Severe pain); and ‘How much did pain as a result of your Raynaud’s interfere with your normal work (Including both outside the home and housework)?’ (1 = Not at all – 5 = Extremely). The final raw scores (ranging from 3 to 13) were rescaled to range from 5 to 100 according to the SF-36 Manual. Higher scores indicate a higher degree of pain. Symptom severity was assessed with the question ‘How do you perceive the severity of your Raynaud’s?’. The question is rated on a 5-point Likert scale (1 = Not serious at all – 5 = Serious). Higher scores indicate higher symptom severity. The Raynaud-Specific Quality of Life Questionnaire (RQLQ; 17) RQLQ is a validated measure that assesses the impact of RD on quality of life. Participants are presented with 29 statements rated on a 5-point Likert scale (1 = Strongly agree – 5 = Strongly disagree). Scores are calculated for 5 subscales: ( 1 ) Impaired Hand Function (e.g., ‘My illness limits my grip strength’); ( 2 ) Social Interaction (e.g., ‘I have to conceal the body parts affected by my illness’); ( 3 ) Emotional Burden (e.g., ‘I am concerned that my condition will worsen)); ( 4 ) Control (e.g., ‘I wear thicker clothes); and ( 5 ) Sleep (e.g., During the night, I wake up due to numbness). Total scores can range between 29 and 145 with higher scores indicating better quality of life. Cronbach’s α for the overall scale in the current study was excellent (.94). WHOIZI5 WellIZIBeing Index (WHO-5; 26) WHO-5 is a validated measure of subjective mental wellbeing. Participants are asked five positively worded statements relating to the past two weeks (e.g., I have felt cheerful and in good spirits). Each statement is rated on a 6-point Likert scale (0 = At no time – 5 = All of the time). Total scores can range between 0 and 30 with higher scores indicating better mental wellbeing. Cronbach’s α in the current study was excellent (.90). The Depression, Anxiety, and Stress Scale – 21 items (DASS-21; 27) DASS-21 is a validated measure that assesses feelings of depression, anxiety, and stress. It comprises three 7-item scales. Participants are asked to indicate whether each statement has applied to them during the last week. Responses are given using a 4-point Likert-type scale (0lll=lllDoes not apply to me at all – 3lll=lllApplies to me a lot/most of the time). Scores are summed and multiplied by two. The total score for each scale ranges between 0 and 42. Higher scores indicate a higher level of the respective construct. The total DASS-21 score is the sum of the three scales and can range between 0 and 126 with higher scores indicating a higher level of general psychological distress. Cronbach’s α in the current study was excellent for the overall scale (.94) and Depression (.92), and good for Anxiety (.80) and Stress (.88). Data analysis Statistical analyses were performed in SPSS v. 28 ( 28 ). Alpha was set at .05. Potential outliers were identified using pre-determined Z-score cut-offs (± 3.29; 29). Statistically significant outliers were identified on the RQLQ domains Emotional Burden (n = 3) and Control (n = 7), and DASS Anxiety scale (n = 4). Despite the high values, the scores were plausible and did not influence analyses. Differences in continuous variables among the three groups were analysed using one-way ANOVA with Bonferroni correction, while Chi-square tests for independence were used to evaluate differences in categorical variables. Likelihood ratios were reported due to violations of Chi-square assumptions. Post-analysis was performed using adjusted standardised residuals. Multivariate Analysis of Variance (MANOVA) was conducted to examine group differences in quality of life, wellbeing, stress, anxiety, and depression based on diagnosis type and climate classification. Post-hoc analyses were performed using one-way ANOVAs with Bonferroni correction. Welch’s MANOVA was reported where appropriate due to the violation of homogeneity of variance as indicated by Levene’s test. Post-hoc analyses were performed using Welch’s ANOVAs followed by Games-Howell tests. Bootstrapped MANOVAs (2,000 samples, 95% CI) were calculated to account for the non-normal distribution of scores. The assumption of homogeneity of variance-covariance matrices was assessed using Box’s M test. Bivariate correlations assessed the relationship between quality of life, wellbeing, stress, anxiety, depression, pain and symptom severity, and meteorological variables. Spearman’s correlations were used due to violations of the assumption of normality. Hierarchical multiple regressions were conducted separately on quality of life and wellbeing to assess the variance accounted for by type of diagnosis, pain and symptom severity, mental health, and meteorological variables. Assumptions of linearity, normality, and homoscedasticity were assessed through visual inspection of scatterplots. Models were checked for outliers (standardised residuals ± 3, Cook’s distance > 1) and multi-collinearity (tolerance 10). Bootstrapped regression analyses were run due to violations of normality. A priori power analysis using G*Power ( 30 ) with α = .05 suggested that the sample had enough power (0.80) to detect a small effect (f = 0.02) as 628 participants were required. Results A total of 721 participants completed the survey. One participant was removed (Raynaud’s quiz score was 0), leaving 720 participants in the analyses. The sample included 340 individuals with pRD, 274 individuals with sRD, and 106 individuals without a diagnosis. The three groups significantly differed on age, F( 2 ,712) = 9.32, p < .001, η = .05, country, χ²( 16 ) = 47.11, p < .001, Cramér’s V < .001, and employment, χ²( 4 ) = 30.48, p < .001, Cramér’s V .05; see Table 1 ). View this table: View inline View popup Table 1. Descriptive information by group A Chi-square test revealed a significant association between type of diagnosis and symptom severity, χ²( 8 ) = 44.11, p = .001, Cramér’s V < .001. Examination of adjusted standardized residuals indicated that participants with sRD were underrepresented in the ‘Not serious at all’ (z = – 3.70, p < .001) and ‘Mildly serious’ categories (z = – 2.10, p < .05), and overrepresented in the ‘Quite serious’ category (z = 2.9, p < .01). Participants without a diagnosis were overrepresented in the ‘Not serious at all’ category (z = 5.2, p < .001) and underrepresented in the ‘Serious category’ (z = –2.1, p < .05). Welch’s ANOVA showed significant group differences in pain severity, F( 2 ,290) = 7.90, p < .001, η² = .04. Games-Howell post-hoc comparison tests indicated that participants with pRD (p = .01) and sRD (p < .001) experienced a higher degree of pain compared to participants without a diagnosis. In comparison with normative data ( 31 ), the sample had significantly higher scores on stress, t(719) = 13.41, p < .001, anxiety, t(719) = 20.74, p < .001, and depression, t(719) = 13.47, p < .001. A one-way MANOVA revealed a significant multivariate effect of type of diagnosis on quality of life, wellbeing, stress, anxiety, and depression, F( 10 , 1428) = 8.06, bootstrapped, p < .001, η² = .05. Follow-up Welch’s ANOVA showed significant group differences on quality of life, F( 2 ,717) = 27.15, bootstrapped p < .001, η² = .11, and anxiety, F( 2 ,717) = 4.18, bootstrapped p = .025, η² = .05. Univariate ANOVAs showed significant group differences on wellbeing, F( 2 ,717) = 11.91, bootstrapped p < .001, η² = .03, stress, F( 2 ,717) = 3.45, bootstrapped p =.03, η² = .01, and depression, F( 2 ,717) = 6.85, bootstrapped p < .001, η² = .03 (see Table 2 ). View this table: View inline View popup Table 2. Between-groups comparisons on dependent variables Post-hoc tests showed that participants with sRD had significantly lower scores than those with pRD and without a diagnosis on quality of life (both p < .001), and wellbeing (p < .001, p = .01, respectively). Participants with primary RD had significantly lower scores than those without a diagnosis on quality of life (p = .04). Participants without a diagnosis had significantly higher stress (p = 0.3) and anxiety scores (p = .01) than those with pRD, and higher depression scores than those with pRD and sRD (both p = .01). A one-way MANOVA revealed a significant multivariate effect of climate on quality of life and wellbeing, F( 15 , 2100) = .046, bootstrapped p = .01 partial η² = .02. Follow-up univariate ANOVAs showed significant group differences on quality of life, F( 3 ,702) = 4.08, bootstrapped p = .01, η² = .017, and wellbeing, F( 3 ,702) = 3.52, bootstrapped p = .02, η² = .02. Post-hoc tests showed that participants living in tropical climates had significantly lower quality of life than those living in temperate (p = .02) and continental climates (p = .04). Additionally, participants in temperate climates had significantly lower wellbeing than those living in continental climates (p = .01). Bivariate correlations showed that quality of life, wellbeing, pain, and symptom severity were all significantly correlated in the expected directions ( Table 3 ). Strong correlations were found between quality of life and pain (-.551, p < .001), and symptom severity and pain (.672, p < .001). There were also strong correlations between stress and anxiety (.673, p < .001), stress and depression (.715, p < .001), and anxiety and depression (.648, p < .001; see Table 3 ). View this table: View inline View popup Table 3. Spearman’s correlations between variables In Step 1, the type of diagnosis explained 7% of the variance in quality of life, R = .07, F( 1 ,659) = 50.78, p < .001. After entry in Step 2, pain and symptom severity explained an additional 30% of the variance, R² change = .30, F change ( 2 , 657) = 154.13, p < .001. In Step 3, wellbeing explained an additional 5% of the variance, R² change = .05, F change ( 1 , 656) = 50.28, p < .001. In Step 4, mental health variables did not account for a significant increase in the explained variance, R² change = .001, F change ( 3 , 656) = .20, p = .89. In Step 5, meteorological variables explained an additional 1% of the variance, R² change = .01, F change ( 7 , 646) = 2.16, p = .04. The total variance explained by the model was 42%, R = .42, F( 7 ,646) = 2.16, p = .04 (see Table 4 ). View this table: View inline View popup Download powerpoint Table 4. Hierarchical regression analysis for quality of life In Step 1, the type of diagnosis explained 3% of the variance in wellbeing, R 2 = .03, F( 1 ,659) = 17.39, p < .001. After entry in Step 2, pain and symptom severity explained an additional 8% of the variance, R² change = .08, F change ( 2 , 657) = 29.01, p < .001. In Step 3, quality of life explained an additional 6% of the variance, R² change = .06, F change ( 1 , 656) = 50.28, p < .001. In Step 4, mental health variables did not account for a significant increase in the explained variance, R² change = .004, F change ( 3 , 656) = .10, p = .39. In Step 5, meteorological variables explained an additional 2% of the variance, R² change = .02, F change ( 7 , 646) = 2.15, p = .04. The total variance explained by the model was 17%, R = .17, F( 7 ,646) = 2.16, p = .04 (see Table 5 ). View this table: View inline View popup Download powerpoint Table 5. Hierarchical regression analysis for wellbeing Discussion This study assessed quality of life, wellbeing, and mental health in RD using a large, international sample. It addressed an important gap in the literature by adding various meteorological variables in the analyses and using an RD-specific measure for quality of life. It is the first study to include people without an RD diagnosis. Despite the relatively high prevalence of RD, it is frequently underdiagnosed due to a lack of diagnostic tools, lack of awareness, or symptom misinterpretation ( 32 , 33 ). The findings are consistent with a body of research showing that mental health is worse in people with RD compared with the general population ( 31 ). In line with past research participants with sRD reported lower quality of life and wellbeing ( 11 , 15 ), higher anxiety and depression ( 11 , 16 ), and greater pain and symptom severity than those with pRD or without a diagnosis ( 11 , 16 ). A cross-sectional survey study found that people with systemic and rheumatologic diseases were amongst those reporting the poorest quality of life ( 34 ). Interestingly, participants without a diagnosis reported lower mental health than the other groups. One possible explanation is that the lack of diagnosis contributes to poor mental health. Mund et al. ( 35 ) found high rates of mental disorders in individuals seeking diagnosis for unexplained symptoms possibly due to uncertainty and associated frustration. Clinicians should prioritise early screening, diagnosis, and tailored support for people living with systemic and rheumatologic diseases. Participants living in tropical climates reported the lowest quality of life, while those living in temperate climates reported the lowest wellbeing. These findings challenge the notion that people living in colder climates experience RD more severely. People living in warmer climates may experience more rapid temperature changes due to air conditioning. Similarly, those living in temperate climates often experience extreme weather changes or conditions, making planning and prevention difficult ( 36 ). The impact of climate on RD may be more complex than a cold/hot dichotomy. Individual (e.g., adaptive and coping strategies) and societal factors (e.g., healthcare access, infrastructure) should be considered. Pain and symptom severity accounted for 30% of the variance in quality of life supporting the revised Wilson Cleary model, according to which symptoms and general health perceptions are determinants of overall quality of life. The strong correlation between pain and symptom severity highlights their role in influencing patients’ experiences. Mental health variables did not significantly account for an additional variance in either quality of life or wellbeing. Measures of quality of life or wellbeing may capture mental health indirectly ( 37 ) or there is an overlap between physical symptoms and mental health symptoms ( 38 ). Meteorological variables accounted for up to 2% of the variance in quality of life and wellbeing, suggesting that although they are important, physical variables are more important. Interventions targeting pain and symptoms management should be prioritised to improve the quality of life and wellbeing of people living with RD. Pain and symptom relief may also benefit mental health. While meteorological variables matter, they should complement rather than replace other assessments. Limitations and future research The study’s cross-sectional design does not allow us to infer how the relationships between the variables may differ over time. Self-reported data introduce biases including subjective interpretation of symptoms. Although including participants without a diagnosis is important given the underdiagnosis of RD, it is possible that some of those included did not have RD. Recruitment through social media and charities may have attracted those who are more symptomatic or more engaged in RD campaigns reducing the generalisability of findings. Several other variables may have affected the outcomes and should be included in future studies (e.g., healthcare access, coping strategies). Future studies should also consider longitudinal designs to establish the directionality of influences and include clinical samples. Conclusion This study showed that diagnosis type, pain, and symptom severity significantly affect quality of life, wellbeing, and mental health, while meteorological variables play a smaller role. Individuals with sRD experience the greatest burden including greater pain, and poorer quality of life and mental health. Tailored interventions targeting pain and symptom severity, are critical for improving patients’ quality of life and wellbeing. Climate influences should be considered alongside clinical and psychosocial factors in healthcare planning. Funding No specific funding was received from any bodies in the public, commercial, or not-for-profit sectors to carry out the work described in this article. Conflict of interest statement The author declares no conflict of interest. Data Availability Statement The data underlying this article will be shared on reasonable request to the corresponding author. References 1. ↵ Hughes M , Herrick AL . Raynaud’s phenomenon . Best Practice & Research Clinical Rheumatology . 2016 ; 30 ( 1 ): 112 – 32 . OpenUrl PubMed 2. ↵ Garner R , Kumari R , Lanyon P , Doherty M , Zhang W . Prevalence, risk factors and associations of primary Raynaud’s phenomenon: systematic review and meta-analysis of observational studies . BMJ Open . 2015 ; 5 ( 3 ): e006389 . OpenUrl Abstract / FREE Full Text 3. ↵ National Institute for Health and Care Excellence . Raynaud’s phenomenon . 2024 . 4. ↵ Plissonneau DP , Pistorius MA , Pottier P , Aymard B , Planchon B . Cold climate could be an etiologic factor involved in Raynaud’s phenomenon physiopathology. Epidemiological investigation from 954 consultations in general practice . Int Angiol . 2015 ; 34 ( 5 ): 467 – 74 . OpenUrl PubMed 5. ↵ Purdie G , Harrison A , Purdie D . Prevalence of Raynaud’s phenomenon in the adult New Zealand population . The New Zealand Medical Journal (Online ). 2009 ; 122 ( 1306 ). 6. ↵ Pauling JD , Nagaraja V , Khanna D . Insight into the contrasting findings of therapeutic trials of digital ischaemic manifestations of systemic sclerosis . Current Treatment Options in Rheumatology . 2019 ; 5 : 85 – 103 . OpenUrl 7. ↵ Merkel PA , Herlyn K , Martin RW , Anderson JJ , Mayes MD , Bell P , et al. Measuring disease activity and functional status in patients with scleroderma and Raynaud’s phenomenon . Arthritis Rheum . 2002 ; 46 ( 9 ): 2410 – 20 . OpenUrl CrossRef PubMed Web of Science 8. ↵ Curtiss P , Svigos K , Schwager Z , Sicco KL , Franks Jr AG . Part II: the treatment of primary and secondary Raynaud’s phenomenon . J Am Acad Dermatol . 2024 ; 90 ( 2 ): 237 – 48 . OpenUrl PubMed 9. ↵ Hughes M , Snapir A , Wilkinson J , Snapir D , Wigley FM , Herrick AL . Prediction and impact of attacks of Raynaud’s phenomenon, as judged by patient perception . Rheumatology . 2015 ; 54 ( 8 ): 1443 – 7 . OpenUrl CrossRef PubMed 10. ↵ Ture HY , Lee NY , Kim NR , Nam EJ . Raynaud’s phenomenon: a current update on pathogenesis, diagnostic workup, and treatment . Vascular Specialist International . 2024 ; 40 : 26 . 11. ↵ Fábián B , Fábián AK , Bugán A , Csiki Z . Comparison of mental and physical health between patients with primary and secondary Raynaud’s phenomenon Category . J Psychosom Res . 2019 ; 116 : 6 – 9 . OpenUrl PubMed 12. Molnár I , Szőke H , Hegyi G . Effects of neural therapy on quality of life in patients suffering from Raynaud syndrome . European Journal of Integrative Medicine . 2018 ; 18 : 59 – 65 . OpenUrl 13. Milio G , Corrado E , Genova C , Amato C , Raimondi F , Almasio PL , et al. Iloprost treatment in patients with Raynaud’s phenomenon secondary to systemic sclerosis and the quality of life: a new therapeutic protocol . Rheumatology . 2006 ; 45 ( 8 ): 999 – 1004 . OpenUrl CrossRef PubMed Web of Science 14. ↵ de Andrade LP , Gobbi LTB , Coelho FGM , Christofoletti G , Riani Costa JL , Stella F . Benefits of Multimodal Exercise Intervention for Postural Control and Frontal Cognitive Functions in Individuals with Alzheimer’s Disease: A Controlled Trial . J Am Geriatr Soc . 2013 ; 61 ( 11 ): 1919 – 26 . OpenUrl CrossRef PubMed 15. ↵ Irving D , Daniels J . Psychological factors in symptom severity and quality of life in Raynaud’s phenomenon . Behavioural and Cognitive Psychotherapy . 2024 ; 52 ( 4 ): 426 – 39 . OpenUrl 16. ↵ Broughton J , Irving D , Daniels J . The common sense model in Raynaud’s phenomenon: do illness perceptions account for variance in symptom severity and quality of life? The Cognitive Behaviour Therapist . 2024 ; 17 : e24 . OpenUrl 17. ↵ Fábián B , Csiki Z , Bugán A . Development and validation of the RQLQ: a Raynaud’s disease–specific measure of health-related quality of life . Clin Rheumatol . 2024 ; 43 ( 12 ): 3963 – 72 . OpenUrl PubMed 18. ↵ Chen GF , Shaw KS , Xu S , Hashemi KB , Castillo RL , Vleugels R , et al. Depression in patients with Raynaud’s phenomenon: A case-control study in the National Institutes of Health’s All of Us Research Program . J Am Acad Dermatol . 2024 ; 90 ( 4 ): 857 – 9 . OpenUrl PubMed 19. ↵ Brown KM , Middaugh SJ , Haythornthwaite JA , Bielory L . The effects of stress, anxiety, and outdoor temperature on the frequency and severity of Raynaud’s attacks: the Raynaud’s Treatment Study . J Behav Med . 2001 ; 24 : 137 – 53 . OpenUrl CrossRef PubMed 20. ↵ Maricq HR , Carpentier PH , Weinrich MC , Keil JE , Palesch Y , Biro C , et al. Geographic variation in the prevalence of Raynaud’s phenomenon: a 5 region comparison . The Journal of Rheumatology . 1997 ; 24 ( 5 ): 879 – 89 . OpenUrl PubMed Web of Science 21. ↵ Ferrans CE , Zerwic JJ , Wilbur JE , Larson JL . Conceptual model of health-related quality of life . Journal of Nursing Scholarship . 2005 ; 37 ( 4 ): 336 – 42 . OpenUrl CrossRef PubMed Web of Science 22. ↵ Kelley K , Clark B , Brown V , Sitzia J . Good practice in the conduct and reporting of survey research . Int J Qual Health Care . 2003 ; 15 ( 3 ): 261 – 6 . OpenUrl CrossRef PubMed Web of Science 23. ↵ Peel MC , Finlayson BL , McMahon TA . Updated world map of the Köppen-Geiger climate classification . Hydrology and earth system sciences . 2007 ; 11 ( 5 ): 1633 – 44 . OpenUrl CrossRef Web of Science 24. ↵ Osczevski R , Bluestein M . The new wind chill equivalent temperature chart . Bulletin of the American Meteorological Society . 2005 ; 86 ( 10 ): 1453 – 8 . OpenUrl 25. ↵ Raynaud’s Association . Take the Raynaud’s Quiz . 2019 . https://www.raynauds.org/take-the-raynauds-quiz/ 26. Bech P , Olsen LR , Kjoller M , Rasmussen NK . Measuring well-being rather than the absence of distress symptoms: a comparison of the SF-36 Mental Health subscale and the WHO-Five well-being scale . International journal of methods in psychiatric research . 2003 ; 12 ( 2 ): 85 – 91 . OpenUrl CrossRef PubMed Web of Science 27. Lovibond PF , Lovibond SH . Depression anxiety and stress scales . Behav Res Ther . 1995 . 28. ↵ IBM . IBM SPSS Statistics for Windows (Version 28) . IBM Corp . 2021 . 29. Tabachnick BG , Fidell LS . Using Multivariate Statistics : Harlow, UK : Pearson Education UK .; 2013 . 30. ↵ Faul F , Erdfelder E , Buchner A , Lang A-G . Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses . Behavior research methods . 2009 ; 41 ( 4 ): 1149 – 60 . OpenUrl CrossRef PubMed Web of Science 31. ↵ Crawford JR , Henry JD . The Depression Anxiety Stress Scales (DASS): Normative data and latent structure in a large non-clinical sample . Br J Clin Psychol . 2003 ; 42 ( 2 ): 111 – 31 . OpenUrl CrossRef PubMed Web of Science 32. ↵ UK SRs . New SRUK research reveals millions of UK adults are ‘woefully unaware’ of Raynaud’s . 2025 . 33. ↵ Temprano KK . A Review of Raynaud’s Disease . Mo Med . 2016 ; 113 ( 2 ): 123 – 6 . OpenUrl PubMed 34. ↵ Bogart KR , Irvin VL . Health-related quality of life among adults with diverse rare disorders . Orphanet J Rare Dis . 2017 ; 12 : 1 – 9 . OpenUrl CrossRef PubMed 35. ↵ Mund M , Uhlenbusch N , Rillig F , Weiler-Normann C , Herget T , Kubisch C , et al. Psychological distress of adult patients consulting a center for rare and undiagnosed diseases: a cross-sectional study . Orphanet J Rare Dis . 2023 ; 18 ( 1 ): 82 . OpenUrl PubMed 36. ↵ Legg S. IPCC , 2021: Climate change 2021-the physical science basis . Interaction . 2021 ; 49 ( 4 ): 44 – 5 . OpenUrl 37. ↵ Topp CW , Østergaard SD , Søndergaard S , Bech P . The WHO-5 Well-Being Index: a systematic review of the literature . Psychother Psychosom . 2015 ; 84 ( 3 ): 167 – 76 . OpenUrl CrossRef PubMed 38. ↵ Hanna MR , Caspi A , Houts RM , Moffitt TE , Torvik FA . Co-occurrence between mental disorders and physical diseases: a study of nationwide primary-care medical records . Psychol Med . 2024 ; 54 ( 15 ): 4274 – 86 . OpenUrl View the discussion thread. Back to top Previous Next Posted June 06, 2025. Download PDF Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Cold Hands, Warm Heart: Quality of Life, Wellbeing, and Mental Health in Raynaud’s Disease – An International Survey Study Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Cold Hands, Warm Heart: Quality of Life, Wellbeing, and Mental Health in Raynaud’s Disease – An International Survey Study Eleftheria Vaportzis medRxiv 2025.06.06.25329136; doi: https://doi.org/10.1101/2025.06.06.25329136 Share This Article: Copy Citation Tools Cold Hands, Warm Heart: Quality of Life, Wellbeing, and Mental Health in Raynaud’s Disease – An International Survey Study Eleftheria Vaportzis medRxiv 2025.06.06.25329136; doi: https://doi.org/10.1101/2025.06.06.25329136 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Rheumatology Subject Areas All Articles Addiction Medicine (568) Allergy and Immunology (863) Anesthesia (300) Cardiovascular Medicine (4435) Dentistry and Oral Medicine (444) Dermatology (382) Emergency Medicine (608) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1509) Epidemiology (15229) Forensic Medicine (30) Gastroenterology (1124) Genetic and Genomic Medicine (6600) Geriatric Medicine (668) Health Economics (997) Health Informatics (4538) Health Policy (1368) Health Systems and Quality Improvement (1613) Hematology (541) HIV/AIDS (1264) Infectious Diseases (except HIV/AIDS) (15916) Intensive Care and Critical Care Medicine (1103) Medical Education (623) Medical Ethics (146) Nephrology (667) Neurology (6599) Nursing (346) Nutrition (998) Obstetrics and Gynecology (1144) Occupational and Environmental Health (957) Oncology (3333) Ophthalmology (974) Orthopedics (369) Otolaryngology (420) Pain Medicine (436) Palliative Medicine (130) Pathology (663) Pediatrics (1693) Pharmacology and Therapeutics (691) Primary Care Research (711) Psychiatry and Clinical Psychology (5447) Public and Global Health (9232) Radiology and Imaging (2198) Rehabilitation Medicine and Physical Therapy (1370) Respiratory Medicine (1196) Rheumatology (593) Sexual and Reproductive Health (712) Sports Medicine (530) Surgery (712) Toxicology (99) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a00dea994f3aad07',t:'MTc3OTY0MjY1Mw=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();