Literature DB >> 32954595

COVID Isolation Eating Scale (CIES): Analysis of the impact of confinement in eating disorders and obesity-A collaborative international study.

Fernando Fernández-Aranda1,2,3, Lucero Munguía1,3, Gemma Mestre-Bach1,4, Trevor Steward5, Mikel Etxandi1, Isabel Baenas1,2, Roser Granero2,6, Isabel Sánchez1,2, Emilio Ortega7,8, Alba Andreu7, Violeta L Moize7,8, Jose M Fernández-Real2,9, Francisco J Tinahones2,10, Carlos Diegüez2,11, Gema Frühbeck2,12, Daniel Le Grange13, Kate Tchanturia14,15, Andreas Karwautz16, Michael Zeiler16, Angela Favaro17, Laurence Claes18,19, Koen Luyckx19,20, Ia Shekriladze15, Eduardo Serrano-Troncoso21, Teresa Rangil22,23, Maria Eulalia Loran Meler22, Jose Soriano-Pacheco24,25, Mar Carceller-Sindreu24,25, Sara Bujalance-Arguijo26, Meritxell Lozano27, Raquel Linares27, Carlota Gudiol3,28,29, Jordi Carratala3,28,29, Jessica Sanchez-Gonzalez1, Paulo Pp Machado30, Anders Håkansson31,32, Ferenc Túry33, Bea Pászthy33,34, Daniel Stein35, Hana Papezová36, Brigita Bax37, Mikhail F Borisenkov38, Sergey V Popov38, Youl-Ri Kim39, Michiko Nakazato40, Nathalie Godart41,42,43, Robert van Voren44, Tetiana Ilnytska45, Jue Chen46, Katie Rowlands14, Janet Treasure14, Susana Jiménez-Murcia1,2,3.   

Abstract

Confinement during the COVID-19 pandemic is expected to have a serious and complex impact on the mental health of patients with an eating disorder (ED) and of patients with obesity. The present manuscript has the following aims: (1) to analyse the psychometric properties of the COVID Isolation Eating Scale (CIES), (2) to explore changes that occurred due to confinement in eating symptomatology; and (3) to explore the general acceptation of the use of telemedicine during confinement. The sample comprised 121 participants (87 ED patients and 34 patients with obesity) recruited from six different centres. Confirmatory Factor Analyses (CFA) tested the rational-theoretical structure of the CIES. Adequate goodness-of-fit was obtained for the confirmatory factor analysis, and Cronbach alpha values ranged from good to excellent. Regarding the effects of confinement, positive and negative impacts of the confinement depends of the eating disorder subtype. Patients with anorexia nervosa (AN) and with obesity endorsed a positive response to treatment during confinement, no significant changes were found in bulimia nervosa (BN) patients, whereas Other Specified Feeding or Eating Disorder (OSFED) patients endorsed an increase in eating symptomatology and in psychopathology. Furthermore, AN patients expressed the greatest dissatisfaction and accommodation difficulty with remote therapy when compared with the previously provided face-to-face therapy. The present study provides empirical evidence on the psychometric robustness of the CIES tool and shows that a negative confinement impact was associated with ED subtype, whereas OSFED patients showed the highest impairment in eating symptomatology and in psychopathology.
© 2020 Eating Disorders Association and John Wiley & Sons Ltd.

Entities:  

Keywords:  COVID Isolation Eating Scale; COVID-19; eating disorders; obesity

Mesh:

Year:  2020        PMID: 32954595      PMCID: PMC7537123          DOI: 10.1002/erv.2784

Source DB:  PubMed          Journal:  Eur Eat Disord Rev        ISSN: 1072-4133


BACKGROUND

In just a few months, COVID‐19 has become a global pandemic that has brought numerous challenges to health professionals and their patients. To stop the speed of the spread of the virus, most governments have chosen to place their populations under confinement, which has implied radical changes in social interactions and the way work was conducted. The final repercussions of confinement are still under investigation, though it is expected to have a significant impact on mental health for many. Considering other health and humanitarian crises, such as the Ebola and H1N1 influenza epidemics, depression (Hewlett & Hewlett, 2005; Kinsman, 2012), isolation, fear of being infected, posttraumatic stress (Li et al., 2018; Raven, Wurie, & Witter, 2018; Main, 2011) and health anxiety (McDonnell, Nelson, & Schunk, 2012; Mihashi, 2009) have been some of the negative effects on mental health reported by the general population, health workers and survivors of past epidemics (Wu, 2009). Confinement has been found to increase the incidence of negative states such as irritability, insomnia, anger, depression symptoms, amongst others (Mihashi, 2009). In response to the COVID‐19 pandemic, several studies have already been carried out to explore the psychological effects of the pandemic and confinement. In the general population, anxiety, depression, stress, worry about being infected, worry about family members being infected, worry about financial stress stability, post‐traumatic stress (Cao et al., 2020; Wang, Pan, et al., 2020; Wang, Di et al., 2020), but also mental health deterioration (Pierce, Hope, Ford, et al., 2020) and nutritional and activity patterns changes (Papandreou, Tsilidis, Arija, Aretouli, & Bulló, 2020), have been reported. Healthcare workers have emerged as a specific population in danger of suffering from psychological distress, depression, anxiety and insomnia (Inchausti, García‐Poveda, Prado‐Abril, & Sánchez‐Reales, 2020; Lai et al., 2020; Rossi et al., 2020) and populations with a prior mental health condition may experience an increase in their symptomatology related to changes in the delivery of their usual treatment (De Girolamo et al., 2020; Fernández‐Aranda et al., 2020). It is important to consider that stay‐at‐home and social‐distancing mandates have increased the frequency of several risk behaviours. The time available for engaging in potentially addictive behaviours, such as online gambling, gaming, and pornography (Håkansson, Fernández‐Aranda, Menchón, Potenza, & Jiménez‐Murcia, 2020; Király et al., 2020; Mestre‐Bach, Blycker, & Potenza, 2020) has increased and these behaviours, along with the use of alcohol or other substances, may be used as coping strategies to avoid negative emotional states (Håkansson et al., 2020; King, Delfabbro, Billieux, & Potenza, 2020; Király et al., 2020; Sun et al., 2020). Although these behaviours do not constitute a risk for all individuals, the current situation may increase the risk for onset, maintenance, and relapse, especially for the most vulnerable individuals (Columb, Hussain, & O'Gara, 2020; Marsden et al., 2020), such as patients with an eating disorders and patients with obesity (Baenas et al., 2020; Graell et al., 2020; Cornejo‐Pareja et al., 2020), as well as patients with less favourable family environments (Vintró‐Alcaraz et al., 2018). It has been hypothesised that the COVID‐19 pandemic may exacerbate the risk factors for overeating and unhealthy weight gain, especially in vulnerable populations such as children and individuals with an eating disorder (ED) and obesity (Rundle, Park, Herbstman, Kinsey, & Wang, 2020, Graell et al., 2020). ED patients have already reported increased worries about the risk of being infected with COVID‐19, disruptions in their work and treatment, the worsening of their ED symptoms, as well as heightened anxiety and stress (Fernández‐Aranda et al., 2020). ED patients and individuals with obesity constitute vulnerable populations who require targeted approaches (Cornejo‐Pareja et al., 2020). As an immediate emergency measure to address this situation, different telemedicine tools during the pandemic have been described within this population (Cooper et al., 2020; Smith, Ostinelli, Macdonald, & Cipriani, 2020), however there is a lack of studies looking at their effectiveness and acceptability by users. New psychometric instruments have been developed to measure different features related to the Covid‐19 pandemic, such as the contextual situation lived during the confinement, the changes occurring in the individuals' life and the impact on their health state. Some of these new scales are: the Fear of COVID‐19 Scale (FCV‐19S; (Ahorsu et al., 2020; Sakib et al., 2020; Soraci et al., 2020), the COVID‐19 Anxiety Scale (CAS; (Chandu, Pachava, Vadapalli, & Marella, 2020), the COVID‐19‐PTSD (Forte, Favieri, Tambelli, & Casagrande, 2020), the CoViD‐19 Peritraumatic Distress Index (CPDI; (Costantini & Mazzotti, 2020), the Coronavirus Impact Scale (CIS; Kaufman & Stoddard, 2020) and the COVID Stress Scales (CSS; (Taylor et al., 2020), including COVID danger and contamination fears, COVID fears about economic consequences, COVID xenophobia, COVID compulsive checking and reassurance seeking, and COVID traumatic stress symptoms. However, to the best of our knowledge, no tool has yet been developed and validated to assess eating disorder symptomatology and treatment‐related aspects in patients with an ED and obesity.

Goals

The aims of this exploratory study were threefold: (1) to analyse the psychometric properties of the COVID Isolation Eating Scale (CIES), a newly created scale for measuring the impact of confinement; (2) to explore changes that occurred due to confinement (eating symptomatology and weight, attitudes and dysfunctional emotions, worries and concerns, anxiety and depressive symptomatology and addictive behaviours); (3) to explore the potential difficulties for participants in using telemedicine during confinement when usual health care was interrupted. Based on previous literature (Baenas et al., 2020; Fernández‐Aranda et al., 2020; Temorshuizen et al., 2020; Mallorqui‐Bague, 2018), we hypothetised that eating disorder subtype and obesity would achieve a moderator/interaction role in the changes occurred during the confinement: behavioural and emotional reactions, eating patterns‐weight, anxiety and affective symptoms should be different depending on the ED subtype previous to the COVID‐19 pandemic.

METHODS

The data collection of this study was conducted between June and July 2020. Our study sample comprised 121 participants (87 ED patients and 34 patients with obesity), recruited from six different child‐adolescent and adult units from the Barcelona (Spain) region. These centres are representative of the public and private sectors of ED treatment services in Barcelona. Participants were involved in ED treatment before the outbreak of COVID‐19 and were asked by therapists from each centre if they were willing to voluntarily complete the study questionnaire. The ED sample was diagnosed according to DSM‐5 criteria (American Psychiatric Association, 2013) by means of a semi‐structured interview. Obese participants were bariatric surgery candidates who were recruited at the Endocrinological Unit at the Clinic Hospital of Barcelona. The sex distribution was 104 women (86.0%) and 17 men (14.0%). The age range was broad (mean = 33.7, SD = 15.8), ranging from 13 to 77. The distribution of the ED diagnoses was as follows: 55 cases met criteria for anorexia nervosa (AN), 18 for bulimia nervosa (BN), 14 were diagnosed with an Other Specified Feeding or Eating Disorder (OSFED). Table S1 (supplementary material) contains the distribution of sex and age within the groups defined by diagnosis. No statistical differences by gender were obtained (χ 2 = 4.06, df = 3, p = .256). However, chronological age was not equally distributed between groups (F = 30.08, df = 3/117, p < .001): obese patients were the oldest (mean = 48.8, SD = 12.9), followed by OSFED (mean = 36.9, SD = 16.4), BN (mean = 31.5, SD = 10.1) and AN (mean = 24.2, SD = 10.7) patients.

Assessment

The COVID Isolation Eating Scale (CIES) is a self‐report questionnaire that assesses the impact of confinement in patients with an eating disorder and/or obesity. This measure has been designed to be answered both with paper and pencil or online. The scale was generated by experts in the ED area through a theoretical‐rationale procedure based on the next steps: (a) identification of the domains (constructs/areas) endeavouring to measure; (b) deciding the number of factors/dimensions and their position into a meaningful order and format into the questionnaire; and (c) generating the items, as well as their distribution within each factor/dimension. After the development of the item pool, independent expert judges assessed whether the items adequately represented the domains of interest. The final CIES, besides exploring patient sociodemographic information, the scale was divided into four sections: (I) Circumstances during confinement (eight items characterising the circumstances of confinement). (II) Effects of confinement on eating disorder symptoms (13 items relating to the eating symptomatology of anorexia nervosa, bulimia nervosa, binge eating disorder and other specified feeding or eating disorder, according to the DSM‐5 and comorbid physical and psychiatric disorders. (III) Behavioural and psychopathological impact of confinement (34 items covering the effects of confinement on eating patterns, attitudes and habits, anxietydepression symptomatology, emotion dysregulation, and other symptomatology associated with substance use disorders and non‐substance related addictive behaviours. (IV) Evaluation of remote interventions (13 items assessing the feasibility, acceptance and satisfaction). The three last scales are answered on a five‐point Likert scale. Sections 2 and 3 consider two moments of time: before confinement and now, the present (for the English version of CIES Scale and translation in 18 additional languages see Supplementary information online).

Additional information

Socio‐demographic/clinical information, including age, affiliation to the patient with an ED, and marital status, but also variables related to COVID and duration and type of the confinement was obtained along with the CIES questionnaire.

Procedure

The present study was approved by the Clinical Research Ethics Committee of Bellvitge University Hospital (PR239/20). Written and signed informed consent was obtained from all participants before taking part in the study.

Statistical analysis

Statistical analyses were carried out with Stata16 for Windows (Stata Press, 2019). Based on the theoretical‐rational method used to develop the CIES, confirmatory factor analyses (CFA) was used to verify the factor structure of the questionnaire. CFA was implemented through structural equation modelling, defining the maximum likelihood, and considering adequate goodness of fit for Root Mean squared Error of Approximation RMSEA < 0.08, Comparative Fit Index CFI > 0.90, Tucker‐Lewis Index TLI > 0.90 and Standardised Root Mean Squared Residuals SRMR<0.10 (Barrett, 2007). An initial CFA assumed the existence of five latent theoretical factors: Factor 1 was defined by 10 items measuring eating related symptoms (such as concerns about weight, attempts to reduce eating quantities and meals, presence of bingeing/purging, use of laxatives/diuretics, and exercise or other activities to control weight); Factor 2 was defined by 10 items measuring the effects of confinement on the eating related style (such as being unable to stop eating during the day, or between meals or certain foods); Factor 3 was defined by 11 items assessing anxiety and depressive symptoms (sleep problems, upsetting thoughts, loneliness, limited social contact, health concerns related to COVID‐19, or sexual problems); Factor 4 was defined by five items related to emotion regulation (emotional control/awareness, anger/shame, aggressive behaviours and irritability); and Factor 5 was defined by 10 items to evaluate telemedicine (adequacy, motivation, satisfaction and usefulness). Factors F1, F2, F3 and F4 were also developed to allow for assessment prior and following COVID‐19 confinement. However, it was not possible to test the initial single CFA for the five‐dimension model, because the sample size was too small to verify this complex structure (fit was not obtained). According to the sample size, separate models were tested for each dimension, programming within the same model the measures for the pre‐ and the post‐confinement to account for the expected correlations between both periods. Figure S1 (supplementary material) contains the path diagrams for the individual constructs tested in this manuscript. The pre‐post changes in the quantitative variables of the study were based on paired‐sample t‐tests for interval scaled variables, and on the McNemar test for categorical measures. The comparison between groups defined by the diagnosis (AN, BN, OSFED and obese) was based on analysis of variance analyses (ANOVAs), with post‐hoc pairwise comparisons estimated via Bonferroni's procedure. For all these analyses, significant tests were complemented with the estimation of the effect size through Cohen's‐d coefficient, considering null effect for |d| < 0.20, low‐poor for |d| > 0.20, mild‐medium for |d| > 0.50 and large‐high for |d| > 0.80) (Cohen, 1988; Kelley & Preacher, 2012; Granero, 2020).

RESULTS

Characteristics of the participants during the COVID‐19 confinement

During the lockdown period, 30 (24.8%) participants lived alone, and 32 (26.4%) lived with one or two people at home, 29 (24.0%) lived with three people, and the remaining 30 participants (24.8%) lived with more than three people. Most participants were not infected by COVID‐19 (n = 115, 95.0%) and most had no infections amongst people close to them (n = 94, 77.7%). Most participants did not report a caring role during the confinement (n = 84, 69.4%). 58% (70 participants) continued to work and 69% (83 participants) had no financial loss. No statistical differences between groups were observed for these contextual variables during lockdown (Table S1, supplementary material, contains the frequency distribution within the groups).

Psychometric properties of the CIES

The factorial analyses confirmed the rational‐theoretical structure for the CIES. All the items obtained significant factor loadings for their specific factor (Table S2, supplementary material, includes the standardised coefficients, standard errors, p‐values and 95% confidence intervals). The upper block of Table 1 includes the fit indices of the CFAs and the internal consistency coefficients of the factors/scales: adequate goodness‐of‐fit was obtained, and Cronbach alpha coefficients ranged from good (α = 0.81, for the factor F1‐impacts at pre‐confinement) to excellent (α = 0.92, for F2‐changes in eating at pre‐confinement). The bottom block of Table 1 contains the correlation matrix for the factor scores. Relevant positive correlations (with |R| coefficients above 0.24) were obtained for the factors F1, F2, F3 and F4, for both at pre‐confinement and after the confinement, with the only exception of F1‐post which did not correlate with F3‐pre and F4‐pre. However, no relevant correlations emerged between F5 (evaluation of telemedicine) and the other factors.
TABLE 1

Internal consistency, fitting indexes in the CFA and correlation‐matrix for CIES scores

Cronbach‐alphaFitting indices
PrePostRMSEACFITLISRMR
F1.Impact on ED symptoms.805.806.061.937.917.088
F2.Changes ‐ eating.922.910.072.941.924.080
F3.Changes‐ anxiety/depression.865.857.093.961.950.089
F4.Changes‐ emotion regulation.826.836.012.999.998.042
F5.Evaluation telemedicine.939.033.983.964.036
Correlation‐matrixF2preF3preF4preF1postF2postF3postF4postF5
F1.Pre‐impact on ED symptoms .675 .368 .401 .547 .480 .278 .256 .006
F2.Pre‐changes—eating .489 .498 .451 .657 .341 .338 .160
F3.Pre‐changes—anxiety/depression .736 .144 .345 .729 .549 −.032
F4.Pre‐changes—emotional regulation.154 .281 .553 .765 −.145
F1.Post‐impact on ED symptoms .656 .365 .331 −.120
F2.Post‐changes—eating .528 .444 −.008
F3.Post‐changes—anxiety/depression .746 −.208
F4.Post‐changes—emotion regulation−.183
F5.Evaluation telemedicine

Abbreviations: CFI, comparative fit index; RMSEA, root mean squared error of approximation; SRMR, standardised root mean squared residual; TLI, Tucker‐Lewis Index.

Note: Bold values indicate correlation coefficient with an effect size in the moderate (|R| > 0.24) to high (|R| > 0.37) range.

Internal consistency, fitting indexes in the CFA and correlation‐matrix for CIES scores Abbreviations: CFI, comparative fit index; RMSEA, root mean squared error of approximation; SRMR, standardised root mean squared residual; TLI, Tucker‐Lewis Index. Note: Bold values indicate correlation coefficient with an effect size in the moderate (|R| > 0.24) to high (|R| > 0.37) range.

Impact of the COVID‐19 on eating related behaviours

Table 2 contains the main changes in weight, BMI, CIES factors F1 to F4, the consumption of substances and the presence of other addictive behaviours. Separate analyses were performed according to the diagnostic subtype, since it was hypothesised that the diagnosis could influence pre‐post differences. Within AN patients, significant decreases after the confinement due to COVID‐19 were found for the factors F1 (impact on eating symptoms), F2 (changes in eating style) and F4 (changes in emotion regulation). Obese patients also reported a significant decrease in weight, BMI and changes in the eating style. However, no significant changes emerged for the BN and OSFED patients.
TABLE 2

Changes during confinement stratified by diagnostic subtype

Pre Post
Anorexia (n = 55) Mean SD Mean SD p |d|
Weight (kg)49.166.9150.276.52.0560.17
BMI (kg/m2)18.252.2518.672.14.0580.19
CIES‐F1 impact ED symptoms11.876.799.405.61 .015 0.40
CIES‐F2 changes—eating8.769.616.116.94 .023 0.32
CIES‐F3 changes—anxiety‐depression18.299.6917.809.64.6620.05
CIES‐F4 changes—emotion regulation9.474.638.334.86 .046 0.24
n % n % P |d|
Tobacco1527.3%1527.3%1.000.00
Alcohol610.9%59.1%1.000.06
Other illegal drugs47.3%35.5%1.000.07
Addictive behaviours2545.5%3156.4%.1800.22
Bulimia (n = 18) Mean SD Mean SD p |d|
Weight (kg)65.2610.9366.2211.81.2300.08
BMI (kg/m2)24.133.7524.474.02.2430.09
CIES‐F1 impact ED symptoms15.726.3114.946.04.6170.13
CIES‐F2 changes—eating19.509.7517.727.51.3060.20
CIES‐F3 changes—anxiety‐depression18.618.8920.227.12.1250.20
CIES‐F4 changes—emotion regulation9.334.199.564.26.5210.05
n % n % p |d|
Tobacco527.8%527.8%1.000.00
Alcohol633.3%633.3%1.000.00
Other illegal drugs15.6%15.6%1.000.00
Addictive behaviours1266.7%1372.2%1.000.12
OSFED (n = 14) Mean SD Mean SD p |d|
Weight (kg)63.078.9962.918.48.9260.02
BMI (kg/m2)23.403.3823.302.84.8860.03
CIES‐F1 impact ED symptoms12.296.6013.148.37.6020.11
CIES‐F2 changes—eating11.5710.8013.3612.68.1400.15
CIES‐F3 changes—anxiety‐depression14.0710.2318.2110.54.0710.40
CIES‐F4 changes—emotion regulation5.144.286.364.80.0660.27
n % n % p |d|
Tobacco642.9%642.9%1.000.00
Alcohol321.4%428.6%1.000.17
Other illegal drugs00.0%00.0%1.000.00
Addictive behaviours750.0%964.3%.5000.29
OBESE (n = 34) Mean SD Mean SD p |d|
Weight (kg)109.6220.51106.4619.61 .035 0.16
BMI (kg/m2)41.157.3739.946.86 .037 0.17
CIES‐F1 impact ED symptoms13.296.0613.566.21.6450.04
CIES‐F2 changes—eating14.0010.409.829.40 .017 0.42
CIES‐F3 changes—anxiety‐depression14.299.8014.0010.33.7650.03
CIES‐F4 changes—emotion regulation4.654.694.064.36.2800.13
n % n % p |d|
Tobacco514.7%411.8%1.000.09
Alcohol617.6%411.8%.5000.17
Other illegal drugs12.9%00.0%1.000.34
Addictive behaviours2367.6%2367.6%1.000.00

Abbreviations: OSFED, other specified feeding eating disorders.

Note: Bold values indicate significant comparison.

Changes during confinement stratified by diagnostic subtype Abbreviations: OSFED, other specified feeding eating disorders. Note: Bold values indicate significant comparison. Figure 1 displays the means of the pre‐post changes in the main variables of the study: weight, BMI, and CIES factors F1 to F4 (Table 3 contains the ANOVA comparing the changes between the groups). The obese patients were characterised by the highest change in weight (with a significant decrease of 3.2 kg, compared to an increase of nearly 1 kg for AN and BN patients and 0 kg for OSFED patients). Patients with AN also improved on other CIES factors. Although for the OSFED patients there were no pre‐post changes in weight and BMI, all other CIES factors deteriorated.
FIGURE 1

Differences (post‐pre changes) in weight, BMI and CIES factors amongst the groups [Colour figure can be viewed at wileyonlinelibrary.com]

TABLE 3

Comparison of the differences (post‐pre changes) for the weight and the CIES factor scores

Anorexia (AN)Bulimia (BN)OSFEDObesity (OBES) Significant
N = 55 N = 18 N = 14 N = 34 Pairwise
Mean SD Mean SD Mean SD Mean SD Comparisons
Weight (kg)1.114.230.963.27−0.166.48−3.168.38OBES ≠ (AN=BN=OSFED)
BMI (kg/m2)0.431.630.351.22−0.102.51−1.213.24OBES ≠ (AN=BN=OSFED)
CIES‐F1 impact ED symptoms−2.477.31−0.786.480.866.000.263.31AN ≠ (BN=OSFED = OBES)
CIES‐F2 changes—eating−2.658.38−1.787.141.794.25−4.189.70OSFED ≠ (AN=BN) ≠ OBES
CIES‐F3 changes—anx‐dep.−0.498.291.614.234.147.89−0.295.70OSFED ≠ (AN=BN=OBES)
CIES‐F4 changes—emotion−1.154.150.221.441.212.26−0.593.12OSFED ≠ (AN=BN=OBES)

Abbreviations: OSFED, other specified feeding eating disorder.

Differences (post‐pre changes) in weight, BMI and CIES factors amongst the groups [Colour figure can be viewed at wileyonlinelibrary.com] Comparison of the differences (post‐pre changes) for the weight and the CIES factor scores Abbreviations: OSFED, other specified feeding eating disorder.

Evaluation of telemedicine

Table 4 contains information about the evaluation of alternatives to face to face therapy. Patients with AN, found these alternatives the least acceptable whereas people with obesity and OSFED patients were more satisfied with these alternatives.
TABLE 4

Comparison of the CIES F5 evaluation of telemedicine between the groups

Anorexia (AN)Bulimia (BN)OSFEDObesity
n = 55 n = 18 n = 14 n = 34
MeanSDMeanSDMeanSDMeanSD
25.5810.4028.616.4629.509.5328.977.25
Pairwise comparisons p |d|
Anorexia vs bulimia.2180.35
Anorexia vs OSFED.1480.39
Anorexia vs obesity .047* 0.38
Bulimia vs OSFED.7820.11
Bulimia vs obesity.8910.05
OSFED vs obesity.8530.06

Abbreviation: OSFED, other specified feeding eating disorder.

Comparison of the CIES F5 evaluation of telemedicine between the groups Abbreviation: OSFED, other specified feeding eating disorder.

DISCUSSION

This study was prompted by the need to assess the effects of confinement due to the COVID‐19 pandemic in vulnerable patients with ED and obesity (Cornejo‐Pareja et al., 2020; Fernández‐Aranda et al., 2020; Todisco & Donini, 2020). The three main aims were to first establish the psychometric properties of the specifically developed assessment measure (CIES), second to measure the changes in eating and general symptomatology, and thirdly to establish the acceptability of remote interventions. The CFA confirmed the rational‐theoretical structure of CIES into five‐factors (impact on eating symptoms, changes in eating style, changes in anxiety/depression symptoms, changes in emotion regulation and evaluation of telemedicine), obtaining adequate goodness‐of‐fit. Other attributes of validity of this tool should be analysed in future research (such as the convergent, discriminant and predictive validity, assessing the relationship between the CIES scores with other external measures related with eating behaviours). The impact of confinement was mixed and varied by diagnosis. In contrast to other studies (Rodgers et al., 2020), the disordered eating improved during the COVID‐19 pandemic. Patients with obesity had a significant decrease both in weight/BMI and in eating psychopathology. This may be due to the fact that candidates for bariatric surgery were receiving ongoing nutritional management, and were selected based on minimal psychopathology. Also the findings from AN and BN patients do not align with previous studies which found a worsening in dietary restriction (Temorshuizen et al., 2020) and heightened psychological distress (Clark Bryan et al., 2020; Pierce et al., 2020). In the present study, AN and BN participants, did not present significant changes in weight/BMI. In this study people with AN, reported a significant decrease in ED symptomatology and in emotion dysregulation after confinement. Factors such as younger age and how participants were dealing with external control environments, might be associated (Darrow, Accurso, Nauman, Goldschmidt, & Le Grange, 2017; Treasure, Gavan, Todd, & Schmidt, 2003). Interestingly, OSFED patients reported most adverse effects on eating behaviours and anxietydepressive symptoms after confinement. As reported previously in the literature (Riesco et al., 2018), clinicians may need to pay special attention to subthreshold cases, who may be more sensitive to adverse environments (Claes, Boekaerts, Verschueren, Boukaert, & Luyckx, 2019; Strand, von Hausswolff‐Juhlin, Fredlund, & Lager, 2019; Vanzhula, Calebs, Fewell, & Levinson, 2019) Finally, although most patients reported being satisfied with the remote treatment used during the pandemic, in concordance with previous studies (Linardon, Shatte, Tepper, & Fuller‐Tyszkiewicz, 2020), patients with AN were the least comfortable with the change. Other studies have reported on the distress caused by premature discharge from inpatient care with a lack of preparation (Clark Bryan et al., 2020). This sensitivity to change may be related with specific temperamental traits, such as managing uncertainty and may be specific therapy targets in future interventions (Baenas et al., 2020; Brown et al., 2017; Kannarkat, Smith, & McLeod‐Bryant, 2020).

Limitations

Despite the novelty of this study, several limitations should be considered in the present study: memory bias due to the retrospective nature of the assessment, limited sample size and heterogeneity of the patient groups analysed.

CONCLUSIONS

The present study provides empirical evidence on the psychometric robustness of the CIES tool. The effects of confinement, varied by ED subtype. Patients with AN and those with obesity endorsed a positive response whereas OSFED patients showed the highest deterioration in eating symptomatology and in psychopathology. Furthermore, AN patients expressed the greatest dissatisfaction with adjustment to remote therapy. The administration of the CIES in populations with ED and obesity may inform clinicians about how to prepare for adjustments to future environmental challenges. Further studies may need to be conducted in different countries with larger samples in order to be able to generalise these results. Figure S1 Scheme of the CFA in the study Click here for additional data file. Table S1 and Table S2 Description of the sample and Standardised coefficients obtained in the CFA Click here for additional data file. CIES Scale v.1.0 (Translation in 19 Languages: English‐Spanish‐Catalan‐French‐Portuguese‐Italian‐German‐Swedish‐Czech‐Lithuanian‐Dutch‐Russian‐Hungarian‐Georgian‐Hebrew‐Japanese‐Korean‐Chinese‐Ukrainian). Click here for additional data file.
  54 in total

Review 1.  On effect size.

Authors:  Ken Kelley; Kristopher J Preacher
Journal:  Psychol Methods       Date:  2012-04-30

2.  Relations of SARS-related stressors and coping to Chinese college students' psychological adjustment during the 2003 Beijing SARS epidemic.

Authors:  Alexandra Main; Qing Zhou; Yue Ma; Linda J Luecken; Xin Liu
Journal:  J Couns Psychol       Date:  2011-07

3.  Validation of the Caregiver Skills (CASK) scale in Catalonia: Concordance between caregivers in attitudes and behaviours.

Authors:  Cristina Vintró-Alcaraz; Gemma Mestre-Bach; Trevor Steward; María Lozano-Madrid; Zaida Agüera; Susana Jiménez-Murcia; Anna M Pedraza; Eduardo Serrano-Troncoso; Ana E Ortiz García; Teresa Rangil; Eulalia Lorán; Jose Soriano-Pacheco; Laura Medrano-Puigdollers; Sara Bujalance-Arguijo; Gina Badia; Maria Luque; Gloria Tràfach; Osane Gómez; Joan Peña; Carme Fabra; Maria Teresa Plana; Reyes Raspall; Isabel Sánchez; Nadine Riesco; Roser Granero; Cristina Carretero-Jardí; Janet Treasure; Fernando Fernández-Aranda
Journal:  Eur Eat Disord Rev       Date:  2018-07

4.  Other Specified Feeding or Eating Disorders (OSFED): Clinical heterogeneity and cognitive-behavioral therapy outcome.

Authors:  Nadine Riesco; Zaida Agüera; Roser Granero; Susana Jiménez-Murcia; José M Menchón; Fernando Fernández-Aranda
Journal:  Eur Psychiatry       Date:  2018-09-05       Impact factor: 5.361

5.  Children and adolescents with eating disorders during COVID-19 confinement: Difficulties and future challenges.

Authors:  Montserrat Graell; M Goretti Morón-Nozaleda; Ricardo Camarneiro; Ángel Villaseñor; Silvia Yáñez; Rudiger Muñoz; Beatriz Martínez-Núñez; Carolina Miguélez-Fernández; María Muñoz; Mar Faya
Journal:  Eur Eat Disord Rev       Date:  2020-07-29

6.  Mitigating and learning from the impact of COVID-19 infection on addictive disorders.

Authors:  John Marsden; Shane Darke; Wayne Hall; Matt Hickman; John Holmes; Keith Humphreys; Joanne Neale; Jalie Tucker; Robert West
Journal:  Addiction       Date:  2020-04-28       Impact factor: 7.256

7.  Brief Report: Increased Addictive Internet and Substance Use Behavior During the COVID-19 Pandemic in China.

Authors:  Yan Sun; Yangyang Li; Yanping Bao; Shiqiu Meng; Yankun Sun; Gunter Schumann; Thomas Kosten; John Strang; Lin Lu; Jie Shi
Journal:  Am J Addict       Date:  2020-06-04

8.  Experiences and challenges in the health protection of medical teams in the Chinese Ebola treatment center, Liberia: a qualitative study.

Authors:  Ying Li; Huan Wang; Xu-Rui Jin; Xiang Li; Michelle Pender; Cai-Ping Song; Sheng-Lan Tang; Jia Cao; Hao Wu; Yun-Gui Wang
Journal:  Infect Dis Poverty       Date:  2018-08-16       Impact factor: 4.520

9.  Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China.

Authors:  Cuiyan Wang; Riyu Pan; Xiaoyang Wan; Yilin Tan; Linkang Xu; Cyrus S Ho; Roger C Ho
Journal:  Int J Environ Res Public Health       Date:  2020-03-06       Impact factor: 3.390

10.  Mobilization of Telepsychiatry in Response to COVID-19-Moving Toward 21st Century Access to Care.

Authors:  Jacob T Kannarkat; Noah N Smith; Stephen A McLeod-Bryant
Journal:  Adm Policy Ment Health       Date:  2020-07
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  25 in total

1.  Impact on the Nutritional Status and Inflammation of Patients with Cancer Hospitalized after the SARS-CoV-2 Lockdown.

Authors:  Patricia Yárnoz-Esquíroz; Ana Chopitea; Laura Olazarán; Maite Aguas-Ayesa; Camilo Silva; Anna Vilalta-Lacarra; Javier Escalada; Ignacio Gil-Bazo; Gema Frühbeck; Javier Gómez-Ambrosi
Journal:  Nutrients       Date:  2022-07-02       Impact factor: 6.706

Review 2.  The Acute Impact of the Early Stages of COVID-19 Pandemic in People with Pre-Existing Psychiatric Disorders: A Systematic Review.

Authors:  Sandra Carvalho; Catarina G Coelho; Bruno Kluwe-Schiavon; Juliana Magalhães; Jorge Leite
Journal:  Int J Environ Res Public Health       Date:  2022-04-23       Impact factor: 4.614

3.  Increase in admission rates and symptom severity of childhood and adolescent anorexia nervosa in Europe during the COVID-19 pandemic: data from specialized eating disorder units in different European countries.

Authors:  Renata Nacinovich; Beate Herpertz-Dahlmann; Susanne Gilsbach; Maria Teresa Plana; Josefina Castro-Fornieles; Michela Gatta; Gunilla Paulson Karlsson; Itziar Flamarique; Jean-Philippe Raynaud; Anna Riva; Anne-Line Solberg; Annemarie A van Elburg; Elisabet Wentz
Journal:  Child Adolesc Psychiatry Ment Health       Date:  2022-06-20       Impact factor: 7.494

Review 4.  Anorexia nervosa: COVID-19 pandemic period (Review).

Authors:  Mihai Cristian Dumitrașcu; Florica Șandru; Mara Carsote; Razvan Cosmin Petca; Ancuta Augustina Gheorghisan-Galateanu; Aida Petca; Ana Valea
Journal:  Exp Ther Med       Date:  2021-05-26       Impact factor: 2.447

Review 5.  A mixed-studies systematic review of the experiences of body image, disordered eating, and eating disorders during the COVID-19 pandemic.

Authors:  Jekaterina Schneider; Georgina Pegram; Benjamin Gibson; Deborah Talamonti; Aline Tinoco; Nadia Craddock; Emily Matheson; Mark Forshaw
Journal:  Int J Eat Disord       Date:  2022-03-23       Impact factor: 5.791

6.  Impact of the COVID-19 Pandemic on Disordered Eating Behavior: Qualitative Analysis of Social Media Posts.

Authors:  Sara K Nutley; Alyssa M Falise; Rebecca Henderson; Vasiliki Apostolou; Carol A Mathews; Catherine W Striley
Journal:  JMIR Ment Health       Date:  2021-01-27

7.  Impact of COVID-19 Confinement on Adolescent Patients with Anorexia Nervosa: A Qualitative Interview Study Involving Adolescents and Parents.

Authors:  Michael Zeiler; Tanja Wittek; Leonie Kahlenberg; Eva-Maria Gröbner; Martina Nitsch; Gudrun Wagner; Stefanie Truttmann; Helene Krauss; Karin Waldherr; Andreas Karwautz
Journal:  Int J Environ Res Public Health       Date:  2021-04-16       Impact factor: 3.390

8.  The abrupt transition from face-to-face to online treatment for eating disorders: a pilot examination of patients' perspectives during the COVID-19 lockdown.

Authors:  Yael Doreen Lewis; Roni Elran-Barak; Rinat Grundman-Shem Tov; Eynat Zubery
Journal:  J Eat Disord       Date:  2021-03-05

9.  Risk and resilience factors for specific and general psychopathology worsening in people with Eating Disorders during COVID-19 pandemic: a retrospective Italian multicentre study.

Authors:  Alessio Maria Monteleone; Giammarco Cascino; Francesca Marciello; Giovanni Abbate-Daga; Monica Baiano; Matteo Balestrieri; Eugenia Barone; Sara Bertelli; Bernardo Carpiniello; Giovanni Castellini; Giulio Corrivetti; Serafino De Giorgi; Angela Favaro; Carla Gramaglia; Enrica Marzola; Paolo Meneguzzo; Francesco Monaco; Maria Ginevra Oriani; Federica Pinna; Marianna Rania; Carolina Alberta Redaelli; Caterina Renna; Valdo Ricca; Pierandrea Salvo; Erika Baldissera; Cristina Segura-Garcia; Patrizia Todisco; Umberto Volpe; Patrizia Zeppegno; Palmiero Monteleone
Journal:  Eat Weight Disord       Date:  2021-01-10       Impact factor: 4.652

10.  COVID Isolation Eating Scale (CIES): Analysis of the impact of confinement in eating disorders and obesity-A collaborative international study.

Authors:  Fernando Fernández-Aranda; Lucero Munguía; Gemma Mestre-Bach; Trevor Steward; Mikel Etxandi; Isabel Baenas; Roser Granero; Isabel Sánchez; Emilio Ortega; Alba Andreu; Violeta L Moize; Jose M Fernández-Real; Francisco J Tinahones; Carlos Diegüez; Gema Frühbeck; Daniel Le Grange; Kate Tchanturia; Andreas Karwautz; Michael Zeiler; Angela Favaro; Laurence Claes; Koen Luyckx; Ia Shekriladze; Eduardo Serrano-Troncoso; Teresa Rangil; Maria Eulalia Loran Meler; Jose Soriano-Pacheco; Mar Carceller-Sindreu; Sara Bujalance-Arguijo; Meritxell Lozano; Raquel Linares; Carlota Gudiol; Jordi Carratala; Jessica Sanchez-Gonzalez; Paulo Pp Machado; Anders Håkansson; Ferenc Túry; Bea Pászthy; Daniel Stein; Hana Papezová; Brigita Bax; Mikhail F Borisenkov; Sergey V Popov; Youl-Ri Kim; Michiko Nakazato; Nathalie Godart; Robert van Voren; Tetiana Ilnytska; Jue Chen; Katie Rowlands; Janet Treasure; Susana Jiménez-Murcia
Journal:  Eur Eat Disord Rev       Date:  2020-09-20
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