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Article

Influence of Menstrual Cycle Length and Age at Menarche on Symptoms, Cognition, Social Cognition, and Metacognition in Patients with First-Episode Psychosis

by
Paula Barrau-Sastre
1,2,3,
Irene Birulés
2,3,
Marina Verdaguer-Rodríguez
1,2,
Raquel López-Carrilero
1,2,4,
Marta Ferrer-Quintero
1,2,3,4,
Helena García-Mieres
1,2,4,
Luciana Díaz-Cutraro
1,2,5,
Eva Grasa
4,6,7,
Esther Pousa
4,6,7,8,9,
Ester Lorente
4,10,
Trinidad Peláez
2,4,
María Luisa Barrigón
11,
Isabel Ruiz-Delgado
12,
Fermín González-Higueras
13,
Jordi Cid
14,
Alfonso Gutiérrez-Zotes
4,15,
Daniel Cuadras
16,
Judith Usall
1,2,
Regina Vila-Badia
1,2,4,
Ana Barajas
17,18,
Susana Ochoa
1,2,4,* and
on behalf of the Spanish Metacognition Group
add Show full author list remove Hide full author list
1
Etiopatogènia I Tractament dels Trastorns Mentals Greus (MERITT), Institut de Recerca Sant Joan de Déu, Santa Rosa 39-57, 08950 Esplugues de Llobregat, Spain
2
Parc Sanitari Sant Joan de Déu, Doctor Antoni Pujadas 42, 08830 Sant Boi de Llobregat, Spain
3
Facultat de Psicologia, Universitat de Barcelona, Passeig de la Vall d’Hebron, 71, 08035 Barcelona, Spain
4
Investigación Biomédica en Red de Salud Mental (CIBERSAM), 28029 Madrid, Spain
5
Psychology Department, FPCEE Blanquerna, Universitat Ramon Llull, 08022 Barcelona, Spain
6
Department of Psychiatry, Institut d’Investigació Biomèdica-Sant Pau (IIB-Sant Pau), Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain
7
Departament de Psicologia Clínica i de la Salut, Facultat de Psicologia, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
8
Salut Mental Parc Taulí. Sabadell, Hospital Universitari, UAB Universitat Autònoma de Barcelona, Sabadell, 08208 Barcelona, Spain
9
Neuropsiquiatria i Addicions, Hospital del Mar. IMIM (Hospital del Mar Medical Research Institute), 08003 Barcelona, Spain
10
Psychiatry Service, Hospital Clínico Universitario de Valencia, 46010 Valencia, Spain
11
Departamento de Psiquiatría, Hospital Universitario Virgen del Rocio, 41013 Sevilla, Spain
12
Unidad de Salud Mental Comunitaria Málaga Norte, UGC Salud Mental Carlos Haya, Servicio Andaluz de Salud, 29014 Málaga, Spain
13
Comunidad Terapéutica Jaén Servicio Andaluz de Salud, 23001 Jaén, Spain
14
Mental Health & Addiction Research Group, IdiBGi—Institut d’Assistencia Sanitària, 17119 Girona, Spain
15
Institut d’Investigació Sanitària Pere Virgili (IISPV), Hospital Universitari Institut Pere Mata, Universitat Rovira i Virgili, 43206 Reus, Spain
16
Statistical Unit, Fundació Sant Joan de Déu, Esplugues de Llobregat, 08950 Barcelona, Spain
17
Serra Húnter Programme, Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
18
Centre d’Higiene Mental Les Corts, Department of Research, 08029 Barcelona, Spain
*
Author to whom correspondence should be addressed.
Membership of the Spanish Metacognition Study Group is provided in the Acknowledgments.
Submission received: 7 February 2022 / Revised: 30 May 2022 / Accepted: 31 May 2022 / Published: 2 June 2022
(This article belongs to the Special Issue Feature Papers in Women 2021)

Abstract

:
A protective effect has traditionally been attributed to estrogen in psychotic disorders. The aim of this study was to investigate cumulative lifetime estrogen by assessing the menstrual cycle length, age at menarche, and years of difference between the onset of psychotic symptoms and the age of menarche, measuring their effects on symptoms, cognition, social cognition, and metacognition. As it was not possible to directly measure cumulative estrogen levels over the lifetime of a patient, the study sample was composed of 42 women with first-episode psychosis; estrogen levels were inferred by the menstrual cycle length, age at menarche, and years of difference between the onset of psychotic symptoms and menarche. All patients were assessed with a battery of questionnaires using the BDI, PSYRATS, PANSS, STROOP, TAVEC, WSCT, IPSAQ, and BCIS questionnaires. The results related to menstrual cycle length showed a relationship with memory; specifically, shorter cycles with semantic strategies (p = 0.046) and longer cycles with serial strategies in the short term (p = 0.005) as well as in the long term (p = 0.031). The results also showed a relationship with perseverative errors (p = 0.035) and self-certainty (p = 0.049). Only personalized bias (p = 0.030) was found to be significant in relation to the age at menarche. When analyzing the differences in years of difference between the age at menarche and the onset of psychotic symptoms, the results indicated lower scores in women with a smaller difference between both events in memory (short-term (p = 0.050), long-term (p = 0.024), intrusions (p = 0.013), and recognition (p = 0.043)) and non-perseverative errors (p = 0.024). No relationship was found between symptoms and menstrual characteristics. The investigatory outcomes seem to indicate a relationship between estrogen cumulative effects and the memory domain. More in-depth investigations in the field are necessary in order to improve personalized treatment in women with psychosis.

1. Introduction

The course of schizophrenia, its expression, and the response to treatment varies widely among patients [1], although it is commonly a highly incapacitating disease that entails a considerable societal burden [2].
Nonetheless, the prognosis of psychotic disorders is still partially unknown [3,4]; first-episode psychosis (FEP) is a five-year critical period in which social development deteriorates. At present, the course of the illness can be determined based on cognitive and social cognition functioning [5,6,7]. Additionally, substance misuse and abuse in women with FEP is being discussed as a possible oxidative factor that can cause further cognitive deficits and negative symptomatology [8,9].
Cumulative evidence has established that cognition, social cognition, and metacognition are among the best predictors of functional outcomes in psychosis [7,10,11,12,13]. People with psychosis often present important deficits in these three constructs, which are stable and appear prior to the onset of the disorder [10,14,15]. However, a growing body of literature suggests that psychological interventions aiming to improve cognition, social cognition, and metacognition have potential for promoting recovery [7,16].
A body of research has focused on understanding the sex differences in psychosis. Commonly, studies have found a lower prevalence and better recovery in females [17], which has led to the estrogenic hypothesis. This hypothesis suggests a protective effect of estrogen [18,19,20,21]. Estrogen plays several roles in females, from the development of secondary sexual characteristics to the regulation of the menstrual cycle. However, this effect is not exclusive to females as estrogen has recently been linked to anti-inflammatory, neuroprotective, and cognitive effects in males [22,23].
The duration of the menstrual cycle is associated with the length of the follicular phase, meaning that shorter follicular phases indicate shorter cycles [24]. Additionally, shorter menstrual cycles are usually associated with lower estradiol levels per cycle, but with a larger cumulative concentration over time [25]. On the other hand, shorter and longer cycles have been related to an increased probability of chronic anovulation and, consequently, a lower exposure to estrogen [25,26].
A delayed age at menarche has also been associated with negative and positive events in adulthood such as worse psychosocial functioning and a greater cardiovascular risk. Conversely, it has a protective effect against breast and endometrial cancer [25,27].
Emerging research indicates that early menarche correlates with higher estrogen levels [28]. In the case of women with psychosis, there seems to be an association between early puberty and a later onset of symptoms, which is consistent with the estrogenic hypothesis [29,30]. Furthermore, symptoms seem to fluctuate throughout the menstrual cycle and are heightened during the late luteal and early follicular phases. Interestingly, this association is also present in patients with mood disorders [26,30,31,32]. In addition, postpartum and menopause psychosis have been related to the abrupt decrease in estrogen after these events [26,30,33].
Compared with healthy populations, women with psychosis have lower estrogen levels [33]. Recent studies have suggested that selective estrogen receptor modulators (SERMs) can improve cognitive symptoms in men and women with psychosis [34,35].
However, how estrogen cumulative effects influence symptoms, cognition, social cognition, and metacognition is still unknown, although a pharmacological treatment with SERMs seems to provide results. Therefore, the present study intended to obtain preliminary data on how pubertal and menstrual characteristics influence the expression of the illness and whether the protective effect of estrogen can be detected. The length of the cycle, age at menarche, and time elapsed since the age at menarche as well as the onset of symptoms could be variables that help us to indirectly deduce the level of estrogen.
The aim of this work was to conduct an exploratory analysis of the clinical, cognitive, social cognitive, and metacognitive differences according to the length of the menstrual cycle, age at menarche, and years of difference between the onset of psychosis and age at menarche in women with FEP. We hypothesized that these indicators could be related to clinical, cognitive, social cognitive, and metacognitive variables with a positive relationship between them and the inferred estrogen levels. An exploratory analysis was performed based on these data because these were the only data that were available as we did not count hormone levels.

2. Method and Materials

The sample of this study was composed of 42 women recruited through the following Spanish outpatient mental health centers between the years 2012 and 2017: The Health Assistance Institute of Girona; Sant Pau Hospital (Barcelona); Andalusian Service of Jaén; Andalusian Service of Málaga Pere Mata’s Institute (Reus); Jiménez Díaz Foundation (Madrid); Mental Health Hygiene Centre of Les Corts (Barcelona); Mental Health Centre of Healthcare and University Corporation of Parc Taulí (Sabadell); Clínic Hospital of València; and Parc Sanitari Sant Joan de Déu (PSSJD).
The inclusion criteria were women between the age of 18 and 45 years with FEP having a diagnosis of schizophrenia, an unspecified psychotic disorder, a schizoaffective disorder, a delusional disorder, a brief psychotic disorder, or a schizophreniform disorder based on DSM-V criteria in addition to psychopathological stability over the previous 3 months (meaning no changes in medication) and having obtained 3 or above on the delusion, grandiosity, or suspicion items on The Positive and Negative Syndrome Scale (PANSS). The exclusion criteria established were an intellectual disability (premorbid IQ inferior or equal to 70), the presence of a cranioencephalic traumatism, a substance abuse disorder, amenorrhea, or the use of hormonal contraceptives, having obtained 5 or above on the hostility and absence of cooperation items and a score of 6 on the suspiciousness item on the PANSS in order to facilitate adherence and collaboration during the evaluation.
Three variables were used to conduct the analysis. To start with, the cycle duration was defined as the average number of days that the menstrual cycle lasted. This variable was subjectively reported by participants, who had to choose which of the three groups they belonged to: short menstrual cycle (<28 days); mean (28–30 days); or long (>30 days). This classification was previously defined in the research protocols used in other studies. The second variable, age at menarche, was defined as the age of first menstruation and was asked of participants or reported based on their clinical history. The age at menarche was divided into three groups: early menarche (aged 9–12); mean (aged 13); or late menarche (aged 14–16). These groups were organized considering the distribution of the sample using the mean and conceptual information. In this case, the age of most women (50%) at menarche was at 13 years; therefore, we used this as the middle group. Those above and below the median formed the other two groups. For the last variable, if 0–5.99, 6–19.99, or >20 years passed between the age at menarche and illness onset, it was defined as the time when symptoms were reported for the first time. This group was divided considering the proximity to hormonal changes; below 5 years between the onset and menarche age was considered to be close to developmental changes and more than 20 years was considered to be hormonal maturation changes.
Regarding the assessment, the data were gathered during the inclusion of the study and through clinical histories; clinical, cognitive, social cognition, and metacognition evaluations were based on a clinical interview and the questionnaires from Table 1.

2.1. Ethical Aspects

The present study was approved by the Ethical Committee of Sant Joan de Déu (coordinator center) (protocol code: PIC-73-11; date of approval: 22 November 2011) and the ethical committee of each of the participant centers, following the guidelines of the Declaration of Helsinki. In addition, each participant was provided with an informative sheet and signed an informed consent form.

2.2. Statistical Analysis

The data analysis was performed using the ANOVA descriptive test and partial eta squared (η2) to calculate the effect size. We considered a p-value equal to or less than 0.05 to be statistically significant. Regarding the effect size, the following criteria were used: less than 0.1 indicated a small effect; between 0.1 and 0.15, a medium one; and larger than 0.15, a high effect size [56]. Multiple analysis corrections were not applied based on the effect size because we were performing an exploratory analysis [57]. We also performed a multimodal regression analysis that compared the three categories of each of the three main variables with the significant variables in the bivariate analysis. Moreover, we included age as a covariant. The reference category of menstrual cycle length was the middle group; in menarche age, the reference group was also the middle group. However, in the difference between the age at menarche and the onset of the illness, the reference group was the first one.

3. Results

Table 2 contains a description of the sociodemographic variables of the sample. The mean age of the patients was 31 years with a standard deviation of 8.06. As can be seen, 76.2% of our sample were single and 69.1% were not working (i.e., 28.6% unemployed; 21.4% inactive; 14.3% permanently or temporarily sick leave and 4.8% pensioners).
Regarding the variables studied, most patients had a 28–30 day menstrual cycle (47.6%). On the other hand, 35.7% had shorter ones (<28 days); only 11.9% were longer (>30 days). The mean menarche age was 12.31 with a standard deviation of 1.62 and the mean difference in years between the menarche age and the age of symptom onset was 15.14 with a standard deviation of 7.71.
We found no relationship between the age at menarche and the age of illness onset (r = 0.137; p = 0.388).
When analyzing the cycle length (Table 3), we found statistically significant differences with high effect sizes between the groups primarily in relation to memory and specifically in terms of semantic strategies (p = 0.046) and serial strategies with short-term (p = 0.005) and long-term (p = 0.031) memory. We also found a relationship between the cycle length and perseverative errors (p = 0.035) and self-certainty (p = 0.049).
The results for the menarche age can be found in Table 4. The only statistically significant result found was for personalizing bias (p = 0.030) with a high effect size (η2 = 0.168). The group with a later menarche was the one that obtained worse scores.
Regarding the years of difference between the onset of psychotic symptoms and menarche age (Table 5), the results indicated lower scores in women with the smallest difference between both events in memory (short-term (p = 0.050), long-term (p = 0.024), intrusions (p = 0.013), and recognition (p = 0.043)) and non-perseverative errors (p = 0.024); all of them had a high effect size.
When performing the multimodal regression analysis concerning the menstrual cycle length, age (p = 0.009), serial strategy on short-term recall with keys (p = 0.002), and self-certainty (p = 0.023) were included in the model. However, in the analysis of each subgroup, we only found a tendency toward a significance regarding the lowest cycle and middle cycle in the serial strategy on short-term recall with keys (B = 0.118; p = 0.088).
Considering the results of the age at menarche, hallucinations measured by the PSYRATS (p = 0.013), a positive PANSS (p = 0.048), and personalized bias (p < 0.001) were included in the model. In this case, personalized bias had a tendency to differ between subgroups 1 and 2 (B = 0.074; p = 0.061). A positive PANSS (B = 1.769; p = 0.098) and personalized bias (B = 38.845; p = 0.051) had a tendency to differ between subgroups 2 and 3.
Finally, regarding the difference between the age at menarche and the age of onset, the only variable included in the model was hits on recognition (p = 0.032), which was significant between subgroups 1 and 2 (B = 0.902; p = 0.046).

4. Discussion

In the present study, we have suggested differences based on the length of the cycle, the time elapsed since the age at menarche and the onset of symptoms, and the age at menarche following the expected protective estrogen hypothesis, indicating that these could be relevant indicators.
Our first finding was that the duration of the menstrual cycle was significantly associated with the different domains of memory. We observed that the semantic strategy was the least used in women with an average cycle length whereas the serial strategy was used more often. Patients with psychosis often present deficits in semantic processing; thus, they tend to rely more on serial memory. According to our results, patients with shorter and longer cycles performed better on semantic processing, indicating a better performance on memory; other authors have suggested that this is related to less severe symptoms [58,59]. Our results were in line with the estrogen levels associated with cycle length reported by Mumford et al. [25], and were also consistent with those in previous studies that reported an association between memory and processes of encoding and recalling [60,61,62]. They are also in line with the estrogen synthesis of the brain, which takes place mostly in the hippocampus and temporal regions [63,64].
Another significant result was that we found that women with shorter menstrual cycles appeared to have more cognitive flexibility and a greater inhibition capacity. These results were consistent with previous studies that reported that the interaction between estrogen and the dopaminergic system modulates executive functions [22,60]. Furthermore, an association between total estradiol and cognitive function in women has been observed [65].
The women with mean menstrual cycles showed less self-certainty, which was also consistent with a reported association between estrogen levels and cycle length [25]. Self-certainty is a metacognitive construct that has been associated with the emergence and maintenance of delusions [66,67] as well as neurocognitive performance [13]
The age at menarche was associated with personalized bias, a cognitive bias directly implicated in the emergence and maintenance of delusions [68,69]. This suggested that women with lower estrogen levels may attribute others with the consequences of negative events. This result followed our expectations although it was the only significant variable.
Similar to previous studies, we did not find a relationship between the age at menarche and the onset of illness [29]. Nonetheless, a more complex relationship between these factors has already been proposed in a previous study [70] and it is possible that there is a critical period in which estrogen exerts its effects [22,60]. Moreover, an early age at menarche has been associated with an increased risk of suffering a mental illness post-menarche [71]. An early age at menarche has also been associated with various factors during prenatal and childhood development such as body weight, trauma, or exposure to certain chemicals [71,72].
Based on the time elapsed since the age at menarche and the onset of symptoms, we also observed important differences in cognition. More precisely, short-term recall with keys and free long-term recall exhibited a larger period of time between both successes and an improved performance. This fact could indicate a better conservation of memory strategies [22,62,73,74], which may be due to the neuroprotective effects of estrogen [60].
We observed significant differences in intrusions, recognition, and non-perseverative errors; unexpectedly, the best performance was seen in the middle group. The worst performance was seen in the shortest period group, indicating that the shorter this time was, the worse the development was, thereby suggesting that a lack of estrogen implies a poorer performance [26,61].
The results obtained indicated a possible association between a few pubertal and menstrual characteristics on account of the protective influence of estrogen. However, the results of our study must be interpreted in the light of several limitations. First, we had a limited sample size, which should be larger in prospective research. Moreover, we based our groups on predefined characteristics and the distribution of the sample and conceptual knowledge. We did not have access to the blood measures of the hormonal parameters. Finally, the fact that correction analyses for multiple testing were not included should also be noted as a limitation. Notwithstanding these limitations, our results highlighted a possible relationship between menarche age, the menstrual cycle, and social cognitive, metacognitive, and neurocognitive performance in women with FEP. In the absence of research on the menstrual and pubertal characteristics of women with FEP, we only intended to conduct an exploratory analysis to guide future investigations on this subject.
Therefore, our findings suggest a relationship between the length of the cycle, the age at menarche, and the time elapsed since the age at menarche and the onset of symptoms with cognitive and metacognitive performance in women with FEP. In the future, it may be worth monitoring menstrual cycle characteristics and hormone blood levels as they are easy indicators to compile and could be useful tools to modulate medication and offer more individualized and personalized treatment. Further studies need to be performed with bigger sample sizes, continuous menstrual monitoring, and blood test analytics to corroborate this relationship.

Author Contributions

Conceptualization, P.B.-S., S.O. and I.B.; methodology, P.B.-S., S.O. and I.B.; validation, S.O. and I.B.; formal analysis, P.B.-S. and S.O.; investigation, P.B.-S.; resources, I.B., M.V.-R., R.L.-C., H.G.-M., M.F.-Q., L.D.-C., E.G., E.P., E.L., T.P., M.L.B., I.R.-D., F.G.-H., J.C., A.G.-Z., D.C. and the Spanish Metacognition Group; data curation, R.L.-C.; writing—original draft preparation, P.B.-S.; writing—review and editing, P.B.-S., I.B., S.O., H.G.-M., M.F.-Q., L.D.-C., J.U. and R.V.-B.; visualization, P.B.-S.; supervision, S.O. and I.B.; project administration, A.B. and S.O.; funding acquisition, S.O. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Instituto de Salud Carlos III, Spanish Government (grant no. PI11/01347, PI14/00044, and PI18/00212); the Fondo Europeo de Desarrollo Regional (FEDER); the Health Department of Catalonia; PERIS call (grant no. SLT006/17/00231); the Progress and Health Foundation of the Andalusian Regional Ministry of Health (grant no. PI-0634/2011 and PI-0193/2014); Obra Social La Caixa (RecerCaixa call 2013); CERCA Programme/Generalitat de Catalunya; Obra Social Sant Joan de Déu (BML); and FI19/00062 (Ayudas para la Contratación de Personal Predoctoral). L.D.-C was the beneficiary of a Predoctoral Training Grant in Health Research for this project.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Research and Ethics Committees of Sant Joan de Déu (protocol code: PIC-73-11; date of approval: 22 November 2011).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are not available upon request due to restrictions (e.g., privacy or ethical). The data presented in this study are available upon request from the corresponding author. Our institution is working on a repository of data.

Acknowledgments

We thank all the volunteers for their remarkable contribution.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Joyce, E.M.; Roiser, J.P. Cognitive Heterogeneity in Schizophrenia. Curr. Opin. Psychiatry 2007, 20, 268–272. [Google Scholar] [CrossRef] [PubMed]
  2. Tandon, R.; Keshavan, M.S.; Nasrallah, H.A. Schizophrenia, “Just the Facts”: What We Know in 2008. Part 1: Overview. Schizophr. Res. 2008, 100, 4–19. [Google Scholar] [CrossRef] [PubMed]
  3. Schmidt, M.J.; Mirnics, K. Neurodevelopment, GABA System Dysfunction, and Schizophrenia. Neuropsychopharmacology 2015, 40, 190–206. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Tandon, R.; Keshavan, M.S.; Nasrallah, H.A. Schizophrenia, “Just the Facts” What We Know in 2008. 2. Epidemiology and Etiology. Schizophr. Res. 2008, 102, 1–18. [Google Scholar] [CrossRef] [PubMed]
  5. Suvisaari, J.; Mantere, O.; Keinänen, J.; Mäntylä, T.; Rikandi, E.; Lindgren, M.; Kieseppä, T.; Raij, T.T. Is It Possible to Predict the Future in First-Episode Psychosis? Front. Psychiatry 2018, 9, 1–15. [Google Scholar] [CrossRef] [Green Version]
  6. Emsley, R.; Chiliza, B.; Asmal, L.; Harvey, B.H. The Nature of Relapse in Schizophrenia. BMC Psychiatry 2013, 13, 50. [Google Scholar] [CrossRef] [Green Version]
  7. Healey, K.M.; Bartholomeusz, C.F.; Penn, D.L. Deficits in Social Cognition in First Episode Psychosis: A Review of the Literature. Clin. Psychol. Rev. 2016, 50, 108–137. [Google Scholar] [CrossRef]
  8. Ventriglio, A.; Bellomo, A.; Donato, F.; Iris, B.; Giovanna, V.; Dario, D.S.; Edwige, C.; Ilaria, D.G.; Pettorruso, M.; Perna, G.; et al. Oxidative Stress in the Early Stage of Psychosis. Curr. Top. Med. Chem. 2021, 21, 1457–1470. [Google Scholar] [CrossRef]
  9. Ricci, V.; Martinotti, G.; Ceci, F.; Chiappini, S.; Di Carlo, F.; Burkauskas, J.; Susini, O.; Luciani, D.; Quattrone, D.; De Berardis, D.; et al. Duration of Untreated Disorder and Cannabis Use: An Observational Study on a Cohort of Young Italian Patients Experiencing Psychotic Experiences and Dissociative Symptoms. Int. J. Environ. Res. Public Health 2021, 18, 12632. [Google Scholar] [CrossRef]
  10. Kahn, R.S.; Keefe, R.S.E. Schizophrenia Is a Cognitive Illness: Time for a Change in Focus. JAMA Psychiatry 2013, 70, 1107–1112. [Google Scholar] [CrossRef]
  11. Mondragón-Maya, A.; Ramos-Mastache, D.; Román, P.D.; Yáñez-Téllez, G. Social Cognition in Schizophrenia, Unaffected Relatives and Ultra- High Risk for Psychosis: What Do We Currently Know? Cognición Social En Esquizofrenia, Familiares No Afectados e Individuos En Riesgo Ultra-Alto de Psicosis: ¿Qué Sabemos Actualmente? Actas Esp. Psiquiatr. 2017, 4545, 218–26218. [Google Scholar]
  12. Lysaker, P.H.; Erickson, M.; Buck, K.D.; Procacci, M.; Nicolò, G.; Dimaggio, G. Metacognition in Schizophrenia Spectrum Disorders: Methods of Assessment and Associations with Neurocognition and Function. Eur. J. Psychiatry 2010, 24, 220–226. [Google Scholar] [CrossRef] [Green Version]
  13. Lysaker, P.H.; Klion, R.E. Recovery, Meaning-Making, and Severe Mental Illness: A Comprehensive Guide to Metacognitive Reflection and Insight Therapy; Routledge: London, UK, 2018. [Google Scholar]
  14. Lysaker, P.H.; Ringer, J.M.; Buck, K.D.; Grant, M.; Olesek, K.; Leudtke, B.L.; Dimaggio, G. Metacognitive and Social Cognition Deficits in Patients with Significant Psychiatric and Medical Adversity: A Comparison between Participants with Schizophrenia and a Sample of Participants Who Are HIV-Positive. J. Nerv. Ment. Dis. 2012, 200, 130–134. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Vohs, J.L.; Lysaker, P.H. Metacognitive Mastery and Intrinsic Motivation in Schizophrenia. J. Nerv. Ment. Dis. 2014, 202, 74–77. [Google Scholar] [CrossRef] [PubMed]
  16. García, R.R.; Aliste, F.; Soto, G. Social Cognition in Schizophrenia: Cognitive and Neurobiological Aspects. Rev. Colomb. Psiquiatr. 2018, 47, 170–176. [Google Scholar] [CrossRef] [Green Version]
  17. Gogos, A.; Ney, L.J.; Seymour, N.; Van Rheenen, T.E.; Felmingham, K.L. Sex Differences in Schizophrenia, Bipolar Disorder, and Post-Traumatic Stress Disorder: Are Gonadal Hormones the Link? Br. J. Pharmacol. 2019, 176, 4119–4135. [Google Scholar] [CrossRef]
  18. Gogos, A.; Sbisa, A.M.; Sun, J.; Gibbons, A.; Udawela, M.; Dean, B. A Role for Estrogen in Schizophrenia: Clinical and Preclinical Findings. Int. J. Endocrinol. 2015, 2015, 615356. [Google Scholar] [CrossRef] [Green Version]
  19. Ochoa, S.; Usall, J.; Cobo, J.; Labad, X.; Kulkarni, J. Gender Differences in Schizophrenia and First-Episode Psychosis: A Comprehensive Literature Review. Schizophr. Res. Treat. 2012, 2012, 916198. [Google Scholar] [CrossRef] [Green Version]
  20. Riecher-Rössler, A.; Butler, S.; Kulkarni, J. Sex and Gender Differences in Schizophrenic Psychoses-a Critical Review. Arch. Womens Ment. Health 2018, 21, 627–648. [Google Scholar] [CrossRef]
  21. Seeman, M.V. Schizophrenia Psychosis in Women. Women 2020, 1, 1–15. [Google Scholar] [CrossRef]
  22. Hwang, W.J.; Lee, T.Y.; Kim, N.S.; Kwon, J.S. The Role of Estrogen Receptors and Their Signaling across Psychiatric Disorders. Int. J. Mol. Sci. 2021, 22, 373. [Google Scholar] [CrossRef] [PubMed]
  23. Sayed, Y.; Taxel, P. The Use of Estrogen Therapy in Men. Curr. Opin. Pharmacol. 2003, 3, 650–654. [Google Scholar] [CrossRef] [PubMed]
  24. Bull, J.R.; Rowland, S.P.; Scherwitzl, E.B.; Scherwitzl, R.; Danielsson, K.G.; Harper, J. Real-World Menstrual Cycle Characteristics of More than 600,000 Menstrual Cycles. Npj Digit. Med. 2019, 2, 83. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Mumford, S.L.; Steiner, A.Z.; Pollack, A.Z.; Perkins, N.J.; Filiberto, A.C.; Albert, P.S.; Mattison, D.R.; Wactawski-Wende, J.; Schisterman, E.F. The Utility of Menstrual Cycle Length as an Indicator of Cumulative Hormonal Exposure. J. Clin. Endocrinol. Metab. 2012, 97, 1871–1879. [Google Scholar] [CrossRef] [PubMed]
  26. Gleeson, P.C.; Worsley, R.; Gavrilidis, E.; Nathoo, S.; Ng, E.; Lee, S.; Kulkarni, J. Menstrual Cycle Characteristics in Women with Persistent Schizophrenia. Aust. N. Z. J. Psychiatry 2016, 50, 481–487. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Zhu, J.; Chan, Y.M. Adult Consequences of Self-Limited Delayed Puberty. Pediatrics 2017, 139, e20163177. [Google Scholar] [CrossRef] [Green Version]
  28. Cohen, R.Z.; Seeman, M.V.; Gotowiec, A.; Kopala, L. Earlier Puberty as a Predictor of Later Onset of Schizophrenia in Women. Am. J. Psychiatry 1999, 156, 1059–1064. [Google Scholar] [CrossRef]
  29. Fassler, C.S.; Gutmark-Little, I.; Xie, C.; Giannini, C.M.; Chandler, D.W.; Biro, F.M.; Pinney, S.M. Sex Hormone Phenotypes in Young Girls and the Age at Pubertal Milestones. J. Clin. Endocrinol. Metab. 2019, 104, 6079–6089. [Google Scholar] [CrossRef]
  30. Brzezinski-Sinai, N.A.; Brzezinski, A. Schizophrenia and Sex Hormones: What Is the Link? Front. Psychiatry 2020, 11, 693. [Google Scholar] [CrossRef]
  31. Van Wingen, G.A.; Ossewaarde, L.; Bäckström, T.; Hermans, E.J.; Fernández, G. Gonadal Hormone Regulation of the Emotion Circuitry in Humans. Neuroscience 2011, 191, 38–45. [Google Scholar] [CrossRef]
  32. Lande, R.G.; Karamchandani, V. Chronic Mental Illness and the Menstrual Cycle. J. Am. Osteopath. Assoc. 2002, 102, 655–659. [Google Scholar] [PubMed]
  33. Ji, E.; Weickert, C.S.; Lenroot, R.; Kindler, J.; Skilleter, A.J.; Vercammen, A.; White, C.; Gur, R.E.; Weickert, T.W. Adjunctive Selective Estrogen Receptor Modulator Increases Neural Activity in the Hippocampus and Inferior Frontal Gyrus during Emotional Face Recognition in Schizophrenia. Transl. Psychiatry 2016, 6, e795. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Usall, J.; Huerta-Ramos, E.; Labad, J.; Cobo, J.; Núñez, C.; Creus, M.; Parés, G.G.; Cuadras, D.; Franco, J.; Miquel, E.; et al. Raloxifene as an Adjunctive Treatment for Postmenopausal Women with Schizophrenia: A 24-Week Double-Blind, Randomized, Parallel, Placebo-Controlled Trial. Schizophr. Bull. 2016, 42, 309–317. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Kulkarni, J.; Butler, S.; Riecher-Rössler, A. Estrogens and SERMS as Adjunctive Treatments for Schizophrenia. Front. Neuroendocrinol. 2019, 53, 100743. [Google Scholar] [CrossRef]
  36. Richter, P.; Werner, J.; Heerlein, A.; Kraus, A.; Sauer, H. On the Validity of the Beck Depression Inventory. Psychopathology 1998, 31, 160–168. [Google Scholar] [CrossRef]
  37. Beck, A.T.; Steer, R.A.; Carbin, M.G. Psychometric Properties of the Beck Depression Inventory: Twenty-Five Years of Evaluation. Clin. Psychol. Rev. 1988, 8, 77–100. [Google Scholar] [CrossRef]
  38. Wang, Y.-P.; Gorenstein, C. Psychometric Properties of the Beck Depression Inventory-II: A Comprehensive Review. Rev. Bras. Psiquiatr. 2013, 35, 416–431. [Google Scholar] [CrossRef] [Green Version]
  39. Drake, R.; Haddock, G.; Tarrier, N.; Bentall, R.; Lewis, S. The Psychotic Symptom Rating Scales (PSYRATS): Their Usefulness and Properties in First Episode Psychosis. Schizophr. Res. 2007, 89, 119–122. [Google Scholar] [CrossRef]
  40. Kay, S.R.; Fiszbein, A.; Opler, L.A. The Positive and Negative Syndrome Scale (PANSS) for Schizophrenia. Schizophr. Bull. 1987, 13, 261–276. [Google Scholar] [CrossRef]
  41. Peralta, V.; Cuesta, M.J. Psychometric Properties of the Positive and Negative Syndrome Scale (PANSS) in Schizophrenia. Psychiatry Res. 1994, 53, 31–40. [Google Scholar] [CrossRef]
  42. Jensen, A.R. Scoring the Stroop Test. Acta Psychol. 1965, 24, 398–408. [Google Scholar] [CrossRef]
  43. Siegrist, M. Test-Retest Reliability of Different Versions of the Stroop Test. J. Psychol. 1997, 131, 299–306. [Google Scholar] [CrossRef]
  44. Stroop, J.R. Studies of Interference in Serial Verbal Reactions. J. Exp. Psychol. Gen. 1993, 121, 15–23. [Google Scholar] [CrossRef]
  45. Luna-Lario, P.; Peña, J.; Ojeda, N. Comparación de La Escala de Memoria de Wechsler-Iii y El Test de Aprendizaje Verbal España-Complutense En El Daño Cerebral Adquirido: Validez de Constructo y Validez Ecológica. Rev. Neurol. 2017, 64, 353–361. [Google Scholar] [CrossRef] [Green Version]
  46. Nieto, A.; Hernández-Rodríguez, E.; Hernández-Torres, A.; Velasco Rodriguez-Solis, P.; Hess-Medler, S.; Machado-Fernández, A.; Molina Rodríguez, Y.; Barroso, J. Versión Paralela Del Test de Aprendizaje Verbal España-Complutense (TAVEC). Rev. Neurol. 2014, 58, 95. [Google Scholar]
  47. Benedet, M.J.; Alejandre, M.Á. TAVEC Test de Aprendizaje Verbal España-Complutense 2. a Edición (Revisada); TEA Ediciones: Madrid, Spain, 2014. [Google Scholar]
  48. Greve, K.W.; Stickle, T.R.; Love, J.M.; Bianchini, K.J.; Stanford, M.S. Latent Structure of the Wisconsin Card Sorting Test: A Confirmatory Factor Analytic Study. Arch. Clin. Neuropsychol. 2005, 20, 355–364. [Google Scholar] [CrossRef] [Green Version]
  49. Gil, D.; Fernández-Modamio, M.; Bengochea, R.; Arrieta, M. Adaptación Al Español de La Prueba de Teoría de La Mente. Rev. Psiquiatr. Salud Ment. 2012, 5, 79–88. [Google Scholar] [CrossRef]
  50. Pinkham, A.E.; Penn, D.L.; Green, M.F.; Harvey, P.D. Social Cognition Psychometric Evaluation: Results of the Initial Psychometric Study. Schizophr. Bull. 2016, 42, 494–504. [Google Scholar] [CrossRef] [Green Version]
  51. Baron-Cohen, S.; Wheelwright, S.; Jolliffe, T. Is There a “Language of the Eyes”? Evidence from Normal Adults, and Adults with Autism or Asperger Syndrome. Vis. Cogn. 1997, 4, 311–331. [Google Scholar] [CrossRef]
  52. Huerta-Ramos, E.; Ferrer-Quintero, M.; Gómez-Benito, J.; González-Higueras, F.; Cuadras, D.; Del Rey-Mejías, A.L.; Usall, J.; Ochoa, S. Translation and Validation of Baron Cohen’s Face Test in a General Population from Spain. Actas Esp. Psiquiatr. 2021, 49, 106–113. [Google Scholar]
  53. Kinderman, P.; Bentall, R.P. Internal, Personal, and Situational Attributions Questionnaire. Pers. Individ. Dif. 1996, 20, 261–264. [Google Scholar] [CrossRef]
  54. Mizrahi, R.; Addington, J.; Remington, G.; Kapur, S. Attribution Style as a Factor in Psychosis and Symptom Resolution. Schizophr. Res. 2008, 104, 220–227. [Google Scholar] [CrossRef]
  55. Gutiérrez-Zotes, J.A.; Valero, J.; Cortés, M.J.; Labad, A.; Ochoa, S.; Ahuir, M.; Carlson, J.; Bernardo, M.; Cañizares, S.; Escartin, G. Adaptación Española de La Escala de Insight Cognitivo de Beck (EICB) En Esquizofrénicos. Actas Esp. Psiquiatr. 2012, 40, 2–9. [Google Scholar] [PubMed]
  56. Churchill, G.A. Marketing Research: Methodological Foundations; Thomson South-Western Publishers: Mason, OH, USA, 2004. [Google Scholar]
  57. Bender, R.; Lange, S. Adjusting for Multiple Testing--When and How? J. Clin. Epidemiol. 2001, 54, 343–349. [Google Scholar] [CrossRef]
  58. Kumar, N.; Debruille, J.B. Semantics and N400: Insights for Schizophrenia. J. Psychiatry Neurosci. 2004, 29, 89–98. [Google Scholar]
  59. Minzenberg, M.J.; Ober, B.A.; Vinogradov, S. Semantic Priming in Schizophrenia: A Review and Synthesis. J. Int. Neuropsychol. Soc. 2002, 8, 699–720. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  60. Crider, A.; Pillai, A. Estrogen Signaling as a Therapeutic Target in Neurodevelopmental Disorders. J. Pharmacol. Exp. Ther. 2017, 360, 48–58. [Google Scholar] [CrossRef] [Green Version]
  61. Hoff, A.L.; Kremen, W.S.; Wieneke, M.H.; Lauriello, J.; Blankfeld, H.M.; Faustman, W.O.; Csernansky, J.G.; Nordahl, T.E. Association of Estrogen Levels with Neuropsychological Performance in Women with Schizophrenia. Am. J. Psychiatry 2001, 158, 1134–1139. [Google Scholar] [CrossRef]
  62. Ko, Y.-H.; Joe, S.-H.; Cho, W.; Park, J.-H.; Lee, J.-J.; Jung, I.-K.; Kim, L.; Kim, S.-H. Estrogen, Cognitive Function and Negative Symptoms in Female Schizophrenia. Neuropsychobiology 2006, 53, 169–175. [Google Scholar] [CrossRef]
  63. Stoffel-Wagner, B.; Watzka, M.; Schramm, J.; Bidlingmaier, F.; Klingmüller, D. Expression of CYP19 (Aromatase) MRNA in Different Areas of the Human Brain. J. Steroid Biochem. Mol. Biol. 1999, 70, 237–241. [Google Scholar] [CrossRef]
  64. Brann, D.W.; Lu, Y.; Wang, J.; Zhang, Q.; Thakkar, R.; Sareddy, G.R.; Pratap, U.P.; Tekmal, R.R.; Vadlamudi, R.K. Brain-Derived Estrogen and Neural Function. Neurosci. Biobehav. Rev. 2022, 132, 793–817. [Google Scholar] [CrossRef] [PubMed]
  65. Boss, L.; Kang, D.H.; Marcus, M.; Bergstrom, N. Endogenous Sex Hormones and Cognitive Function in Older Adults: A Systematic Review. West. J. Nurs. Res. 2014, 36, 388–426. [Google Scholar] [CrossRef] [PubMed]
  66. García-Mieres, H.; Usall, J.; Feixas, G.; Ochoa, S. Placing Cognitive Rigidity in Interpersonal Context in Psychosis: Relationship With Low Cognitive Reserve and High Self-Certainty. Front. Psychiatry 2020, 11, 594840. [Google Scholar] [CrossRef] [PubMed]
  67. García-Mieres, H.; Villaplana, A.; López-Carrilero, R.; Grasa, E.; Barajas, A.; Pousa, E.; Feixas, G.; Ochoa, S. The Role of Personal Identity on Positive and Negative Symptoms in Psychosis: A Study Using the Repertory Grid Technique. Schizophr. Bull. 2020, 46, 572–580. [Google Scholar] [CrossRef] [PubMed]
  68. Garety, P.A.; Freeman, D. The Past and Future of Delusions Research: From the Inexplicable to the Treatable. Br. J. Psychiatry 2013, 203, 327–333. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  69. Savla, G.N.; Vella, L.; Armstrong, C.C.; Penn, D.L.; Twamley, E.W. Deficits in Domains of Social Cognition in Schizophrenia: A Meta-Analysis of the Empirical Evidence. Schizophr. Bull. 2013, 39, 979–992. [Google Scholar] [CrossRef]
  70. Rubio-Abadal, E.; Usall, J.; Barajas, A.; Carlson, J.; Iniesta, R.; Huerta-Ramos, E.; Baños, I.; Dolz, M.; Sánchez, B.; Ochoa, S.; et al. Relationship between Menarche and Psychosis Onset in Women with First Episode of Psychosis. Early Interv. Psychiatry 2016, 10, 419–425. [Google Scholar] [CrossRef]
  71. Colich, N.L.; Platt, J.M.; Keyes, K.M.; Sumner, J.A.; Allen, N.B.; Mclaughlin, K.A. Earlier Age at Menarche as a Transdiagnostic Mechanism Linking Childhood Trauma with Multiple Forms of Psychopathology in Adolescent Girls. Psychol. Med. 2020, 50, 1090–1098. [Google Scholar] [CrossRef]
  72. Yermachenko, A.; Dvornyk, V. Nongenetic Determinants of Age at Menarche: A Systematic Review. Biomed. Res. Int. 2014, 2014, 371583. [Google Scholar] [CrossRef]
  73. Huerta-Ramos, E.; Iniesta, R.; Ochoa, S.; Cobo, J.; Miquel, E.; Roca, M.; Serrano-Blanco, A.; Teba, F.; Usall, J. Effects of Raloxifene on Cognition in Postmenopausal Women with Schizophrenia: A Double-Blind, Randomized, Placebo-Controlled Trial. Eur. Neuropsychopharmacol. 2014, 24, 223–231. [Google Scholar] [CrossRef]
  74. Gurvich, C.; Gavrilidis, E.; Worsley, R.; Hadaib, A.; Thomas, N.; Kulkarni, J. Menstrual Cycle Irregularity and Menopause Status Influence Cognition in Women with Schizophrenia. Psychoneuroendocrinology 2018, 96, 173–178. [Google Scholar] [CrossRef] [PubMed]
Table 1. Questionnaires.
Table 1. Questionnaires.
Symptom Evaluation
  • The Beck Depression Inventory (BDI) was used to evaluate depressive symptoms as it has a high internal consistency and content validity. Higher scores indicate worse symptomatology [36,37,38];
  • The Psychotic Symptom Rating Scales (PSYRATS) was used to assess the severity of hallucinations and delusions in psychotic patients as it has demonstrated its validity as a complement in order to evaluate these dimensions. Higher scores indicate a greater presence of hallucinations and delusions [39];
  • The Positive and Negative Syndrome Scale (PANSS) is a semi-structured interview that allows for differentiating between positive, negative, and general symptoms. Higher scores mean a greater symptom severity [40,41].
Cognitive Evaluation
  • The Stroop Test was used for its reliability in evaluating executive functioning, measuring cognitive inhibition, and flexibility [42,43,44];
  • The Test de Aprendizaje Verbal España-Complutense (TAVEC), the Spanish version of the California Verbal Learning Test, assesses learning capacity, memory domains, and strategies used in addition to counting with reliability and validity. Higher scores indicate a better performance [45,46,47];
  • The Wisconsin Card Sorting Test (WSCT) is an executive functioning test used to evaluate problem solving and the ability to change tasks and response maintenance, and it measures these constructs well. A good development on this test is reflected by high scores [48].
Social Cognition Evaluation
  • The Hinting Task, used to evaluate the theory of mind, was chosen because of its strong psychometric properties. In our study, we used the abbreviated version; the higher the punctuation, the higher this ability [49,50];
  • The Emotion Recognition Face Test consists of a set of different pictures that represent different emotions and the patient must choose between two options. We selected this test because of its reliability in detecting deficits, even though it reaches ceiling performance scores [51,52];
  • The Internal, Situational, and Personal Attributions Questionnaire (IPSAQ), which has supported internal reliability [53], is used to describe the causal locus of the thinking of a person. High results reflect the attributional style they tend to use and whether it is a personalizing or externalizing bias style [54].
Metacognitive Evaluation
  • The Beck Cognitive Insight Scale (BCIS) is a self-assessed scale that evaluates the capacity of the patient to think about their own behavior and includes two scales: self-certainty and self-reflectivity. The higher the punctuations obtained on each scale, the more developed their capacity. This scale was chosen because its assessment is based on good psychometric properties [55].
Table 2. Sociodemographic characteristics of the sample.
Table 2. Sociodemographic characteristics of the sample.
VariablesCategoriesN%
Marital statusSingle3276.2
Married or living with a partner49.5
Separated49.5
Divorced12.4
Widowed12.4
Study levelPrimaryIncomplete12.4
Complete614.3
SecondaryIncomplete716.7
Complete1126.2
UniversityIncomplete614.3
Complete1126.2
Working situationActive occupied511.9
Active unemployed1228.6
Student614.3
Housework24.8
Pensioner24.8
Permanent or temporary sick leave614.3
Inactive921.4
Principal diagnosticSchizophrenia921.4
Unspecified psychotic disorder1126.2
Schizoaffective disorder819.0
Delusional disorder49.5
Brief psychotic disorder511.9
Schizophreniform disorder511.9
Menstrual cycle description<28 days1535.7
28–30 days2047.6
>30 days511.9
Age at menarche9–12 years1228.6
13 years2150.0
14–16 years921.4
Difference in age at menarche and age of symptom onset0–5.99 years819.0
6–19.99 years2047.6
>20 years1433.3
Table 3. Relationship between cycle length and symptoms, cognition, social cognition, and metacognition.
Table 3. Relationship between cycle length and symptoms, cognition, social cognition, and metacognition.
<28 Days28–30 Days>30 Daysp-ValuePartial Eta Squared
MSDMSDMSD
SymptomsBDI14.877.4315.0011.2013.408.170.9440.003
PSYRATSHallucinations1.625.825.009.445.2011.630.5230.037
Delusions9.007.204.455.664.204.920.1070.120
PANSS: positive13.737.3513.404.1612.005.240.8390.009
PANSS: negative13.804.5113.856.4315.005.050.9090.005
PANSS: general29.277.2428.759.7528.209.580.9690.002
CognitionSTROOPWord44.8711.8242.009.5239.808.260.5770.031
Color40.938.6534.897.5435.407.470.0960.125
Word–color49.9313.8040.1110.7340.408.650.0590.149
Interference56.6710.5350.726.3750.406.430.1060.120
TAVECShort-term free recall44.6411.9038.1311.5636.5416.210.2450.075
Short-term recall with keys43.7111.5637.8315.0233.2214.250.2660.071
Long-term free recall43.7310.7639.4216.0935.5916.420.4880.039
Long-term recall with keys41.7712.6736.2015.5032.7515.890.3860.052
Semantic strategy on short-term recall with keys50.3910.5042.736.9443.819.220.0460.158
Semantic strategy on long-term recall with keys48.4810.1042.268.2243.969.820.1560.098
Serial strategy on short-term recall with keys44.190.5250.046.5147.464.070.0050.256
Serial strategy on long-term recall with keys45.604.1253.3410.8347.465.730.0310.176
Perseverations44.487.8249.329.0356.5711.240.0350.110
Total intrusions on recall with keys52.6513.1749.1110.7054.9121.330.5980.028
Total intrusions on free recall49.578.2845.594.8547.499.520.2680.071
Hits on recognition 48.9311.8943.7616.0441.5220.270.5110.037
WSCTHits 75.0011.7070.398.2875.7515.710.4060.053
Total errors45.437.5040.616.0044.006.220.1350.100
Perseverative errors46.299.1940.448.2646.755.320.1220.120
Non-perseverative errors44.577.4741.225.9740.508.390.3360.064
Social cognitionHinting task1.680.361.700.241.730.280.9300.004
Emotion recognition facial test18.331.1117.651.4217.201.640.1830.088
IPSAQExternalization bias2.473.831.003.883.003.160.4040.048
Personalizing bias0.890.501.260.681.450.880.1490.100
Metacognition BCISSelf-reflectivity 13.144.1914.506.9116.006.250.6290.025
Self-certainty7.643.546.903.2311.404.560.0490.155
Table 4. Relationship between the age at menarche and symptoms, cognition, social cognition, and metacognition.
Table 4. Relationship between the age at menarche and symptoms, cognition, social cognition, and metacognition.
9–12 Years13 Years14–16 Yearsp-ValuePartial Eta Squared
MSDMSDMSD
SymptomsBDI12.008.0720.4012.2615.568.530.0720.130
PSYRATSHallucinations3.377.088.9112.670.000.000.0630.142
Delusions4.805.849.277.734.895.270.1520.097
PANSS: positive11.953.3216.278.7313.003.120.0940.114
PANSS: negative13.555.8116.186.8714.564.390.4810.037
PANSS: general28.416.1532.3713.9827.895.690.4310.042
CognitionSTROOPWord40.827.8043.2512.2645.897.670.6480.023
Color37.368.4137.009.6838.335.480.9340.004
Word–color43.7513.1743.4513.3743.4410.270.9970.000
Interference53.3510.5654.007.4848.674.820.3410.056
TAVECShort-term free recall39.6014.2742.228.5639.1011.650.8160.011
Short-term recall with keys37.9715.4439.7512.3638.0515.010.9430.003
Long-term free recall38.6215.2542.6212.4239.7614.540.7570.015
Long-term recall with keys35.9315.4737.5415.1437.6215.930.9440.003
Semantic strategy on short-term recall with keys45.2410.7046.087.4245.318.240.9700.002
Semantic strategy on long-term recall with keys42.8410.8945.368.5845.988.100.6540.022
Serial strategy on short-term recall with keys46.995.2149.806.8546.833.630.3350.056
Serial strategy on long-term recall with keys50.7411.0650.227.2548.124.590.7680.014
Perseverations48.158.1050.1812.2046.118.600.6340.027
Total intrusions on recall with keys51.9612.4744.171.6356.9717.920.0710.130
Total intrusions on free recall48.597.6343.974.6848.376.480.1710.089
Hits on recognition42.3515.9548.838.6244.5119.790.5320.033
WSCTHits77.279.2871.269.5770.2513.080.7470.017
Total errors42.755.8245.208.3641.137.400.5690.032
Perseverative errors43.058.1645.309.6542.639.470.7630.015
Non-perseverative errors42.255.3445.208.3540.508.140.3350.061
Social cognitionHinting task1.700.281.680.281.700.360.9880.001
Emotion recognition facial test17.911.3117.451.4417.781.640.6870.019
IPSAQExternalization bias1.954.022.002.930.334.210.5270.032
Personalizing bias1.010.541.070.611.680.820.0300.168
MetacognitionBCISSelf-reflectivity14.146.6614.275.8314.754.270.9700.002
Self-certainty8.503.807.553.566.634.000.4650.039
Table 5. Relationship between the difference in age at menarche and age of onset of psychosis and symptoms, cognition, social cognition, and metacognition.
Table 5. Relationship between the difference in age at menarche and age of onset of psychosis and symptoms, cognition, social cognition, and metacognition.
0–5.99 Years6–19.99 Years>20 Yearsp-ValuePartial Eta Squared
MSDMSDMSD
SymptomsBDI16.008.5015.4510.9113.158.980.7570.015
PSYRATSHallucinations5.7110.364.8010.052.175.130.6350.025
Delusions3.886.155.856.787.836.120.4080.047
PANSS: positive13.753.6613.956.8312.143.920.6250.024
PANSS: negative14.504.5415.756.9712.574.270.2990.060
PANSS: general29.636.5730.8511.3926.934.340.4450.041
CognitionSTROOPWord36.577.6646.378.6642.1411.910.0820.127
Color35.004.8037.898.3737.939.970.7170.018
Word–color42.578.7243.1610.7644.7116.070.9150.005
Interference54.007.0949.476.5555.7911.170.1110.112
TAVECShort-term free recall32.9817.0139.6210.8244.6310.180.1120.109
Short-term recall with keys28.7316.9437.6613.9644.4910.800.0500.146
Long-term free recall28.7418.6039.4912.8946.1910.150.0240.179
Long-term recall with keys26.6416.4136.1015.5942.6811.380.0660.133
Semantic strategy on short-term recall with keys42.729.7445.558.9046.769.760.6480.023
Semantic strategy on long-term recall with keys39.5710.6045.339.5944.929.240.3820.049
Serial strategy on short-term recall with keys46.743.3447.804.1748.067.700.8720.007
Serial strategy on long-term recall with keys50.187.9948.785.1851.7413.060.6450.023
Perseverations50.059.9949.899.6645.008.230.2820.073
Total intrusions on recall with keys63.3420.5847.488.5849.779.930.0130.204
Total intrusions on free recall52.0510.5045.984.8846.836.660.1240.104
Hits on recognition31.8325.3248.169.7845.7912.990.0430.153
WSCTHits72.3312.7271.849.4074.3811.440.7990.013
Total errors39.676.0244.007.4043.236.330.4990.039
Perseverative errors43.338.8243.589.1343.628.580.9980.000
Non-perseverative errors36.176.0844.746.3042.626.490.0240.193
Social cognition Hinting task1.810.241.620.281.730.330.2760.065
Emotion recognition facial test17.381.4117.751.5918.001.110.6100.025
IPSAQExternalization bias0.884.641.253.432.573.840.5110.034
Personalizing bias1.390.881.220.710.980.380.3700.051
Metacognition BCISSelf-reflectivity16.256.7814.684.7512.646.810.3690.051
Self-certainty8.884.617.583.497.713.790.7110.018
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Barrau-Sastre, P.; Birulés, I.; Verdaguer-Rodríguez, M.; López-Carrilero, R.; Ferrer-Quintero, M.; García-Mieres, H.; Díaz-Cutraro, L.; Grasa, E.; Pousa, E.; Lorente, E.; et al. Influence of Menstrual Cycle Length and Age at Menarche on Symptoms, Cognition, Social Cognition, and Metacognition in Patients with First-Episode Psychosis. Women 2022, 2, 135-146. https://0-doi-org.brum.beds.ac.uk/10.3390/women2020015

AMA Style

Barrau-Sastre P, Birulés I, Verdaguer-Rodríguez M, López-Carrilero R, Ferrer-Quintero M, García-Mieres H, Díaz-Cutraro L, Grasa E, Pousa E, Lorente E, et al. Influence of Menstrual Cycle Length and Age at Menarche on Symptoms, Cognition, Social Cognition, and Metacognition in Patients with First-Episode Psychosis. Women. 2022; 2(2):135-146. https://0-doi-org.brum.beds.ac.uk/10.3390/women2020015

Chicago/Turabian Style

Barrau-Sastre, Paula, Irene Birulés, Marina Verdaguer-Rodríguez, Raquel López-Carrilero, Marta Ferrer-Quintero, Helena García-Mieres, Luciana Díaz-Cutraro, Eva Grasa, Esther Pousa, Ester Lorente, and et al. 2022. "Influence of Menstrual Cycle Length and Age at Menarche on Symptoms, Cognition, Social Cognition, and Metacognition in Patients with First-Episode Psychosis" Women 2, no. 2: 135-146. https://0-doi-org.brum.beds.ac.uk/10.3390/women2020015

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