Journal of Personalized Medicine

Research

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13 pages, 1814 KiB

Open AccessFeature PaperArticle

Longitudinal Association of Universal Screening and Treatment for Major Depressive Disorder with Survival in Cancer Patients

by Yung-Chieh Yen, Chin-Yu Huang, Hsue-Wei Chan, You-Yu Wang, Te-Chang Changchien, Deng-Wu Wang, Po-Chun Lin, Ting-Ting Chang and Yu-Wen Chiu

J. Pers. Med. 2022, 12(8), 1213; https://doi.org/10.3390/jpm12081213 - 26 Jul 2022

Cited by 3 | Viewed by 1360

Abstract

Evidence for clinical screening and intervention for depression in cancer and the effect of this intervention on cancer prognosis is suboptimal. This study substantialized a complete model with universal screening and intervention for major depressive disorder (MDD) and explored its effect on survival [...] Read more.

Evidence for clinical screening and intervention for depression in cancer and the effect of this intervention on cancer prognosis is suboptimal. This study substantialized a complete model with universal screening and intervention for major depressive disorder (MDD) and explored its effect on survival in patients. This longitudinal study recruited cancer patients routinely screened for MDD with a two-stage model. Data including sex, age, cancer diagnosis, first diagnosis date, date of death, cancer stage, and MDD diagnosis and treatment were collected from medical records and the national registration system for cancer. Kaplan–Meier’s survival analysis and the Cox proportional hazards regression model were applied to analyze the effects of associated factors on survival. Further subgroup analysis for 14 types of cancer primary site was also performed. Overall, the hazard for patients adhering to psychiatric treatment for MDD before cancer diagnosis was not statistically different from that for patients without MDD (hazard ratio (HR) = 1.061, 95% CI: 0.889–1.267, p = 0.512). The hazard for patients adhering to psychiatric treatment after cancer diagnosis was significantly lower than that for patients without MDD (HR = 0.702, 95% CI: 0.607–0.812, p < 0.001). Those who were diagnosed with MDD after cancer diagnosis and adhered poorly to psychiatric treatment had the greatest hazard (HR = 1.829, 95% CI: 1.687–1.984, p < 0.001). The effect of intervention for MDD varied across different primary cancer types. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

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11 pages, 525 KiB

Open AccessArticle

Effectiveness of More Personalized, Case-Managed, and Multicomponent Treatment for Patients with Severe Schizophrenia Compared to the Standard Treatment: A Ten-Year Follow-Up

by Juan J. Fernández-Miranda, Silvia Díaz-Fernández and Francisco López-Muñoz

J. Pers. Med. 2022, 12(7), 1101; https://doi.org/10.3390/jpm12071101 - 04 Jul 2022

Cited by 6 | Viewed by 1764

Abstract

Case management is a model of personalized intervention in people with severe mental illness. To explore the treatment adherence and effectiveness of patients with severe schizophrenia (Clinical Global Impression Severity, CGI-S ≥ 5) undergoing treatment in a community-based, case-managed program (CMP) with an [...] Read more.

Case management is a model of personalized intervention in people with severe mental illness. To explore the treatment adherence and effectiveness of patients with severe schizophrenia (Clinical Global Impression Severity, CGI-S ≥ 5) undergoing treatment in a community-based, case-managed program (CMP) with an integrated pharmacological and psychosocial approach compared with the standard treatment, an observational, ten-year follow-up study was conducted on patients treated in mental health units (MHUs) or a CMP (n = 688). Treatment discontinuation, hospitalizations, suicide attempts, and antipsychotic (AP) medications were recorded. Clinical severity was assessed with the CGI-S. Adherence to the CMP was higher than adherence to standard treatment (p < 0.001). There were fewer hospitalizations and suicide attempts in the CMP (p < 0.001). The clinical severity decreased more in the CMP (p < 0.005). Long-acting injectable (LAI) antipsychotic medication was more closely related to these outcomes than oral antipsychotics (APs) were (p < 0.001). Patients with severe schizophrenia in an integrated CMP recorded higher treatment compliance and better outcomes compared with standard care. Treatment with LAI APs was linked to these outcomes. A personalized combination of case management and LAI AP medication was more effective in these patients than standard treatment and oral APs. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

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12 pages, 287 KiB

Open AccessArticle

Early and Late Luteal Executive Function, Cognitive and Somatic Symptoms, and Emotional Regulation of Women with Premenstrual Dysphoric Disorder

by Pai-Cheng Lin, Chih-Hung Ko and Ju-Yu Yen

J. Pers. Med. 2022, 12(5), 819; https://doi.org/10.3390/jpm12050819 - 18 May 2022

Cited by 3 | Viewed by 2283

Abstract

Objective: Cognitive and somatic symptoms were vital factors in developing personalized treatment of depressive disorder. The study aimed to evaluate the following: (1) the cognitive and somatic symptoms of premenstrual dysphoric disorder (PMDD) in the early luteal (EL) and later luteal (LL) phase; [...] Read more.

Objective: Cognitive and somatic symptoms were vital factors in developing personalized treatment of depressive disorder. The study aimed to evaluate the following: (1) the cognitive and somatic symptoms of premenstrual dysphoric disorder (PMDD) in the early luteal (EL) and later luteal (LL) phase; and (2) their association with depression and functional impairment of PMDD. Methods: We prospectively evaluated executive function, emotion regulation, cognitive and somatic symptoms, and depression in the EL and LL phases in women with PMDD. Sixty-three women with PMDD and 53 healthy controls completed Simon’s task and questionnaire to assess emotion regulation, inattention, fatigue, insomnia, and depression. Results: Women with PMDD had a poor performance in Simon’s task during the LL phase. They were less likely to exercise cognitive reappraisal during EL and LL phases. Their cognitive reappraisal positively correlated with executive function and negatively associated with depression. In the LL phase, they also experience higher inattention, insomnia, and fatigue, which correlate with the depression and functional impairment of PMDD. Inattention is the most associated factor of PMDD and functional impairment in controlling depression. Conclusion: Executive function was impaired in women with PMDD during the LL phase. Its performance correlated positively with emotion regulation and negatively with depression. The association between inattention and PMDD functional impairment indicates that evaluation and intervention for cognitive impairment were essential in treating women with PMDD. Further studies were required to elucidate the possible etiology underlying these associations. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

17 pages, 3261 KiB

Open AccessArticle

by I-Chun Chen, Chia-Ling Chen, Chih-Hao Chang, Zuo-Cian Fan, Yang Chang, Cheng-Hsiu Lin and Li-Wei Ko

J. Pers. Med. 2022, 12(5), 731; https://doi.org/10.3390/jpm12050731 - 30 Apr 2022

Cited by 3 | Viewed by 2027

Abstract

This study used a wireless EEG system to investigate neural dynamics in preschoolers with ADHD who exhibited varying cognitive proficiency pertaining to working memory and processing speed abilities. Preschoolers with ADHD exhibiting high cognitive proficiency (ADHD-H, n = 24), those with ADHD exhibiting [...] Read more.

This study used a wireless EEG system to investigate neural dynamics in preschoolers with ADHD who exhibited varying cognitive proficiency pertaining to working memory and processing speed abilities. Preschoolers with ADHD exhibiting high cognitive proficiency (ADHD-H, n = 24), those with ADHD exhibiting low cognitive proficiency (ADHD-L, n = 18), and preschoolers with typical development (TD, n = 31) underwent the Conners’ Kiddie Continuous Performance Test and wireless EEG recording under different conditions (rest, slow-rate, and fast-rate task). In the slow-rate task condition, compared with the TD group, the ADHD-H group manifested higher delta and lower beta power in the central region, while the ADHD-L group manifested higher parietal delta power. In the fast-rate task condition, in the parietal region, ADHD-L manifested higher delta power than those in the other two groups (ADHD-H and TD); additionally, ADHD-L manifested higher theta as well as lower alpha and beta power than those with ADHD-H. Unlike those in the TD group, the delta power of both ADHD groups was enhanced in shifting from rest to task conditions. These findings suggest that task-rate-related neural dynamics contain specific neural biomarkers to assist clinical planning for ADHD in preschoolers with heterogeneous cognitive proficiency. The novel wireless EEG system used was convenient and highly suitable for clinical application. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

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17 pages, 810 KiB

Open AccessArticle

Predicting the Treatment Outcomes of Antidepressants Using a Deep Neural Network of Deep Learning in Drug-Naïve Major Depressive Patients

by Ping-Lin Tsai, Hui Hua Chang and Po See Chen

J. Pers. Med. 2022, 12(5), 693; https://doi.org/10.3390/jpm12050693 - 26 Apr 2022

Cited by 3 | Viewed by 2233

Abstract

Predicting the treatment response to antidepressants by pretreatment features would be useful, as up to 70–90% of patients with major depressive disorder (MDD) do not respond to treatment as expected. Therefore, we aim to establish a deep neural network (DNN) model of deep [...] Read more.

Predicting the treatment response to antidepressants by pretreatment features would be useful, as up to 70–90% of patients with major depressive disorder (MDD) do not respond to treatment as expected. Therefore, we aim to establish a deep neural network (DNN) model of deep learning to predict the treatment outcomes of antidepressants in drug-naïve and first-diagnosis MDD patients during severe depressive stage using different domains of signature profiles of clinical features, peripheral biochemistry, psychosocial factors, and genetic polymorphisms. The multilayer feedforward neural network containing two hidden layers was applied to build models with tenfold cross-validation. The areas under the curve (AUC) of the receiver operating characteristic curves were used to evaluate the performance of the models. The results demonstrated that the AUCs of the model ranged between 0.7 and 0.8 using a combination of different domains of categorical variables. Moreover, models using the extracted variables demonstrated better performance, and the best performing model was characterized by an AUC of 0.825, using the levels of cortisol and oxytocin, scales of social support and quality of life, and polymorphisms of the OXTR gene. A complex interactions model developed through DNN could be useful at the clinical level for predicting the individualized outcomes of antidepressants. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

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12 pages, 611 KiB

Open AccessArticle

A Multi-Center Study for the Development of the Taiwan Cognition Questionnaire (TCQ) in Major Depressive Disorder

by Yung-Chieh Yen, Nan-Ying Chiu, Tzung-Jeng Hwang, Tung-Ping Su, Yen-Kuang Yang, Cheng-Sheng Chen, Cheng-Ta Li, Kuan-Pin Su, Te-Jen Lai and Chia-Ming Chang

J. Pers. Med. 2022, 12(3), 359; https://doi.org/10.3390/jpm12030359 - 26 Feb 2022

Cited by 1 | Viewed by 2055

Abstract

Cognitive dysfunction is associated with functional impairment of patients with Major Depressive Disorder (MDD). The goals were to explore the associated factors of cognitive impairment in MDD and to develop and validate a brief and culture-relevant questionnaire, the Taiwan Cognition Questionnaire (TCQ), among [...] Read more.

Cognitive dysfunction is associated with functional impairment of patients with Major Depressive Disorder (MDD). The goals were to explore the associated factors of cognitive impairment in MDD and to develop and validate a brief and culture-relevant questionnaire, the Taiwan Cognition Questionnaire (TCQ), among patients with MDD. This was a cross-sectional, multi-center observational study of MDD patients in Taiwan. Participants of Group 1 from 10 centers contributed to the validation of the TCQ by their response and sociodemographics. The participants of Group 2 from one center received an objective cognitive assessment for clarification of the relationship between the TCQ score and its associated factors. In Group 1, 493 participants were recruited. As for Group 2, an extra 100 participants were recruited. The global Cronbach’s alpha for the TCQ was 0.908. According to the coordinates of the ROC curve, 9/10 was the ideal cut-off point. With the criteria, the sensitivity/specificity of the TCQ was 0.610/0.689. The TCQ score was positively associated with a history of being admitted to acute psychiatric care and the severity of depression and negatively associated with objective cognitive measures. The TCQ provides a reliable, valid, and convenient measure of subjective cognitive dysfunction in patients with MDD. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

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13 pages, 3640 KiB

Open AccessArticle

Effect of Bifidobacterium bifidum on Clinical Characteristics and Gut Microbiota in Attention-Deficit/Hyperactivity Disorder

by Liang-Jen Wang, Chia-Yu Yang, Ho-Chang Kuo, Wen-Jiun Chou, Ching-Shu Tsai and Sheng-Yu Lee

J. Pers. Med. 2022, 12(2), 227; https://doi.org/10.3390/jpm12020227 - 07 Feb 2022

Cited by 15 | Viewed by 4315

Abstract

This study aimed to examine whether probiotics supplements using Bifidobacterium bifidum (Bf-688) can improve clinical characteristics and gut microbiomes among patients with attention-deficit/hyperactivity disorder (ADHD). This open-label, single-arm trial consisted of 30 children aged 4–16 years who met the criteria for ADHD diagnosis. [...] Read more.

This study aimed to examine whether probiotics supplements using Bifidobacterium bifidum (Bf-688) can improve clinical characteristics and gut microbiomes among patients with attention-deficit/hyperactivity disorder (ADHD). This open-label, single-arm trial consisted of 30 children aged 4–16 years who met the criteria for ADHD diagnosis. Each subject took Bf-688, with one sachet in the morning and one in the evening (daily bacteria count 5 × 10⁹ CFUs), for 8 weeks. Patients’ clinical symptoms were assessed using the Swanson, Nolan, and Pelham Rating Scale (SNAP-IV). We collected stool samples at the baseline, the 8th week, and the 12th week for gut microbiota examination. During the 8-week Bf-688 supplement period, patients’ inattention symptoms and hyperactivity/impulsive symptoms improved, and their weights and BMIs increased. For gut microbiota, the Firmicutes to Bacteroidetes ratio (F/B ratio) decreased significantly. LEfSe analysis revealed that Firmicutes significantly decreased while Proteobacteria significantly increased during the 8-week treatment period. After Bf-688 was discontinued for 4 weeks (12 weeks from baseline), Bacteroidota significantly decreased and Shigella significantly increased. The probiotic Bf-688 supplement was associated with an improvement of clinical symptoms and with weight gain among ADHD children. Furthermore, gut microbiota composition was significantly altered by the Bf-688 supplement. A future randomized control trial is warranted to verify these findings. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

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11 pages, 274 KiB

Open AccessArticle

Plasma BDNF and Cytokines Correlated with Protein Biomarkers for Bipolar II Disorder

by Sheng-Yu Lee, Tzu-Yun Wang, Ru-Band Lu, Liang-Jen Wang, Cheng-Ho Chang, Yung-Chih Chiang, Chih-Chuan Pan and Kuo-Wang Tsai

J. Pers. Med. 2021, 11(12), 1282; https://doi.org/10.3390/jpm11121282 - 02 Dec 2021

Cited by 4 | Viewed by 1623

Abstract

We have previously identified five candidate proteins (matrix metallopeptidase 9 (MMP9), phenylalanyl-TRNA synthetase subunit beta (FARSB), peroxiredoxin 2 (PRDX2), carbonic anhydrase 1 (CA-1), and proprotein convertase subtilisin/kexin Type 9 (PCSK9)) as potential biomarkers for bipolar II disorder (BD-II). These candidate proteins have been [...] Read more.

We have previously identified five candidate proteins (matrix metallopeptidase 9 (MMP9), phenylalanyl-TRNA synthetase subunit beta (FARSB), peroxiredoxin 2 (PRDX2), carbonic anhydrase 1 (CA-1), and proprotein convertase subtilisin/kexin Type 9 (PCSK9)) as potential biomarkers for bipolar II disorder (BD-II). These candidate proteins have been associated with neuroprotective factors (BDNF) and inflammatory factors (cytokines, C-reactive protein (CRP), and tumor necrosis factor-α (TNF-α)). However, the correlations between these proteins with plasma BDNF and inflammatory factors remain unknown. We recruited a total of 185 patients with BD-II and 186 healthy controls. Plasma levels of candidate proteins, BDNF, cytokines (TNF-α, CRP, and interleukin-8 (IL-8)) were assessed from each participant. The correlations between levels of candidate proteins, BDNF, and cytokines were analyzed. In the BD-II group, we found that the level of FARSB was positively correlated with the BDNF level (r = 0.397, p < 0.001) and IL-8 (r = 0.320, p < 0.001). The CA-1 level positively correlated with IL-8 (r = 0.318, p < 0.001). In the control group, we found that the FARSB level positively correlated with the BDNF level (r = 0.648, p < 0.001). The CA-1 level positively correlated with TNF-α (r = 0.231, p = 0.002), while the MMP-9 level positively correlated with the CRP level (r = 0.227, p = 0.002). Our results may help in clarifying the underlying mechanism of these candidate proteins for BD-II. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

16 pages, 818 KiB

Open AccessArticle

Prefrontal Lobe and Posterior Cingulate Cortex Activations in Patients with Major Depressive Disorder by Using Standardized Weighted Low-Resolution Electromagnetic Tomography

by I-Mei Lin, Hong-En Yu, Yi-Chun Yeh, Mei-Feng Huang, Kuan-Ta Wu, Chiao-Li Khale Ke, Pei-Yun Lin and Cheng-Fang Yen

J. Pers. Med. 2021, 11(11), 1054; https://doi.org/10.3390/jpm11111054 - 21 Oct 2021

Cited by 4 | Viewed by 2545

Abstract

Background: The differences in brain activity between patients with major depressive disorder (MDD) and healthy adults have been confirmed by functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and electroencephalography (EEG). The prefrontal lobe and posterior cingulate cortex (PCC) are related to [...] Read more.

Background: The differences in brain activity between patients with major depressive disorder (MDD) and healthy adults have been confirmed by functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and electroencephalography (EEG). The prefrontal lobe and posterior cingulate cortex (PCC) are related to emotional regulation in patients with MDD. However, the high cost and poor time resolution of fMRI and PET limit their clinical application. Recently, researchers have used high time resolution of standardized weighted low-resolution electromagnetic tomography (swLORETA) to investigate deep brain activity. This study aimed to convert raw EEG signals into swLORETA images and explore deep brain activity in patients with MDD and healthy adults. Methods: BrainMaster EEG equipment with a 19-channel EEG cap was used to collect resting EEG data with eyes closed for 5 min. NeuroGuide software was used to remove the EEG artifacts, and the swLORETA software was used to analyze 12,700 voxels of current source density (CSD) for 139 patients with MDD and co-morbid anxiety symptoms (mean age = 43.08, SD = 13.76; 28.78% were male) and 134 healthy adults (mean age = 40.60, SD = 13.52; 34.33% were male). Deep brain activity in the frontal lobe and PCC at different frequency bands was analyzed, including delta (1–4 Hz), theta (5–7 Hz), alpha (8–11 Hz), beta (12–24 Hz), beta1 (12–14 Hz), beta2 (15–17 Hz), beta3 (18–24 Hz), and high beta (25–29 Hz). Results: There was lower delta and theta and higher beta, beta1, beta2, beta3, and high-beta activity at the prefrontal lobe (dorsal medial prefrontal cortex [dmPFC], ventral medial prefrontal cortex [vmPFC], and dorsal lateral prefrontal cortex [dlPFC], ventral lateral prefrontal cortex [vlPFC], orbital frontal cortex [OFC]) and PCC in MDD patients compared with healthy adults. There was no significant difference in alpha activity between the two groups. Conclusion: This study indicates brain hyperactivity in the right prefrontal lobe (dlPFC and vmPFC) and PCC in patients with MDD with co-morbid anxiety symptoms, and the dlPFC and PCC were also related to emotion regulation in MDD. Inhibiting high-beta activity or restoring delta and theta activity to the normal range in the right frontal lobe and PCC may be possible in z-score neurofeedback protocols for patients with MDD in future studies. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

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Review

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33 pages, 428 KiB

Open AccessReview

Effectivity of (Personalized) Cognitive Behavioral Therapy for Insomnia in Mental Health Populations and the Elderly: An Overview

by Teus Mijnster, Gretha J. Boersma, Esther Meijer and Marike Lancel

J. Pers. Med. 2022, 12(7), 1070; https://doi.org/10.3390/jpm12071070 - 29 Jun 2022

Cited by 3 | Viewed by 3113

Abstract

Insomnia is very prevalent in psychiatry and is considered a transdiagnostic symptom of mental disorders. Yet, it is not only a consequence of a mental condition but may also exert detrimental effects on psychiatric symptom severity and therapeutic response; thus, adequate insomnia treatment [...] Read more.

Insomnia is very prevalent in psychiatry and is considered a transdiagnostic symptom of mental disorders. Yet, it is not only a consequence of a mental condition but may also exert detrimental effects on psychiatric symptom severity and therapeutic response; thus, adequate insomnia treatment is particularly important in psychiatric populations. The first choice of intervention is cognitive behavioral therapy for insomnia (CBT-I) as it is rather effective, also in the long run without side effects. It is offered in various forms, ranging from in-person therapy to internet-delivered applications. CBT-I protocols are typically developed for individuals with insomnia disorder without co-occurring conditions. For an optimal therapeutic outcome of CBT-I in individuals with comorbid mental disorders, adaptations of the protocol to tailor the treatment might be beneficial. Based on a literature search using major search engines (Embase; Medline; APA Psych Info; and Cochrane Reviews), this paper provides an overview of the effectiveness of the different CBT-I applications in individuals with diverse comorbid mental conditions and older adults and describes the functionality of CBT-I protocols that have been personalized to specific psychiatric populations, such as depression, substance abuse, and schizophrenia spectrum disorder. Finally, we discuss urgent needs for insomnia therapy targeted to improve both sleep and psychopathologies. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

13 pages, 1202 KiB

Open AccessReview

Progress in Personalized Psychiatric Therapy with the Example of Using Intranasal Oxytocin in PTSD Treatment

by Sandra Szafoni and Magdalena Piegza

J. Pers. Med. 2022, 12(7), 1067; https://doi.org/10.3390/jpm12071067 - 29 Jun 2022

Cited by 3 | Viewed by 1869

Abstract

Post-traumatic stress disorder (PTSD) is a severe mental disorder that results in the frequent coexistence of other diseases, lowers patients’ quality of life, and has a high annual cost of treatment. However, despite the variety of therapeutic approaches that exist, some patients still [...] Read more.

Post-traumatic stress disorder (PTSD) is a severe mental disorder that results in the frequent coexistence of other diseases, lowers patients’ quality of life, and has a high annual cost of treatment. However, despite the variety of therapeutic approaches that exist, some patients still do not achieve the desired results. In addition, we may soon face an increase in the number of new PTSD cases because of the current global situation—both the COVID-19 pandemic and the ongoing armed conflicts. Hence, in recent years, many publications have sought a new, more personalized treatment approach. One such approach is the administration of intranasal oxytocin (INOXT), which, due to its pleiotropic effects, seems to be a promising therapeutic option. However, the current findings suggest that it might only be helpful for a limited, strictly selected group of patients. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

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14 pages, 2875 KiB

Open AccessReview

Development of Digital Biomarkers of Mental Illness via Mobile Apps for Personalized Treatment and Diagnosis

by I-Ming Chen, Yi-Ying Chen, Shih-Cheng Liao and Yu-Hsuan Lin

J. Pers. Med. 2022, 12(6), 936; https://doi.org/10.3390/jpm12060936 - 06 Jun 2022

Cited by 5 | Viewed by 3526

Abstract

The development of precision psychiatry is largely based on multi-module measurements from the molecular, cellular, and behavioral levels, which are integrated to assess neurocognitive performances and clinically observed psychopathology. Nevertheless, quantifying mental activities and functions accurately and continuously has been a major difficulty [...] Read more.

The development of precision psychiatry is largely based on multi-module measurements from the molecular, cellular, and behavioral levels, which are integrated to assess neurocognitive performances and clinically observed psychopathology. Nevertheless, quantifying mental activities and functions accurately and continuously has been a major difficulty within this field. This article reviews the latest efforts that utilize mobile apps to collect human–smartphone interaction data and contribute towards digital biomarkers of mental illnesses. The fundamental principles underlying a behavioral analysis with mobile apps were introduced, such as ways to monitor smartphone use under different circumstances and construct long-term patterns and trend changes. Examples were also provided to illustrate the potential applications of mobile apps that gain further insights into traditional research topics in occupational health and sleep medicine. We suggest that, with an optimized study design and analytical approach that accounts for technical challenges and ethical considerations, mobile apps will enhance the systemic understanding of mental illnesses. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

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17 pages, 784 KiB

Open AccessEditor’s ChoiceReview

by Mirabela Romanescu, Valentina Buda, Adelina Lombrea, Minodora Andor, Ionut Ledeti, Maria Suciu, Corina Danciu, Cristina Adriana Dehelean and Liana Dehelean

J. Pers. Med. 2022, 12(6), 907; https://doi.org/10.3390/jpm12060907 - 31 May 2022

Cited by 17 | Viewed by 4890

Abstract

In the last decades, both animal and human studies have neglected female subjects with the aim of evading a theorized intricacy of feminine hormonal status. However, clinical experience proves that pharmacological response may vary between the two sexes since pathophysiological dissimilarities between men [...] Read more.

In the last decades, both animal and human studies have neglected female subjects with the aim of evading a theorized intricacy of feminine hormonal status. However, clinical experience proves that pharmacological response may vary between the two sexes since pathophysiological dissimilarities between men and women significantly influence the pharmacokinetics and pharmacodynamics of drugs. Sex-related differences in central nervous system (CNS) medication are particularly challenging to assess due to the complexity of disease manifestation, drugs’ intricate mechanisms of action, and lack of trustworthy means of evaluating the clinical response to medication. Although many studies showed contrary results, it appears to be a general tendency towards a certain sex-related difference in each pharmacological class. Broadly, opioids seem to produce better analgesia in women especially when they are administered for a prolonged period of time. On the other hand, respiratory and gastrointestinal adverse drug reactions (ADRs) following morphine therapy are more prevalent among female patients. Regarding antidepressants, studies suggest that males might respond better to tricyclic antidepressants (TCAs), whereas females prefer selective serotonin reuptake inhibitors (SSRI), probably due to their tolerance to particular ADRs. In general, studies missed spotting any significant sex-related differences in the therapeutic effect of antiepileptic drugs (AED), but ADRs have sex variations in conjunction with sex hormones’ metabolism. On the subject of antipsychotic therapy, women appear to have a superior response to this pharmacological class, although there are also studies claiming the opposite. However, it seems that reported sex-related differences regarding ADRs are steadier: women are more at risk of developing various side effects, such as metabolic dysfunctions, cardiovascular disorders, and hyperprolactinemia. Taking all of the above into account, it seems that response to CNS drugs might be occasionally influenced by sex as a biological variable. Nonetheless, although for each pharmacological class, studies generally converge to a certain pattern, opposite outcomes are standing in the way of a clear consensus. Hence, the fact that so many studies are yielding conflicting results emphasizes once again the need to address sex-related differences in pharmacological response to drugs. Full article

(This article belongs to the Special Issue Personalized Treatment and Diagnosis Strategies in Psychiatry)

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