Systematic Literature Review Of Studies Research Articles

The Awake Craniotomy: A Patient’s Experience and A Literature Review

We present a case report and a literature review of the awake craniotomy procedure for mass resection, with emphasis on the historical aspects, anatomical and surgical considerations, and, uniquely, a patient’s experience undergoing this procedure. This procedure is a safe and effective method for lesion resection when working in and around eloquent brain. We have described our process of guiding a patient through an awake craniotomy procedure and detailed the patient's experience in this study. We also conducted a systematic literature review of studies involving awake craniotomy over three years, 2018-2021. Lastly, we compared the methodology used by our institution and the current mostly used methods within the neurosurgical community. Several studies were identified using PubMed and Google Scholar. Awake craniotomy is a safe and effective method of achieving a high rate of resection of lesions located in and around the eloquent cortex with a low degree of postoperative neurological deficit.

The Efficacy and Safety of Laser and Electrosurgical Transurethral Procedures for the Treatment of BPO in High-Risk Patients: A Systematic Review.

ObjectiveTo compare efficacy and safety outcomes of GreenLight, Holmium and Thulium laser techniques with standard monopolar and bipolar transurethral resection of the prostate (TURP) in high-risk patients with lower urinary tract symptoms (LUTS) secondary to benign prostatic obstruction (BPO).MethodsWe conducted a systematic literature review of studies in patients undergoing BPO surgeries who may be considered high-risk for standard TURP, with higher risk defined as follows: large prostates (≥80 mL) and/or taking antithrombotic agents and/or urinary retention and/or age >80 years and/or significant comorbidity. Outcomes summarised included bleeding complications, re-intervention rates, hospital length of stay, and standard measures of disease and symptom severity for all available timepoints.ResultsA total of 276 studies of 32,722 patients reported relevant data. Studies were heterogeneous in methodology, population and outcomes reported. IPSS reduction, Qmax improvement and PVR were similar across all interventions. Mean values at baseline and after 12 months across interventions were 13.2−29 falling to 2.3−10.8 for IPSS, 0−19 mL/s increasing to 7.5−34.1 mL/s for Qmax and 41.4−954 mL falling to 5.1−138.3 mL for PVR. Laser treatments show some advantages compared with monopolar and bipolar TURP for some adverse events and safety parameters such as bleeding complications. Duration of hospital stay, reinterventions and recatheterisations were lower with GreenLight, HoLEP, Thulium lasers, and bipolar enucleation than TURP.ConclusionsLaser therapies are effective and well-tolerated treatment options in high-risk patients with BPO compared with monopolar or bipolar TURP. The advantageous safety profile of laser treatments means that patients with a higher bleeding risk should be offered laser surgery preferentially to mTURP or bTURP.

Towards the sustainability of small and medium software enterprises through the implementation of software process improvement: Empirical investigation

AbstractTo improve and sustain the quality of software products, software process improvement (SPI) is needed. Currently, small and medium software enterprises (SMSEs) represent a high proportion of companies around the world and become a cornerstone in the worldwide industry economy. These companies have realized that improving their process is crucial for success, but they are facing difficulties to implement it due to limited resources, limited knowledge, and time constraints. This study aimed to identify the sustainability success factors (SSFs) that have a positive impact on implementing SPI efforts in SMSEs. Data were collected through a systematic literature review (SLR) approach and quantitatively through a survey questionnaire. A list of 44 SSFs was identified during SLR and empirical study. Results illustrate that there is a positive correlation between the ranks obtained from both dataset (rs (44) = .548, ρ = .001). Therefore, there would be significant differences between the SSFs identified in both datasets. In conclusion, the top‐ranked factors can then be used to guide the SPI coordinators on where they should focus their attention to reach the desired SPI goals, which is crucial to deliver the software products and also facilitates in development of model for SPIs in the future.

Applications of deep learning for phishing detection: a systematic literature review.

Phishing attacks aim to steal confidential information using sophisticated methods, techniques, and tools such as phishing through content injection, social engineering, online social networks, and mobile applications. To avoid and mitigate the risks of these attacks, several phishing detection approaches were developed, among which deep learning algorithms provided promising results. However, the results and the corresponding lessons learned are fragmented over many different studies and there is a lack of a systematic overview of the use of deep learning algorithms in phishing detection. Hence, we performed a systematic literature review (SLR) to identify, assess, and synthesize the results on deep learning approaches for phishing detection as reported by the selected scientific publications. We address nine research questions and provide an overview of how deep learning algorithms have been used for phishing detection from several aspects. In total, 43 journal articles were selected from electronic databases to derive the answers for the defined research questions. Our SLR study shows that except for one study, all the provided models applied supervised deep learning algorithms. The widely used data sources were URL-related data, third party information on the website, website content-related data, and email. The most used deep learning algorithms were deep neural networks (DNN), convolutional neural networks, and recurrent neural networks/long short-term memory networks. DNN and hybrid deep learning algorithms provided the best performance among other deep learning-based algorithms. 72% of the studies did not apply any feature selection algorithm to build the prediction model. PhishTank was the most used dataset among other datasets. While Keras and Tensorflow were the most preferred deep learning frameworks, 46% of the articles did not mention any framework. This study also highlights several challenges for phishing detection to pave the way for further research.

Treatment Algorithm of Periprosthetic Femoral Fracturens.

Introduction. The ever-expanding indications for total hip arthroplasty are leading to more implants being placed in younger as well as in older patients with high functional demand. Also, prolonged life expectancy is contributing to an overall increment of periprosthetic femoral fractures. The Vancouver classification has been the most used for guiding the surgeon choice since its proposal in 1995. Fractures occurring over a hip femoral implant can be divided into intra-operative and post-operative PFFs, and their treatment depends on factors that may severely affect the outcome: level of fracture, implant stability, quality of bone stock, patients’ functional demand, age and comorbidities, and surgeon expertise. There are many different treatment techniques available which include osteosynthesis and revision surgery or a combination of both. The goals of surgical treatment are patients’ early mobilization, restoration of anatomical alignment and length with a stable prosthesis and maintenance of bone stock. Significance. The aim of this review is to describe the state-of-the-art treatment and outcomes in the management of PFFs. We performed a systematic literature review of studies reporting on the management of PFFs around hip stems and inter-prosthetic fractures identifying 45 manuscripts eligible for the analysis. Conclusions. PFFs present peculiar characteristic that must be considered and special features that must be addressed. Their management is complex due to the extreme variability of stem designs, the possibility of having cemented or uncemented stems, the difficulty in identifying the “real” level of the fracture and the actual stability of the stem. As a result, the definition of a standardized treatment is unlikely, thereby high expertise is fundamental for the surgical management of PPFs, so this kind of fractures should be treated only in specialized centres with both high volume of revision joint arthroplasty and trauma surgery.

Structural validity of the Eating Disorder Examination-Questionnaire: A systematic review.

ObjectiveThe main aim was to perform a systematic literature review of studies investigating the factor structure of the Eating Disorder Examination‐Questionnaire (EDE‐Q), a widely used measure of eating pathology. Secondary aims were to summarize the quality of reporting of latent variable (factor) analyses in these studies and review support for different factor solutions.MethodLiterature was identified through Scopus, Medline, PsycInfo, and ProQuest databases published up to February 23, 2022 and outreach via an international listserv. All studies published in English reporting factor analysis of the EDE‐Q were included with few restrictions. Sixty studies including 63,389 participants met inclusion criteria.ResultsThe originally proposed four‐factor solution received little empirical support, although few alternative models have been robustly evaluated. Items assessing shape and weight concerns frequently coalesce in factor solutions, suggesting that these constructs are closely related. Investigations of brief versions of the EDE‐Q have produced more consistent findings, suggesting that these measures, particularly a seven‐item version, might be useful alternatives to the full version. Quality of studies was reasonable, with important methodological elements of factor analysis often reported.DiscussionThe findings are of relevance to practitioners and researchers, suggesting that the “original” factor structure of the EDE‐Q should be reconsidered and that use of a seven‐item version is to be encouraged.Public SignificanceSelf‐report questionnaires are widely used in the assessment of disordered eating. The current study found that there is little consensus about the structure of a common measure of eating psychopathology. There is more consistent support for a brief, seven‐item, version assessing dietary restraint, body dissatisfaction, and overvaluation of weight and shape.

Systematic Literature Review of Studies Reviewing Third Party (Other) Customers in the Process of Service Failure and Recovery

Systematic Literature Review of Studies Reviewing Third Party (Other) Customers in the Process of Service Failure and Recovery

Identification of NF1 Frameshift Variants in Two Chinese Families With Neurofibromatosis Type 1 and Early-Onset Hypertension.

Background: Neurofibromatosis type 1 (NF-1) is a common autosomal dominant disorder caused by mutations in the NF1 gene. It is characterized by multiple café-au-lait macules, cutaneous neurofibromas, optic glioma, Lisch nodules, and axillary and inguinal freckling. The aim of this study was to investigate NF1 mutations in two Chinese families with NF-1 who presented with early-onset hypertension, and to determine the prevalence of hypertension associated with NF-1 to better understand this complication.Methods: Whole-exome sequencing was performed for the probands with NF-1 from two unrelated families. Possible pathogenic mutation was predicted by bioinformatic tools. Sanger sequencing was used to confirm candidate variants in all available individuals for familial co-segregation analysis. We also performed a systematic literature review of studies that reported the prevalence of hypertension in patients with NF-1.Results: In family 1, a recurrent mutation c.6789_6792delTTAC in NF1 was identified in the proband but in no other family members, indicating that this is a de novo mutation. In family 2, a novel mutation c.6934_6936delGCAinsTGCT in NF1 was detected in the proband and two other family members, which co-segregated with the disease phenotype within the family. Both mutations were predicted to be pathogenic by bioinformatic analysis. We found hypertension was a relatively common complication of NF-1, with a prevalence range of 6.1–23.4%. Ambulatory blood pressure monitoring is a stable method for detecting initial alterations of the blood pressure pattern, particularly for pre-hypertension.Conclusions: We identified one recurrent (c.6789_6792delTTAC) and one novel frame-shift mutation (c.6934_6936delGCAinsTGCT) in two unrelated families with NF-1 using whole-exome sequencing. In consideration of phenotypic heterogeneity in NF-1, genetic testing is a robust tool which helps early and accurate diagnosis. Because hypertension is not a rare complication of NF-1, routine screening for hypertension in patients with NF-1, especially children and adolescents, is important to avoid serious cardiovascular events.

Big Data COVID-19 Systematic Literature Review: Pandemic Crisis

The COVID-19 pandemic has frightened people worldwide, and coronavirus has become the most commonly used phrase in recent years. Therefore, there is a need for a systematic literature review (SLR) related to Big Data applications in the COVID-19 pandemic crisis. The objective is to highlight recent technological advancements. Many studies emphasize the area of the COVID-19 pandemic crisis. Our study categorizes the many applications used to manage and control the pandemic. There is a very limited SLR prospective of COVID-19 with Big Data. Our SLR study picked five databases: Science direct, IEEE Xplore, Springer, ACM, and MDPI. Before the screening, following the recommendation, Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) were reported for 893 studies from 2019, 2020 and until September 2021. After screening, 60 studies met the inclusion criteria through COVID-19 data statistics, and Big Data analysis was used as the search string. Our research’s findings successfully dealt with COVID-19 healthcare with risk diagnosis, estimation or prevention, decision making, and drug Big Data applications problems. We believe that this review study will motivate the research community to perform expandable and transparent research against the pandemic crisis of COVID-19.

Drivers and barriers to the deployment of pumped hydro energy storage applications: Systematic literature review

Storage technology is recognized as a critical enabler of a reliable future renewable energy network. There is growing acknowledgement of the potential viability of pumped hydro energy storage solutions, despite multiple barriers for large-scale installations. A plethora of articles have been published covering the drivers for and barriers to the widespread diffusion of pumped hydro energy storage, but the literature has yet to coherently categorise and rate the various reported drivers and barriers. Therefore, a systematic literature review of studies published between 2000 and 2020 was conducted using meta-analysis guidelines to analyse, synthesize and consolidate findings covering both the techno-environmental and socio-economic drivers for, and barriers to, the development of pumped hydro energy storage. The study ranked the significance of reported drivers and barriers as well as the lessons learned for both developed and developing countries. The top-ranked techno-environmental driving factor was grid resilience (i.e., grid balancing, energy time-shifting, etc.) and the top-ranked socio-economic driver was revenue generation and rural development (i.e., job and businesses opportunities, infrastructural development, etc.). In terms of barriers, the top ranked techno-environmental barrier was as the lack of good infrastructure (i.e., roads, transmission lines, etc.) near potential sites, and top ranked socio-economic barrier was securing the initial and ongoing capital requirements for a less understand investment category. Overall, this study synthesises and categorises the drivers and barriers to the development of pumped hydro energy storage. Study findings will be useful to both researchers and practitioners seeking to better direct resources and efforts to foster the development of pumped hydro energy in the future. • Reviewed studies between 2000-2020 to determine the PHES drivers and barriers. • Key drivers to PHES deployment are energy storage, revenue and renewables integration. • Key barriers to PHES development are high capital cost and absence of power lines. • Growing interest in closed-loop systems compared to open loop systems. • Feasibility studies using GIS-MCDM were the most reported method in studies.

Identification and prioritization of security challenges of big data on cloud computing based on SLR: A fuzzy‐TOPSIS analysis approach

AbstractNowadays, data is increasing exponentially, although cloud computing is an eminent approach for the organization, processing, and availability of data for organizational growth over the internet. Besides, a lot of advantages of cloud computing, yet it is suffered from security challenges, which affect big data while using cloud services on the internet. For this purpose, we conducted a detailed systematic literature review (SLR) study, to identify and capture the security challenges of big data on the cloud computing platform. Our research findings determine and develop a taxonomy, based on the prioritization of the security challenges of big data on cloud computing. We identified a total of 15 critical security challenges using the proposed SLR, with the frequency of each challenge >25%, and are further validated by the industrial specialists using a questionnaire survey study. The identified security challenges are data secrecy issue, geographical data location issue, unauthorized data access issue, lack of control, lack of data management, network‐level issues, data integrity issue, data recovery issue, lack of trust, data sharing issue, data availability, asset issues, legal amenabilities, lack of quality issues, and lack of consistency. The security challenges identified and captured through the SLR study are categorized into four levels, namely, steadiness, management, control, and eminence. Conclusively, we applied the fuzzy‐TOPSIS approach to prioritize and identify the significance of each identified security challenge for the big data usage on cloud computing. Based on our proposed approach, the “data secrecy issue” has been identified as the most prominent security challenge with the captured value of “0.765.” The fuzzy TOPSIS is an effective and innovative research approach in the field of computer science. It has been applied positively to other research areas to address and identify the fuzziness and uncertainty of multiple decision‐making glitches. The findings of the research paper will assist the software vendor organization when using the cloud platform for big data security. Also, using the proposed approach, software vendors can prioritize and analyze the uncertainty and ambiguousness among these security challenges.

A systematic literature review of studies estimating the risk factor attributable burden in Europe

Abstract Along with the computation of disability-adjusted life years (DALY), the Global Burden of Disease (GBD) study uses the comparative risk assessment method to estimate the burden attributable to risk factors (RF). The methodology used for GBD studies has undergone continuous improvements through the years and across many independent studies. The European burden of disease network launched a series of systematic literature reviews (SLR) to explore key assumptions used in the European burden of disease (BoD) assessments. The SLR will give an overview of existing studies, including those estimating the BoD attributable to RF and focus on the different computational approaches. The SLR will also help to identify ways to harmonize computational procedures to enhance the comparability of RF attributable burden. The SLR involved four parallel reviews: non-communicable diseases, communicable diseases, injuries and RF. For the latter, we used a search strategy with terms describing the population (GBD area “European region”) and terms specifically used in comparative risk assessments (comparative risk assessment [CRA], attributable mortality/burden/risk). Studies published between January 1990 and April 2020 were included, without language restrictions. The search strategy was run in PubMed, Web of Science, Cochrane, and Embase. OpenGrey, OAIster, CABDirect, WHO, and targeted public health agency websites were screened for indexed grey literature. In addition, burden-eu members were asked to supplement the list of publications with any material available in their national public health institutes. The title, abstract, and full-text screening resulted in the final inclusion of 114 publications. The list of publications includes peer-reviewed articles and reports showing a variability in CRA analysis (e.g. use of exposure-response function, relative risks) and other methodological choices. Further data extraction and analysis is in process and will be presented during the workshop.

Significant barriers to the adoption of the agricultural cooperative model of entrepreneurship: a literature review

PurposeLiterature contributions to agricultural cooperative (AC) entrepreneurship model are fragmented and show some significant limitations. The purpose of this paper is to identify the existing important barriers to this entrepreneurship model as well as to group them into respective themes.Design/methodology/approachA systematic literature review (SLR) of peer reviewed journal articles was carried out by the authors in well-known databases, such as Scopus, Emerald, ScienceDirect, Google Scholar, IDEAS/RePEc search and Web of Science. In total, 78 articles from 26 different countries during 2010–2019 were collected.FindingsA large number of important barriers are identified in the literature and meaningful dimensions of these barriers are also revealed.Practical implicationsThe study has important implications regarding the ways to improve the effectiveness of AC model. Researchers and practitioners can use the results presented in this study for further development of this model.Originality/valueThis study presents the important barriers in AC model in global scope analytically and groups them into meaningful themes, which significantly differentiate the present SLR study from those published so far.

Data Science Projects in Pharmaceutical Industry

The purpose of this paper is to discuss the relevance of data science in Medical Affairs (MA) functions in the pharmaceutical industry, where data is becoming more important for the execution of activities and strategic planning in the health industry. This study analyses pharmaceutical companies who have a data science strategy and the variables that can influence the definition of a data science strategy in pharma companies in opposite to other pharmaceutical companies without a data science strategy. The current paper is empirical and the research approach consists of verifying the characteristics and differences between those two types of pharmaceutical companies. A questionnaire specifically for this research was developed and applied to a sample of 280 pharma companies. The development and analysis of the questionnaire was based on a Systematic Literature Review of studies published up to (and including) 2017 through a database search and backward and forward snowballing. In total, we evaluated 2247 papers, of which 11 included specific data science methodologies criteria used in medical affairs departments. It was also made a quantitative analysis based on data from a questionnaire applied to a Pharma organization. The findings indicate that there is good evidence in the empirical relation between Data Science and the strategies of the organization.

Application-Aware Intrusion Detection: A Systematic Literature Review, Implications for Automotive Systems, and Applicability of AutoML

Modern and flexible application-level software platforms increase the attack surface of connected vehicles and thereby require automotive engineers to adopt additional security control techniques. These techniques encompass host-based intrusion detection systems (HIDSs) that detect suspicious activities in application contexts. Such application-aware HIDSs originate in information and communications technology systems and have a great potential to deal with the flexible nature of application-level software platforms. However, the elementary characteristics of known application-aware HIDS approaches and thereby the implications for their transfer to the automotive sector are unclear. In previous work, we presented a systematic literature review (SLR) covering the state of the art of application-aware HIDS approaches. We synthesized our findings by means of a fine-grained classification for each approach specified through a feature model and corresponding variant models. These models represent the approaches’ elementary characteristics. Furthermore, we summarized key findings and inferred implications for the transfer of application-aware HIDSs to the automotive sector. In this article, we extend the previous work by several aspects. We adjust the quality evaluation process within the SLR to be able to consider high quality conference publications, which results in an extended final pool of publications. For supporting HIDS developers on the task of configuring HIDS analysis techniques based on machine learning, we report on initial results on the applicability of AutoML. Furthermore, we present lessons learned regarding the application of the feature and variant model approach for SLRs. Finally, we more thoroughly describe the SLR study design.

Strategies for safe prescribing of antipsychotics for youth

Clinicians have been urged to use guidelines for metabolic screening for their pediatric patients who need antipsychotics, but many are not doing so. A recent systematic literature review of studies, which attempted to improve risk screening practices, focused on strategies used to influence screening practices. Clearly, screening for risk is essential, but exactly how it should be done is unclear. There are guidelines, but there is a “gap” between the guidelines and practice.

Predictive accuracy of prenatal ultrasound findings for lower urinary tract obstruction: A systematic review and Bayesian meta-analysis.

Lower urinary tract obstruction (LUTO) is a rare but critical fetal diagnosis. Different ultrasound markers have been reported with varying sensitivity and specificity. The objective of this systematic review and meta-analysis was to identify the diagnostic accuracy of ultrasound markers for LUTO. We performed a systematic literature review of studies reporting on fetuses with hydronephrosis or a prenatally suspected and/or postnatally confirmed diagnosis of LUTO. Bayesian bivariate random effects meta-analytic models were fitted, and we calculated posterior means and 95% credible intervals for the pooled diagnostic odds ratio (DOR). A total of 36,189 studies were identified; 636 studies were available for full text review and a total of 42 studies were included in the Bayesian meta-analysis. Among the ultrasound signs assessed, megacystis (DOR 49.15, [15.28, 177.44]), bilateral hydroureteronephrosis (DOR 41.33, [13.36,164.83]), bladder thickening (DOR 13.73, [1.23, 115.20]), bilateral hydronephrosis (DOR 8.36 [3.17, 21.91]), male sex (DOR 8.08 [3.05, 22.82]), oligo- or anhydramnios (DOR 7.75 [4.23, 14.46]), and urinoma (DOR 7.47 [1.14, 33.18]) were found to be predictive of LUTO (Table 1). The predictive sensitivities and specificities however are low and wide study heterogeneity existed. Classically, LUTO is suspected in the presence of prenatally detected megacystis with a dilated posterior urethra (i.e., the keyhole sign), and bilateral hydroureteronephrosis. However, keyhole sign has been found to have modest diagnostic performance in predicting the presence of LUTO in the literature which we confirmed in our analysis. The surprisingly low specificity may be influenced by several factors, including the degree of obstruction, and the diligence of the sonographer at searching for and documenting it during the scan. As a result, providers should consider this when establishing the differential for a fetus with hydronephrosis as the presence or absence of keyhole sign does not reliably rule in or rule out LUTO. Megacystis, bilateral hydroureteronephrosis and bladder wall thickening are the most accurate predictors of LUTO. Given the significant consequences of a missed LUTO diagnosis, clinicians providing counselling for prenatal hydronephrosis should maintain a low threshold for considering LUTO as part of the differential diagnosis.

A systematic review of risk stratification tools internationally used in primary care settings.

Background and AimsIn our current healthcare situation, burden on healthcare services is increasing, with higher costs and increased utilization. Structured population health management has been developed as an approach to balance quality with increasing costs. This approach identifies sub‐populations with comparable health risks, to tailor interventions for those that will benefit the most. Worldwide, the use of routine healthcare data extracted from electronic health registries for risk stratification approaches is increasing. Different risk stratification tools are used on different levels of the healthcare continuum. In this systematic literature review, we aimed to explore which tools are used in primary healthcare settings and assess their performance.MethodsWe performed a systematic literature review of studies applying risk stratification tools with health outcomes in primary care populations. Studies in Organisation for Economic Co‐operation and Development countries published in English‐language journals were included. Search engines were utilized with keywords, for example, “primary care,” “risk stratification,” and “model.” Risk stratification tools were compared based on different measures: area under the curve (AUC) and C‐statistics for dichotomous outcomes and R 2 for continuous outcomes.ResultsThe search provided 4718 articles. Specific election criteria such as primary care populations, generic health utilization outcomes, and routinely collected data sources identified 61 articles, reporting on 31 different models. The three most frequently applied models were the Adjusted Clinical Groups (ACG, n = 23), the Charlson Comorbidity Index (CCI, n = 19), and the Hierarchical Condition Categories (HCC, n = 7). Most AUC and C‐statistic values were above 0.7, with ACG showing slightly improved scores compared with the CCI and HCC (typically between 0.6 and 0.7).ConclusionBased on statistical performance, the validity of the ACG was the highest, followed by the CCI and the HCC. The ACG also appeared to be the most flexible, with the use of different international coding systems and measuring a wider variety of health outcomes.

Country-related future research agenda of Lean Manufacturing–A systematic literature review

PurposeMany future research proposals of Lean Manufacturing (LM) are presented in the literature. The purpose of this paper is to determine these future research proposals of LM which are country-related and classify them.Design/methodology/approachA systematic literature review (SLR) of peer-reviewed journal articles in LM was conducted. A total of 145 articles published in 34 journals during 2010–2020 were collected from four major management science publishers namely, Emerald Online, Elsevier/Science Direct, Springer Link and Taylor and Francis. The country-related future research proposals of LM identified in the literature were classified according to, firstly, the continent of the country of reference, and secondly, some form of natural affinity of these proposals creating meaningful themes. The quality tool “affinity diagram” was applied to classify the country-related future research proposals of LM.FindingsThe country-related future research proposals of LM, which are increasing in the literature over time, refer mostly to studies to be conducted in several continents/countries and to multinational studies. Conducting studies specifically in Asia, Europe, South and North America, Africa and Australia–New Zealand is also suggested. The plethora of the country-related future research proposals of LM were classified, based on the affinity of their content, into 18 meaningful themes. These themes were also classified based on their affinity into two broad categories, namely “themes concerning the LM approach itself” and “themes concerning factors outside the LM approach”.Research limitations/implicationsThe restricted number of the databases searched and the subjectivity of classifying the large number of the country-related future research proposals into themes are the main limitations of the present SLR. Based on these limitations, future literature review studies can be carried out.Practical implicationsUseful proposals are provided to researchers of several countries for conducting original and country-specific research studies which can enrich the knowledge of the implementation of LM under the specific circumstances of a country for the benefit of practitioners.Originality/valueThis study goes beyond previous literature review studies on LM by focusing exclusively on the LM future research agenda which is country related. The analytical presentation of the country-related future research proposals as well as the formulation of clusters of these proposals make the present SLR study substantially different from those carried out worldwide so far.

Effects of Personal Therapy During Psychotherapy Training - A Systematic Review

Self-experiential work/personal therapy as part of psychotherapeutic training is often under critical discussion. In the German system, self-experiential work will remain an established part of training in psychosocial medical specialties and will continue to be part of the future curriculum in psychotherapy and in practical training subsequent to the study. Identification of different impacts of self-experiential work on psychotherapy trainees. Systematic literature review of studies between 2005 and 2020. Literature search via electronic databases, prior literature search and searches through reference lists of previous research. Selection via previously determined inclusion and exclusion criteria. Thirteen studies were selected for this review. Results were summarised related to 7 outcome variables which mostly displayed positive impacts of self experience related to interpersonal skills, self-perception, knowledge and understanding of therapeutic work, well-being and relief. Satisfaction and the acceptance of the subjective importance of personal therapy for increasing competence were more common than reports about intensive emotions and stress. Self-experiential work is highly valued by psychotherapy trainees and is therefore correctly considered as an obligatory part of training. Nonetheless, it should be evaluated regularly. For further research, self-reports, the most commonly used method, should be combined with objective measures, representativeness of samples should be enhanced and long-term effects should be investigated.