Historical development in the field of 3D printing (table adapted from Ref. [8]).
\\n\\n
More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:{caption:"IntechOpen Maintains",originalUrl:"/media/original/113"}},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"10980",leadTitle:null,fullTitle:"Biogas - Basics, Integrated Approaches, and Case Studies",title:"Biogas",subtitle:"Basics, Integrated Approaches, and Case Studies",reviewType:"peer-reviewed",abstract:"Anaerobic digestion is by far the most important technology for providing clean renewable energy to millions of people in rural areas around the world. It produces biomethane with anaerobic-digestate as a byproduct that can be used as a biofertilizer. In the context of energy consumption, more than 85% of the total energy consumed currently comes from non-renewable fossil resources. A wide variety of biowastes can be used as feedstocks for biogas production. Biogas technology can provide sustainable, affordable, and eco-friendly green energy along with useful byproducts. This book discusses the basics of biogas production and aims to address the needs of graduate and postgraduate students as well as other professionals through further evaluation of biogas production via case studies.",isbn:"978-1-80355-109-8",printIsbn:"978-1-80355-108-1",pdfIsbn:"978-1-80355-110-4",doi:"10.5772/intechopen.95674",price:119,priceEur:129,priceUsd:155,slug:"biogas-basics-integrated-approaches-and-case-studies",numberOfPages:142,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"5ae044532b8c1b30f5802c74ba76e1ae",bookSignature:"Abd El-Fatah Abomohra and El-Sayed Salama",publishedDate:"May 25th 2022",coverURL:"https://cdn.intechopen.com/books/images_new/10980.jpg",numberOfDownloads:340,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:0,numberOfDimensionsCitationsByBook:0,hasAltmetrics:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"July 1st 2021",dateEndSecondStepPublish:"September 2nd 2021",dateEndThirdStepPublish:"October 7th 2021",dateEndFourthStepPublish:"December 26th 2021",dateEndFifthStepPublish:"February 24th 2022",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"186114",title:"Dr.",name:"Abdelfatah",middleName:null,surname:"Abomohra",slug:"abdelfatah-abomohra",fullName:"Abdelfatah Abomohra",profilePictureURL:"https://mts.intechopen.com/storage/users/186114/images/system/186114.jpg",biography:"Abd El-Fatah Abomohra is a professor of Environmental Engineering and the director of the New Energy and Environmental Laboratory (NEEL), Chengdu University, China. He is a DAAD fellow and performed postdoctoral research at Hamburg University, Germany, and Harbin Institute of Technology, China. He was named in the world’s top 2% of scientists for two consecutive years. His team is primarily working on green energy production from different biomass feedstocks.",institutionString:"Chengdu University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"3",institution:{name:"Chengdu University",institutionURL:null,country:{name:"China"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"347657",title:"Prof.",name:"El-Sayed",middleName:null,surname:"Salama",slug:"el-sayed-salama",fullName:"El-Sayed Salama",profilePictureURL:"https://mts.intechopen.com/storage/users/347657/images/system/347657.png",biography:"El-Sayed Salama is a professor in the Public Health School,\nLanzhou University, China. He is also a director of the Green Environmental & Energy Laboratory (GEEL) and a distinguished\nexpert of science and technology in the ecological industry, Gansu Province. His GEEL research work focuses on bioenvironmental science and bioenergy. He has several journal publications to\nhis credit.",institutionString:"Lanzhou University, Gansu Academy of Membrane Science and Technology",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Lanzhou University",institutionURL:null,country:{name:"China"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"890",title:"Renewable Energy",slug:"environmental-sciences-waste-management-renewable-energy"}],chapters:[{id:"81327",title:"Introductory Chapter: From Biogas Lab-Scale towards Industrialization",doi:"10.5772/intechopen.104500",slug:"introductory-chapter-from-biogas-lab-scale-towards-industrialization",totalDownloads:13,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:null,signatures:"El-Sayed Salama and Abd El-Fatah Abomohra",downloadPdfUrl:"/chapter/pdf-download/81327",previewPdfUrl:"/chapter/pdf-preview/81327",authors:[{id:"186114",title:"Dr.",name:"Abdelfatah",surname:"Abomohra",slug:"abdelfatah-abomohra",fullName:"Abdelfatah Abomohra"},{id:"347657",title:"Prof.",name:"El-Sayed",surname:"Salama",slug:"el-sayed-salama",fullName:"El-Sayed Salama"}],corrections:null},{id:"79776",title:"Biogas Production: Evaluation and Possible Applications",doi:"10.5772/intechopen.101544",slug:"biogas-production-evaluation-and-possible-applications",totalDownloads:118,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Biogas is an excellent example of renewable feedstock for energy production enabling closure of the carbon cycle by photosynthesis of the existing vegetation, without charging the atmosphere with excessive carbon dioxide. The present review contains traditional as well as new methods for the preparation of raw materials for biogas production. These methods are compared by the biogas yield and biogas content with the possible applications. Various fields of biogas utilization are discussed. They are listed from simple heating, electricity production by co-generation, fuel cell applications to catalytic conversions for light fuel production by the Fischer-Tropsch process. The aspects of carbon dioxide recycling reaching methane production are considered too.",signatures:"Venko Beschkov",downloadPdfUrl:"/chapter/pdf-download/79776",previewPdfUrl:"/chapter/pdf-preview/79776",authors:[{id:"191530",title:"Prof.",name:"Venko",surname:"Beschkov",slug:"venko-beschkov",fullName:"Venko Beschkov"}],corrections:null},{id:"80192",title:"Resource Reclamation for Biogas and Other Energy Resources from Household and Agricultural Wastes",doi:"10.5772/intechopen.101747",slug:"resource-reclamation-for-biogas-and-other-energy-resources-from-household-and-agricultural-wastes",totalDownloads:11,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The chapter’s goal is to highlight how the reclamation of household and agricultural wastes can be used to generate biogas, biochar, and other energy resources. Leftover food, tainted food and vegetables, kitchen greywater, worn-out clothes, textiles and paper are all targets for household waste in this area. Agricultural waste includes both annual and perennial crops. Annual crops are those that complete their life cycle in a year or less and are comparable to bi-annual crops, although bi-annuals can live for up to two years before dying. The majority of vegetable crops are annuals, which can be harvested within two to three months of seeding. Perennials crops are known to last two or more seasons. Wastes from these sources are revalued in various shapes and forms, with the Green Engineering template being used to infuse cost-effectiveness into the process to entice investors. The economic impact of resource reclamation is used to determine the process’s feasibility, while the life cycle analysis looks at the process’s long-term viability. This is in line with the United Nations’ Sustainable Development Goals (SDGs), whose roadmap was created to manage access to and transition to clean renewable energy by 2030, with a target of net zero emissions by 2050.",signatures:"Donald Kukwa, Maggie Chetty, Zikhona Tshemese, Denzil Estrice and Ndumiso Duma",downloadPdfUrl:"/chapter/pdf-download/80192",previewPdfUrl:"/chapter/pdf-preview/80192",authors:[{id:"245715",title:"Ms.",name:"Zikhona",surname:"Tshemese",slug:"zikhona-tshemese",fullName:"Zikhona Tshemese"},{id:"281613",title:"Dr.",name:"Maggie",surname:"Chetty",slug:"maggie-chetty",fullName:"Maggie Chetty"},{id:"323336",title:"Dr.",name:"Donald",surname:"Tyoker Kukwa",slug:"donald-tyoker-kukwa",fullName:"Donald Tyoker Kukwa"},{id:"443095",title:"Mr.",name:"Ndumiso",surname:"Duma",slug:"ndumiso-duma",fullName:"Ndumiso Duma"},{id:"443096",title:"Mr.",name:"Denzil",surname:"Estrice",slug:"denzil-estrice",fullName:"Denzil Estrice"}],corrections:null},{id:"80783",title:"Role of Microbial and Organic Amendments for the Enrichment of Methane Production in Bioreactor",doi:"10.5772/intechopen.102471",slug:"role-of-microbial-and-organic-amendments-for-the-enrichment-of-methane-production-in-bioreactor",totalDownloads:44,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Studies were carried out on lab-scale levels for biogas production using two different wastewaters, that is, herbal pharmaceutical wastewater and food processing wastewater. A total of eight methane bacteria were isolated from cattle dung and mass culturing was carried out to study their feasibility in biogas escalation. Optimization of methane bacteria that could increase biogas production was identified. Among the methane bacteria, two species Bacillus sk1 and Bacillus sk2 were found to enhance the biogas production to a maximum level. Gas analysis showed CH4 content of 63% in the case of food processing wastewater and around 67% with herbal pharmaceutical wastewater. Bacillus sk1 was found to be more suitable for both wastewater and biogas production and was found to be 46.4% in food processing wastewater and 43.3% in herbal pharmaceutical wastewater. Amendment of Bacillus sk2 in food processing wastewater produces 39.7% and 30.3% of biogas in herbal pharmaceutical wastewater was observed. Enzyme Bacillidine™ (P-COG-concentrate aqueous base) was also tried but results were not very encouraging. Comparative studies on both the wastewater have been discussed in detail in this article.",signatures:"Sharda Dhadse and Shanta Satyanarayan",downloadPdfUrl:"/chapter/pdf-download/80783",previewPdfUrl:"/chapter/pdf-preview/80783",authors:[{id:"427054",title:"Dr.",name:"Sharda",surname:"Dhadse",slug:"sharda-dhadse",fullName:"Sharda Dhadse"},{id:"427065",title:"Dr.",name:"Shanta",surname:"Satyanarayan",slug:"shanta-satyanarayan",fullName:"Shanta Satyanarayan"}],corrections:null},{id:"79771",title:"Global Fertilizer Contributions from Specific Biogas Coproduct",doi:"10.5772/intechopen.101543",slug:"global-fertilizer-contributions-from-specific-biogas-coproduct",totalDownloads:14,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The impact of Haber-Bosch process on modern agriculture is prodigious. Haber-Bosch process led to invention of chemical fertilizers that powered green revolution, minimized food scarcity, and improved human and animal nutrition. Haber–Bosch process facilitated agricultural productivity in many parts of the world, with up to 60% of crop yield increase attributed solely to nitrogen fertilizer. However, Haber-Bosch fertilizers are expensive, and their poor use efficiency exerts adverse external consequences. In European Union for example, the annual damage of up to € 320 (US$ 372.495) billion associated with chemical fertilizers outweighs their direct benefit to farmers, in terms of crops grown, of up to € 80 (US$ 93.124) billion. A substitute for chemical fertilizers is therefore needed. In this chapter, external costs of chemical fertilizers are highlighted. The capability of liquid fraction of cassava peeling residue digestate to supplant and mitigate pecuniary costs of chemical fertilizers required for production of cassava root is also analyzed and presented. Results indicate that about 25% of fund used to purchase chemical fertilizers required for cassava root production could be saved with the use of liquid fraction of cassava peeling residue digestate. The pecuniary value is estimated at US$ 0.141 (≈ € 0.121) billion for the 2019 global cassava root output. This saving excludes external costs associated with Haber-Bosch fertilizers such as ammonia air pollution, eutrophication, greenhouse gasses emissions, and contamination of potable water supply reserves. Consequently, liquid fraction digestate could reduce the cost of cassava root production, as well as minimize adverse health and environmental consequences attributed to chemical fertilizers.",signatures:"Sammy N. Aso, Simeon C. Achinewhu and Madu O. Iwe",downloadPdfUrl:"/chapter/pdf-download/79771",previewPdfUrl:"/chapter/pdf-preview/79771",authors:[{id:"219927",title:"Ph.D.",name:"Sammy N.",surname:"Aso",slug:"sammy-n.-aso",fullName:"Sammy N. Aso"},{id:"219929",title:"Dr.",name:"Simeon C.",surname:"Achinewhu",slug:"simeon-c.-achinewhu",fullName:"Simeon C. Achinewhu"},{id:"428714",title:"Prof.",name:"Madu O.",surname:"Iwe",slug:"madu-o.-iwe",fullName:"Madu O. Iwe"}],corrections:null},{id:"81583",title:"A Case Study for Economic Viability of Biogas Production from Municipal Solid Waste in the South of Chile",doi:"10.5772/intechopen.104558",slug:"a-case-study-for-economic-viability-of-biogas-production-from-municipal-solid-waste-in-the-south-of-",totalDownloads:13,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"This research evaluated the technical and economic feasibility of a biogas plant in the south of Chile to generate energy (WtE) for the plant’s own consumption, energy for sale to the country’s electricity grid and produce biofertilizer from municipal solid waste (MSW). In the town of Panguipulli, 26 tons of solid waste are produced daily, of which 12 tons correspond to household organic waste. These arrive directly to a landfill, wasting their potential to generate products and energy. To study the economic feasibility, an analysis was carried out on the investment, costs and income that make up the cash flow of the project evaluated at 15 years. The results gave an NPV of 214.099.637 CLP and an IRR of 15% at a real discount rate of 10%, with a payback period of 6 years. The research concluded that it is feasible to design a biogas plant that works from household organic waste in Panguipulli. This will contribute to the mitigation of climate change and will promote circular economy actions and the sustainable management of MSW in the south of Chile.",signatures:"Jean Pierre Doussoulin and Cristina Salazar Molina",downloadPdfUrl:"/chapter/pdf-download/81583",previewPdfUrl:"/chapter/pdf-preview/81583",authors:[{id:"327931",title:"Assistant Prof.",name:"Jean Pierre",surname:"Doussoulin",slug:"jean-pierre-doussoulin",fullName:"Jean Pierre Doussoulin"},{id:"438855",title:"BSc.",name:"Cristina",surname:"Salazar Molina",slug:"cristina-salazar-molina",fullName:"Cristina Salazar Molina"}],corrections:null},{id:"79715",title:"Case Studies in Biogas Production from Different Substrates",doi:"10.5772/intechopen.101622",slug:"case-studies-in-biogas-production-from-different-substrates",totalDownloads:127,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The present paper involves applicative research in the field of biogas production with the accent on small laboratory scale installations built for biogas production, preliminary testing of substrate for biogas production and combustion applications for biogas-like mixtures. The interconnected aspect of the presented material involves cumulative expertise in multidisciplinary fields of interest and continuous development of possibilities to determine the energetic potential of substrates subjected to biodegradable fermentation conversion for further applications. The research analyzed the combustion behavior of biogas with different methane/carbon dioxide ratio without and in the presence of specific catalysts. Also, laboratory analysis on biomass substrates for determining their physical and chemical potential for different applications was performed. The main conclusions are drawn revolve around the untapped potential of the different types of biomasses that are not commonly used in the production of renewable energy carriers, like biogas, and also the potential use of residual biomass in combustion processes for an enclosed life cycle from cradle to the grave. 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\r\n\tIn the future, with the artificial functional nucleotides, combinatorial chemistry of nucleotides fostering synthetic life would never have been a distant dream.
Gaining immense interest both in academic and industrial sector is the concept of three dimensional (3D) printing (3DP) technologies. Domains like aerospace, engineering, FMCG, architecture, military, fashion industry, chemical industry, and medical field are by no way untouched by this technology [1, 2]. 3DP has a wide range of applications like tissue design, printing of organ, diagnostics, manufacture of biomedical devices, and the design of drug and delivery systems in the medical field [3, 4]. From the data originated by various techniques like computed tomography (CT) scan and magnetic resonance imaging (MRI), complex anatomical and medical structures according to the need of patient can be fabricated [5, 6]. Replacing and repairing the defective organs like kidney, heart etc. or all together creating a new organ that mimics the same functions as that of original are some additional uses of this technology [7]. This technology is so widespread that its applications include things that are an integral part of human life like clothing, eyeglasses, jewelry, parts of cars, and drugs that can be printed in almost any geometry and shape as per the requirement of the user [8].
In this technology a concept is transformed into prototype by taking help from 3D computer-aided design (CAD) files, hence digitally controlled and customized product can be fabricated [9]. This technology utilizes a bottom-up approach in which layers of materials like living cells, wood, alloy, thermoplastic, metals etc. are placed on top of each other in order to make the required 3D object [10]. Therefore, 3D printing is also known by other terminologies such as layered manufacturing, additive manufacturing, computer automated manufacturing, rapid prototyping, or solid freeform technology (SFF) [9].
In subtractive methodology or conventional method, the product is designed from the bulk substance and due to non-advanced tools used non-standard geometries and objects made from many materials cannot be made with high quality [11, 12]. In contrast to the conventional method, 3DP technology is more automated, rapid and easy to use, customized and sophisticated and cost-effective [13, 14, 15].
First, a virtual 3D design of an object using digital design software like Onshape, Solidworks, Creo parametric, Autocad, Autodesk etc. is created [2, 16, 17].
This digital model is then converted to (.STL) digital file format which stands for standard tessallation language or stereolithography [2].
Triangulated facets give information regarding the surface of the 3D model that is present in the (.STL) file [2].
The (.STL) file is converted into G file by slicing the design into a series of 2D horizontal cross-sections by the help of specialized slicer software, which is installed in the 3D printer (Tables 1–2).
Year | Major development |
---|---|
1980 | Dr. Hideo Kodama filed first patent for RP technology |
1984 | Stereo lithography apparatus (SLA) was invented by Charles Hull |
1986 | Carl Deckard invented apparatus for producing parts by selective sintering |
1989 | Patent was granted to Carl Deckard for SLA |
1990 | Fused deposition modeling (FDM) |
1992 | First SLA machine was produced using 3D system |
1993 | 3D printing patent was granted to E.M Sachs |
1996 | Clinical application of biomaterials for tissue regeneration |
1999 | Luke Massella received first 3D printed bladder which was an amalgamation of 3D printed biomaterials and his own cells |
2000 | MCP technologies introduced the SLM technology |
2002 | Miniature functional kidney was fabricated |
2003 | Term organ printing was coined |
2004 | Dr. Bowyer conceived the RepRap concept of an open-source, self-replicating 3D printer |
2005 | First color 3D printer was introduced by Z Corp |
2007 | Selective layer customization and on-demand manufacturing of industrial parts |
2009 | Organovo, Inc., announced the release of data on the first fully bioprinted blood vessels |
2011 | 3D printing was applied in gold and silver World’s first 3D printed car, robotic aircarft was introduced |
2012 | Extrusion-based bioprinting for an artificial liver 3D printed prosthetic jaw was implanted |
2013 | SolidConcepts produced a 3D printed metal gun |
2014 | Implementation of multi-arm bioprinter to integrate tissue fabrication with printed vasculature |
2015 | First 3D printed pill was approved by US FDA Organovo announced the release of data on the first fully bioprinted kidney |
Historical development in the field of 3D printing (table adapted from Ref. [8]).
3D printing technology used | Formulations | API | Ref. |
---|---|---|---|
Semi-solid extrusion (SSE) | Bi-layered tablets (polypill) | Guaifenesin | [30] |
Multiactive tablets (polypill) | Nifedipine, Glipizide, and captopril | [31] | |
Stereolithography (SLA) | Hydrogels | Ibuprofen | [32] |
Facial mask | Salicylic acid | [33] | |
Selective layer sintering (SLS) | Tablets | Paracetamol | [34] |
Drug delivery device | Progesterone | [35] | |
Fused deposition modeling (FDM) | Caplets | Caffeine | [36] |
Tablets | Hydrochlorothiazide | [37] | |
Oral films | Aripiprazole | [38] | |
Binder jet printing | Tabular devices | Methylene blue and alizarin yellow (dyes) | [39] |
Cubic tabular devices | Pseudoephedrine | [40] | |
Tablets | Chlorpheniramine meleate and fluorescein | [41] | |
Orodispersible tablets | Levetiracetam | [42] | |
Inkjet 3D printing | Implant | Levofloxacin | [43] |
3D printing machine | Multidrug implant | Rifampicin and isoniazid | [44] |
Inkjet 3D printing | Nanosuspension | Folic acid | [45] |
Thermal inkjet (TIJ) printing | Solution | Salbutamol sulfate | [22] |
Inkjet 3D printing | Nanoparticle | Rifampicin | [27] |
Pharmaceutical preparations that were developed by 3DP technology.
Now the print head is moved in the x-y axis to create the base of the 3D object.
The print head is now allowed to move in the z-axis, thereby depositing the layers sequentially of the desired material, hence creating a complete 3D object [2, 9].
Maximum numbers of 3D printing technologies are compatible with (.STL) file format. Some errors might occur during the conversion of the 3D model to .STL digital file; therefore, software like Magics (Materialise) can be employed to correct the errors during conversion. File formats other than .STL like additive manufacturing file format (AMF) and 3D manufacturing format (3MF) are used as .STL does not have information regarding the type of material, its color, texture, properties, and other features [18].
The process involves the selection of the desired polymer, which is melted and forced through a movable heated nozzle. Along the entire 3 axis (i.e., x-y-z), the polymer is laid down layer by layer, which on solidification gives the exact shape as was designed by computer aided design models. Multiple dosage forms like implants, zero-order release tablets etc. that include polymer as a part of their formulation can be made by this method [9, 19, 20, 21].
It involves the heating of ink fluid by the help of micro-resistor, thereby creating a bubble of vapor that nucleates and upon expansion forces the ink to drop out of the nozzle. Dispensing of extemporaneous preparation/solution of drug onto 3D scaffolds is an area where this technique can be employed [22, 23].
It is a powder-based 3D printing that utilizes powder as a substrate on which layer by layer different combinations of active ingredients and ink is sprayed which is of varying droplet size that eventually solidifies into solid dosage form [9, 19, 24, 25, 26, 27, 28].
It encompasses a pattern-generating device that moves as per the guidance of computer-controlled translational stage so that layers after layers are put on in order to achieve a 3D microstructure [29].
This technology provides a personalized dose in additional to the delivery of a high drug-load with high disintegration and dissolution levels by manufacturing highly porous material [25].
It is light-induced polymerization where materials like photopolymers, radiation-curable resins, and liquid are collected in vats, which are successively cured into layers, one layer at a time by irradiating with a light source, thereby providing a 2D patterned layer. This involves techniques such as stereolithography (SLA), digital light processing (DLP), and continuous direct light processing (CDLP). Depending on the orientation of light source and the surface where polymerization of the photoactive resin occurs, SLA can be divided into two different configurations:
Bath configuration (free surface approach)
Bat configuration (constrained surface approach) [2].
By eradicating the use of unnecessary resources, manufacturing cost can also be reduced. For instance, 20-mg tablets could be potentially formulated as 1-mg tablets as per need [19].
4. 3DP allows controlled size of droplets, complex drug release profiles, strength of dosage and multi-dosing [44, 48, 49].
In inkjet printing, proper flow of ink can only be achieved with ink that has precise viscosity [50].
Ink formulation material should have the property of self-binding but should not bind to other printer elements. In some formulation when the ink does not possess adequate self-binding property or it binds with other elements of printer then the resultant formulation does not have required hardness [51].
Rate of drug release may get affected due to binding of ink with other printer materials [52].
One of the critical medical issues is the failure of organs and tissues as a result of accident, congenital defects, aging etc (Figure 1) and the current resolution for this problem is organ transplant from dead or living donors. However, only few fortunate people receive organs and the rest die due to donor shortage. Moreover, the procedures for organ transplants are so expensive that it is out of reach of common people. Another problem with transplant surgery is that donors with tissue match are difficult to find [7, 53].
Different medical applications of 3D printing technology.
The solution to this problem lies in the fact that the required tissue or organ should be fabricated using the patient’s own body cells, which would decrease the risk of tissue or organ rejection; moreover, the requirement for immunosuppressant will also be greatly reduced [7, 54].
In the conventional method of tissue engineering from a small tissue sample, stem cells are isolated, amalgamated with growth factor, and then multiplied in the laboratory. Then the cells are seeded onto scaffolds that direct cell proliferation and differentiation into a functioning tissue.
Placement of cell with accuracy, digitally controlled speed, drop volume, resolution, concentration of cells and diameter of printed cell are some of the additional advantages that 3D bioprinting offers over traditional tissue engineering [2, 54].
Depending upon the porosity, the type of tissue, and required strength, various materials are present to make the scaffolds. Among all materials, hydrogels are said to be the most suitable for building soft tissues [2, 55].
No doubt that organ printing is still in the phase of development but several researches have demonstrated its concept with proof. Scientists have built an artificial ear, cartilage and bone, and heart valve by the help of 3D printers [2, 47, 55]. Wang et al. used 3D bioprinting technology to deposit different cells within various biocompatible hydrogels to produce an artificial liver [54].
As with the increasing interest of researcher and academician and with vast potential of this technology it can possibly unfold new potential therapeutic drugs thereby greatly cutting research cost and time [7].
Infinite dosage forms can be created using 3D printing. Inkjet-based 3D printing and inkjet powder-based 3D printing are the two main printing technologies employed in the pharmaceutical industry. Microcapusles, antiobiotic printed micropatterns, mesoporous bioactive glass scaffolds, nanosuspensions, and hyaluronan-based synthetic extracellular matrices are some of the novel dosage forms formulated using 3D printing [53] (Table 3).
Active pharmaceutical ingredients | Inactive pharmaceutical ingredients |
---|---|
Vancomycin | Glycerin |
Ofloxacin | Methanol |
Folic acid | Acetone |
Dexamethasone | Surfactants (likeTween 20) |
Theophylline | Kollidon SR |
Acetaminophen | Ethanol-dimethyl sulfoxide |
Paclitaxel | Propylene glycol |
Tetracycline etc. | Cellulose etc. |
List of active and inactive ingredients used in 3D printing.
Increasing the efficacy of drugs and at the same time reducing the chances of adverse reaction should be the aim of drug development, which can be achieved by using 3D printing to fabricate personalized medications [7, 26, 53].
Oral tablets are prepared by mixing, milling, and dry and wet granulation of powder ingredients, which are eventually compressed to form tablets; till today, tablets are the most popular dosage form because of the ease of preparation, good patient compliance and accurate dosing and because they are painless. However, no method is available that can prepare personalized solid dosage forms like tablets.
In the traditional way of preparing tablets, drugs can easily undergo degradation if proper guidelines are not followed, leading to altered therapeutic value of the final product. Moreover, these conventional methods cannot be used to prepare customized dosage forms that possess long-lasting stability, novel drug release profile, and detailed geometries [26].
Drugs with narrow therapeutic index can easily be prepared using 3D printing; and, by knowing the patient’s pharmacogenetic profile and other characteristics like age, race etc., optimal dosage can be given to the patient [53].
Preparation of entirely new formulation is another vital potential of 3D printing for instance fabrications of pills that have a blend of more than one active pharmaceutical ingredient or dispensed as multi-reservoir printed tablets. Hence patients suffering from more than one disease can get their formulation ready in one multi-dose form at the healthcare point itself, thereby providing personalized and accurate dose to the patient with better or best compliance [26].
In most conventional compressed dosage forms, a simple drug release profile which is a homogenous mixture of active ingredients is observed. Whereas in 3D printed dosage forms, a complex drug release profile that allows fabrication of complex geometries that are porous and loaded with multiple drugs throughout, surrounded by barrier layers that modulate release, is found [55]. One example is the printing of a multilayered bone implant with a distinct drug release profile alternating between rifampicin and isoniazid in a pulse release mechanism. 3D printing has also been used to print antibiotic micropatterns on paper, which have been used as drug implants to eradicate
In a research concerning drug release profiles, chlorpheniramine maleate was 3D printed onto a cellulose powder substrate in amounts as small as 10–12 moles to demonstrate that even a minute quantity of drug could be released at a specified time. This study displayed improved accuracy for the release of very small drug doses compared with conventionally manufactured medications [53].
By the support of MRI, CT scan, and X-ray and its translation into .stl 3D print files, implants and prostheses of any possible shape can be made [1, 7, 55].
Standard as well as complex surgical implants and prosthetic limbs can be made as per need in time as less as 24 hours. Spinal dental and hip implants have been fabricated so far but their validation is a time-consuming process. Previously, in order to achieve a desired shape and size that fits perfectly, surgeons had to craft metal and plastic pieces and perform bone grafting or use drill machines to modify the implants [2, 7]. This also stands correct in neurosurgery cases due to the irregular shape of the skull whose standardization is a complex procedure.
Some examples of commercially and clinically successful 3D printed implants and prostheses are as follows:
First 3D printed titanium mandibular porsthesis was implanted successfully at BIOMED Research Institute in Belgium [1].
Dental, orthopedic, maxillofacial, and spinal implants are manufactured by a company named Layer Wise [55].
Invisalign braces is another successful commercial use of 3D printing.
By using silver nanoparticles, chondrocytes, and silicon, a prosthetic ear was made out of 3D printing technology that was able to detect electromagnetic frequencies. The impact of this technology is so extensive in the field of hearing aids that today 99% of customized hearing aids are made using 3D printers, because, as everyone’s ear canal has a different shape, this technology is able to provide perfect fit for each receiver and, moreover, the devices can be produced efficiently and cost effectively [7].
In order to have successful medical procedures, knowledge about patients’ specific anatomy before medical surgery is essential due to variations in individual and complex human anatomy. 3D printed models have helped extensively in this respect, making them a vital tool for surgical methods [1, 55].
One of the most complicated structures of human body is the head, whose 3D printed neuro-anatomical models are of great help to neurosurgeons. Sometimes, it is very difficult to gain detailed information about the connections between skull architecture, cerebral structure, cranial nerves, and vessels from radiographic 2D images only and even a slight error in the medical procedure can be fatal. Here comes the role of 3D models, which are more realistic and provide in detail comparison and contrast between a normal brain structure and a brain with deformity or lesions, which suggest the surgeons more safe procedures to follow.
For liver transplant, Japan’s Kobe University Hospital had used 3D printed models by using replica of patients’ own organ, to find out how to precisely craft a donor liver with least tissue loss [1].
3D printed model of calcified aorta for surgical planning of plaque removal was used by surgeons [55].
To study aerosol drug delivery to lungs, airways of premature infants was reconstructed using 3D printing technology [55].
3D printing technology is a valuable and potential tool for the pharmaceutical sector, leading to personalized medicine focused on the patients’ needs. It offers numerous advantages, such as increasing the cost efficiency and the manufacturing speed. 3D printing has revolutionized the way in which manufacturing is done. It improves the design manufacturing and reduces lead time and tooling cost for new products. This chapter has summarized different fabrication methods and some notable applications of 3D printing in the healthcare sector, especially in pharmaceutical sciences.
The impact severe mental disorders (SMDs) have on a student acquires great relevance in the adolescent’s life. This is because of the repercussion it has on academic performance and the construction of a personal project while hindered by the disorder [1]. We emphasize the importance of this study, given that it aims to make it known that these students with mental disorders, in order for them to remain in the educational system, must receive adequate attention that meets their needs. It is a vulnerable population that presents greater risks of early school dropout than the general population [2]. It is pertinent to study in-depth lines of work that respond to such a specific need [3].
Before going any further, we would like to delimit the concept of SMD, so we can understand the profile of the studied population and some of the elements that make this population a homogeneous observation group. The severe mental disorders would be those disorders that “due to their severity, seriously compromise evolution, learning, personal development and the social and labor insertion of those children or adolescents who suffer from it. ….. that mental disorder of long duration and involving a variable degree of disability and social dysfunction” [4].
We found different perspectives [5], but they all could be synthesized in the idea that a serious mental disorder is that whose symptomatology affects very severely on different areas of the person and for a long time.
It is estimated that 20% of adolescents suffer from some type of mental disorder [6]. We know mental health problems account for 16% of total adolescent health problems. Also, half of mental health problems begin at the age of 14 years, and most of them go undetected or untreated. The same authors point out that suicide is the third cause of death between ages 15 and 19 years, as a consequence of not addressing mental health problems during the transition from adolescence to adulthood [7]. This limits the opportunities to develop a fulfilling life as an adult. This population segment is at a disadvantage regarding their participation, permanence, and promotion in the educational field. Adopting support measures that respond to their educational needs should compensate this situation.
According to the United Nations Children’s Fund [8], children who suffer from mental health problems are among the most vulnerable population groups. For an adolescent with a SMD, academic success is central and structural for the construction of their personal project, both from an academic and therapeutic point of view. Maintaining the relationship and staying in school allow students with SMD to have a reference of fundamental normality, so as to make improvements in other areas of their lives.
Some publications suggest that students with externalizing disorders are more likely to obtain poor academic results. This same publication points out that the economic factors, the age of onset of the mental disorder, academic performance, and family support are among some of the factors that are present in students with severe mental disorders [9]. Other studies indicate that groups of students with higher levels of emotional strength and low levels of distress obtain higher grades, have a greater prosocial contribution to the community, and show greater satisfaction with life [10].
The relationship between mental health and psychosocial factors seems clear [11]. Psychosocial factors play an important role in the adherence to interventions of the population with severe mental disorders. They could also play it on their academic results. Knowing the psychosocial factors of students with severe mental disorders could help us to personalize interventions [12].
We understand that, in order to develop educational practices appropriate to the needs of students with a SMD [13], understanding and knowing the psychosocial characteristics of this class of students is mandatory. This is how the European Education Information Network of the European Union warned in 2017 that one in eight children has a diagnosed mental disorder [14]. These same authors argue that 50% of mental health problems in adulthood begin to take effect before the age of 15 years, in adolescence. From this reality, it is necessary to deepen the development of educational practices that respond to many adolescents who are in a situation of greater vulnerability.
Based on the results obtained in a previous research carried out by us [15], and on the research in the scientific literature, we have used 18 variables to analyze the observed reality. We want to show the meanings attributed to each variable, since they will serve to interpret and help us make decisions in the factor analysis adjustment that we explain in the following section.
Thus, when we have observed the family accompaniment, we understand the fundamental role the family has both in the genesis and the treatment of the disorder [16]. So, depending on how the family support developed, the family will therefore be either a protective or a risk factor for students in a situation of SMD. When we talk about a family providing positive support, we refer to those families that understand their children’s clinical situation and, therefore, make good use of training guidelines favoring a healthy upbringing. We could differentiate between those families that play an abandonment and negligent role, not very favorable to the children’s rehabilitation process. At the other extreme, we would find families with an excessively care role and whose accompaniment is overprotective. In either case, we would be referring to families with difficulties in establishing a healthy parental-filial relationship.
When we analyzed the type of linkage with the school, we considered that it was a good linkage when maintaining the relationship and staying in school allow students with severe mental disorders to maintain a reference of fundamental normality that propitiates improvements in other areas of their lives. A proper bond with the school describes not only permanence and regular assistance – elements that are closely related –, but the grade the student feels and perceives the context with [3]. Failure to establish stable and healthy links with teachers, the educational center and the classmates are directly related with low self-esteem and could have a direct impact in the student’s academic performance [17]. We cannot forget that the perception that the rest of the educational community has and perceives of students with SMD would be included in the relationship with the educational center. This is how some research indicates that young people have negative attitudes toward their peers with mental health difficulties [18].
With the definition of this variable, we talk about lack of conflicts and a good relationship with teachers and peers. All this defines a contextual framework that allows students to express themselves with emotional tranquility. This is fundamental for their emotional wellness and the avoidance of subclinical or clinical symptoms. So is some authors see the inability to bond as a determining risk factor in obtaining mental health [19].
When analyzing academic success, we cannot forget that the children with mental health problems obtain worse academic results [20]. We also know there is an association between mental health problems and persistent truancy. This relationship is greater in those students who showed externalizing symptoms, since they obtain worse academic results [21]. So, when talking about academic success, we are referring to obtaining good academic results. It is mandatory to pass all subjects, except two, to be promoted to the next course. When a child makes through, we considered they have achieved academic success. When a student fails more than two subjects, we consider they are not in a situation of academic success. Academic success can be interpreted in multiple ways. It depends on where the light is pointing. We have not wanted to establish references in the scientific literature. We wanted to define what the concept means to us. That has been our way of observing and looking for the data in the consulted reports.
On the other hand, we also wanted to analyze the degree of academic promotion of the population analyzed. In this sense, some research shows the negative relationship between academic performance and psychiatric disorders, whether externalizing or internalizing ones [22]. Therefore, the possibility of repeating an academic year seems to be a conditioning element for the population studied. We have taken as a unit of temporal analysis the moment of the analytical work of the present investigation. This circumstance could have happened more times. Anyway, we understand that when a member of the sample repeated a school year at last once prior to hospitalization, the variable is marked as positive.
Regarding the continuity of learning processes and school attendance of these students, we found data indicating that the degree of truancy in students with mental disorders is higher than in the rest of the population [23]. Many factors define the situation of an absconding student. However, we would like to stress how important the degree of connection between the child and their school is. When a child feels a high-level bond with the school, it is because they also feel understood and included. So, for us, the degrade of truancy is a consequence of the engagement level with the educative center. Moreover, we think an avoidant behavior is an indication that something is not working as it should.
We have considered that the previous academic history of students with severe mental disorders also becomes a conditioning element for the improvement of these students. Thus, when we have considered this variable, we want to highlight one element that could be present in a student with a SMD [15]. Thus, there is a high chance they have bad previous academic records. This circumstance is present specially in externalizing disorders [9].
We also know that curricular backwardness affects many students with a SMD [24]. This variable defines the level of educative competence of a student in relation to their age. When a student has at least 1 year of curricular lag, we believed it pertinent to conceptualize the variable as positive.
Among the risk factors that predispose a student toward an early school dropout, there is the motivation toward study [25]. This is important for clinical improvement, as school expectations are a fundamental protective factor for mental health [26]. We considered this as a qualitative dichotomous variable.
It is also common for students with SMD to have poor study habits. This is because the disorder interrupts any process. Thus, when the student gets in a dire situation, they find it very difficult to maintain a routine in any activity [27].
In relation to limited conceptual and procedural power and/or cognitive difficulties, we can observe that this obstacle to participate in classroom dynamics predisposes students with SMD toward greater vulnerability in the educational context. This is because they lack the necessary skills to function adaptively in the methodological dynamics of a mainstream classroom [9].
We would also like to highlight the attentional difficulties of these pupils. In this regard, we will not only refer to the disorder with the highest level of attention impairment, as is the attention-deficit hyperactivity disorder. Attention difficulties are a circumstance present in many SMDs. This is because, whether the disorder is an externalizing or internalizing one, the moment of the disorder onset marks the difference [28]. Being in a severe moment could provoke attention difficulties due to circumstances such as problems arising from the disorder and medication, among others.
On the other hand, it seems relevant to us to differentiate between internalizing and externalizing disorders, since the way they are represented in the educational context is different. Thus, internalizing disorders collide less with interpersonal relationships, since they do not contribute to the distortion of coexistence in the educative center. On the other hand, externalizing disorders clash frontally with the school life in an educational center [9, 15]. As these disorders generate more disruption in the classroom, the student’s struggle with this type of disorder challenges more people and is more evident. So, we could say that internalizing disorders can go unnoticed and externalizing disorders become apparent more easily. Finally, we will point out that internalizing disorders, despite going unnoticed in most cases, are sometimes expressed with greater implosion on social networks. Hence, a minor who goes unnoticed in the educational center might be sharing on social sites such material that could compromise them before the educational community even more than an externalizing disorder. In our research when we found one of these cases, we conceptualized it as a problem of coexistence.
We also found it interesting to focus on relational style, as the learner may be more or less inhibited in the way he/she relates to others. It is common to find a greater degree of uninhibited in behavioral disorders. On the other hand, internalizing disorders do not always manifest themselves in a little visible way [29]. Because of this, the inhibited-uninhibited categorization could help to clarify how the mental disorder is represented in the educational center.
In the scientific literature, we also find data that leads us to consider the moment at which the disorder was detected, since when detection is early the prognosis may improve. In this sense, it is known that the prodrome symptoms of SMD begin to present themselves during adolescence [21]. For this reason, early detection could be an element that helps reduce the impact of the disorder on the child’s vital development.
From here, we could analyze when educational problems start. Some studies show vulnerability to clinical symptoms already in the early school years [30]. We also know mental disorders in early childhood are three times as likely in children who present misconduct at the age of 5 years, and around seven times as likely in children with special educational needs [31]. That is, the moment of detection could determine if the disorder occurs one way or the other, as early detection allows intervening in more preventive and less palliative terms [32].
Having analyzed the conceptual elements on which we have decided to focus our research, we set ourselves the following aim, to define psychosocial factors of students aged 12–18 years who have been diagnosed with a severe mental disorders.
For the selection of the sample, we have used an intentional sampling criterion [33]. One hundred and nine cases of students with SMD in the educational field have been analyzed. We have analyzed both internalizing and externalizing serious mental disorders. They range in age from 12 to 17 years old. The mean and mode is 15 years of age. Forty-five percent of them are female and 55% are male.
As inclusion criteria, we note that all cases have been treated for an average of 11 months in a Day Hospital for adolescents with subacute symptomatology. In this Day Hospital, they have received both clinical care and formal educational care. It is therefore a specialized center in which the patients are also students and fulfill this dual role. To be admitted to this Day Hospital, a public Mental Health Centre under DSM-5 and ICD-10 criteria must previously diagnose all patients. All patients have a diagnosis considered a serious mental disorder due to its repercussion and durability. All patients were between 12 and 17 years of age. All of them were in school and doing their studies. Those cases that, despite meeting the criteria indicated, have not been able to access all the information necessary for their analysis because it is not included in their file have been excluded.
The time of the investigative analysis has been retrospective. Therefore, it is a longitudinal study in time that we have analyzed in the present with data from the past. We have analyzed the evolution of the student throughout his academic history until the moment in which he/she is hospitalized in serious condition. We have not taken into account the time after hospitalization. We have performed the analysis with the data collected up to the time of the onset of hospitalization. The analysis of the sample was carried out during the 2018–2019 school year in the Madrid Regional Authority.
We have taken into account, at all times, ethical principles consistent with scientific honesty and the protection of privacy in the cases analyzed [34]. The cases analysis was conducted by reviewing educational records opened for students hospitalized in a day care hospital working with adolescents with a SMD. In our research, we used secondary documents, not the real persons. We kept the anonymity of the cases throughout the whole research and did not ever use any real names. All cases were assigned a code so as to preserve anonymity. The educational director of the specialized center where the students are hospitalized authorized access to secondary reports. The reports were anonymized prior to submission for further analysis. We evaluated the data using a working matrix of a data sheet, which was the basis for analysis with SPSS. In this work matrix, we have added the data obtained from the reading of educational reports.
To conclude this section, we would like to point out, in relation to the conflict of interest, that the data collection was carried out by a member of the educational team working in the Day Hospital specialized in the care of students with SMD where the fieldwork was conducted. We consider that this element provided analytical depth and global vision to the development of the work.
In order to further develop our study, we drew upon a previous research. In that research, carried out under qualitative methodology, we inferred the main characteristics that define students with a SMD. This research used triangulation of in-depth interviews, questionnaires, and case analysis. More information can be found in [15]. This was the first step, but we could feel this investigation as the beginning of something that needed more depth of analysis. We also saw the need to use a larger sample with which to obtain greater rigor and statistical value. With this previous research, we verified that the model obtained was pertinent to the cases analyzed via a qualitative methodology. So, based on the data objected to in this previous research, we understand the present research have construct validity. It is also reliable, since it measures the relationship between variables that it claims to measure with statistical rigor – we explain this element in the next section. Once the sample is shaped, the next step was to define the variables to be used. Then, we have constructed a meaning for the variables, and we have established an observation map for completing the work matrix needed to develop this research. In the following section, we have read the educational reports of the selected students. The analyzed information was recorded in said files. With the reading of these reports, we have completed an ad hoc matrix. This statistical matrix synthesizes the description of the 109 cases observed, allowing us to reduce the complexity of the cases in qualitative terms to measurable and observable units. The records are made up of psycho-pedagogical reports and educational longitudinal information. This information provides data related to the evolution of the student throughout their educational career so far. Then, in relation to reliability, we affirm that we were able to access all the indicated information. Regarding the reliability of the coding of the observed variables, we have been looking for each variable in the report of each student. In the work matrix used, we marked whether it was met or not. Therefore, all the variables have been dichotomous, except for variable 14 – age – and variable 17 – when did the academic problems begin?. When the report did not provide the information needed, the case was dismissed.
Finally, the variables used and their statuses were as follows: (Table 1).
V1. | Accompanying family. We conceptualized this as a qualitative dichotomous variable: Family that accompanies positively in the therapeutic process of the child versus family that does not accompany positively. |
---|---|
V2. | Good bonding with the educational center. We conceptualized this as a qualitative dichotomous variable: has good school bonding versus poor school bonding. |
V3. | Academic success. The educational norm tells us that it is necessary to pass all but two subjects in order to move on to the next year. When the child is in this situation, we understand that he/she has achieved academic success. When the student has failed more than two subjects, we consider that he/she was not in a situation of academic success. We conceptualized this as a qualitative dichotomous variable. |
V4. | Sex. We have differentiated between female and male students. We conceptualized this as a qualitative dichotomous variable. |
V5. | They repeated some grade. We conceptualized this as a qualitative dichotomous variable: Repitieron algún grado frente a no repetir. |
V6. | Truancy/irregular assistance. We conceptualized this as a qualitative dichotomous variable: in the case of a student whose class attendance is not continued. |
V7. | Bad previous academic history. We conceptualized this as a qualitative dichotomous variable: bad previous school history versus good previous school history. |
V8. | Curricular lag. We considered this as a qualitative dichotomous variable: we have used the curricular lag as a variable that defines the level of educative competence that the student has in relation to their age. If the student has at least 1 year of curricular lag at least, we have understood that was pertinent to conceptualize the variable like positive. |
V9. | Good motivation toward study. We considered this as a qualitative dichotomous variable: has good study motivation versus does not have good study motivation |
V10. | Study habits. We considered this as a qualitative dichotomous variable: has study habits versus does not have study habits. |
V11. | Limited conceptual and procedural power/cognitive difficulties. Students with less procedural and conceptual skills have more difficulties and accumulated negative experiences in the educational context. This incidence in basic elements to participate in the dynamics of classroom-class predisposes students with serious mental disorders to have greater vulnerability in the educational context. This is because they do not meet the necessary skills to function in the methodological dynamics of a classroom. We considered this as a qualitative dichotomous variable. |
V12. | Attention difficulties. The attention difficulties are a circumstance present in many severe mental disorders. It is because, whether the disorder is externalizing or internalizing, the moment of the disorder marks the different. Being in a severe moment could involve having difficulties with attention due to circumstances such as problems arising from the disorder and medication, among others. We considered this as a qualitative dichotomous variable. |
V13. | Coexistence issues. We considered this as a qualitative dichotomous variable: presents coexistence problems versus does not present coexistence problems. |
V14. | Age. We considered this as a quantitative scale variable. |
V15. | Relational style (inhibited/uninhibited). We considered this as a qualitative dichotomous variable. |
V16. | Early detection. Early detection is a fundamental element to be able to conduct a good prognosis and minimize the impact of the disease on adulthood. We considered this as a qualitative dichotomous variable: has an early detection record versus does not have an early detection record. |
V17. | Onset of the educational issues. We considered this as a qualitative polychotomous variable. The ranges used were primary education, 1st year of secondary education, 2nd year of secondary education, 3rd year of secondary education, and 4th year of secondary education. |
V18. | Disorder typology. We conceptualized this as a qualitative dichotomous variable: externalizing versus internalizing. |
Variable.
A descriptive analysis of the quantitative variables yields the following data:
After collecting all the information on the work matrix, and identifying the items that apply to each participant in the sample, we used the exploratory factor analysis to conduct our research (Table 2). As this is a multivariate method that allows for reducing the dimensionality of a problem in a set of underlying variables, we considered it adequate for obtaining factors as a set of variables that allow us to understand the relationships between the variables previously described. Therefore, we looked for those factors that explain most of the common variance.
Statistics | |||
---|---|---|---|
Age | Academic problems begin | ||
N | Valid | 109 | 109 |
Missing | 0 | 0 | |
Mean | 14,69 | 1,05 | |
Std. deviation | 1296 | ,937 |
Academic problems begin.
We used an exploratory factor analysis with SPSS Statistics Mac software (v.20.0.0). For this analysis, we used all the variables that make up the study. After analyzing the correlation matrix, we decided on removing variables V4-Sex, V12-Difficulties of attention, and V16-Early detection. We noticed that, by removing them, we obtained a more adequate model, regardless of the values obtained from correlation, the level of Kaiser-Meyer-Olkin sample adequacy, and the significance of the Bartlett sphericity test. To make this decision, we have factored the analysis of communalities and the total value of the variance explained. Regardless of the variables used, we obtained communities close to and greater than .6, as well as better values for total variance. Also, we found greater explanatory coherence according to the theoretical model used, since our intention has been to reach the greatest possible objectivity through a reflective process in which, sometimes, the researcher has to distance himself/herself from the reality constructed by himself/herself [35]. We have ruled out that the variables can cause problems with collinearity because there are no values equal to or greater than 0.9 in the correlation matrix [36]. Finally, after dispensing with the variables indicated, we obtained a Kaiser-Meyer-Olkin sample adequacy result of .776 and significance in the Bartlett test p < .001. Since the Kaiser-Meyer-Olkin test is greater than 0.7, we can count this as a good value [37]. Bartlett’s sphericity test is <.05 and therefore significant. It indicates there are sufficient correlations between the variables to proceed. Given this data, we could say the factor analysis is relevant (Table 3).
Kaiser-Meyer-Olkin measure of sampling adequacy | .776 | |
---|---|---|
Bartlett’s test of sphericity | Approx. Chi-square | 721.333 |
df | 105 | |
Sig. | .000 |
Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett\'s test of sphericity.
Analysis of the anti-image correlation matrix through the sample adequacy measure shows that, once said variables are eliminated and we work with the chosen model, all the variables show high correlation. We have used the anti-image correlation matrix analysis because it is the most suitable for principal component analysis, and this is the method we have used. This method gives us a representation of variance for each variable explained by the factors. The data obtained in the table of communalities offer adequate extraction values, since they are close to or above 0.6 (Tables 4 and 5) [38].
V1 | V2 | V3 | V5 | V6 | V7 | V8 | V9 | V10 | V11 | V13 | V14 | V15 | V17 | V18 | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
V1 | .615 | −.164 | −.032 | −.018 | −.041 | −.107 | .090 | −.161 | .048 | −.115 | −.026 | .096 | .015 | .130 | −.065 | |
V2 | −.164 | .549 | −.109 | −.017 | .189 | .048 | −.019 | .072 | −.063 | .068 | .064 | .041 | −.078 | −.063 | .032 | |
V3 | −.032 | −.109 | .429 | .081 | .018 | .083 | −.044 | −.068 | −.094 | .025 | −.036 | .013 | .000 | .045 | −.067 | |
V5 | −.018 | −.017 | .081 | .540 | .007 | −.091 | −.025 | .031 | .037 | .000 | −.005 | .146 | −.052 | −.086 | −.066 | |
V6 | −.041 | .189 | .018 | .007 | .742 | −.061 | −.027 | −.038 | .042 | .071 | −.008 | .031 | −.061 | .041 | .115 | |
V7 | −.107 | .048 | .083 | −.091 | −.061 | .289 | −.155 | .060 | −.033 | .026 | .022 | .012 | .032 | −.105 | .003 | |
V8 | .090 | −.019 | −.044 | −.025 | −.027 | −.155 | .324 | −.003 | .048 | −.211 | .010 | −.057 | −.001 | .055 | −.007 | |
V9 | −.161 | .072 | −.068 | .031 | −.038 | .060 | −.003 | .397 | −.186 | .077 | .037 | .039 | −.048 | −.091 | −.010 | |
V10 | .048 | −.063 | −.094 | .037 | .042 | −.033 | .048 | −.186 | .418 | −.105 | −.015 | .001 | −.004 | .063 | .081 | |
V11 | −.115 | .068 | .025 | .000 −005 | .071 | .026 | −.211 | .077 | −.105 | .487 | .015 | .054 | −.078 | −.084 | .009 | |
V13 | −.026 | .064 | −.036 | −.005 | −.008 | .022 | .010 | .037 | −.015 | .015 | .353 | .023 | .161 | −.146 | −.162 | |
V14 | .096 | .041 | .013 | .146 | .031 | .012 | −.057 | .039 | .001 | .054 | .023 | .698 | .003 | −.191 | −.043 | |
V15 | .015 | −.078 | .000 | −.052 | −.061 | .032 | −.001 | −.048 | −.004 | −.078 | .161 | .003 | .447 | −.036 | .094 | |
V17 | .130 | −.063 | .045 | −.086 | .041 | −.105 | .055 | −.091 | .063 | −.084 | −.146 | −.191 | −.036 | .468 | .037 | |
V18 | −.065 | .032 | −.067 | −.066 | .115 | .003 | −.007 | −.010 | .081 | .009 | −.162 | −.043 | .094 | .037 | .436 | |
V1 | .632a | −.283 | −.062 | −.032 | −.061 | −.253 | .201 | −.327 | .094 | −.210 | −.057 | .147 | .029 | .243 | −.125 | |
V2 | −.283 | .795a | −.224 | −.031 | .296 | .120 | −.045 | .155 | −.132 | .132 | .145 | .067 | −.157 | −.124 | .065 | |
V3 | −.062 | −.224 | .882a | .168 | .032 | .234 | −.117 | −.164 | −.223 | .055 | −.092 | .024 | −.001 | .100 | −.155 | |
V5 | −.032 | −.031 | .168 | .878a | .011 | −.230 | −.060 | .066 | .079 | .000 | −.012 | .238 | −.107 | −.171 | −.137 | |
V6 | −.061 | .296 | .032 | .011 | .672a | −.131 | −.055 | −.070 | .075 | .118 | −.015 | .044 | −.106 | .069 | .203 | |
V7 | −.253 | .120 | .234 | −.230 | −.131 | .799a | −.507 | .178 | −.096 | .071 | .069 | .026 | .089 | −.286 | .008 | |
V8 | .201 | −.045 | −.117 | −.060 | −.055 | −.507 | .741a | −.009 | .131 | −.532 | .031 | −.120 | −.002 | .141 | −.020 | |
V9 | −.327 | .155 | −.164 | .066 | −.070 | .178 | −.009 | .799a | −.458 | .174 | .100 | .075 | −.115 | −.210 | −.024 | |
V10 | .094 | −.132 | −.223 | .079 | .075 | −.096 | .131 | −.458 | .820a | −.233 | −.040 | .002 | −.010 | .142 | .189 | |
V11 | −.210 | .132 | .055 | .000 | .118 | .071 | −.532 | .174 | −.233 | .646a | .037 | .092 | −.168 | −.176 | .019 | |
V13 | −.057 | .145 | −.092 | −.012 | −.015 | .069 | .031 | .100 | −.040 | .037 | .742a | .046 | .405 | −.358 | −.413 | |
V14 | .147 | .067 | .024 | .238 | .044 | .026 | −.120 | .075 | .002 | .092 | .046 | .748a | .005 | −.335 | −.078 | |
V15 | .029 | −.157 | −.001 | −.107 | −.106 | .089 | −.002 | −.115 | −.010 | −.168 | .405 | .005 | .803a | −.079 | .212 | |
V17 | .243 | −.124 | .100 | −.171 | .069 | −.286 | .141 | −.210 | .142 | −.176 | −.358 | −.335 | −.079 | .735a | .081 | |
V18 | −.125 | .065 | −.155 | −.137 | .203 | .008 | −.020 | −.024 | .189 | .019 | −.413 | −.078 | .212 | .081 | .762a | |
Measures of sampling adequacy (MSA) |
Matrix of anti-image correlations.
Initial | Extraction | |
---|---|---|
Accompanying family | 1.000 | .672 |
Good bonding with the educational center | 1.000 | .583 |
Academic success | 1.000 | .659 |
They have repeated some grade | 1.000 | .588 |
Truancy/irregular assistance | 1.000 | .657 |
Bad previous academic history | 1.000 | .771 |
Curricular lag | 1.000 | .730 |
Good motivation toward study | 1.000 | .570 |
Study habits | 1.000 | .614 |
Reduced conceptual and procedural power/cognitive difficulties | 1.000 | .692 |
Coexistence problems | 1.000 | .769 |
Age | 1.000 | .661 |
Relational style | 1.000 | .717 |
Disorder typology | 1.000 | .761 |
Onset of the educational issues | 1.000 | .570 |
Commonalities obtained through principal component analysis.
Extraction method: principal component analysis.
To determine the number of factors extracted, we took into account the initial self-values, the total of the explained variance, and the theoretical model. Looking at Table 6, we find that all four factors selected are above 1. Therefore, we have performed the factor analysis extracting four factors. Although with other models we obtained a higher percentage of the total variance explained, we consider the chosen model does a better job at explaining its representation from a theoretical point of view.
Initial autovalues | Extraction sums of squared loadings | Rotation sums of squared loadings | |||||||
---|---|---|---|---|---|---|---|---|---|
Component | Total | % of variance | Cumulative% | Total | % of variance | Cumulative % | Total | % of variance | Cumulative % |
1 | 4.880 | 32.536 | 32.536 | 4.880 | 32.536 | 32.536 | 3.238 | 21.584 | 21.584 |
2 | 2.607 | 17.381 | 49.916 | 2.607 | 17.381 | 49.916 | 2.827 | 18.846 | 40.429 |
3 | 1.355 | 9.034 | 58.950 | 1.355 | 9.034 | 58.950 | 1.997 | 13.315 | 53.745 |
4 | 1.172 | 7.813 | 66.763 | 1.172 | 7.813 | 66.763 | 1.953 | 13.019 | 66.763 |
5 | .911 | 6.073 | 72.836 | ||||||
6 | .764 | 5.096 | 77.932 | ||||||
7 | .627 | 4.181 | 82.113 | ||||||
8 | .506 | 3.372 | 85.485 | ||||||
9 | .445 | 2.964 | 88.449 | ||||||
10 | .433 | 2.885 | 91.333 | ||||||
11 | .343 | 2.289 | 93.622 | ||||||
12 | .300 | 2.001 | 95.623 | ||||||
13 | .270 | 1.799 | 97.422 | ||||||
14 | .231 | 1.540 | 98.962 | ||||||
15 | .156 | 1.038 | 100.000 |
Total variance explained with the first four factors.
Extraction method: principal component analysis.
In other words, we weighted the part of the common variance that enables us to explain these factors with greater theoretical sense. We therefore seek an interpretation that combines parsimony and plausibility [38].
The total accumulated variance value is 66.763%, which, together with the criteria described earlier, allows us to think about the model’s adequacy. As the value obtained is above .60%, we consider it appropriate [37] (Table 6).
The extraction method is the principal component analysis, while rotation type is orthogonal with the varimax method. We see each factor is represented by three or more variables; therefore, we consider that the model obtained meets moderate conditions for interpretation (Tables 7 and 8) [38].
Component | ||||
---|---|---|---|---|
1 | 2 | 3 | 4 | |
Accompanying family | −.439 | .011 | .652 | −.233 |
Good bonding with the educational center | −.624 | .090 | .263 | .341 |
Academic success | −.736 | −.262 | .146 | .166 |
They repeated some grade | .641 | .198 | .351 | −.119 |
Truancy/irregular assistance | .201 | .400 | −.268 | −.620 |
Previous academic history | .777 | .331 | .238 | −.034 |
Curricular lag | .650 | .462 | .248 | .181 |
Motivation toward study | −.751 | .016 | .075 | .001 |
Study habits | −.734 | .161 | .092 | .202 |
Reduced conceptual and procedural power/cognitive difficulties | .365 | .555 | .388 | .316 |
Coexistence problems | .434 | −.739 | .184 | −.017 |
Age | .411 | −.178 | −.452 | .506 |
Relational style | −.376 | .737 | −.113 | .138 |
Disorder typology | .327 | −.738 | .331 | −.016 |
Onset of the educational issues | .662 | −.084 | −.034 | .353 |
Matrix of main components.
Extraction method: principal component analysis. a. Four components extracted.
Component | ||||
---|---|---|---|---|
1 | 2 | 3 | 4 | |
Accompanying family | −.005 | .044 | .275 | |
Good bonding with the educational center | −.167 | −.276 | .262 | |
Academic success | −.509 | −.037 | .287 | |
They have repeated some grade | .205 | −.274 | .061 | |
Truancy/irregular assistance | .051 | −.286 | .135 | |
Bad previous academic history | .101 | −.334 | −.108 | |
Curricular lag | −.079 | −.125 | −.155 | |
Good motivation toward study | −.288 | .369 | .373 | |
Study habits | −.327 | −.420 | .279 | |
Reduced conceptual and procedural power/cognitive difficulties | −.241 | .152 | −.003 | |
Coexistence problems | .033 | −.023 | −.137 | |
Age | .069 | .125 | .056 | |
Relational style | .069 | .121 | .092 | |
Disorder typology | .038 | .085 | .009 | |
Onset of the educational issues | .467 | .289 | −.025 |
Rotated component matrix.
Extraction method: principal component analysis. Rotation method: varimax with Kaiser normalization. a. Rotation converged in six iterations.
We will focus our analysis on the rotated components matrix and not on the main components matrix. In this way, we obtain what is called the simple structure principle, achieving a better scientific interpretation of the obtained factors, since we give more importance to the variables that obtain greater weight in the obtained factors [39].
Analyzing the matrix of rotated components, we can see factor number 1 is formed by these variables:
V5. They have repeated some course.
V7. Bad previous school history.
V8. Curricular lag.
V9. Motivation toward study.
V11. Reduced conceptual and procedural power/cognitive difficulties.
We called this factor
Factor number 2, which we will call the
V18. Type of disorder.
V15. Relational style.
V13. Coexistence problems.
We can observe that, in all three cases, the weight of the variables in the factor is higher than 0.8, so we consider that their contribution is relevant.
Factor number 3, which we will call
V2. Good bonding with the educational center.
V3. Academic success.
V6. Truancy. Irregular assistance.
V10. Study habits.
Of the four variables that make up the factor, the best representations are V6 and V2. We can see the other variables have a lesser weight.
Finally, factor number 4 will consist of these variables:
V1. Accompanying family.
V14. Age.
V17. Onset of the academic issues.
We called this factor
Study limitations | Symptomatology representation | ||
---|---|---|---|
They have repeated some course Bad previous school history Curricular lag Motivation toward study Reduced conceptual and procedural power/cognitive difficulties | Type of disorder Relational style Coexistence problems | Good bonding with the educational center Academic success Truancy. Irregular assistance Study habits. | Accompanying family Age Onset of the academic issues |
Factors.
Beyond the mental disorder and knowing how it is represented, we have tried to understand how it is present in the educational environment. We believe that knowing how MSD is represented in the 109 cases analyzed can help us to deepen the understanding and establishment of compensation mechanisms in preventive terms [3]. Only by understanding and knowing the elements that define a reality in contextual terms, we can develop and implement educational measures that are empathetic [40].
Therefore, we wanted to look at the common elements the students with mental disorders show when in a severe condition. We used 18 variables to test them using the quantitative methodology. In the interpretation of the exploratory factor analysis that we have carried out, we have decided to dispense with the variables V4-Sex, V12-Attention Difficulties, and V16-Early Detection. Using these three variables, the factorial models obtained were less statistically consistent. Therefore, in making the decision not to include the three variables we have dispensed with in the proposed factor analysis, we have taken into account both the statistical data obtained and the theoretical framework. We put theory and data together to make a decision. In this way, we were able to obtain a more consistent factor model.
We observed that the variable V12 expresses a symptomatic value that mainly affects externalizing disorders. We were also able to observe that without this variable in the factor analysis, we obtained better statistical results. So given that its contribution to the model generated many doubts from a statistical point of view, and after reviewing the theoretical framework, we decided to eliminate this variable.
Regarding variable V16, we can see it defines a time frame from the clinical perspective. The analysis we are doing focuses on the educational field. In this sense, it must be said we already had another variable covering the moment in which the disorder visibly affects the educational environment, and that is variable V17 – when academic problems start. Thus, given the little representativeness obtained for the model by incorporating variable V16 and the weight of the interpretation carried out under the theoretical framework, we decided to continue without it.
Therefore we find that, when in a serious situation, students with mental disorders show a profile that could be defined by the following factors:
Study Limitations
Symptomatology Representation
Study Facilitators
Other Limitations.
The four factors obtained explain 66.763% of the total variance. Thus, we can affirm that the reduction to four factors gives us a satisfactory result.
With this research, we want to gain an in-depth understanding of the way in which mental disorder is represented in the educational environment through the 18 variables used in the population analyzed. We understand that, when implementing educational practices that serve students with severe mental disorders, we should think about working along four different lines. These intervention lines cannot be understood without the others; therefore, the practices to be implemented should involve specific actions in each of the indicated factors.
In this regard, we observe that the factor
Regarding the
The
With the factor
We consider this research as a descriptive approach that brings us closer to the object studied. In statistical terms, the exploratory factor analysis has been statistically relevant, since we obtained a Kaiser-Meyer-Olkin sample adequacy result of .776 and significance in the Bartlett test p < .001. In conceptual terms, we have been able to understand which are the factorial groups that condition the educational reality of a student with a serious mental disorder. These factors indicate the elements to work to help this population achieve academic success. On the other hand, they also point out the main risk factors that a student with a mental disorder could have. This would allow for preventive pedagogical practices. Therefore, we consider factor analysis to be informative for the data set.
Finally, we could have investigated in relation to the variables that predict school results in this population. We could also have analyzed the differences between students with externalizing disorders versus internalizing. Likewise, to know with certainty the adequacy of the information from the factor analysis for the data set, it is necessary to perform a confirmatory factor analysis. We are indicated these elements as limitations of the present investigation. We will investigate future research in relation to these elements.
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