38 research outputs found
Conversational Artificial Intelligence in Psychotherapy: A New Therapeutic Tool or Agent?
Conversational artificial intelligence (CAI) presents many opportunities in the psychotherapeutic landscape-such as therapeutic support for people with mental health problems and without access to care. The adoption of CAI poses many risks that need in-depth ethical scrutiny. The objective of this paper is to complement current research on the ethics of AI for mental health by proposing a holistic, ethical, and epistemic analysis of CAI adoption. First, we focus on the question of whether CAI is rather a tool or an agent. This question serves as a framework for the subsequent ethical analysis of CAI focusing on topics of (self-) knowledge, (self-)understanding, and relationships. Second, we propose further conceptual and ethical analysis regarding human-AI interaction and argue that CAI cannot be considered as an equal partner in a conversation as is the case with a human therapist. Instead, CAI's role in a conversation should be restricted to specific functions.
Keywords: Artificial intelligence; agency; ethics; psychotherapy; therapeutic alliance
Conversational AI for Psychotherapy and Its Role in the Space of Reason
The recent book by Landgrebe and Smith (2022) offers compelling arguments against the possibility of Artificial General Intelligence (AGI) as well as against the idea that machines have the abilities to master human language, human social interaction and morality. Their arguments leave open, however, a problem on the side of the imaginative power of humans to perceive more than there is and treat AIs as humans and social actors independent of their actual properties and abilities or lack thereof. The mathematical and ontological arguments will not help against this strong human tendency to treat conversational AI (CAI) as if it was human
The Role of Humanization and Robustness of Large Language Models in Conversational Artificial Intelligence for Individuals With Depression: A Critical Analysis
Large language model (LLM)–powered services are gaining popularity in various applications due to their exceptional performance in many tasks, such as sentiment analysis and answering questions. Recently, research has been exploring their potential use in digital health contexts, particularly in the mental health domain. However, implementing LLM-enhanced conversational artificial intelligence (CAI) presents significant ethical, technical, and clinical challenges. In this viewpoint paper, we discuss 2 challenges that affect the use of LLM-enhanced CAI for individuals with mental health issues, focusing on the use case of patients with depression: the tendency to humanize LLM-enhanced CAI and their lack of contextualized robustness. Our approach is interdisciplinary, relying on considerations from philosophy, psychology, and computer science. We argue that the humanization of LLM-enhanced CAI hinges on the reflection of what it means to simulate “human-like” features with LLMs and what role these systems should play in interactions with humans. Further, ensuring the contextualization of the robustness of LLMs requires considering the specificities of language production in individuals with depression, as well as its evolution over time. Finally, we provide a series of recommendations to foster the responsible design and deployment of LLM-enhanced CAI for the therapeutic support of individuals with depression
Comparison of analog and digital patient decision aids for the treatment of depression: a scoping review
Introduction: Patient decision aids (PDAs) are important tools to empower patients and integrate their preferences and values in the decision-making process. Even though patients with mental health problems have a strong interest in being more involved in decision making about their treatment, research has mainly focused on PDAs for somatic conditions. In this scoping review, we focus on patients suffering from depression and the role of PDAs for this patient group. The review offers an overview of digital and analog PDAs, their advantages and disadvantages as well as recommendations for further research and development.
Methods: A systematic search of the existing literature guided by the Cochrane Handbook for Systematic Reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses - extension for scoping reviews (PRISMA-ScR) was conducted. Three electronic literature databases with the appropriate thematic focus were searched (PubMed, PsycInfo, and Web of Science). The search strategy used controlled and natural language to search for the key concepts decision aids and depression. The articles were selected in a two-step process guided by predefined inclusion and exclusion criteria. We narratively synthetized information extracted from 40 research articles.
Results: We included 40 articles in our review. Our review revealed that there is more focus on digital PDAs in research than in clinical practice. Digitalization can enhance the benefits of PDAs by developing tools that are more efficient, interactive, and personalized. The main disadvantages of both types of PDAs for the treatment of depression are related to time, dissemination, and capacity building for the health care providers. Digital PDAs need to be regularly updated, effective strategies for their dissemination and acceptance need to be identified, and clinicians need sufficient training on how to use digital PDAs. There is more research needed to study which forms of PDAs are most appropriate for various patient groups (e.g., older adults, or patients with comorbidities), and to identify the most effective ways of PDAs' integration in the clinical workflow. The findings from our review could be well aligned with the International Patient Decision Aids Standards.
Discussion: More research is needed regarding effective strategies for the implementation of digital PDAs into the clinical workflow, ethical issues raised by the digital format, and opportunities of tailoring PDAs for diverse patient groups
Challenges and best practices for digital unstructured data enrichment in health research: A systematic narrative review
Digital data play an increasingly important role in advancing health research and care. However, most digital data in healthcare are in an unstructured and often not readily accessible format for research. Unstructured data are often found in a format that lacks standardization and needs significant preprocessing and feature extraction efforts. This poses challenges when combining such data with other data sources to enhance the existing knowledge base, which we refer to as digital unstructured data enrichment. Overcoming these methodological challenges requires significant resources and may limit the ability to fully leverage their potential for advancing health research and, ultimately, prevention, and patient care delivery. While prevalent challenges associated with unstructured data use in health research are widely reported across literature, a comprehensive interdisciplinary summary of such challenges and possible solutions to facilitate their use in combination with structured data sources is missing. In this study, we report findings from a systematic narrative review on the seven most prevalent challenge areas connected with the digital unstructured data enrichment in the fields of cardiology, neurology and mental health, along with possible solutions to address these challenges. Based on these findings, we developed a checklist that follows the standard data flow in health research studies. This checklist aims to provide initial systematic guidance to inform early planning and feasibility assessments for health research studies aiming combining unstructured data with existing data sources. Overall, the generality of reported unstructured data enrichment methods in the studies included in this review call for more systematic reporting of such methods to achieve greater reproducibility in future studies
Ethics of telepsychiatry versus face-to-face treatment: let the patients make their autonomous choice
Badanie mechanizmów stosowanych przez glony w celu zmniejszenia toksyczności srebra w środowisku wodnym
In the study SEM, EDS, TEM and UV-vis analysis were used to investigate the biosorption, bioaccumulation and bioprecipitation/bioreduction of silver by freshwater green alga Parachlorella kessleri and to shed light on the reasons of biological silver nanoparticle production. When dead biomass of P. kessleri was used for silver removal, majority of silver (75%) was removed within 2 min. Biosorption was probably the main mechanisms responsible for Ag+ ions removal from aqueous solutions. However, when behaviour of living biomass in the presence of silver ions was studied, the decrease of silver concentration was slower (68% within 24 hours) with subsequent increase of silver concentration in the solution and extracellular formation of silver nanoparticles. The formed AgNPs exhibited a lower toxicity against tested organisms. Algal cells probably used the formation of nanoparticles combined with rapid biosorption as detoxification mechanisms against silver toxicity. Bioaccumulation inside the cells played only a minor role in the detoxification process.W badaniu wykorzystano analizę SEM, EDS, TEM i UV-vis do zbadania biosorpcji, bioakumulacji i bioprecypitacji/bioredukcji
srebra przez słodkowodną zieloną algę Parachlorella kessleri i rzucenia światła na przyczyny biologicznej produkcji nanocząstek srebra. Gdy do usunięcia srebra użyto martwej biomasy P. kessleri, większość srebra (75%) usunięto w ciągu 2 minut. Biosorpcja była prawdopodobnie głównym mechanizmem odpowiedzialnym za usuwanie jonów Ag+ z roztworów wodnych. Jednakże, gdy badano zachowanie żywej biomasy w obecności jonów srebra, spadek stężenia srebra był wolniejszy (68% w ciągu 24 godzin) z późniejszym wzrostem stężenia srebra w roztworze i zewnątrzkomórkowym tworzeniem nanocząstek srebra. Utworzone AgNP wykazywały mniejszą toksyczność wobec badanych organizmów. Komórki glonów prawdopodobnie wykorzystywały tworzenie nanocząstek połączonych z szybką biosorpcją jako mechanizmów detoksykacji przeciwko toksyczności srebra. Bioakumulacja wewnątrz komórek odgrywała tylko niewielką rolę w procesie detoksykacji
Hypomagnetic Fields and Their Multilevel Effects on Living Organisms
The Earth’s magnetic field is one of the basic abiotic factors in all environments, and organisms had to adapt to it during evolution. On some occasions, organisms can be confronted with a significant reduction in a magnetic field, termed a “hypomagnetic field—HMF”, for example, in buildings with steel reinforcement or during interplanetary flight. However, the effects of HMFs on living organisms are still largely unclear. Experimental studies have mostly focused on the human and rodent models. Due to the small number of publications, the effects of HMFs are mostly random, although we detected some similarities. Likely, HMFs can modify cell signalling by affecting the contents of ions (e.g., calcium) or the ROS level, which participate in cell signal transduction. Additionally, HMFs have different effects on the growth or functions of organ systems in different organisms, but negative effects on embryonal development have been shown. Embryonal development is strictly regulated to avoid developmental abnormalities, which have often been observed when exposed to a HMF. Only a few studies have addressed the effects of HMFs on the survival of microorganisms. Studying the magnetoreception of microorganisms could be useful to understand the physical aspects of the magnetoreception of the HMF
SPOTREBITEL'SKE SPRAVANIE SA MLADYCH SLOVENSKYCH KONZUMENTOV - VPLYV ETNOCENTRIZMU A POVDU POTRAVIN
This study examines the consumer's perception in the field of national food products and ethnocentric tendencies among young Slovak consumers — students. The image of Slovakia and Slovak food products has also been analysed. The study shows that young consumers prefer domestic food products. More than a half of the respondents pointed out the importance of the country of the origin of the product
Wpływ metali ciężkich na rozwój odporności na zawartość metali w mikroflorze w glebie
Heavy metal pollution caused by anthropogenic activity is a great concern of the present days. Widespread use of substances containing metals inevitably lead to their deposition in soil affecting soil microbiota, which plays important role in maintaining soil functions. The aim of our study was to determine number of heavy metal resistant isolates acquired from the soil from heavy metal polluted area of dump near Hnúšťa. Soil samples were obtained from two collection sites (48° 36´ 4,47502´´ N, 19° 57´32,654´´ E and 48° 36´ 4,4634´´ N, 19° 57´ 32,67´´ E) and mixed together. The microorganisms used in this study were routinely cultivated and screened for resistance to different concentrations of four heavy metals – Zn (2–500 mg/l), Cu, Ni, Pb (all three metals tested at concentrations from 0,5 to 125 mg/l). Very high resistance against Cu, Ni and Pb even at the highest tested concentrations was found at majority of tested bacterial strains. Almost all 89 from 89 isolates show resistance against these metals at tested concentrations. Only in case of Zn we determined the MIC (minimal inhibitory concentration) – 125 mg/l. The results point out very high resistance pattern in soil bacteria.Zanieczyszczenie metalami ciężkimi wywołane działalnością antropogeniczną jest wielkim problemem współczesności. Powszechne stosowanie substancji zawierających metale nieuchronnie prowadzi do ich odkładania się w glebie co wpływa na mikroflorę glebową, która odgrywa ważną rolę w utrzymywaniu funkcji gleby. Celem badań było określenie liczby izolatów odpornych na metale ciężkie pozyskanych z gleby z zanieczyszczonego obszaru składowiska metali ciężkich w pobliżu Hnúšťa. Próbki gleby pobrano z dwóch miejsc (48° 36' 4,47502'' N, 19° 57'32,654'' E i 48° 36' 4,4634''bN, 19° 57'32,67'' E) i wymieszano razem. Mikroorganizmy wykorzystane w tym badaniu były rutynowo hodowane i badane pod kątem odporności na różne stężenia czterech metali ciężkich: Zn (2–500 mg/l), Cu, Ni, Pb (wszystkie trzy badane metale w stężeniach od 0,5 do 125 mg/l). Bardzo wysoką odporność na Cu, Ni i Pb nawet przy najwyższych testowanych stężeniach stwierdzono w większości badanych szczepów bakteryjnych. Prawie wszystkie z 89 izolatów wykazują odporność na te metale w testowanych stężeniach. Tylko w przypadku Zn określiliśmy MIC (minimalne stężenie hamujące) = 125 mg/l. Wyniki wskazują na bardzo wysoki wzór oporności w bakteriach glebowych