Leonas, Linas

Impaired mentalizing abilities are found among persons with chronic pain, yet it is still unknown why. The current study focuses on mentalizing abilities and how these could be affected by different pain factors, alexithymia traits, and other aspects of psychological functioning (depression, anxiety, attention) in persons experiencing chronic pain.

Although Artificial Intelligence and its applications in medicine are growing rapidly, its integration into mental health remains at an early stage. The aim of the study is to evaluate psychology students’ attitudes and the significance of brief interventions towards Artificial Intelligence systems and their application in mental healthcare. The study involved 62 psychology students (M= 23.19±4.69; 85.5% women). Thirty-one participants tested the Artificial Intelligence-based emotional support app Wysa, and thirty-one others watched a presentation on the use of Artificial Intelligence in providing psychological assistance, based on the latest scientific research. Attitudes towards Artificial Intelligence were assessed before and after the interventions using the General Attitudes towards Artificial Intelligence Scale and an adapted version of the Questionnaire for Attitudes Toward Medical Application of Artificial Intelligence to examine psychologists’ attitudes towards the use of artificial intelligence in their work. During interventions, facial expression analysis software FaceReader was used to assess participants’ emotions. Following a scientific presentation, participants showed significative increases in positive attitudes, compared to those who used Wysa. While improvements in negative attitudes were noted, these did not differ significantly between groups. Positive changes in perceived Artificial Intelligence advantages were positively associated with feelings of surprise and fear, and negatively with contempt and disgust. Perceived Artificial Intelligence disadvantages correlated positively with contempt. The scientific presentation helped students develop more positive attitudes toward Artificial Intelligence, suggesting that education on Artificial Intelligence is important in shaping future psychologists’ view on new technologies. Emotional responses (particularly surprise, fear, disgust, and contempt) played a significant role in these attitude changes.

Introduction. Sound can both enhance and disturb concentration. Most studies look exclusively at white noise or the effects of listening to music in general. In this study, we aim to fill two gaps: to investigate the effects of brown noise and to compare the effects of instrumental classical music and songs with lyrics on attention. Methods. The experiment involved 30 adult participants. Participants performed five tasks with different auditory stimuli (silence, white noise, brown noise, music with words and classical music). The loudness of all stimuli was ~65 dB. In each task, the participant read a text, mentally counted the words in the specified categories and answered a question about the plot after reading. All texts were of similar length, each containing words from two different semantic categories, with between 5 and 25 words in each category. The order of presentation of the auditory conditions was balanced using a 5 × 5 Latin square, with a 3-minute break between tasks. Participants came to the experiment twice on different days, with a mirrored sequence of auditory conditions on the second visit. The tasks were presented using a custom computer program. The data were collected in two ways: eye movement recording using “Tobii Pro” to count the number and duration of gaze fixations in the text and lateral areas; and video analysis using cameras in the lab and “Viso” and “ObserverXT” software to assess eye blinks, head/body movements and frequency of facial expressions. Results. The results showed no statistically significant differences between the different sound conditions (p > 0.05). Conclusions. This may be explained by the greater influence of individual personal traits, sensory sensitivity or method limitations. Also, a cognitively demanding task may have placed a maximum load on the cognitive systems and rendered the auditory background irrelevant in the context of the overall processes (“ceiling”; effect).

Įvadas. Nors medicinoje dirbtinis intelektas (DI) ir jo pritaikymas vystosi greitai, ir yra naudingas tiek medicinos personalui, tiek pacientams (Liuir kt., 2018), dirbtinio intelekto integracija į psichikos sveikatos priežiūrą vis dar yra ankstyvoje stadijoje (Fiske ir kt., 2019). Tyrimo tikslas –įvertinti psichologijos studentų požiūrį ir trumpų intervencijų reikšmę į psichologinę pagalbą teikiančias dirbtinio intelekto sistemas.Metodai.Tyrime dalyvavo 53 psichologijos studentai nuo 18 iki 43 metų (M=23,40 ± 5,024; 83% moterys) -27 studentai išmėgino DI paremtą emocinės pagalbos programėlę „Wysa“, o 26 studentai stebėjo moksliniais duomenimis grįstą prezentaciją apie DI panaudojimą psichologinei pagalbai teikti. Požiūris į DI vertintas prieš ir po intervencijų Bendro požiūrio į dirbtinį intelektą skale ir Oh ir kt. (2019) klausimynu, pritaikytu tirti psichologų požiūrį į DI taikymą savo darbe. Abiejų intervencijų metu, emocijų vertinimui taikyta automatizuota veido išraiškų matavimo sistema „FaceReader“.Rezultatai. Lyginant grupes nustatyti statistiškai reikšmingi emocijų skirtumai -Wysa grupėje stebėti aukštesni „pykčio“, „paniekos“, „pasibjaurėjimo“ ir „laimės“ įverčiai (Mann-Whitney U p= 0,04; 0,01; <0,001; <0,001), o pristatymo grupėje –aukštesnis „neutralios“ būsenos lygis (Mann-Whitney U p<0,00). XXI JMPK28Lyginant požiūrį prieš ir po intervencijų, nustatyta, kad „Bendro požiūrio į DI psichologijoje“ ir „DI naudojimo psichologijoje privalumų“ pokytis buvo statisiškai reikšmingas ir priklausė nuo grupės (kartotinių matavimų ANOVA, atitinkamai F(1,51) = 14, 176, p < 0.001; F(1,51) = 6,779, p= 0,012) –pristatymą stebėjusių studentų tarpe, požiūrio įverčiai po intervencijos buvo statistiškai reikšmingai aukštesni (F(1,25) = 28,580, p< 0,001; F(1,25) = 6,882, p= 0,015). Po intervencijos, prezentaciją stebėję dalyviai demonstravo ir reikšmingai aukštesnius „Teigiamo požiūrio į DI“ įverčius (F(1,25) = 18,496, p= 0,017). Programėlę naudojusių dalyvių tarpe reikšmingi požiūrio į DI pokyčiai nenustatyti.Išvados.Po prezentacijos apie dirbtinio intelekto panaudojimą psichologinei pagalbai teikti, stebėti teigiami požiūrio į DI psichologijoje pokyčiai, o DI paremtos emocinės pagalbos programėlės išbandymas dalyvių požiūrio nepakeitė. Tai gali lemti didesnis studentų pasitikėjimas mokslu grįstais duomenimis apie DI nei praktiniu metodų išbandymu.

Įvadas. Nors medicinoje dirbtinis intelektas (DI) ir jo pritaikymas vystosi greitai, ir yra naudingas tiek medicinos personalui, tiek pacientams (Liu ir kt., 2018), dirbtinio intelekto integracija į psichikos sveikatos priežiūrą vis dar yra ankstyvoje stadijoje (Fiske ir kt., 2019). Tyrimo tikslas – įvertinti psichologijos studentų požiūrį į psichologinę pagalbą teikiančias DI sistemas ir požiūrio pokytį po trumpų intervencijų. Metodai. Tyrime dalyvavo 35 psichologijos studentai (amžius=23,11 ± 4,993; 85,7% moterys) - 18 studentų išmėgino DI paremtą emocinės pagalbos programėlę „Wysa“, o 17 studentų stebėjo moksliniais duomenimis grįstą prezentaciją apie DI panaudojimą psichologijoje. Požiūris į DI vertintas prieš ir po intervencijų Bendro požiūrio į dirbtinį intelektą skale ir Oh ir kt. (2019) klausimynu, pritaikytu tirti psichologų požiūrį į DI taikymą savo darbe. Abiejų intervencijų taikymo metu taip pat naudota ir automatizuota emocijų vertinimo sistema „FaceReader“. Rezultatai. Lyginant grupes nustatyti statistiškai reikšmingi emocijų skirtumai - Wysa grupėje stebėti aukštesni „pykčio“, „paniekos“, „pasibjaurėjimo“, „laimės“ ir „baimės“ įverčiai (Mann-Whitney U p=0.02; 0.03; <0.001; <0.001; 0.09), o pristatymo grupėje – aukštesnis „neutralios“ būsenos lygis (Mann-Whitney U p<0.00). Lyginant požiūrio įverčius prieš ir po intervencijų, nustatyta, kad prieš intervencijas „Bendras požiūris į DI psichologijoje“ tarp grupių nesiskyrė (Mann-Whitney U p=0.252), o po intervencijų, pristatymą stebėjusių tiriamųjų tarpe, „Bendras požiūris į DI psichologijoje“ buvo statistiškai reikšmingai aukštesnis, lyginant su „Wysa“ grupe (MannWhitney U p=0.010). Analizuojant pokyčius grupėse nustatyta, kad po intervencijos, prezentaciją stebėję dalyviai demonstravo reikšmingai aukštesnius „Bendro požiūrio į DI psichologijoje“, „DI naudojimo psichologijoje privalumų“ ir „Teigiamo požiūrio į DI“ įverčius (Vilkoksono ženklų kriterijus p=0.001; 0.013; 0.017). Programėlę naudojusių dalyvių tarpe reikšmingi požiūrio į DI pokyčiai nestebėti. Diskusija ir išvados. Po prezentacijos apie dirbtinio intelekto panaudojimą psichologijoje, stebėti teigiami požiūrio į DI psichologijoje pokyčiai, o DI paremtos emocinės pagalbos programėlės išbandymas dalyvių požiūrio nepakeitė – tai galėjo lemti didesnis studentų pasitikėjimas mokslu grįstais duomenimis.

Introduction. While artificial intelligence (AI) and its application in medicine are developing rapidly, its integration into mental health care is nascent. The prevalence of negative psychological states create a need to further investigate the potential effectiveness of AI and its application methods. The aim of the study is to evaluate psychology students’ attitudes and the significance of brief interventions towards AI systems and their application in mental healthcare. Methods. The study included 53 psychology students – the first group (n = 27) utilized Wysa, a mobile app offering emotional support through AI-driven chat conversations; second group (n = 26) watched a recorded presentation on AI in psychology. Attitudes towards AI were evaluated pre- and post-interventions in both groups using The General Attitudes towards Artificial Intelligence Scale and Oh et al. (2019) questionnaire. During interventions, facial expression analysis software “FaceReader” was used to assess participants’ emotions. Results. Significant differences in emotions emerged between intervention groups, with the Wysa group exhibiting higher levels of “angry”, “contempt”, “disgusted” and “happy” (Mann-Whitney p = 0.04; 0.01; < 0.001; < 0.001, correspondingly) while the presentation group demonstrated a higher prevalence of the “neutral” state (Mann-Whitney p < 0.001). Comparing attitudes before and after interventions revealed a statistically significant change in both “Perception of AI in psychology” and “Advantages of using AI in psychology” dependent on the group (Repeated measures ANOVA p < 0.001; 0.012). Among the students observing the presentation, attitude scores post-intervention were significantly higher (p < 0.001; 0.015). Participants of the Wysa group did not show significant changes in the attitudes on AI technologies. This outcome could potentially be attributed to the greater confidence in science-based data about AI than in testing practical methods. Conclusions. The presentation intervention elicited significant positive changes in attitudes towards AI in psychology, whereas the Wysa intervention did not yield significant alterations in attitudes among participants.

Background and aim. While artificial intelligence (AI) and its application in medicine are developing rapidly (Liu et al., 2018), its integration into mental health care is nascent (Fiske et al., 2017). The aim of this study is to evaluate the attitudes of future psychologists towards AI systems and their application in mental health care. Methods. The study included 34 psychology students (mean=23,1 ± 5; 86% females) with 18 assigned to the Wysa group and 17 to the second group. The first group used Wysa, a mobile app offering emotional support through AI-driven chat conversations. The second group watched a recorded presentation on AI in mental health. Attitudes towards AI were evaluated pre- and post- interventions in both groups using The General Attitudes towards Artificial Intelligence Scale and Oh et al. (2019) questionnaire. During interventions, automated facial expression analysis software “FaceReader” was used to assess participants’ emotions. Results. Significant differences in emotional states emerged between the groups, with the Wysa group showing significantly higher levels of the emotions “angry”, “contempt”, “disgusted”, “happy” and “scared” (Mann-Whitney test p=0.02; 0.03; <0.001; <0.001; 0.09, correspondingly) while the presentation group demonstrated a significantly higher prevalence of the “neutral” state (Mann-Whitney test p<0.00). Moreover, we investigated the differences in the attitudes between the presentation and Wysa groups. Before the intervention, the scores of “Perception of AI technologies in psychology” did not differ significantly (MannWhitney test p=0.252). Post-intervention, participants of the presentation group showed a higher positive attitude compared to the Wysa group (Mann-Whitney test p=0.010). Next, we analyzed the changes in the attitudes within the two groups. After the intervention, participants in the presentation group reported higher scores on the “Perception of AI technologies in psychology”, “Advantages of using AI in psychology” and “Positive attitudes towards AI” (Wilcoxon signed rank test p=0.001; 0.013; 0.017, correspondingly). Participants of the Wysa group did not show significant changes in the attitudes on AI technologies. Conclusion. The presentation intervention elicited significant positive changes in attitudes towards AI in psychology, whereas the Wysa intervention did not yield statistically significant alterations in attitudes among participants.

Introduction: Chronic pain is one of the most prevalent and disabling chronic health conditions affecting people. Based on biopsychosocial model, chronic pain has significant biological, psychological, and social causes and consequences, such as loss of productivity, depressive symptoms, cognitive impairments and social interaction disturbances [1]. The highly increasing evidence shows that this may be due to structural, functional and neurochemical changes. Especially functional connectivity reorganisation in several brain regions and increased activation in certain brain regions such as insula, anterior cingulate cortex (ACC), thalamus, amygdala, prefrontal cortex (PFC) which overlaps with emotion regulation pathways [2]. Aim: Recently, researchers started exploring the association between chronic pain and emotional awareness through alexithymia, which refers to an ineffective identification and expression of one's emotions [3]. Yet very little studies analyse pain impact on Theory of Mind (ToM), or mentalizing – the ability to infer on mental states, such as intentions, beliefs, or emotions in others [4]. Analyzing relationship between pain and mentalising abilities could help to understand pain impact to cognitive-emotional functioning and explain the difficulties in social interactions. The aim of our study was to explore the link between pain characteristics, mentalising and emotional awareness in persons with chronic pain. [...].

Įvadas. Placebo efektas – plačiai žinomas mokslinis fenomenas, atskleidžiantis sudėtingą žmogaus mąstymo ir organizmo reakcijų sąveiką. Klasikiniais placebo efektą lemiančiais veiksniais yra laikomi sąlygojimas ir įsitikinimas, tačiau vieningos nuomonės dėl šių veiksnių vaidmens iniciuojant placebo poveikį nėra. Tikslas. Išsiaiškinti sąlygojimo ir įsitikinimo svarbą placebo veikimo mechanizmuose, analizuojant kofeino ir placebo poveikį dėmesio funkcijoms. Metodai. Šiame eksperimente dalyvavo 88 savanoriai tiriamieji. Eksperimento metu tiriamieji buvo suskirstyti į 4 tiriamąsias grupes: kavos-kofeino (6,6 g kavos/100 ml vandens), kavos-placebo (6,6 g dekofeinizuotos kavos/100 ml vandens), sulčių-kofeino (100 mg kofeino/100 ml sulčių), sulčių-placebo (100 ml sulčių). Siekiant sustiprinti tiriamųjų įsitikinimą, tiriamiesiems buvo teigiama, kad visi gėrimai pasižymi stipriu kofeino poveikiu, taip pat eksperimento metu buvo skaitoma paskaita apie kofeino poveikį kognityvinėms funkcijoms. Dėmesio funkcijoms įvertinti buvo naudojami kompiuterinės Stroop užduoties rezultatai. Rezultatai. Tyrimo rezultatai parodė reikšmingą tiriamųjų reakcijos laiko ir klaidų skaičiaus pagerėjimą kavos-kofeino, kavos-placebo ir sulčių-kofeino grupėse. Sulčių-placebo grupėje pokyčiai buvo statistiškai nereikšmingi (p>0,05). Reakcijos laiko pagerėjimas, stebimas kavos-placebo ir kavos-kofeino grupėse statistiškai reikšmingai nesiskyrė (atitinkamai 11,78 proc. ir 14,82 proc.), todėl galima teigti, jog dekofeinizuotos kavos ir kofeino poveikis tiriamųjų dėmesio funkcijoms buvo panašus. Išvados. Sąlygojimas ir įsitikinimas yra būtinos sąlygos pasireikšti placebo efektui. Placebo poveikis, veikiant tik įsitikinimui, net esant verbaliniam sustiprinimui ir socialiniam modeliavimui, yra nereikšmingas.

PURPOSE: Hip dislocation after arthroplasty for femoral neck fractures (FNF) remains a serious complication. The aim of our study was to investigate FNF patients treated with THA, with a special focus of comparing the effect of surgical approach and femoral head size on the risk of revision for dislocation. METHODS: Data were derived from the Lithuanian Arthroplasty Register, and we calculated the cumulative revision rates after surgery. For survival analysis, we used revision due to dislocation as an end-point. Cox proportional hazards models were used to analyse the influence of various covariates (age, gender, femoral head size, surgical approach). RESULTS: A total of 8,813 primary THAs were registered from 1 January 2011 to 31 December 2013, of which 1,412 were due to FNF: 899 involved 28-mm femoral heads and the remaining 513 received 32-mm heads. The posterior approach was used in 1,156 cases and the anterolateral approach in 256.. At the end of the follow-up period, 74 hips had been revised for recurrent dislocation. Cox regression adjusting for age, gender and head size showed that the posterior approach had 2.3-times [95% confidence interval (CI): 1.0-5.0, p = 0.04] greater risk of revision for dislocation CONCLUSIONS: We conclude that in order to reduce the early dislocation rate in FNF patients treated with THA, it is more effective to use the anterolateral approach than it is to select a femoral head size of 32 mm instead of 28 mm.