A single tDCS session can enhance numerical competence

While numerical skills are increasingly important in modern life, few interventions have been developed to support those with numeracy skills difficulties. Previous studies have demonstrated that applying transcranial Direct Current Stimulation (tDCS) can improve numerical skills. However, tDCS interventions designed to induce lasting changes typically involve reapplying brain-stimulation over several days. Repeated tDCS application can increase the risks associated with the procedure, as well as restricts the transferability of the method to a wider population, particularly those who may experience mobility issues, such as stroke survivors with acalculia. The current study investigated whether a single session of tDCS (anodal to right parietal lobe and cathodal to left parietal lobe), followed by four self-practice sessions without tDCS, could result in enhancement of numerical skills. Nineteen healthy adults (n = 10 tDCS, n = 9 sham control) implicitly learnt the magnitude association of nine arbitrary symbols, previously used by Cohen Kadosh et al. (2010). Numerical proficiency was assessed using number-to-space task, while automaticity was assessed with numerical Stroop. Results revealed that single-session tDCS had a significant effect on participants' accuracy on the number-to-space tasks, but not on the numerical Stroop task's congruity effect, implying automaticity may require longer practice. We conclude that a single session of tDCS should be considered as an avenue for interventions

Towards a smart smoking cessation app: a 1D-CNN model predicting smoking events

Nicotine consumption is considered a major health problem, where many of those who wish to quit smoking relapse. The problem is that overtime smoking as behaviour is changing into a habit, in which it is connected to internal (e.g., nicotine level, craving) and external (action, time, location) triggers. Smoking cessation apps have proved their efficiency to support smoking who wish to quit smoking. However, still, these applications suffer from several drawbacks, where they are highly relying on the user to initiate the intervention by submitting the factor the causes the urge to smoke. This research describes the creation of a combined Control Theory and deep learning model that can learn the smoker’s daily routine and predict smoking events. The model’s structure combines a Control Theory model of smoking with a 1D-CNN classifier to adapt to individual differences between smokers and predict smoking events based on motion and geolocation values collected using a mobile device. Data were collected from 5 participants in the UK, and analysed and tested on 3 different machine learning model (SVM, Decision tree, and 1D-CNN), 1D-CNN has proved it’s efficiency over the three methods with average overall accuracy 86.6%. The average MSE of forecasting the nicotine level was (0.04) in the weekdays, and (0.03) in the weekends. The model has proved its ability to predict the smoking event accurately when the participant is well engaged with the app

Decision Tree Model of Smoking Behaviour

Smoking is considered the cause of many health problems. While most smokers wish to quit smoking, many relapse. In order to support an efficient and timely delivery of intervention for those wishing to quit smoking, it is important to be able to model the smoker’s behaviour. This research describes the creation of a combined Control Theory and Decision Tree Model that can learn the smoker’s daily routine and predict smoking events. The model structure combines a Control Theory model of smoking with a Bagged Decision Tree classifier to adapt to individual differences between smokers, and predict smoking actions based on internal stressors (nicotine level, with- drawal, and time since the last dose) and external stressors (e.g. location, environment, etc.). The designed model has 91.075% overall accuracy of classification rate and the error rate of forecasting the nicotine effect using the designed model is also low (MSE=0.048771, RMSE=0.216324, and NRMSE=0.153946) for regular days and (MSE=0.048804, RMSE=0.216637, and NRMSE=0.195929)

Are Machine Learning Methods the Future for Smoking Cessation Apps?

Smoking cessation apps provide efficient, low-cost and accessible support to smokers who are trying to quit smoking. This article focuses on how up-to-date machine learning algorithms, combined with the improvement of mobile phone technology, can enhance our understanding of smoking behaviour and support the development of advanced smoking cessation apps. In particular, we focus on the pros and cons of existing approaches that have been used in the design of smoking cessation apps to date, highlighting the need to improve the performance of these apps by minimizing reliance on self-reporting of environmental conditions (e.g., location), craving status and/or smoking events as a method of data collection. Lastly, we propose that making use of more advanced machine learning methods while enabling the processing of information about the user’s circumstances in real time is likely to result in dramatic improvement in our understanding of smoking behaviour, while also increasing the effectiveness and ease-of-use of smoking cessation apps, by enabling the provision of timely, targeted and personalised intervention

The language network is not engaged in object categorization

The relationship between language and thought is the subject of long-standing debate. One claim states that language facilitates categorization of objects based on a certain feature (e.g. color) through the use of category labels that reduce interference from other, irrelevant features. Therefore, language impairment is expected to affect categorization of items grouped by a single feature (low-dimensional categories, e.g. "Yellow Things") more than categorization of items that share many features (high-dimensional categories, e.g. "Animals"). To test this account, we conducted two behavioral studies with individuals with aphasia and an fMRI experiment with healthy adults. The aphasia studies showed that selective low-dimensional categorization impairment was present in some, but not all, individuals with severe anomia and was not characteristic of aphasia in general. fMRI results revealed little activity in language-responsive brain regions during both low- and high-dimensional categorization; instead, categorization recruited the domain-general multiple-demand network (involved in wide-ranging cognitive tasks). Combined, results demonstrate that the language system is not implicated in object categorization. Instead, selective low-dimensional categorization impairment might be caused by damage to brain regions responsible for cognitive control. Our work adds to the growing evidence of the dissociation between the language system and many cognitive tasks in adults

"I feel dumb, embarrassed, and frustrated”: A qualitative exploration of the lived experience of acalculia.

Introduction: Acalculia is an acquired disability following stroke or brain injury, which involves difficulty processing numerical information (e.g. phone numbers, measurements) or problems with calculations and understanding quantities. Acalculia is not routinely screened for as part of standard post-stroke assessment. As a result, there is a lack of understanding of the nature and prevalence of poststroke acalculia, and the impact it has on stroke survivors. This qualitative study aimed to explore stroke survivors’ experiences of acalculia. Stroke survivors with a strong interest in acalculia and its rehabilitation initiated the study and contributed to its design. Methods: We explored the impact of acalculia on the lives of 16 stroke/brain injury survivors with acalculia and 7 carers using semi-structured online interviews. Participants ranged in age, gender, time post onset, lesion localisation, country of residence and numeracy level prior to brain injury. Data were analysed using thematic analysis. Results: Three main themes were identified: Awareness and Diagnosis, Emotional and Physical Impact, and Coping Strategies and Independence. Participants and carers repeatedly referred to the lack of awareness and treatment for acalculia and the devastating impact acalculia has had on their lives and independence. Practical impacts included managing money, making appointments, using timetables, organising social activities and employment, and managing medication. Conclusions: Our results highlight the urgent need to develop suitable assessments and interventions for acalculia and the scope for this to be PCPI-led. The data also reveal useful strategies and suggestions regarding effective timing and approaches for intervention

A qualitative exploration of the lived experience of, and quality of professional support for, number processing deficits after brain injury or stroke

Introduction: Acalculia is an acquired disability following brain-injury (hence forth, including stroke) (Ardila & Rosselli, 2002), which involves difficulty processing numerical information (e.g. ‘phone numbers) or problems with calculations and understanding quantities (money, time). While difficulties may result from damage to quantity-processing units in the parietal region, or executive frontal regions, common difficulties are closely related to aphasic symptoms - for example, difficulties articulating numbers, understanding spoken number words, or reading digits or number words. Acalculia is not routinely screened for as part of standard brain-injury assessment, but studies suggest a prevalence of between 35%-60%. Aims: To understand the impact of acalculia on adults with acquired brain-injury, and to explore professional support available for patients with acalculia. Methods: We explored the impact of acalculia on the lives of 16 brain-injury survivors (7 males) with acalculia and 7 carers (4 males), using semi-structured online interviews (mean length of interview = 56min). Interviews investigated participants’ experiences of living with acalculia and the type and quality of professional support they received post brain-injury. Fifteen participants with acalculia also reported aphasic symptoms. Participants ranged in age (mean = 58 years, SD=12.95), time post onset (mean =7.39 years; SD=6.52), lesion localisation, country of residence, severity of aphasic symptoms, and numeracy level prior to brain injury. Data were analysed using thematic analysis. Results: Three main themes were identified: Awareness and Diagnosis, Emotional and Physical Impact, and Coping Strategies and Independence. Participants emphasised that concerns about language and mobility took precedence in the period immediately post brain-injury, and they only became aware of their specific difficulties with numbers later in their recovery. Both participants and carers repeatedly referred to the lack of awareness of, and treatment for, acalculia by all professionals they came across. This contrasted markedly to identification and support given for equally prevalent conditions such as aphasia. Many mentioned the devastating impact acalculia has had on their lives and independence. Practical impacts included managing money or medication, making appointments, using timetables, organising social activities and employment. Conclusions: Our results highlight the urgent need to increase awareness of acalculia amongst patients and professionals involved in post brain-injury care. There is a substantial and presently unmet clinical need to support professionals and patients by developing suitable assessments and interventions for acalculia. Contribution to new knowledge: While a lot is known about numerical cognition, this study highlights the gap between advances in theory and the lack of translational research that positively impact patient care. Implications for practice and/or policy service-user engagement and/or involvement in the study: This study was initiated by stroke survivors with a strong interest in acalculia and its rehabilitation, and the findings are testimony to the contribution of PCPI-led research. Going forward, findings will be used to identify and develop screening tests and interventions, and to increase awareness of acalculia among brain-injury survivors, their carers and professionals

The language network is not engaged in object categorization

The relationship between language and thought is the subject of long-standing debate. One claim states that language facilitates categorization of objects based on a certain feature (e.g. color) through the use of category labels that reduce interference from other, irrelevant features. Therefore, language impairment is expected to affect categorization of items grouped by a single feature (low-dimensional categories, e.g. “Yellow Things”) more than categorization of items that share many features (high-dimensional categories, e.g. “Animals”). To test this account, we conducted two behavioral studies with individuals with aphasia and an fMRI experiment with healthy adults. The aphasia studies showed that selective low-dimensional categorization impairment was present in some, but not all, individuals with severe anomia and was not characteristic of aphasia in general. fMRI results revealed little activity in language-responsive brain regions during both low- and high-dimensional categorization; instead, categorization recruited the domain-general multiple-demand network (involved in wide-ranging cognitive tasks). Combined, results demonstrate that the language system is not implicated in object categorization. Instead, selective low-dimensional categorization impairment might be caused by damage to brain regions responsible for cognitive control. Our work adds to the growing evidence of the dissociation between the language system and many cognitive tasks in adults

'It's bit of an eye opener' - A qualitative study of women's attitudes towards tanning, sun protection and a facial morphing intervention.

OBJECTIVE: Skin cancer is to a large degree behaviourally preventable, meaning that evidence-based interventions have scope to make a difference. Previous research indicates that appearance-based interventions such as facial morphing may be more effective than health-based interventions, and that it can personalise the issue of skin cancer. METHOD: This study examined attitudes to UV exposure, as well as reactions to a facial morphing intervention, through interviews with 25 women aged 35 years and older. RESULTS: Thematic analysis revealed four themes; two regarding attitudes to UV exposure (confusion and contradiction, and change and continuity), and two relating to the facial morphing intervention (negative reactions to UV-exposed photo and positive outcomes of the intervention). Women experienced a number of barriers to adopting safer behaviour in the sun; their current attitudes to UV exposure had been shaped by available information sources throughout their ageing. They expressed negative evaluations of the UV photo, which fed directly into motivation to reduce UV exposure. CONCLUSIONS: These results can be interpreted along the lines of goal-directed behaviour. This type of intervention has the potential to reduce UV exposure among this participant group, something that needs to be further investigated with randomised control trials

What information do consumers consider, and how do they look for it, when shopping for groceries online?

Previous research investigating what information shoppers seek when purchasing groceries has used either lab-experiments or observed shoppers in supermarkets. The present research investigates this question in a relatively naturalistic online-grocery environment. Forty participants completed their weekly shopping online while their eye-movements were recorded. Ten of the participants were subsequently interviewed to gain insight into their information seeking behaviour. We found that, when looking for products, 95% of participants navigated through the 'virtual departments', 80% used the 'search' facility, and 68% browsed the special offer pages. Once on the product pages, participants tended to look at the pictures of products, rather than examine detailed product information. To explain these findings, we suggest that online grocery sites simulate familiar supermarket environments, which may explain why consumers prefer to browse categories of products rather than use search terms. We also suggest that additional strategies are needed if consumers are to be encouraged to view detailed product information