Why A Change In Financial Behaviour Does Not Always Trigger A Change In Financial Well-Being?

“Finance, money and debt” are the most common causes of anxiety affecting mental health and well-being (Swift et al., 2014). Previous research has sought to understand financial well-being and the important factors for promoting financial well-being (FWB) for both individuals and society. The research seeks to explain why financial behaviour change matters. Financial education is considered as an important intervention to improve FWB (Brüggen et al., 2017). Nevertheless, the level of impact of financial education on financial behaviour change, capability and well-being are disputed. Behaviour change is not only influenced by education; other factors play an important role. There are constraints preventing people from changing behaviour, such as socioeconomic status, personality, financial knowledge, literacy, psychological and demographic characteristics (Hensley, 2015; Collins and Holden, 2014; Lyons et al., 2006; Bird et al., 1997). This paper investigates how behaviours influence individual FWB and how financial education can play a role in enhancing these elements. Saving and borrowing are key behaviours discussed in this paper. Some factors that might constrain people from making a change, such as financial attitudes and resources are also explored. Using data from my PhD, the efficacy of the online financial education intervention “Managing My Money” on Future Learn will be explored. The research uses a mix of quantitative and qualitative methods including surveys, financial literacy quizzes, interviews and content from online discussions. Key findings show that there is no significant change in perceived FWB before and after the intervention. From the data, it is not clear why there were some changes in influential factors such as financial behaviour, attitudes, attitudes towards making a change, knowledge and capacity, but no significant change in FWB. It might be that the level of change of these influential factors was not large enough to trigger a change in FWB. It could also be that the changes in some indicators of these influential factors are not sufficient to create a significant change in FWB. For instance, there was a positive change in saving behaviour within the financial behaviour factor, however, a positive change simultaneously in other indicators (i.e. paying off debts, retirement funds) might be needed to generate a positive change in FWB. Low response rates in post-surveys make it difficult to justify the causes of this result. The findings from the thematic analysis of the qualitative data revealed that saving and borrowing were the favourite topics in the online discussions. Learners were contemplating how their cognition, attitudes and behaviours in managing their finances had been changed over time. They asked for advice and stressed that they needed some help in managing their finances. Financial education was recognised by learners as key in achieving their financial needs and goals. The stories of their life-changing situations explained how these changes influenced their financial behaviours such as spending, saving and borrowing money. This research found that learners were at different stages of behaviour change for individual financial behaviours. Due to various circumstances, a few learners had relapsed in their saving behaviour, but over a twelve-month period were back on track. It was the limited financial resources in a specific period that prevented them from maintaining a desirable behaviour such as saving, rather than a lack of self-efficacy to maintain the change, awareness of the desirability of change or a lack of knowledge of saving for instance. These learners stressed they knew that they needed to save and to pay off debt. However, when the relapse was caused by limited financial resources, it might take longer than the one to six months cut-off periods, as suggested in five stages of behaviour change (Prochaska et al., 2002) to observe the change in behaviour after a relapse. Financial behaviour is constrained by an individual’s financial capacity, so the approach to dealing with behaviour change is distinguished from other types of behaviour change that involve purely physical and psychological factors (e.g. exercise, diet, smoking etc.). It requires a different approach and more thought to define the stages of financial behaviour change. Learners also discussed how risk attitude influenced the way they spend, save, borrow and invest their money. Risk attitude is defined as “an individual’s orientation toward taking or avoiding risk when deciding how to proceed in situations with uncertain outcomes” (Glanz et al., 2016, p.1). Financial capacity constrained the levels of risk attitude of learners. The more risk-averse attitude the learners had the more resilience they developed to resist pressure to “keep up with the Joneses”. There is not one answer that fits all, as it depends on an individual’s financial situation. Informed decision making is more important to help them make the right decision at the right time with reasonable costs or risks. This paper offers some preliminary findings on the above to inform the social marketers in designing financial education interventions that work for different segments

What can we learn about immediate memory from the development of children's free recall?

We ask the question: Which aspects of immediate memory performance improve with age? In two studies, we reexamine the widely held view that primary memory capacity estimates derived from children's immediate free recall are age invariant. This was done by assessing children's immediate free-recall accuracy while also measuring the order in which they elected to recall items (Experiment 1) and by encouraging children to begin free recall with items from towards the end of the presented list (Experiment 2). Across samples aged between 5 and 8 years we replicated the previously reported age-related changes in free-recall serial position functions when aggregated across all trials of the standard task, including an absence of age differences in the recency portion of this curve. However, we also show that this does not reflect the fact that primary memory capacity is constant across age. Instead, when we incorporate order of report information, clear age differences are evident in the recall of list-final items that are output at the start of a participant's response. In addition, the total amount that individuals recalled varied little across different types of free-recall tasks. These findings have clear implications for the use of immediate free recall as a means of providing potential indices of primary memory capacity and in the study of the development of immediate memory

Autophagy-Modulating Long Non-coding RNAs (LncRNAs) and Their Molecular Events in Cancer

Cancer is a global threat of health. Cancer incidence and death is also increasing continuously because of poor understanding of diseases. Although, traditional treatments (surgery, radiotherapy, and chemotherapy) are effective against primary tumors, death rate is increasing because of metastasis development where traditional treatments have failed. Autophagy is a conserved regulatory process of eliminating proteins and damaged organelles. Numerous research revealed that autophagy has dual sword mechanisms including cancer progressions and suppressions. In most of the cases, it maintains homeostasis of cancer microenvironment by providing nutritional supplement under starvation and hypoxic conditions. Over the past few decades, stunning research evidence disclosed significant roles of long non-coding RNAs (lncRNAs) in the regulation of autophagy. LncRNAs are RNA containing more than 200 nucleotides, which have no protein-coding ability but they are found to be expressed in most of the cancers. It is also proved that, autophagy-modulating lncRNAs have significant impacts on pro-survival or pro-death roles in cancers. In this review, we highlighted the recently identified autophagy-modulating lncRNAs, their signaling transduction in cancer and mechanism in cancer. This review will explore newly emerging knowledge of cancer genetics and it may provide novel targets for cancer therapy

Spotlight influenza: Laboratory-confirmed seasonal influenza in people with acute respiratory illness: a literature review and meta-analysis, WHO European Region, 2004 to 2017

Background: Across the WHO European Region, there are few estimates of the proportion of people seeking medical care for influenza-like illness or acute respiratory infections and who have confirmed seasonal influenza infection when tested for respiratory viruses.Methods: We conducted meta-analyses of data extracted from a) literature review of studies published between 2004 and 2017; b) sentinel data from the European surveillance system (TESSy), pooling within-season estimates by influenza type/subtype, setting (outpatient/inpatient) and age-group, to estimate the proportion of people tested who have laboratory-confirmed medically-attended seasonal influenza in Europe.Results: In the literature review, the pooled proportion for all influenza was 33% (95% CI, 30%-36%), and higher among outpatients (36% [33-40%]) than inpatients (24% [20-29%]). Pooled estimates for all influenza by age group were: 0-17 years, 26% (22-31); 18-64 years, 41% (32-50); ≥65 years, 33% (27-40%). From TESSY data, 33% (31-24%) of outpatients and 24% (21-27%) of inpatients were positive. The highest proportion of influenza A overall was in people aged 18-64 years (22% [16-29%]). By subtype, influenza A(H1N1)pdm09 was highest in 18-64 year-olds (16% [11-21%]) whereas influenza A(H3N2) was highest in those ≥65 years (10% [2-22%]). For influenza B, the highest proportion of infections was those aged 18-64 years (15% [9-24%]). Estimated proportions of confirmed influenza varied across seasons and across countries. Conclusions: Both the literature review and TESSy analyses showed a higher proportion of laboratory-confirmed influenza in non-hospitalised patients, with further variation by influenza type, age-group, country and season

A Comparison of Benefit Limits in Mental Health

This study provides insight to policy makers and stakeholders on how three types of benefits limits on Medicaid-covered mental health services might affect access for consumers diagnosed with severe mental illness. The study used a retrospective cohort design with data for Medicaid-covered, community-based mental health services provided in Ohio during fiscal year 2010. Log-binomial regression was used for the analysis. Results indicate that limits compared have significant, varying consequences based on Medicaid coverage and diagnoses. When constraining Medicaid costs, policy makers should consider how limits will disrupt care and include clinicians in discussions prior to implementatio

Nurses’ Contacts and Potential for Infectious Disease Transmission

These data can help predict staff availability and provide information for pandemic preparedness planning

Validation of a sports nutrition knowledge questionnaire for athletes in the United Kingdom and Ireland.

Sound general and sports nutrition knowledge in athletes is essential for making appropriate dietary choices. Assessment of nutrition knowledge enables evaluation and tailoring of nutrition education. However, few well-validated tools are available to assess nutrition knowledge in athletes. The objective of the present study was to establish the validity of the Platform to Evaluate Athlete Knowledge Sports - Nutrition Questionnaire (PEAKS-NQ) for use in the United Kingdom and Irish (UK-I) athletes. To confirm content validity, twenty-three sports nutritionists (SNs) from elite, UK-I sports institutes provided feedback on the PEAKS-NQ via a modified Delphi method. After minor changes, the UK-I version of the PEAKS-NQ was administered to UK-I SN from the British Dietetic Association Sport and Exercise Nutrition Register, and elite athletes (EA) training at elite sports institutes in the UK and Ireland. Independent samples -test and independent samples median tests were used to compare PEAKS-NQ total and subsection scores between EA and SN (to assess construct validity). Cronbach's alpha (good ≥ 0⋅7) was used to establish internal consistency. The SN achieved greater overall [SN ( 23) 92⋅3 (9⋅3) EA ( 154): 71⋅4 (10⋅0)%; < 0⋅001] and individual section scores ( < 0⋅001) except Section B, Identification of Food Groups ( = 0⋅07). Largest knowledge differences between SN and EA were in Section D, Applied Sports Nutrition [SN: 88⋅5 (8⋅9) EA: 56⋅7 (14⋅5)%; < 0⋅00]. Overall ES was large (2⋅1), with subsections ranging from 0⋅6 to 2⋅3. Cronbach's alpha was good (0⋅83). The PEAKS-NQ had good content and construct validity, supporting its use to assess nutrition knowledge of UK-I athletes