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Beyond using composite measures to analyze the effect of unmet supportive care needs on caregivers’ anxiety and depressionObjective: Caregiver research has relied on composite measures (e.g., count) of unmet supportive care needs to determine relationships with anxiety and depression. Such composite measures assume that all unmet needs have a similar impact on outcomes. The purpose of this study is to identify individual unmet needs most associated with caregivers’ anxiety and depression. Methods: 219 Caregivers completed the 44-item Supportive Care Needs Survey and the Hospital Anxiety and Depression scale [minimal clinically important difference (MCID)=1.5] at 6-8 months, 1, 2, 3.5, and 5 years following the patients' cancer diagnosis. The list of needs was reduced using Partial Least Square regression and those with a Variance Importance in Projection > 1 were analyzed using Bayesian Model Averaging. Results: Across time, eight items remained in the top 10 based on prevalence and were labelled “core”. Three additional ones were labelled “frequent”, as they remained in the top 10 from 1- year onwards. Bayesian Model Averaging identified a maximum of four significant unmet needs per time point – all leading to a difference greater than the MCID. For depression, none of the core unmet needs were significant, rather significance was noted for frequent needs and needs that were not prevalent. For anxiety, 3/8 core and 3/3 frequent unmet needs were significant. Conclusions: Prevalent Those unmet needs that are most prevalent are not necessarily the most significant ones, and findings provide an evidence-based framework to guide the development of caregiver interventions. A broader contribution is proposing a different approach to identify significant unmet needs.
Recruiting cancer survivors into research studies using online methods: a secondary analysis from an international cancer survivorship cohort study.Recruiting participants into cancer survivorship research remains a significant challenge. Few studies have tested and compared the relative use of non-clinical online recruitment methods, especially in samples of adult cancer survivors. This paper reports on the feasibility of recruiting a representative cohort of cancer survivors using online social media. Two-hundred participants with a cancer diagnosis within the past 12 months were recruited via social media (Facebook, Twitter, Reddit) into a longitudinal questionnaire study. Different methods of online recruitment proved to be more effective than others over time. Paid Facebook boosting, Reddit posts, and Twitter adverts placed by existing cancer charities proved most helpful in reaching our recruitment target (contributing 27%, 22% and 32% respectively). Recruiting online achieved a more demographically and clinically representative sample for our study: our sample was younger, less heteronormative, including those with a range of clinical diagnoses, primary and recurrence illness, and patients who had both completed and were still receiving treatment. This was certainly not a quick method of sample recruitment but that could have been optimised by focussing only on the three most effective methods describe earlier. Whilst we found that online recruitment is significantly lower cost than traditional recruitment methods, and can reduce some biases, there still remains the potential for some biases (e.g. excluding much older participants) and ethical/methodological issues (e.g. excluding those without access to the internet). We outline our recruitment strategy, retention rates, and a cost breakdown in order to guide other researchers considering such methods for future research in cancer survivorship.