Search

Overview and aims The Holly Health app and infrastructure helps individuals to prioritise, achieve and sustain small but influential daily health habits across exercise, sleep, mental health, and relationship with food, all from a psychological medicine perspective. The app and its recommendations (including habits, articles, challenges, reflective exercises) are personalised to each person, and adapt throughout the time they use the service. The aims of the study are to (1) evaluate the efficacy of the app on improving people’s attitude towards their health and food choices (measured via the health survey and food choice questionnaire), (2) test if outcomes differ between people who use the app ‘regularly’ vs. ‘occasionally’, (3) assess if people’s attitudes towards their health and food choices predicts life satisfaction (measured via the ONS-4), and (4) assess the acceptability of the Holly Health app (measured via retrospective questions). Materials The items are collected as follows: Health survey (administered at baseline, week 8 and week 12): 1. Physical activity How many hours a week do you do any type of moderate physical activity? (e.g., walking, swimming, running, cycling, yoga, etc) • I don't do any exercise • Less than 1 h/week • 1-2 h/week • 2-3 h/week • 3+ h/week 2. ONS-4: Scale from 0-10 (Personal wellbeing) Overall, how satisfied are you with your life nowadays? • 0=Not at all • 10= Completely Overall, to what extent do you feel that the things you do in your life are worthwhile? • 0=Not at all • 10= Completely Overall, how happy did you feel yesterday? • 0=Not at all • 10= Completely On a scale where 0 is “not at all anxious” and 10 is “completely anxious”, overall, how anxious did you feel yesterday? 3. Self-confidence How would you rate your self-confidence? • Very poor • Poor • Average • Good • Excellent 4. Relationship with food: Which of these statements best describes how you relate to food? • I tend to feel guilty when I eat certain foods, I try to restrict what I eat, and sometimes I end up overeating based on strong emotions • I see some foods as 'good' or 'bad' and I tend to base my eating choices on different diet programmes • I try to eat based on what I think is 'healthy' but it's not always possible • I often eat what I fancy but sometimes I feel guilty if I eat more than usual • Most of the time I base my eating choices on what I fancy and what makes me feel good 5. Energy levels: How would you rate your average energy levels on any given day? • I'm exhausted most of the time • I'm pretty tired most days • It varies quite a lot • I often feel I have enough energy throughout the day • My energy levels are great most of the time 6. Mindfulness: *(Item 7 of MAAS scale, validated questionnaire) How much do you relate to the following statement: “It seems I am “running on automatic,” without much awareness of what I’m doing” • Almost always • Very frequently • Sometimes • Very rarely • Almost never 7. Short vs long-term mindset: How much do you identify with the following statement when setting health and wellbeing goals: 'I tend to set short-term goals with big gains in mind. I usually lose motivation if I don't see results quickly' • A lot. That's me pretty much every time I set new health and wellbeing goals • Very much. Though sometimes I can keep going even if the results don't come as fast • Somewhat. My motivation varies based on why I started the goal in the first place • Not that much. Often I set health and wellbeing goals thinking of long-term outcomes • Not at all. Most of the time when I set health and wellbeing goals, I focus on the small steps to get there and my motivation doesn't usually depend on the outcome 8. Health mindset: When thinking about your health, which statement applies the most to you: • "I don't think about my health at all" • "I sometimes think about my health but I don't do anything to improve it" • "I think about my health and I do a few things on and off to improve it" • "I often think about my health and I do what I can to improve it" • "Everyday I think about my health and I take actions to improve it" 9. Self-kindness: *(Item 12 of Self-compassion scale, validated questionnaire) Please choose the answer that best describes how you feel: “When I’m going through a very hard time, I give myself the caring and tenderness I need” • Almost always • Very frequently • Sometimes • Very rarely • Almost never Food choice questionnaire (administered at baseline & week 8): Retrospective questions administered at weeks 8 and 12: 1. Using Holly: Have you been using the Holly Health app (at least once a week) in the last (x) weeks? • Yes • No 2. (If yes) Automatic habits: Have you started to do any of your habits automatically? That is, without relying on the app to remind you? • Yes • No 3. Usefulness: Overall, have you found Holly Health useful? • Yes • No 4. Feedback: Do you have any specific feedback you'd like to share about the app? • Free text In future, would you like to see more services like this provided by your local council? • Yes • No Do you have any feedback about taking part in this study so far? • Free text Retrospective questions administered at week 12 only: Acceptability: In general, how appropriate did you find the Holly Health service as a tool for older adults to keep up with their healthy ageing goals? • Not appropriate at all • Not very appropriate • Quite neutral • Very appropriate • Extremely appropriate How likely are you to recommend Holly Health to other people with similar health and wellbeing goals as you? • 1 (Not at all likely) • 2 • 3 • 4 • 5 (Extremely likely) Data analysis period: April 2023 to end of June 2023 or beyond. Analysis plan: For our main analyses, we will take data derived from baseline, 8 weeks, and 12 weeks (see Table below). Primary outcomes will be each subscale of the health survey (physical activity, self-confidence, relationship with food, energy, mindfulness, short- & long-term mindset, health mindset, and self-kindness). Physical activity, self-confidence, energy, mindfulness, health mindset, and self-kindness are coded as continuous data, and responses will be coded on a Likert scale rated from 0-5. Relationship with food & short- & long-term mindset are coded as categorical data, and responses will be coded on a Likert scales rated from 0-5 to indicate how likely an individual would endorse each statement after 8 weeks of using the app. Secondary outcomes will comprise of the ONS-4, food choice questionnaire, and retrospective questions. Wherever possible, bootstrapping approaches will be used to account for possible skews in data and outliers (see Efron, 1979; Sainani, 2012 for a full rationale of this approach). We will conduct the following planned analyses; 1. Zero order correlations will be undertaken to illustrate the relationships between all measures at each time point (baseline, week 8, week 12), and descriptive statistics will be provided. 2. To assess changes in scores on the health survey and food choice questionnaire compared to baseline, repeated measure t-tests will be carried out for all continuous data, and Chi-Square Goodness of Fit Tests will be carried out for all categorical data. We make no directional predictions around these analyses. 3. To assess the impact of ‘regular’ vs. ‘occasional’ use of the Holly Health app, t-tests will be carried out to assess differences in change scores on all measures between participants who answered ‘yes’ to using the app at least once a week vs those who don’t. A change score will be calculated by subtracting scores on each measure collected at baseline from those collected at 8 and 12 weeks. We make no directional predictions around these analyses. 4. To identify predictors of satisfaction (ONS-4), logistical regressions on the ONS-4 will be conducted at 8 and 12 weeks, predicted by scores on the health survey and food choice questionnaire (collected at baseline). We make no directional predictions around these analyses. 5. Descriptive statistics will be provided for responses to the retrospective questions Status at time of registration: • Ethics for secondary data analysis has been granted by LSBU University Ethics Panel (reference ETH2223-0097). • Anonymised data to be used in the proposed analysis has been transferred to the research team. No analysis has been conducted at the time of registration.

Analysis Plan Data sampling period: We anticipate sampling data from the period October 2022 to end of January 2023 or beyond. An opportunity sample approach will be undertaken. Main analysis For our main analyses, we will take draw down data generated at Week 1 (pre-intervention), Week 6 (post-intervention), Week 10 (follow up 1), and Week 12 (follow up 2), Specifically, the primary outcomes which will be analysed are the GAD-7, DASS-21, and the Autonomic Questionnaire. Zero order correlations will be undertaken to illustrate the relationships between these variables and descriptive statistics provided. Within-group effect sizes will be calculated to assess change over time. Additionally, between-group differences will be calculated to investigate the effect of the intervention. Effect sizes will be interpreted using the following criteria: 0.20, small effect; 0.50, medium effect; and 0.80, large effect (Cohen, 1988). It is hypothesised that there will be improvements on the GAD-7, DASS-21, and the Autonomic Questionnaire following the completion of the intervention.

This is a feasibility study to access the acceptability of a novel, online CBM-I platform tailored for people with Multiple Sclerosis.

Club Soda is a mindful drinking movement and social impact business that supports individuals to change their drinking habits through moderation or becoming alcohol-free. Club Soda offers online courses, including How to Stop Drinking and How to Drink Mindfully, which offer individuals a structured and self-directed approach to change. Each in-depth course comprises 31 online lessons, with introductory and bonus materials, organised into four parts. Course participants track their progress by rating their happiness with the drinking at the end of each lesson. They also review their progress, reset their intentions and measure changes in their wellbeing, confidence and commitment at the end of each part of the course. Participants are encouraged to progress at their own pace. They receive daily motivational email prompts encouraging them to continue. They are also invited to engage in a private messaging group on Telegram, and to attend weekly face-toface discussions on Zoom. As noted above, the course comprises 31 lessons, including an introduction, 22 lesson and 4 interim reviews (after lessons 7, 14, 21 and 28). These can be completed at participants own pace. Participant complete baseline measures in the introduction, happiness with their drinking at each lesson point, and a wider range of measures at each review point (see Table 1 for details). The aim of the study is to evaluate the efficacy of the platform on (i) increases with people’s happiness with their drinking, and their related efficacy and (ii) test if outcomes differ between people who stop drinking completely (abstinence) vs those who aim to reduce their drinking. Materials: The items collected are as follows: Happiness with drinking: A sliding scale from -5 (I feel completely unhappy) to +5 (I feel completely happy), with 0.1. increments for the item " “Overall, how happy are you with your drinking?" . Anchors are not presented in later presentations of the scales (applies to here and below) Drinking in last seven days: "Thinking about the last seven days, did you drink more or less alcohol than you normally would?" Likert type scale with response options, Much more (coded +2) , A bit more (+1), About the same as normal (0), A bit less (-1), Much less (-2), Not at all (-99) Withdrawal risk: Three items, "Do you drink more than half a bottle of spirits, one and a half bottles of wine or six pints of beer every day?", "Do you have a drink soon after you wake up to relieve shakes or sweats?", "Have you had withdrawal symptoms (like sweating, shaking, feeling sick or anxious) in the past when cutting down or stopping drinking?" with a Yes/No option for each. Drinking refusal self-efficacy (adapted): An adapted version of the drink refusal efficacy scale comprising 15 items. Each item is on a sliding scale (-5, anchored at I definitely would not have a drink and +5, anchored at I definitely would have a drink)., 0.1 increments) Move the circle left (I would not) or right (I would), depending on what you would generally do." The items in response to the question "How likely are you to have a drink in these different circumstances?” are [1] When I am out to dinner, [2] When I am watching TV, [3] When I am angry, [4] When someone offers me a drink, [5] When I am having lunch, [6] When I feel frustrated, [7] When I am worried,[8] When I feel upset, [9] When I have finished work, [10] When I feel down, [11] When my partner is drinking, [12] When I am relaxing,[13] When my friends are drinking, [14] When I am by myself, [15] When I am at a pub, bar or club. The scale comprises three subscales, Social efficacy (items [1],[4], [11], [13] and [15]), Emotional efficacy (items [3],[6], [7], [8], [10]) and Opportunistic efficacy), (items [2],[5], [9], [12], [14]). Impacts (sleep, energy, nutrition, etc): "Changing your drinking can have an effect in other parts of your life. Overall, how are things going in these areas? Followed by a sliding scale anchored at -5 (things are going really bad) to +5 (things are going really well) and measured in 0.1 increments. The impacts measures are, Energy, Nutrition, Emotions, Relationships, social life, work, money. Intention: "How do you intend to change your drinking?", single choice response between 3 choices, ‘Be alcohol-free’, ‘Moderate in some way’, ‘Not sure’. Confidence: A single item, "How confident are you about changing your drinking?" measured on a -5 to +5 sliding scale, in 0.1 increments, no anchors. Commitment: "How committed are you to changing your drinking?" measured on a -5 to +5 sliding scale, in 0.1 increments, no anchors. Age: Single item, "What is your year of birth?" converted into years of age at time of questionnaire. Gender: Single response option from the following choices; Female, Male, Nonbinary, I use a different term, Prefer not to say. Analysis plan: Data sampling period: We anticipate sampling data from the period May 2022 to end of March 2022 or beyond. An opportunity sample approach will be undertaken. Main analysis: For our main analyses, we will take draw down data on from the introduction, each interim review and the lesson immediately preceding and following each review (see table). The primary outcome will be happiness with drinking. Secondary outcomes will comprise withdrawal risk, DRSE, intention (abstinence vs. controlled drinking), confidence and commitment. Zero order correlations will be undertaken to illustrate the relationships between these variables and descriptive statistics provided. For each of the above, we will undertake ANOVAs with Lesson/Review point as a within subjects factor, should a main effect be present, we will unpack these with Bonferroni adjusted comparisons, comparing each time point to the previous session measure. Bootstrapping approaches will be used to account for possible skews in data and outliers (see see Efron, 1979; Sainani, 2012 for a full rationale of this approach). We predict increases lesson on lesson / review to review increases for each measure. Attrition analysis: We will undertake an attrition analysis by conducting logistical regressions on attrition at each review point, predicted by intention (abstinence vs reduced drinking, collected at baseline). We will conduct a sensitivity analysis repeating this logistic regression controlling for baseline withdrawal risk, gender and age. We make no directional hypotheses for these analyses. Sensitivity analysis: We will undertake a sensitivity analysis by analysing intention) and baseline withdrawal risk as a moderator variables. This will be achieved using the Haye Process macro. We make no directional predictions around these analyses Power analysis: We anticipate n ~= 700 people starting the course. Pilot data suggests a retention rate of around 33%, leading to an estimated completed cases of n ~231. Power analysis with GPower suggests this will allows for a detection of a within participant effects in the region of f = 0.07 (within participants ANOVA main effect of time, 4 (f = 0.8) or 7 (f = 0.07) timepoints, power of 0.80, alpha = 0.05). ttests (prior Bonferroni correction) will be able to reveal between time differences in the region of dz 0.16 (using the same assumptions) Analysis with the R wp.logistic function suggests the sample will also allow us to detect differences in retention in the region of 5% (assuming 33% vs 38%, where n=712, power 0.8, alpha 0.05). Status at time of registration: • Ethics for secondary data analysis has been granted by LSBU University Ethics Panel (reference ETH2122-0108). References: Efron, B. (1979). Bootstrap methods: Another look at the jackknife. Annals of Statistics, 1, 1–26. https://doi.org/10.1007/978-1-4612-4380-9_41 Sainani, K. L. (2012). Dealing With Non-normal Data. PM&R, 4, 1001–1005. https://doi.org/10.1016/j.pmrj.2012.10.013

People with synaesthesia have been reported to show atypical electrophysiological responses to certain simple sensory stimuli, even if these stimuli are not inducers of synaesthesia. However, it is unclear whether this constitutes a neural marker that is relatively specific to synaesthesia or whether it reflects some other trait that co-occurs with synaesthesia, but is not specific to it. One candidate is atypical sensory sensitivity (e.g., strong aversion to certain lights and sounds, 'sensory overload') which is a feature of both synaesthesia and autism and that varies greatly in the neurotypical population. Using visual evoked-potentials (to stimuli varying in spatial frequency) and auditory-evoked potentials (to stimuli varying in auditory frequency), we found that synaesthetes had a modulated visual evoked-potential around P1/N1 (emanating from fusiform cortex), a greater auditory N1, as well as differences in the time-frequency domain (increased alpha and beta induced power for visual stimuli). This was distinct from that found in non-synaesthetes. By contrast, no significant electrophysiological differences were found that were linked to neurotypical variation in sensory sensitivity.