ObjectivesTo explore reasons for non-participation in a primary care-based physical activity trial and understand how these may contribute to recruitment of non-representative research samples. We also aimed to elicit non-participants’ own recommendations for enhancing trial uptake in primary care.DesignSemistructured telephone interviews with non-participants to a randomised controlled trial of a very brief intervention for promoting physical activity conducted in primary care (the Very Brief Interventions trial), with thematic analysis of interview transcripts.Setting5 general practice (GP) surgeries in the East of England, UK.ParticipantsInterviews were completed with 10 female and 6 male non-participants of white ethnicity and aged between 40 and 71 years. 13 of the 16 interviewees were either active or moderately active according to the GP Physical Activity Questionnaire (GPPAQ).ResultsInterviewees discussed a range of reasons for non-participation. These included beliefs surrounding the personal relevance of the trial based on preconceptions of intervention content. Many interviewees considered themselves either sufficiently active or too functionally limited to increase activity levels further, so rendering participation pointless in their view. Other identified barriers included a lack of free time, for trial participation and for increasing physical activity, and dissatisfaction with appointment scheduling systems in place at GP surgeries. Interviewees questioned the appropriateness of primary care as a context for delivering interventions to promote physical activity. In general, interviewees were positively disposed towards the idea of trial participation, especially if personal benefits are made salient, but suggested that interventions could be delivered in a different setting such as the internet.ConclusionsTo increase participation in physical activity promotion trials conducted in primary care, the content of invitation materials and procedures for contacting potential participants require reconsideration. Specific recommendations include streamlining intervention materials and enhancing their relevance to the health concerns of invitees.Trial registration numberISRCTN72691150; Pre-results.

SS and LK conceived of the study and developed the research question. LK developed the search strategy with input from SS, AA and MVE. Searches were conducted by LK; screening was conducted by LK, AA, MVE and NC; data was extracted by LK and NC; study quality was appraised by AA, LK and MVE. Data was analysed and interpreted, and the

Smartphones have become popular in assessing eating behaviour in real-life and real-time. This systematic review provides a comprehensive overview of smartphone-based dietary assessment tools, focusing on how dietary data is assessed and its completeness ensured. Seven databases from behavioural, social and computer science were searched in March 2020. All observational, experimental or intervention studies and study protocols using a smartphone-based assessment tool for dietary intake were included if they reported data collected by adults and were published in English. Out of 21,722 records initially screened, 117 publications using 129 tools were included. Five core assessment features were identified: photo-based assessment (48.8% of tools), assessed serving/ portion sizes (48.8%), free-text descriptions of food intake (42.6%), food databases (30.2%), classification systems (27.9%). On average, a tool used two features. The majority of studies did not implement any features to improve completeness of the records. This review provides a comprehensive overview and classification scheme of smartphone-based dietary assessment tools to help researchers identify suitable assessment tools for their studies. Future research needs to address the potential impact of specific dietary assessment methods on data quality and participants’ willingness to record to ultimately improve the quality of smartphone-based dietary assessment for health research.

Background The majority of people do not achieve recommended levels of physical activity. There is a need for effective, scalable interventions to promote activity. Self-monitoring by pedometer is a potentially suitable strategy. We assessed the effectiveness and cost-effectiveness of a very brief (5-minute) pedometer-based intervention ('Step It Up') delivered as part of National Health Service (NHS) Health Checks in primary care. Methods and findings The Very Brief Intervention (VBI) Trial was a two parallel-group, randomised controlled trial (RCT) with 3-month follow-up, conducted in 23 primary care practices in the East of England. Participants were 1,007 healthy adults aged 40 to 74 years eligible for an NHS Health Check. They were randomly allocated (1:1) using a web-based tool between October 1, 2014, and December 31, 2015, to either intervention (505) or control group (502), stratified by primary care practice. Participants were aware of study group allocation. Control participants received the NHS Health Check only. Intervention participants additionally received Step It Up: a 5-minute face-to-face discussion, written materials, pedometer, and step chart.

Smartphones have become popular in assessing eating behaviour in real-life and realtime. This systematic review provides a comprehensive overview of smartphone-based dietary assessment tools, focusing on how dietary data is assessed and its completeness ensured.Seven databases from behavioural, social and computer science were searched in March 2020.All observational, experimental or intervention studies and study protocols using a smartphone-based assessment tool for dietary intake were included if they reported data collected by adults and were published in English. Out of 21,722 records initially screened, 117 publications using 129 tools were included. Five core assessment features were identified: photo-based assessment (48.8% of tools), assessed serving/ portion sizes (48.8%), free-text descriptions of food intake (42.6%), food databases (30.2%), and classification systems (27.9%). On average, a tool used two features. The majority of studies did not implement any features to improve completeness of the records. This review provides a comprehensive overview and framework of smartphone-based dietary assessment tools to help researchers identify suitable assessment tools for their studies. Future research needs to address the potential impact of specific dietary assessment methods on data quality and participants' willingness to record their behaviour to ultimately improve the quality of smartphone-based dietary assessment for health research.

ObjectivesTo explore patients’ and healthcare practitioners’ (HCPs) views about non-adherence to hypertension medication and potential content of a combined very brief face-to-face discussion (VBI) and digital intervention (DI).MethodsA qualitative study (N=31): interviews with patients with hypertension (n=6) and HCPs (n=11) and four focus groups with patients with hypertension (n=14). Participants were recruited through general practices in Eastern England and London. Topic guides explored reasons for medication non-adherence and attitudes towards a potential intervention to support adherence. Stimuli to facilitate discussion included example SMS messages and smartphone app features, including mobile sensing. Analysis was informed methodologically by the constant comparative approach and theoretically by perceptions and practicalities approach.ResultsParticipants’ overarching explanations for non-adherence were non-intentional (forgetting) and intentional (concerns about side effects, reluctance to medicate). These underpinned their views on intervention components: messages that targeted forgetting medication or obtaining prescriptions were considered more useful than messages providing information on consequences of non-adherence. Tailoring the DI to the individuals’ needs, regarding timing and number of messages, was considered important for user engagement. Patients wanted control over the DI and information about data use associated with any location sensing. While the DI was considered limited in its potential to address intentional non-adherence, HCPs saw the potential for a VBI in addressing this gap, if conducted in a non-judgemental manner. Incorporating a VBI into routine primary care was considered feasible, provided it complemented existing GP practice software and HCPs received sufficient training.ConclusionsA combined VBI-DI can potentially address intentional and non-intentional reasons for non-adherence to hypertension medication. For optimal engagement, recommendations from this work include a VBI conducted in a non-judgmental manner and focusing on non-intentional factors, followed by a DI that is easy-to-use, highly tailored and with provision of data privacy details about any sensing technology used.

Self-report measures of health behaviour have several limitations including measurement reactivity, i.e. changes in people’s behaviour, cognitions or emotions due to taking part in research. It is thus often recommended to use objective digital measurements instead; however, it is unclear whether they also induce reactivity. Therefore, this pre-registered systematic review and meta-analysis synthesised 31 studies, including 7 experimental studies with 18 effects. Most studies investigated reactivity to digital measurement of physical activity, reporting small but significant effects. Measurement reactivity may be amplified by (1) ease of changing the behaviour, (2) awareness of being measured and social desirability, and (3) resolving discrepancies between actual and desired behaviour through self-regulation. Measurement reactivity may be reduced by discarding the first days of measurement and by restricting visibility of the data. Studies on reactivity to measurement of other health behaviours were scarce, indicating the need for future rigorous experimental research.

The PAM intervention is a behavioural intervention to support adherence to anti-hypertensive medications and therefore to lower blood pressure. This feasibility trial recruited 101 nonadherent patients (54% male, mean age 65.8 years) with hypertension and high blood pressure from nine general practices in the UK. The trial had 15.5% uptake and 7.9% attrition rate. Patients were randomly allocated to two groups: the intervention group (n = 61) received the PAM intervention as an adjunct to usual care; the control group (n = 40) received usual care only. At 3 months, biochemically validated medication adherence was improved by 20% (95% CI 3–36%) in the intervention than control, and systolic blood pressure was reduced by 9.16 mmHg (95% CI 5.69–12.64) in intervention than control. Improvements in medication adherence and reductions in blood pressure suggested potential intervention effectiveness. For a subsample of patients, improvements in medication adherence and reductions in full lipid profile (cholesterol 1.39 mmol/mol 95% CI 0.64–1.40) and in glycated haemoglobin (3.08 mmol/mol, 95% CI 0.42–5.73) favoured the intervention. A larger trial will obtain rigorous evidence about the potential clinical effectiveness and cost-effectiveness of the intervention.Trial registration Trial date of first registration 28/01/2019. ISRCTN74504989. https://doi.org/10.1186/ISRCTN74504989.