A Randomised Controlled Trial of a Brief Planning Intervention to Promote Physical Activity
A Randomised Controlled Trial of a Brief Planning Intervention to Promote Physical Activity
People of low socioeconomic status are more inclined to incur poor health than those of high socioeconomic status. Different factors have been attributed to contributing to such health inequalities, including differences in modifiable lifestyle factors. For example, people of high socioeconomic status are more likely to engage in greater levels of physical activity, and are more inclined to adhere and take up population-level behaviour change interventions. Subsequently, there has been a call to create more targeted interventions designed to especially target people with low socioeconomic status.
Socioeconomic status represents availability and access to resources, and measures that are broadly divided into individual measures such as income, education and occupational status, and area-level or neighbourhood deprivation measures. However, while socioeconomic status is a multifaceted concept, there is a tendency in research to use a single measure (such as either income or education level) interchangeably to capture the full scope of socioeconomic status. This is based upon the assumption that one socioeconomic measure taps into the underlying features of another aspect of socioeconomic status, despite little being known about the effect each socioeconomic status measure has upon physical activity intervention outcomes.
Therefore the purpose of this study is to consider the effect the different measures of socioeconomic status, specifically income, occupational status, education and area deprivation, have upon the effectiveness of an established implementation intentions-based intervention (the volitional helpsheet) designed to increase physical activity.
Detailed Description A health gap exists such that people of low socioeconomic status are more inclined to incur poor health than those of high socioeconomic status (Marmot, 2005). Differences in modifiable lifestyle factors between high- and low-socioeconomic groups, such as differences in physical activity levels, have been implemented in contributing to this health gap. Additionally, interventions created to redress this health gap can unintentionally have the reverse effect of increasing health inequalities as more affluent individuals are more likely to take up and adhere to behaviour change interventions, thus creating intervention-generated inequalities (White et al., 2009). Subsequently, there has been an increased call for interventions designed to promote healthy lifestyle behaviours, including physical activity, to be targeted towards specific groups of individuals including people with low-socioeconomic status (White et al., 2009). However, socioeconomic status is typically operationalised using a single measure such as educational status, yet socioeconomic status represents availability of and access to resources (Psaki et al., 2014), including those that access physical activity.
Socioeconomic measures can broadly be categorised as individual level factors, such as income, education and occupation, and area-level indicators or neighbourhood deprivation indices (Galobardes et al., 2006a, 2006b) such as the Index of Multiple Deprivation. While each measure captures a specific aspect of socioeconomic status, having its own relative strengths and limitations, there is a tendency in research to use a single measure (such as either income or education level) interchangeably to capture the full scope of socioeconomic status (Geyer et al., 2006). This is based upon the assumption that one socioeconomic measure taps into the underlying features of another aspect of socioeconomic status, despite little being known about the effect each socioeconomic status measure has upon physical activity intervention outcomes.
The purpose of this study is to consider the effect the different measures of socioeconomic status, specifically income, occupational status, education and area deprivation, have upon the effectiveness of an established implementation intentions-based intervention (the volitional help sheet) designed to increase physical activity and which has been shown to increase physical activity among manual workers (Armitage & Arden, 2010).
This study will seek to address the following research questions;
Method A two-armed randomised controlled trial design was used. Participants were randomised into either the intervention or control condition using an online random number generator.
Participants A sample size calculation was conducted using evidence from Belanger-Gravel et al., (2013) in their meta-analysis examining the effects of implementation intentions on physical activity. Assuming an effect size of 0.24 (α = 0.05), the study was powered to 90%, giving a desired sample size of 786 participants (384 participants per group). However, the desired sample size was not achieved. Subsequently, a total of 118 adult participants (aged 18 years or older) were recruited from leisure centres in deprived areas of a city located in the North West of England. The final total sample size was 98 due to issues associated with missing values of some key socioeconomic status variables.
Procedure New leisure centre members were invited to take part in the study by either the researcher or a staff member. Each participant was provided with a participant information sheet, and asked to complete a consent form before completing the questionnaire which had been randomised in advance. It was explained to each participant in writing that their gym attendance was be tracked for 12-months using their electronic gym entry swipes. Each questionnaire was identical, differing only in the instructions on how to complete the volitional help sheet.
Intervention The volitional help sheet is a psychological tool based on implementations intentions, which helps the formation of "if-then" plans. This helps individuals to translate motivation into behavioural action. "If-then" plans are created when an individual links a critical situation in memory ("if") with an appropriate behavioural response ("then") (Armitage and Arden, 2010). In this way "if-then" plans enable an individual to automatically initiate the specified behavioural response when the environmental cue is encountered (Armitage and Arden, 2010). The volitional help sheet is comprised of two lists; one of critical situations that challenge participants to being physically active (e.g. "If I'm tempted not to go to the gym because it's cold outside"), and the other appropriate behavioural solutions (e.g. "then I will make myself go to the gym anyway because I know I will feel better afterward". In the present study, the intervention group participants are required to draw a line to between relevant critical situations and solutions to create "if-then" plans. The control group receive the exact same volitional help sheet, the only difference being that participants are instructed to tick relevant critical situations and solutions.
Measures Demographic information including gender, age and ethnicity was taken in addition to the following measures.
Gym attendance - Gym attendance for each participant was measured electronically by tracking gym entry swipes. Gym attendance was obtained for 12-months from when the baseline questionnaire was completed. As each participant is required to attend a mandatory induction session to access the gym suite, this session was discounted from the total attendance.
Physical activity - The short form International Physical activity Questionnaire (IPAQ-SF) (Craig et al., 2003) was used to obtain a self-reported measure of physical activity.
The following socioeconomic status measures were taken; Area deprivation - Each participants post-code was used to obtain an area deprivation score using the English Indices of Multiple Deprivation (IMD, 2015) which was then grouped to obtain a decile ranking.
Household Income - was assessed using the Living Costs and Food survey (LCFS, 2014). Accordingly, participants were asked to select which income band from eleven represents there household income. Income bands increase by £100 increments and range from "Less than £100 per week" to "Over £1000 per week".
Occupational Status - An adapted version of the National Statistics Socioeconomic Classification NS-SEC method (NS-SEC 2010) was used to obtain a measure of occupational status for each participant. Participants were initially asked to indicate their employments status from six options including "employed", "self-employed" and "student", and to state their most recent or current job role and what it entails. Participant job titles were then mapped onto the NS-SEC coding framework to derive an occupation code, which was used to establish an NS-SEC analytic and operational category for each participant.
Education - was measured using the qualification questions obtained from the UK Census 2011. Participants were required to indicate, from a list of qualifications ("1 - 4 O levels / CSEs / GCSEs (any grade), Entry Level, Foundation Diploma", "Apprenticeship", "Degree (for example BA, BSc), higher degree (for example MA, PhD, PGCE" and "No qualifications") every qualification that applied to them from the list. Participants were instructed to tick the nearest equivalent qualification if their UK qualification was not listed. For those participants who had acquired qualifications outside of the UK, they were instructed to tick "Foreign Qualifications" and then the nearest UK equivalent qualification, if known.
Statistical Analysis Randomisation success of the total sample was evaluated using multivariate analysis of variance (MANOVA).
A one-way between groups analysis of variance (ANOVA) was used to assess the effectiveness of the volitional help sheet upon total gym attendance during the 12-month study period between the experimental and control groups. Two way between-group ANOVA's were used to evaluate the direct and indirect effects of each socioeconomic measure of income, education, occupation and area deprivation upon gym attendance between both the experimental and control conditions.
Inclusion Criteria:
Exclusion Criteria: