Smoking cessation behavioural therapy in disadvantaged neighbourhoods: an explorative analysis of recruitment channels

Abstract

BackgroundThe optimum channel(s) used to recruit smokers living in disadvantaged neighbourhoods for smoking cessation behavioural therapy (SCBT) is unknown. This paper examines the channels through which smokers participating in a free, multi-session SCBT programme heard about and were referred to this service in a disadvantaged neighbourhood, and compares participants’ characteristics and attendance between channels.Methods109 participants, recruited from free SCBT courses in disadvantaged areas of two cities in the Netherlands, underwent repeated surveys. Participants were asked how they heard about the SCBT and who referred them. Participant characteristics were compared between five channels, including the General Practitioner (GP), a community organisation, word of mouth, another health professional, and media or self-referred. Whether the channels through which people heard about or were referred to the service predicted attendance of ≥4 sessions was investigated with logistic regression analysis.ResultsOver a quarter of the participants had no or primary education only, and more than half belonged to ethnic minority populations. Most participants heard through a single channel. More participants heard about (49 %) and were referred to (60 %) the SCBT by the (GP) than by any other channel. Factors influencing quit success, including psychosocial factors and nicotine dependence, did not differ significantly between channel through which participants heard about the SCBT. No channel significantly predicted attendance.ConclusionThe GP was the single most important source to both hear about and be referred to smoking cessation behavioural therapy in a disadvantaged neighbourhood. A majority of participants of low socioeconomic or ethnic minority status heard about the programme through this channel. Neither the channel through which participants heard about or were referred to the therapy influenced attendance. As such, concentrating on the channel which makes use of the existing infrastructure and which is highest yielding, the GP, would be an appropriate strategy if recruitment resources were scarce.

Classroom Popularity Hierarchy Predicts Prosocial and Aggressive Popularity Norms Across the School Year

“…The socioeconomic status of participants was calculated based on the zip codes, using “status scores” of the Social Cultural Planning Office, The Netherlands (see for instance Benson, Nierkens, Willemsen, & Stronks, ). These status scores were based on the percentage of inhabitants with lower incomes, the percentage of lowly educated inhabitants, average income of inhabitants within an area, and the percentage of unemployed inhabitants.…”

Associations between Ethnic Minority Status and Popularity in Adolescence: the role of Ethnic Classroom Composition and Aggression

“…In our sample, 46.7% of the students were enrolled in lower-level education (including preparatory secondary school for technical and vocational training), and 53.3% were attending higher-level education (including preparatory secondary school for higher professional education and for university). Family socioeconomic status was determined by means of families' zip codes for which "status scores" were assessed by the Dutch Social Cultural Planning Office (Benson et al 2015). These status scores were calculated based on the percentage of inhabitants with a low educational level and with relatively low incomes, the average income of inhabitants within an area, and the percentage of unemployed inhabitants.…”

The Role of Prosocial and Aggressive Popularity Norm Combinations in Prosocial and Aggressive Friendship Processes

“…Of the participants, 48.1% were attending lower-level education (i.e., preparatory secondary school for technical and vocational training), whereas 51.9% were enrolled in higher-level education (including preparatory secondary school for higher professional education and for university). Most respondents were native Dutch (80.9%) Participants' socioeconomic status was assessed based on the zip codes, using "status scores" of the Social Cultural Planning Office, The Netherlands (see Benson et al 2015). These status scores were based on the percentage of habitants with lower incomes, the percentage of lowly educated habitants, average income of habitants within an area, and the percentage of unemployed habitants.…”