Environment International 140 (2020) 105738 Contents lists available at ScienceDirect Environment International journal homepage: www.elsevier.com/locate/envint Measuring for change: A multi-centre pre-post trial of an air quality T feedback intervention to promote smoke-free homes Ruaraidh Dobsona, Rachel O'Donnella, Olena Tigovab,c,e, Marcela Fub,c,d,e, Marta Enríquezb,c,e, Esteve Fernandezb,c,d,e, Giulia Carrerasf, Giuseppe Gorinif, Simona Verdif, Alessandro Borginig, Andrea Tittarellig, Chiara Veroneseg, Ario Ruprechtg, Vergina Vyzikidouh, Anna Tzortzih, Constantine Vardavash, Sean Semplea, on behalf of the TackSHS investigators1 a Institute for Social Marketing and Health, University of Stirling, Stirling, UK b Tobacco Control Unit, Institut Català d’Oncologia (ICO), Barcelona, Spain c Tobacco Control Research Group, Institut d’Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain d School of Medicine and Health Sciences, Universitat de Barcelona, Spain e Consortium for Biomedical Research in Respiratory Diseases (CIBER en Enfermedades Respiratorias, CIBERES), Madrid, Spain f Oncologic Network, Prevention and Research Institute (ISPRO), Florence, Italy g Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy h Hellenic Cancer Society, Athens, Greece A R T I C LE I N FO A B S T R A C T Handling Editor: Xavier Querol Introduction: Second-hand smoke exposure in the home is a serious cause of ill-health for children. Behaviour Keywords: change interventions have been developed to encourage parents to keep homes smoke-free. This study evaluates Second-hand smoke a novel air quality feedback intervention using remote air quality monitoring with SMS and email messaging to Particulate matter promote smoke-free homes among families from deprived areas. Indoor air quality Methods: This paper presents a pre-post study of this intervention. Using internet connected monitors developed Environmental tobacco smoke with the Dylos DC1700, daily SMS and weekly email feedback provided for 16 days to participants recruited in four European countries. Participants were recruited based on their stage of change, in order to target those most able to achieve smoke-free homes. The primary outcome measure was median change in mean fine particulate matter (PM2.5) concentration between baseline and follow-up periods, while secondary outcome measures in- cluded change in time over the World Health Organisation (WHO) guideline limit for PM2.5 exposure over 24 h (25 µg/m3) in those periods and the number of homes where PM2.5 concentrations reduced. Telephone inter- views were conducted with participants in Scotland post-intervention to explore intervention experience and perceived effectiveness. Results: Of 86 homes that completed the intervention study, 57 (66%) experienced pre-post reductions in measured PM2.5. The median reduction experienced was 4.1 µg/m3 (a reduction of 19% from baseline, p = 0.008). Eight homes where concentrations were higher than the WHO guideline limit at baseline fell below that level at follow-up. In follow-up interviews, participants expressed positive views on the usefulness of air quality feedback. Discussion: Household air quality monitoring with SMS and email feedback can lead to behaviour change and 1 The TackSHS Project Investigators: Catalan Institute of Oncology (ICO); Bellvitge Biomedical Research Institute (IDIBELL), Spain: Esteve Fernández, Yolanda Castellano, Marcela Fu, Montse Ballbè, Beladenta Amalia, Blanca Paniello, Olena Tigova. Public Health Agency of Barcelona (ASPB), Spain: Maria José López, Xavier Continente, Teresa Arechavala, Elisabet Henderson. Istituto di Ricerche Farmacologiche Mario Negri IRCCS (IRFMN), Italy: Silvano Gallus, Alessandra Lugo, Xiaoqiu Liu, Cristina Bosetti, Enrico Davoli, Elisa Borroni; Istituto DOXA, Worldwide Independent Network/Gallup International Association, Italy: Paolo Colombo. University of Stirling (UNISTIR), the UK: Sean Semple, Rachel O’Donnell, Ruaraidh Dobson. TobaccoFree Research Institute Ireland (TFRI), Ireland: Luke Clancy, Sheila Keogan, Hannah Byrne. Hellenic Cancer Society - George D. Behrakis Research Lab (HCS), Greece: Panagiotis Behrakis, Anna Tzortzi, Constantine Vardavas, Vergina Konstantina Vyzikidou, Gerasimos Bakelas, George Mattiampa. Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Italy: Roberto Boffi, Ario Ruprecht, Cinzia De Marco, Alessandro Borgini, Chiara Veronese, Martina Bertoldi, Andrea Tittarelli. Istituto per lo Studio, la Prevenzione, e la Rete Oncologica (ISPRO), Italy: Giuseppe Gorini, Giulia Carreras, Barbara Cortini, Simona Verdi, Alessio Lachi, Elisabetta Chellini. Polytechnic University of Cartagena (UPCT), Spain: Ángel López Nicolás, Marta Trapero-Bertran, Daniel Celdrán Guerrero. European Network on Smoking and Tobacco Prevention (ENSP), Belgium: Cornel Radu-Loghin, Dominick Nguyen, Polina Starchenko. Hospital Universitario La Princesa (IISP), Spain: Joan B Soriano, Julio Ancochea, Tamara Alonso, María Teresa Pastor, Marta Erro, Ana Roca, Patricia Pérez, Elena García Castillo. https://doi.org/10.1016/j.envint.2020.105738 Received 31 January 2020; Received in revised form 7 April 2020; Accepted 10 April 2020 Available online 01 May 2020 0160-4120/ © 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/). R. Dobson, et al. Environment International 140 (2020) 105738 consequent reductions in SHS in homes, but within the context of our study few homes became totally smoke- free. 1. Introduction concentration (PM2.5) installed in their homes for a period of 30 days. These devices allow data acquisition in real-time with a 3G internet Second-hand smoke (SHS) is a risk factor for a range of childhood connection but no information is directly displayed on the device; 2) illnesses, including otitis media, meningitis and asthma exacerbations Personalised feedback: during the intervention, personalised feedback (US Surgeon General, 2006). In countries with comprehensive smoke- was provided via SMS and email to the smoker, and was discussed with free indoor places legislation, the home is the primary remaining lo- the smoker along with goal-setting and exploration of suitable methods cation of childhood exposure to SHS (Akhtar et al., 2007). A wide range of behaviour change by telephone; 3) A final home visit gathered data of behaviour change interventions have been designed and trialled to on changes made. Intervention components over time are shown in encourage parents who smoke not to do so indoors. Techniques such as Fig. 1. counselling (Abdullah et al., 2015; Chellini et al., 2013), smoking ces- Particulate matter monitoring was conducted in the participant’s sation support for parents (Jiménez-Muro et al., 2013) and feedback of home for 30 days. Monitoring with no feedback took place during the children’s biomarkers of SHS exposure (McIntosh et al., 1994) have first seven days (the pre-intervention period). Between days 8 and 23 been used in some interventions, but the evidence does not clearly in- (inclusive), one SMS message giving information about the air quality dicate a best-practice strategy to reduce SHS exposure and improve in the home along with a semi-randomly generated advice to encourage children’s health (Behbod et al., 2018). parents to make their home smoke-free was sent to the participant’s One promising technique for promoting smoke-free homes is air mobile phone each day. On days 8, 16 and 22 emails containing a graph quality feedback – giving parents objective information about the im- of air quality over the past seven days and a graphical representation of pact of their smoking on indoor air, and thereby on their children’s the mean air quality in that time were sent. On days 9 & 23, participants health. Of five randomised controlled intervention trials using this received a 15-minute phone call from a member of the local research technique, four led to significant reductions in the intervention arm team to discuss the information they received the day before, asking (Emmons et al., 2001; Ratschen et al., 2017; Hughes et al., 2018; additional questions about their progress and offering them the chance Harutyunyan et al., 2013) with one leading to no change at follow-up to ask questions about the intervention process. (Semple et al., 2018). Previous studies have often used feedback provided days or weeks 2.2. Recruitment after air quality measurements were taken (Emmons et al., 2001; Ratschen et al., 2017; Wilson et al., 2013; Dobson et al., 2017;3.), An overall recruitment target of 160 individuals was set across four which could reduce the effectiveness of feedback if participants have countries/five study centres. Centres in Scotland, Greece and Catalonia forgotten their behaviours during the measurement period. were set targets of 40 recruits, while the two Italian centres (Milan and In order to build on these previous intervention studies in a lower- Florence) were each set a target of 20. Although inclusion and exclusion cost intervention, it was decided to develop an intervention which used criteria remained the same in each centre, specific recruitment strate- remote feedback, providing information from internet-based air quality gies varied to take account of different circumstances in each country. monitoring. This intervention would employ both immediate and de- Among the strategies used were advertisements displayed on social layed feedback techniques to communicate information about SHS in networks (including Facebook), primary health care centres, uni- the home using SMS, email messaging and phone calls. versities and libraries. This intervention incorporates the remote delivery of objective Monitoring took place from November 2017 – September 2018 in feedback on SHS levels in the home using both air quality feedback and Scotland, April 2018 – July 2018 in Florence, April 2018 – November mobile health techniques. This study aims to evaluate the effectiveness 2018 in Greece, April 2018 – December 2018 in Milan and September of that intervention. 2018 – April 2019 in Catalonia. 2. Methods 2.3. Inclusion and exclusion criteria 2.1. Study design and overall intervention To be eligible to participate, individuals had to smoke in their home indoors or live with someone who smoked indoors, take care of a child This paper describes a pre-post study of the Measuring for Change aged 16 or under at least once a week, have regular access to the in- intervention to promote smoke-free homes. The intervention had sev- ternet and have no plans to move home for two months from first eral components: 1) PM2.5 monitoring: participants were provided with contact with the research team. particle counting instruments to measure in real time particulate matter Following a previous air quality intervention study conducted in Fig. 1. Intervention components over the course of an intervention. 2 R. Dobson, et al. Environment International 140 (2020) 105738 Scotland in which many participants were unable to make a substantial communications between smoking-permitted and smoke-free homes in change to their smoking behaviours (Semple et al., 2018) this inter- SMS messages, an estimated value for PM2.5 in homes where smoking is vention was designed to target those who were motivated and capable not allowed was required. Ambient air pollution varies in locations of making their homes smoke-free. For this reason, a stage of change around the world. As this study was conducted in five cities across assessment questionnaire was designed to assess participants’ capacity Europe with variable levels of air pollution specific comparison values to change. This questionnaire incorporated an assessment of stage of were generated for each study centre. change pre-intervention, based on the five sequential stages of change Each centre conducted five-day measurements in five smoke-free outlined in the transtheoretical model of behaviour change (Prochaska homes within their study area to determine a smoke-free homes value. and Velicer, 1997), in order to identify potential participants who were In addition to the generation of smoke-free homes values, these mea- in the contemplation (thinking about change), preparation (taking steps surements were used as an opportunity to train researchers in the op- toward changing) and maintenance (changing) stages of change who eration of the RAPID monitors. may be more likely to engage with the intervention. Also included were two questions to assess feasibility of change towards creating a smoke- 2.5. SMS and email messages free home, based on previous research that has identified a number of barriers associated with successful behaviour change in this context Messages were generated automatically using custom software de- (Passey et al., 2016). veloped for this study following pre-defined templates. SMS messages Potential participants were asked to assess whether smoking in the were made up of a selection of components, some based on the air home was a problem for themselves or anyone living in their home, quality of the participant’s home, others randomly selected. A message asked when they might change their behaviour, and asked how realistic would first give the estimated PM2.5 concentration in the home over the it would be to make their home smoke-free, and how realistic it would 24 h before the message was generated. It would then provide a com- be to reduce the amount of SHS in the home (on a Likert scale where 0 parison to the estimated concentration over the previous seven days represented “not realistic at all” and 10 represented “extremely rea- (higher, similar or lower) followed by a comparison to PM2.5 con- listic”). A further free-form question asked about barriers and facil- centrations in smoke-free homes as measured in an urban area relevant itators to making the home smoke-free, focusing on practical issues to the participant (Edinburgh, Milan, Florence, Athens or Barcelona). such as other smokers living there and access to outdoor space. Finally, a short piece of advice on keeping a smoke-free home derived Participants were ineligible to participate if they indicated that from the Scottish Government’s Right Outside campaign (Inform, 2018) smoking was not a problem in the home, or if their answer to how was appended. Example messages can be seen in Supplementary file 1. realistic making the home smoke-free would be was less than or equal These components were translated into Italian, Greek and Spanish. to 3. Recruits could be eligible to take part in the study if they lived with 2.6. Telephone feedback an adult smoker but did not smoke themselves. In this case, the inter- vention was delivered as with a smoking participant with researchers Participants were telephoned on two occasions (at day 9 and day using elements of the AFRESH Programme (Dobson et al., 2017;3.; 23). These days were chosen to allow participants to receive and read O’Donnell et al., 2019) to provide assistance on communicating mes- emails on days 8 and 22, and consider questions and thoughts during sages about SHS in homes to other householders. that time. These calls were semi-structured, including a questionnaire mirroring elements of the initial stage of change questionnaire given at 2.4. Monitoring strategy recruitment (to track changes in motivation to change). Participants were asked about the status of previously identified barriers and facil- Dylos DC1700 monitors, low-cost optical particle counters which itators, with guidance given on overcoming barriers. have been used to detect SHS-related PM2.5 in previous studies (Hughes et al., 2018; Semple et al., 2018; Semple et al., 2013), were converted 2.7. Follow-up interviews into internet-connected RAPID monitors as described in a previous paper (Dobson et al., 2019;17.). These monitors were used to provide In Scotland, participants who had completed the intervention were continuous internet-connected air quality monitoring in each inter- invited to take part in a 20-minute follow-up telephone interview, vention household for 30 days. Monitors were installed in the main which explored participant experience of the intervention process and living area of the house to provide a representation of personal ex- participant views on its effectiveness, using a mix of open-ended and posure at home, at a height of at least one metre from the floor to avoid closed questions (see Supplementary file 2 for interview schedule). low-level dust, and away from any open windows (to avoid air currents) or obvious sources of PM (such as cookers). 2.8. Questionnaires Each monitor used in the study was individually calibrated to im- prove the accuracy of the device’s measurements. Calibration was In addition to stage of change questionnaires given at recruitment, conducted in Milan by researchers at the National Cancer Institute of day 9 and day 23 (Supplementary file 2), participants were given Italy (INT). Calibration of 29 Dylos devices took place against a BAM- baseline and follow-up questionnaires at first and last home visits. 1020 continuous particle monitor (Met One Instruments, Inc., Grants Questions asked for information about the home, smoking rules indoors Pass, Oregon), a high-precision instrument frequently used for reg- and knowledge about the health effects of SHS. ulatory purposes. Dylos devices were collocated with the BAM-1020 and three fans in an office owned by INT. Volunteer smokers were asked 2.9. Statistical analysis to smoke in this room for one hour, with the monitors left running for six hours. 2.9.1. Quantitative analysis Instrument-specific calibration factors were generated by dividing The primary outcome measure was change in mean PM2.5 between the mean BAM-1020 PM2.5 concentration by each Dylos’ estimated baseline monitoring period (day 1 – day 7 inclusive) and follow-up PM2.5 concentration (as derived from a previously developed equation monitoring period (day 24 – day 30). Secondary outcome measures designed to estimate SHS-related PM2.5 mass concentration from Dylos included the time spent over the WHO guideline limit for PM2.5 over small particle number concentration data) (Semple et al., 2015). The 24 h (25 µg/m3) at baseline and follow-up and the number of homes in calibration factors for the Dylos devices ranged between 1.39 and 3.18. which PM2.5 concentrations fell. In order to provide a general point of comparison in SMS and email Changes in paired home concentration data at baseline and follow- 3 R. Dobson, et al. Environment International 140 (2020) 105738 up, and home time over the WHO guideline limit, were tested for sig- Full results by each centre and combined overall can be seen in Table 1. nificance using the paired Wilcoxon signed-rank test. Pairs of baseline Declines in measured PM2.5 occurred at each centre and overall. In and follow-up values from each household were submitted to this test. total, 57/86 homes (66%) had reduced PM2.5 concentrations at follow- up compared to baseline. The percentage decline was similar across 2.10. Qualitative analysis centres, ranging between 59% in Stirling and 72% in Milan. Overall, this suggests that the intervention resulted in the majority of homes in Follow-up interviews were hand-recorded, with the interviewer each centre reducing their smoking behaviour indoors. [RO] taking intelligent verbatim notes on open-ended responses. Two A secondary outcome measure in this study was change in the researchers (RO and RD) independently reviewed the content of each percentage of time where measured PM2.5 concentrations exceeded the interview, compared responses and identified preliminary themes. WHO’s guideline indoor limit for PM2.5 over 24 h (25 µg/m3). The Additional analysis led to the agreement of key themes that reflected percentage of time at follow-up where PM2.5 was measured to be above participant’s experiences, quotes were extracted to illustrate each this concentration was compared to the percentage of time at baseline identified theme. where this was so. Overall, time spent over 25 µg/m3 fell by a median 3.3% from 2.11. Ethics, trial registration and study consortium baseline to follow-up, representing around one hour per day in which the median home was below that level following the intervention Ethical approval for the overall study was provided in the first in- (p = 0.012). stance by the College Ethics Review Board of the College of Life Sciences & Medicine at the University of Aberdeen (CERB/2016/12/ 1412). Each research centre outside of Scotland applied for and re- 3.3. Telephone interview findings ceived ethical approval from a local and applicable ethics board. The study was registered on ClinicalTrials.gov (Identifier: Eight participants in Scotland took part in an interview. The key NCT03151421). themes that reflected participant’s experiences are outlined in Table 2. The data obtained supports the finding that the intervention was suc- 3. Results cessful in reducing rather than eliminating SHS exposure in partici- pating homes. Two of the eight participants interviewed had created a 3.1. Recruitment completely smoke-free home, others reduced their smoking consump- tion, or made changes to when/where smoking took place in the home Recruitment involved an initial contact by telephone, during which (Fig. 3 quote a). Four participants attempted to raise the issue of potential participants were given information on the study, assessed smoking in the home with other adult household members who against inclusion criteria and asked to complete a stage of change as- smoked, with varying levels of success (Fig. 3 quote b), highlighting the sessment to determine whether they were ready to change the smoking importance of facilitating and maintaining change in relation to behaviour in their home. Due to an error, no stage of change assess- smoking in the home as a collective responsibility. Participants noted ments were conducted at first contact with participants in Milan. This several benefits associated with taking part in the intervention related could have resulted in participants unready to make behaviour changes to increased knowledge and awareness of the risks of SHS exposure taking part in the intervention study. (Fig. 3, quote c), but they raised a number of barriers associated with A total of 110 recruits passed the inclusion criteria while 86 com- creating an entirely smoke-free home, including mental health status, pleted the intervention. Of the 24 participants who initially agreed to sole caring responsibilities and poor weather conditions (Fig. 3, quote take part but did not complete the intervention, 21 withdrew before the d). informed consent stage while 3 were withdrawn due to technical issues All eight participants stated that they valued receiving objective, with air quality monitoring in their homes. personalised feedback on their home air quality levels, which was often viewed as ’evidence’ or ‘proof’ of the risks associated with smoking in 3.2. Intervention results the home (Fig. 3, quote e). Seven participants stated that they found the texts and emails received easy to understand, and they often compared Overall, there was a small but statistically significant reduction in the PM2.5 levels received in texts from one day to the next (Fig. 3, quote measured mean PM2.5 concentrations in the follow-up periods com- f). One participant needed help from their partner to understand the pared to the baseline across all participants in the study (the primary graphs. Three participants could not easily access the weekly emails outcome measure), with a median reduction of −19% (-4.1 µg/m3). using their mobile phones (Fig. 3, quote g). Table 1 Median of mean PM2.5 concentrations at baseline and follow-up, and median change in time spent over the WHO 24-hour guideline limit for PM2.5 (25 µg/m3), by centre and overall. Centre N Median of baseline mean Median of follow-up mean Median PM2.5 change for Median PM2.5 change as a % Median change in % time over PM2.5 concentration PM2.5 concentration paired samples of baseline WHO guideline limit (interquartile range) (interquartile range) (µg/m3) (µg/m3) (µg/m3) % % Athens 20 20.0 14.0 −3.2 (−7.6 – 0.9) −24.0 (−35.6 – 9.8) −8.6 Barcelona 18 102.7 67.3 − 11.2 (−44.3 – 1.3) −18.3 (−3.5 – 6.1) −0.5 Florence 3 32.0 19.0 −4.8 (−11.8 – 1.8) −12.0 (−35.7 – 3.5) −0.1 Milan 18 17.0 14.0 −2.1 (−11.2 – 0.6) −18.0 (−53.6 – 1.4) −1.6 Stirling 27 64.0 59.0 −8.3 (−30.3 – 22.8) −12.0 (−37.1 – 19.8) −5.5 Overall 86 33.0 33.0 −4.1 (−18.5 – 3.8) −19.0 (−39.9 – 9.2) −3.3 A Wilcoxon signed rank test was conducted on the paired baseline and follow-up mean concentrations of all centres over the course of the intervention, showing that this change was statistically significant (p = 0.008). Due to the small sample sizes available, significance testing was not conducted on samples by centre. Mean PM2.5 declined in most homes between baseline and follow-up at each centre. Fig. 2 plots mean PM2.5 at baseline (X axis) and follow-up (Y axis) for each participant across all centres. The dots on the lower right of the diagonal line (lower concentration at follow-up) graphically show the level of decline. 4 R. Dobson, et al. Environment International 140 (2020) 105738 Table 2 Themes interpreted from the follow-up telephone interview data. Core theme Sub-themes Acceptability of air quality monitoring - Personalised feedback - User experience - Interpretation and impact of results Acceptability of mobile health techniques - Daily (text) vs. weekly (email) feedback - User experience - Interpretation and impact of information received Raising the issue of smoking in the home with other household members - SHS as a collective responsibility - Household-level communications - Ability to influence household-level change Changes made as a result of the intervention - Reduced cigarette consumption - Changing where/when smoking takes places indoors - Taking smoking right outside the home - Switching to an e-cigarette Barriers to smoking behaviour change in the home - Other adult smokers in the household - Changing existing routines - Health-related barriers (mental health, physical illness, addiction) - Practical barriers (weather, dark nights, comfort) - Psychological factors (motivation, stigma, guilt) Perceived benefits of taking part - Changes in smoking behaviour in the home - Acquiring new knowledge - Increased awareness of the risks of smoking in the home 4. Discussion long intervention. However, this reduction does not typically lead to participants having fully smoke-free homes, instead leading to sig- Based on the results of this study, the Measuring for Change inter- nificant but small reductions of about 19% in mean PM2.5 concentra- vention can reduce SHS exposure in homes over the course of a month- tions and 3.3% in percentage time spent over the WHO guideline limit Fig. 2. PM2.5 concentrations at baseline and follow-up in each participating home. Results to the lower right of the identity line represent declines in PM2.5 concentration over the intervention period. 5 R. Dobson, et al. Environment International 140 (2020) 105738 Fig. 3. Participant experiences of taking part in the intervention. for PM2.5 over 24 h in the home. This, alongside the telephone inter- than other intervention designs, comparison of recent results to past view findings, suggests that the intervention leads to participants giving results within the home was limited to four telephone counselling ses- greater consideration to the impact of smoking on household air quality sions over the course of three months. This may have impacted the and/or the harms of SHS, but being unable to take all the necessary ability of participants to set goals to reduce SHS indoors, as there was a steps to make the home entirely smoke-free all of the time. lack of immediacy in the feedback and they may not have been able to This study represents a new approach to air quality feedback for associate particular behaviour with poor air quality results. Ad- smoke-free homes, incorporating novel techniques such as SMS mes- ditionally, this intervention required the use of two air quality monitors saging and internet-based feedback. Other studies of air quality feed- and custom equipment to produce warnings and transmit data to re- back interventions have used either immediate (Hughes et al., 2018; searchers, increasing cost. Harutyunyan et al., 2013) or significantly delayed (Ratschen et al., As a quasi-experimental study without comparison group rather 2017; Semple et al., 2018) feedback. This study is the first to use a than a randomised controlled trial, this study cannot definitively de- hybrid approach, combining near-immediate feedback through SMS monstrate causation. However, the effect size (a median decline in messages with delayed, in-depth researcher-supported feedback mean PM2.5 concentration of 19% between baseline and follow-up through emails and phone calls. periods) is similar to other published research on air quality feedback Other interventions have taken rapid feedback approaches. One trial interventions (Ratschen et al., 2017; Hughes et al., 2018) which in- has provided participants with real-time feedback on their air quality cluded a control group. over a sustained period of time. This intervention, developed and tested Unlike some other studies in this area, no non-air quality feedback at San Diego State University (Hughes et al., 2018; Klepeis et al., 2013; elements such as nicotine replacement therapy (Ratschen et al., 2017) Hovell et al., 2019:) involved the use of a customised monitor with were included in the intervention, making this study a true test of air LEDs and speakers to produce specially designed auditory and visual quality feedback as a method of promoting smoke-free homes. The warnings (Bellettiere, et al., 2014) when detected particle concentra- value of adding a component of cessation to this smoke-free home in- tions exceeded certain levels. While this provided more rapid feedback tervention should be evaluated in further studies. 6 R. Dobson, et al. Environment International 140 (2020) 105738 Telephone interviews were confined to a small proportion of the PM2.5 concentrations in homes undergoing the intervention. Scottish sub-sample of participants, and the views and experiences of Participants found SMS and email messages useful in reducing SHS in those who took part are not representative of participants in the wider their home, although some technical problems occurred viewing sample. Conducting relatively short, hand-recorded telephone inter- emails. An intervention of this kind can successfully reduce SHS ex- views may have limited the detail given in participant responses to posure in the home over a short trial period, although in this group of open-ended questions. However, this strategy may also have increased smokers it did not lead to wholly smoke-free homes on a large scale. participation at follow-up given there was no need to schedule a home visit or take part in a longer, in-depth interview. Intervention fidelity was heterogeneous across centres; in Milan, Funding stage of change data were not acquired at first contact and SMS mes- sages were sent less frequently than in other centres. The limited This project has received funding from the European Union’s sample size means that this study is underpowered to detect differences Horizon 2020 research and innovation programme under grant agree- between centres, but Milan had the lowest absolute median decline in ment No 681040. We thank CERCA Programme / Generalitat de PM2.5 of any centre (−2.8 µg/m3). Catalunya for institutional support. EF, MF, ME and OT were supported Difficulties in recruitment across all centres led to a smaller sample by the Ministry of Research and Universities from the Government of size than initially intended. While we observed statistically significant Catalonia (2017SGR319). EF was supported by the Instituto de Salud change in the primary outcome measure, it should be noted that this Carlos III, Government of Spain, co-funded by the European Regional small sample size (combined with the small change in PM2.5 observed) Development Fund (FEDER) (INT16/00211 and INT17/00103). EF, and may increase the chance that this did not represent real change. Future MF, ME and OT thank CERCA Programme / Generalitat de Catalunya studies of interventions of this type should include control elements and for institutional suppor This project has received funding from the recruit a larger sample size to mitigate against this risk. European Union’s Horizon 2020 research and innovation programme Recruitment strategies differed by centre which may have con- under grant agreement No 681040. We thank CERCA Programme / tributed to differences in recruitment success and participant retention Generalitat de Catalunya for institutional support. EF, MF, ME and OT (particularly in Stirling drop-out was unusually high). How to reach the were supported by the Ministry of Research and Universities from the target population is a matter of concern in all community-based and Government of Catalonia (2017SGR319). EF was supported by the health promotion interventions (World Health Organisation. A guide to Instituto de Salud Carlos III, Government of Spain, co-funded by the implementation research in the prevention and control of non- European Regional Development Fund (FEDER) (INT16/00211 and communicable diseases. Geneva:, 2016), and an important topic when INT17/00103). EF, and MF, ME and OT thank CERCA Programme / implementing them. Generalitat de Catalunya for institutional support. The RAPID monitor system performed well but occasional failures in monitoring required researchers to monitor the status of each monitor CRediT authorship contribution statement on a frequent basis. Due to the nature of the system, which included several components with external wired connections, it was possible for Ruaraidh Dobson: Conceptualization, Methodology, Software, connections to become loose if the device was accidentally knocked. Validation, Investigation, Data curation, Writing - original draft, Additionally, software errors occurred causing delays or failures in Visualization, Project administration. Rachel O’Donnell: sending data to the server. These were partially remedied by ongoing Conceptualization, Methodology, Investigation, Data curation, Writing development of the system during the course of the study, but were not - original draft. Olena Tigova: Methodology, Investigation, Writing - completely eliminated. Using an alternative monitoring system with review & editing, Project administration. Marcela Fu: Methodology, integrated long-term data storage and internet connection capabilities Investigation, Writing - review & editing. Marta Enríquez: may reduce these problems further. Methodology, Investigation, Writing - review & editing. Esteve Fernandez: Conceptualization, Investigation, Writing - review & 4.1. Alternative explanations for change editing, Funding acquisition, Supervision. Giulia Carreras: Methodology, Investigation, Writing - review & editing. Giuseppe As this study did not include a control group, it is possible that Gorini: Methodology, Investigation, Writing - review & editing. PM2.5 concentrations declined in homes for reasons not related to the Simona Verdi: Methodology, Investigation, Writing - review & editing. intervention. The median change detected in PM2.5 concentration be- Alessandro Borgini: Methodology, Investigation, Writing - review & tween baseline and follow-up periods was statistically significant but editing. Andrea Tittarelli: Methodology, Investigation, Writing - re- small in absolute terms (< 5µg/m3). Seasonal variation in ambient air view & editing. Chiara Veronese: Methodology, Investigation, Writing pollution could have accounted for some of this change, as the month- - review & editing. Ario Ruprecht: Methodology, Writing - review & long measurement periods used could have reflected gradual changes in editing. Vergina Vyzikidou: Methodology, Investigation, Writing - PM2.5 concentration over this time (depending on the infiltration of review & editing. Anna Tzortzi: Methodology, Investigation, Writing - PM2.5 into homes in each setting, which may relate to building design review & editing. Constantine Vardavas: Methodology, Investigation, and location among other factors). Analysis of ambient PM2.5 con- Writing - review & editing. Sean Semple: Conceptualization, centrations available from four of the five study centres using European Methodology, Validation, Data curation, Writing - original draft, Environment Agency (European Environment Agency. Air Quality e- Funding acquisition, Supervision. : . Reporting (AQ e-Reporting). https://www.eea.europa.eu/data-and- maps/data/aqereporting-8 (accessed 7 Apr 2020) monitoring station data from 2018 (not presented in this paper) indicated no correlation Declaration of Competing Interest between change in outdoor air from baseline to follow-up periods and change in measured PM2.5 concentrations in participating households. The authors declared that there is no conflict of interest. 5. Conclusions Appendix A. Supplementary material An air quality feedback intervention using a hybrid of immediate and delayed feedback techniques through remote air quality monitoring Supplementary data to this article can be found online at https:// is feasible and acceptable to participants, resulting in a 19% decline in doi.org/10.1016/j.envint.2020.105738. 7 R. Dobson, et al. Environment International 140 (2020) 105738 References Wilson, I., Semple, S., Mills, L.M., et al., 2013. 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