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The effectiveness of digital health communication may be increased by enhancing autonomy supportiveness.
This study aimed to identify the most autonomy-supportive message frame within an intervention for increasing vegetable intake by testing the effect of the following 2 strategies: (1) using autonomy-supportive language and (2) providing choice.
A Web-based 2 (autonomy-supportive vs controlling language)×2 (choice vs no choice) experiment was conducted among 526 participants, recruited via a research panel. The main outcome measures were perceived autonomy support (measured using the Virtual Care Climate Questionnaire, answered with scores 1 to 5), perceived relevance (measured with one question, answered with scores 1 to 5), and overall evaluation of the intervention (measured with 1 open-ended question, answered with scores 1 to 10).
Choice had a significant positive effect on the overall evaluation of the intervention (
Results suggest that provision of choice rather than the use of autonomy-supportive language can be an easy-to-implement strategy to increase the effectiveness of digital forms of health communication, especially for people with a high need for autonomy.
Digital forms of health communication, for example, Web-based computer-tailored interventions, can be a cost‑effective strategy for health promotion [
Such effect improvement may be achieved by moving beyond a focus on
Previously, both autonomy-supportive and more directive communication styles have been identified and studied in offline forms of health communication [
Computer-tailored health communication uses a computerized process to adjust message content based on the individual users’ personal characteristics (eg, behavior, personality, attitudes, and beliefs), with the goal of increasing perceptions of personal relevance [
Given the positive effects found of an autonomy-supportive communication style (ie, including the use of autonomy-supportive language and the provision of choice) in the face-to-face setting [
H1: The use of autonomy-supportive language will result in (a) higher perceived autonomy support, (b) higher perceived relevance, and (c) a more positive overall evaluation of the intervention compared with the use of controlling language.
H2: The provision of choice will result in (a) higher perceived autonomy support, (b) higher perceived relevance, and (c) a more positive overall evaluation of the intervention compared with no provision of choice.
Although SDT suggests a universal need for autonomy, there may be individual differences in how autonomy needs influence message impact [
On the basis of these previous studies, we propose that in the context of digital health communication, baseline need for autonomy will interact with the intervention manipulations as follows:
H3: The effects of the use of autonomy-supportive language (vs the use of controlling language) on (a) perceived autonomy support, (b) perceived relevance, and (c) the overall evaluation of the intervention will be stronger for respondents with a high need for autonomy than for respondents with a low need for autonomy.
H4: The effects of the provision of choice (vs no provision of choice) on (a) perceived autonomy support, (b) perceived relevance, and (c) the overall evaluation of the intervention will be stronger for respondents with a high need for autonomy than for respondents with a low need for autonomy.
To test the hypotheses, an experiment with a 2 (language use: autonomy-supportive vs controlling language)×2 (choice: provided vs not provided) between-subjects design was conducted within the context of an existing Web-based computer-tailored intervention module aimed at increasing vegetable consumption [
A total of 728 Dutch adult participants started the experiment. Participants who did not give their informed consent (1/728, 0.1%) were not interested in eating—or continuing to eat—250 g of vegetables per day or did not provide an answer to this inclusion question (7/728, 1.0%) were excluded and not randomized. Of 720 randomized participants, 604 (83.8%) completed the entire intervention and questionnaire. However, we excluded participants with problematic or implausible response patterns: 7/604 (0.9%) participants took too long to fill in the questionnaire (3 SDs or more above the mean completion time), 23/604 (3.0%) participants filled in the questionnaire too fast (ie, <5 min), 2/604 (0.3%) participants filled in 0 as their weight, 9/604 (13.0%) participants had an extremely high vegetable consumption (3 SDs or more above the mean vegetable consumption), and 46/604 (6.0%) participants did not answer the 7 process evaluation questions in a logically consistent manner (ie, they filled in the same response for all questions even when items were scaled in opposing directions). For some of the participants, more than one of these problems were encountered; a total of 79/604 (13.1%) participants were excluded, and the final sample consisted of 525 participants. Of them, 231/525 (44.0%) were men, and 294/525 (56.0%) were women, with age ranging from 18 to 65 years (mean 43.35 years, SD 13.80). About half of the participants (261/525, 49.7%) were highly educated, and participants consumed on an average 183.80 g of vegetables daily (SD 96.45). Their average body mass index (BMI) was 25.52 kg/m2 (SD 4.95).
A Consolidated Standards of Reporting Trials flow diagram is provided in
Sample characteristics (N=525).
Variables | Value, n (%) | Value, mean (SD) | Range | |
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Male | 231 (44.0) | —a | — |
|
Female | 294 (56.0) | — | — |
Age (years) | — | 43.35 (13.80) | 18-65 | |
Length (cm) | — | 174.64 (9.69) | 154-200 | |
Weight (kg) | — | 78.07 (17.63) | 30-192 | |
Body mass index (kg/m2) | — | 25.52 (4.95) | 12.49-52.08 | |
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Low | 41 (7.8) | — | — |
|
Middle | 222 (42.3) | — | — |
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High | 261 (49.7) | — | — |
|
Other | 1 (0.1) | — | — |
Vegetable consumption | — | 183.80 (96.45) | 0-700 |
aNot applicable.
This study was approved by the ethics committee of the University of Amsterdam (reference number: 2016-PC-7205). First, participants received a brief explanation about the study aims and procedures as well as information about their rights and the confidential handling of their data. After participants provided their Web-based informed consent, they were asked about their intention to (continue) eating 250 g of vegetables per day, that is, the Dutch guideline for vegetable consumption [
Experimental conditions.
Choice | Language use, n (%) | Total, n (%) | |
Autonomy supportive | Controlling | ||
Yes | 147 (28.0) | 124 (26.6) | 271 (51.6) |
No | 141 (26.9) | 113 (21.5) | 254 (48.4) |
Total | 288 (54.9) | 237 (45.1) | 525 (100.00) |
The Web-based computer-tailored intervention was based on an intervention previously developed by Schulz et al, which aimed to improve several lifestyle-associated behaviors (ie, physical activity, vegetable consumption, fruit consumption, alcohol intake, and smoking cessation) and was called myHealthyBehaviour. As the study into the effectiveness of myHealthyBehaviour showed that the percentage of noncompliance with Dutch health guidelines was highest for vegetable intake (ie, 68%) [
The intervention consisted of 4 steps, each consisting of a set of questions and tailored feedback based on their answers, following an initial assessment of respondents’ vegetable consumption. The first step looked at the advantages and disadvantages participants experienced with regard to consuming enough vegetables, for example, the (expensive) price of vegetables and their positive effect on one’s health. The second step looked at the influence of the social environment of the participants, including one’s partner, family, friends, and colleagues. The third step assisted participants in making preparatory plans to consume enough vegetables, for example, by bringing vegetables to work as part of their lunch. The fourth step looked at participants’ self-efficacy and aided them in making plans to cope with potentially difficult situations, for example, in busy times.
The tailored feedback participants received was written in either an autonomy-supportive or controlling language, and choice options were either provided or not provided throughout the intervention.
Language was manipulated into autonomy-supportive language or controlling language that was used throughout the intervention, that is, in (the introductions to) the questions and the tailored feedback. Autonomy-supportive language was intended to provide participants a sense of volition over their decisions and used more tentative advice, for example, “you could try to bring snack vegetables to work.” In contrast, controlling language was more directive and definitive, for example, “you must bring snack vegetables to work!” [
Provision of choice was manipulated by either providing or not providing participants the possibility to choose if they wanted to make each out of 5 suggested preparatory plans (step 3) and to choose whether or not they wanted to make coping plans for each of the 7 potentially difficult situations described (step 4). Accordingly, participants who were provided with choice received feedback that was tailored based on the plans they chose (not) to make. Participants who were not provided with choice received 1 (nontailored) advice statement for preparatory planning and 1 (nontailored) advice statement addressing plans to cope with potentially difficult situations.
A pilot test of the manipulations was conducted among experts in digital health communication and health message framing (N=8) and target group members (N=8), the latter varying in age, sex, and socioeconomic status. Experts were identified through the professional network of the first author, and target group members were identified through the first and second authors’ private networks. Both were invited to complete the intervention and accompanying evaluation questions and were asked to identify any ambiguities in the questions and/or feedback. Moreover, they were asked to indicate whether the intervention felt autonomy supportive or controlling and whether they experienced choice or not. On the basis of the results from the pilot test, several improvements were made to messages and assessments.
An example of a feedback message in autonomy-supportive and controlling language, combined with and without choice, is provided in
Several demographic variables were assessed, that is, sex, age, educational level, and marital status. BMI was estimated based on the participant’s self-reported height and weight, and weekly vegetable consumption was measured using a 4-item food frequency questionnaire [
Perceived autonomy support was the first dependent variable and was measured using the Virtual Care Climate Questionnaire [
Perceived relevance was the second dependent variable and was measured with 1 question (“I perceived the feedback messages as personally relevant”) that could be answered from 1 (
Overall evaluation of the intervention was the third dependent variable and was measured by an open-ended question to give an overall grade for the intervention: “Please evaluate the intervention with a school grade from 1 to 10” (1=lowest grade and 10=highest grade; mean 7.50, SD 1.20).
Need for autonomy, the main moderator variable, was measured with a 9-item scale. First, 6 items from the Health Causality Orientation Scale (HCOS) were included. The HCOS was developed by the third author based on the General Causality Orientation Scale [
First, we checked whether there was an equal distribution of demographic and other background variables across the conditions by conducting Chi-square tests and analyses of variance. If baseline differences were detected, correlations between these variables and the dependent variables were calculated. Variables that were not equally distributed across conditions and were correlated significantly with one or more of the dependent variables were included in subsequent analyses as covariates.
Second, regression analyses were conducted to test the effects of language and choice on each of the 3 dependent variables (ie, perceived autonomy support, perceived relevance, and overall evaluation of the intervention). When there appeared to be a significant interaction effect between (either of) the 2 conditions and (one of) the moderator(s), the interaction was dismantled by conducting a median split of the moderator and comparing outcomes between the 2 groups.
Sex (χ23=6.5
Means (SDs) for dependent variables per condition (N=525).
Variables | Autonomy-supportive language and choice (n=147) | Autonomy-supportive language and no choice (n=141) | Controlling language and choice (n=124) | Controlling language and no choice (n=113) |
Perceived autonomy support | 3.77 (0.76) | 3.70 (0.84) | 3.82 (0.73) | 3.76 (0.72) |
Perceived relevance | 3.77 (0.94) | 3.67 (1.12) | 3.80 (1.00) | 3.69 (1.03) |
Overall evaluation | 7.60 (1.05) | 7.33 (1.40) | 7.66 (1.07) | 7.42 (1.23) |
The positive effect of choice on perceived autonomy support approached significance (
Effect of choice, language use, and need for autonomy on perceived autonomy support.
Variables |
|
SE ( |
|
|
95% CI | |
Choice | .06 | 0.03 | .07 | 1.85 (11,513) | .07 | 0.85 to 1.73 |
Language | −.03 | 0.03 | −.04 | −0.97 (11,513) | .33 | −0.09 to 0.03 |
Need for autonomy | .37 | 0.05 | .32 | 7.95 (11,513) | <.001 | 0.28 to 0.46 |
Need for external control | .32 | 0.04 | .32 | 8.04 (11,513) | <.001 | 0.24 to 0.39 |
Choice×language | −.01 | 0.03 | −.01 | −0.30 (11,513) | .76 | −0.07 to 0.05 |
Choice×need for autonomy | −.03 | 0.03 | −.04 | −1.03 (11,513) | .30 | −0.09 to 0.03 |
Choice×need for external control | −.03 | 0.03 | −.04 | −0.96 (11,513) | .34 | −0.09 to 0.03 |
Language×need for autonomy | −.03 | 0.03 | −.04 | −1.09(11,513) | .28 | −0.09 to 0.03 |
Language×need for external control | −.01 | 0.03 | −.01 | −0.15 (11,513) | .88 | −0.07 to 0.06 |
Choice×language×need for autonomy | .01 | 0.03 | .02 | 0.40 (11,513) | .69 | −0.05 to 0.07 |
Choice×language×need for external control | −.02 | 0.03 | −.02 | −0.55 (11,513) | .58 | −0.08 to 0.04 |
There was a significant interaction effect between choice and the need for autonomy on perceived relevance (
Effect of choice, language use, and need for autonomy on perceived relevance for participants with a high and a low need for autonomy.
Variables |
|
SE |
|
|
95% CI | ||
|
|||||||
|
Choice | −.05 | 0.05 | −.05 | −0.86 (7,235) | .39 | −0.15 to .06 |
|
Language use | −.08 | 0.05 | −.09 | −1.40 (7,235) | .16 | −0.18 to 0.03 |
|
Need for external control | .36 | 0.08 | .28 | 4.58 (7,235) | <.001 | 0.21 to 0.52 |
|
Choice×language use | .01 | 0.05 | .01 | 0.15 (7,235) | .89 | −0.10 to 0.11 |
|
Choice×need for external control | .06 | 0.06 | .06 | 1.00 (7,235) | .32 | −0.06 to 0.18 |
|
Language×need for external control | −.12 | 0.06 | −.12 | −1.89 (7,235) | .06 | −0.24 to 0.01 |
|
Choice×language×need for external control | −.09 | 0.06 | −.09 | −1.50 (7,235) | .13 | −0.22 to 0.03 |
|
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Choice | .15 | 0.06 | .13 | 2.40 (7,274) | .02 | 1.74 to 2.59 |
|
Language use | .02 | 0.06 | .02 | 0.34 (7,274) | .73 | −0.10 to 0.14 |
|
Need for external control | .58 | 0.07 | .44 | 8.20 (7,274) | <.001 | 0.44 to 0.72 |
|
Choice×language use | −.02 | 0.06 | −.01 | −0.25 (7,274) | .80 | −0.14 to 0.10 |
|
Choice×need for external control | −.07 | 0.06 | −.07 | 1.32 (7,274) | .19 | −0.18 to 0.04 |
|
Language×need for external control | −.02 | 0.06 | −.02 | −0.38 (7,274) | .70 | −0.13 to 0.09 |
|
Choice×language×need for external control | −.04 | 0.06 | −.04 | −0.68 (7,274) | .50 | −0.15 to 0.07 |
In terms of overall intervention rating, there was neither a significant interaction effect, rejecting hypotheses 3c and 4c, nor a significant main effect of language, rejecting hypothesis 1c. There was, however, a significant positive main effect of choice on the overall evaluation of the intervention (
Effect of choice, language use, and need for autonomy on overall evaluation of the intervention.
Variables |
|
SE |
|
|
95% CI | |
Choice | .14 | 0.05 | .12 | 2.95 (11,513) | .003 | 0.05 to 0.24 |
Language use | −.04 | 0.05 | −.03 | −0.74 (11,513) | .46 | −0.13 to 0.06 |
Need for autonomy | .27 | 0.08 | .15 | 3.55 (11,513) | <.001 | 0.12 to 0.42 |
Need for external control | .49 | 0.06 | .32 | 7.66 (11,513) | <.001 | 0.36 to 0.61 |
Choice×language use | −.00 | 0.05 | −.00 | −0.09 (11,513) | .93 | −0.10 to 0.09 |
Choice×need for autonomy | .01 | 0.05 | .01 | −0.17 (11,513) | .87 | −0.09 to 0.11 |
Choice×need for external control | −.07 | 0.05 | −.06 | −1.46 (11,513) | .15 | −0.17 to 0.03 |
Language×need for autonomy | −.01 | 0.05 | −.01 | −0.24 (11,513) | .81 | −0.11 to 0.09 |
Language×need for external control | .06 | 0.05 | .05 | 1.22 (11,513) | .23 | −0.04 to 0.16 |
Choice×language×need for autonomy | .06 | 0.05 | .05 | 1.21 (11,513) | .23 | −0.04 to 0.16 |
Choice×language×need for external control | −.07 | 0.05 | −.06 | −1.33 (11,513) | .19 | −0.16 to 0.03 |
In a sensitivity analysis, we checked whether including a relative score of the need for autonomy (ie, score of need for autonomy–score of need for external control) as a potentially moderating variable, instead of 2 separate, unyoked variables for the need for autonomy and need for external control, yielded a change in results. The results were similar, yet 1 minor difference was observed; the marginally significant effect of choice on more perceived autonomy-support turned nonsignificant (data not reported).
This study aimed to identify the most autonomy-supportive message frame within a Web-based computer-tailored intervention for increasing vegetable consumption. To this end, based on prior empirical research and theory, we investigated the effects of 2 strategies, that is, using autonomy-supportive language and offering choice, among Dutch adults on 3 outcomes (ie, perceived autonomy support, perceived relevance, and the overall evaluation of the intervention). Moreover, we examined whether individual differences in the need for autonomy and need for external control moderated these effects.
First of all, there appeared to be a main effect of choice on the overall evaluation of the intervention compared with no provision of choice, as well as positive effects of choice on perceived autonomy support that approached significance. This is in line with the expectations we had based on previous studies conducted in the face-to-face setting [
With regard to the potentially moderating role of need for autonomy, a significant interaction effect with choice was found for the dependent variable of perceived relevance: only for participants with a high need for autonomy was there a significant positive effect of choice. This is in line with our expectations, as we hypothesized that the positive effects of the provision of choice would be stronger for respondents with a high need for autonomy and strengthens the idea that message frame tailoring based on the need for autonomy might be a promising avenue to advance digital forms of health communication [
On the other hand, the language manipulation resulted in neither significant main effects nor significant interaction effects with the needs for autonomy and external control were found for any of the 3 dependent variables. Thus, the tone used in our health communication messages did not impact our 3 outcomes. It appeared not to matter whether the participants received the Web-based computer-tailored intervention using an autonomy-supportive or controlling communication style. This is, surprisingly, in line with the results from a recently published study into the effects of autonomy-supportive versus controlling message frames on individual’s perceived autonomy support from and reactance toward such messages, studied in the context of a Web-based computer-tailored alcohol reduction intervention [
The provision of choice resulted in the Web-based computer-tailored intervention being more positively evaluated and perceived as more autonomy supportive compared with no provision of choice, although the effect of perceived autonomy support only approached significance and should be interpreted with caution. For health communication practice, this may imply that the provision of choice could be an effective and easy-to-implement strategy to increase the effectiveness of digital forms of health communication. Given its potentially large reach, this increased effectiveness may improve the impact of this low-cost health behavior change strategy on public health. There is, however, still room for future research in this area as, in this study, the provision of choice was operationalized by providing participants the possibility to indicate to what extent they wanted to make several preparatory and coping plans that were recommended based on previous research findings. This may be interpreted as a combination of both verbal choice (in this case, emphasizing to the respondents that they could choose which of the recommended plans they wanted to make) and physical choice (in this case, physically giving respondents the opportunity to indicate their desire to make a certain plan or not). As it has previously been suggested that different types of choice may lead to different effects [
Second, the interaction effect found between choice and respondents’ need for autonomy suggests that both health behavior change theorists and health communication professionals may need to take each individual’s communication style preferences (more) into account. Both SDT [
Some limitations also should be considered. First, we used perceived autonomy support, perceived relevance, and the overall evaluation of the intervention as outcome measures, assessed directly postintervention. Although we can assume that these measures would facilitate the internalization of motivation and ultimately predict health behavior change and its maintenance [
This study suggests that provision of choice rather than the use of autonomy-supportive language can be an easy-to-implement strategy to increase the effectiveness of digital health communication, especially for people with a high need for autonomy.
Consolidated Standards of Reporting Trials flow diagram.
An example of a feedback message in autonomy-supportive and controlling language combined with and without choice.
CONSORT-EHEALTH checklist (V 1.6.1).
body mass index
Health Causality Orientation Scale
Self-Determination Theory
This study was supported by the Innovational Research Incentives Scheme Veni from NWO-MaGW (Netherlands Organization for Scientific Research—Division for the Social Sciences) accredited to ESS (project number 451-15-028).
None declared.